Personalisation based on data mining

This process involves adapting the learning experience through the use of data mining methods to achieve personalisation. It applies data analysis techniques to generate insights from learner data, enabling functions such as prediction and classification. By leveraging statistical techniques and algorithms, including machine learning, data mining helps identify patterns, trends, and insights that are essential for creating personalised learning experiences for distance learners. Thus, data mining can be used to analyse learners’ needs and preferences, such as their learning behaviours, engagement with content, and academic performance, in order to provide personalised educational content. This may include recommending suitable learning resources and tailoring learning experiences to individual learners.

taxonomy of personalized educational data mining
Personalized educational data mining taxonomy (Xiong et al., 2024).
taxonomy of personalized educational data mining
Example of personalized learning - multimodal data fusion techonology (Ji et al., 2024).

Resources

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