E-learning System Research Articles

Implementing Problem-Based Learning in Marketing Education: A Systematic Review and Analysis

The marketing industry is rapidly evolving, prompting educational programs to adapt and provide graduates with relevant skills and knowledge. This systematic literature review and bibliometric analysis (SLRBA) explores the incorporation of problem-based learning (PBL) in marketing education. PBL is a teaching approach that encourages students to solve real-world problems by integrating theory and practice, thereby improving their critical thinking and decision-making skills. Our review synthesizes data from 71 sources, detailing the definition of PBL, strategies for its implementation in marketing education, and the associated benefits and challenges. The findings show that PBL enhances student engagement, provides hands-on experience, and equips students for real-world marketing challenges. Effective strategies for PBL adoption include leveraging social media, serious games, E-learning, and feedback systems to facilitate active learning and student participation. However, PBL poses challenges, such as high resource requirements, student resistance, and concerns over information accuracy. This review underscores the importance of PBL in closing the gap between theoretical concepts and practical skills, helping marketing students better meet industry expectations. The paper concludes with suggestions for future research and best practices for integrating PBL in marketing education.

Analysis of user satisfaction of e-learning systems in Uganda using DeLone and McLean model

Analysis of user satisfaction of e-learning systems in Uganda using DeLone and McLean model

Influence of region, experience, and subjective norm on the use of e-learning: Lesson from the insurance industry in Indonesia

The effectiveness and efficiency of e-learning system in industry significantly depend on users’ acceptance and adoption. This is specifically determined by external and internal factors represented by subjective norms (SN) and experience (XP), both believed to affect users’ perceived usefulness (PU) and perceived ease of use (PEOU). Users’ acceptance of e-learning system is influenced by the immensity of region, often hampered by inadequate infrastructure support. Therefore, this study aimed to investigate behavioral intention to use e-learning in the Indonesian insurance industry by applying Technology Acceptance Model (TAM). To achieve this objective, Jabotabek and Non-Jabotabek regions were used as moderating variables in all related hypotheses. An online survey was conducted to obtain data from 800 respondents who were Indonesian insurance industry employees. Subsequently, Structural Equation Model (SEM) was used to evaluate the hypotheses, and Multi-Group Analysis (MGA) to examine the role of region. The results showed that out of the seven hypotheses tested, only one was rejected. Furthermore, XP had no significant effect on PU, and the most significant correlation was found between PEOU and PU. In each relationship path model, the role of region (Jabodetabek and Non Jabodetabek) had no significant differences. These results were expected to provide valuable insights into the components of e-learning acceptability for the development of a user-friendly system in the insurance industry.

Saudi (EFL) Learners’ Attitudes Toward Google Sites E-portfolio Systems in Relation to Their Language Learning Motivation

Electronic portfolios have emerged as an essential element of e-learning systems in the Saudi educational system, particularly in higher education. Google Sites e-portfolios enable prompt sharing of assignments and foster reflection and collaboration among students and instructors. The aim of this study is to investigate Saudi female EFL students’ attitudes toward the Google Sites e-portfolio system in relation to language learning motivation. The sample comprised 138 EFL female Saudi students. The participants were enrolled in an English advanced course and were required to submit an e-portfolio as part of a course assessment. A quantitative research approach was employed. Data were collected through questionnaires. Descriptive statistics, means, standard deviation, and correlation were conducted. The study revealed that the learners showed positive attitudes toward the ease of use of Google’s e-portfolio system. Furthermore, they perceived it as a valuable tool, recognizing its usefulness in facilitating timely submissions, effective feedback, and reflective learning. The study also found a positive correlation between learners’ attitudes toward the system and their language learning motivation; a stronger correlation was observed for instrumental motivation. The study highlighted the significant educational value of Google e-portfolios and indicated possibilities for educators to enhance learners’ experiences by tackling current obstacles and promoting motivation. Educators should encourage the use of the Google Sites e-portfolio system for reflective practices and highlight its useful features. They should also focus on students’ language learning motivation, which affects attitudes toward technology implementation. Educational institutions should enhance students’ comprehension of the system through focused instruction, workshops, and peer assistance.

