Facilitating Cognitive Load Management and Improved Learning Outcomes and Attitudes in Middle School Technology and Vocational Education Through AI Chatbot

Authors

Keywords:

cognitive load, Artificial Intelligence (AI), Chatbots, learning outcomes , retention, student attitude, Vocational Education, TVET

Abstract

Junior Secondary School (JSS) or middle school education is peculiar as it involves the introduction of a wide array of subjects across the sciences, arts, humanities, business and vocational fields to young learners. This situation can be ovewhelming, resulting in high cognitive load (CL), with consequent poor learning outcomes, and other negative issues including high dropout rates, requiring urgent attention. AI tools have been explored for addressing multiple learning issues. AI chatbots are particularly useful based on their ability to support individualized learning, pre-training, and other concepts that can facilitate CL management.  This study evaluated the impact of an AI-based chatbot system for reducing students’ CL and improving learning outcomes, attitude and retention among JSS students. A quasi-experimental study with 120 students was conducted over an 8 week period with 24 learning sessions. The experimental group (N=60) learnt using ‘iLearnTech’, an AI Chatbot developed specifically for the study. The control group (N=60) learnt through the traditional approach with no chatbot. Learning content was based on the JSS Basic Technology education, a precursor to TVET. Data was collected using the Cognitive Load Measure, the Basic Technology Achievement Test, Students’ Attitude Survey (SAS), and Students’ Retention Test. The experimental group exhibited huge reductions in CL and corresponding improvements in learning outcomes, attitude and retention. The results also confirmed known relationship between the dependent variables and highlights the potential of AI powered educational tools for addressing diverse educational issues including promoting equitable access, and sustainable education in developing nations and resource-constrained environments. This work contributes to ongoing discussions on AI applications in education. Its novelty lies in its exploration of AI technology in addressing CL issues in the context of junior secondary education. Implications for educational policy and practice, particularly curriculum design and e-learning integration are highlighted.

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Author Biographies

  • Bosede Iyiade Edwards, Universiti Sains Malaysia

    Dr. Bosede Iyiade Edwards' is a Senior Lecturer at the Center for Instructional Technology and Multimedia, Universiti Sains Malaysia (USM), Penang. Her research interests range from emerging technologies in education and Human–Machine Interfaces in Education, to Adaptive Learning Interfaces within the future school theme. She is a seasoned academic and industry professional with over 25 years of work experience. She holds both Masters and PhD in Educational Technology in addition to a Honours Bachelors in Chemistry, Master in Organic Chemistry, and a PGD in Education. This multidisciplinary background enriches her perspectives in research and teaching. She has a proven track record in research leadership, and multi- and trans-disciplinary approaches to academic research. She has authored and co-authored over 25 journals and conference papers, and has been recognized with the IEEE Frontiers in Education 'Faculty Fellow' Award. She is passionate about SDG4's focus on equitable and sustainable education, and particularly on how educational technologies can be leveraged for achieving this.

  • Damola Olugbade, First Technical University Ibadan, Nigeria

    Dr. Damola Olugbade earned his PhD in Educational Technology from Obafemi Awolowo University, Nigeria, in 2018. He is a Principal Research Fellow at First Technical University, Ibadan, where he leads research on learning technologies and digital pedagogy. His work centers on integrating artificial intelligence (AI), learning cognition, and innovative educational technologies to enhance educational outcomes. Dr. Olugbade has made significant contributions through publications in prominent journals like Education and Information Technologies and the African Journal of Teacher Education. He frequently presents at international conferences on topics such as AI-driven education, technology-enhanced learning, and social media in education, advancing the practical applications of educational technologies in Nigeria and beyond.

  • Olayinka Anthony Ojo, University of Bolton

    Dr. Olayinka Anthony Ojo holds PhD in Educational Technology from Obafemi Awolowo University, Ile-Ife, and has a background in Computer Science. His work experience spans both the industry and academia, and he has been extensively involved with executive training in computer applications, computer/network maintenance services, and computer solutions development for top-rated organizations. Dr. Ojo has taught various computer science and educational technology courses at the University of Ilesa (former Osun State College of Education, Ilesa, Nigeria), University of Ibadan (Ilesa Campus), and Lagos State University Sandwich program. He was an examiner for the West African Examination Council (WAEC) and a Facilitator and  research supervisor (bachelors & masters programs) at the National Open University of Nigeria (NOUN). Dr. Ojo served as a Senior Educational Technologist at the University of Medical Sciences, Ondo, Nigeria co-ordinating technology integration and training for the university academic staff. He is a dynamic researcher with published works in educational technologies and computer science. He recently completed another MSc in Cloud and Network Security at the University of Bolton, UK (with Distinction), focusing his research on the security of the online learning platform. He is currently pursuing research interests in the application of AI in teaching and learning, and works with the University of Bolton research team on ongoing AI application in trade training for World Trade Organization staff.

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Published

24-12-2024

Issue

Vol. 16 No. 3 (2024)

Section

Articles

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How to Cite

Edwards, B. I., Olugbade, D., & Ojo, O. A. (2024). Facilitating Cognitive Load Management and Improved Learning Outcomes and Attitudes in Middle School Technology and Vocational Education Through AI Chatbot. Journal of Technical Education and Training, 16(3), 114-131. https://penerbit.uthm.edu.my/ojs/index.php/JTET/article/view/19476

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