Generating adaptive learning paths in e-learning environments

2012 ◽  
Author(s):  
Irma Gamez Suazo ◽  
Cesar Garita Rodriguez ◽  
Mario Chacon Rivas
Keyword(s):  
Learning Environments ◽  
Adaptive Learning ◽  
E Learning ◽  
Learning Paths

Authoring Adaptive 3D Virtual Learning Environments

2016 ◽  
pp. 714-733 ◽  
Author(s):  
Ahmed Ewais ◽  
Olga De Troyer
Keyword(s):  
Virtual Reality ◽  
Learning Environments ◽  
Adaptive Learning ◽  
Virtual Learning ◽  
Learning Technologies ◽  
Virtual Learning Environments ◽  
Authoring Tool ◽  
E Learning ◽  
Adaptive Learning Environment ◽  
3D Virtual Learning Environments

The use of 3D and Virtual Reality is gaining interest in the context of academic discussions on E-learning technologies. However, the use of 3D for learning environments also has drawbacks. One way to overcome these drawbacks is by having an adaptive learning environment, i.e., an environment that dynamically adapts to the learner and the activities that he performs in the environment. In this paper, the authors discuss adaptive 3D virtual leaning environments and explain how a course author can specify such an environment (i.e., authoring). The approach and tool that the authors present allow authors to create adaptive 3D virtual learning environments without the need to be an expert in 3D or using programming or scripting languages. The authors also conducted an evaluation to validate the approach and the usability and acceptability of the authoring tool. Based on the results, recommendations for authoring adaptive 3D virtual learning environments have been formulated.

A Strategy to Join Adaptive and Reputation-Based Social-Collaborative E-Learning, Through the Zone of Proximal Development

2013 ◽  
Vol 11 (3) ◽  
pp. 12-31 ◽  
Author(s):  
Maria De Marsico ◽  
Andrea Sterbini ◽  
Marco Temperini
Keyword(s):  
Collaborative Learning ◽  
Adaptive Learning ◽  
Zone Of Proximal Development ◽  
Learning Activities ◽  
Proximal Development ◽  
Student Model ◽  
Web Based ◽  
E Learning ◽  
Learning Paths ◽  
The One

The educational concept of “Zone of Proximal Development”, introduced by Vygotskij, stems from the identification of a strong need for adaptation of the learning activities, both traditional classroom and modern e-learning ones, to the present state of learner’s knowledge and abilities. Furthermore, Vygotskij’s educational model includes a strong bent towards social and collaborative learning. The joint answer to these two trends can be concretely implemented through a tight integration between personalized learning paths and collaborative learning activities. Along this line, the authors designed the combination of the functions of two pre-existing prototypes of web-based systems, to investigate how the above integration can merge adaptive and social e-learning. LECOMPS is a web-based e-learning environment for the automated construction of adaptive learning paths. SOCIALX is a web-based system for shared e-learning activities, which implements a reputation system to provide feedback to its participants. The authors propose a two-way tunneling strategy to integrate the above prototypes. The result is twofold: on the one hand the use of the student model supported by LECOMPS in an adaptive e-learning course is extended to support choosing exercise activities delivered through SOCIALX; on the other hand the reputation and the skills gained during social-collaborative activities are used to update the student model. Under the social perspective induced by the integration, the authors present a mapping between the student model and the definition of Vygotskij’s Autonomous Problem Solving and Proximal Development regions, with the aim to provide the learner with better guidance, especially in the selection of available social learning activities.

Educational Technology Standards

2011 ◽  
pp. 413-425
Author(s):  
Michael O’Dea
Keyword(s):  
Learning Environments ◽  
Adaptive Learning ◽  
Educational Program ◽  
Approaches To Learning ◽  
Technology Standards ◽  
Learning Models ◽  
Student Records ◽  
Teaching Institution ◽  
E Learning ◽  
Pedagogical Approaches

The “holy grail” of e-learning is to enable individualized, flexible, adaptive learning environments that support different learning models or pedagogical approaches to learning to allow any Internet-connected user to undertake an educational program. It is also very highly desirable, from a more practical viewpoint, if this environment can also integrate into the wider MIS/student records system of the teaching institution.