Developing and evaluating an e-learning and e-assessment tool for organic chemistry in higher education

A convincing e-learning system for higher education should offer adequate usability and not add unnecessary (extraneous) cognitive load. It should allow teachers to switch easily from traditional teaching to flipped classrooms to provide students with more opportunities to learn and receive immediate feedback. However, an efficient e-learning and technology-enhanced assessment tool that allows generating digital organic chemistry tasks is yet to be created. The Universities of Bonn and Duisburg-Essen are currently developing and evaluating an e-learning and technology-enhanced assessment tool for organic chemistry. This study compares the effectiveness of traditional paper-pencil-based and digital molecule-drawing tasks in terms of student performance, cognitive load, and usability—factors that all contribute to learning outcomes. Rasch analysis, t-tests, and correlation analyses were used for evaluation, revealing that the developed system can generate digital organic chemistry tasks. Students performed equally well on simple digital and paper-pencil molecule-drawing tasks when they received an appropriate introduction to the digital tool. However, using the digital tool in two of three studies imposes a higher extraneous cognitive load than using paper and pencil. Nevertheless, the students rated the tool as sufficiently usable. A significant negative correlation between extraneous load and tool usability was found, suggesting room for improvement. We are currently concentrating on augmenting the functionality of the new e-learning tool to increase its potential for automatic feedback, even for complex tasks such as reaction mechanisms.

Sustainable Adoption of E-Learning in Romanian Universities after the COVID-19 Outbreak

The COVID-19 pandemic disrupted economic processes and various facets of daily life, including education, necessitating adjustments to help society adapt to the temporary status quo, with Romanian educational institutions being profoundly affected, and a full transition to online learning was mandated by central authorities in March 2020. The paper’s scope is to assess the sustainability of e-learning in Romanian higher education in the aftermath of the COVID-19 outbreak. The study was conducted on bachelor students from three Romanian universities through an online questionnaire with a sample size of 505 valid responses. This study aims to investigate the relationships between information quality (IQ), system quality (SQ), service quality (SEQ), and quality of life (QL) within an integrated model, based on the variables of the technology acceptance model (TAM) and performance models of information systems (IS). Specifically, the research explores how these factors, along with the mediating roles of perceived usefulness (PU) and perceived ease of use (PEOU), influence students’ behavioral intention to adopt e-learning systems (BISE) and actual use of them (EUOES) as a sustainable solution for post-pandemic COVID-19 education. Partial least squares structural equation modeling (PLS–SEM) was the selected method for data analysis performed with SmartPLS 4.0 software. The research results demonstrated that PU and PEOU showed a positive correlation relationship and were significantly influenced by IQ, SQ, and QL in the educational setting. The study also revealed that PEOU and PU exerted a positive influence on students’ behavioral intention to adopt e-learning systems (BISE) sustainably and on their actual use (EUOES). This study benefits universities and higher education institutions by providing insights into enhancing e-learning platforms and integrating technology effectively, as well as by supporting the formulation of sustainable online learning strategies beyond the COVID-19 pandemic.

Evaluating the Success of Learning Management Systems using the EESS Model and Expected Confirmation Theory

E-learning and LMS (Learning Management Systems) have been implemented in most universities to modernize learning and assist in the learning process of university students. This study aims to explore the factors that can be used to measure e-learning system success using the EESS (Evaluating E-learning System Success) model and Expectation and Confirmation Theory (ECT). A quantitative research method was employed, using questionnaires to collect data on users’ perceptions of LMS. The collected data were then statistically analyzed using the PLS-SEM method with SmartPLS 3.2.9. Results revealed that out of 29 hypotheses, 16 were accepted and 13 were rejected. A novel discovery was that ECT can be implemented in the EESS model. Three hypotheses involving expectation confirmation had p-values of 0.001, 0.000, and 0.000, indicating significant roles. The study concluded that incorporating expectation confirmation quality into the EESS model enhances its effectiveness by providing a comprehensive perspective.

