Human–Machine Co-Learning in Digital Educational Environments
Keywords:
Human–machine co-learning, digital learning environments, artificial intelligence, affective learning, technology ethicsAbstract
The aim of this study was to systematically review and qualitatively analyze research on human–machine co-learning in digital educational environments to identify its cognitive, emotional, social, and technological dimensions. This study adopted a qualitative systematic review design. The research corpus consisted of peer-reviewed papers published between 2015 and 2024 in Scopus, Web of Science, ScienceDirect, Springer, and Google Scholar databases. After applying inclusion and exclusion criteria, 12 eligible articles were selected. Data were analyzed thematically using NVivo 14 through open, axial, and selective coding, and data collection continued until theoretical saturation was achieved. The results revealed three overarching themes: “Cognitive Co-evolution,” “Emotional and Social Interactions,” and “Technological and Ethical Mechanisms.” Cognitively, continuous interaction between humans and machines enhances self-regulation, metacognition, and cognitive flexibility. Emotionally, affective computing technologies foster empathy, trust, and emotional engagement in human–machine communication. Technologically, deep learning, reinforcement learning, and predictive analytics form the foundation of intelligent educational systems, while ethical concerns such as transparency, algorithmic fairness, and data privacy are vital for sustainable learning ecosystems. The study concludes that human–machine co-learning represents a transformative model of symbiotic education built upon cognitive, emotional, and technological integration. Its successful implementation requires responsible educational technology design, enhancement of teachers’ data and AI ethics literacy, and the development of equitable educational policies. This approach can lead to improved quality, personalization, and sustainability of learning in the era of artificial intelligence.
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References
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