Learning Style and Behavior Analysis: A Study on the Learning Management System Manhali

Haddioui, Ismail El; Khaldi, Mohamed

doi:10.5120/8877-2862

Cited by 5 publications

(3 citation statements)

References 6 publications

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“…Kolb's learning styles are detected from our behavioral indicators collected on the platform, and Felder's learning styles are calculated from the results of a questionnaire. We classified the four learning styles of Kolb into only two categories [12]: -The active experimenter (accommodating/converging style): This category includes students who prefer handling, task execution and activities implementation.…”

Section: Learning Style Resultsmentioning

confidence: 99%

Study of learner Behavior and Learning Styles on the Adaptive Learning Management System Manhali: Results and Analysis According to Gender and Academic Performance

Haddioui¹,

Khaldi²

2017

JSW

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This paper presents the detailed results of the study that we performed on our adaptive Learning Management System Manhali. This study was addressed to first year university students in Computer Engineering. The experiment was in the form of an online course intended to analyze and evaluate learner behavior on the e-learning platform and to identify their learning styles according to two learning styles theories: Kolb's theory and Felder's theory. The main objective was to study two important relationships in e-learning systems: The relationship between the behavior of a learner and their academic performance, and the relationship between the gender of the learner and their learning style.

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Section: Learning Style Resultsmentioning

confidence: 99%

Study of learner Behavior and Learning Styles on the Adaptive Learning Management System Manhali: Results and Analysis According to Gender and Academic Performance

Haddioui¹,

Khaldi²

2017

JSW

Self Cite

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“…A valuable source of information about the characteristics of the user is interpreted and analyzed from his log files (El Haddioui and Khaldi, 2012;Popescu, 2009b). For this purpose, to deduce the tutoring styles of tutors, we have based on the behavioral indicators from the analysis of tutors' activities (Figure 3).…”

Section: Description Of the Tutoring Styles' Indicatorsmentioning

confidence: 99%

Automatic Detection of Tutoring Styles Based on Tutors' Behavior

Bendjebar

Lafifi

Zedadra

2016

International Journal of Distance Education Technologies

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In e-learning systems, tutors have a significant impact on learners' life to increase their knowledge level and to make the learning process more effective. They are characterized by different features. Therefore, identifying tutoring styles is a critical step in understanding the preference of tutors on how to organize and help the learners. In this context, the authors address the problem of extracting tutoring styles from tutors' behavior. According to this later, tutors are classified automatically into their styles. This technique will be helpful to provide a suitable advice to learners. In the first step, a set of indicators are defined to characterize a tutoring style. In the second one, the accuracy between the tutoring styles obtained from the proposed approach and those defined from a simple questionnaire is investigated. To validate this approach, the authors have collected data from an on line tutoring system (LETline, http://www.labstic.com/letline). They present the results of their analysis and discuss some limitations that can be helpful to the researchers working in the tutoring field.

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“…There are some of definitions on learning style. One of the definitions explain that learning styles is learning styles are unique behaviors and serve as indicators of how a person learns and how he or she adapts to their environment and how they can provide clues about how someone thinks [3]. Students online learning behaviors can also be used to predict student 32 performance.…”

Section: Introductionmentioning

confidence: 99%

Develop a User Behavior Analysis Tool in ETHOL Learning Management System

Susanto

Qurani

Rasyid

2021

emitter

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Students have different learning styles when studying online. Meanwhile, lecturers use the same method for all students who take their online lectures. These different learning styles can affect the level of understanding and the results obtained by students. By knowing student learning styles, lecturers are expected to be able to use the right way in delivering material. In this research, we developed a student behavior analysis feature on self-developed Virtual Learning Environment (VLE) called Enterprise Hybrid Online Learning (ETHOL). Students’ data collected includes data on online activities, personal data, and survey data on student learning styles. User behavior analysis was carried out by dividing into three clusters: average scores, time to collect assignments, and student learning styles. The clustering method used is the Hierarchical K-Means. The results obtained are students who have the habit of collecting assignments on time have higher scores than others. In addition, the lecturer is able to see the results of the analysis of the behavior and learning styles of each student. These results can be used as information in delivering lecture material.

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Learning Style and Behavior Analysis: A Study on the Learning Management System Manhali

Cited by 5 publications

References 6 publications

Study of learner Behavior and Learning Styles on the Adaptive Learning Management System Manhali: Results and Analysis According to Gender and Academic Performance

Study of learner Behavior and Learning Styles on the Adaptive Learning Management System Manhali: Results and Analysis According to Gender and Academic Performance

Automatic Detection of Tutoring Styles Based on Tutors' Behavior

Develop a User Behavior Analysis Tool in ETHOL Learning Management System

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