Implementation of Affective States and Learning Styles Tactics in Web-Based Learning Management Systems

Khan, Farman Ali; Graf, Sabine; Weippl, Edgar; Tjoa, A. Min

doi:10.1109/icalt.2010.213

Cited by 18 publications

(15 citation statements)

References 4 publications

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“…More complex emotions and human nature characteristics are confusion, confidence, independence, flow, concentration and effort. These are affective states with respect to learning [21], [24].…”

Section: B Affective States and Learning Affectmentioning

confidence: 99%

Design of Cognitive MCQ test in Virtual Learning Systems to Determine Learner Affect

Kelkar*,

Bakal

2020

IJRTE

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Virtual learning systems are expected to be adaptive to the grasp exhibited by the learner. Learner affects like confusion and confidence are displayed by the learner through behavioural cues. Identifying affect in a non-intrusive, sensor-free and scalable setting is preferable. Using interaction based behavioural log features; methodology for determining learner affect is presented. The MCQ test questions in the system are based on Bloom’s Taxonomy Cognitive levels. The system records interactions of the learner. The regression analysis result on the dataset shows accuracy of confusion detection above 70%.

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Section: B Affective States and Learning Affectmentioning

confidence: 99%

Design of Cognitive MCQ test in Virtual Learning Systems to Determine Learner Affect

Kelkar*,

Bakal

2020

IJRTE

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“…al. in [9] , an automatic identification for learning styles and affective states in web-based learning management systems; 4) Dung and Florea in [10], an approach for detecting FSLSM learning styles in learning management systems based on students behaviors.…”

Section: Automatic Detection Of Students' Characteristics In Elearmentioning

confidence: 99%

Personalized Course Retrieval Using Literature Based Method in e-Learning System

Gaikwad

Potey

2013

2013 IEEE Fifth International Conference on Technology for Education (T4e 2013)

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Nowadays, many educational institutions offering elearning courses. Moreover, these courses unable to cope up with the individuals difference among learners. The learning efficiency of students increased by providing personalized course material based on characteristics such as knowledge ability, learning style, motivation in e-learning system. In this paper, we propose a new literature based method to identify learning style, motivation and knowledge ability of students automatically and dynamically using simple rules and finally offering the personalized course material based on these three factors. We used recorded data of learners' behavior during their interaction with learning objects, forums and a mapping rule to infer motivation, knowledge ability and learning styles with respect to the Felder-Silverman Learning Style Model.

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“…Various indicators for the detection of the patterns of students’ behavior can be used for this purpose, such as the number of visits to different learning objects, and time spent during the usage of these objects. The similar methods of monitoring students’ behavior to determine students’ learning styles were applied in references .…”

Section: Related Workmentioning

confidence: 99%

A semantic approach to enhance moodle with personalization

Perišić

Milovanović

Kazi

2018

Comp Applic In Engineering

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The purpose of this paper is to present a framework for an adaptive mechanism implemented in Moodle in order to improve learning outcomes and students' satisfaction with the learning process. The proposed mechanism adapts the learning content within the course according to students' characteristics expressed by their learning style. In our study, student's learning style is dynamically determined by monitoring students’ actions and activities during the learning process, and detecting patterns of behavior that correspond to specific learning style. Semantic web technologies are in the background of the entire adaptive system. In order to examine the effectiveness of the proposed model and students' feedback, an evaluation study was conducted on two groups of students. Students from the control group had access to standard Moodle course, while students from experimental group had access to personalized learning content. The results indicated that students' performance was improved by using the proposed framework, while the student's feedback from regarding its usefulness was positive.

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Implementation of Affective States and Learning Styles Tactics in Web-Based Learning Management Systems

Cited by 18 publications

References 4 publications

Design of Cognitive MCQ test in Virtual Learning Systems to Determine Learner Affect

Design of Cognitive MCQ test in Virtual Learning Systems to Determine Learner Affect

Personalized Course Retrieval Using Literature Based Method in e-Learning System

A semantic approach to enhance moodle with personalization

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