Metrics
21 Record Views
Book chapter
Towards the Generation of Learning Objects with Generative Artificial Intelligence
Applied Cognitive Computing and Artificial Intelligence, Vol.2251, pp.343-355
Communications in Computer and Information Science, 2251, Springer Nature Switzerland
03/30/2025
Web of Science ID: WOS:001483820100025
Abstract
This conference paper was published in the proceedings for CSCE 2024.
This paper describes ongoing research on the use of Generative Artificial Intelligence (GenAI) in generating learning objects. Learning Objects are digital or non-digital artifacts, which can be used, re-used or referenced to augment or enhance the learning process. Examples of these are presentation slides, images, text, surveys, quizzes, and hands-on exercises. The unprecedented availability and capability of GenAI tools in recent years brings us to consider how their technical capacities and abilities can bring about effective and useful learning objects. We first explore the published literature to survey work that has been reported in the field of applied GenAI to generate learning objects. Next, we provide a review of their technical features and closely look at the distinctive features of the tools used in various GenAI models. The focus of this research is to develop a method of utilizing freely available GenAI tools to expedite the generation of learning objects and to evaluate their effectiveness. Specifically, we seek to optimize the utilization of these AI-generated learning objects for active-learning applications and learning best practices.
Related links
Details
- Title
- Towards the Generation of Learning Objects with Generative Artificial Intelligence
- Publication Details
- Applied Cognitive Computing and Artificial Intelligence, Vol.2251, pp.343-355
- Resource Type
- Book chapter
- Publisher
- Springer Nature Switzerland; Cham
- Series
- Communications in Computer and Information Science; 2251
- Number of pages
- 13
- Grant note
- University of West Florida's Office of Undergraduate Research's First Year Research Experience Award
This study was funded by the University of West Florida's Office of Undergraduate Research's First Year Research Experience Award.
- Copyright
- © 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG
- Identifiers
- WOS:001483820100025; 99381312114506600
- Academic Unit
- Center for Cybersecurity; Division of Academic Affairs
- Language
- English