scholarly journals Student modelling in adaptive e-learning systems

2011 ◽  
pp. 342-355 ◽  
Keyword(s):  
Online Courses ◽  
Learning Systems ◽  
Domain Model ◽  
Learning System ◽  
Knowledge Level ◽  
Student Model ◽  
Java Programming ◽  
E Learning ◽  
The Right ◽  
And Behavior

Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

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.

scholarly journals E-Learning Systems Requirements Elicitation

2017 ◽  
Vol 7 (1) ◽  
pp. 44-55 ◽  
Author(s):  
Shaikha B. AlKhuder ◽  
Fatma H. AlAli
Keyword(s):  
Knowledge Exchange ◽  
Requirements Elicitation ◽  
Learning Systems ◽  
Learning System ◽  
Functional Requirements ◽  
Training And Education ◽  
E Learning ◽  
Systems Requirements ◽  
The Right ◽  
Simple Materials

Training and education have evolved far beyond black boards and chalk boxes. The environment of knowledge exchange requires more than simple materials and assessments. This article is an attempt of parsing through the different aspects of e-learning, understanding the real needs, and conducting the right requirements to build the appropriate e-learning system. E-learning systems, unlike the normally developed systems, have variable customers and on-going demands. It is not the easiest task to elicit unambiguous functional and non-functional requirements for such systems. However, a brief exploration of some of the e-learning characteristics may tremendously decrease the difficulty of prioritizing the most important requirements.

Virtual Co Learner

2010 ◽  
pp. 41-54 ◽  
Author(s):  
Dimitrios Georgiou ◽  
Sotirios Botsios ◽  
Georgios Tsoulouhas
Keyword(s):  
Collaborative Learning ◽  
Learning Environments ◽  
Learning Style ◽  
Learning Systems ◽  
Learning System ◽  
Cognitive Characteristics ◽  
Learning Procedure ◽  
E Learning ◽  
On Line ◽  
And Behavior

Adaptation and personalization of the information and instruction offered to the users in on-line e-learning environments are considered to be the turning point of recent research efforts. Collaborative learning may contribute to adaptive and personalized asynchronous e-learning. In this chapter authors intend to introduce the Virtual co Learner (VcL) that is a system designed on a basis of distributed architecture able to imitate the behavior of a learning companion who has suitable to the user’s cognitive and learning style and behavior. To this purpose an asynchronous adaptive collaborating e-learning system is proposed in the sense of reusing digitized material which deployed before by the users of computer supported collaborating learning systems. Matching real and simulated learners who have cognitive characteristics of the same type, one can find that learning procedure becomes more efficient and productive. Aiming to establish such VcL, one faces a number of questions. An important question is related to the user’s cognitive or learning characteristics diagnosis. Other questions are examined too.

scholarly journals Effective Adaptive E-Learning Systems According to Learning Style and Knowledge Level

10.28945/4459 ◽  
2019 ◽  
Vol 18 ◽  
pp. 529-547 ◽  
Author(s):  
Mohammad T Alshammari ◽  
Amjad Qtaish
Keyword(s):  
Computer Security ◽  
Learning Style ◽  
Student Characteristics ◽  
Learning Systems ◽  
Learning System ◽  
Learning Material ◽  
Knowledge Level ◽  
Learning Gains ◽  
Adaptive Approach ◽  
E Learning

