Pedagogical Chatbots and the Quality of Student Learning: A Qualitative Study in Higher Education Running head: Pedagogical Chatbots and Learning Quality

Abstract

Purpose: The recent rise of large-language-model chatbots is transforming learning practices in higher education, particularly in pre-service teacher training; this article analyses how pedagogical chatbots influence the quality of student learning, asking whether they strengthen or weaken it, and how usage modalities shape motivation and engagement. Approach: A conceptual model articulating technology acceptance, cognitive and self-regulatory support (planning, monitoring, cognitive load), and socio-relational motivation (autonomy, competence, relatedness) guided thirty semi-structured interviews with undergraduate education students at ESEF, Ibnou Zohr University, analysed lexically and thematically. Findings: Chatbots are widely accepted when useful and easy to use; they support self-regulation and reduce some cognitive load while exposing students to overload and superficial processing; they mainly strengthen autonomy and competence rather than social presence. Implications: Chatbots improve learning quality as critical, complementary tools, but substitutive use weakens deep learning and widens inequalities.