scholarly journals The research trends in recommender systems for e-learning

2019 ◽  
Vol 14 (1) ◽  
pp. 12-27
Author(s):  
Jiemin Zhong ◽  
Haoran Xie ◽  
Fu Lee Wang
Keyword(s):  
Learning Outcomes ◽  
Recommender Systems ◽  
Learning Systems ◽  
Learning System ◽  
Future Research ◽  
Content Type ◽  
Evaluation Indicator ◽  
Recommendation Algorithms ◽  
E Learning ◽  
Key Indicators

Purpose A recommendation algorithm is typically applied to speculate on users’ preferences based on their behavioral characteristics. The purpose of this paper is to provide a systematic review of recommendation systems by collecting related journal articles from the last five years (i.e. from 2014 to 2018). This paper aims to study the correlations between recommendation technologies and e-learning systems. Design/methodology/approach The paper reviews the relevant articles using five assessment aspects. A coding scheme was put forward that includes the following: the metrics for the e-learning system, the evaluation metrics for the recommendation algorithms, the recommendation filtering technology, the phases of the recommendation process and the learning outcomes of the system. Findings The research indicates that most e-learning systems will adopt the adaptive mechanism as a primary metric, and accuracy is a vital evaluation indicator for recommendation algorithms. In existing e-learning recommender systems, the most common recommendation filtering technology is hybrid filtering. The information collection phase is an important process recognized by most studies. Finally, the learning outcomes of the recommender system can be achieved through two key indicators: affections and correlations. Originality/value The recommendation technology works effectively in closing the gap between the information producer and the information consumer. This technology could help learners find the information they are interested in as well as send them a valuable message. The opportunities and challenges of the current study are discussed; the results of this study could provide a guideline for future research.

A sustainable quality assessment model for the information delivery in E-learning systems

2018 ◽  
Vol 46 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Shahid Farid ◽  
Rodina Ahmad ◽  
Mujahid Alam ◽  
Atif Akbar ◽  
Victor Chang
Keyword(s):  
Quality Assessment ◽  
State Of The Art ◽  
Statistical Tests ◽  
Information Delivery ◽  
Learning Systems ◽  
Learning System ◽  
Assessment Model ◽  
Content Type ◽  
E Learning

Purpose The purpose of this study is to propose a sustainable quality assessment approach (model) for the e-learning systems keeping software perspective under consideration. E-learning is becoming mainstream due to its accessibility, state-of-the-art learning, training ease and cost effectiveness. However, the poor quality of e-learning systems is one of the major causes of several failures reported. Moreover, this arena lacks well-defined quality assessment measures. Hence, it is quite difficult to measure the overall quality of an e-learning system effectively. Design/methodology/approach A pragmatic mixed-model philosophy was adopted for this study. A systematic literature review was performed to identify existing e-learning quality models and frameworks. Semi-structured interviews were conducted with e-learning experts following empirical investigations to identify the crucial quality characteristics of e-learning systems. Various statistical tests like principal component analysis, logistic regression, chi-square and analysis of means were applied to analyze the empirical data. These led to an adequate set of quality indicators that can be used by higher education institutions to assure the quality of e-learning systems. Findings A sustainable quality assessment model for the information delivery in e-learning systems in software perspective has been proposed by exploring the state-of-the-art quality assessment/evaluation models and frameworks proposed for the e-learning systems. The proposed model can be used to assess and improve the process of information discovery and delivery of e-learning. Originality/value The results obtained led to conclude that very limited attention is given to the quality of e-learning tools despite the importance of quality and its effect on e-learning system adoption and promotion. Moreover, the identified models and frameworks do not adequately address quality of e-learning systems from a software perspective.

An m-learning framework for ERP systems in higher education

2014 ◽  
Vol 11 (4) ◽  
pp. 287-301 ◽  
Author(s):  
Brenda Scholtz ◽  
Mando Kapeso
Keyword(s):  
Higher Education ◽  
Success Factors ◽  
Theoretical Framework ◽  
Learning Systems ◽  
Learning System ◽  
Erp Systems ◽  
Content Type ◽  
Erp System ◽  
E Learning ◽  
Learning Projects

