learning goals thesis

How to Write Learning Goals

Main navigation, learning goals overview.

Specific, measurable goals help you design your course and assess its success. To clearly articulate them, consider these questions to help you determine what you want your students to know and be able to do at the end of your course.

• What are the most important concepts (ideas, methods, theories, approaches, perspectives, and other broad themes of your field, etc.) that students should be able to understand, identify, or define at the end of your course?
• What would constitute a "firm understanding", a "good identification", and so on, and how would you assess this? What lower-level facts or information would students need to have mastered and retained as part of their larger conceptual structuring of the material?
• What questions should your students be able to answer at the end of the course? 
• What are the most important skills that students should develop and be able to apply in and after your course (quantitative analysis, problem-solving, close reading, analytical writing, critical thinking, asking questions, knowing how to learn, etc.)?
• How will you help the students build these skills, and how will you help them test their mastery of these skills?
• Do you have any affective goals for the course, such as students developing a love for the field?

A note on terminology: The academy uses a number of possible terms for the concept of learning goals, including course goals, course outcomes, learning outcomes, learning objectives, and more, with fine distinctions among them. With respect for that ongoing discussion, given that the new Stanford course evaluations are focused on assessing learning goals, we will use "learning goals" when discussing what you want your students to be able to do or demonstrate at the end of your class.

A CTL consultant  can help you develop your learning goals.

For more information about how learning goals can contribute to your course design, please see  Teacher-centered vs. Student-centered course design .

Learning Goal Examples

Examples from Stanford’s office of Institutional Research & Decision Support and syllabi of Stanford faculty members:

Languages and Literature

Students will be able to:

• apply critical terms and methodology in completing a literary analysis following the conventions of standard written English
• locate, apply, and cite effective secondary materials in their own texts
• analyze and interpret texts within the contexts they are written

Foreign language students will be able to:

• demonstrate oral competence with suitable accuracy in pronunciation, vocabulary, and language fluency
• produce written work that is substantive, organized, and grammatically accurate
• accurately read and translate texts in their language of study

Humanities and Fine Arts

• demonstrate fluency with procedures of two-dimensional and three-dimensional art practice
• demonstrate in-depth knowledge of artistic periods used to interpret works of art including the historical, social, and philosophical contexts
• critique and analyze works of art and visual objects
• identify musical elements, take them down at dictation, and perform them at sight
• communicate both orally and in writing about music of all genres and styles in a clear and articulate manner
• perform a variety of memorized songs from a standard of at least two foreign languages
• apply performance theory in the analysis and evaluation of performances and texts

Physical and Biological Sciences

• apply critical thinking and analytical skills to interpreting scientific data sets
• demonstrate written, visual, and/or oral presentation skills to communicate scientific knowledge
• acquire and synthesize scientific information from a variety of sources
• apply techniques and instrumentation to solve problems

Mathematics

• translate problems for treatment within a symbolic system
• articulate the rules that govern a symbolic system
• apply algorithmic techniques to solve problems and obtain valid solutions
• judge the reasonableness of obtained solutions

Social Sciences

• write clearly and persuasively to communicate their scientific ideas clearly
• test hypotheses and draw correct inferences using quantitative analysis
• evaluate theory and critique research within the discipline

Engineering

• explain and demonstrate the role that analysis and modeling play in engineering design and engineering applications more generally
• communicate about systems using mathematical, verbal and visual means
• formulate mathematical models for physical systems by applying relevant conservation laws and assumptions
• choose appropriate probabilistic models for a given problem, using information from observed data and knowledge of the physical system being studied
• choose appropriate methods to solve mathematical models and obtain valid solutions

For more information about learning goals, meet with a  CTL consultant .

See more STEM learning goal examples  from the  Carl Wieman Science Education Initiative .

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Get answers to some common questions.

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Key ideas guiding evaluations and student feedback at Stanford.

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Teaching Resources

Writing Effective Learning Goals

Resource overview.

Tips and resources to help you set learning goals for your course

Oftentimes when instructors are developing courses, they start by thinking about a reading list or a list of topics to lecture on. This is considered a forward-thinking process of designing a course. By contrast, Wiggins and McTighe (2005) recommend a backward design approach that encourages you to consider your outcomes (goals) for students first. A learning goal is a statement of what your students should know or be able to do as a result of successfully completing your course.

By clarifying and explicitly stating your learning goals first, you can then design assessments and learning activities that are aligned with those goals. The benefit of following backward design that you can be confident that students who succeed in the course will leave having achieved the goals that you set for them at the beginning.

Identifying Your Learning Goals

Ideally, learning goals for a course are developed through considering contextual factors, as well as the kinds of knowledge production activities (e.g. synthesis, analysis, comparison, etc.) and skills that you want your students to leave your course comfortable performing. Starting from contextual factors, and considering types of learning on a macro-level, should make it easier to identify specific course-level learning goals for your students. As you are exploring the chart below, consider the relationships among the teaching context, types of learning, and beginning draft of learning goals provided:

What’s the Big Deal about Learning Goals?

So, you might be wondering at this point: what’s the big deal about learning goals? You might even be annoyed if you see learning goals as simply an output of the corporatization of higher education. The truth is however that even if you haven’t used the words “learning goals” before to describe your classes, instructors always have in mind what it is they want their students to get out of a course. And, the best, most meaningful classes for students tend to be those in which that foundational set of goals drives every other decision that is made about the course: What assignments should I ask my students to complete? What should they read or watch? What should we do in class? How should they interact with each other? In short, learning goals can be our compass, can keep us from veering off course in ways that don’t support our students’ learning.

In a time when fancy new technologies and all the other considerations seem overwhelming, learning goals are all the more critical. If you are willing to start from your learning goals, the noise of possibilities will begin to die down, and everything that is truly essential for you to know in order to support your students’ learning will become clearer.

Writing a Learning Goal

As you develop and refine your learning goals for students, you’ll want to make sure they are specific and measurable. It’s critical that the goals that you choose are ones that can be measured–that is, that it would be possible for you to assess how well students have been able to accomplish this goal in your class.

A good way to start drafting a specific learning goal is to identify what you want students to actually  do  with the knowledge that you hope they will gain in your course. Examining  a list of verbs can really be helpful for identifying the specific things that you’d like students to be able to do with knowledge acquired.

One common way to break down these cognitive activities (what students are “doing”) is Bloom’s (revised) Taxonomy, a hierarchical framework for constructing and classifying learning goals (Anderson & Krathwohl, 2001). The revised taxonomy includes the following levels of cognitive engagement: Remember, Understand, Apply, Analyze, Evaluate, and Create. This taxonomy suggests that one isn’t ready to do more complex cognitive tasks (e.g. application, analysis) until one has a firm grasp on the lower-levels (remember, understand).

Traditionally, learning goals are written from the student’s point of view, for example:  “The student should be able to trace the carbon cycle in a given  ecosystem.” 

Click here to see more examples of learning goals.

Characteristics of Effective Learning Goals

It’s relatively easy to write a learning goal, it’s more challenging to write a really effective one! Watch the short video presentation below (~6 minutes) to learn some of the basic principles of effective learning goals.

Further Reading

Nilson, L. (2016). “Outcomes-Centered Course Design” in  Teaching at It’s Best , 4th edition. Jossey-Bass.

Poorvu Center for Teaching and Learning, Yale University. (2017).  Bloom’s Taxonomy .

Fink, L. D. (2005). A Self-Directed Guide to Designing Courses for Significant Learning .

Anderson, L. W. & Krathwohl, D. R. (Eds.). (2001). A taxonomy for learning, teaching, and assessing : A revision of Bloom’s taxonomy of educational objectives. Longman.

Wiggins, G. & McTighe, J. (2005). Understanding by design . ASCD.

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Creating Learning Outcomes

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A learning outcome is a concise description of what students will learn and how that learning will be assessed. Having clearly articulated learning outcomes can make designing a course, assessing student learning progress, and facilitating learning activities easier and more effective. Learning outcomes can also help students regulate their learning and develop effective study strategies.

Defining the terms

Educational research uses a number of terms for this concept, including learning goals, student learning objectives, session outcomes, and more. 

In alignment with other Stanford resources, we will use learning outcomes as a general term for what students will learn and how that learning will be assessed. This includes both goals and objectives. We will use learning goals to describe general outcomes for an entire course or program. We will use learning objectives when discussing more focused outcomes for specific lessons or activities.

For example, a learning goal might be “By the end of the course, students will be able to develop coherent literary arguments.” 

Whereas a learning objective might be, “By the end of Week 5, students will be able to write a coherent thesis statement supported by at least two pieces of evidence.”

Learning outcomes benefit instructors

Learning outcomes can help instructors in a number of ways by:

• Providing a framework and rationale for making course design decisions about the sequence of topics and instruction, content selection, and so on.
• Communicating to students what they must do to make progress in learning in your course.
• Clarifying your intentions to the teaching team, course guests, and other colleagues.
• Providing a framework for transparent and equitable assessment of student learning. 
• Making outcomes concerning values and beliefs, such as dedication to discipline-specific values, more concrete and assessable.
• Making inclusion and belonging explicit and integral to the course design.

Learning outcomes benefit students 

Clearly, articulated learning outcomes can also help guide and support students in their own learning by:

• Clearly communicating the range of learning students will be expected to acquire and demonstrate.
• Helping learners concentrate on the areas that they need to develop to progress in the course.
• Helping learners monitor their own progress, reflect on the efficacy of their study strategies, and seek out support or better strategies. (See Promoting Student Metacognition for more on this topic.)

Choosing learning outcomes

When writing learning outcomes to represent the aims and practices of a course or even a discipline, consider:

• What is the big idea that you hope students will still retain from the course even years later?
• What are the most important concepts, ideas, methods, theories, approaches, and perspectives of your field that students should learn?
• What are the most important skills that students should develop and be able to apply in and after your course?
• What would students need to have mastered earlier in the course or program in order to make progress later or in subsequent courses?
• What skills and knowledge would students need if they were to pursue a career in this field or contribute to communities impacted by this field?
• What values, attitudes, and habits of mind and affect would students need if they are to pursue a career in this field or contribute to communities impacted by this field?
• How can the learning outcomes span a wide range of skills that serve students with differing levels of preparation?
• How can learning outcomes offer a range of assessment types to serve a diverse student population?

Use learning taxonomies to inform learning outcomes

Learning taxonomies describe how a learner’s understanding develops from simple to complex when learning different subjects or tasks. They are useful here for identifying any foundational skills or knowledge needed for more complex learning, and for matching observable behaviors to different types of learning.

Bloom’s Taxonomy

Bloom’s Taxonomy is a hierarchical model and includes three domains of learning: cognitive, psychomotor, and affective. In this model, learning occurs hierarchically, as each skill builds on previous skills towards increasingly sophisticated learning. For example, in the cognitive domain, learning begins with remembering, then understanding, applying, analyzing, evaluating, and lastly creating. 

Taxonomy of Significant Learning

The Taxonomy of Significant Learning is a non-hierarchical and integral model of learning. It describes learning as a meaningful, holistic, and integral network. This model has six intersecting domains: knowledge, application, integration, human dimension, caring, and learning how to learn. 

See our resource on Learning Taxonomies and Verbs for a summary of these two learning taxonomies.

How to write learning outcomes

Writing learning outcomes can be made easier by using the ABCD approach. This strategy identifies four key elements of an effective learning outcome:

Consider the following example: Students (audience) , will be able to label and describe (behavior) , given a diagram of the eye at the end of this lesson (condition) , all seven extraocular muscles, and at least two of their actions (degree) .

Audience 

Define who will achieve the outcome. Outcomes commonly include phrases such as “After completing this course, students will be able to...” or “After completing this activity, workshop participants will be able to...”

Keeping your audience in mind as you develop your learning outcomes helps ensure that they are relevant and centered on what learners must achieve. Make sure the learning outcome is focused on the student’s behavior, not the instructor’s. If the outcome describes an instructional activity or topic, then it is too focused on the instructor’s intentions and not the students.

Try to understand your audience so that you can better align your learning goals or objectives to meet their needs. While every group of students is different, certain generalizations about their prior knowledge, goals, motivation, and so on might be made based on course prerequisites, their year-level, or majors. 

Use action verbs to describe observable behavior that demonstrates mastery of the goal or objective. Depending on the skill, knowledge, or domain of the behavior, you might select a different action verb. Particularly for learning objectives which are more specific, avoid verbs that are vague or difficult to assess, such as “understand”, “appreciate”, or “know”.

The behavior usually completes the audience phrase “students will be able to…” with a specific action verb that learners can interpret without ambiguity. We recommend beginning learning goals with a phrase that makes it clear that students are expected to actively contribute to progressing towards a learning goal. For example, “through active engagement and completion of course activities, students will be able to…”

Example action verbs

Consider the following examples of verbs from different learning domains of Bloom’s Taxonomy . Generally speaking, items listed at the top under each domain are more suitable for advanced students, and items listed at the bottom are more suitable for novice or beginning students. Using verbs and associated skills from all three domains, regardless of your discipline area, can benefit students by diversifying the learning experience. 

For the cognitive domain:

• Create, investigate, design
• Evaluate, argue, support
• Analyze, compare, examine
• Solve, operate, demonstrate
• Describe, locate, translate
• Remember, define, duplicate, list

For the psychomotor domain:

• Invent, create, manage
• Articulate, construct, solve
• Complete, calibrate, control
• Build, perform, execute
• Copy, repeat, follow

For the affective domain:

• Internalize, propose, conclude
• Organize, systematize, integrate
• Justify, share, persuade
• Respond, contribute, cooperate
• Capture, pursue, consume

Often we develop broad goals first, then break them down into specific objectives. For example, if a goal is for learners to be able to compose an essay, break it down into several objectives, such as forming a clear thesis statement, coherently ordering points, following a salient argument, gathering and quoting evidence effectively, and so on.

State the conditions, if any, under which the behavior is to be performed. Consider the following conditions:

• Equipment or tools, such as using a laboratory device or a specified software application.
• Situation or environment, such as in a clinical setting, or during a performance.
• Materials or format, such as written text, a slide presentation, or using specified materials.

The level of specificity for conditions within an objective may vary and should be appropriate to the broader goals. If the conditions are implicit or understood as part of the classroom or assessment situation, it may not be necessary to state them. 

When articulating the conditions in learning outcomes, ensure that they are sensorily and financially accessible to all students.

Degree 

Degree states the standard or criterion for acceptable performance. The degree should be related to real-world expectations: what standard should the learner meet to be judged proficient? For example:

• With 90% accuracy
• Within 10 minutes
• Suitable for submission to an edited journal
• Obtain a valid solution
• In a 100-word paragraph

The specificity of the degree will vary. You might take into consideration professional standards, what a student would need to succeed in subsequent courses in a series, or what is required by you as the instructor to accurately assess learning when determining the degree. Where the degree is easy to measure (such as pass or fail) or accuracy is not required, it may be omitted.

Characteristics of effective learning outcomes

The acronym SMART is useful for remembering the characteristics of an effective learning outcome.

• Specific : clear and distinct from others.
• Measurable : identifies observable student action.
• Attainable : suitably challenging for students in the course.
• Related : connected to other objectives and student interests.
• Time-bound : likely to be achieved and keep students on task within the given time frame.

Examples of effective learning outcomes

These examples generally follow the ABCD and SMART guidelines. 

Arts and Humanities

Learning goals.

Upon completion of this course, students will be able to apply critical terms and methodology in completing a written literary analysis of a selected literary work.

At the end of the course, students will be able to demonstrate oral competence with the French language in pronunciation, vocabulary, and language fluency in a 10 minute in-person interview with a member of the teaching team.

