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Applying big data analysis technique to students' learning behavior and learning resource recommendation in a MOOCs course

Through MOOCs and social media platforms, users can share, track, and search for the information of their specific interests. Thus, they can make interactive discussions as well as social media learning on multimedia texts and learning materials. This paper proposes a big data analysis technique on learning portfolio to explore how the interaction, unknown correlations, and hidden patterns among learners on MOOCs and social media platforms starts, and recognize the using big data analytics transforming on students' learning behavior. Therefore, the learning behavior information will be the recommendation of the analogous courses for the instructors in the future.