Educational Technology Standards

2011 ◽  
pp. 247-256
Author(s):  
Michael O’Dea
Keyword(s):  
Learning Environments ◽  
Adaptive Learning ◽  
Educational Program ◽  
Approaches To Learning ◽  
Technology Standards ◽  
Learning Models ◽  
Student Records ◽  
Teaching Institution ◽  
E Learning ◽  
Pedagogical Approaches

The “holy grail” of e-learning is to enable individualized, flexible, adaptive learning environments that support different learning models or pedagogical approaches to learning to allow any Internet-connected user to undertake an educational program. It is also very highly desirable, from a more practical viewpoint, if this environment can also integrate into the wider MIS/student records system of the teaching institution.

. Learning analytics technology in adaptive electronic learning environments.

2021 ◽  
Vol 92 (2) ◽  
pp. 144-153
Author(s):  
M.R. Attia ◽  
Keyword(s):  
Learning Styles ◽  
Learning Environments ◽  
Adaptive Learning ◽  
Learning Analytics ◽  
Rapid Identification ◽  
Electronic Learning ◽  
E Learning ◽  
Mental Abilities ◽  
The Difference ◽  
As If

Adaptive e-learning environments are based on diversifying the presentation of content according to the learning styles of each learner, where the content is presented as if it is directed to each student separately, and activities and tests are presented so that they are sensitive to the different styles of learners and suitable for their mental abilities. These environments depend in their design on intelligence, therefore, these environments can analyze the characteristics and capabilities of learners, each separately, and this is done through learning analytics technology that helps in the rapid identification of the patterns of learners and the development of their behavior within the environment. In this article, firstly we review what adaptive learning environments and its characteristics are; the difference between adaptable and adaptive environments; components of adaptive learning environments. Learning analytics technology is also highlighted; and its importance in adaptive e-learning environments.

Adaptive E-Learning Environments

2013 ◽  
Vol 11 (3) ◽  
pp. 1-11 ◽  
Author(s):  
Pierpaolo Di Bitonto ◽  
Teresa Roselli ◽  
Veronica Rossano ◽  
Maria Sinatra
Keyword(s):  
Distance Learning ◽  
Learning Environments ◽  
Recommender System ◽  
Adaptive Learning ◽  
Multi Agent System ◽  
Agent System ◽  
Educational Environments ◽  
E Learning ◽  
Multi Agent ◽  
Learning Research

One of the most closely investigated topics in e-learning research has always been the effectiveness of adaptive learning environments. The technological evolutions that have dramatically changed the educational world in the last six decades have allowed ever more advanced and smarter solutions to be proposed. The focus of this paper is to depict the three main dimensions that have driven research in the e-learning field and the evolution of the technological approaches adopted for the purposes of building advanced educational environments for distance learning. Then, the three different approaches adopted by the authors are discussed; these consist of a multi-agent system, an adaptive SCORM compliant package and an e-learning recommender system.

scholarly journals A Survey of Artificial Intelligence Techniques Employed for Adaptive Educational Systems within E-Learning Platforms

2017 ◽  
Vol 7 (1) ◽  
pp. 47-64 ◽  
Author(s):  
Khalid Colchester ◽  
Hani Hagras ◽  
Daniyal Alghazzawi ◽  
Ghadah Aldabbagh
Keyword(s):  
Artificial Intelligence ◽  
Learning Environments ◽  
Learning Process ◽  
Adaptive Learning ◽  
Educational Systems ◽  
Artificial Intelligence Techniques ◽  
Learning Capabilities ◽  
E Learning ◽  
Learning Platforms ◽  
Adaptive Educational Systems

