My teaching goals for the Fall 2021 semester included:
- Teach the ITCS 3162 class (Introduction to Data Mining)
- Continue developing my personal website and teaching portfolio
- Attend two CTL (Center for Teaching and Learning) Seminars
In my previous report, I mentioned how explaining the course material to students helped increase my own understanding and confidence. Even though I was viewed as the sole instructor this semester, this learning has not stopped, and probably never will. There were still many moments of uncertainty, but I also know now that uncertainty is OK and I have the resources to try to find the answers.
For my other two goals, I have continued making edits to my personal website. Updates have been made to the teaching experience, service, and research pages.
For the seminars, I attended the following:
- Reimagining Learning Materials: “This Active Learning Academy Workshop is presented to you by Pilar Zuber (Public Health Sciences) and Deborah Beete (Public Health Sciences). This interactive workshop examines the types of learning materials used in courses. It addresses the use of alternative learning materials vs traditional academic learning materials as well as how the utilization of non-traditional materials may extend before, during and after class meetings. Application of strategies will be discussed within the context of different learning levels and course types.“
- Improving Student Engagement: Increasing Attendance and Effective Time Management: “This Active Learning Academy workshop is presented by Matt Metzgar (Economics), Monika Sawhney (Public Health Sciences), and Mary Ellen Muesing (Writing, Rhetoric, and Digital Studies). Many instructors created online lectures and resources during our virtual learning time. With these additional resources available, class attendance may suffer and students may become overwhelmed with the variety of different learning paths. In this workshop, we will explore how online resources affect these outcomes. We will present strategies to increase in-class attendance and help students manage time and resources effectively.“
In the rest of this report, I will focus on reflecting on my teaching experience this semester.
Teach ITCS 3162 (Intro to Data Mining)
Education is not the filling of a pot but the lighting of a fire.
W. B. Yeats
Being the sole instructor was honestly terrifying, especially during that first week of the semester. But as I got to know the twelve students in my class, I got much more comfortable and genuinely enjoyed the experience.
When first planning for the class, I had the goal of student-centered learning in mind. I wanted to find ways to help motivate students by learning about their own goals and interests with the course. Why are they here? And how can I help them remember those reasons? How can I give them the flexibility to really focus on their individual interests and inspire them to dig deeper?
“…In the student-centered classroom, the roles of the roles of teacher and student of necessity change so that the teacher changes from the ‘sage on the stage’ to the ‘guide on the side’ who views the students not as empty vessels to be filled with knowledge but as seekers to be guided along their intellectual developmental journey.” (Wright, 2011)
I wrote my teaching philosophy in 2019 when I still only had experience with being a teaching assistant. And yet, it seems my goals have largely remained the same. This semester, I was also in a GRAD 8000 (Leadership Essentials) course hoping it would help give me the skills and practice needed for teaching. In this class, we took a career questionnaire giving us insights into our own motivations and what moves us. Part of my results (attached below) showed the importance of taking on inspiring roles and bringing meaning (to the classroom, in this case). I felt like this also aligned with my teaching philosophy. These motivations will be something for me to keep in mind as I progress throughout my career.
Course Structure
“The key objectives of this course are two-fold: (1) to teach the basic concepts of data mining and (2) to provide extensive hands-on experience in applying the concepts to real-world business applications. Topics include: Data Collection, Data Preprocessing, Data Exploration, Feature Engineering, Prediction Model, Clustering, Association Analysis, Graph/Network Analysis, Text Mining and Social Media Analysis, and Anomaly Detection.” (Banner Course Description)
I created the course syllabus (downloadable below) to follow the topics listed in the course description.
The course was centered around students building up their own portfolios in order to provide that hands-on experience. I had read previously that students’ motivation is improved when they can make connections between the current course material and their future goals, such as careers. On the very first day, I discussed with them my teaching philosophy and student-centered learning. Then I introduced the portfolios as both a method for project-based learning and applying the concepts they will learn in class, as well as something they could then take with them even after the class ended (such as to keep building it up and potentially using it in future interviews). Here is an example student portfolio (sharing with permission from the student).
Each week, students had a discussion prompt to respond to as preparation for the class. I would also provide initial resources to guide students in the right direction while also encouraging them to include any resources they find on their own. Discussions were set up on Campuswire, a class platform for discussion boards, chat rooms, and virtual rooms (for calls). Prompts included questions such as “what are association rules” or “explain how k-means clustering works.” Again, this was to encourage students to start learning about the material before the more in-depth classroom discussions.
In the classroom, I would then provide additional material. This would include more in-depth lectures on the topic, demoing bits of Python code, providing a coding activity for students to follow using Jupyter notebooks, walking through the problems on the board, and having students also work out problems as groups on the whiteboards around the room. I feel like very early on, I ended up spending much more time lecturing than I thought and hoped I would. Over time, I was able to adjust to provide the students themselves more time to work through activities (both code and problems on the board).
Reflection
While going through the course and after receiving student feedback, I would like to reflect on what changes I can make in the upcoming semester. Since my class only had 12 students and the upcoming semester (currently) has 63 students, I will need to think about what else I may need to do to adapt to the larger class size. Lastly, since I now have TAs (very exciting!), I will also need to learn how to lead the group.
Based on the end-of-semester feedback, most students seemed to think positively of the course. Students seemed to appreciate the portfolios and the freedom given to be creative in applying the knowledge learned in class in ways that interested them and fit with their own career goals. One student also stated that the content was accessible to those completely new to the material but complex enough to engage those with existing experience. I was glad to hear this as I had wondered how to make the course content beneficial to students from such a wide range of experiences.
As I was going through the course, I wondered about having more frequent but low-stake forms of assessment. The class activities (such as working problems out on the board) allowed me to see how groups were doing with the material, and the portfolios were a way to see students apply the knowledge more practically. However, I wasn’t always sure if each individual student was fully grasping more of the theory (e.g., how the algorithms worked). At one point, I tried using Kahoot to provide questions in an engaging way. However, I think something like this but more consistent would be beneficial. Multiple students suggested possibly using short quizzes to reinforce learning, so I will work on adding these to the upcoming semester.
The reason I would also like to make the quizzes more low-stakes is to emphasize the importance of learning rather than grades. I believe the quizzes should be used for reinforcing learning that students are already doing, rather than being the incentive itself. Here is an article discussing the concept of “ungrading” that I will periodically come back to as I continuously reflect on my teaching.
References
Wright, Gloria Brown. “Student-centered learning in higher education.” International Journal of Teaching and Learning in Higher Education 23.1 (2011): 92-97.
Stommel, Jesse. “Grades are Dehumanizing; Ungrading is No Simple Solution.” June (2021). Website.
Aileen Benedict 
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