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Session 4: Climate, Diversity, Inclusion, and Feedback

Lesson Overview

Students and professionals alike in computer science point to climate as a major factor that influences their persistence or departure. Climate refers to the reputation and the norms of a particular organization (organizational climate) or department (departmental climate). 

Within the research literature and popular literature alike, numerous examples have been provided where the climate in many STEM-related disciplines is considered "chilly" or "hostile" for women, people of color, and other underrepresented groups (see, for example, Johnson, 2012).

Learning more about Inclusive pedagogy is considered a way to promote a positive climate, at least within academic realms. Teaching inclusively means you teach in a way that is open, inviting, and encourages participation from a wide range of people (see for example, UNC Chapter). Intentionality needs to be provided to inviting students who may look different from the teacher/peer mentor or from a "prototypical" successful student, and may approach problem-solving or view the world differently from the normative profile (i.e., currently a White male prototype; for more about the prototypes in computer science see Cheryan et al., 2013). 

Indeed, teaching inclusively does not have to exist separately from teaching with rigor, as indicated by the movement toward inclusive excellence" (see

Because peer mentors are on the front lines of feedback and may be viewed as ambassadors of the department, their preparation needs to include a focus on inclusive pedagogy as well as an awareness of how climate affects learning.

Overall Motivations and Objectives

  • To continue to gain competence and confidence in practical code review skills
  • To reflect on their own assumptions and biases
  • To reflect and understand the complexities of diversity, inclusion, and climate it a technical setting and to be able to apply this when interacting with students and providing feedback

Prerequisite Knowledge

To use this module, the following readings, activities, and reflections should be completed:


    Preliminary Activities

    • Activities to be completed prior to this session:
      • Practice Code Review
      • Reflection: Emotional Intelligence and Mentoring Roles

    Instructor Reflections

    Due to its particular focus on inclusion and climate, this session is an excellent time

    for the instructor(s) to take time to reflect on the climate they create in the classroom. In

    order to create an inclusive and welcoming atmosphere for a discussion of diversity, it is

    important to consider how much space you as the instructor take up in the room.

    • What is my definition of "diversity"?

    • What cultural groups do I identify with?

    • How do my experiences working, living, or studying within different cultures affect my practices in the learning context?

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    Lesson Plan


    1. ActivityCompare code reviews in pairs (15 min)
    2. Discussion: Code review experience (20 min)
    3. Activity: Assumptions scenarios (15 min)
    4. Break (5 min)
    5. DiscussionDiversity in Computer Science (1 hr 30 min)
    6. DiscussionInclusion and climate in educational settings and mentor relationships (25 min)
    7. Review Assignments for Next Session
    8. Exit Feedback

    Activity: Compare code reviews in pairs (15 min)


    In pairs, students use this time to discuss their code reviews. They should be instructed to discuss both the technical portion of code review, as well as the process of reviewing code in general. Some prompt questions for them to consider: Did they find something that their partner missed, or vice versa? Did they find the same error, but respond to it in different ways?




    In doing written code reviews before class and discussing the code review process, students are working on the core technical competencies required to be an effective peer mentor.

    Discussion: Code review experience (20 min)


    As a whole class, allow groups to share what they discussed in pairs. Technical questions are likely to arise, so have the code ready to refer to on a projector. Draw the students attention to the ways in which they gave feedback. How might they have given feedback differently if they were meeting this student in person? What types of considerations would they need to make?




    • As reviewed in previous lessons, learners are more apt to identify their own strengths and weaknesses and internalize feedback that helps them to boost their confidence and engage in strategic action when they are able to visualize and articulate the learning process and where they are within it. 
    • Peer mentors need to have practice where they construct feedback and receive feedback, whether using scenarios or in simulation with a peer. In addition, being able to observe and critique feedback as provided by peers can also be an effective strategy.
    • Rather than telling peer mentors a list of do's and don'ts, a key strategy for the peer mentors learning is to also have them engage actively in seeing others and seeing themselves engage in the activity with constructive feedback.

    Activity: Assumptions scenarios (15 min)


    Before beginning this activity, a brief explanation of assumptions is useful. The purpose of this exercise is not to shame people for making assumptions - that's natural - but rather to examine critically the assumptions that we make and prevent them from affecting our behavior towards others. 
    Display a small number of assumption scenarios to the class. Each student should read them, and select one scenario. Students will then create a written reflection of the assumptions they would make in this scenario. When complete, students should reflect on this process of understanding and acknowledging their own assumptions.


    Assumption scenarios can be adjusted to suit the needs of a particular course.

