An Adaptive E-Learning System based on Student's Learning Styles

2016 ◽  
Vol 14 (3) ◽  
pp. 34-51 ◽  
Author(s):  
Samia Drissi ◽  
Abdelkrim Amirat
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning System ◽  
Educational Materials ◽  
Learning Achievement ◽  
Web Based ◽  
Research Areas ◽  
E Learning ◽  
The Impact

Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia. The main objective was to develop a new Adaptive Educational Hypermedia System based on Honey and Mumford learning style model (AEHS-H&M) and assess the effect of adapting educational materials individualized to the student's learning style. To achieve the main objectives, a case study was developed. An experiment between two groups of students was conducted to evaluate the impact on learning achievement. Inferential statistics were applied to make inferences from the sample data to more general conditions was designed to evaluate the new approach of matching learning materials with learning styles and their influence on student's learning achievement. The findings support the use of learning styles as guideline for adaptation into the adaptive e-learning hypermedia systems.

The influence of learning style on satisfaction and learning effectiveness in the asynchronous web-based learning system

2017 ◽  
Vol 35 (4) ◽  
pp. 473-489 ◽  
Author(s):  
Fei-Fei Cheng ◽  
Chui-Chen Chiu ◽  
Chin-Shan Wu ◽  
Der-Chian Tsaih
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning System ◽  
Learning Effectiveness ◽  
Web Based ◽  
Content Type ◽  
Web Based Learning ◽  
Significant Difference ◽  
E Learning ◽  
The Web

Purpose The purpose of this paper is to investigate the effect of user’s learning style (including accommodators, divergers, convergers, and assimilators) on user’s satisfaction on the web-based learning system and their learning effectiveness. Design/methodology/approach This experimental research used the college students from a technology institute in Taiwan as the subject sources. By using the Kolb’s learning style model, the students are classified as four types of learners: convergers, divergers, assimilators, and accommodators. The authors analyzed the relationships among the different learning styles with their effectiveness of learning and satisfaction of using the web-based learning system. The mediation effect of gender is also presented. Findings This research indicates that: first, the satisfaction of the web-based learning system has significant influence on the learning performance of learners; second, different learning styles learners have no significant effect to the satisfaction on using the web-based learning system; third, learning effectiveness has significant difference among different learning style learners on the web-based learning system; the learning effectiveness of accommodators and divergers was significantly higher than the assimilators; fourth, different learning styles learners show significant difference in gender proportion. In addition to accommodators, whose proportion of women is higher than men, the other three learning styles’ proportions in men are higher than women. Research limitations/implications This study was grounded in the Kolb’s learning style theory. The authors provide implications for academic studies in e-learning research stream that aimed at understanding the role of learning style as well as gender differences in the asynchronous web-based learning system. Practical implications Results from this study provided the implications for students, educators, and e-learning system designers. The design of teaching materials as well as functions of e-learning systems should take learners’ learning style into consideration to ensure the best learning outcome. Originality/value This study examined the students’ learning style as well as gender differences in the asynchronous web-based learning system. An experiment was conducted to ensure the data were collected in a controlled environment, thus, offer the value that most of the prior study lacks.

scholarly journals Learning Styles and Dyslexia Types – Understanding Their Relationship and its Benefits in Adaptive E-learning Systems

2020 ◽  
Vol 14 (15) ◽  
pp. 25
Author(s):  
Aisha Y Alsobhi ◽  
Khaled H Alyoubi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning Systems ◽  
Learning System ◽  
Knowledge Level ◽  
Educational Establishment ◽  
E Learning ◽  
User Learning ◽  
The Relationship ◽  
Better Than

Learning is a fundamental element of people’s everyday lives. Learning experiences can take the form of our interactions with others, through attending an educational establishment, etc. Not everyone learns in the same way, and even people who are considered to have a similar standard of abilities or proficiency will exhibit different learning styles. This does not necessarily mean that some students are better than others; it means that students are different from one another. Adaptive e-learning system should be capable of adapting the content to the user learning style, abilities and knowledge level. In this paper, we investigate the benefits of incorporating learning styles and dyslexia type in adaptive e-learning systems. Adaptivity aspects based on dyslexia type and learning styles enrich each other, enabling systems to provide learners with materials which fit their needs more accurately. Besides, consideration of learning styles and dyslexia type can contribute to more accurate student modelling. In this paper, the relationship between learning styles, the Felder–Silverman learning style model (FSLSM), and dyslexia type, is investigated. These relationships will lead to a more reliable student model.