Implementation of independent learning campus independent certified internship program for strengthening 21st century skills

Implementation of the Merdeka Belajar Campus Merdeka Certified Internship Program in Strengthening 21st Century Skills is a way to strengthen skills in using media information as well as career and life skills. The aim of this research is to; (1) Describe the implementation of the MBKM certified internship program in universities, (2) Describe the mastery of 21st century skills among students participating in certified internships. This research is qualitative research with an analytical study approach. The results of this research show that first, in the implementation of MBKM, the certified internship program was implemented in three areas of activity, namely marketing, finance and operations, both in banking and companies. In implementing a certified internship, there are several stages, namely conversion of 20 credits, internship activities for 18 weeks, experience in the world of work and the professional world, a series of skills, mentoring, and obtaining a certificate of recognition for the skills and experience gained. Apart from that, during the implementation of the certified internship program there is an evaluation. Evaluation is carried out by following up on reports, providing mentoring, checking recaps of internship activities, sharing lessons, and conducting a final assessment of student performance. Second, the mastery of 21st century skills by students participating in certified internships focuses on the skills of mastering the use of technology, including the use of marketplace applications, the use of Microsoft office applications, the use of e-learning systems, e-commerce, design and so on. Meanwhile, mastery of career abilities and life skills is carried out through strengthening adaptation and social abilities, productivity and accountability, and providing leadership abilities and responsibility

Towards multi-agent system for learning object recommendation

The rapid increase of online educational content has made it harder for students to find specific information. E-learning recommender systems help students easily find the learning objects they require, improving the learning experience. The effectiveness of these systems is further improved by integrating deep learning with multi-agent systems. Multi-agent systems facilitate adaptable interactions within the system's various parts, and deep learning processes extensive data to understand learners' preferences. This collaboration results in custom-made suggestions that cater to individual learners. Our research introduces a multi-agent system tailored for suggesting learning objects in line with learners' knowledge levels and learning styles. This system uniquely comprises four agents: the learner agent, the tutor agent, the learning object agent, and the recommendation agent. It applies the Felder and Silverman model to pinpoint various student learning styles and organizes educational content based on the newest IEEE Learning Object Metadata standard. The system uses advanced techniques, such as Convolutional Neural Networks (CNN) and Multilayer Perceptrons (MLP), to propose learning objects. In terms of creating personalized learning experiences, this system is a considerable step forward. It effectively suggests learning objects that closely match each learner's personal profile, greatly enhancing student engagement and making the learning process more efficient.

FROM RESISTANCE TO READINESS: A ULTIDIMENSIONAL ANALYSIS OF E-LEARNING IN HIGHER EDUCATION

In the face of rapid digital transformations within the higher education sector, assessing the readiness of educational institutions to adopt e-learning systems has become crucial to ensure the success of these initiatives and avoid potential challenges that may hinder implementation. This study aims to explore the effectiveness of the ADKAR model components (awareness, desire, knowledge, ability, and reinforcement) in assessing the readiness of Algerian universities to adopt e-learning in digital education systems. The study also addresses the role of motivation and satisfaction in influencing the personal and behavioral aspects of 530 students and academics. The results reveal that 90% of the participants demonstrated a strong readiness and desire to integrate e-learning. Notably, the ADKAR model has proven to be highly effective in assessing the readiness of higher education institutions to adopt e-learning, as all variables showed significant effects. Desire was the most influential element, followed by knowledge, then awareness, ability, and finally reinforcement of change. Additionally, the study highlights that satisfaction and motivation were also found to have positive and significant effects. This study provides crucial insights that can greatly contribute to guiding policy makers, educational officials, and academics interested in implementing e-learning systems in the context of higher education.

Цифровой образовательный контент для современного урока: технология экспертизы качества

Widely and universally used e-learning systems (ELS) remain the subject of close attention of researchers. An integral and most important part of the ELS is digital educational content. This is a key element for both distance and full-time education, and in recent years it has been widely used not only in higher education, but also in general education. Assessing the quality of educational content for the expert community is a delicate issue, the complexity of which is due to the examinator subjectivity. Modern automation tools, developed within the framework of the artificial intelligence paradigm, which have already demonstrated the ability to solve various problems, allow us to approach this issue from a new position. The purpose of the article is to present the results of a preliminary study of approaches to increasing the accuracy and objectivity of the examination of the quality of digital educational content through partial automation of expert procedures. The leading research methods are analysis, examination, modeling, ascertaining experiment, description. As a result, a theoretical justification for automating the examination of the quality of digital educational content as a new interdisciplinary scientific research area is presented, tasks are set, goals and methods are defined, and the first results obtained within this area are presented. It is shown that the development goal will be the formation of an expanded description of the process of examination of the quality of digital educational content, including proposals for expert procedures implemented only by automation means, description of the examination information model and interpretation of the results of automatic examination. The novelty of the results obtained lies in the formation of the theoretical foundations for automatic analysis of the digital educational content quality. This will form a fundamentally new quality of assessment procedures in relation to electronic means of teaching and education, based on objective and measurable qualitative characteristics and indicators, formalized stages (processes) of examination, and quantitatively qualified assessment results.

