Data on learners emotional states, mental responses and fuzzy learning flows during interaction with learning environment.

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Abstract

The emotional state of the learner is an important factor that must be taken into consideration during evaluating learning process and managing learning flows in computer based learning environments. This factor has a significant impact on the process of interaction between the learner and the learning environment. Enriching this type of interaction make the learning flow more dynamic based on emotional and mental responses of the learners. This approach can manage various learning flows based on learner’s capabilities which lead to enhance the learning process outcome. This article provides data on learners’ emotional states during their interaction with learning environment and other data that describe their learning activities and learning flows. The learning activities data is a combination of data that represents summary of learners’ emotional states and data that represents the mental responses per learning session. All of emotional states data and mental responses data are used to provide the next learning level for each learner using fuzzy rules. The datasets are hosted in the Mendeley Dataset Repository (Megahed, 2019).