The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery (SD) approach based on MapReduce. The proposed SD approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope…

Almost in every aspect of life, classification and categorization make it easier for humans to analyze complex structures and systems. In games, the classification of the players based on their demographics, behaviors, expectations and preferences of the game is important to increase players' motivation and satisfaction. Likewise, knowing the…

This study utilised the instant semantic analysis and feedback system (ISAFS) to assist learners in the online discussion learning activities of socio-scientific issues (SSIs) and to document their learning process behaviours for behavioural analyses. The aim was to understand the learners' discussion behaviours during the ISAFS assisted learning…

The flipped classroom pedagogy has been widely used recently. Despite many researches have paid attention with the learning outcome of flipped classroom, there has been limited attention in regard to investigate the relationship between learning behavior and learning outcomes in a flipped classroom. In this paper, we proposed to investigate the…

Learning analytics focuses on extracting meaning from large amounts of data. One of the largest datasets in education comes from Massive Open Online Courses (MOOCs) that typically feature enrollments in the tens of thousands. Analyzing MOOC discussion forums presents logistical issues, resulting chiefly from the size of the dataset, which can…