Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment

Abstract

The emergence of generative artificial intelligence (GenAI) requires innovative educational environments to leverage this technology effectively to address concerns like academic integrity, plagiarism, and others. Additionally, higher education needs effective pedagogies to achieve intended learning outcomes. This emphasizes the need to redesign active learning experiences in the GenAI era. Authentic assessment and experiential learning are two possible meaningful alternatives in this context. Accordingly, this article investigates how GenAI can enhance teaching and learning by constructively addressing study situations beyond conventional learning approaches and cultivating high-order skills and knowledge acquisition. This study employs thing ethnography to examine GenAI tools’ integration with authentic assessment and experiential learning and explore implementation alternatives. The results reveal insights into creating human-centered and GenAI-enhanced learning experiences within a constructive alignment. Specific examples are also provided to guide their implementation. Our contributions extend beyond the traditional use of GenAI tools as mere agents-to-write or agents-to-answer questions to become agents-to-support experiential learning for authentic assessment. These findings underscore the transformative role of GenAI tools in enhancing teaching and learning efficacy and effectiveness. The limitations in treating GenAI tools as subjects in thing ethnography are acknowledged, with potential for future implementation evaluation.

Publication DOI: https://doi.org/10.3390/educsci14010083
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School
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Funding Information: The authors would like to acknowledge the financial support of Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, in the production of this work.
Additional Information: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Uncontrolled Keywords: authentic assessment,constructive alignment,educational innovation,experiential learning,generative artificial intelligence,higher education,Computer Science (miscellaneous),Education,Developmental and Educational Psychology,Physical Therapy, Sports Therapy and Rehabilitation,Computer Science Applications,Public Administration
Publication ISSN: 2227-7102
Last Modified: 26 Apr 2024 07:22
Date Deposited: 23 Jan 2024 13:57
Full Text Link:
Related URLs: https://www.mdp ... 27-7102/14/1/83 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2024-01-12
Accepted Date: 2024-01-10
Authors: Salinas-Navarro, David Ernesto (ORCID Profile 0000-0002-7919-4885)
Vilalta-Perdomo, Eliseo (ORCID Profile 0000-0002-4551-8327)
Michel-Villarreal, Rosario
Montesinos, Luis

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