Adaptation algorithms for selecting personalised learning experience based on learning style and dyslexia type

2019 ◽  
Vol 53 (2) ◽  
pp. 189-200 ◽  
Author(s):  
Aisha Yaquob Alsobhi ◽  
Khaled Hamed Alyoubi
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Learning Experience ◽  
Assistive Technologies ◽  
Learning Systems ◽  
Learning System ◽  
Fixed Cost ◽  
Learning Material ◽  
Content Type ◽  
E Learning

PurposeThrough harnessing the benefits of the internet, e-learning systems provide flexible learning opportunities that can be delivered at a fixed cost at a time and place to suit the user. As such, e-learning systems can allow students to learn at their own pace while also being suitable for both distance and classroom-based learning activities. Adaptive educational hypermedia systems are e-learning systems that employ artificial intelligence. They deliver personalised online learning interventions that extend electronic learning experiences beyond a mere computerised book through the use of intelligence that adapts the content presented to a user according to a range of factors including individual needs, learning styles and existing knowledge. The purpose of this paper is to describe a novel adaptive e-learning system called dyslexia adaptive e-learning management system (DAELMS). For the purpose of this paper, the term DAELMS will be employed to describe the overall e-learning system that incorporates the required functionality to adapt to students’ learning styles and dyslexia type.Design/methodology/approachThe DAELMS is a complex system that will require a significant amount of time and expertise in knowledge engineering and formatting (i.e. dyslexia type, learning styles, domain knowledge) to develop. One of the most effective methods of approaching this complex task is to formalise the development of a DAELMS that can be applied to different learning styles models and education domains. Four distinct phases of development are proposed for creating the DAELMS. In this paper, we will discuss Phase 3 which is the implementation and some adaption algorithms while in future papers will discuss the other phases.FindingsAn experimental study was conducted to validate the proposed generic methodology and the architecture of the DAELMS. The system has been evaluated by group of university students studying a Computer Science related majors. The evaluation results proves that when the system provide the user with learning materials matches their learning style or dyslexia type it enhances their learning outcomes.Originality/valueThe DAELMS correlates each given dyslexia type with its associated preferred learning style and subsequently adapts the learning material presented to the student. The DAELMS represents an adaptive e-learning system that incorporates several personalisation options including navigation, structure of curriculum, presentation, guidance and assistive technologies that are designed to ensure the learning experience is directly aligned with the user's dyslexia type and associated preferred learning style.

scholarly journals Analysing the relationship between learning styles and navigation behaviour in web-based educational system

2010 ◽  
pp. 400-421 ◽  
Keyword(s):  
Learning Styles ◽  
Computer Science ◽  
Learning Style ◽  
Web Based ◽  
Learning Platform ◽  
Web Based Learning ◽  
Index Of Learning Styles ◽  
Type Indicator ◽  
E Learning ◽  
The Relationship

The aim of our research is to automatically deduce the learning style from the analysis of browsing behaviour. To find how to deduce the learning style, we are investigating, in this paper, the relationships between the learner’s navigation behaviour and his/her learning style in web-based learning. To explore this relation, we carried out an experiment with 27 students of computer science at the engineering school (ESI-Algeria). The students used a hypermedia course on an e-learning platform. The learners’ navigation behaviour is evaluated using a navigation type indicator that we propose and calculate based on trace analysis. The findings are presented with regard to the learning styles measured using the Index of Learning Styles by (Felder and Solomon 1996). We conclude with a discussion of these results.

scholarly journals Learning achievement and knowledge transfer: the impact factor of e-learning system at Bach Khoa University, Vietnam

2018 ◽  
Vol 6 (3) ◽  
pp. 194-206
Author(s):  
Quoc Trung Pham ◽  
Minh Chau Huynh
Keyword(s):  
Knowledge Transfer ◽  
Social Presence ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Learning System ◽  
Learning Achievement ◽  
E Learning ◽  
Internet In Education ◽  
The Impact ◽  
E Mail

E-learning is the application of innovative ICT platforms and Internet in education to make it easier, spacious, and more efficient. Advantages of e-learning are recognized, but its impact on learning achievement and knowledge transferring are not confirmed clearly. Learning is considered the skills of students and knowledge gained through experience in the training process. Learning achievement has been defined as students' knowledge, skills and study habits in a training course and effectiveness of their application to their work. Based on previous research, this study suggested that learning achievement as a dependent variable affected by the capacity factors, such as: computer self efficacy, ease of use, perceived usefulness, face to face interaction, e-mail interaction, and social presence. Besides, knowledge transfer is also affected by learning achievement. The study result showed that 3 factors: easiness usefulness, e-mail interaction, and social presence have positive impacts on learning transferring knowledge through the e-learning system of Bach Khoa University (BKU). Based on analysis results, some managerial implications are suggested for improving the effectiveness of e-learning system at BKU.

