Exploring the Use of NLP Techniques for Building Learner Models: A Study on Text Mining for Personalized Learning

DOI

10.2991/978-94-6463-360-3_11How to use a DOI?

Keywords

Learner models; Personalized learning; Natural language processing (NLP); Text mining

Abstract

The importance of learner models has been growing in recent years due to the increasing focus on personalized learning. Learner models provide a way to understand learner behavior and preferences, which can be used to tailor instruction to the individual needs and preferences of each learner. This can lead to more effective and efficient learning, as learners receive instruction that is tailored to their unique needs and abilities.

Furthermore, the rise of online and distance learning has increased the need for learner models. In these environments, teachers and instructors often have limited visibility into learner behavior and progress. Learner models can provide valuable insights into learner behavior and preferences, which can be used to improve the effectiveness of online instruction.

In this article we explore the use of natural language processing (NLP) techniques for building learner models, from text data, based on Text Mining.

As well, text mining is the process of extracting useful information from unstructured text data. Extracting relevant information from text data using techniques such as tokenization, stemming, and stop word removal is one of the ways in which NLP can be used to build learner models.

Once the relevant information has been extracted, it can be used to create features that can be used to train machine learning models to predict learner behavior and preferences. These features can include things like the frequency of certain words or phrases, the sentiment of learner responses, and the topics discussed in learner writing.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jalal Lahiassi
AU  - Souhaib Aammou
AU  - Badr Touis
AU  - Oussama EL Warraki
PY  - 2024
DA  - 2024/02/05
TI  - Exploring the Use of NLP Techniques for Building Learner Models: A Study on Text Mining for Personalized Learning
BT  - Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2023)
PB  - Atlantis Press
SP  - 95
EP  - 101
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-360-3_11
DO  - 10.2991/978-94-6463-360-3_11
ID  - Lahiassi2024
ER  -