Design empathy is a core HCI concept for understanding user perspectives in design processes. Although researchers advocate for leveraging design empathy in the design of assistive technology, educating novice designers about this is challenging; this is especially true in HCI classrooms when the target population includes people with disabilities, and students who do not have a disability are less aware of the diversity of disability. To help students better understand disability experiences, HCI education often adopts “be-like” (mimicking disabled-experience) approaches. However, accessibility researchers advocate adopting the “be-with” approach—learning about other’s experiences through companionship. To mitigate the logistical challenges of being-with in a classroom setting, we developed a “be-connected” approach, which facilitates learning about the disability experience through the narratives of real individuals. Using social media posts from a spinal cord injury subreddit, we developed and deployed an activity aiming to develop design empathy. Our qualitative evaluation showed a notable transformation in students’ design thinking process, suggesting an opportunity to leverage social media data to learn about disabled perspectives and develop design empathy.

In recognition of the growing need for ethics instruction in computing, many instructors incorporate ethics into their computing courses. However, such integration poses an important question: does incorporating ethics into computing topics enhance or distract from students' understanding of core technical content? To answer this question, I designed a controlled lab study, assessing technical content knowledge and ethical issue-spotting abilities among students exposed to ethics-integrated compared to technical-only instruction. 82 student participants were randomly assigned to receive instruction on K-Means Clustering in one of two groups: the treatment group learned the topic through an ethical narrative, and the control group learned the topic using only abstract, numeric examples. Comparing pre- and post-test learning gains between the groups can offer insights into the impact of ethics instruction on student learning outcomes. This study can help educators find the best ways to teach ethics while recognizing that computing instructors also need to provide thorough instruction on their core computing subject. Ultimately, these findings can help ensure our efforts to teach ethics within computing effectively support students' learning of both ethics and technical computing topics.

How does students' knowledge of code structure improve as they progress through their degree, and where do students struggle? We conducted a comparative study between introductory (CS1) and intermediate CS students (CS2) to explore these questions. Using an online survey with several tasks, including identification of expert patterns, judgment of readable structure, code comprehension, code writing, and editing, we focused on two important code structures: (S1) returning boolean expressions directly and (S2) unique vs. repeated code within if and else. Student performance varied based on structure and task: in both S1 and S2, CS2 students demonstrated higher performance in identifying patterns, judgment of readable structure, and editing. However, evidence of improvement in code writing was only found for S1, and improvement in code comprehension was only found for S2. Therefore, students may need different supports across different code structures. With the exception of comprehension of S1, student performance was far below ceiling, suggesting a need for more support.

While the CS education community has successfully incorporated tech-ethics assignments and modules into computing courses, we lack a defined process for instructional design to create these materials from scratch across the curriculum. To enable the development of such a process, we explore two research questions: (1) What specific instructional design challenges emerge when creating ethically-integrated assignments for CS courses? And (2) what strategies might overcome them? We address these questions using Research through Design, a method for critically examining design processes. Applying this method to our own process of creating ethics-integrated CS assignments yielded four key challenges: identifying an ethical context, maintaining a technical focus, eliciting both ethical and technical thinking from students, and making the assignment practical for the classroom. Further, the Research through Design approach revealed process-level insights for addressing these challenges, which can apply across the computing curriculum. This paper also serves as a case study of Research through Design for CS education, highlighting the importance of the instructional design process and the behind-the-scenes challenges and design decisions that go into tech-ethics materials.

How can we teach AI students to use human concerns to guide their technical decisions? We created an AI assignment with a human context, asking students to find the safest path rather than the shortest path. This integrated assignment evaluated 120 students’ understanding of the limitations and assumptions of standard graph search algorithms, and required students to consider human impacts to propose appropriate modifications. Since the assignment focused on algorithm selection and modification, it provided the instructor with a different perspective on student understanding (compared with questions on algorithm execution). Specifically, many students: tried to solve a bottleneck problem with algorithms designed for accumulation problems, did not distinguish between calculations that could be done during the incremental construction of a path versus ones that required knowledge of the full path, and, when proposing modifications to a standard algorithm, did not present the full technical details necessary to implement their ideas. We created rubrics to analyze students’ responses. Our rubrics cover three dimensions: technical AI knowledge, consideration of human factors, and the integration of technical decisions as they align with the human context. These rubrics demonstrate how students’ skills can vary along each dimension, and also provide a template for scoring integrated assignments for other CS topics. Overall, this work demonstrates how to integrate human concerns with technical content in a way that deepens technical rigor and supports instructor pedagogical content knowledge.