Aim/Purpose: Effective e-learning systems need to incorporate student characteristics such as learning style and knowledge level in order to provide a more personalized and adaptive learning experience. However, there is a need to investigate how and when to provide adaptivity based on student characteristics, and more importantly, to evaluate its value in learning enhancement. This study aims to bridge that gap by examining the effect of different modes of learning material adaptation and their sequences to the learning style and knowledge level of students in e-learning systems. Background: E-learning systems aim to provide acceptability and interactivity between students, instructors, and learning content anytime and anywhere. However, traditional systems are typically designed for generic students irrespective of individual requirements. Successful e-learning systems usually consider student characteristics such as learning style and knowledge level to provide more personalized and adaptive student-system interaction. Methodology: A controlled experiment was conducted in a learning context with 174 subjects to evaluate the learning effectiveness of adaptivity in e-learning systems. Contribution: The main contributions of the paper are threefold. First, a novel adaptive approach is proposed based on a specific learning style model and knowledge level. Second, the approach is implemented in an e-learning system to teach computer security, the application domain. Third, a rigorous experimental evaluation of the learning effect of the adaptive approach is offered. Findings: The results indicate that adaptation according to the combination of learning style and knowledge level produces significantly better learning gains, both in the short-term and medium-term, than adaptation according to either trait individually. Recommendations for Practitioners: Practitioners should consider the combination of learning style and knowledge level when delivering and presenting learning material to their students. Recommendation for Researchers: Researchers should consider sound educational models when designing adaptive e-learning systems. Also, rigorous and carful experimental design evaluations should be taken into account. Impact on Society: Universities and e-learning industries can benefit from the proposed adaptive approach and the findings in designing and developing more personalized and adaptive e-learning systems. The incorporation of student characteristics, especially learning style and knowledge level, may be used to enhance learning. Future Research: The experiment might be duplicated with a focus on longer-term learning gains by including more subjects and more learning resources. Also, the study might be expanded to application domains other than computer security. Moreover, other variables such as student satisfaction, motivation, and affective state might be explored to further the understanding of the effect of adaptivity on learning gains.

scholarly journals E-learning-Oriented Software Architecture Design and Case Study

2015 ◽  
Vol 10 (4) ◽  
pp. 59
Author(s):  
Peng Lu ◽  
Xiao Cong ◽  
Dongdai Zhou
Keyword(s):  
Software Architecture ◽  
Building Blocks ◽  
Domain Model ◽  
Learning System ◽  
Application Framework ◽  
Component Library ◽  
E Learning ◽  
The Difference ◽  
High Level

Nowadays, E-learning system has been widely applied to practical teaching. It was favored by people for its characterized course arrangement and flexible learning schedule. However, the system does have some problems in the process of application such as the functions of single software are not diversified enough to satisfy the requirements in teaching completely. In order to cater more applications in the teaching process, it is necessary to integrate functions from different systems. But the difference in developing techniques and the inflexibility in design makes it difficult to implement. The major reason of these problems is the lack of fine software architecture. In this article, we build domain model and component model of E-learning system and components integration method on the basis of WebService. And we proposed an abstract framework of E-learning which could express the semantic relationship among components and realize high level reusable on the basis of informationized teaching mode. On this foundation, we form an E-learning oriented layering software architecture contain component library layer, application framework layer and application layer. Moreover, the system contains layer division multiplexing and was not built upon developing language and tools. Under the help of the software architecture, we could build characterized E-learning system flexibly like building blocks through framework selection, component assembling and replacement. In addition, we exemplify how to build concrete E-learning system on the basis of this software architecture.

Factors Associated with students’ Intention to use E-Learning System: A Study from Public Universities of Lahore

2021 ◽  
Vol 9 (2) ◽  
pp. 167-173
Author(s):  
Shagufta Shaheen ◽  
Mubasher Muhammad Kamran ◽  
Saira Naeem ◽  
Tahir Mahmood
Keyword(s):  
Undergraduate Students ◽  
Public Universities ◽  
Positive Impact ◽  
Cross Sectional Study ◽  
Learning Systems ◽  
Learning System ◽  
Policy Implications ◽  
Intention To Use ◽  
Cross Sectional ◽  
E Learning

The study's primary purpose is to explore the factors affecting the students' intention to use e-learning systems in the COVID pandemic. The model of the “Unified theory of acceptance and use of technology” (UTAUT) was used as a theoretical underpinning. The Independent variables include “performance expectancy, effort expectancy, social influence, facilitating condition,” and the dependent variable is the intention to use e-learning systems. The quantitative data were collected from the postgraduate and undergraduate students of the public universities of Lahore. A total of n=411 students were approached, out of which the responses of only 399 were considered valid and were used for Multiple linear regression through SPSS 25. It was a cross-sectional study. It was found that almost all constructs of the model have a significant positive impact on intention to use e-learning systems.  The study's main contribution is exposing the factors that affect the acceptance and use of e-learning systems. This study has several policy implications for policy experts of higher education”.

