On the Other Side of the Classroom

I have started taking classes again for a Master’s degree in Psychology. This area has always interested me, and, I can learn new ways to manipulate my students into studying well! On a serious note, ever since acquiring that Coursera certificate on Learning How to Learn, the only MOOC course I ever completed, I have grown fond of cognitive science. Taking advantage of my education benefit, I decided that pursuing a formal degree in Psychology would be beneficial for me. The course that I am taking this semester, Cognitive Psychology, so far has proven me to be correct. Halfway through this semester, I want to write this reflection essay to summarize what I have learned so far.

At this point in the semester, the class has covered 8 lectures. They include introductory concepts of cognitive science, perception, attention, short-term/working memory, long-term memory structures, and long-term memory processes. I have completed 8 quizzes, 6 Cog Labs, 1 progress reflection, and 6 Hypothesis readings. My grade is at a solid 88.75%, and I am also banking on several low grades being dropped, as per the syllabus.

Pedagogical Practices: Learning from Another Professor

At West Chester University, we have the opportunity to sit in and observe other professors’ classes as part of their evaluation process. On these occasions, we can glimpse into one’s teaching techniques, but only barely scratch the surface.

My first lesson is the structural design of the course itself on D2L, the university’s LMS. I am not unfamiliar with Dr. M’s course design, as I have had the privilege of co-teaching an introductory class for incoming undergraduate students with her. This class I am taking has the same level of detailed design as the other introductory class. I was not particularly impressed with this design back then, but my student perspective has now allowed me to appreciate this approach more. Everything is enclosed within and supported by D2L’s builtin functionalities in an easy-to-reach manner. I have grown to appreciate these details, as I always know exactly what needs to be done next for the class. On the other hand, my approach is to host all teaching materials on a GitHub Page and provide linkage only through D2L. When comparing the two approaches (using my own perspective), mine gives me more freedom and convenience in designing my lectures with the tools I like, but students also have to step away from their familiar LMS to reach these contents without much support and reminders. In the future, I would adapt a less detailed version of Dr. M’s course design to help anchor my external lecture notes closer to D2L.

My second lesson is the utilization of Kahoot. I have always thought of clickers, and by extension, Kahoot, are rather simplistic tools that are used only in introductory classes. Seeing Kahoot being used extensively in this senior-level course as a multiple purpose tool to take attendance, check whether students did the before-class reading, and provide review opportunities is eye-opening. I can certainly do this via D2L’s quizzes, but the interface is clunky and mostly likely require students to have their laptop out. I certainly will gradually integrate Kahoot into my own class workflow going forward.

And finally, the Hypothesis tool where students read and comment on the same article. I absolutely love this. I wished I had had this when I was teaching the Computer Science seminar course that had students reading a dozen papers over the semester. I will utilize this tool in a slightly different manner. Since all my courses use open source textbook, I will have students read and comment on the chapter to be discussed next. Combined with Kahoot, this shows potential to organically bring the class-flipping model to my courses.

Going back to my initial perspective on peer observation, perhaps it allows you to see teaching, but becoming a student allows you to experience its cumulative effects. While I am aware that peer observation is primarily used for evaluation at my university, one can learn so much more about fellow professors’ craft by experiencing their teaching from a student’s perspective.

Pedagogical Foundations: Understanding How Students Learn

I did start my degree program with a motivation: how to manipulate my students better! Some lectures of this class either remind me of what I have suspected (e.g. students who are good at typing are likely to learn in class better as they don’t have to expend as much cognitive resource to take note?) or give me ideas about what to change in how to design my own materials (carve out time at the end for a short immediate recall practice to help consolidate long-term memory?). Others have given me much to think about.

For example, the lecture on Perception, while seemingly focused on recognizing, organizing, and interpreting information from senses, made me think about how students would perceive and process information in solving a problem. When reflecting intentionally, I have often caught myself flipping between bottom-up processing and top-down processing as I solve a programming problem. In other words, I zoom in, do something, then zoom out and look at the big picture. How can we train students to zoom in/out quicker or are we limited to practice a lot to get better?