Learning objectives

After completing lessons 1 through 5, given images of specific works of art, students will be able to identify the artist, artistic period, and describe their historical, social, and philosophical contexts in a two-page written essay.

By the end of this course, students will be able to describe the steps in planning a research study, including identifying and formulating relevant theories, generating alternative solutions and strategies, and application to a hypothetical case in a written research proposal.

At the end of this lesson, given a diagram of the eye, students will be able to label all of the extraocular muscles and describe at least two of their actions.

Using chemical datasets gathered at the end of the first lab unit, students will be able to create plots and trend lines of that data in Excel and make quantitative predictions about future experiments.

• How to Write Learning Goals , Evaluation and Research, Student Affairs (2021).
• SMART Guidelines , Center for Teaching and Learning (2020).
• Learning Taxonomies and Verbs , Center for Teaching and Learning (2021).

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• v.21(3); Fall 2022

Writing and Using Learning Objectives

Rebecca b. orr.

† Division of Academic Affairs, Collin College, Plano, TX 75074

Melissa M. Csikari

‡ HHMI Science Education, BioInteractive, Chevy Chase, MD 20815

Scott Freeman

§ Department of Biology, University of Washington, Seattle, WA 98195

Michael C. Rodriguez

∥ Educational Psychology, College of Education and Human Development, University of Minnesota, Minneapolis, MN 55455

Learning objectives (LOs) are used to communicate the purpose of instruction. Done well, they convey the expectations that the instructor—and by extension, the academic field—has in terms of what students should know and be able to do after completing a course of study. As a result, they help students better understand course activities and increase student performance on assessments. LOs also serve as the foundation of course design, as they help structure classroom practices and define the focus of assessments. Understanding the research can improve and refine instructor and student use of LOs. This essay describes an online, evidence-based teaching guide published by CBE—Life Sciences Education ( LSE ) at http://lse.ascb.org/learning-objectives . The guide contains condensed summaries of key research findings organized by recommendations for writing and using LOs, summaries of and links to research articles and other resources, and actionable advice in the form of a checklist for instructors. In addition to describing key features of the guide, we also identify areas that warrant further empirical studies.

INTRODUCTION

Learning objectives (LOs) are statements that communicate the purpose of instruction to students, other instructors, and an academic field ( Mager, 1997 ; Rodriguez and Albano, 2017 ). They form the basis for developing high-quality assessments for formative and summative purposes. Once LOs and assessments are established, instructional activities can help students master the material. Aligning LOs with assessments and instructional practice is the essence of backward course design ( Fink, 2003 ).

Many terms in the literature describe statements about learning expectations. The terms “course objectives,” “course goals,” “learning objectives,” “learning outcomes,” and “learning goals” are often used interchangeably, creating confusion for instructors and students. To clarify and standardize usage, the term “objective” is defined as a declarative statement that identifies what students are expected to know and do . At the same time, “outcome” refers to the results measured at the end of a unit, course, or program. It is helpful to think of LOs as a tool instructors use for describing intended outcomes, regardless of the process for achieving the outcome ( Mager, 1997 ). The term “goal” is less useful. Although it is often used to express more general expectations, there is no consistent usage in the literature.

In this guide, “learning objective” is defined as a statement that communicates the purpose of instruction using an action verb and describes the expected performance and conditions under which the performance should occur. Examples include:

• At the end of this lesson, students should be able to compare the processes of diffusion, osmosis, and facilitated diffusion, and provide biological examples that illustrate each process.
• At the end of this lesson, students should be able to predict the relative rates at which given ions and molecules will cross a plasma membrane in the absence of membrane protein and explain their reasoning.

In terms of content and complexity, LOs should scaffold professional practice, requirements for a program, and individual course goals by communicating the specific content areas and skills considered important by the academic field ( Rodriguez and Albano, 2017 ). They also promote course articulation by supporting consistency when courses are taught by multiple instructors and furnishing valuable information about course alignment among institutions. As a result, LOs should serve as the basis of unit or module, course, and program design and can be declared in a nested hierarchy of levels. For clarity, we describe a hierarchy of LOs in Table 1 .

Levels of LOs ( Rodriguez and Albano, 2017 )

a Hereafter, our use of the term “learning objectives” specifically refers to instructional LOs.

This article describes an evidence-based teaching guide that aggregates, summarizes, and provides actionable advice from research findings on LOs. It can be accessed at http://lse.ascb.org/learning-objectives . The guide has several features intended to help instructors: a landing page that indicates starting points ( Figure 1 ), syntheses of observations from the literature, summaries of and links to selected papers ( Figure 2 ), and an instructor checklist that details recommendations and points to consider. The focus of our guide is to provide recommendations based on the literature for instructors to use when creating, revising, and using instructional LOs in their courses. The Effective Construction section provides evidence-based guidelines for writing effective LOs. The Instructor Use section contains research summaries about using LOs as a foundational element for successful course design, summaries of the research that supports recommended practices for aligning LOs with assessment and classroom instruction, and direction from experts for engaging with colleagues in improving instructor practice with LOs. The Student Use section includes a discussion on how students use LOs and how instructor guidance can improve student use of LOs, along with evidence on the impact of LO use coupled with pretests, transparent teaching methods, and summaries of LO-driven student outcomes in terms of exam scores, depth of learning, and affect (e.g., perception of utility and self-regulated learning). Some of the questions and considerations that serve to organize the guide are highlighted in the following sections.

LO guide landing page, which provides readers with an overview of choice points.

Screenshots representing summaries of and links to selected papers.

WRITING EFFECTIVE INSTRUCTIONAL LEARNING OBJECTIVES

Writing LOs effectively is essential, as their wording should provide direction for developing instructional activities and guide the design of assessments. Effective LOs clearly communicate what students should know and be able to do and are written to be behavioral, measurable, and attainable ( Rodriguez and Albano, 2017 ). It is particularly important that each LO is written with enough information to ensure that other knowledgeable individuals can use the LO to measure a learner’s success and arrive at the same conclusions ( Mager, 1997 ). Clear, unambiguous wording encourages consistency across sections and optimizes student use of the stated LOs.

Effective LOs specify a visible performance—what students should be able to do with the content—and may also include conditions and the criteria for acceptable performance ( Mager, 1997 ). When constructing an LO, one should use an action verb to describe what students are expected to know and be able to do with the disciplinary knowledge and skills ( Figure 3 ). Bloom’s taxonomy of cognitive skills provides a useful framework for writing LOs that embody the intended complexity and the cognitive demands involved in mastering them ( Bloom, 1956 ; Anderson and Krathwohl, 2001 ). Assessment items and course activities can then be aligned with LOs using the Blooming Biology Tool described by Crowe et al. (2008) . However, LOs should not state the instructional method(s) planned to accomplish the objectives or be written so specifically as to be assessment tasks themselves ( Mager, 1997 ).

Components of an LO.

Our Instructor Checklist provides specific recommendations for writing LOs, along with a link to examples of measurable action verbs associated with Bloom’s taxonomy.

COURSE DESIGN: ALIGNING LEARNING OBJECTIVES WITH ASSESSMENT AND CLASSROOM INSTRUCTION

Course designs and redesigns built around clear and measurable LOs result in measurable benefits to students (e.g., Armbruster et al. , 2009 , and other citations in the Course and Curriculum Design and Outcomes section of this guide). LOs are established as the initial step in backward design ( McTighe and Wiggins, 2012 ). They provide a framework for instructors to 1) design assessments that furnish evidence on the degree of student mastery of knowledge and skills and 2) select teaching and learning activities that are aligned with objectives ( Mager, 1997 ; Rodriguez and Albano, 2017) . Figure 4 depicts depicts integrated course course design, emphasizing the dynamic and reciprocal associations among LOs, assessment, and teaching practice.

Components of integrated course design (after Fink, 2003 ).

Used in this way, LOs provide a structure for planning assessments and instruction while giving instructors the freedom to be creative and flexible ( Mager, 1997 ; Reynolds and Kearns, 2017 ). In essence, LOs respond to the question: “If you don’t know where you’re going, how will you know which road to take and how do you know when you get there?” ( Mager, 1997 , p. 14). When assessments are created, each assessment item or task must be specifically associated with at least one LO and measure student learning progress on that LO. The performance and conditions components of each LO should guide the type of assessment developed ( Mager, 1997 ). Data gathered from assessment results (feedback) can then inform future instruction. The Assessment section of our guide contains summaries of research reporting the results of aligning assessment with LOs and summaries of frameworks that associate assessment items with LOs.

The purpose of instruction is communicated to students most effectively when instructional activities are aligned with associated instructional and course-level LOs (e.g., Chasteen et al. , 2011 , and others within the Instructor Use section of this guide). The literature summarized in the Course and Curriculum Design section of the guide supports the hypothesis that student learning is strongly impacted by what instructors emphasize in the classroom. In the guide’s Student Buy-In and Metacognition section, we present strategies instructors have used to ensure that LOs are transparent and intentionally reinforced to students . When LOs are not reinforced in instruction, students may conclude that LOs are an administrative requirement rather than something developed for their benefit. The guide’s Instructor Checklist contains evidence-based suggestions for increasing student engagement through making LOs highly visible.

Using LOs as the foundation of course planning results in a more student-centered approach, shifting the focus from the content to be covered to the concepts and skills that the student should be able to demonstrate upon successfully completing the course (e.g., Reynolds and Kearns, 2017 , and others within the Active Learning section of this guide). Instead of designing memorization-driven courses that are “a mile wide and an inch deep,” instructors can use LOs to focus a course on the key concepts and skills that prepare students for future success in the field. Group problem solving, discussions, and other class activities that allow students to practice and demonstrate the competencies articulated in LOs can be prioritized over lectures that strive to cover all of the content. The guide’s Active Learning section contains a summary of the literature on the use of LOs to develop activities that promote student engagement, provide opportunities for students to practice performance, and allow instructors to gather feedback on learning progress. The evidence-based teaching guides on Group Work and Peer Instruction provide additional evidence and resources to support these efforts.

ENGAGING WITH COLLEAGUES TO IMPROVE LEARNING OBJECTIVES

Momsen et al. (2010) examined Bloom’s level of assessment items and course goals from 50 faculty in 77 introductory biology courses for majors. The authors found that 93% of the assessment items were rated low-level Bloom’s, and 69% of the 250 course goals submitted were rated low-level Bloom’s ( Momsen et al. , 2010 ). A recent survey of 38 instructors of biology for nonmajors found similar results. Heil et al. (unpublished data) reported that 74% of the instructors surveyed write their own LOs, and 95% share their LOs with their students ( Heil et al. , unpublished data ). The action verbs used in 66% of these LOs were low-level Bloom’s cognitive skills, assessing knowledge and comprehension ( Heil et al. , unpublished data ). Further, an analysis of 1390 LOs from three best-selling biology textbooks for nonscience majors found that 89% were rated Bloom’s cognitive skill level 1 or level 2. Vision & Change competencies, as articulated in the BioSkills Guide ( Clemmons et al. , 2020 ), were only present in 17.7% of instructors’ LOs and 7% of the textbook LOs ( Heil et al. , unpublished data ). These data suggest that, in introductory biology for both majors and nonmajors, most instructors emphasize lower-order cognitive skills that are not aligned with teaching frameworks.

Researchers have documented effective strategies to improve instructors’ writing and use of LOs. The guide’s Engaging with Colleagues section contains summaries demonstrating that instructor engagement with the scholarship of teaching and learning can improve through professional development in collaborative groups—instructors can benefit by engaging in a collegial community of practice as they implement changes in their teaching practices (e.g., Richlin and Cox, 2004 , and others within the Engaging with Colleagues section of the guide). Collaboration among institutions can create common course-level LOs that promote horizontal and vertical course alignment, which can streamline articulation agreements and transfer pathways between institutions ( Kiser et al. , 2022 ). Departmental efforts to map LOs across program curricula can close gaps in programmatic efforts to convey field-expected criteria and develop student skills throughout a program ( Ezell et al. , 2019 ). The guide contains summaries of research-based recommendations that encourage departmental support for course redesign efforts (e.g., Pepper et al. , 2012 , and others within the Engaging with Colleagues section of the guide).

HOW DO LEARNING OBJECTIVES IMPACT STUDENTS?

When instructors publish well-written LOs aligned with classroom instruction and assessments, they establish clear goalposts for students ( Mager, 1997 ). Using LOs to guide their studies, students should no longer have to ask “Do we have to know …?” or “Will this be on the test?” The Student Use section of the guide contains summaries of research on the impact of LOs from the student perspective.

USING LEARNING OBJECTIVES TO GUIDE STUDENT LEARNING

Researchers have shown that students support the use of LOs to design class activities and assessments. In the Guiding Learning section of the guide, we present evidence documenting how students use LOs and how instructors can train students to use them more effectively ( Brooks et al. , 2014 , and other citations within this section of the guide). However, several questions remain about the impact of LOs on students. For example, using LOs may improve students’ ability to self-regulate, which in turn may be particularly helpful in supporting the success of underprepared students ( Simon and Taylor, 2009 ; Osueke et al. , 2018 ). But this hypothesis remains untested.

There is evidence that transparency in course design improves the academic confidence and retention of underserved students ( Winkelmes et al. , 2016 ), and LOs make course expectations transparent to students. LOs are also reported to help students organize their time and effort and give students, particularly those from traditionally underserved groups, a better idea of areas in which they need help ( Minbiole, 2016 ). Additionally, LOs facilitate the construction of highly structured courses by providing scaffolding for assessment and classroom instruction. Highly structured course design has been demonstrated to improve all students’ academic performance. It significantly reduces achievement gaps (difference in final grades on a 4.0 scale) between disadvantaged and nondisadvantaged students ( Haak et al. , 2011 ). However, much more evidence is needed on how LOs impact underprepared and/or underresourced students:

• Does the use of LOs lead to increased engagement with the content and/or instructor by underprepared and/or underserved students?
• Does LO use have a disproportionate and positive impact on the ability of underprepared and/or underresourced students to self-direct their learning?
• Is there a significant impact on underserved students’ academic performance and persistence with transparent LOs in place?

In general, how can instructors help students realize the benefits of well-written LOs? Research indicates that many students never receive instruction on using LOs ( Osueke et al. , 2018 ). However, when students receive explicit instruction on LO use, they benefit ( Osueke et al. , 2018 ). Examples include teaching students how to turn LOs into questions and how to answer and use those questions for self-assessment ( Osueke et al. , 2018 ). Using LOs for self-assessment allows students to take advantage of retrieval practice, a strategy that has a positive effect on learning and memory by helping students identify what they have and have not learned ( Bjork and Bjork, 2011 ; Brame and Biel, 2015 ). Some students, however, may avoid assessment strategies that identify what they do not understand or know because they find difficulty uncomfortable ( Orr and Foster, 2013 ; Dye and Stanton, 2017 ).

Brooks et al. (2014) reported that about one-third of students surveyed indicated that they had underestimated the depth of learning required to pass an assessment on the stated LOs. Further, students may have difficulty understanding the scope or expectations of stated LOs until after learning the content. Research on how instructors should train students to use LOs has been limited, and many of these open questions remain:

• What are the best practices to help students use LOs in self-assessment strategies?
• How can instructors motivate students to go outside their comfort zones for learning and use LOs in self-assessment strategies?
• How can instructors help students better understand the performance, conditions, and criteria required by the LOs to demonstrate successful learning?
• How might this differ for learners at different institutions, where academic preparedness and/or readiness levels may vary greatly?

