Facilitating Cognitive Load Management and Improved Learning Outcomes and Attitudes in Middle School Technology and Vocational Education Through AI Chatbot - Edwards, Bosede Iyiade; Olugbade, Damola; Ojo, Olayinka Anthony (Journal of Technical Education and Training, 2024)
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.