scholarly journals Investigation of Emerging Trends in the E-Learning Field Using Latent Dirichlet Allocation

2021 ◽  
Vol 22 (2) ◽  
pp. 1-18
Author(s):  
Fatih Gurcan ◽  
Ozcan Ozyurt ◽  
Nergiz Ercil Cagitay
Keyword(s):  
Adaptive Learning ◽  
Teaching And Learning ◽  
Latent Dirichlet Allocation ◽  
High Volume ◽  
Learning Systems ◽  
Mobile Platforms ◽  
Emerging Trends ◽  
E Learning ◽  
Learning Factors ◽  
Dirichlet Allocation

E-learning studies are becoming very important today as they provide alternatives and support to all types of teaching and learning programs. The effect of the COVID-19 pandemic on educational systems has further increased the significance of e-learning. Accordingly, gaining a full understanding of the general topics and trends in e-learning studies is critical for a deeper comprehension of the field. There are many studies that provide such a picture of the e-learning field, but the limitation is that they do not examine the field as a whole. This study aimed to investigate the emerging trends in the e-learning field by implementing a topic modeling analysis based on latent Dirichlet allocation (LDA) on 41,925 peer-reviewed journal articles published between 2000 and 2019. The analysis revealed 16 topics reflecting emerging trends and developments in the e-learning field. Among these, the topics “MOOC,” “learning assessment,” and “e-learning systems” were found to be key topics in the field, with a consistently high volume. In addition, the topics of “learning algorithms,” “learning factors,” and “adaptive learning” were observed to have the highest overall acceleration, with the first two identified as having a higher acceleration in recent years. Going by these results, it is concluded that the next decade of e-learning studies will focus on learning factors and algorithms, which will possibly create a baseline for more individualized and adaptive mobile platforms. In other words, after a certain maturity level is reached by better understanding the learning process through these identified learning factors and algorithms, the next generation of e-learning systems will be built on individualized and adaptive learning environments. These insights could be useful for e-learning communities to improve their research efforts and their applications in the field accordingly.

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.

A Survey on the Use of Adaptive Learning Techniques Towards Learning Personalization

2021 ◽  
pp. 790-808
Author(s):  
Sonali Banerjee ◽  
Kaustuv Deb ◽  
Atanu Das ◽  
Rajib Bag
Keyword(s):  
Learning Strategies ◽  
Adaptive Learning ◽  
Teaching And Learning ◽  
Problem Area ◽  
Learning Technology ◽  
Individual Learner ◽  
Learning Techniques ◽  
Teaching And Learning Strategies ◽  
Recent Developments ◽  
E Learning

E-learning has a great impact on learners today. E-learning supports enhancing learner knowledge anytime, anywhere with lesser efforts than traditional models. In these situations, nonlinear approaches often modify teaching and learning strategies according to students' needs, and hence, automated machine-guided approaches seem useful in the name of adaptive learning. It identifies individual learner styles and provides the most suitable strategy that fits each learner as a case of personalization. Adaptive learning uses personalization for continuously improving student outcomes. Personalized learning takes place when e-learning systems use educational experience supporting desires, objectives, endowments, and curiosities of each individual learner. This work has reviewed the recent developments in the problem area of learning personalization through adaptive learning. Then the solution domain methods are compared to identify the knowledge and technology gap from their limitations. These analyses help to identify research potentials in learning technology for future works.

