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Evolutionary Trends in Decision Sciences Education Research from Simulation and Games to Big Data Analytics and Generative Artificial Intelligence.

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Názov: Evolutionary Trends in Decision Sciences Education Research from Simulation and Games to Big Data Analytics and Generative Artificial Intelligence.
Autori: Akpan IJ; Department of Information Systems and Business Analytics, Kent State University, Kent, OH, USA., Razavi R; Department of Information Systems and Business Analytics, Kent State University, Kent, OH, USA., Akpan AA; Ibom International Center for Research and Scholarship, Windsor, Ontario, Canada.
Zdroj: Big data [Big Data] 2025 Oct; Vol. 13 (5), pp. 416-437. Date of Electronic Publication: 2025 Feb 28.
Spôsob vydávania: Journal Article
Jazyk: English
Informácie o časopise: Publisher: Mary Ann Liebert, Inc Country of Publication: United States NLM ID: 101631218 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2167-647X (Electronic) Linking ISSN: 21676461 NLM ISO Abbreviation: Big Data Subsets: MEDLINE
Imprint Name(s): Original Publication: New Rochelle, NY : Mary Ann Liebert, Inc., 2013-
Výrazy zo slovníka MeSH: Artificial Intelligence* , Big Data*, Data Science ; Humans ; Computer Simulation ; Decision Making ; Generative Artificial Intelligence ; Data Analytics
Abstrakt: Decision sciences (DSC) involves studying complex dynamic systems and processes to aid informed choices subject to constraints in uncertain conditions. It integrates multidisciplinary methods and strategies to evaluate decision engineering processes, identifying alternatives and providing insights toward enhancing prudent decision-making. This study analyzes the evolutionary trends and innovation in DSC education and research trends over the past 25 years. Using metadata from bibliographic records and employing the science mapping method and text analytics, we map and evaluate the thematic, intellectual, and social structures of DSC research. The results identify "knowledge management," "decision support systems," "data envelopment analysis," "simulation," and "artificial intelligence" (AI) as some of the prominent critical skills and knowledge requirements for problem-solving in DSC before and during the period (2000-2024). However, these technologies are evolving significantly in the recent wave of digital transformation, with data analytics frameworks (including techniques such as big data analytics, machine learning, business intelligence, data mining, and information visualization) becoming crucial. DSC education and research continue to mirror the development in practice, with sustainable education through virtual/online learning becoming prominent. Innovative pedagogical approaches/strategies also include computer simulation and games ("play and learn" or "role-playing"). The current era witnesses AI adoption in different forms as conversational Chatbot agent and generative AI (GenAI), such as chat generative pretrained transformer in teaching, learning, and scholarly activities amidst challenges (academic integrity, plagiarism, intellectual property violations, and other ethical and legal issues). Future DSC education must innovatively integrate GenAI into DSC education and address the resulting challenges.
Contributed Indexing: Keywords: complex dynamic systems; data analytics; decision sciences; digitization; generative artificial intelligence; simulation and games
Entry Date(s): Date Created: 20250228 Date Completed: 20251011 Latest Revision: 20251011
Update Code: 20251011
DOI: 10.1089/big.2024.0128
PMID: 40019821
Databáza: MEDLINE
Popis
Abstrakt:Decision sciences (DSC) involves studying complex dynamic systems and processes to aid informed choices subject to constraints in uncertain conditions. It integrates multidisciplinary methods and strategies to evaluate decision engineering processes, identifying alternatives and providing insights toward enhancing prudent decision-making. This study analyzes the evolutionary trends and innovation in DSC education and research trends over the past 25 years. Using metadata from bibliographic records and employing the science mapping method and text analytics, we map and evaluate the thematic, intellectual, and social structures of DSC research. The results identify "knowledge management," "decision support systems," "data envelopment analysis," "simulation," and "artificial intelligence" (AI) as some of the prominent critical skills and knowledge requirements for problem-solving in DSC before and during the period (2000-2024). However, these technologies are evolving significantly in the recent wave of digital transformation, with data analytics frameworks (including techniques such as big data analytics, machine learning, business intelligence, data mining, and information visualization) becoming crucial. DSC education and research continue to mirror the development in practice, with sustainable education through virtual/online learning becoming prominent. Innovative pedagogical approaches/strategies also include computer simulation and games ("play and learn" or "role-playing"). The current era witnesses AI adoption in different forms as conversational Chatbot agent and generative AI (GenAI), such as chat generative pretrained transformer in teaching, learning, and scholarly activities amidst challenges (academic integrity, plagiarism, intellectual property violations, and other ethical and legal issues). Future DSC education must innovatively integrate GenAI into DSC education and address the resulting challenges.
ISSN:2167-647X
DOI:10.1089/big.2024.0128