Purpose – The purpose of this paper is to investigate the factors of m-learning approaches which can be used for enterprise resource planning (ERP) system training and to propose a theoretical framework for m-learning of ERP systems. Design/methodology/approach – A literature review of several theories relating to success factors for mobile learning (m-learning) and electronic learning (e-learning) are analysed and a theoretical framework of success factors for m-learning of ERP systems is proposed. Two field studies are undertaken to identify the features of e-learning and m-learning systems which users enjoyed and which related to the factors identified in the theoretical framework. The technology acceptance model (TAM) was used to evaluate the acceptance, usefulness and perceived ease of use (PEOU) of the two systems evaluated in the field study, the openSAP e-learning application and the SAP Learn Now m-learning application. Findings – The results confirmed several of the theoretical elements identified in the framework and the m-learning system was rated positively for PEOU and perceived usefulness (PU). The findings confirmed other studies showing the importance of the quality of course content in e-learning and m-learning projects. Research limitations/implications – The empirical study was limited to a small number of participants in higher education. However, a deeper understanding of the factors influencing m-learning for ERP systems was obtained. Practical implications – The study provides a valuable practical contribution because the framework can be used in the improved design of an ERP m-learning approach, which in turn can lead to an improvement in ERP training and education programmes and ultimately ERP project success. Originality/value – Several studies propose the use of m-learning systems. However, research related to the factors impacting on m-learning projects for ERP system training is limited. The paper presents original work and the results provide a valuable contribution to several theories of m-learning.

Digital learning approaches in an intermediate-level computer science course

2019 ◽  
Vol 36 (5) ◽  
pp. 467-484 ◽  
Author(s):  
Mikko Apiola ◽  
Erno Lokkila ◽  
Mikko-Jussi Laakso
Keyword(s):  
Computer Science ◽  
Learning Outcomes ◽  
Learning Analytics ◽  
Learning Systems ◽  
Intermediate Level ◽  
Future Research ◽  
Digital Learning ◽  
Learning Behaviour ◽  
Content Type ◽  
Practical Implications

Purpose Digital learning has become a global trend. Partly or fully automatic learning systems are integrated into education in schools and universities on a previously unseen scale. Learning systems have a lot of potential for re-education, life-long learning and for increasing access to educational resources. Learning systems create massive amounts of data about learning behaviour. Analysing that data for educational decision making has become an important track of research. The purpose of this paper is to analyse data from an intermediate-level computer science course, which was taught to 141 students in spring 2018 at University of Turku, Department of Future Technologies, Finland. Design/methodology/approach The available variables included number of submissions, submission times, variables of groupwork and final grades. Associations between these variables were looked at to reveal patterns in students’ learning behaviour. Findings It was found that time usage differs per different grades so that students with grade 4 out of 5 used most time. Also, it was found that studying at night is connected to weaker learning outcomes than studying during daytime. Several issues in relation to groupwork were revealed. For example, associations were found between prior skills, preference for individual vs groupwork, and course learning outcomes. Research limitations/implications The research was limited by the domain of available variables, which is a common limitation in learning analytics research. Practical implications The practical implications include important ideas for future research and interventions in digital learning. Social implications The importance of research on soft skills, social skills and collaboration is highlighted. Originality/value The paper points a number of important ideas for future research. One important observation is that some research questions in learning analytics need qualitative approaches, which need to be added to the toolbox of learning analytics research.

Will personalized e-Learning increase deep learning in higher education?

2019 ◽  
Vol 47 (1) ◽  
pp. 53-63 ◽  
Author(s):  
María Consuelo Sáiz-Manzanares ◽  
César Ignacio García Osorio ◽  
José Francisco Díez-Pastor ◽  
Luis Jorge Martín Antón
Keyword(s):  
Higher Education ◽  
Student Satisfaction ◽  
Learning Outcomes ◽  
Teaching Practice ◽  
Learning Management Systems ◽  
Learning System ◽  
Management Systems ◽  
Content Type ◽  
E Learning ◽  
Learning Management

PurposeRecent research in higher education has pointed out that personalized e-learning through the use of learning management systems, such as Moodle, improves the academic results of students and facilitates the detection of at-risk students.Design/methodology/approachA sample of 124 students following the Degree in Health Sciences at the University of Burgos participated in this study. The objectives were as follows: to verify whether the use of a Moodle-based personalized e-learning system will predict the learning outcomes of students and the use of effective learning behaviour patterns and to study whether it will increase student satisfaction with teaching practice.FindingsThe use of a Moodle-based personalized e-learning system that included problem-based learning (PBL) methodology predicted the learning outcomes by 42.3 per cent, especially with regard to the results of the quizzes. In addition, it predicted effective behavioural patterns by 74.2 per cent. Increased student satisfaction levels were also identified through the conceptual feedback provided by the teacher, arguably because it facilitated a deeper understanding of the subject matter.Research limitations/implicationsThe results of this work should be treated with caution, because of the sample size and the specificity of the branch of knowledge of the students, as well as the design type. Future studies will be directed at increasing the size of the sample and the diversity of the qualifications.Originality/valueLearning methodology in the twenty-first century has to be guided towards carefully structured work from the pedagogic point of view in the learning management systems allowing for process-oriented feedback and PBL both included in personalized e-learning systems.

