Surveilling to motivate? affective computing, academic motivation, and emotional artificial intelligence in secondary education
DOI:
https://doi.org/10.51247/pdlc.v7i4.1031Keywords:
affective computing, artificial intelligence, motivation, secondary education, ethics, emotion, governanceAbstract
The incorporation of artificial intelligence into secondary education has extended educational debate toward the affective dimension of learning, placing affective computing at the center of discussions about the possibility of interpreting signals associated with students’ emotions and responding to them pedagogically; in light of this promise, the manuscript develops a critical reflection that examines the extent to which such technology can foster motivation without overlooking the limitations arising from its application, an issue addressed through achievement emotion theory and self-determination theory to understand how boredom, confusion, and flow influence interest and self-efficacy; this relationship leads to an examination of the scientific evidence, whose limitations call into question the inference of internal states through biometric data, a problem that acquires ethical implications in relation to the surveillance of minors and has prompted a regulatory response expressed in the European prohibition in force since February 2025; in response to these tensions, the manuscript proposes directing AI toward the development of emotional agency and self-regulation under human decision-making, a perspective that opens discussion about the governance conditions required in Colombia and Latin America to prevent its adoption from widening educational inequalities
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