scholarly journals The Impact of Felder’s Learning Styles Index on Motivation and Adoption of Information Through E-Learning

2017 ◽  
Vol 12 (2) ◽  
Author(s):  
Željko Pekić ◽  
Srđan Jovanovski ◽  
Nađa Pekić
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Statistical Significance ◽  
Relevant Information ◽  
The Other ◽  
Independent Variables ◽  
E Learning ◽  
Initial Idea ◽  
The Individual ◽  
The Impact

In this paper, we examined the nature and distribution (direction and intensity) of motivation for using e-learning, focusing the connection between the independent variables on one side and the Felder’s learning style on the other. The most relevant information that we wanted to examine and present is the individual ways of the respondents in adopting the same material. We were also interested in the ways to technically adjust the information delivery. The results confirm the statistical significance of the initial idea.

Behavioral Tracking in E-Learning by Using Learning Styles Approach

2017 ◽  
Vol 8 (1) ◽  
pp. 17 ◽  
Author(s):  
Amira Fatiha Baharudin ◽  
Noor Azida Sahabudin ◽  
Adzhar Kamaludin
Keyword(s):  
Learning Styles ◽  
Learning Style ◽  
Student Behavior ◽  
User Behavior ◽  
Learning System ◽  
Learning Needs ◽  
Learning Materials ◽  
Behavioral Tracking ◽  
E Learning ◽  
The Cost

Currently, e-learning is becoming an option as it can save the cost of education, time, and more flexible in its implementation. The main problem that arises is how to create e-learning content that is interesting and really fit the needs of the users. One way that can be done to optimize the content of e-learning is to analyze the user behavior. This study aims to analyze user (student) behavior in KALAM UMP, based on logs report (activity history), which is often called as behavioral tracking. First, the learning style of the students is determined based on Honey and Mumford Learning Styles Model by using Learning Styles Questionnaire. The analysis is done using SPSS 16.0 for Windows. The results shows that student with Reflector and Theorist learning styles access e-learning materials the most. From Spearman Correlation analysis, the relationship between learning styles and students’ behavior in e-learning is found to be very weak (r<sub>s</sub>=.276, p=.000), but statistically significant (p&lt;0.05). In other words, students’ learning styles and behavior in e-learning have significant impacts on the improvement or degradation of students’ performance. Therefore, from the results of this study, an adaptive KALAM e-learning system which can suits the learning styles of UMP students is proposed. In adaptive e-learning system, students can access learning materials that match the students' learning needs and preferences.

scholarly journals Prediction of Learner’s Profile based on Learning Styles in Adaptive E-learning System

2017 ◽  
Vol 12 (06) ◽  
pp. 31 ◽  
Author(s):  
Sucheta V Kolekar ◽  
Radhika M Pai ◽  
Manohara Pai M M
Keyword(s):  
Neural Network ◽  
Learning Styles ◽  
Learning Style ◽  
Search Algorithm ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Learning System ◽  
E Learning ◽  
Gravitational Search ◽  
Better Than

The major requirement of present e-learning system is to provide a personalized interface with adaptiveness. This is possible to provide by analyzing the learning behaviors of the learners in the e-learning portal through Web Usage Mining (WUM). In this paper, a method is proposed where the learning behavior of the learner is captured using web logs and the learning styles are categorized according to Felder-Silverman Learning Style Model (FSLSM). Each category of FSLSM learner is provided with the respective content and interface that is required for the learner to learn. Fuzzy C Means (FCM) algorithm is used to cluster the captured data into FSLSM categories. Gravitational Search based Back Propagation Neural Network (GSBPNN) algorithm is used to predict the learning styles of the new learner. This algorithm is a modification of basic Back Propagation Neural Network (BPNN) algorithm that calculates the weights using Gravitation Search Algorithm (GSA). The algorithm is validated on the captured data and compared using various metrics with the basic BPNN algorithm. The result shows that the performance of GSBPNN algorithm is better than BPNN. Based on the identified learning style, the adaptive contents and interface can be provided to the learner.

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