Abstract
E-learning assessment is a key aspect in the overall e-learning process. There are several parameters to consider during the assessment. In recent years, several sets of factors, called Critical Success Factors, have been defined to provide a structural approach to assessment. They focus on many aspects but, in our view, they do not properly consider student satisfaction with courses. In e-learning applications, student opinion must be examined where it is expressed: on e-learning course social pages and/or social pages outside the platform but specific to the e-learning course. The problem is that these resources are unstructured and thus it is important to structure these resources before using them for assessment. In this paper, we discuss a proposal that can capture student opinion from social pages, combining several techniques, such as Natural Language Processing, Information Extraction; ontologies that help us to understand what and how students discuss about e-learning courses.
Cite
CITATION STYLE
Caione, A., Guido, A. L., Paiano, R., Pandurino, A., & Pasanisi, S. (2016). E-learning project assessment: A new approach through the analysis of learners’ posts on social media. EAI Endorsed Transactions on E-Learning, 3(10), e5. https://doi.org/10.4108/eai.11-4-2016.151152
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