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Aadarsh Padiyath

Publications and source records attributed to Aadarsh Padiyath.

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Self-Regulated Personal Contracts as a Harm Reduction Approach to Generative AI in Undergraduate Programming Education

Students learning programming exercise agency in deciding when and how to use GenAI tools like ChatGPT. However, this agency is often implicit and shaped by deadline pressure and peer behavior rather than explicit and conscious learning goals. We designed a GenAI Contract grounded in harm reduction and self-regulated learning theory to scaffold intentional decision-making: students articulated personal learning goals, created usage guidelines, and reflected on alignment at strategic points across an eleven-week semester. The contract was non-binding and graded only for completion, emphasizing self-awareness over enforcement. We implemented this with N=217 students in an intermediate Python course. For students still forming their relationship with GenAI, it worked, as 58% of students reported the intervention changing their thinking and created helpful accountability structures. However, awareness did not always translate to sustained behavior change. Some students who valued their guidelines still abandoned them under various pressures. Maintaining guidelines required constant self-control across hundreds of decisions, while using GenAI freely requires none. Many students could not sustain this burden despite this self-awareness. We discuss supporting student agency when GenAI tools and learning goals create tension.

cs.CY

Validation of the Critical Reflection and Agency in Computing Index: Do Computing Ethics Courses Make a Difference?

Computing ethics education aims to develop students' critical reflection and agency. We need validated ways to measure whether our efforts succeed. Through two survey administrations (N=474, N=464) with computing students and professionals, we provide evidence for the validity of the Critical Reflection and Agency in Computing Index. Our psychometric analyses demonstrate distinct dimensions of ethical development and show strong reliability and construct validity. Participants who completed computing ethics courses showed higher scores in some dimensions of ethical reflection and agency, but they also exhibited stronger techno-solutionist beliefs, highlighting a challenge in current pedagogy. This validated instrument enables systematic measurement of how computing students develop critical consciousness, allowing educators to better understand how to prepare computing professionals to tackle ethical challenges in their work.

cs.CY

Development of the Critical Reflection and Agency in Computing Index

As computing's societal impact grows, so does the need for computing students to recognize and address the ethical and sociotechnical implications of their work. While there are efforts to integrate ethics into computing curricula, we lack a standardized tool to measure those efforts, specifically, students' attitudes towards ethical reflection and their ability to effect change. This paper introduces the novel framework of Critically Conscious Computing and reports on the development and content validation of the Critical Reflection and Agency in Computing Index, a novel instrument designed to assess undergraduate computing students' attitudes towards practicing critically conscious computing. The resulting index is a theoretically grounded, expert-reviewed tool to support research and practice in computing ethics education. This enables researchers and educators to gain insights into students' perspectives, inform the design of targeted ethics interventions, and measure the effectiveness of computing ethics education initiatives.

cs.CY

Insights from Social Shaping Theory: The Appropriation of Large Language Models in an Undergraduate Programming Course

The capability of large language models (LLMs) to generate, debug, and explain code has sparked the interest of researchers and educators in undergraduate programming, with many anticipating their transformative potential in programming education. However, decisions about why and how to use LLMs in programming education may involve more than just the assessment of an LLM's technical capabilities. Using the social shaping of technology theory as a guiding framework, our study explores how students' social perceptions influence their own LLM usage. We then examine the correlation of self-reported LLM usage with students' self-efficacy and midterm performances in an undergraduate programming course. Triangulating data from an anonymous end-of-course student survey (n = 158), a mid-course self-efficacy survey (n=158), student interviews (n = 10), self-reported LLM usage on homework, and midterm performances, we discovered that students' use of LLMs was associated with their expectations for their future careers and their perceptions of peer usage. Additionally, early self-reported LLM usage in our context correlated with lower self-efficacy and lower midterm scores, while students' perceived over-reliance on LLMs, rather than their usage itself, correlated with decreased self-efficacy later in the course.

cs.HC

Critiquing Computing Artifacts through Programming Satirical Python Scripts

Computing artifacts tend to exclude marginalized students, so we must create new methods to critique and change them. We studied the potential for "satirical programming" to critique artifacts as part of culturally responsive computing (CRC) pedagogy. We conducted a one-hour session for three different BPC programs (N=51). We showed an example of a satirical Python script and taught elements of Python to create a script. Our findings suggest this method is a promising CRC pedagogical approach: 50% of marginalized students worked together to create a satirical script, and 80% enjoyed translating their "glitches" into satirical Python scripts.

cs.CY