CAPITALIZING ON THE PRETEST EFFECT

The guide’s Pretesting section contains research findings building on the pretesting effect reported by Little and Bjork (2011) . Pretesting with questions based on LOs has been shown to better communicate course expectations to students, increase student motivation and morale by making learning progress more visible, and improve retention of information as measured by final test scores ( Beckman, 2008 ; Sana et al. , 2020 ). Operationalizing LOs as pretest questions may serve as an effective, evidence-based model for students to self-assess and prepare for assessment. The research supporting this strategy is very limited, however, prompting the following questions:

• How broadly applicable—in terms of discipline and course setting—is the benefit of converting LOs to pretest questions?
• Is the benefit of operationalizing LOs to create pretests sustained when converting higher-level Bloom’s LOs into pretest questions?
• Does the practice of using LOs to create pretest questions narrow students’ focus such that the breadth/scope of their learning is overly limited/restricted? This is particularly concerning if students underestimate the depth of learning required by the stated LOs ( Brooks et al. , 2014 ).
• Could this practice help instructors teach students to use LOs to self-assess with greater confidence and persistence?

STUDENT OUTCOMES

The guide concludes with research summaries regarding the specific benefits to students associated with the use of LOs. Specifically, 1) alignment of LOs and assessment items is associated with higher exam scores (e.g., Armbruster et al. , 2009 , and others within the Outcomes section of the guide); 2) exam items designed to measure student mastery of LOs can support higher-level Bloom’s cognitive skills (e.g., Armbruster et al. , 2009 , and others within the Outcomes section of the guide); and 3) students adjust their learning approach based on course design and have been shown to employ a deeper approach to learning in courses in which assessment and class instruction are aligned with LOs ( Wang et al. , 2013 ).

CHALLENGES IN MEASURING THE IMPACT OF LEARNING OBJECTIVES

It is difficult to find literature in which researchers measured the impact of LOs alone on student performance due to their almost-necessary conflation with approaches to assessment and classroom practices. We argue that measuring the impact of LOs independently of changes in classroom instruction or assessment would be inadvisable, considering the role that LOs play in integrated course design ( Figure 4 ). Consistent with this view, the guide includes summaries of research findings on course redesigns that focus on creating or refining well-defined, well-written LOs; aligning assessment and classroom practice with the LOs; and evaluating student use and/or outcomes ( Armbruster et al. , 2009 ; Chasteen et al. , 2011 ). We urge instructors to use LOs from this integrated perspective.

CONCLUSIONS

We encourage instructors to use LOs as the basis for course design, align LOs with assessment and instruction, and promote student success by sharing their LOs and providing practice with how best to use them. Instructor skill in using LOs is not static and can be improved and refined with collaborative professional development efforts. Our teaching guide ends with an Instructor Checklist of actions instructors can take to optimize their use of LOs ( http://lse.ascb.org/learning-objectives/instructor-checklist ).

Acknowledgments

We thank Kristy Wilson for her guidance and support as consulting editor for this effort and Cynthia Brame and Adele Wolfson for their insightful feedback on this paper and the guide. This material is based upon work supported in part by the National Science Foundation under grant number DUE 201236 2. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors. They do not necessarily reflect the views of the National Science Foundation.

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• Learning Goals
• Course Design
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• Learning Goals (Currently Selected)
• Emotion and Learning
• UDL and Assessment
• Executive Functioning in Online Environments
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What is this resource about? This resource discusses the ways in which learning goals can be constructed through the lens of Universal Design for Learning . Within instructional design, goals are expectations for knowledge, skills, or outcomes. These expectations can be communicated as performance goals -- which focus on proving ability -- or as learning goals (also known as mastery goals), which emphasize developing and improving an ability. 1 Read more about Learning Goals from a UDL Perspective , and Separating the Means from the Ends .

Why is this important in higher education? Learners at all stages benefit from being aware of their own goals and the goals instructors and institutions hold for them. 2 Some instructional circumstances call for performance goals; but learning goals, oriented towards growth, are more likely to support course completion, persistence through challenging transitions, and change in deeply-held conceptions. 3

UDL Connections

Consider how goals are articulated and communicated: goals that unnecessarily prescribe narrow means of achievement will inadvertently privilege, exclude, and under-engage learners. 4 Clear goals are the cornerstone of well-designed curricula, as only through clarification of what learners are expected to accomplish, and by when, can instructors begin to consider which assessments , methods and materials will be most effective.

Learning Goals from a UDL Perspective

In the UDL model, goals move beyond their traditional role in curriculum planning as mere content or performance markers. A UDL approach seeks to create clear learning goals and support the development of expert, lifelong learners that are strategic, resourceful, and motivated. 5 A UDL approach to effective learning goals in postsecondary settings consists of three key components:

• separating the means from the ends
• addressing variability in learning
• providing UDL options in the materials, methods, and assessments

Separating the Means from the Ends

From a UDL perspective, goals and objectives should be attainable by different learners in different ways. In some instances, linking a goal with the means for achievement may be intentional; however, often times we unintentionally embed the means of achievement into a goal, thereby restricting the pathways students can take to meet it.

The following sample curricular goal is articulated as: “Write a paragraph about how the circulatory system works.” What are the barriers this goal might pose for students?

Writing a paragraph is an additional task layered over mastery of the content knowledge that you want your students to attain. Rephrasing this goal into something like, “Describe a complete cycle in the circulatory system” is more explicit about what students should be able to explain, and allows flexibility in terms of how students convey their knowledge (create a diagram, label an image, write out the steps in the process, make a short video explaining an image, etc.). It is also more of a learning goal than a performance goal in that it invites students to demonstrate the fullest extent of their understanding – rather than asking them to prove that they can write a paragraph.

In your College Writing Seminar, the learning goal (learning how to write strong essays) is frequently linked to the production means (writing essays). Given the wide variability of writing abilities in the classroom, you want to be sure that your students first get a strong understanding of the concept of a thesis statement first before adding the additional challenge of writing one.

In the case of this learning objective, the desired outcome is that students understand the concept of a strong thesis statement--perhaps as a prerequisite to writing one. Therefore, the means by which students demonstrate this ability can be more flexible, since the concept of a thesis statement and the ability to write one are not always one in the same. Students could write a thesis statement, but they could also put forward a video with a narrative, or some sort of visual. Requiring that students fulfill this objective through only one modality would, for some students, add task-irrelevant demands that pose a barrier to their fundamental understanding of a thesis statement.

The solutions above illustrate a key characteristics of well-designed goals: to make explicit the desired outcomes, rather than the means of achieving those outcomes. By focusing on the desired outcomes, instructors are able to maintain high expectations for students while opening multiple pathways towards achievement. This focus also capitalizes on the varied strengths of a wider range of students. Such support encourages persistence and content mastery that otherwise might be inadvertently deterred.

Goals need to be relevant to students. Especially at the postsecondary level -- where there is a focus on functioning independently in professions or life after school -- educators must consider that “students will never use knowledge they don't care about, nor will they practice or apply skills they don't find valuable.” 6

1 Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41(10), 1040; Rusk, N., Tamir, M., & Rothbaum, F. (2011). Performance and learning goals for emotion regulation. Motivation and Emotion, 35(4), 444-460. http://dx.doi.org/10.1007/s11031-011-9229-6

2 Simon, B., & Taylor, J. (2009). What is the value of course-specific learning goals. Journal of College Science Teaching, 39(2), 52-57. https://testwww2.bc.edu/maya-tamir/download/rusk%20et%20al_201

3 Yeager, D. S., & Dweck, C. S. (2012). Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist, 47(4), 302-314; Ranellucci, J., Muis, K. R., Duffy, M., Wang, X., Sampasivam, L., & Franco, G. M. (2013). To master or perform? Exploring relations between achievement goals and conceptual change learning. British Journal of Educational Psychology, 83(3), 431-451. http://www.ncbi.nlm.nih.gov/pubmed/23822530

4 Meyer, A., Rose, D. H., & Gordon, D. (2014). Universal design for learning: Theory and practice. Wakefield MA: CAST Professional Publishing. http://udltheorypractice.cast.org/login

6 Rose, D. H., Harbour, W. S., Johnston, C. S., Daley, S. G., & Abarbanell, L. (2006). Universal Design for Learning in Postsecondary Education: Reflections on Principles and their Application. Journal of Postsecondary Education and Disability, 19(2), 135-151. https://www.cast.org/products-services/resources/2006/udl-postsecondary-education-reflections-principles-application-rose-johnston-daley

UDL is an educational approach based on the learning sciences with three primary principles—multiple means of representation of information, multiple means of student action and expression, and multiple means of student engagement.

Assessment is the process of gathering information about a learner’s performance using a variety of methods and materials in order to determine learners’ knowledge, skills, and motivation for the purpose of making informed educational decisions.

Video is the recording, reproducing, or broadcasting of moving visual images.

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UMGC Effective Writing Center Designing an Effective Thesis

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Key Concepts

• A thesis is a simple sentence that combines your topic and your position on the topic.
• A thesis provides a roadmap to what follows in the paper.
• A thesis is like a wheel's hub--everything revolves around it and is attached to it.

After your prewriting activities-- such as assignment analysis and outlining--you should be ready to take the next step: writing a thesis statement. Although some of your assignments will provide a focus for you, it is still important for your college career and especially for your professional career to be able to state a satisfactory controlling idea or thesis that unifies your thoughts and materials for the reader.

Characteristics of an Effective Thesis

A thesis consists of two main parts: your overall topic and your position on that topic. Here are some example thesis statements that combine topic and position:

Sample Thesis Statements

Importance of tone.

Tone is established in the wording of your thesis, which should match the characteristics of your audience. For example, if you are a concerned citizen proposing a new law to your city's board of supervisors about drunk driving, you would not want to write this:

“It’s time to get the filthy drunks off the street and from behind the wheel: I demand that you pass a mandatory five-year license suspension for every drunk who gets caught driving. Do unto them before they do unto us!”

However, if you’re speaking at a concerned citizen’s meeting and you’re trying to rally voter support, such emotional language could help motivate your audience.

Using Your Thesis to Map Your Paper for the Reader

In academic writing, the thesis statement is often used to signal the paper's overall structure to the reader. An effective thesis allows the reader to predict what will be encountered in the support paragraphs. Here are some examples:

Use the Thesis to Map

Three potential problems to avoid.

Because your thesis is the hub of your essay, it has to be strong and effective. Here are three common pitfalls to avoid:

1. Don’t confuse an announcement with a thesis.

In an announcement, the writer declares personal intentions about the paper instead stating a thesis with clear point of view or position:

Write a Thesis, Not an Announcement

 2. a statement of fact does not provide a point of view and is not a thesis..

An introduction needs a strong, clear position statement. Without one, it will be hard for you to develop your paper with relevant arguments and evidence.

Don't Confuse a Fact with a Thesis

3. avoid overly broad thesis statements.

Broad statements contain vague, general terms that do not provide a clear focus for the essay.

Use the Thesis to Provide Focus

Practice writing an effective thesis.

OK. Time to write a thesis for your paper. What is your topic? What is your position on that topic? State both clearly in a thesis sentence that helps to map your response for the reader.

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Creating Measurable Learning Objectives

Sara Bakker

Music Department, Utah State University

E-mail: [email protected]

Received June 2019

Peer Reviewed by: Abigail Shupe, Daniel Blim

Accepted for publication September 2019

Published September 2, 2020

https://doi.org/10.18061/es.v7i0.7369

This essay argues for the articulation of learning goals at all levels of teaching in music theory, from the curriculum to the individual lesson plan. It summarizes the use of cognitive-process verbs from the field of learning theory and acknowledges a confusing overlap between common music theory tasks and cognitive-process verbs. It suggests a model for stating learning goals in music theory that blends our current terminology with more universal and established terms. It concludes with a detailed discussion of several models of learning goals at the assignment, course, and curricular levels.

Keywords: goals, objectives, outcomes, Bloom's taxonomy, verbs, curriculum

Introduction

"[A]ll aspects of theory teaching—from the presentation of lecture material and drill practice to the construction of curricular models and statements of objectives—should be patterned by design and not by chance ."

"While a philosophy may remain unspoken, it should never remain unknown ."

These statements come from the second edition of Michael Rogers's (2004, 15–16, emphasis added) foundational book on music theory pedagogy. They emphasize, much like the book more broadly, the importance of intention in every aspect of teaching: lessons, practice, curricula, and learning goals. These are indeed laudable, almost superfluous aims in teaching, and yet the book, and indeed the field more broadly, has not developed them evenly. While the field of music theory pedagogy has flourished in the development of innovative and effective ways of teaching, I argue that it has grossly neglected learning goals. There is a critical lack of research in music theory to assist in selecting or articulating them. I hypothesize that articulating learning goals is especially challenging because many common music-theory tasks do not fit neatly in the most commonly used model for creating learning goals, the Bloom taxonomy. Finally, I provide sample learning goals and critique real-world examples of learning goals at three levels of learning—assignment, course, and curriculum.

Education researchers distinguish between learning objectives and learning outcomes , both of which are examples of goal-setting for learning. Learning objectives focus on a specific skill and are most appropriate at the lesson- or assignment-level, whereas learning outcomes focus on more synthetic skill sets and are most appropriate at the course- or curriculum-level. In the literature, these are treated as distinct categories. Individual studies and articles tend to address either objectives or outcomes. I have found it helpful in my own teaching, however, to group them together. I understand objectives and outcomes as different by degree, but not in kind, and will use "learning goal" as an umbrella term to refer to goal-setting for learning at any level. Learning goals are statements of the knowledge and skills that students are expected to demonstrate as a result of learning. They can address learning at any level, from individual lessons and assignments to whole courses and curricula. Thinking of learning goals more holistically is helpful in coordinating different levels of teaching, ensuring a good fit between curricular and course goals on the one hand and day to day classroom activities on the other.

According to renowned specialist in course design Allen Miller (1987) , learning goals serve three main purposes. They (1) clarify for students the instructor's expectations of learning so that students can direct their efforts and monitor their own progress, (2) assist instructors in selecting and organizing appropriate teaching and learning activities, and (3) assist instructors in selecting appropriate ways to assess student-learning. In addition to this, I would add that they (4) can also be used to coordinate instructors, both across sections of a single course and across a curriculum to ensure students are prepared for subsequent courses.

In music theory pedagogy, we have no foundational references to assist with selecting or articulating learning goals. Anna Gawboy (2013) confronts the issue in a syllabus-writing workshop. She is stumped by its most fundamental question, "What do you want your students to be able to do after taking your class?" Gawboy seeks models from the syllabi of courses she has taken and ones her colleagues taught, but finds that none describe the course from the perspective of student-doing. Instead, she finds descriptions of what the class will cover, answering a related, but different question, "What do you want your students to know after taking your class?" Essentially, Gawboy is describing a common confusion between content goals and learning goals. The difference is subtle: one frames a class from the perspective of teacher-input (this is what I will teach you), while the other frames it with student-output (this is what you will be able to do because of what you have learned). Without adequate models and resources, Gawboy frames the course she is designing at the workshop with content-goals instead of learning-goals, and realizes retrospectively that in so doing she "managed to sidestep the most profound question facing every theory teacher."

