Lessons Learned from Integrating Generative AI into an Introductory Undergraduate Astronomy Course at Harvard

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   Résumé scientifique

   Over the last year, the ascent of Generative AI (GenAI) has raised concerns about its impact on core skill development, such as problem-solving and algorithmic thinking, in Computer Science students. Preliminary anonymous surveys show that at least 48.5% of our students use GenAI for homework. With the proliferation of these tools, the academic community must contemplate the appropriate role of these tools in education. Neglecting this might culminate in a phenomenon we term the "Junior-Year Wall," where students struggle in advanced courses due to prior over-dependence on GenAI. Instead of discouraging GenAI use, which may unintentionally foster covert usage, our research seeks to answer: "…

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   Résumé scientifique

   Universities are under pressure to build generative artificial intelligence (GenAI) literacy quickly, yet few documented interventions address generative AI specifically or can be deployed outside the curriculum at short notice. This paper documents AI Literacy Lab, a ten-hour extracurricular workshop programme designed and taught by a student research society at the Jagiellonian University in Kraków in 2026 and evaluates what it achieved. Thirty-three students enrolled, 85% of them from one social sciences and humanities faculty, and 67% reported no regular use of AI coding assistants. The programme ran as five two-hour modules covering large language models, everyday study workflows, promp…

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   Résumé scientifique

   Navigating generative artificial intelligence (GenAI) in higher education is a challenge for instructors, prompting calls for disciplinary guidance. This article connects current physics education research on GenAI with the Effective Practices for Physics Programs Guide, offering practical strategies for higher ed instructors. The potential integration of GenAI into existing research-based instructional strategies can support students in active learning and problem solving and aid instructors in providing feedback, developing instructional materials, and balancing GenAI's potential and pitfalls.

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   Zhengdong Zhang, Zihan Dong, Yang Shi et al. · 2023 · Human-Computer Interaction · cité 62 fois · Résumé IA disponible

   Résumé scientifique

   The rapid evolution of artificial intelligence (AI), specifically large language models (LLMs), has opened opportunities for various educational applications. This paper explored the feasibility of utilizing ChatGPT, one of the most popular LLMs, for automating feedback for Java programming assignments in an introductory computer science (CS1) class. Specifically, this study focused on three questions: 1) To what extent do students view LLM-generated feedback as formative? 2) How do students see the comparative affordances of feedback prompts that include their code, vs. those that exclude it? 3) What enhancements do students suggest for improving AI-generated feedback? To address these ques…

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   Should one teach coding in a required introductory statistics and data science class for non-major students? Many professors advise against it, considering it a distraction from the important and challenging statistical topics that need to be covered. By contrast, other professors argue that the ability to interact flexibly with data will inspire students with a lasting love of the subject and a continued commitment to the material beyond the introductory course. With the release of large language models that write code, we saw an opportunity for a middle ground, which we tried in Fall 2023 in a required introductory data science course in our school's full-time MBA program. We taught studen…

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   Résumé scientifique

   Generative AI tools are being widely taken up by students in their physics courses and beyond, often before instructors and institutions can develop policies and effective approaches for the use of these tools. Building on a framework for change in the era of AI, we developed and implemented a faculty learning community to help a university physics department address these challenges collectively. Over six biweekly sessions, faculty worked through course policies, classroom conversations about AI, AI-integrated coursework tasks, and assessment. Each session shared a common structure: we presented local data and department-sourced materials, tested them in small groups, and discussed them tog…

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   Résumé scientifique

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   Résumé scientifique

   In response to the challenges posed by generative artificial intelligence and increasingly diverse student populations, this paper examines a decade-long programme of pedagogical innovation in undergraduate mathematics education. At a research-intensive university in Hong Kong, a coherent set of evidence-informed practices has been developed and scaled across courses of different sizes and natures. These include a fully flipped classroom model supported by animated lecture videos and an exercise generator, a deliberate shift towards open-book and oral assessments, and the adoption of an AI-assisted grading platform to provide timely and individualised feedback. Drawing on multi-year institut…