    Example Activity
    Read the introduction to each of the following hypothetical students. Pick one and write the assumptions you find yourself making about that student as a person, as a student in general, and how that student will perform in an introductory level Computer Science class. (We recommend picking the hypothetical student who is inspiring the most or the strongest assumptions in your mind.)
    Note: These are private and will not be collected or shown to the class. Write them in
    whatever way flows most easily: handwritten or typed, list or complete sentences. This is
    just for you so express your thoughts however you want.

    Student A: When you first meet with them, they express anxieties about taking Com-
    puter Science and are clearly concerned that they will be in over their heads. They mention
    that they are an Art History major and have no experience with programming.
    Student B: When you first meet her, she starts telling you about some of her favorite
    programming projects in high school. She makes a point of dropping a few technical terms
    and expressing enthusiasm about studying Computer Science.
    Student C: When you first meet her, she is effusive and scattered. She tells you that
    she is a Frances Perkins Scholar [non-traditional age student] and that she hasn't taken a
    Math class in over 30 years. She says her kids have convinced her that she needs to get
    more familiar with computers. She doesn't seem at all anxious about the class.


    As discussed in the previous activity, there are a variety of ways to engage the peer mentor's. In this case, we discuss sample scenarios of typical students they may encounter (for more about case study approaches, see

    Discussion: Diversity in Computer Science (1 hr 30 min)


    Prior to the session, students have been instructed to select and read and reflect upon at

    least one of the five readings on diversity.

    Have students break themselves into groups based on the reading they selected. They

    should discuss their reflections, in particular:

    • What were the most important points for them?

    • Did they disagree or feel skeptical?

    • How will this be useful or relevant to the MaGE program?

    Once students have had ample opportunity to discuss in small groups (approximately

    15-20 minutes), bring the entire class together for discussion. In turn, each group will tell

    the class what was discussed in their group. Groups should keep in mind that not everyone

    in the class read their reading, so a brief summary may be necessary! Students from other

    groups are encouraged to ask questions.


    Allow the students to guide the discussion, but if discussion stalls possible prompts are:
    • What value does diversity add to computer science as a field? For example, why does it matter if women or people of color participate, or not?
    • Describe different types of diversity, and why diversity of any kind can make a difference to the field.
    • What is the cost (or benefit) to the field, if computer science does not improve its diversity? Why isn’t the status quo advantageous?
    • What are some barriers to diversity in computer science? What kinds of initiatives are being developed to address these? In your assessment, what are the strengths and limitations of different initiatives—and why?
    • Does the classroom environment, instructional approaches, course description/focus, and resources play a role in who participates in computer science? If yes, why and how?


    Peer mentors need to be prepared for their role by talking about the process of learning for students from diverse backgrounds.

    Discussion: Inclusion and climate in educational settings and mentor relationships (25 min)


    One strategy that aligns with inclusive pedagogy is for instructors to think intentionally about how they provide feedback on learning. Feedback, to be effective, needs to be provided to students in ways that inspires students to undertake challenges and continue to engage in their learning. Helpful feedback is specific, informative, formative (rather than purely summative, and focused on the performance (rather than just the outcome) and timely, as well as informative and focused on the process and is future-oriented (formative and performance rather than summative) where possible (see Tanes et al., 2011). Feedback is more helpful when it is encouraging without sugarcoating the problems. Helpful feedback leaves the learner hopeful and with a direction for further action.



    • How does race of the instructor and student (and in particular when the instructor is White) contribute to a potential feeling of mistrust by the student?

    • According to the authors of the Mentor's Dilemma, why does buffered or wise feedback contribute to motivation to revise? What element does buffered feedback contain that other forms of feedback sometimes miss?

    • Why does it matter how an instructor delivers feedback? Isn’t honesty the best policy?

    • How does race of the advisor and student (and in particular when the advisor is White) contribute to the possibility of different feedback for students based on race? Or put another way, why would an advisor hold back negative feedback from a student?

    • What is the potential harm to students who fail to receive critical feedback (when it is warranted)?

    • What options does an advisor have in this situation? What kinds of strategies might help both parties to contribute to a successful communication?


    To understand how to provide effective feedback (in written and spoken form), with an awareness of teacher and student social identity/climate.


    Common Issues

    • When doing pair exercises such as Comparing Code Reviews, you may wish to create the pairs ahead of time for a variety of reasons. Particularly when technical competence is a factor, we found it beneficial to pair students further into the CS curriculum with the less senior students.
    • The discussions in the session are open ended and may run longer than expected.


