Between Algorithm and Authenticity. Educational Transactional Analysis in Research on TikTok Learning

Abstract

This article proposes a theoretical and methodological integration of Educational Transactional Analysis (ETA) into research on informal learning on TikTok. While existing studies focus on technology acceptance models, nano-learning behaviours, and reverse socialisation, they lack a psychodynamic and relational understanding of how learners interact with algorithmic environments. Drawing on desk research of recent empirical studies (2024–2026), the article identifies a significant research gap: the absence of qualitative analysis of ego states, transactions, psychological hungers, life positions, and games in TikTok-based learning. The author argues that TikTok’s recommendation algorithm functions as a surrogate Parent ego state, that user–algorithm interactions constitute crossed and ulterior transactions, and that the platform predominantly satisfies the hunger for stimulation while leaving the hunger for structure unmet. The article concludes with a proposal for an empirical qualitative study and outlines practical implications for media educators.