The lecture on Attention makes me think about what can I do to capture and retain students’ attention so that they can stay focus on the relevant information better. How should I divide my 50-minute class into sections (and account for the overhead) so that students do not get bored (or professionally speaking, hit their capacity and duration limits?). Perhaps a 5-minute Kahoot on review/reading assignment, 10-minute lecture, 10-minute hands-on, another 10/10, then a final 5-minute Kahoot recall? On the other hand, is there anything I can do to train the students to improve these capacities.

All of these findings are very interesting, and I have only been through half of the semester of a first course in Psychology (my Introduction to Psychology taken in 2003 as a gen-ed does not count!).

Interdisciplinary Impact: New Connections and Research Directions

I had a student, M.B., who dual majored in Computer Science and Psychology. I didn’t think much about this combination then, as I saw psychology at that time was more about psychiatry and therapy. When I first decide to pursue the MS in Psychology degree, it was for better understanding cognitive processes and their impact on learning.

In the first lecture, when Dr. M talked about mental processes in cognitive functions, information these processes act upon, and the corresponding mental representations, the immediate analogy that popped into my head was the relationship between a program and a process (of that running program). The accompanying Hypothesis reading, Why the modern world is bad for your brain by Daniel J. Levitin, talked about the problems with multi-tasking, which definitely echo the issues of context switching overhead when a fixed number of CPUs have to handle an infinite amount of processes.

When the lecture on Perception mentioned geons in the Recognition-by-Components theory or how the interpretation of blob in blurry images depending on the environmental context, I can see the corresponding analogy of machine learning’ image processing techniques where complex images are transformed into matrices. Various segments of these matrices, through mathematical processes, can be mapped to known templates (label) for interpretation and recognition purposes. The top-down theories, through Helmholtz’s Theory of Unconscious Transference or Gestalt’s Principles of Perceptual Organization, carry the taste of Deep Learning and Clustering, to name a few.

The lectures on short-term and long-term memory provided extremely interesting perspective regarding the relationship (or situationship?) between human memory and large language models (LLM). I am leaning toward the idea that LLMs are somewhat similar to the concept of semantic memory. Perhaps an added component representing episodic memory would help improving LLMs capability, allowing users (not the big companies) to construct and improve their own AIs without having to retrain these AIs using massive data centers. I was excited to discover that a recent peer-reviewed work, Human-Inspired Episodic Memory for Infinite Context LLM published in ICLR 2025, explores a similar direction. This makes the idea particularly promising for me and my research lab.

Beyond the Classroom: Rethinking Advising and General Education

Back when I was an undergraduate, I did take my general education classes to expand my horizon. From Music Theories, Introduction to Psychology, to Organizational Behavior, I took those courses because I felt that those courses would be useful. Taking Cognitive Psychology now, I definitely, positively, confirmed that interdisciplinary knowledge is tremendously useful. However, I arrive at this conclusion with the benefit of a 25-year hindsight and experience.

Should we consider this approach when advise early year students? Perhaps they should spend the majority of their efforts in their first two years on their own majors, and only after that, start considering general education courses. I am not talking about introductory writing or speaking emphasis classes, but I am talking about natural and social sciences and the humanities. Having some knowledge of one’s discipline perhaps would allow one to better appreciate the perspective of another. Furthermore, in-depth domain knowledge will help students to get into an applied mindset faster (how would my field relate/apply to this new field), and from the memory lectures of Cognitive Psychology, this can make students learn better in these general education classes.

The counter argument to my own suggestion is that the early general education courses also contribute toward students’ own early development. Maybe they did not pick a fitting discipline from the beginning, and these general education classes would help them find their direction. To that end, perhaps there are two purposes of general education courses: those for exploration and those for interdisciplinary integration. My successes so far with Cognitive Psychology was definitely an example of interdisciplinary integration. The practical take away message for me, as an advisor, is to explain the difference between these two types for students and have them take full advantage of the options.