TY - JOUR
T1 - Domain knowledge, ethical acumen, and query capabilities (DEQ)
T2 - a framework for generative AI use in education and knowledge work
AU - Asamoah, Pasty
AU - Zokpe, Daniel
AU - Boateng, Richard
AU - Marfo, John Serbe
AU - Boateng, Sheena Lovia
AU - Asamoah, David
AU - Muntaka, Abdul Samed
AU - Manso, John Frimpong
N1 - Publisher Copyright:
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - academic integrity
KW - Artificial Intelligence
KW - deontological ethics theory
KW - education
KW - expertise acquisition model
KW - Generative AI
KW - Higher Education
KW - information retrieval theory
KW - plagiarism
KW - Sustainability Education, Training & Leadership
UR - http://www.scopus.com/inward/record.url?scp=85212305463&partnerID=8YFLogxK
U2 - 10.1080/2331186X.2024.2439651
DO - 10.1080/2331186X.2024.2439651
M3 - Article
AN - SCOPUS:85212305463
SN - 2331-186X
VL - 11
JO - Cogent Education
JF - Cogent Education
IS - 1
M1 - 2439651
ER -