Had she looked to contemporary music theory literature for guidance, she would have found only two sources, neither of which would have been much help. Rogers (2004) underscores the importance of learning goals with statements such as those quoted at the outset of this article, but does not go into enough detail to even provide a workable definition. Deborah Rifkin and Phillip Stoecker (2011) address learning from a student-doing perspective, but they only address the aural skills classroom in their model. Indeed, music theory literature on learning goals remains an underrepresented area. Editors Rachel Lumsden and Jeffrey Swinkin (2018) include over twenty essays on music theory pedagogy, only one of which address learning goals with any intentionality. Although they are central to Brian Alegant's chapter, readers would not know to look for them based on the title, "Teaching Post-Tonal Aural Skills." Echoes of the concept of learning goals are also present in essays by Janet Bourne and Elizabeth West Marvin, but learning goals are not the central point of any chapter. Leigh VanHandel (2020) similarly lacks dedicated essays on learning goals. Searches of keywords "goal," "objective," and "outcome" return no hits on the Journal of Music Theory Pedagogy 's website. Perhaps it is telling that the two sources that foreground learning goals, do so in relation to aural skills pedagogy. Maybe we feel that skills classes are where students do things, as opposed to learn things. This is a false distinction, however, because learning should always be framed as something students can do because of information, reflection, teaching, and so on.

Designing Learning Goals

Most recommendations for articulating learning goals emphasize three main issues. Learning goals should (1) be student-centered, (2) emphasize the appropriate cognitive task using codified verbs, and (3) name the applicable course content. Some also recommend (4) clarifying any constraints, such as time, approved reference material, etc., and (5) listing the specific instruction that prepares students, such as a lesson, reading, module, course, etc. To read a few examples parsed according to these categories, please see Example 2.

One of the most crucial elements of a learning goal is a verb that clearly defines the intended task. These verbs both focus attention on student-doing and indicate possible methods of assessment. The most commonly referred to taxonomy of such verbs is by learning theorists Harold Bloom and David Krathwohl (1956) , updated by Lorin Anderson and David Krathwohl (2001) . Their taxonomy codifies six hierarchical categories of knowledge, each of which is named by a "hallmark" verb and exemplified by similar verbs. Each category subsumes all categories to its left, modeling increased processing of information, incorporation of educated opinions, use of originality, and general cognitive load with each leftward category. Example 1 reproduces an especially concise list, although the information in the taxonomy is widely available in a variety of formats , including automated builders , and in Rifkin and Stoecker (2011) with modifications for aural-skills tasks.

Designing Music Theory Learning Goals

Two special issues confront teachers of music theory who wish to write clear learning goals: verb-fit for music theory learning and unfamiliarity with appropriate models of goals at various levels of learning.

Verb-Fit for Music Theory

Choosing appropriate verbs is essential to the success and clarity of learning goals, yet there are issues with applying Bloom-verbs to music theory. One challenge is that many common music theory tasks are actually quite complex, relying on multiple component cognitive tasks. Labeling nonchord tones, for example, requires an understanding of Roman numerals, which itself requires an understanding of keys, scales, chords, and inversions. We might think that naming nonchord tones is an "Understand" task, when in most contexts it would more likely be an "Evaluate" task. Other music theory tasks may also be surprisingly complex to instructors, including stylistic composition ("Create"), harmonic dictation and sight singing ("Evaluate," where the most complex element involves judging the fit between the given stimulus and what the student produces), or resolving chordal 7ths properly ("Apply").

A second complication with using Bloom verbs in music theory is that "Analyze" is a category unto itself. Analysis is perhaps the quintessential music theory task, one we know, love, and assign frequently. Yet as my previous example suggests, we must be careful not to conflate analytical tasks with "Analyze" tasks. Here are some common analytical tasks that are not "Analyze" tasks:

• Analyzing Roman numerals in contexts without nonchord tones; analyzing pre-segmented set classes ("Understand")
• Analyzing or realizing figured bass ("Apply")
• Analyzing Roman numerals in contexts with nonchord tones; set class analysis where the segmentation is not given; analyzing form ("Evaluate")
• Schenkerian analysis; analytical essays ("Create")

A final complication for using Bloom verbs in music theory is that some of the most common music theoretical tasks, such as "harmonization," "sight singing," and "notate" are not represented in the verb list at all. Instructors are on their own to determine where these fit. Below, I present a method to aid in determining the most appropriate Bloom verb for common music theory tasks.

To identify where a given task falls on the Bloom chart, one must carefully determine the subskills involved, perhaps through listing them, rewording the task using only verbs from the Bloom chart (imagining that you can't say "harmonize," for example), or finding substitute verbs from the Bloom chart. Next, determine which of the subskills involved in the target task is the most leftward on the Bloom chart. Finally, reword the target task using a verb from the appropriate category. Additionally, it will be helpful to students and instructors alike if the traditional music theory verb also appears in the learning goal, perhaps in parentheses, to clarify instructor expectations. Example 2 shows some common music theory tasks articulated first with the traditional music theory verb and the most appropriate Bloom verb in parentheses.

Assignment-Level Learning Goals

Learning goals at the assignment level should use carefully chosen verbs and make the learning task as explicit as possible. The models above do this by including common music theory verbs that are not on Bloom lists, as well as a representative Bloom verb, and puts that verb in the second position of the learning goal. Michaelsen 2020 discusses ways to assess progress on learning goals using the concept of mastery learning. Below, I demonstrate how to revise existing learning goals, using examples from Daniel Stevens's keynote for the Pedagogy into Practice conference in May 2019.

His handouts use the heading "Outcome" for a series of five tasks he asked participants to do. Two of these are reproduced below as Example 3. The presence of outcomes at the top of the handout shows that Stevens is thoughtful and intentional about his purpose, yet the clarity of those outcomes varies. Example 3a is excellent: It is "participant-centered," focuses on an appropriate verb, and includes information about constraints. This learning goal could be strengthened by emphasizing the action-verb. The "Compare" version, which I have written, suggests one way to focus on the main verb by reordering. Example 3b is somewhat less clearly articulated. The main verb is "track," with modifiers for where (a sonata-form development) and how (by ear). "Track," however, is not a clearly defined learning task—What does it mean to "track by ear?"—and it is not a Bloom verb, either. Additionally, "large-scale harmonic design" could be more specific. The "Compare" version suggests a revision that clarifies the intended task and highlights the main verb.

Example 3. Learning Goals at the Assignment Level (Stevens)

• Outcome for Challenge 2: Participants will "break" a poetic text and recombine its phonetic and rhythmic materials to create a new piece of music. Compare: Participants will create a new piece of music by "breaking" and recombining the phonetic and rhythmic materials of a poetic text.
• Outcome for Challenge 5: Participants will track the large-scale harmonic design of a sonata-form development section by ear. Compare: Participants will sing do or ti while listening to a sonata-form development section to track changes in tonic.

To be fair, Stevens is an expert at articulating clearly stated, measurable learning goals—he includes nine of them on his rubric for Challenge 2 .

Course-Level Learning Goals

At the course level, it is important to balance different ways of demonstrating learning. Ideally, no course is only about "Remembering" or "Creating," but rather blends and cultivates different kinds of knowing. Cognitive science research, summarized in Brown, Roedinger, and McDaniel (2014) , suggests that using knowledge in different ways strengthens the learning and makes it more durable.

One way to ensure a balanced course is to choose tasks from at least four Bloom categories. Example 4a compares course descriptions of a single course as it transitions from content goals (2014) to learning goals (2019). The course is Music Theory I, taught by Timothy Chenette. First, notice Chenette's verb choices (underlined). The 2014 actions are "learn" or "gain," verbs that emphasize learning and improvement and are even called "learning objectives" on the syllabus. They are actually framing content goals, however, because they are largely saying students will learn about some abstract concept (voice leading, harmonic progressions, etc.), rather than learn to do something concrete with knowledge. Neither verb is included in the list of codified verbs. The 2019 actions are much more varied, and all clearly align with a cognitive category. Relatedly, notice how much more clearly the tasks themselves are defined in 2019 of Example 4a. What would it mean to know "how diatonic harmony works," or to "gain in your appreciation of common-practice music?" Those are completely valid things for students to learn, but in 2014 they are framed too broadly and without attention to how the learning might be evaluated to serve as learning goals.

Example 4b provides a framework for evaluating the balance of learning tasks in a course. Learning-goal verbs for Chenette's 2019 syllabus are listed in the left column and the corresponding category name from the Cognitive-Process Verbs in Example 1 are on the right. This course has five types of tasks (verbs) that correspond to four or five different Bloom categories. (The difference between four and five will rely on the types of context in which "Describe" is used, whether it is oriented more toward "Listing" or "Explaining.") This represents an excellent balance of types of learning, which suggests that it will help students develop robust, durable knowledge that they can readily apply in different ways.

Curricular-Level

At the level of the entire music theory curriculum, learning goals tend to be broader than those at the course level. Curricular learning goals are helpful because they provide an element of cohesion among courses with different types of content and levels of detail and also because they can help prepare students for a robust future in their discipline. Several essays in this volume demonstrate the value of goal-setting at various levels of learning when updating the curriculum ( Gades 2020 , Lavengood 2020 , and Peebles 2020 ).

To meet such broad goals, curricular goals are ideally comprehensive, but also visionary and actionable: they should identify wide-ranging priorities that will help students be resilient. The process of generating curricular goals should also include a discussion of how they relate to individual courses.

Example 5 reproduces the curricular learning goals by Ann Stutes and Scott Strovas (2019) for the four-semester music theory sequence at Wayland Baptist University. It has several visionary, future-oriented elements, including its emphasis on communication, collaboration, and problem-solving in different situations. These are varied enough that they could apply to aural skills and written courses, introductory and capstone courses alike, and they are ultimately transferable skills. These curricular goals would be stronger, however, if they used cognitive verbs to clarify the goals ("progress," "navigate," "engage" are unnecessarily vague), and especially if they clarified the connection to courses. Such a connection could be made through a statement that recommends, for example, that each course have at least one course learning goal that supports each curricular learning goal. Ideally, individual curricular goals would be met through multiple courses. While curricular goals may or may not be widely known or intentionally incorporated into courses at any given institution or by any given instructor, building in a connection between curricular learning goals and course learning goals helps to prevent the curriculum from becoming divorced from practice.

Example 5. Curricular Learning Goals (Stutes and Strovas)

Through conceptual inquiry into and hands-on engagement with assigned music literature, individuals actively preparing for the profession will progress in their ability to…

• Communicate effectively in the language of the profession of music;
• Critically engage in the craft of music as informed listeners and creative artists;
• Collaborate with peers in solving musical problems through an evolving collective understanding of musical material;
• Navigate musical situations confronted in the applied studio, in ensembles, through professional opportunities, and through independent creative exploration

This article focuses on the importance of considering learning goals in the process of curriculum reform. This is useful whether that change is oriented toward broadening the types of music we study, incorporating more socially or ecologically conscious analytical perspectives, or including opportunities for student-choice. Using clear, verb-oriented learning goals at every stage of planning for learning (lessons, assignments, courses, and curricula) is a concrete way of turning a vision into a formal curriculum, while emphasizing learning. Furthermore, learning goals are most effective when they are coordinated across all levels of learning, from curriculum to course to assignment and even to lessons, and that coordination is easiest to implement in the curricular-redesign phase. Without actively, intentionally choosing learning goals, we risk treating student-learning as a byproduct of our teaching, rather than its main purpose, and leaving what is arguably the most important part of what we do "unknown" and "patterned by chance."

Acknowledgements

This content was initially delivered in workshop format for the Pedagogy into Practice conference in Santa Barbara. I would like to thank the participants of that workshop for their probing and engaged discussions on this topic and for an especially provocative debate on the cognitive tasks involved in sight singing.

Bibliography

• Alegant, Bryan. 2018. "Teaching Post-Tonal Aural Skills." In The Norton Guide to Teaching Music Theory , edited by Rachel Lumsden and Jeffrey Swinkin, 147-60. New York: W. W. Norton & Company, Inc.
• Ambrose, Susan, Michael W. Bridges, Michele DiPietro, Marsha C. Lovett, Marie K. Norman. 2010. How Learning Works: Seven Research-Based Principles for Smart Teaching. San Francisco: Jossey-Bass.
• Anderson, Lorin, and David Krathwohl. 2001. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives . New York: Longman.
• Brown, Daniel, Henry Roediger, and Mark McDaniel. 2014. Make it Stick: The Science of Successful Learning. Cambridge, MA: Belknap Press.
• Bloom, Harold, and David Krathwohl. 1956. Taxonomy of Educational Objectives: The Classification of Educational Goals. New York: Longman.
• Gawboy, Anna. 2013. "On Standards and Assessment." Engaging Students: Essays in Music Pedagogy 1. https://doi.org/10.18061/es.v1i0.7162
• Lumsden, Rachel, and Jeffrey Swinkin, eds. 2018. The Norton Guide to Teaching Music Theory. New York: W. W. Norton & Company, Inc.
• Miller, Allen. 1987. Course Design for University Lecturers . London: Kogan Page.
• Rifkin, Deborah, and Phillip Stoecker. 2011. "A Revised Taxonomy for Music Learning." Music Theory Pedagogy Online 25.
• Rogers, Michael R. 2004. Teaching Approaches in Music Theory: An overview of Pedagogical Philosophies . Second edition. Carbondale, IL: Southern Illinois University Press.
• "Tips on Writing Course Goals/Learning Outcomes and Measurable Learning Objectives." Center for Excellence in Learning and Teaching, Iowa State University. Accessed September 11, 2019.
• VanHandel, Leigh. 2020. The Routledge Companion to Music Theory Pedagogy . New York: Taylor & Francis Group.

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Engaging Students: Essays in Music Pedagogy presents short essays on the subject of student-centered learning, and serves as an open-access, web-based resource for those teaching college-level classes in music.

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• How to Write a Thesis Statement | 4 Steps & Examples

How to Write a Thesis Statement | 4 Steps & Examples

Published on January 11, 2019 by Shona McCombes . Revised on August 15, 2023 by Eoghan Ryan.

A thesis statement is a sentence that sums up the central point of your paper or essay . It usually comes near the end of your introduction .

Your thesis will look a bit different depending on the type of essay you’re writing. But the thesis statement should always clearly state the main idea you want to get across. Everything else in your essay should relate back to this idea.

You can write your thesis statement by following four simple steps:

• Start with a question
• Write your initial answer
• Develop your answer
• Refine your thesis statement

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Table of contents

What is a thesis statement, placement of the thesis statement, step 1: start with a question, step 2: write your initial answer, step 3: develop your answer, step 4: refine your thesis statement, types of thesis statements, other interesting articles, frequently asked questions about thesis statements.

A thesis statement summarizes the central points of your essay. It is a signpost telling the reader what the essay will argue and why.

The best thesis statements are:

• Concise: A good thesis statement is short and sweet—don’t use more words than necessary. State your point clearly and directly in one or two sentences.
• Contentious: Your thesis shouldn’t be a simple statement of fact that everyone already knows. A good thesis statement is a claim that requires further evidence or analysis to back it up.
• Coherent: Everything mentioned in your thesis statement must be supported and explained in the rest of your paper.

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The thesis statement generally appears at the end of your essay introduction or research paper introduction .

The spread of the internet has had a world-changing effect, not least on the world of education. The use of the internet in academic contexts and among young people more generally is hotly debated. For many who did not grow up with this technology, its effects seem alarming and potentially harmful. This concern, while understandable, is misguided. The negatives of internet use are outweighed by its many benefits for education: the internet facilitates easier access to information, exposure to different perspectives, and a flexible learning environment for both students and teachers.

You should come up with an initial thesis, sometimes called a working thesis , early in the writing process . As soon as you’ve decided on your essay topic , you need to work out what you want to say about it—a clear thesis will give your essay direction and structure.

You might already have a question in your assignment, but if not, try to come up with your own. What would you like to find out or decide about your topic?

For example, you might ask:

After some initial research, you can formulate a tentative answer to this question. At this stage it can be simple, and it should guide the research process and writing process .

