Domain knowledge, ethical acumen, and query capabilities (DEQ): a framework for generative AI use in education and knowledge work

The increasing reliance on Generative Artificial Intelligence (GenAI) among students and knowledge workers poses significant risks and raises integrity concerns, prompting some institutions to impose bans on its use. With scant research on a guided framework, strategies, and checklists for the utili...

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Main Authors: Pasty Asamoah, Daniel Zokpe, Richard Boateng, John Serbe Marfo, Sheena Lovia Boateng, David Asamoah, Abdul Samed Muntaka, John Frimpong Manso
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Cogent Education
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Online Access:https://www.tandfonline.com/doi/10.1080/2331186X.2024.2439651
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author Pasty Asamoah
Daniel Zokpe
Richard Boateng
John Serbe Marfo
Sheena Lovia Boateng
David Asamoah
Abdul Samed Muntaka
John Frimpong Manso
author_facet Pasty Asamoah
Daniel Zokpe
Richard Boateng
John Serbe Marfo
Sheena Lovia Boateng
David Asamoah
Abdul Samed Muntaka
John Frimpong Manso
author_sort Pasty Asamoah
collection DOAJ
description The increasing reliance on Generative Artificial Intelligence (GenAI) among students and knowledge workers poses significant risks and raises integrity concerns, prompting some institutions to impose bans on its use. With scant research on a guided framework, strategies, and checklists for the utilization of GenAI, we propose a framework based on the expertise acquisition model, information retrieval theory, and deontological ethics theory, emphasizing the need for domain knowledge, query capabilities, and ethical acumen (DEQ). Using a ‘thing’ ethnography methodology with ChatGPT, we validated our framework, highlighting the importance of these competencies to mitigate risks, including the generation of factually incorrect and plagiarized content. Our findings suggest that while GenAI can drive innovation, its content should be used as a guiding tool to enhance critical thinking and reasoning, ultimately helping knowledge workers and students avoid plagiarism and maintain academic integrity. We discuss this novel framework and provide avenues for extending this study.
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issn 2331-186X
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publisher Taylor & Francis Group
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series Cogent Education
spelling doaj-art-0574c8c3b51b41789e02ac625a86929f2024-12-11T16:34:55ZengTaylor & Francis GroupCogent Education2331-186X2024-12-0111110.1080/2331186X.2024.2439651Domain knowledge, ethical acumen, and query capabilities (DEQ): a framework for generative AI use in education and knowledge workPasty Asamoah0Daniel Zokpe1Richard Boateng2John Serbe Marfo3Sheena Lovia Boateng4David Asamoah5Abdul Samed Muntaka6John Frimpong Manso7Supply Chain and Information Systems Department, Kwame Nkrumah University of Science and Technology, Kumasi, GhanaSupply Chain and Information Systems Department, Kwame Nkrumah University of Science and Technology, Kumasi, GhanaDepartment of Operations and Management Information Systems, University of Ghana Business School, Accra, GhanaSupply Chain and Information Systems Department, Kwame Nkrumah University of Science and Technology, Kumasi, GhanaDepartment of Marketing and Entrepreneurship, University of Ghana Business School, Accra, GhanaSupply Chain and Information Systems Department, Kwame Nkrumah University of Science and Technology, Kumasi, GhanaSupply Chain and Information Systems Department, Kwame Nkrumah University of Science and Technology, Kumasi, GhanaSupply Chain and Information Systems Department, Kwame Nkrumah University of Science and Technology, Kumasi, GhanaThe increasing reliance on Generative Artificial Intelligence (GenAI) among students and knowledge workers poses significant risks and raises integrity concerns, prompting some institutions to impose bans on its use. With scant research on a guided framework, strategies, and checklists for the utilization of GenAI, we propose a framework based on the expertise acquisition model, information retrieval theory, and deontological ethics theory, emphasizing the need for domain knowledge, query capabilities, and ethical acumen (DEQ). Using a ‘thing’ ethnography methodology with ChatGPT, we validated our framework, highlighting the importance of these competencies to mitigate risks, including the generation of factually incorrect and plagiarized content. Our findings suggest that while GenAI can drive innovation, its content should be used as a guiding tool to enhance critical thinking and reasoning, ultimately helping knowledge workers and students avoid plagiarism and maintain academic integrity. We discuss this novel framework and provide avenues for extending this study.https://www.tandfonline.com/doi/10.1080/2331186X.2024.2439651Generative AIeducationinformation retrieval theoryexpertise acquisition modeldeontological ethics theoryacademic integrity
spellingShingle Pasty Asamoah
Daniel Zokpe
Richard Boateng
John Serbe Marfo
Sheena Lovia Boateng
David Asamoah
Abdul Samed Muntaka
John Frimpong Manso
Domain knowledge, ethical acumen, and query capabilities (DEQ): a framework for generative AI use in education and knowledge work
Cogent Education
Generative AI
education
information retrieval theory
expertise acquisition model
deontological ethics theory
academic integrity
title Domain knowledge, ethical acumen, and query capabilities (DEQ): a framework for generative AI use in education and knowledge work
title_full Domain knowledge, ethical acumen, and query capabilities (DEQ): a framework for generative AI use in education and knowledge work
title_fullStr Domain knowledge, ethical acumen, and query capabilities (DEQ): a framework for generative AI use in education and knowledge work
title_full_unstemmed Domain knowledge, ethical acumen, and query capabilities (DEQ): a framework for generative AI use in education and knowledge work
title_short Domain knowledge, ethical acumen, and query capabilities (DEQ): a framework for generative AI use in education and knowledge work
title_sort domain knowledge ethical acumen and query capabilities deq a framework for generative ai use in education and knowledge work
topic Generative AI
education
information retrieval theory
expertise acquisition model
deontological ethics theory
academic integrity
url https://www.tandfonline.com/doi/10.1080/2331186X.2024.2439651
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