Verkko-oppimisympäristöjen kehittäminen tekoälyn avulla: Tulevaisuusvisio matematiikan opetuksen täydennyskoulutuksesta

Abstract

Web-based learning enviroments have become increasingly popular world-wide. At the same time, the need for new approaches to both supporting and investigating teaching and learning have emerged. Although log information enables research of online behavior, this opportunity is not used to its full potential in the context of web-based teaching and learning. This research utilized log information in the assessment of a MOOC course and its development. This article describes the learning process with the help of log information. It also envisions what kind of understanding of the learning process log information can provide and how this understanding may be harnessed to support learning in the future. The data consisted of the log information of mathematic teachers (N=58) participating in an online continuing training course. The results show that in-depth time-consuming activities interrupt studying more easily than video lectures for example. Short videos and quick queries engage the participant in more coherent study. Although there are individual differences in the studying, less well-functioning teaching content and tasks can be recognized through log information. We present a vision of how log information can be automatically analyzed; the system would recognize learning profiles and the online environment would automatically modify itself according to the profile. When AI (artificial intelligence) is utilized the profiling algorithm would develop automatically as user data accumulates.