Now you need to consider why this is your answer and how you will convince your reader to agree with you. As you read more about your topic and begin writing, your answer should get more detailed.

In your essay about the internet and education, the thesis states your position and sketches out the key arguments you’ll use to support it.

The negatives of internet use are outweighed by its many benefits for education because it facilitates easier access to information.

In your essay about braille, the thesis statement summarizes the key historical development that you’ll explain.

The invention of braille in the 19th century transformed the lives of blind people, allowing them to participate more actively in public life.

A strong thesis statement should tell the reader:

• Why you hold this position
• What they’ll learn from your essay
• The key points of your argument or narrative

The final thesis statement doesn’t just state your position, but summarizes your overall argument or the entire topic you’re going to explain. To strengthen a weak thesis statement, it can help to consider the broader context of your topic.

These examples are more specific and show that you’ll explore your topic in depth.

Your thesis statement should match the goals of your essay, which vary depending on the type of essay you’re writing:

• In an argumentative essay , your thesis statement should take a strong position. Your aim in the essay is to convince your reader of this thesis based on evidence and logical reasoning.
• In an expository essay , you’ll aim to explain the facts of a topic or process. Your thesis statement doesn’t have to include a strong opinion in this case, but it should clearly state the central point you want to make, and mention the key elements you’ll explain.

If you want to know more about AI tools , college essays , or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

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A thesis statement is a sentence that sums up the central point of your paper or essay . Everything else you write should relate to this key idea.

The thesis statement is essential in any academic essay or research paper for two main reasons:

• It gives your writing direction and focus.
• It gives the reader a concise summary of your main point.

Without a clear thesis statement, an essay can end up rambling and unfocused, leaving your reader unsure of exactly what you want to say.

Follow these four steps to come up with a thesis statement :

• Ask a question about your topic .
• Write your initial answer.
• Develop your answer by including reasons.
• Refine your answer, adding more detail and nuance.

The thesis statement should be placed at the end of your essay introduction .

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Learning Goals and Writing in the Major

Integrated writing in american studies.

The American Studies curriculum emphasizes writing as a central part of the development of students’ intellectual and professional lives. Student writing is expected to include critical, analytical and historical dimensions, not least because all students in the major must complete a senior research thesis project.

In preparation for this project, lower-division American Studies courses and junior seminars include weekly writing assignments in the practice of making arguments and supporting them with evidence from texts read in class.  Additionally, students in these courses explore different forms of writing in multiple short genres, including museum exhibit descriptions, book introductions, etc.  Students also complete research papers that encourage them to make connections between disparate ideas, identify and utilize primary research, and make compelling arguments.  This work is facilitated through training in library research and through the use of citation formatting techniques.

In the interim between the lower-division courses and the senior thesis seminar, American Studies majors may be asked to participate in a student-led collaborative writing project.  The objective of these projects is to engage students with forms of public scholarship.  This is an opportunity for them to exercise their research and writing skills and present their work in various forms to not only fellow students and faculty, but also to alumni, parents, and a broader intellectual community.

The senior thesis seminar is organized into two courses taken sequentially in the student’s fourth year.  These courses provide the opportunity for the genesis and development of an extended project, with a research and writing process that includes the development and refinement of research questions, methodologies, literature reviews/bibliographies, and work plans.  Students are expected to have a regular habit of writing in order to digest and synthesize research insights, and do extensive draft and revision work to make clear, specific and discussion-worthy arguments.  The emphasis of this process is the intellectual maturation of students, whereby their writing practice allows them to take ownership and responsibility for their final project produced at the year’s end.

Learning Goals

The work done by majors in American Studies is guided by the program’s unifying Learning Goals, and is organized through faculty and student goals, strategies and outcomes.

Faculty seek:

• To expose students to theoretical, critical, analytical, and methodological approaches from diverse perspectives within the humanities and social sciences, including anthropology, cultural studies, history, literary studies, media studies, sociology, performance studies, political science, theology, etc.
• To have students develop a course of study that integrates academic work across a range of disciplines and to think and do research in interdisciplinary ways; to have students synthesize and critically evaluate knowledge from diverse fields; to foster student research concentrations in particular areas of American Studies that reflect their individual interests and goals.
• To have students work closely with faculty mentors as they develop their individualized curricula, develop integrated courses of study, and produce original thesis projects.
• To develop and implement innovative research and pedagogic techniques both in the classroom and through related activities and practices. Students in the American Studies major receive instruction in the use of different media for creating and sharing knowledge, such as digital portfolios, digital museums, digital stories, student-produced documentary videos, blogs, live performance, scripts, novels, poetry, and music, which are integrated into the curriculum.
• To have students develop innovative approaches to disseminating knowledge from their studies.  Students should graduate with the ability to use digital tools for displaying and sharing knowledge.

Students seek:

• To develop well-organized arguments about the knowledge produced in the research process.
• To organize sustained student research agendas through the writing of the required senior thesis that reflects their area of primary interest and which is the culmination of their academic program.
• To learn as a community and to work collaboratively through sustained conversation within the classroom and outside it, the latter through internships, study abroad experiences, program field trips, activities, and lectures.
• To use digital portfolios to assemble and integrate students’ coursework and related academic experiences as they progress through the major and to provide a foundation for the development of their senior thesis project.

(Revised Fall 2014) 

ORIGINAL RESEARCH article

When learning goal orientation leads to learning from failure: the roles of negative emotion coping orientation and positive grieving.

• 1 Department of Human Resource Management, Business School, Beijing Normal University, Beijing, China
• 2 Department of Business Administration, Asper School of Business, University of Manitoba, Winnipeg, MB, Canada

Considering failure is a common result in project management, how to effectively learn from failure has becoming a more and more important topic for managers. Drawing on the goal orientation theory and grief recovery theory, the purpose of this paper is to clarify the impact of learning goal orientation on learning from failure. Furthermore, this paper examines the mediating effect of two negative emotion coping orientations (restoration orientation and loss orientation) and the moderating effect of positive grieving in this relationship. The results indicated that: (1) A learning goal orientation is positively related to learning from failure; (2) As a dual-path mediation model, restoration orientation and loss orientation mediate the relationship between a learning goal orientation and learning from failure; and (3) Positive grieving negatively moderates the relationship between a loss orientation and learning from failure.

Introduction

Failure is inevitable in today’s business environment and may bring adverse consequences to the enterprise, but failure can also bring great value and experience to the enterprise. As a result, more and more studies are focusing on failure and individual’s learning behavior after failure. Learning from failure means that “ individuals can gain knowledge and skills from failure and can apply these knowledge and skills in practice ” ( Shepherd et al., 2011 ). Previous studies have shown that learning from failure can have a positive impact on individuals; this includes reducing the risk of future organizational failures ( Ingram and Baum, 1997 ), improving innovation ( Arenas et al., 2006 ), and improving performance ( Argote and Darr, 2001 ). Because of the great value contained in failure, recent studies have begun to explore the antecedent variables (e.g., leadership, organizational culture, and team atmosphere) of learning from failure ( Carmeli and Sheaffer, 2008 ) to make a better failure management for employees to meet the next challenge. However, most scholars focus their research on variables associated with specific failure events (e.g., shame, guilt; according to Wang et al., 2018 ), but pay scant attention to stable psychological variables such as cognition orientation and behavior patterns, which have been found to affect individuals’ learning behavior ( Woolfolk, 1995 ). Specifically, goal orientation theory emphasizes that an individual’s goal orientation, as the cognition and understanding of the achievement, influences behavior responses ( Dweck and Leggett, 1988 ). A learning goal orientation refers to “a tendency for individuals to the desire to develop the self by acquiring new skills, mastering new situations, and improving one’s competence” ( Vandewalle and Cummings, 1997 ). Learning goal orientation has been shown to have a strong driving effect on the motivation of individuals to learn and master skills, and it plays an important role in promoting individuals to make positive behaviors: for example, improving work performance ( Chughtai and Buckley, 2011 ) and promoting innovation behavior ( Hirst et al., 2009 ). However, most of these studies are about its possible important impact on success, ignoring the important role on individual’s behavior after failure. Therefore, exploring the important role of learning goal orientation in the learning behavior of individuals after failure can analyze the psychological process that affects failure from a deeper level, so as to make up for the lack of literature on individual’s learning from failure in the past. As the R&D personnel of high-tech enterprises, as the core component of the enterprise, studying its solutions to failure has a key effect on the stability and sustainable development of the organization ( Wang et al., 2013 ).

In order to deeply explore the role of learning goal orientation on individual’s learning from failure, we need to further explore the mediation variables that may affect this role. Goal-orientation theory believes that goal orientation will affect the individual’s cognitive or emotional tendency toward events, which in turn will trigger behavioral responses ( Dweck and Leggett, 1988 ). In fact, many scholars associate learning goal orientation with the cognitive process at the individual psychological level to explore the specific mechanism of subsequent behavioral responses. With this contention in mind, we focused the present study on investigating the affective mechanisms linking learning goal orientation and learning from failure. Among them, the “grief recovery theory” emphasizes the important influence of negative emotions after failure on learning from failure. And its basic logic is “failure events—negative emotions—learning from failure,” emphasizing the important role of negative emotions represented by grief brought by failure in reducing the quality of learning from failure ( Shepherd, 2003 ). Shepherd (2003) and Shepherd et al. (2009 , 2014 , 2011 ) based on this theory focused on grief and its recovery mechanism, and proposed several coping orientations for individuals to cope with negative emotions: restoration orientation (a kind of emotion-focused coping orientation), loss orientation (a kind of event-focused coping orientation), and oscillation orientation (alternately use restoration orientation and loss orientation). While goal orientation has an important influence on the internal and external motivations and behavioral responses of individuals ( Steele-Johnson et al., 2000 ). Therefore, according to the grief recovery theory and goal orientation theory, we assume that individuals with learning goal orientation may adopt different types of coping orientations to adapt to the negative emotions brought about by the failure, and the emotional coping behaviors may have a further effect on subsequent learning.

Furthermore, is it possible that some boundary variables will accelerate the effect of the above mechanism? We further anticipate that emotion (e.g., grieving caused by failure) may be crucial to the relationship between cognition (i.e., negative emotion coping orientation) and behavior (i.e., learning from failure) after a failure event has occurred ( Dolan, 2002 ; Phelps, 2006 ). Grieving will inevitably arise after failure. According to grief recovery theory, the negative emotions represented by grief will affect the breadth and depth of individuals’ information collection and processing, thus reducing the quality of learning from failure. While positive grieving is a form of grieving first proposed by Blau (2006) , which describes the positive aspects of grieving, usually manifested in acceptance, exploration, etc. Some previous studies have shown that positive grieving will positively related to learning behavior ( Wang et al., 2019 ), but as a bright aspect of the grieving, few studies use it as a moderator to explore its boundary effect on the learning process. Therefore, exploring whether positive grieving can play a positive role in the relationship between the individual’s coping orientations to negative emotions and learning from failure can help us further understand the mechanism of positive grieving.

In summary, we addressed this issue by testing the conceptual model depicted in Figure 1 . First of all, we combined the individual’s deeper-level psychological and cognitive variables to explore the important influence of learning goal orientation on subsequent learning behavior, and further developed the application situation of learning goal orientation mechanism; secondly, by combining with grief recovery theory, we extend the application scope of Shepherd et al. (2011) emotional recovery mechanism, taking the individual’s coping orientation to negative emotions as an mediation variables. Finally, according to the conclusion of Dolan (2002) and Phelps (2006) that emotion plays an important role in the mechanism of behavior, we add a moderation variable, namely positive grieving, which may promote the path of “coping orientation—learning from failure.” Through analyze questionnaire data from high-tech companies in China, in demonstrating the linkages proposed in the model, our results contribute to the literature in several important ways, and also provide practical significance for enterprise management. First, we replicate much of the work reported in Shepherd et al. (2011) , among conceptually similar constructs but at the individual’s cognition and behavior level of analysis. Also, to explore the individuals’ deeper level of psychological and behavioral variables (e.g., learning goal orientation and coping orientations), we make learning goal orientation as an antecedent and make coping orientations as a mediation variable to learning from failure. Hence, the current research answers mounting calls for individual-level studies on goal orientation, coping behavior orientations, and learning behavior within an integrated framework. Second, since grieving is inevitable after failure, it is necessary to explore positive grieving (i.e., the positive side of grief) for the occurrence of learning behavior. Our findings may benefit both applied researchers and practitioners, as they reveal a previously unidentified boundary condition regarding the relationship between coping orientations and learning from failure.

Figure 1. Theoretical model.

Literature Review and Hypotheses

In fact, previous scholars used learning from failure as an outcome variable to explore the individual-level influencing factors that may affect individual’s learning behaviors. Most of these studies focused on the emotional and cognitive variables generated by individuals after failures events. Regarding the influence of emotional response on learning from failure, Shepherd and Cardon (2009) shows that the individual’s negative emotions after failure will have an impact on learning from failure and following tries. Bohns and Flynn (2013) compared the impact of the emotional response caused by failure on the performance output of employees in the next cycle, and they emphasize that for learning from failure, the emotional response of guilt is more positive and effective than shame. Secondly, the individual’s cognition to failure event will also affect learning from failure. For example, Hao et al. (2018) research shows that critical thinking is beneficial to learning from failure. Boss and Sims (2008) researched that employees’ self-efficacy, emotional regulation and self-leadership can help them recover faster from failure. In addition, failure is not changeless. The number of failures experienced by employees has also become an important influencing factor. For example, Boso et al. (2019) believe that business failure experience will significantly predict learning from failure behavior. Although previous studies have analyzed the influence mechanism of learning from failure from multiple perspectives at the individual level, these variables mostly focus on the emotional or cognitive response after failure, and still lack individual stable psychological factors. Exploring the stable characteristics of individuals can better interpret the cognitive and behavioral processes of ordinary individuals in the face of failure. Specifically, goal orientation theory can well explain the psychological process of the generation of individual’s behavior. Previous scholars have confirmed that different goal orientations lead to different cognitive and behavioral patterns. Dweck’s goal orientation theory represents how personal goals and beliefs create the mental framework from which individuals follow avoidance or approach strategies toward goals, being a distinct construct from both goal setting (e.g., personal choices concerning most attractive goals) and goal striving (e.g., behaviors and thoughts directed toward a specific) ( Dweck, 1986 ; Dweck and Leggett, 1988 ; Vandewalle and Cummings, 1997 ). Goal orientation relies on personal beliefs concerning intelligence as either incremental (e.g., learning orientation) or stable (e.g., performing orientation), arguing that these beliefs are responsible for the way individuals apply specific strategies toward the pursuit of goals. performance orientation has shown to possess an avoidance dimension (avoiding failure and to show incompetence) and a performing dimension (choosing to perform easier tasks in order to succeed, showing competence) toward the pursuit of results ( Vandewalle et al., 1999 ; Chen and Mathieu, 2008 ). Previous research has also confirmed that compared with other goal orientation, learning goal orientation has a variety of positive effects on individual cognition and behavior, such as promoting individual internal motivation ( Steele-Johnson et al., 2000 ), promoting innovation ( Hirst et al., 2009 ), and communicating and cooperating with others ( Levy et al., 2004 ). Therefore, learning goal orientation may also have a positive impact on individual learning from failure behavior. We chose to use learning goal orientation as an antecedent variable that affects individual learning from failure. Exploring this logical relationship can further clarify the stable personal characteristics factors that may promote learning from failure.

