Categories: GSI Online Library, Teaching Effectiveness Award Essays
By Xueqin Lin, School of Education
Teaching Effectiveness Award Essay, 2025
One of the challenges I encountered while teaching lab sessions for EDUC 293A: Data Analysis in Education Research in Fall 2025 was supporting students struggling with statistical software, particularly Stata. One student, who had no prior experience with quantitative data analysis, faced significant difficulties with data cleaning and visualization, leading to poor performance on her first lab assignment. Her anxiety about using Stata not only hindered her ability to complete assignments but also affected her overall confidence in the course. Recognizing that this was a common challenge, I sought to make learning more accessible and reduce the cognitive load associated with complex statistical concepts.
To address this issue, I implemented a multi-faceted approach to improve comprehension and engagement. First, I adjusted my instructional design by incorporating multiple representations of information. I minimized text on slides and used visual tools such as normal distribution plots to illustrate statistical concepts dynamically. I also created a decision tree to help students determine which statistical tests to use under different conditions. When demonstrating Stata syntax, I provided clear explanations of command functions, ensuring students understood their purpose rather than memorizing steps mechanically.
Beyond instructional enhancements, I offered individualized support tailored to students’ needs. I regularly checked in with students during lab sessions and monitored their performance on homework and assignments. For the struggling student, I scheduled an office hour to provide step-by-step guidance on data cleaning and preliminary analysis while allowing space for independent practice. Additionally, I created a Stata commands cheat sheet for all students to reduce reliance on rote memorization and foster problem-solving skills. To further boost students’ confidence in data analysis and make the analysis more meaningful, I encouraged them to submit their final course projects to the American Psychological Association (APA) Convention, an international conference in psychology.
To assess the effectiveness of these strategies, I gathered both formal and informal feedback. Students in my lab sessions completed a mid-term evaluation assessing their confidence in understanding and applying statistical concepts across eight key areas covered in the course. This allowed me to identify their strengths and areas for growth. Additionally, I engaged in informal conversations with students before class and during breaks to gather real-time feedback on specific activities, allowing me to address concerns promptly. The struggling student showed marked improvement, as reflected in higher lab grades and increased confidence. Their feedback reinforced the impact of these changes: “The lab is absolutely great. XXX is really doing a great job and puts a lot of effort into making sure that everybody understands the topics!” More broadly, students engaged more actively with Stata, and their improved performance on lab assignments indicated a deeper understanding of statistical analysis. Notably, two students’ poster proposals based on their final projects were accepted for presentation at the 2025 APA Convention.
This experience reinforced my commitment to designing inclusive, student-centered learning experiences. By integrating visual aids, scaffolding instruction, and providing personalized support, I was able to enhance student engagement and confidence in mastering statistical tools—an approach I continue to refine in my teaching.