This study brings an evidence-based review of user individual characteristics employed as sources of adaptation in recent adaptive learning systems. Twenty-two user individual characteristics were explored in a systematically designed search procedure, while 17 of them were identified as sources of adaptation in final selection. The content analysis of 98 selected publications that include evidence of adaptation efficiency is conducted. The quantitative representation of the findings shows current trends in the research of individual differences, as well as the tendencies of their further employment in student modeling. The article contributes to the body of knowledge on user individual differences and consequently to the research and development of adaptive learning systems. Additional contribution of the study is in-depth description of development and evaluation of the search strategy which makes the method easily replicable as well as suitable for modification and employment in systematic literature review in any research field.

The chapter provides a comprehensive and up-to-date insight into main research findings in the area of educational technology acceptance, adoption, and usage. Over the past decades, a variety of theoretical perspectives have been advanced to provide an understanding of the determinants of adoption of various technologies used to support the process of knowledge transfer and acquisition. Although some prominent theoretical approaches in educational contexts include Innovation Diffusion Theory (IDT), Unified Theory of Acceptance and Use of Technology (UTAUT), as well as Motivational Model (MM), research reveals the Technology Acceptance Model (TAM) as the most influential model and leading scientific paradigm in investigating acceptance of educational technology by students, teachers, and other stakeholders. Aiming to increase their predictive validity, in numerous empirical studies, models have been extended with different predictive factors, like the most often validated self-efficacy, subjective norm, perceived enjoyment, perceived playfulness, anxiety, social influence, system quality, and facilitating conditions. Research revealed electronic learning (e-learning) as the most common validated mode of delivery, followed by mobile learning (m-learning), learning management system (LMS), personal learning environment (PLE), and massive open online course (MOOC), along with different supportive facilitating technologies used in education such as social media platforms, teaching assistant robots, simulators, as well as virtual reality (VR) and augmented reality (AR) technologies. To enhance explanatory power, new developments in educational technology acceptance and adoption have suggested the need of integration of TAM and UTAUT with other contributing adoption and post-adoption theories and models, together with several established approaches from other fields.