Furthermore, combined with the coping-oriented mechanism of individuals coping with negative emotions after failure, we added the mediation variable, that is, the coping orientation of individuals coping with negative emotions. Most of the research on coping orientation is based on the grief recovery theory. Based on this, Shepherd (2003) proposed the coping orientation of individuals to cope with negative emotions. Restoration orientation is a coping strategy that focuses on emotional recovery. Loss orientation is a coping strategy that focuses on event resolution. If an individual alternates using two coping orientations, it is called oscillation orientation. In fact, Shepherd et al. (2011) has proposed that every coping orientation play a moderating role in the relationship between negative emotions and learning from failure, but the conclusions in the article have not been fully confirmed after empirical research. Many scholars have also constructed a theoretical framework based on the coping orientation, and explored the key role of coping orientations in entrepreneurial failure or subsequent entrepreneurial processes. However, few scholars have explored how the coping orientation of emotional response directly affects the learning from failure process. In addition, due to the oscillation orientation integrate the characteristics of restoration orientation and loss orientation, and the generation of oscillation orientation has time continuity, usually manifested as a method of coping with negative emotions on a long-term scale ( Shepherd et al., 2011 ). Therefore, in this article, we only consider the mediating effect of a single loss orientation or restoration orientation, and do not consider the possible mediating effect of oscillation orientation. Therefore, based on the Chinese cultural background, we try to solve this research limitation through empirical research. The contextual factors specific to Chinese culture will cause Chinese employees or managers to show different research results from Western scholars. Many scholars have explored Chinese management culture based on Chinese unique values such as “ mianzi. ” The results show that China’s unique cultural factors will affect individual cognition and behavior patterns from many aspects such as attitude and emotion ( Bedford, 2011 ). Whether this will affect employees’ learning from failure behavior, and how the specific mechanism of this process is still not studied by scholars.

In addition, the concept of grieving was first used in research on commercial failure by Shepherd (2003) , who proposed that it is a type of negative emotional response after a failure is experienced. Blau (2006) observes that grieving may be either negative (i.e., denial, anger, and negotiation) or positive (i.e., exploration and acceptance). As a normal emotional response, negative grieving usually appears after a failure event occurs, and often leads to some undesirable consequences such as low performance and low organization citizenship behaviors. There is no doubt that negative grieving will negatively affect the individual’s learning process and behavior. However, as time goes by, there is a transition to positive grieving, which includes an individual’s acceptance and exploration of the event ( Blau, 2006 ); this allows them to make up for the deficiencies caused by negative grieving, which will, in turn, have a positive impact on the individual’s future behavior pattern ( Blau, 2007 ). There are few studies on whether positive grieving has a positive effect or a negative effect on individuals. Some previous studies have shown that positive grieving will positively related to learning behavior ( Wang et al., 2019 ), but as a bright aspect of the grieving, few studies use it as a moderator to explore its effect on the process of “cognition—learning.” When employees are dealing with the impact of negative emotions, can positive grieving have a boundary effect on the learning process? This is very important for employees to learn from failure in a grieving mood. We proposed a different opinion on this question. A coping orientation usually determines the focus of an individual’s use of follow-up resources and strategies, which further influences the occurrence of subsequent behavior patterns ( Shepherd et al., 2011 ), which in turn will be affected by individual emotions. Because positive grieving has been shown to have a positive effect on individuals, we try to further explore its mechanism on learning from failure ( Blau, 2007 ). Therefore, we assume that positive grieving can moderate the process mechanism of the relationship between coping orientation to learning from failure. Based on the above, we have constructed a theoretical model with coping orientation and positive grieving as a mediator and boundary variable, we will systematically explain this model below.

Learning Goal Orientation and Learning From Failure

According to the goal orientation theory, an individual’s learning goal orientation will have a positive impact on that individual’s behavior ( Cury et al., 2006 ). Individuals with a learning goal orientation mainly focus on behavioral processes related to learning and tasks ( Zweig and Webster, 2004 ). Therefore, we believe that a learning goal orientation will promote individual behavior that helps them learn more from failure.

Individuals with a high learning goal orientation believe that abilities can be improved through learning ( Dweck, 1999 ). With persistence and hard work, anyone can solve and overcome difficulties, develop their ability, and achieve better success in future tasks ( Dweck, 1999 ). Rather than worrying about the adverse effects of failure, they are more interested in improving their ability ( Levy et al., 2004 ). Therefore, people with a high learning goals orientation are more likely to persist in learning after failure events, continue to work hard, summarize their experience in order to further develop their ability, and achieve future improvements.

LGO will affect peoples’ perceptions of event feedback ( Nisan, 1972 ). Individuals with a high LGO view feedback as useful because it provides information about events. Understanding this information and learning from it allows more effective completion of future tasks ( Dahling and Ruppel, 2016 ). For individual with a high LGO, negative feedback is seen as a challenge and provides motivating information. If we can learn from it, we can make ourselves better ( Dweck, 1986 ). When individuals with a high LGO receive negative feedback, they continue to work hard to find solutions ( Dweck and Leggett, 1988 ). Overall, individuals with a high LGO regard failure as an opportunity to develop themselves, and when encountering failure events, they try to learn from them. Therefore, we propose the following hypotheses:

Hypothesis 1: Individual employees who have a high LGO will learn more from failure than individual employees who have a low LGO.

The Mediation of Restoration Orientation

Goal orientation theory says that an individual’s goal orientation will stimulate motivation, which in turn will influence behavior. Therefore, we propose that, as a stable behavioral orientation, the individual’s learning goal orientation will affect the individual’s coping response (e.g., restoration or loss orientation) after failure occurs.

A restoration orientation refers to “the suppression of feelings of loss and proactiveness toward secondary sources of stress that arise from a loss” ( Shepherd et al., 2011 ). Individuals with a strong learning goal orientation pay more attention to the development of abilities ( Dweck, 1986 ). They are willing to try to achieve challenging goals, possess a strong internal motivation and autonomy, and actively look for opportunities for learning and creation in a future work environment ( Van Yperen, 2003 ). Therefore, we assume that a high learning goal orientation will lead to a restoration orientation.

A restoration orientation focuses on recovering from negative events by diverting attention away from failure events and toward other goals ( Shepherd et al., 2011 ). Employees tend to avoid major stressors like project failures and deal with secondary stressors by “cleaning up negative consequences caused by project failures” ( Stroebe and Schut, 1999 ). Seijts and Latham (2006) found that individuals with a high learning goal orientation collect additional information to obtain to improve their capabilities. In addition to the negative impact of project failure, it also brings challenging task requirements and follow-up work tasks ( Shepherd et al., 2011 ), which provides employees with follow-up learning goals and tasks. Thus, the derivative problems caused by failure become an important source of learning, and the experiences and lessons learned from them can become an important source of individual knowledge and skill development ( Stroebe and Schut, 1999 ). Therefore, individuals with a high learning goal orientation may divert their attention from the failure event, and actively engage in the handling of external events (e.g., follow-up challenging tasks and works), that is, take a restoration orientation.

Additionally, individuals with a high learning goal orientation are sensitive to information that may help them ( Dahling and Ruppel, 2016 ). They usually hold the view that “ability can be changed,” thinking that ability can be increased through continuous learning from various events related to failure, so they often have self-confidence in their ability ( Dahling and Ruppel, 2016 ). They are eager to enhance their internal motivation to learn through a series of challenging events brought on by failures, and then improve their abilities ( Dweck and Leggett, 1988 ). For the derivative problems caused by failure, they will also be considered as a way of learning to strengthen the learning of experience in failure to improve personal ability ( Dahling and Ruppel, 2016 ), which will prompt individuals to turn to solve the derivative problems (that is, external events), and continue to pay attention to the “secondary stressors” brought on by failed events. Therefore, we assume that:

Hypothesis 2a: There is a positive relationship between a high learning goal orientation and a restoration orientation.

Eastern culture usually pays attention to “mianzi” (also called “Face” or “Lian”), which is a unique cultural characteristic ( Bedford and Hwang, 2003 ), often be interpreted as both the showing of respect (“giving face”) and ensuring that you do not offend people (causing them to “lose face”). It is a positive public image that a person conveys to others ( Ting-Toomey, 1994 ). Factors such as external stimulus events will increase the individual’s motivation to maintain “mianzi,” and then make corresponding behavioral responses ( Hwang, 1987 ). When facing negative events (i.e., failure events), individuals immerse themselves in a series of negative effects will influence their maintenance of “mianzi,” and increase their fear that they will be looked down upon by others ( Jiang, 2006 ). Implementing a restoration orientation can help people divert attention away from negative events, buffer the negative effects caused by the failure, and thereby provide employees with new information about failures and a new perspective on overcoming failures ( Shepherd et al., 2011 ).

As Yamakawa and Cardon (2015) note, individuals usually produce learning behavior through multiple links such as scanning (i.e., selectively paying attention to, and collecting important information about, failure) and interpretation (processing the scanned information for easy understanding). The two aspects of a restoration orientation—“proactiveness restoration” (i.e., proactively solving the derivative problems caused by a failure) and “avoidance restoration” (i.e., diverting attention away from the failure) are intertwined ( Shepherd et al., 2011 ). When proactively solving a series of problems that derive from a failure, individuals can obtain information about the failure, which is conducive to information scanning ( Cope, 2011 ). When using avoidance restoration, individuals will be free from the negative effects of the failure (such as negative emotions), will enhance the information processing ability, and promote the interpretation of the failure event ( Shepherd et al., 2011 ). Every level can shift the attention to events other than failure, pay more attention to a series of challenges brought by failure, which will reduce the negative emotions caused by loss of “mianzi.” By scanning and interpreting failures and follow-up events, individuals can enhance their ability to construct the meaning of a failure, which helps individuals better understand failures and learn from them ( Shepherd and Cardon, 2009 ). Therefore, we assume that:

Hypothesis 2b: There is a positive relationship between a restoration orientation and learning from failure.

H2a predicted the positive relationship between learning goal orientation and restoration orientation, and H2b predicted the positive relationship between restoration orientation and learning from failure. In conclusion, we also assume that individuals with a high learning goal orientation will trigger a restoration orientation, which will reduce the negative effects of the failure and stimulate positive behavior (i.e., learning from failure). Thus, we assume that a restoration orientation is a mediator in the relationship between learning goal orientation and learning from failure:

Hypothesis 2c: A restoration orientation mediates the relationship between a learning goal orientation and learning from failure.

The Mediation Effect of a Loss Orientation

A loss orientation refers to “working through and processing aspects of a loss” ( Shepherd et al., 2011 ). Some individuals with loss orientation regard failure as an important learning resource ( Shepherd et al., 2011 ). Learning knowledge, skills, and experience from failures will help individuals improve their abilities to deal with similar tasks ( Dweck, 1986 ). We assume that there is a close relationship between a learning goal orientation and loss orientation.

People with a high learning goal orientation value the plasticity of ability, and they believe that they can change the direction of events and improve their ability through their hard work ( Dweck, 1999 ). So they pay more attention to the failure and tend to invest more effort in handling failure events, such as exploring the cause of the failure and suppressing the negative emotions caused by the failure ( Dweck and Leggett, 1988 ). When individuals with a high learning goal orientation deal with work issues, they often use a task involvement strategy, which means actively participating in issue processing in order to meet the needs of the work role. When they experience failure, they will immerse themselves in the event ( VandeWalle et al., 2001 ), that is, adopt a loss orientation.

Failure events usually bring on negative emotions, and these negative emotions will make individuals avoid future failures ( Iyer et al., 2007 ). Individuals with a high learning goal orientation regard negative feedback as an opportunity to make progress in their life. They face the negative feedback with confidence, ignore the negative emotions brought on by failure, and weaken the impact of negative emotions by self-adjusting ( Dweck and Leggett, 1988 ). They investigate the cause of failure and try to determine what went wrong. In doing so, they are sensitive to information that can help them to develop ( Dahling and Ruppel, 2016 ). Although a failure event indicates that the individual’s ability is lacking in some way, it also makes the individual aware of valuable information contained in the failure event ( VandeWalle et al., 2001 ). Rather than regard failure as a blow, individuals are more likely to regard failure as an opportunity to learn new skills. They will explore the reason of failure, search and summarize relevant information to achieve personal development ( Dahling and Ruppel, 2016 ), thus strengthening their loss orientation. Therefore, we assume that:

Hypothesis 3a: A high learning goal orientation has a positive relationship with a loss orientation.

Shepherd et al. (2011) found that a loss orientation includes two dimensions: a “self-dimension” (which focuses on the failure process and investigates the reason for the failure), and an “others-dimension” (which involves communicating with the outside world to discover the reason for the failure). In the “self-dimension,” individuals who adopt a loss orientation after failure will pay more attention to the failure and its reasons. Although they will also face negative emotions such as sadness and inferiority caused by the failure, those who adopt a loss orientation will not mindlessly engage in negative thinking from which they cannot extricate themselves ( Shepherd et al., 2011 ). They are able to quickly break the relationship between a bad mood and failures and make the transition to a stable mood as they reflect on their failure ( Shepherd et al., 2011 ). By exploring the reasons for a failure, individuals can understand failure deeply ( Corbett et al., 2007 ), have a better understanding in the errors or limitations in the failed project ( Birtchnell, 2001 ), and make an objective attribution ( Baron, 2000 ).

In the “others-dimension” of loss orientation, individuals who adopt a loss orientation after failure tend to talk about their feelings regarding the project failure to their friends and family, and find out the reasons for the failure by asking others for their opinions ( Shepherd, 2003 ). This helps them explore and accept the reasons for the failure, increases their confidence, and prepares them to make corresponding adjustments to improve their present situation ( Rybowiak et al., 1999 ). All of this helps them learn from failure.

Investigating the reasons of failure and its solutions will make individuals aware of the potential value of failure and help them to integrate relevant and useful information. Individuals who adopt a loss orientation will tend to regard failure as an opportunity to improve skills and develop themselves ( Tjosvold et al., 2004 ). Such an orientation will help the individual have a positive cognitive assessment of failure, and encourage them to learn from failure. From the perspective of eastern culture, whether people take measures of correct attribution or cognitive assessment, they can maintain their positive images or social status, which is an effective way for them to pursue subsequent learning. Therefore, we assume that:

Hypothesis 3b: A loss orientation has a positive relationship with learning from failure.

H3a predicted the positive relationship between learning goal orientation and loss orientation, and H3b predicted the positive relationship between loss orientation and learning from failure. Together, these hypotheses specify a model in which a learning goal orientation indirectly increase learning from failure by contributing to a loss orientation. We assume that individuals with a high learning goal orientation will devote themselves to the summary of failure events and further participate in the follow-up treatment of failure events will help them become immersive, further explore the experiences and lessons learned from failures, promote them to face failures and learn from failures. Therefore, loss orientation is another mediator in the relationship between learning goal orientation and learning from failure:

Hypothesis 3c: A loss orientation mediates the relationship between a learning goal orientation and learning from failure.

