Technology Knowledge and Learning

Technology Knowledge and Learning英文简介

Technology, Knowledge and Learning emphasizes the increased interest on context-aware adaptive and personalized digital learning environments. Rapid technological developments have led to new research challenges focusing on digital learning, gamification, automated assessment and learning analytics. These emerging systems aim to provide learning experiences delivered via online environments as well as mobile devices and tailored to the educational needs, the personal characteristics and the particular circumstances of the individual learner or a (massive) group of interconnected learners. Such diverse learning experiences in real-world and virtual situations generates big data which provides rich potential for in-depth intelligent analysis and adaptive feedback as well as scaffolds whenever the learner needs it. Novel manuscripts are welcome that account for how these new technologies and systems reconfigure learning experiences, assessment methodologies as well as future educational practices. Technology, Knowledge and Learning also publishes guest-edited themed special issues linked to the emerging field of educational technology.   

Submissions can be empirical investigations, work in progress studies or emerging technology reports. Empirical investigations report quantitative or qualitative research demonstrating advances in digital learning, gamification, automated assessment or learning analytics. Work-in-progress studies provide early insights into leading projects or document progressions of excellent research within the field of digital learning, gamification, automated assessment or learning analytics. Emerging technology reports review new developments in educational technology by assessing the potentials for leading digital learning environments.   Manuscripts submitted to Technology, Knowledge and Learning undergo a blind review process involving expert reviews and in-depth evaluations. Initial feedback is usually provided within eight weeks including in progress open-access abstracts and review snapshots.

IF值(影响因子)趋势图