arXiv subjects

Helen Weixu Chen

Publications and source records attributed to Helen Weixu Chen.

3 recordsLinked to original sources

arXiv2026

Probing How Users Interact with Turn-Level Design Frictions for AI Chatbots

AI chatbots can help people write faster, but they can also encourage overreliance by making it easy to turn minimal input into usable text. We study turn-level design friction: intentional constraints added to each chatbot exchange that slow, limit, or redirect how users request, access, or use model responses. We designed six friction probes, organized around three mechanisms: eliciting user contribution, restricting access to generated content, and reshaping system output. In a within-subject study with 24 participants, all six probes increased workload, task duration, and perceived ownership relative to a conventional AI chatbot, while their effects on recall and recognition were more selective. We further found that participants adapted to friction in different ways, and that the same constraint could support or obstruct involvement depending on users' goals and workflows.

cs.HC↗

arXiv2026

Make or Take: How Students Navigate Self-Created and Instructor-Provided Cheat Sheets

The use of cheat sheets in exams is often framed as a way to reduce cognitive load and support student performance. However, little is known about how students choose between self-created and instructor-provided cheat sheets, or how these choices relate to their broader approaches to exam preparation. We conducted a longitudinal study in a senior-level undergraduate software requirements course, where students could use either an instructor-provided or a self-created cheat sheet for both the midterm and final exams. Across three survey waves, we received 53, 50, and 44 responses, respectively. 41 students completed all three surveys and formed the longitudinal cohort used to examine how choices and experiences evolved over time, while exam-specific analyses used all available responses from the corresponding wave. Our findings identify several considerations that shaped students' choices, including trust in instructor expertise, the desire for personalization, and preparation efficiency. We further show how students' attitudes shifted over time and how their preferences were reflected in patterns of cheat sheet use, perceived content coverage, and challenges encountered during the exams.

cs.HC↗

arXiv2026

Sketch Bug: Using Sketch-Based Input for Interactive Code Debugging

We investigate sketch-like pen input as an alternative way to support execution control in interactive debugging. In our interface, programmers draw lightweight marks to set breakpoints, use symbolic strokes to control execution, and extend strokes into spirals to repeat traversal actions. The prototype combines gesture recognition with Python execution tracing in a conventional editor interface. In a controlled study with 24 programmers, we compared the sketch interface with conventional mouse-and-keyboard input on debugging tasks that required breakpoint placement, step-wise execution, and runtime state inspection. The results show that sketch-like input can support these execution-control tasks, while also introducing challenges in precision, recognition, and gesture recall. Our findings suggest that pen input is most promising where debugger interactions benefit from spatial grounding or continuous movement, rather than as a wholesale replacement for conventional debugging controls.

cs.HC↗