The Moderation Effect of Positive Grieving

Individuals will experience some negative emotions (e.g., guilt, anger, and shame) after a failure ( Carver and Scheier, 1990 ), and these emotions can strengthen or weaken learning behavior ( Zhao and Olivera, 2006 ; Shepherd and Cardon, 2009 ). Dolan (2002) and Phelps (2006) argue that emotion will play an important role in the learning process, and will have an impact on cognition and behavior after a failure occurs. Grief is a negative emotional response ( Shepherd, 2003 ), but positive grieving is the bright side of grief. According to Blau (2007) , positive grieving manifests itself in two ways: exploration (i.e., for hopeful opportunities and new possibilities), and acceptance (i.e., accepting the fact of failure). Individuals with positive grieving will accept the facts of failure, helping them shift the attention away from failure events ( Ellard et al., 2017 ). Individuals with a high restoration orientation are good at dealing with external or derivative information regarding failure, and pay more attention to other goals ( Shepherd et al., 2011 ). Therefore, they can further enhance their motivation to learn from outside the failure event. In addition, individuals with high positive grieving are not afraid of failure, and tend to easily escape from its negative effects ( Blau, 2007 ). From a resource perspective, they will have more cognitive resources to deal with the external or derivative information ( Shepherd, 2003 ). Individuals with positive grieving will show more constructive behaviors, such as communicating with colleagues to conclude the experience and lessons from failure, which will help them invest in the next project task earlier ( Blau, 2007 ). These benefits will help individuals with a restoration orientation to enhance their learning behaviors.

By contrast, individuals with a loss orientation usually focus more on information about the failure event. They tend to explore the reasons for the failure, and continuously search for information about the failure. From two perspectives of positive grieving, in exploration, individuals with high positive grieving usually have a bright view of the future, and pay more attention to future tasks and work opportunities ( Blau, 2007 ). Limited cognition resources will not be used to obsess about the failure, and less attention will be paid to the failure. This will weaken the motivation of such individuals to learn from the failure, which in turn will weaken the relationship between loss orientation and learning from failure. With respect to acceptance, accepting the fact of failure will help individuals to shift their attention from concentrating on the negative events to reflecting on the significance of the event ( Ellard et al., 2017 ). With an acceptance, individuals will reduce their excessive attention on the failure, and they will come to regard failures as “normal events,” This will weaken the motivation of learning from failure events. Therefore, we propose the following hypotheses:

Hypothesis 4a: Positive grieving positively moderates the relationship between a restoration orientation and learning from failure, i.e., the relationship will be stronger when positive grieving is higher, rather than when it is lower.

Hypothesis 4b: Positive grieving negatively moderates the relationship between a loss orientation and learning from failure, i.e., the relationship will be weaker when positive grieving is higher, rather than when it is lower.

Materials and Methods

Participants and procedure.

As the R&D teams of high-tech companies are more likely to encounter setbacks and failures in the R&D process, most technology-based employees may have experienced failures, and the sample is more representative than other industries. Therefore, we focus on high-tech firms in China as our research participants. We define a firm as “high-tech” if 60% or more of its annual sales revenues come from high-tech products and services, and if 10% or more of its employees have engaged in R&D in the past year. According to this standard, we randomly selected 400 high-tech enterprises from the list of Beijing high-tech enterprises provided by the Beijing Municipal Science and Technology Commission, and we invited them to participate in the research during an introductory telephone conversation. The participants are members of the R&D teams in these companies. These teams are required to have participated in project development in the past 3 years and have had the experience of project failure. During the phone call, we emphasized the purpose of the research and the confidentiality of data collection. We then asked the CEO to write an endorsement to encourage employees to participate in a questionnaire survey, and we promised to give the final research results to the companies’ leaders.

The distribution and recovery of the questionnaires was accomplished using the following steps. First, the firms that participated in the study selected a coordinator (usually a human resource manager) who provided our research assistant with a list of research teams (usually R&D teams). With the help of the coordinator, the research assistant distributed questionnaires to the staff before the weekly (or monthly) regular meeting of the team. To ensure everyone’s participation, the research assistant obtained contact information from the coordinator for any members who missed meetings. An envelope was left for these absentees to fill out and return to the research assistant. In order to improve the recovery rate of the research questionnaire, we also distributed small gifts and the endorsement of the CEO. After answering the questionnaire, all participants signed a confidentiality agreement to ensure that the questionnaire was not used for other purposes.

The final sample included 22 companies in Beijing area technology industry (750 responses in total). All team leaders and members provided completed questionnaires. The average team size, including the team leader, was 5.43, and ranged from 3 to 10 ( SD = 1.60). The mean respondent age was 31.67 years (age range was 20–56 years, SD = 5.525), with 577 men (79%) and 173 women (21%). About 51.2% of the respondents had bachelor’s degrees and 38.5% had a master’s or doctor’s degrees, and the remaining samples are all college degrees.

In this study, we defined project failure depending on the results of research projects. Following previous studies, we defined project failure as ‘the termination of an initiative to create organizational value that has fallen short of its goals’ ( McGrath, 1999 ; Hoang and Rothaermel, 2005 ), and we gave this definition in the introduction section of our questionnaires. We first arrange and organize the original scales, and then use the back-translation method ( Brislin, 1970 ) to ensure that there will be no translation errors. All coefficient alpha is Cronbach’s alphas. All scales are scored by using the Likert-6 scale.

Learning Goal Orientation

We used the five-item scale developed by Vandewalle and Cummings (1997) to measure learning goal orientation. It asks employees to explain how they learn from a project failure. Sample items include “I am willing to choose those challenging tasks,” and “I often seek opportunities to develop new skills and learn new knowledge.” Response options ranged from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.852.

Restoration Orientation

We used the six-item scale developed by Shepherd et al. (2011) to measure restoration orientation. It asks employees to explain to what extent they agree with each behavior statement after a failure. Sample items include “I intentionally divert my attention, not thinking about the problem of the project failure” and “After the project fails, I try to sort out my thoughts.” Response options range from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.636.

Loss Orientation

We used the six-item scale developed by Shepherd et al. (2011) to measure loss orientation. It asks employees the extent to which they agree with the behavior statement after a failure. Sample items include “I worked with my colleagues to find the cause of the failure” and “I worked hard to overcome the negative emotions associated with the failure of the project.” Response options range from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.696.

Positive Grieving

We used the six-item scale developed by Blau (2007) to measure positive grieving. It asks employees to state their personal acceptance of failed projects. Sample items include “I accept the reality of project failure” and “I am willing to explore other possibilities from failed projects.” Response options range from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.833.

Learning From Failure

We used the eight-item scale developed by Shepherd et al. (2011) to measure learning from failure. Employees are asked to explain the degree of change in their own behavior after a failure, including both personal and project dimensions. Sample items include “I have learned to execute the project plan better” and “I have improved my ability to make more contributions to new projects.” Response options ranged from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.907.

Control Variables

Beyond the demographic variables (i.e., gender, age, education level, and tenure in the firm and on a project), we also controlled for the critical factors in project failure and the parallel variables of the variables in the following model: performance-approach goal orientation, performance-avoidance goal orientation, oscillation orientation, and negative grieving. These are described below.

Critical factors in project failure

We used the two-item scale adapted by Dilts and Pence (2006) (According to the results of exploratory factor analysis (EFA), the original 13 items are divided into two items for internal and external factors) to measure the critical factors in project failure. The instrument asks employees to explain why they think the project failed. Sample items include “change in the importance of the entire project in the organization,” and “changes in user needs.” Response options ranged from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.656.

Performance-approach goal orientation

We used the four-item scale developed by Vandewalle and Cummings (1997) to measure performance-approach goal orientation. It asks employees to explain their personal strategy for improving their performance after a failure has occurred. Sample items include “I tried to find a way to prove my ability to colleagues” and “I am willing to do projects that can prove my ability to others.” Response options ranged from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.789.

Performance-avoidance goal orientation

We used the four-item scale adapted by Vandewalle and Cummings (1997) to measure performance-avoidance goal orientation. Because the reliability of the original scale in our research is not enough, we deleted one of the items to improve the reliability. The instrument asks employees to state their personal strategy for avoiding the possibility of failure. Sample items include “I am not willing to take on a task that may show my lack of ability” and “When performing a task, I just try to avoid showing incompetence.” Response options ranged from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.820.

Oscillation orientation

An oscillation orientation involves moving between using the restoration orientation and using the loss orientation. We used the three-item scale developed by Shepherd et al. (2011) to measure oscillation orientation. It asks employees the extent to which they agree with their statement of behavior after a failure has occurred. Sample items include “After giving my emotions a rest, I confront my negative feelings arising from the project’s failure” and “After thinking about the failure for a period of time, I try not to think about it as much as possible.” Responses options ranged from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.580. Because the alpha of this variable is low, we removed this variable and did another data test. The results showed that the existence of this variable did not have much impact on the data test results (the data results are shown in the Appendix ).

Negative grieving

We used the six-item scale adapted by Blau (2007) to measure negative grieving. Because the reliability of the original scale was low, we deleted one of the items to improve the reliability. The instrument asks employees to state their acceptance of failed projects. Sample items include “I can’t believe this will happen to me” and “I’m depressed for the failure of the project.” Responses options ranged from 1 (strongly disagree) to 6 (strongly agree). The coefficient alpha of the scale was 0.864.

In this study, we used Amos 24.0, SPSS 25.0, and Stata 12.0 for data analysis and hypothesis testing. We analyzed the validity of the measurement model, the basic distribution of data, the correlation between variables, and the reliability of the scale. We also do multiple linear regression analysis to test our hypotheses. We use Harman’s single factor analysis to test whether the data has serious common method bias. The results show that the interpretation rate of the first common factor is less than 40% (18.66%, so our data does not have serious common method bias).

Confirmatory Factor Analysis

We first conducted a confirmatory factor analysis (CFA). As shown in Table 1 , our theoretical model (10-factor model) fits better (CMIN/df = 2.470, CFI = 0.909, RMSEA = 0.044) than other models, indicating the construct distinctiveness of our measurements.

Table 1. Comparison of measurement model.

Descriptive Statistics

Table 2 shows the descriptive statistics and the correlations among the variables. As shown in the table, learning goal orientation is significantly related to restoration orientation ( r = 0.145, p < 0.01), loss orientation ( r = 0.174, p < 0.01), and learning from failure ( r = 0.368, p < 0.01). Restoration orientation is significantly related to learning from failure ( r = 0.390, p < 0.01), and loss orientation is significantly related to learning from failure ( r = 0.439, p < 0.01). The data results indicate that there may be a close relationship between learning goal orientation, coping orientation, and learning from failure.

Table 2. Means, standard deviations, reliability, and correlations among study variables.

Hypothesis Testing

Since the research participants come from different companies, in order to test whether the company environment will affect the research results, we compared the results of the hierarchical regression in SPSS 25.0 and the results of the hierarchical regression after using the cluster statement to control the company variables in Stata 12.0. We found that there is a slight difference between the two regression results (results of Stata are shown in the Appendix ), but the effect of learning goal orientation on learning from failure behavior is similar in different companies’ employees. We used SPSS 25.0 for data processing to test our hypotheses, and the result of the hierarchical regression is shown in Table 3 .

Table 3. Hierarchical regression analysis for models.

Hypothesis 1 proposed a positive relationship between a learning goal orientation and learning from failure. As shown in Table 3 , the coefficient between learning goal orientation and learning from failure is significant ( b = 0.322, p < .001, Model 3.2); this supports Hypothesis 1. Hypothesis 2a posited that learning goal orientation is positively associated with restoration orientation. As shown in Table 3 , the relationship between learning goal orientation and restoration orientation is significant ( b = 0.150, p < 0.01, Model 1.2). Hypothesis 2b posited that restoration orientation is positively associated with learning from failure. In Table 3 , the relationship between restoration orientation and learning from failure is significant ( b = 0.126, p < 0.01, Model 3.3). These results provide support for both hypotheses 2a and 2b. Hypothesis 3a proposed that learning goal orientation is positively associated with loss orientation. As shown in Table 3 , the relationship between learning goal orientation and loss orientation is significant ( b = 0.132, p < 0.01, Model 2.2). Hypothesis 3b proposed that loss orientation is positively associated with learning from failure. In Table 3 , the relationship between loss orientation and learning from failure is significant ( b = 0.253, p < 0.001, Model 3.3). These results provide support for hypotheses 3a and 3b. Hypothesis 2c and 3c assumed a mediating role of restoration orientation and loss orientation. We use the Macro program Process developed by Hayes for Bootstrap test to further examine the mediating role of restoration orientation and loss orientation. Our results show that the indirect effect of restoration orientation is.0173 (95% CI [0.0042–0.0361]) and the indirect effect of loss orientation is.0353 (95% CI [0.0102–0.0603]); these results provide support for hypothesis 2c and 3c.

Hypotheses 4a and 4b proposed a moderating role of positive grieving. As shown in Table 3 , when the interactive items (positive grieving × restoration orientation and positive grieving × loss orientation) are entered at the same time, the coefficients of the two are both significant ( b RO = 0.052, p RO < 0.05, b LO = –0.115, p LO < 0.001, Model 3.7). When the interaction items are entered separately, the coefficient of positive grieving × loss orientation is also significant ( b = –0.08, p < 0.001, Model 3.6), but the coefficient of positive grieving × restoration orientation is not significant ( b = –0.016, p > 0.05, Model 3.5). Thus, hypothesis 4b is supported, but hypothesis 4a is rejected. We also test the moderated mediation effect by Process. The results show that the moderating effect of positive grieving on the relationship between restoration orientation and learning from failure is not supported (index 1 = 0.006, 95% CI [–0.0005–0.0145]). Instead, the moderating effect of positive grieving on the relationship between loss orientation and learning from failure is supported (index = –0.0143, 95% CI [–0.029 to –0.0034]).

In order to better interpret the moderating role of positive grieving between loss orientation and learning from failure, following Cohen and Cohen (1983) , we define high and low positive grieving as plus and minus one standard deviation from the mean. As shown in Figure 2 , for individuals with a higher level (1 SD above the mean) of positive grieving, their loss orientation will take more learning from failure behaviors ( b = 0.349, p < 0.05) than those with a lower level of positive grieving ( b = 0.119, p < 0.05).

Figure 2. The moderating role of Positive Grieving between Loss Orientation and Learning from Failure.

Analysis and Discussion

In this study, we analyzed how a learning goal orientation promotes learning among team members after a project failure occurs. Our results show that both a restoration coping orientation and a loss coping orientation mediate the relationship between a learning goal orientation and learning from failure. Positive grieving negatively moderates the relationship between a loss orientation and learning from failure, but a hypothesis that positive grieving moderates the relationship between a restoration orientation and learning from failure is not supported.

Theoretical Contribution

The theoretical contributions of the current study are threefold. First, our study enriches the research on the antecedent variables of learning from failure. Past research has focused mostly on the cognitive reactions after failure ( Zhao and Olivera, 2006 ; Shepherd and Cardon, 2009 ), little is known about the effects of a stable mindset on failure (i.e., goal orientation). This study focuses on the impact of individual behavior orientation on learning from failure. The results of the study validate the role of individual learning goal orientation in promoting learning after a failure. According to the goal orientation theory, an individual’s behavioral orientation will directly or indirectly affect the individual’s behavior ( Dweck and Leggett, 1988 ). However, previous studies tend to pay more attention to variables at the surface-level (such as team atmosphere and individual personality), and there is little research that is focused on individuals’ deep-level attributes such as behavioral orientation. Therefore, this research provides a new research direction.

Second, combined with the theory of grief recovery theory, we extend the application environment of the theory. Shepherd et al. (2011) used grief recovery as a boundary variable to explore the moderating role of emotional coping orientation in the recovery of negative emotions, and believed that loss orientation can promote learning from failure while restoration orientation cannot promote learning. However, after empirical testing, the results have not been fully confirmed. Based on the Chinese cultural background, we propose and test that loss orientation and restoration orientation both have a positive mediating effect in the relationship between learning goal orientation and learning from failure. This expands the context of the grief recovery theory, and subsequent scholars can carry out qualitative research such as case analysis to further confirm its reliability.