PAUL

2010 ◽  
pp. 173-186 ◽  
Author(s):  
Charoula Angeli ◽  
George Veletsianos
Keyword(s):  
Teacher Development ◽  
Teaching And Learning ◽  
Virtual Communities ◽  
Learning Systems ◽  
Pedagogical Content ◽  
Computer Based Learning ◽  
Body Of Knowledge ◽  
Content Domain ◽  
E Learning ◽  
Virtual Communities Of Practice

Adaptive e-learning systems can be extremely valuable tools in developing innovative learner-centered environments in any content domain. One area that can benefit greatly from adaptive e-learning systems is teacher development in the educational uses of computers. In this chapter, we discuss the design of PAUL, an adaptive computer-based learning environment for the development of ICT-related pedagogical content knowledge, a unique body of knowledge that teachers need to develop in order to be able to teach with ICT. PAUL combines two opposing trends in adapting instruction, namely instruction that is both controlled by the learner and the system. We expect the impact of PAUL to be significant as it will provide a venue for effective teacher professional development situating learning in virtual communities of practice and supporting teacher thinking about the educational uses of ICT in teaching and learning.

scholarly journals An Approach to Smart Study using Pen and Paper Learning

2017 ◽  
Vol 12 (05) ◽  
pp. 117
Author(s):  
Ahmad Tasnim Siddiqui ◽  
Mohd Muntjir
Keyword(s):  
Teaching And Learning ◽  
New Technologies ◽  
Traditional Education ◽  
Learning Systems ◽  
Digital Format ◽  
Smart Study ◽  
Digital Contents ◽  
E Learning ◽  
Traditional Manner

With the emergence of new technologies the area of education is also growing very fast. By using new innovations teaching and learning has become technically very strong. Learning is becoming tech learning or e-learning. Educators and students are getting very smart and hence study and learning is also becoming smart. Maximum available learning systems don’t involve pen and paper based learning. Due to the emergence of ICTs in the learning atmosphere it doesn’t indicate that our traditional education methodologies have become outdated. Smart study is such a stage which allows students continue to learn in smart way by using smart pens and papers. Using smart paper and pen the contents written on the paper can be converted into digital format. Smart study using pen and paper is helpful for practicing handwriting in same traditional manner. This paper presents a smart study platform which combines work with printed and digital contents.

scholarly journals Modern Probabilistic Model: Filtering Massive Data in E-learning

2021 ◽  
pp. 52-58
Author(s):  
Hachem Harouni Alaoui ◽  
Elkaber Hachem ◽  
Cherif Ziti
Keyword(s):  
Machine Learning ◽  
Probabilistic Model ◽  
Latent Dirichlet Allocation ◽  
Web Pages ◽  
Massive Data ◽  
Learning Session ◽  
Learning Procedure ◽  
E Learning ◽  
Dirichlet Allocation

So muchinformation keeps on being digitized and stored in several forms, web pages, scientific articles, books, etc. so the mission of discovering information has become more and more challenging. The requirement for new IT devices to retrieve and arrange these vastamounts of informationaregrowing step by step. Furthermore, platforms of e-learning are developing to meet the intended needsof students.The aim of this article is to utilize machine learning to determine the appropriate actions that support the learning procedure and the Latent Dirichlet Allocation (LDA) so as to find the topics contained in the connections proposed in a learning session. Ourpurpose is also to introduce a course which moves toward the student's attempts and which reduces the unimportant recommendations (Which aren’t proper to the need of the student grown-up) through the modeling algorithms of the subjects.

Artificial Intelligence Methods in E-Learning

2019 ◽  
pp. 287-307
Author(s):  
Meltem Eryılmaz ◽  
Afaf Muftah Adabashi ◽  
Ali Yazıcı
Keyword(s):  
Artificial Intelligence ◽  
Teaching And Learning ◽  
Intelligent Tutoring ◽  
Learning Systems ◽  
Educational Systems ◽  
Educational Materials ◽  
Tutoring Systems ◽  
Challenges And Opportunities ◽  
E Learning ◽  
Effective Teaching And Learning

Gathering and extracting knowledge from the large amount of data available today is becoming more and more important in our information society, and similarly, learning is an essential important part of our everyday lives. The new requirements of the competing world and the development of more advanced technologies have also changed traditional educational systems, which now employ better and more effective teaching and learning methods. In this regard, the integration of artificial intelligence (AI) technologies in the field of education offers both great challenges and opportunities in building e-learning systems. E-learning systems allow learners to access the educational materials ubiquitously from anywhere at any time. Therefore, these systems have to become adaptive to the needs and preferences of each individual learner. This chapter presents a review of the important concepts and background for research to include introduction and examination of e-learning systems and intelligent tutoring systems (ITSs), available today.

