The Development, Status, and Challenges of Learning Analysis: A Review of the 7th International Conference on Learning Analytics and Knowledge
The International Conference on Learning Analytics and Knowledge ( LAK) is dedicated to the dissemination and promotion of cutting-edge research in the field of learning analysis. The 7th International Conference on Learning Analysis and Knowledge (LAK' 17) was held in Vancouver， Canada， in March 2017. The theme of LAK' 17 was purposely focused on the trans disciplinary nature of research in learning analytics. Three experts from different backgrounds shared their keynote speeches. This paper reviews and analyzes the LAK' 17 keynotes， articles and posters systematically， exploring the process of tracking learning， understanding learning and improving learning， as well as the sustainability of learning analysis. This part includes the following four aspects : 1 ) tracking learning by multimodal data analysis ， including the multimodal biometric technology and the online & offline consistency analysis of learners' behavior， psychological & physiological data. 2) Understanding learning using multi-angle analysis of learners and the learning process ， including learner behavior modeling， text mining， discourse analysis， psychological measurement and emotional analysis. 3 ) Improving learning by providing multi-faceted teaching and learning support， including personalized and adaptive learning support ( such as learner knowledge modeling， learning resource management and self~regulated learning scaffolding) ， learning design and teaching decision-making support， learning risk prediction and intervention， and learning evaluation and feedback etc. 4) The sustainable development of learning analysis， including the discussions on data authority and ethics. Finally， based on the above analyses， this paper puts forward two major trends in the transdisciplinary nature of research in learning analytics: the construction of multimodal data base， and the search for interdisciplinary technical support. At the same time， this paper points out the challenges in promoting the development of learning and analysis standards and the construction of disciplines， so as to provide inspirations for the development of learning analysis research， and the practical applications that improve learning.
|關鍵詞||学习分析、LAK、多模态学习分析、理解学习、改进学习、learning analysis、LAK、multimodallearning analysis、understanding learning、improved learning|