Students are humans.

Students are not brains on sticks. When I first began teaching, I missed this. I focused so much on crafting perfect explanations and was dismayed when students didn’t learn well. I responded by studying cognitive psychology to understand why learning is difficult. This knowledge improved my teaching, but was also inadequate, addressing my students’ cognition but not the rest of their being. Students come to my courses with complex and varied motivations, experiences, and knowledge all contextualized by history, politics, and culture. I’ve since become a student of organizational psychology, sociology, counseling psychology, and history. I’m beginning to understand the systemic factors that give some students a head start and keep others shackled at the starting line. I’ve started to scratch the surface of how things like cultural narratives and social media can paralyze students with fears of inadequacy and drive them away from a field where they could thrive. I am cultivating what I hope is a holistic teaching philosophy that embraces the needs of all my students.

Designing for cognition

When I started graduate school, I bought a pair of black Burberry glasses. Shortly thereafter, I noticed several of my friends had the exact same pair. They already wore those glasses, but I’d never noticed because those glasses were not previously important to me. Dual Process Theory posits that we have two cognitive systems: a fast, automated, intuitive system (system 1) and a slow, conscious system (system 2). We typically teach to system 2 cognition when presenting information, but system 1 can render these efforts fruitless. Because we are constantly bombarded by information, our system 1 cognition instantly and undetectably tosses out enormous amounts of information that it doesn’t perceive as important (like my friends’ choice in glasses). System 1 is also essential for high-level expert performance, allowing us to automatically complete cognitively demanding tasks, like deploying correct syntax when programming or intuitively knowing where a bug is in our code. Our students’ system 1 cognition readily discards important new information, because their experience, culture, and motivations do not value that information, despite their desire to learn. To help students experience new information as important and develop expert-like intuition, I design my courses to engage students in active practice with feedback and spaced repetition.

I design sequences of activities that require students to put their knowledge and skills into action. Before coming to class in CS 233 Computer Architecture, students watch short video lectures and then complete a short, autograded assignment. Then in class, students solve problems on the same material in a group with their peers. These assignments require students to use their knowledge in many ways, explaining their reasoning to peers, answering autograded questions, and wrestling with reflection questions that ask them why a solution was sufficient or how concepts interact. These multi-modality activities are critical for helping students develop robust knowledge and the ability to use it flexibly. Students then engage the same material yet again after class through short homework assignments and longer lab assignments. I try to directly build on knowledge from one module to the next. If not possible, I assign short exercises late in the semester to remind students of content from earlier in the course. The possibility of success or failure, the immediate feedback, the minimal points, and the repeated exercises on the same content all help students’ bodies and minds experience the information as important and give them enough practice to begin automating their use of knowledge to achieve higher-level performance.

I reinforce these practices with how I interact with students in the classroom and how I design individual learning activities. When students ask questions, I only provide hints or respond with questions to help students remember what they need to know on their own. I likewise design my assessments assuming that students will not (and cannot) remember all of the information I provided in a video lecture. I provide brief recaps of important content knowledge within the question prompt when needed or I provide callout boxes that alert students to common mistakes (e.g., “Don’t forget to consider your data’s type!”). In other words, I try to provide the information that students have forgotten at just the moment when they are sensing that that information is important.

Designing for humans

While learning is challenging in the best of situations, it can become so much more difficult for our students due to the myriad pressures and challenges that they face beyond the course content.

Students are juggling multiple courses that all have different policies and conflicting deadlines (not to mention jobs and extra-curriculars). To help students manage their time, I design my class to have a clear rhythm with the same assignments and activities due every week so that students can just rely on habits to meet course deadlines. The comment, “this class is easily one of the best structured classes I’ve taken,” is representative of the most common feedback I get on student evaluations. I also use flexible deadlines to help better manage their multitude of responsibilities. For example, students can earn up to 80% credit on low-stakes, autograded homework assignments after the deadline. For higher-stakes assessments, students are given one no-questions-asked extension to use at their discretion. They can request additional extensions but must meet with me so that I can learn how they’re managing their time and help them find solutions for the pressures or difficulties that are derailing them.