Review of Data Mining Techniques and Parameters for Recommendation of Effective Adaptive E-Learning System

2017 ◽  
pp. 1-23 ◽  
Author(s):  
Renuka Mahajan
Keyword(s):  
Data Mining ◽  
Recommender System ◽  
Learning Systems ◽  
Learning System ◽  
Future Research ◽  
Comprehensive List ◽  
Research Areas ◽  
New Models ◽  
E Learning ◽  
Research Intensity

This chapter revolves around the synthesis of three research areas- data mining, personalization, recommendation systems and adaptive e-Learning systems. It also introduces a comprehensive list of parameters, extricated by reviewing the existing research intensity during the period of 2000 to October 2014, for understanding what should be essential parameters for adapting an e-learning. In general, we can consider and answer few questions to answer this body of literature ‘what' can be adapted? What can we adapt to? How do we adapt? This review tries to answer on ‘what' can be adapted. Thus, it advances earlier personalization studies. The gaps in the previous studies in building adaptive e-learning systems were also reviewed. It can help in designing new models for adaptation and formulating novel recommender system techniques. This will provide a foundation to industry experts and scientists for future research in adaptive e-learning.

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.

Evaluation of an IoT-based e-learning testbed

2017 ◽  
Vol 13 (1) ◽  
pp. 2-13 ◽  
Author(s):  
Masafumi Yamada ◽  
Miralda Cuka ◽  
Yi Liu ◽  
Tetsuya Oda ◽  
Keita Matsuo ◽  
...  
Keyword(s):  
Learning Systems ◽  
Learning System ◽  
Raspberry Pi ◽  
Delivery Ratio ◽  
Hop Count ◽  
Content Type ◽  
Link State ◽  
Constant Bit Rate ◽  
E Learning ◽  
Optimized Link State Routing

Purpose This paper aims to present the design and implementation of an Internet of Things (IoT)-based e-learning testbed using Raspberry Pi mounted on Raspbian operating system (OS). Design/methodology/approach The testbed is composed of five Raspberry Pi B+ computers. The experiments are carried out in the department floor considering an non line of sight (NLoS) environment. Single constant bit rate (CBR) flows were transmitted over user datagram protocol (UDP), and data were collected for five metrics: throughput, packet delivery ratio (PDR), hop count, delay and jitter using the Iperf. Findings The implemented testbed was evaluated using experiments. The experimental results showed that the nodes in the testbed were communicating smoothly, and by using attention value, the learner concentration is increased. Research limitations/implications The performance of the Optimized Link State Routing (OLSR) protocol was analyzed in a floor environment considering the NLoS scenario. However, this testbed can be implemented to other protocols also. Originality/value Because of the opportunities provided by the internet, people are taking advantage of e-learning courses, and enormous research efforts have been dedicated to the development of e-learning systems. To date, many e-learning systems are proposed and used practically. However, in these systems, the e-learning completion rate is low. To deal with this problem, an IoT-based e-learning system was implemented to increase the e-learning completion ratio by increasing the learner concentration.

A comprehensive literature review on the medical learning systems in the developing countries

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahdi Bohlouli ◽  
Omed Hassan Ahmed ◽  
Ali Ehsani ◽  
Marwan Yassin Ghafour ◽  
Hawkar Kamaran Hama ◽  
...  
Keyword(s):  
Developing Countries ◽  
Literature Review ◽  
The Body ◽  
Learning Systems ◽  
Learning System ◽  
Clinical Learning ◽  
Learning Mechanisms ◽  
Content Type ◽  
E Learning ◽  
Medical Learning

