AI-based multidisciplinary framework to assess the impact of gamified video-based learning through schema and emotion analysis

As a natural and continual process, the initial learning stages encompass mastering and recalling basic facts. The process proves effective with the integration of new information with pre-existing knowledge characterised as schema to facilitate memory encoding. Additionally, emotions also have the ability to modulate human cognition in terms of learning and memory. The recent advent of gamification in e-learning, which has garnered much scholarly and industrial interest, necessitates a thorough examination between video-based learning and its subsequent implications on schema, emotions, and gamification. The current multidisciplinary research triangulated cognitive psychology, affective science, and education technology with artificial intelligence for evaluating digital learning pedagogy based on memory retrieval accuracy, response time, and emotional valence. This three-way (2 x 2 x 2) mixed factorial experiment design with repeated measures entailed 64 healthy young adult volunteers (n = 64) with 32 in the schema congruent group and 32 in the schema incongruent group. Additionally, 27 (42%) of the volunteers were males, while 37 (58%) were females with an age range between 20 and 39 years old (mean age 27.78 years, SD = 4.77 years). The findings demonstrate that the schema congruent group attained a statistically significant and higher retrieval accuracy (p < .001). The delayed recall response time was faster than its immediate recall counterpart (p < .001). Overall, the gamified learning mode depicted more positive emotions compared to non-gamified learning, although both groups primarily portrayed more negative emotions (p = .05). The synthesis of current research aimed to recommend an AI-based multidisciplinary framework to assess the impact on adult learners in terms of schema and evaluate their emotions in experiencing gamified or non-gamified video materials as a learning medium. The implications expedited from this research offer valuable insights for diverse stakeholders engaged in the video-based learning ecosystem.