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...

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Veröffentlicht in:Computers and education. Artificial intelligence 2022, Vol.3, p.100109, Article 100109
Hauptverfasser: Vidanaralage, Anjana Junius, Dharmaratne, Anuja Thimali, Haque, Shamsul
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Sprache:eng
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Zusammenfassung: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 
ISSN:2666-920X
2666-920X
DOI:10.1016/j.caeai.2022.100109