PurposeMany people have been dying as a result of medical errors. Offering clinical learning can lead to better medical care. Clinics have conventionally incorporated direct modality to teach personnel. However, they are now starting to take electronic learning (e-learning) mechanisms to facilitate training at work or other suitable places. The objective of this study is to identify and prioritize the medical learning system in developing countries. Therefore, this paper aims at describing a line of research for developing medical learning systems.Design/methodology/approachNowadays, organizations face fast markets' changing, competition strategies, technological innovations and accessibility of medical information. However, the developing world faces a series of health crises that threaten millions of people's lives. Lack of infrastructure and trained, experienced staff are considered essential barriers to scaling up treatment for these diseases. Promoting medical learning systems in developing countries can meet these challenges. This study identifies multiple factors that influence the success of e-learning systems from the literature. The authors have presented a systematic literature review (SLR) up to 2019 on medical learning systems in developing countries. The authors have identified 109 articles and finally selected 17 of them via article choosing procedures.FindingsThe paper has shown that e-learning systems offer significant advantages for the medical sector of developing countries. The authors have found that executive, administrative and technological parameters have substantial effects on implementing e-learning in the medical field. Learning management systems offer a virtual method of augmented and quicker interactions between the learners and teachers and fast efficient instructive procedures, using computer and Internet technologies in learning procedures and presenting several teaching-learning devices.Research limitations/implicationsThe authors have limited the search to Scopus, Google Scholar, Emerald, Science Direct, IEEE, PLoS, BMC and ABI/Inform. Many academic journals probably provide a good picture of the related articles, too. This study has only reviewed the articles extracted based on some keywords such as “medical learning systems,” “medical learning environment” and “developing countries.” Medical learning systems might not have been published with those specific keywords. Also, there is a requirement for more research with the use of other methodologies. Lastly, non-English publications have been removed. There could be more potential related papers published in languages other than English.Practical implicationsThis paper helps physicians and scholars better understand the clinical learning systems in developing countries. Also, the outcomes can aid hospital managers to speed up the implementation of e-learning mechanisms. This research might also enable the authors to have a role in the body of knowledge and experience, so weakening the picture of the developing country's begging bowl is constantly requesting help. The authors hoped that their recommendations aid clinical educators, particularly in developing countries, adopt the trends in clinical education in a changing world.Originality/valueThis paper is of the pioneers systematically reviewing the adoption of medical learning, specifically in developing countries.

Student learning outcomes and online engagement in time of crisis: the role of e-learning system usability and teacher behavior

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khalid Abed Dahleez ◽  
Ayman A. El-Saleh ◽  
Abrar Mohammed Al Alawi ◽  
Fadi Abdel Muniem Abdel Fattah
Keyword(s):  
Learning Outcomes ◽  
Teacher Behavior ◽  
Learning System ◽  
Equation Modeling ◽  
Research Approach ◽  
Content Type ◽  
Online Engagement ◽  
System Usability ◽  
E Learning

PurposeThis research explores the effect of e-learning Moodle-based system usability on students' learning outcomes with the possible intervening role of teacher's behavior and online engagement.Design/methodology/approachIn this research, the authors followed a quantitative methodology and a deductive research approach. Data were collected from 433 students at different study levels and academic specializations in higher education institutions (HEIs) in Oman. The data have been analyzed using partial least squares structural equation modeling via Smart-PLS.FindingsThe findings of this research show that e-learning system usability affects students' learning outcomes. Moreover, the relationship between these two variables is mediated by teacher behavior and students' online engagement.Originality/valueThis study is important as it adds to the understanding of the role of e-learning system usability in predicting student outcomes. From practical perspectives, especially during the spread of the COVID-19 pandemic, this study also helps practitioners at private HEIs use e-learning systems more efficiently and effectively to improve students' engagement and learning outcomes.

The Role of Multi-Agent Social Networking Systems in Ubiquitous Education

2010 ◽  
pp. 72-88 ◽  
Author(s):  
Jonathan Bishop
Keyword(s):  
Social Networking ◽  
Information Science ◽  
Learning Systems ◽  
Learning System ◽  
Future Research ◽  
System A ◽  
E Learning ◽  
Multi Agent ◽  
Social Networking Technology ◽  
Networks Of Practice

Knowledge it could be argued is constructed from the information actors pick up from the environments they are in. Assessing this knowledge can be problematic in ubiquitous e-learning systems, but a method of supporting the critical marking of e-learning exercises is the Circle of Friends social networking technology. Understanding the networks of practice in which these e-learning systems are part of requires a deeper understanding of information science frameworks. The Ecological Cognition Framework (ECF) provides a thorough understanding of how actors respond to and influence their environment. Forerunners to ecological cognition, such as activity theory have suggested that the computer is just a tool that mediates between the actor and the physical environment. Utilising the ECF it can be seen that for an e-learning system to be an effective teacher it needs to be able to create five effects in the actors that use it, with those being the belonging effect, the demonstration effect, the inspiration effect, the mobilisation effect, and the confirmation effect. In designing the system a developer would have to consider who the system is going to teach, what it is going to teach, why it is teaching, which techniques it is going to use to teach and finally whether it has been successful. This chapter proposes a multi-agent e-learning system called the Portable Assistant for Intelligently Guided Education (PAIGE), which is based around a 3D anthropomorphic avatar for educating actors ubiquitously. An investigation into the market for PAIGE was carried out. The data showed that those that thought their peers were the best form of support were less likely to spend more of their free time on homework. The chapter suggests that future research could investigate the usage of systems like PAIGE in educational settings and the effect they have on learning outcomes.

Sign in / Sign up

Export Citation Format

Share Document