I design my courses with my students’ mental and emotional health in mind. While some stress is needed to trigger deeper learning, too much stress makes learning impossible. Rather than having a few high-stakes exams, I use many lower stakes quizzes to minimize test anxiety. I also provide students with a second chance on quizzes for when they perform poorly. These techniques make stress more manageable and also reinforce active learning with spaced repetition in their learning.

I also share about my own struggles with mental health and frequently remind students about the accommodations we provide. The use of frequent assessments and course rhythms helps me detect when students are struggling. For example, students who are struggling with their emotional health during my class frequently start by missing deadlines for the labs and then missing quizzes and then homework assignments. By monitoring when students miss multiple deadlines, I have been better able to reach out to students before they enter a freefall and get them the help and accommodations they need. I know that these little actions of reaching out to students matter based on the feedback they provide, such as the following comment I received on an evaluation: “The fact you actually went out of your way to contact me to sort something out speaks volumes that are not lost on me. Perhaps I’ve grown somewhat jaded with what to expect in regard to instructor leniency, but it really was a shock to have an agreeable solution from someone who obviously cares.”

Our courses are steeped in historical injustices and cultural norms that lead many students, especially students from historically underrepresented groups, to believe that they don’t belong or that they are somehow uniquely “not good” at CS. These beliefs create additional burdens that even the best students from these groups must carry, distracting from their learning and hindering their efforts to grow into the field.

I use collaborative learning for my in-class activities to fight these historic injustices. We require all students in CS 233 to rotate group members for the first couple weeks of the semester so that isolated students have a chance to network and build their social capital and find study partners. When we need to assign students to teams, we make sure that students from minoritized groups are not isolated on their teams but get to see other minoritized students in CS and normalize their own presence. I also focus on hiring students from underrepresented groups to my course staff to help student teams during class and further increase their visible representation in my classroom. Collaborative learning also provides a context where students feel that they are not alone in their struggles to learn but instead build connections with others through shared struggles. The use of collaborative learning also gives me the freedom to devote more of my attention and energy to students who are struggling. When helping teams during class, I normalize failure and struggle by always reinforcing that each team had a question or made a mistake that I had seen other teams have and that groups were not alone in their struggles. I essentially get to give 8 hours of individualized attention to students every week, even in a class of 400.

The switch to collaborative learning is leveling the playing field for women in my course. My research team administered a Sense of Belonging survey at the start and end of the semester and found that women still enter my course with a lower sense of belonging than men, they leave the course with a comparable sense of belonging as the men (who also increased their sense of belonging). Likewise, there is now no longer a gender-based gap in student performance in CS 233, which had existed for 15 years prior (Herman and Azad, 2020; Tomkin, West, Herman, 2018). These improvements in gender equity have persisted, suggesting that the course structures and policies are making a difference.

I also understand that many students have social anxiety, ADHD, or other individual differences that make the chaotic and loud environment of collaborative learning detrimental to their learning and well-being. I provide a built-in opt-out policy and structures that let these students complete learning activities outside the classroom and use an online queuing system so they can receive the help they need. As I continue to improve my teaching, I want to continue focusing on implementing policies and procedures that help my course become increasingly welcoming and accessible for all.

In the near future, I plan to improve the accessibility of my course for students with physical disabilities and non-native English speakers, by writing an e-text to better support these students. One particular challenge for this endeavor is that my course relies heavily on complex circuit diagrams that are not accessible. I am exploring new collaborations with faculty from the School of Information Sciences to create screen-reader-compatible, web-based circuit diagrams.

I am also exploring more ways to amplify students’ voices and perspectives in my courses. I have started identifying students in my classes who ask great questions, especially those from groups traditionally underrepresented in computing. I invite these students to record podcast-style videos where the students interview me about course content to complement or replace my old video lectures. My hope is that these podcasts will normalize students asking questions and that these questions will prime students to detect what is important in the content that they might otherwise have missed.

I am committed to continuing to learn as a teacher and grow as a person so that I can better dignify and humanize my students, caring for their whole persons and not just their learning outcomes.