Emotions used in Learning Analytics: a state-of-the-art review

Rienties, Bart and Alden, Bethany (2014). Emotions used in Learning Analytics: a state-of-the-art review. LACE project.

Abstract

Emotions play a critical role in the learning and teaching process because learners’ feelings impact motivation, self-regulation and academic achievement. In this literature review of 100+ studies, we identify approximately 100 different emotions that may have a positive, negative or neutral impact on learners’ attitudes, behaviour and cognition. In this review, we explore seven methods of data gathering approaches to measure and understand emotions (i.e., content analysis, natural language processing, behavioural indicators, quantitative instruments, qualitative approaches, well-being word clouds, and intelligent tutoring systems). With increased affordances of technologies to continuously measure emotions (e.g., facial and voice expressions with tablets and smart phones), it might become feasible to monitor learners’ emotions on a real-time basis in the near future.

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About

• Item ORO ID
• 72634
• Item Type
• Other - Research Report (for external body)
• Project Funding Details

• Funded Project Name	Project ID	Funding Body
  Learning Analytics Community Exchange (H-13-001-DC)	619424	EC (European Commission): FP (inc.Horizon2020 & ERC schemes)

• Academic Unit or School
• Institute of Educational Technology (IET)
• Depositing User
• Bart Rienties