KNOWLEDGE ASSESSMENT AND RESULTS VISUALIZATION BASED ON TEXT MINING IN E-LEARNING PLATFORMS.
DOI:
https://doi.org/10.5281/zenodo.20787052Keywords:
E-learning, Text Mining, knowledge assessment, TF-IDF, sentiment analysis, clustering, data visualization, learning analytics, artificial intelligence.Abstract
This article explores the application of Text Mining technologies for assessing learners’ knowledge levels and
analyzing educational activities in E-learning platforms. The main objective of the study is to develop methods for the
automatic evaluation of students’ knowledge and the visualization of learning outcomes based on the analysis of textual
data generated during the learning process. The research methodology includes text preprocessing, keyword extraction
using the TF-IDF algorithm, sentiment analysis, and K-Means clustering techniques. The findings demonstrate that Text
Mining technologies are effective tools for identifying students’ knowledge levels and learning engagement. Furthermore,
visualization techniques, including charts and graphs, significantly improve the monitoring of educational processes, the
analysis of learning outcomes, and the efficiency of decision-making.
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