Abstract:

The article presents the Quality of Interaction (QoI) Factors Framework developed within the research phase of the Erasmus+ Forward-Looking project "Quality of Interaction of the Virtual Auditorium". The project, involving Higher Education Institutions, Non-Governmental Organizations, Public authorities and EdTech companies from Italy, Germany, Latvia, Greece, Turkey, France and Croatia, investigates how higher-education students interact with learning management systems (LMS) in digital learning environments, with a specific focus on the determinants of quality of interaction between human users and the machine and provide potential improvements through EdTech solutions (plug-in) adapted on learners’ profile. While the rapid expansion of distance and online education has led to widespread LMS adoption, existing research often treats interaction quality as a generic usability or satisfaction issue, without systematically distinguishing between internal learner-related factors and external contextual or technological conditions.

The study addresses three interrelated research questions:
(1) Which endogenous and exogenous factors influence the QoI in digital learning environments?;
(2) Which national and European policies in the participating countries support improvements in learner–LMS interaction?;
(3) How does current literature position itself with regard to phenomenological accounts of human–machine interaction, individual usability and content design, and environmental and relational dynamics between students and academic staff?

The methodological approach combines an initial conceptual mapping of potential determinants of QoI; an extensive review of regulatory and policy frameworks on digital education in the partner countries; a case-study analysis and literature review on the adoption and use of digital learning systems in higher education.

The analysis results in a multidimensional QoI Factors Framework that organizes the determinants of interaction quality across four key dimensions—technological, ethical/legal, human engagement and pedagogical—while classifying them as endogenous (linked to learners’ motivation, self-efficacy, cognitive effort and emotional states) or exogenous (related to infrastructure, platform design, data governance, teaching practices and learning context). The framework provides a structured lens for analysing human–machine interaction in LMS-based learning, offering conceptual guidance for future empirical studies and practical indications for the design of more inclusive, trustworthy and pedagogically robust digital learning environments.

Keywords:

Digital learning, Quality of interaction, Higher education, human–machine interaction.