    For Students
    • Discussing First Code Review Assignment
      • Don't be afraid to get things wrong. This was for practice so that you could learn from any mistakes you made.
    • Recording Mock-1on-1 Meetings
      • It’s a very awkward experience, but it’s very helpful.
    • Watching your own Mock 1-on-1 video and writing a reflection
      • Try to look at the big picture.
      • Treat this more like a blog post and less like an assignment.
    • Exit Feedback
      • Be honest and self-reflective, don’t worry about giving the responses you think the instructors want to hear.

    Assessment, Debrief, and Looking Ahead


    For each session, two types of feedback are collected.
    • First, anonymous feedback collected immediately at the end of the session. While this may be done in any form, we chose to use simple index cards passed out at the end of the class deposited anonymously at the classroom exit as the students left. The benefit of this form of feedback is its immediacy - thoughts and feelings relating to the session are fresh in the students' minds. Students were instructed to write anything they felt like - or nothing at all.
    • The second type of feedback was an Exit Feedback Google Form which the students were asked to complete before Midnight on the day of the session. Sample Exit Feedback Form.


    Students should complete the Reflection: Diversity, Inclusion, Candid Feedback, and Climate by writing answers to the following prompts:
    • What did I learn about my own views of what it means to be an inclusive teacher/peer mentor?
    • What did I learn about my self-efficacy to give feedback in written form in a buffered manner?
    • What did I learn about my self-efficacy to give candid spoken feedback in a way that could be perceived as constructive?
    • What did I learn today that will be useful when I am a peer mentor?
    • What might I need to invest in or work on to be effective as a peer mentor?
    • What did I learn about our group as a peer mentors from this session?

    Looking Ahead

    In preparation for the next session on Active Learning students should read:

    Students should also complete:
    • Practice Code Review
    • Record Mock 1-on-1 Videos

    Supplemental Reading

    Tanes, Z., Arnold, K. E., King, A. S., Remnet, M. A. (2011). Using Signals for appropriate feedback: Perceptions and practices. Computers & Education, 57, 2414-2422.

    This article helps to explain different kinds of feedback, including motivational vs.

    informative, formative vs. summative, and performance vs. outcome.

    Cheryan, S. Drury, B. J., & Vichayapai, M. (2013). Enduring influence of stereotypical computer science role models on women's academic aspirations. Psychology of Women Quarterly, 37(1), 72-79.

    Explains how stereotype activation negatively influences women's interests in computer science.

    Cohen, G. L., Steele, C. M., & Ross, L. D. (1999). The mentor's dilemma: Providing critical feedback across the racial divide. Personality and Social Psychology Bulletin, 25, 1302?1318.

    Explains that giving critical feedback across the racial divide can be challenging because of mistrust of the instructor's motive. Students may wonder: is this feedback because of my work or because of my race? The researchers document the benefits of combining specific candid feedback about the work's limitations with a reassurance of reaching a higher standard (and strategies to get there). This buffered approach to giving feedback, also called wise mentoring, may be especially important for underrepresented students.

    Constantine M. G., & Sue, D. W. (2007). Perceptions of racial microaggressions among black supervisees in cross-racial dyads. Journal of Counseling Psychology, 54(2), 142-153.

    Student trainees' reports of stereotyping and microaggressions from their clinical


    Crosby, J.R., & Monin, B. (2007). Failure to warn: The eect of race on warnings of potential academic diculty. Journal of Experimental Social Psychology, 43, 663-670.

    Advisors may fail to warn black advisees of a course overload for fear of looking racist.

    Johnson, D. R. (2012). Campus racial climate perceptions and overall sense of belonging among racially diverse women in STEM majors. Journal of College Student Development, 53(2), 336-346.

    Discusses how the campus attitudes toward racial diversity can contribute to belongingness and persistence of diverse women in STEM.

    Tobias, S. (1994). They're not dumb, they're different: Stalking the second tier. Arizona: Research Corporation.

    This short inexpensive book documents case studies of learners who were asked to seriously audit STEM classes and explain what their experiences were. The case studies clearly illustrate why the climate of the classroom can be off-putting to students with talent to contribute when they find the environment does not motivate them or leverage their strengths. Choosing one case study (Vicky) can be helpful for peer mentors who might not identify with or empathize with students who leave STEM and may assume they leave because they cannot handle the rigor.

    University of North Carolina-Chapel Hill's Center for Teaching and Learning. (1997). Strategies for Inclusive Teaching. (Chapter 2). From Teaching for Inclusion: Diversity in the College Classroom.

    A very useful chapter that denes inclusive teaching and explains how to support

    underrepresented students without singling out or stereotyping.

    Heather Pon-Barry,
    Jun 16, 2016, 10:17 PM