Third, an emotional response after failure will influence individuals’ behavior responses ( Dolan, 2002 ; Phelps, 2006 ). We explored the important role of positive grieving generated by individuals interacting with projects. Regarding to the boundary factors that affect the learning from failure process, previous scholars usually limit the moderating variables to the individual’s stable emotions (e.g., shame, shame, etc.), the organization’s management style (e.g., error management culture), and individual characteristics (e.g., resilience), there is little research on the role of failure-induced transitional emotions (i.e., positive grieving) in individual learning process ( Zhao, 2011 ; Fang He et al., 2018 ). As a normal emotion after negative events occur, previous research shows that positive grieving may have an impact on learning behaviors ( Wang et al., 2019 ). However, few scholars use it as a moderating variable to study its influence on the mechanism of individual behavior and its antecedent variables. We further expand the research field of positive grieving. After data testing, the negative moderating role on the relationship between loss orientation and learning from failure has been supported. This is very different from the research conclusions of previous scholars. Most of the previous scholars have confirmed that positive grieving has a positive effect (e.g., learning from failure) ( Wang et al., 2019 ). Our research confirms that positive grieving may also have a negative effect, which provides a theoretical and practical basis for follow-up scholars to further explore. However, the moderating role on the relationship between restoration orientation and learning from failure hasn’t been supported. We contend that our cross-section design contributes to this result. In fact, the benefits of a restoration orientation require time to manifest ( Shepherd et al., 2011 ). Such an orientation cannot buffer the negative effects of failure in the short-term in the way that a loss orientation can. Therefore, our findings reveal the potential difference between loss and restoration orientation, which bears further empirical examination in the future.

Practical Contributions

In terms of management practice, this study suggestions the following recommendations. First, the research results show that individuals with a higher learning goal orientation are more concerned about the development of their abilities and are willing to work hard to improve them ( VandeWalle et al., 2001 ) so that they can learn better from failure. Therefore, team leaders and managers can introduce incentives to encourage staff members to improve themselves. Such a system will increase performance and rewards, motivate a learning goal orientation, and help individuals to learn from failure.

Our research also shows that both restoration and loss orientations can promote learning behavior. Managers should guide and encourage employees to take appropriate countermeasures after a failure occurs. Employees should consciously adopt appropriate treatment methods to maximize the value of their experience and skill learning that failure events provide.

Finally, managers need to realize that positive grieving affects the relationship between loss orientation and learning from failure, and that appropriate grieving can promote individual learning behavior. If individual has an overly optimistic attitude toward the failed project too soon after the failure, this is not conducive to learning from the failure. Managers can encourage employees to “get out of the shadow” so they can more effectively from failure.

Limitations and Future Directions

We recognize that this study has several limitations. First, the data used in this study were cross-sectional, and participants were asked to recall a recent project failure, which may contribute to some biases. In fact, commercial failure often appears random, and it is therefore hard to trace the chain of events that led to the failure. Thus, previous studies usually ask employees to recall such an experience via questionnaires or interviews. To better understand individuals’ reactions after failure, future research should integrate field research and neuroscience-based experiments ( Metcalfe, 2017 ). The key advantage of applying neuroscience methods is to provide more robust conclusions and interpret human behavior from a more fundamental level (i.e., neural processes). Furthermore, in order to further explore the various influencing factors of success and failure in the progress of the project, and further deepen the research, future research can collect data during the project.

Second, the data we collected were from a single point in time and from a single resource (i.e., self-reports of employees). Though we tested Harman’s one factor analysis and CFA to test the risk of CMB, we still recommend that future research use data from multiple sources to make the influence of CMB minimum. We can use coworker or leader reports to see the change of employees’ behavior.

Third, the emotion variable considered in the research model is positive grieving, which is a transitional emotion after an individual experiences a negative event. We only considered one kind of grieving emotion in the study, and did not take into account the mechanism of other emotional variables such as psychological safety ( Tjosvold et al., 2004 ), so future research should also examine other emotional variables as moderators.

Finally, our research considered the role of “mianzi” and other Eastern cultures in the process of learning from failure in the Chinese culture background. Is it possible that there are other Chinese cultural contextual factors that will affect the relationship between individual cognition and behavior? In recent years, many scholars have put forward some Chinese native cultural concepts such as traditionality and Chaxu climate. Are these factors likely to influence individual’s learning process as boundary variables? Additionally, does Western culture have characteristics similar to Chinese contextual factors, and can the research conclusions on Eastern culture be applied to Western culture? Follow-up scholars can further explore from the aspects of cultural differences and commonalities.

Because failure is a common occurrence in the turbulent world of business, learning from failure is an important research topic. This study validates the effect of a learning goal orientation on learning from failure, and examines the moderating role of positive grieving in the process. We not only enrich the theoretical knowledge of learning from failure, but also provide suggestions on how to promote individual learning after a failure has occurred.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

Author Contributions

WW and SS substantially contributed to the conception and the design of the work as well as in the analysis and interpretation of the data. XC and WY prepared the draft and reviewed it critically. All the authors contributed to the article and approved the submitted version.

This research was supported by MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Grant No. 19YJA630082).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

• ^ This index refers to the moderated mediation effect of the path. If its interval does not contain 0, the moderated mediation effect is significant. What needs to be noted here is the moderator only affects this path.

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Appendix Table 1. Hierarchical regression analysis in Stata.

Appendix Table 2. Hierarchical regression analysis without oscillation orientation.

Keywords : learning from failure, learning goal orientation, loss orientation, restoration orientation, positive grieving

Citation: Wang W, Song S, Chen X and Yuan W (2021) When Learning Goal Orientation Leads to Learning From Failure: The Roles of Negative Emotion Coping Orientation and Positive Grieving. Front. Psychol. 12:608256. doi: 10.3389/fpsyg.2021.608256

Received: 19 September 2020; Accepted: 06 April 2021; Published: 29 April 2021.

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Copyright © 2021 Wang, Song, Chen and Yuan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Wenlong Yuan, [email protected]

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What is a Lesson Objective?

When planning lessons, GOALS  describe the lesson’s summative outcomes (where students will go) and the OBJECTIVES describe how students will get there.

Include SMART attributes when writing objectives:

S-Specific:   Concise, well-defined statements of what students will know, understand, and be able to do at the end of the lesson.  The objective should state  exactly   what is to be accomplished by the student and the conditions in place, such as, “Given a topic on American history”,  “Provided with a calculator and a three minute time limit”, or “Independently, following the five-step scientific method”.

Learning outcomes should be simply stated in student-centered terms.  If students are aware of the intended outcome, then they know where their focus should lie.  This clarity helps decrease anxiety about their ability to succeed and helps build intrinsic motivation.

M-Measurable:   Learning objectives must be quantifiable.  Measurable objectives state the outcomes that can be assessed in definite and specific ways; the quality or level of performance that will be considered acceptable (mastery level).  The criterion can be expressed by describing the performance standard to be met, such as, “Write a descriptive paragraph that includes a topic sentence, three supporting detail sentences, and a closing sentence.”  When writing mastery level, you often begin with the word “with”, then add description, such as “90% accuracy”, “no errors”, “appropriate punctuation” or “accurate vocabulary”.

Start with behavioral verbs (action verbs) that can be observed (either informally or formally) and measured.  Using concrete verbs will help keep your objectives clear and concise. Bloom’s Taxonomy provides a list of such verbs and these are categorized according to the level of achievement at which students should be performing.

While the verbs above clearly distinguish the action that should be performed, there are verbs to avoid when writing a learning objective. The following verbs are too vague or difficult to measure: appreciate, cover, realize, be aware of, familiarize, study, become acquainted with, gain knowledge of, comprehend, know, learn, understand, learn.

A-Attainable:  Learning objectives should be written at the appropriate developmental level for student success.  It is essential that students have the pre-requisite knowledge and skills and that the lesson’s time frame supports achievement of the objective.  You can determine the appropriate level of challenge by referring to pre assessment results.  Learning activities should be challenging, yet offer students a realistic chance to master the objective.

R-Relevant:    The skills or knowledge described must be appropriate for the grade level and subject area or an individual’s IEP goals. The process of setting learning objectives begins with knowing the specific standards, benchmarks, and supporting knowledge students in your school or district are required to learn.  Common Core State Standards and curriculum documents are the source for this information.  This is essential to ensure students receive the same important content from teacher to teacher.

T-Time-bound:   Time-bound – State when students should be able to demonstrate the skill (“By the end of the lesson” , etc.).

Note: As you complete your clinical experiences, it will be expected that written lesson objectives present all of the attributes of a SMART Goal.  You may write more than one lesson objective for a single lesson as a result of grouping your students in response to their needs.  Determination of the need for more than one objective will be the result of your analysis of students’ current performance (formative assessment).

SMART GOAL EXAMPLES

• After reading the book “Life in the Rainforest” and participating in a class discussion, students will accurately identify three specific similarities and three specific differences of plants and animals as demonstrated through written completion of a Venn diagram.
• At the conclusion of this lesson and following class discussion, students will accurately present, in writing or explanation with illustrations, three roles of local government and the responsibilities of each.
• After two lessons on the pattern of digestion, students will accurately identify, in writing, the digestive function of each area of the alimentary digestive system as demonstrated in a student generated labeled diagram.

(Center for Educational Resources – John Hopkins University, The Innovative Instructor Blog-Marcia Hall, July 2016;  Designing Lessons for the Diverse Classroom, Bureau of Instructional Support and Community Services, Division of Public Schools and Community Education, Florida Department of Education)

Additional examples:

• Following this 30 minute lesson, provided with 5 index cards containing two-syllable nonsense words ending with the “consonant-le” syllable pattern, students will correctly read at least 4 of the 5 words without visually marking them.
• By the end of two lessons on bullying, students will correctly explain the difference between a bully and a friend.  Students will have a choice of writing a short paragraph that includes a thesis statement and call to action or providing an oral presentation that includes a thesis statement and call to action.
• At the conclusion of this lesson on measuring volume,  in which students will work in pairs to measure the volume of a cone, sphere, and cylinder, students will individually measure the volume of each correctly.  Students will choose one object of each shape from a variety of everyday objects, correctly identify each shape, and choose the correct formula for measuring as well as label each measurement accurately.

Measurable Objectives in the CPS Lesson Plan

Section 1a calls for a lesson goal/objective, an introductory criteria to lesson planning.  As discussed above, this lesson goal should be written as a SMART goal and clearly articulate what students should know and/or be able to do at the end of the lesson.

In subsequent lessons, this objective will be revised and adapted based on evidenced student progress toward the objective.  In other words, students who master the objective move on to more complex and/or new skills in subsequent lessons.  Others who are unable to demonstrate mastery yet might continue to target this lesson objective in upcoming small group lesson activities that provide remediation and support.

The best lesson objectives require that students utilize higher order/deep thought processes.  Goals that target learning (versus completion) are more likely to be connected to quality learning experiences that stretch students’ thinking, foster self-reflection, and encourage transfer of skills.  Lesson objectives that are learning oriented (EX:  “Students will accurately describe four cause and effect relationships” vs “Students will accurately answer four of five comprehension questions”) focus on the actual skill that the lesson objective targets.

CPS’s Aligned Lesson Plan Section

Cps’s aligned loft evaluation criteria and aligned annotation, cps’s aligned lesson plan rubric criteria,    gsc’s, standards, curricular goals, and iep goal.

As stated above, Common Core State Standards or, as necessary, curriculum documents are referred to when planning lessons.  The lesson objective is the appropriate ‘next step’ in moving towards mastery of a standard or goal.  While more than one standard may be addressed by an objective, identifying one is sufficient.  This must be a standard in the subject area in which the lesson is being taught.  For example, if you are teaching a science lesson, note a science standard you are specifically addressing.

CPS’s Aligned LOFT Evaluation Criteria and Annotations

Essential questions.

State the ‘big understanding’ your lesson is targeting.  Identify the reason this lesson is important in real life, outside of the classroom.  This should be a higher level thinking question that presents the ‘why’ of the lesson.  Essential questions are not answerable with finality in a single lesson or a brief sentence. Their aim is to stimulate   thought , to provoke inquiry , and to spark more questions .

• How do we identify patterns and use them to predict what will happen next?
• When and why should we estimate?
• What are all of the ways to represent a number?
• How does what we measure influence how we measure?
• How can you use equations to solve real-world problems?
• How should governments balance the rights of individuals with the common good?
• How do we overcome prejudice and social bias?
• What is worth fighting for?
• What can we learn from the past?
• What remains the same?
• What strategies can you use to make writing come alive for a reader?
• What do good readers do, especially when they don’t recognize a word?
• How does  what  I am reading influence  how  I should read it?
• What impact does fluency have on comprehension?
• How does word choice affect meaning?
• How do we create, test, and validate a scientific model?
• When and how do scientific theories change?
• How are structure and function related in living things?
• Why are scientists concerned with cause and effect?
• How can we determine what is truly “real” and what is not?

Essential Questions by Jay McTighe & Grant Wiggins, ASCD 2013

Lesson Planning 101 Copyright © 2019 by Deborah Kolling and Kate Shumway-Pitt is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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/images/cornell/logo35pt_cornell_white.svg" alt="learning goals thesis"> Cornell University --> Graduate School

Learning goals.

The maintenance of academic quality resides primarily with graduate field faculty and directors of graduate study, working through the special committee—the group of faculty providing primary advisement and academic oversight for each graduate student. The Graduate School leadership works closely with field faculty in establishing and articulating intended outcomes, objectives, and rubrics through which the aims of graduate education can be met.   Monitoring time-to-degree and other program metrics , and supporting faculty mentoring and student teaching are additional ways in which the Graduate School establishes and uphold standards. 

Faculty assess student performance through a variety of direct and indirect measures, including: 

• Student progress reviews
• Official milestones and special  exams , such as qualifying exams (Q exams), administered early in an academic program; admission to candidacy exams (A exams), which assess breadth and depth in the discipline; and the defense of the thesis or dissertation (B exams)
• Public presentations of scholarly work
• Semesters of  registration  

While intended learning outcomes vary across the many academic programs , a set of overarching goals (listed below) characterize the graduate educational experience. 

Learning Proficiencies for all Graduate Students

• Serve as an ambassador for research and scholarship
• Effectively engage in one’s broader community through various forms of outreach
• Focus on plural contexts and cultures
• Respect research in other areas
• Understand and articulate the impact of research on society

Research Master’s Proficiencies

A candidate for a research master’s degree is expected to demonstrate knowledge in the chosen discipline and to synthesize and create new knowledge, making a contribution to the field in an appropriate timeframe.

• Make a contribution to the scholarship of the field.
• Synthesize existing knowledge, identifying and accessing appropriate resources and other sources of relevant information and critically analyzing and evaluating one’s own findings and those of others
• Apply existing research methodologies, techniques, and technical skills
• Communicate in a style appropriate to the discipline
• Keep abreast of current advances within one’s field and related areas
• Show commitment to personal professional development through engagement in professional societies and other knowledge transfer modes
• Show a commitment to creating an environment that supports learning   through teaching, collaborative inquiry, mentoring, or demonstration
• Adhere to ethical standards in the discipline
• Listen, give, and receive feedback effectively 

Doctoral Proficiencies

A candidate for a doctoral degree is expected to demonstrate mastery of knowledge in the chosen discipline and to synthesize and create new knowledge, making an original and substantial contribution to the discipline in an appropriate timeframe. 

• Think originally and independently to develop concepts and methodologies
• Identify new research opportunities within one’s field
• Master application of existing research methodologies, techniques, and technical skills
• Show commitment to personal professional development through engagement in professional societies, publication, and other knowledge transfer modes
• Show a commitment to creating an environment that supports learning through teaching, collaborative inquiry, mentoring, or demonstration