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A Fuzzy-Based Multi-agent Model for Group Formation in Collaborative Learning Environments Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Using Large Margin Nearest Neighbor Regression Algorithm to Predict Student Grades Based on Social Media Traces

Authors : Florin Leon, Elvira Popescu

Published in: Methodologies and Intelligent Systems for Technology Enhanced Learning

Publisher: Springer International Publishing

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Abstract

Predicting students’ performance is a popular objective of learning analytics, aimed at identifying indicators for learning success. Various data mining approaches have been applied for this purpose on student data collected from learning management systems or intelligent tutoring systems. However, the emerging social media-based learning environments have been less explored so far. Hence, in this paper we present an approach for predicting students’ performance based on their contributions on wiki, blog and microblogging tool. An innovative algorithm (Large Margin Nearest Neighbor Regression) is applied, and comparisons with other algorithms are conducted. Very good correlation coefficients are obtained, outperforming commonly used regression algorithms. Overall, results indicate that students’ active participation on social media tools is a good predictor of learning performance.

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next chapter Adaptive Agent-Based Environment Model to Enable the Teacher to Create an Adaptive Class
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Metadata
Title
Using Large Margin Nearest Neighbor Regression Algorithm to Predict Student Grades Based on Social Media Traces
Authors
Florin Leon
Elvira Popescu
Copyright Year
2017
Book
Methodologies and Intelligent Systems for Technology Enhanced Learning

Print ISBN: 978-3-319-60818-1

Electronic ISBN: 978-3-319-60819-8

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-60819-8_2

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