scholarly journals POSSIBILITIES OF DEVELOPING INTERACTIVE E-LEARNING SYSTEM FOR BORDER GUARDS TRAINING IN THE STATE BORDER GUARD COLLEGE OF THE REPUBLIC OF LATVIA

2020 ◽  
Vol 3 (8) ◽  
pp. 45-53
Author(s):  
Mārtiņš Spridzāns ◽  
Jans Pavlovičs ◽  
Diāna Soboļeva
Keyword(s):  
Scientific Literature ◽  
Online Communication ◽  
The State ◽  
Learning Systems ◽  
Learning System ◽  
Digital Learning ◽  
E Learning ◽  
Research Findings ◽  
The Republic ◽  
Learning Development

Efficient use of educational technology and digital learning possibilities has always been the strategic area of high importance in border guards training at the State Border Guard College of Latvia. Recently, issues related to training during the Covid-19, have spurred and revived the discussion, topicality and practical need to use the potential of e-learning opportunities which brought up unexpected, additional, previously unsolved, unexplored, challenges and tasks to border guards training. New opportunities and challenges for trainers, learners and administration of training process both in online communication and learning administration contexts. In order to find out and define further e-learning development possibilities at the State Border Guard College the authors of this research explore the scientific literature on the current research findings, methodologies, approaches on developing interactive e-learning systems in educational contexts, particularly within the sphere of law enforcement. Based on scientific literature research findings authors put forward suggestions on improving the e-learning systems for border guards training.

scholarly journals INCA: A cognitive multi-agents architecture for designing intelligent & adaptive learning systems

2005 ◽  
Vol 2 (2) ◽  
pp. 99-114 ◽  
Author(s):  
Thierry Nabeth ◽  
Liana Razmerita ◽  
Albert Angehrn ◽  
Claudia Roda
Keyword(s):  
Knowledge Sharing ◽  
Adaptive Learning ◽  
Management Practices ◽  
Learning Systems ◽  
Learning System ◽  
Cognitive Agents ◽  
E Learning ◽  
Personal Agent ◽  
Adaptive Learning Systems ◽  
Multi Agents

This paper presents a cognitive multi-agents architecture called Intelligent Cognitive Agents (InCA) that was elaborated for the design of Intelligent Adaptive Learning Systems. The InCA architecture relies on a personal agent that is aware of the user's characteristics, and that coordinates the intervention of a set of expert cognitive agents (such as story telling agents, assessment agents, stimulation agents or help agents). This InCA architecture has been applied for the design of K"InCA, an e-learning system aimed at helping people to learn and adopt knowledge-sharing management practices.

scholarly journals PRE-PROCESSED LATENT SEMANTIC ANALYSIS FOR AUTOMATIC ESSAY GRADING

Kursor ◽  
2017 ◽  
pp. 175 ◽  
Author(s):  
Ruth Ema Febrita ◽  
Wayan Firdaus Mahmudy
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Learning System ◽  
Semantic Meaning ◽  
Lexical Database ◽  
Java Programming ◽  
E Learning ◽  
Manual Processing ◽  
Essay Grading ◽  
High Order Thinking

In education, essay is considered as the best tool to evaluate student’s high order thinking and understanding. In the other hand, manual processing and grading essay answers by a teacher need much time and tending to subjectivity grading. Meanwhile automatic essay grading in e-learning system find the difficulties in comparing model or key answer to student’s answer because student’s can answer the question with so various way. That means a right answer also can be so various, for they have same semantic meaning. This paper proposed automatic essay grading using Latent Semantic Analysis. But before the texts being scored, they will be pre-processed using stop words removal and synonyms checking. Calibration process implemented for dealing with the various possible right answer and help to simplify the term matrix. Implementation of this approach using Java Programming Language and WordNet as lexical database for searching the synonyms of every given words. The accuracy obtained by this method is 54.9289%.

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