This quantitative psychological research analyzes predictive relationships between basic psychological needs, digital affordances and online behavior. The sample included 119 women (aged 20 to 46; M = 22.98, SD = 4.95) enrolled in early childhood and primary education programs. Data were collected in three phases during a trimester; in the first and second phases, focus groups and an artificial intelligence tool were used along with the Q-sort technique to create and shape 52 online behavior items, and in the third phase, basic psychological needs were measured and online behavior items were operationalized. Five structures of digital self and identity were identified through confirmatory factor analysis: digital collaborative learning, digital community participation, resource and privacy management, cognitive productivity and creative expression with AI as well as emotional regulation and multimedia stimulation. Structural modeling has shown that basic psychological needs predict consistent digital self and identity structures. The results provide insights into digital behaviors in the context of contemporary psychology as well as the needs of educators and education.

digital affordances, digital self, teacher education, online behaviors, basic psychological needs