Browsing by Author "Kumar, Rahul"

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    Academic Integrity Lessons: Practical Ideas for Teaching, Learning, and Assessment
    (University of Calgary, 2023-10-12) Eaton, Sarah Elaine; Kumar, Rahul
    Purpose: The purpose of this Open Educational Resource (OER) is to offer comprehensive lesson plans that focus on instilling skills and values related to academic integrity. The intended audience for this work is educators at elementary, secondary, and higher education levels. Methods: Contributors were invited to contribute lesson plans with a positive orientation to academic integrity, focusing on building skills and competencies, rather than focusing on consequences for committing academic misconduct. To maintain consistency and clarity, every lesson plan adheres to a standardized format. This format helps identify whether the target audience is elementary and secondary, higher education, or a combination of multiple educational levels. All lesson plans underwent open peer review by the editors and some included additional review by contributors to this edited collection. Results: This OER contains twenty-four (24) open-access lesson plans contributed by authors across four countries: Canada, the UK, Finland, and Qatar. There are five lessons specific to elementary or secondary levels, 13 for use in higher education, and another five which can be used or adapted at elementary, secondary or higher education levels. Implications: This work is licensed under a Creative Commons Attribution-NonComercial-ShareAlike 4.0 International License. This work may not be sold or used commercially. This work is freely and publicly available, downloadable, printable, and shareable. The editors and contributors have volunteered their knowledge, expertise, and time to contribute to this work. Language: English Additional Materials: Each lesson plan incorporates its respective references for further clarity and for citation purposes.
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    AI & AI: Exploring the contemporary intersections of artificial intelligence and academic integrity
    (2022-05-17) Kumar, Rahul; Mindzak, Michael; Eaton, Sarah Elaine; Morrison, Ryan
    Issues emerging from the use of artificial intelligence technologies in academic integrity are examined using deontological (principle-based), utilitarian (consequence-based), and feminist (community-based) ethical theories. Specifically, how are these ethical theories to be applied to the matters of Ai when AI mitigates educational interactions? Aside from ethics, the reality of the use of artificial intelligence technology has an impact on labour and even academic labour. Using contemporary theories that tackle automation and work is examined in the context of higher education. Although the futures are volatile, uncertain, complex, and ambiguous (VUCA), the trajectory of how artificial intelligence will be deployed is certainly uncertain. But the application of AI in text generation is here and readily available. Currently, there are a growing number of automatic text generators based on Large Language Models (LLMs) that are available to students at little or no cost. The impact on academics and education is inevitable, and while there are no explicit solutions, there are pedagogically appropriate opportunities that could provide broader change in creating more authenticity in the development of student writing. All the previously explored trends immediately affect academic integrity and assessment in post-secondary education. In the final presentation, the current practices will be troubled, and new opportunities discussed.
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    Understanding the Impact of Artificial Intelligence on Higher Education
    (2023-06-08) Eaton, Sarah Elaine; Dawson, Phillip; McDermott, Brenda; Brennan, Robert; Wiens, Jason; Moya, Beatriz; Dahal, Bibek; Milne, Nick; Miller, Allyson; Mindzak, Michael; Kumar, Rahul; Hamilton, Melanie
    This one-day public conference included transdisciplinary research presentations on various topics related to artificial intelligence in higher education including, but not limited to, pedagogy, assessment, ethics, artificial intelligence, ChatGPT, large language models, bias, equity, diversity, inclusion Sponsors include: Social Sciences and Humanities Research Council (SSHRC) (Grant #: 611-2022-0398) Social Sciences and Humanities Research Council of Canada (SSHRC) University of Calgary International Research Partnership Workshop Grant University of Calgary Teaching and Learning Grant Werklund School of Education, University of Calgary Deakin University Brock University Toronto Metropolitan University University of Saskatchewan