Emotion analysis meets learning analytics: online learner profiling beyond numerical data

Learning analytics is an emerging field of research, which deals with collecting and analysing data about learners and their learning context, as well as developing solutions that utilise the analysed data. Traditionally, learning analytics methods focus on the analysis of learners' digital trails or numerical big data, e.g., online material access, digital learners' records, grades, and length of interaction with the learning environment. However, profiling a learner without taking into account the emotional aspects that may hinder the learner's progress, can only offer an incomplete view of the learning experience. Hence, in this paper, we elaborate on the fusion of emotional aspects (i.e., emotion data) and learning analytics, specifically in online learning settings. We bring an open discussion to the educational technology community regarding the potential of analysing learner's emotions from pedagogical texts (i.e., non-structured text data) generated during an online course. We also discuss the role of negative emotions during learning, the ethical issues with the use of emotion data and the technology acceptance and reliability.

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