The Preliminary Investigation of the Factors that Influence the E-Learning Adoption in Higher Education Institutes

2010 ◽  
Vol 8 (4) ◽  
pp. 1-11 ◽  
Author(s):  
Maen Al-hawari ◽  
Sanaa Al-halabi
Keyword(s):  
High Performance ◽  
Preliminary Investigation ◽  
Learning Systems ◽  
Educational Institutions ◽  
Traditional Learning ◽  
Web Content ◽  
Analysis Software ◽  
E Learning ◽  
And Performance ◽  
Learning Factors

Creativity and high performance in learning processes are the main concerns of educational institutions. E-learning contributes to the creativity and performance of these institutions and reproduces a traditional learning model based primarily on knowledge transfer into more innovative models based on collaborative learning. In this paper, the authors focus on the preliminary investigation of factors that influence e-learning adoption in Jordan. As a pioneer country for e-learning systems in the Middle East, an investigation has been completed for one of Jordan’s universities that has implemented e-learning. Factors are defined through the analysis of unstructured interviews with developers and users of the e-learning systems, and Leximancer content analysis software is used to analyze the interview’s content. Main factors include Internet, legislations, human factors, and Web content.

scholarly journals An Assessment of E-Learning System for Instructors and Students of Panpacific University

2018 ◽  
Vol 1 (1) ◽  
pp. 63-70
Author(s):  
Jane M. Fernandez ◽  
Gina Lee M. Santos ◽  
Wennielyn C. Javier
Keyword(s):  
Student Learning ◽  
User Satisfaction ◽  
Teaching And Learning ◽  
Vital Role ◽  
Learning Systems ◽  
Learning System ◽  
E Learning ◽  
The Impact ◽  
Computer Studies ◽  
Positive Effect

Through teaching innovations, E-learning play a vital role in education. The researcher attests by determining the e-learning systems influence on students and instructors. In order to know the perceptions of the students and Instructors the researcher conducted a survey regarding their current experiences. The main purpose of the study was to investigate the impact of elearning used by the School of Computer Studies at Panpacific University. This study will detail the e-learning impacts which had on Instructors and Student participant’s performance about the level of user satisfaction and productivity, utilization and problems encountered. The study found out that the use of e-learning systems shows a positive effect on student learning. Instructors utilized e-learning system as presentation and preparation tool in teaching and learning. Most instructors positively confirm that e-learning supports teaching and learning effectively implemented.

scholarly journals Preparing Students for Success in a Changing World: The Role of Virtual Whiteboards in the Modern Classroom

2021 ◽  
Author(s):  
Kevin Fuchs
Keyword(s):  
Higher Education ◽  
Active Learning ◽  
Undergraduate Students ◽  
Teaching And Learning ◽  
Learning Systems ◽  
Information Communication ◽  
E Learning ◽  
Changing World

Information communication and technologies (ICT) as a facilitator of active learning (AL) in higher education is becoming an increasingly important tool. One of the most significant developments with the use of ICT in higher education over the last decade has been the integration and application of e-learning systems to support the processes of teaching and learning. The implementation of ICT into the classroom should not be seen as merely an add-on, but should be included with purpose: meaningfully implemented based on pedagogy. Despite the suggested power of ICT in educating students for a modern future, the implementation of these technologies into the classroom is not as widespread as expected; debate still abounds as to what role ICT should play in the classroom. This research examined a variety of dependable attributes that assessed the engagement of undergraduate students (n1=87) through virtual whiteboards. This quantitative inquiry revealed that students perceived virtual whiteboards as beneficial for their learning and improved their engagement level in the classroom. Furthermore, a correlation between the level of engagement and the year of study was revealed as the primary implication of this research.

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