Abstract The adaptive educational systems within e-learning platforms are built in response to the fact that the learning process is different for each and every learner. In order to provide adaptive e-learning services and study materials that are tailor-made for adaptive learning, this type of educational approach seeks to combine the ability to comprehend and detect a person’s specific needs in the context of learning with the expertise required to use appropriate learning pedagogy and enhance the learning process. Thus, it is critical to create accurate student profiles and models based upon analysis of their affective states, knowledge level, and their individual personality traits and skills. The acquired data can then be efficiently used and exploited to develop an adaptive learning environment. Once acquired, these learner models can be used in two ways. The first is to inform the pedagogy proposed by the experts and designers of the adaptive educational system. The second is to give the system dynamic self-learning capabilities from the behaviors exhibited by the teachers and students to create the appropriate pedagogy and automatically adjust the e-learning environments to suit the pedagogies. In this respect, artificial intelligence techniques may be useful for several reasons, including their ability to develop and imitate human reasoning and decision-making processes (learning-teaching model) and minimize the sources of uncertainty to achieve an effective learning-teaching context. These learning capabilities ensure both learner and system improvement over the lifelong learning mechanism. In this paper, we present a survey of raised and related topics to the field of artificial intelligence techniques employed for adaptive educational systems within e-learning, their advantages and disadvantages, and a discussion of the importance of using those techniques to achieve more intelligent and adaptive e-learning environments.

Open Learner Modelling as the Keystone of the Next Generation of Adaptive Learning Environments

2011 ◽  
pp. 288-312 ◽  
Author(s):  
Rafael Morales ◽  
Nicolas Van Labeke ◽  
Paul Brna ◽  
María Elena Chan
Keyword(s):  
Learning Environments ◽  
Adaptive Learning ◽  
Critical Role ◽  
Learner Characteristics ◽  
Learner Model ◽  
E Learning ◽  
Learner Modelling ◽  
Set Up ◽  
Intelligent Learning Environments ◽  
Modelling Process

It is believed that, with the help of suitable technology, learners and systems can cooperate in building a sufficiently accurate learner model they can use to promote learner reflection through discussion of their knowledge, preferences and motivational dispositions (among other learner characteristics). Open learner modelling is a technology that can help set up this discussion by giving the learners a representation of aspects of the learner as “believed” by the system. In this way/role, open learner modelling can perform a critical role in a new breed of intelligent learning environments driven by the aim to support the development of self-management, signification, participation and creativity in learners. In this chapter we provide an analysis of the migration of open learner modelling technology to common e-learning settings, the implications for modern e-learning systems in terms of adaptations to support the open learner modelling process,

Authoring Adaptive 3D Virtual Learning Environments

2014 ◽  
Vol 5 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Ahmed Ewais ◽  
Olga De Troyer
Keyword(s):  
Virtual Reality ◽  
Learning Environment ◽  
Learning Environments ◽  
Adaptive Learning ◽  
Virtual Learning ◽  
Learning Technologies ◽  
Virtual Learning Environments ◽  
E Learning ◽  
Adaptive Learning Environment ◽  
3D Virtual Learning Environments

The use of 3D and Virtual Reality is gaining interest in the context of academic discussions on E-learning technologies. However, the use of 3D for learning environments also has drawbacks. One way to overcome these drawbacks is by having an adaptive learning environment, i.e., an environment that dynamically adapts to the learner and the activities that he performs in the environment. In this paper, the authors discuss adaptive 3D virtual leaning environments and explain how a course author can specify such an environment (i.e., authoring). The approach and tool that the authors present allow authors to create adaptive 3D virtual learning environments without the need to be an expert in 3D or using programming or scripting languages. The authors also conducted an evaluation to validate the approach and the usability and acceptability of the authoring tool. Based on the results, recommendations for authoring adaptive 3D virtual learning environments have been formulated.

Sign in / Sign up

Export Citation Format

Share Document