CSC 130: Data Structures and Algorithms

Coverage, Acceptance, Attempt

Reflection on Instructional Change:

One practice from the ACUE Gen AI course that I implemented was "Empowering Students to Use AI Responsibly." In my CSC 130 Data Structures and Algorithms class, specifically during our lectures on runtime analysis in the second week, I modeled how to use prompts on ChatGPT to answer complex questions. I demonstrated how altering the parameters and phrasing of a question could yield different responses from the AI. The steps involved presenting a standard question, then modifying it slightly to observe changes in the output. I took these steps to highlight the importance of precision in communication and to show how critical thinking is essential when interpreting AI-generated information.

Implementing this practice had a noticeable impact on my teaching and on student engagement. The students were intrigued—and even shocked—to see the variability in responses from different GPT models based on how the questions were asked. This led them to be more mindful of how they formulate questions, not just with AI but in their studies overall. One student exclaimed, "I couldn't believe that changing just a few words in my question completely changed the answer I got!" This exercise fostered a deeper understanding of the subject matter and encouraged them to critically assess the information they receive.

The FLC activity that most influenced changes in my instruction was the "Writing Effective Prompts: Discussion and Reflection." This activity underscored the significance of clear and precise language when interacting with AI tools. It was influential because it provided practical strategies that I could bring directly into the classroom to help students improve their own prompt-writing skills, thereby enhancing their learning experience with AI.

Participating in the "Observe and Analyze Session" with my colleagues offered an invaluable "aha moment." I realized that the clarity of my directions greatly affects student outcomes. By ensuring my instructions were explicit and unambiguous, I noticed increased engagement and better comprehension during class activities involving AI. This reinforced the idea that effective communication is key to successful teaching and learning.

Evidence of Instructional Change

evidence of instructional change
Programming assignment using GenAI	Student working with ChatGPT on an assignment	I completed all badges.

Practice and Reflect Teaching and Learning with AI:

The ACUE course on integrating AI has brought meaningful changes to my teaching methods, particularly in my CSC 130 Data Structures and Algorithms class. One benefit of using AI is that it makes challenging concepts, like runtime analysis, more approachable for students. For instance, I’ve used AI tools during class to explore multiple ways of understanding algorithms, which has helped students see problems from different angles. A key challenge, however, has been ensuring students remain active problem-solvers rather than simply relying on AI-generated answers. To address this, I’ve designed activities that require students to test and refine the outputs they receive, encouraging a more hands-on and critical approach.

One specific AI tool I’ve introduced is ChatGPT. In our discussions on runtime analysis, I showed students how small changes in the phrasing of a question can lead to significantly different outcomes. This exercise opened their eyes to how much precision and context matter when tackling technical problems. As a result, students have become more thoughtful in their approach, often questioning the validity of the information they encounter. One student noted, “It’s surprising how easily a poorly written question can lead to misleading results—I’ve started paying much more attention to how I ask things now.”

Course Syllabus

CSC_130_Syllabus (2).pdf

Faculty Bio

faculty bio
	Anna Baynes is an Associate Professor in the Computer Science Department at Sacramento State. She teaches CSC 130, CSC 131, CSC 173, CSC 177, CSC 180, and CSC 238. She also participates in Computer Science Education Research.

Funding
	This work was supported by: US Department of Education Hispanic Serving Institution Project TECH4Equity US Department of Education Hispanic Serving Institution Project STEM4Equity P031C210012 *Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation or the US Department of Education.