Conference Agenda (All times are shown in Eastern Daylight Time)

Despite industrial initiatives and government regulations to ensure fairness in AI, gender bias remains a concerning issue, causing bad user experience, injustices, and mental harm to women. Computing education has incorporated ethics discussions to prepare students to design more ethical AI systems. However, through interviews with 18 AI practitioners/learners, we revealed limitations of the current gender bias education in the computing curricula – the education is absent, sporadic, abstract, or tech-oriented. We designed and evaluated hands-on tutorials to raise AI practitioners/learners’ awareness and knowledge of gender bias – such tutorials have the potential to complement the insufficient education on AI gender bias in computing/AI courses. By reflecting on the lessons from the design and evaluation process, we synthesized design implications and a rubric to guide future research, education, and design.

This study explores the use of handheld whiteboards as a low-tech, active learning strategy in a large undergraduate Information Science course. Grounded in Cognitive Apprenticeship and Situated Learning theories, the study investigates how whiteboard-based activities support student engagement, peer collaboration, and visualization of abstract concepts. Using a mixed-methods approach, survey responses from 184 students revealed that most participants perceived the whiteboard exercises as helpful for enhancing participation and conceptual understanding. Thematic analysis of qualitative feedback highlighted benefits such as increased attentiveness, real-time feedback, and peer learning, alongside challenges related to note-taking and anxiety. The study contributes to a deeper understanding of how simple, physical tools can complement technology-driven instructional strategies and inform inclusive, scalable approaches in information science education.

The debut of Generative AI (GAI) tools in late 2022 profoundly unsettled higher education institutions (HEIs), including the iSchools. This exploratory study is the first to scrutinize the 130 iSchools’ GAI engagement. Consulting each iSchool’s website, we conducted a qualitative content analysis of their GAI policies. Eighty-seven (66.9%) have public-facing GAI policies; the other third do not. We teased out seven themes in these 87 iSchools’ policies: the ecology of GAI, opportunities and affordances, risk and concerns, conditions of use, best practices, compliance measures, and aspirations. We urge the iSchools to develop and implement a policy predicated on human-centered GAI literacy. This research ultimately represents both a call for self-reflexivity and a call to action.

With the increased usage of Artificial Intelligence (AI) and tools like ChatGPT, various disciplines, including instructional design (ID), are experiencing rapid changes to organizational identity, pedagogy and practice. Thus, it is essential to understand how AI impacts the ID community and how the community reacts and adjusts to the change in practice brought in by AI-driven initiatives and workflows. Motivated by this social premise, we explored a sample of 100 conversations focused on AI from a popular subreddit (r/instructionaldesign) to understand community perceptions, learning visions and implications for practice. Our initial exploration highlights three key themes associated with the need for expanding curriculum and training, understanding the impact of practice and the evolution of disciplinary norms. These insights spark the need to understand how the ID field is evolving, embracing, and realigning disciplinary values to appropriate the usage of AI within the practice of ID. The long-term implications of this work include understanding the usage of online communities as forums of informal on-demand learning and the varied sociotechnical affordances that shape and regulate community building through these online formats, ultimately impacting the sustenance and efficacy of such virtual forums of learning and professional development.

On-campus generative AI (GenAI) deployment enhances the digital infrastructure of universities and can provide opportunities for students to interact with GenAI. However, limited research has explored the attitudes of college students initially exposed to on-campus GenAI deployment. This study conducts semi-structured interviews with 13 participants based on the socio-technical configuration perspective. The preliminary findings show that the on-campus GenAI deployment as a socio-technical enacted information practice has four characteristics: AI-focused activities, generative of rules and norms, the inclusion of individual and collective agency, and the embrace of the body and materiality. Furthermore, our findings illuminate students' general understanding of on-campus GenAI deployment, their developing prompt literacy, and their primary concerns and worries regarding its use. This work provides valuable insights into student attitudes toward on-campus GenAI deployment and contributes to a nuanced understanding of such information practices.