Online Based Learning System (E-Learning) as Distance Learning Method Solutions: A Literature Review

Purpose – This study aims to identify critical success factors influencing the effectiveness of e-learning systems in Indonesia. It examines the advantages of e-learning, such as flexibility and affordability, as well as challenges like the digital divide and varying digital skills. By reviewing literature from diverse sources, the research underscores e-learning's potential as a distance learning solution, emphasizing the need for educational institutions to address challenges to maximize its effectiveness in Indonesian educational settings. Methodology/approach This study employs a literature review method to identify critical success factors affecting the efficacy of e-learning systems in Indonesia. Data is gathered from scientific journals, books, and research reports to analyze the advantages (flexibility, affordability) and challenges (digital divide, varying digital skills) associated with e-learning. Findings The research results show that e-learning has several advantages as a distance learning solution, such as flexibility, accessibility, interactivity and affordability. However, e-learning also has several challenges, such as the digital divide, differences in digital skills, and learning motivation. Novelty/value This study contributes novel insights by specifically examining the factors influencing the effectiveness of e-learning systems within the Indonesian educational context. Unlike broader studies, it focuses on the unique challenges and opportunities present in Indonesia, including the impact of the digital divide, varying levels of digital skills among learners, and specific strategies for enhancing learner engagement and motivation. By conducting a comprehensive literature review drawing from scientific journals, books, and research reports, the study consolidates existing knowledge and identifies gaps that are crucial for informing policy and practice

Research on Challenges and Strategies of Students' Adaptive Learning within AI

It's acknowledged that an adaptive e-learning system can be efficient for users to conduct personalized learning in which learners could choose appropriate content and preferred models based on artificial intelligence (AI) recommendations. Nowadays, the rapid development of adaptive platforms, fueled by the evolution of machine learning and AI, incontestably brings innovative potential to the educational field. However, there are many unavoidable challenges followed by the swift process of integrating AI and other technologies into adaptive learning practices. Through the extensive review of previous research on adaptive e-learning and comprehensive analysis of their prominent outcomes, the paper focuses on exploring the challenges of adaptive learning within AI that students are facing and proposing possible solutions. It's found that adaptive learning is mainly experiencing the challenges involving how to avoid data bias and protect personal privacy, making continuous evaluations of users, lack of emotion monitoring and technological support for both students and teachers and the technology integration and inequity. To deal with the increasing problems, some practical strategies are presented, such as properly governing data for learning management, conducting continuous evaluation and prediction for users, and visualizing cognition, which can be supportive of students' professional development in adaptive learning.

Gamification as an e-learning tool: A Literature Review

The purpose of the article is to highlight the status of gamification of the educational process as an element of e-learning. The use of the game space in the educational process requires compliance with a number of specific conditions, so the task of the study is to determine the organisational and functional characteristics of gamification. The methodology involves the use of the principles of qualitative research, which analyses scientific views (53 sources were analysed) on the use of gamification in the educational process. The systematic literature review is conducted using the PRISMA 2020 flowchart, which allowed for a variable selection of sources relevant to the study of the current problem. The results of the study indicate the following trends in the positioning of gamification tools in the e-learning cluster: auxiliary status of gamification (42%), reinforcing status of the game factor (39%), alternative status of game-based learning (15%), negative feedback on the actualisation of gamification (4%). The literature review confirms the trend of involving a game case in the educational paradigm. At the same time, the role and format of gamification does not have a clear algorithm for implementation and functioning in learning activities, which indicates the need to streamline this cluster of e-learning. The scientific and pedagogical discourse today does not have a clear answer to the general positioning of gamification in the educational system. Institutionally, gamification is enshrined in educational strategies due to global trends in the digitalisation of society, but at the organisational and functional level, there are contradictions about the status of the game space in the structure of e-learning. The study identified two cases of game-based learning platforms in the innovative educational space: an autonomous online game-based learning format (54%) and a game tool as an element of the digital learning environment (46%). The scientific novelty of the study is focused on the correlation of indicators of quantitative increase in the level of gamification and qualitative indicators of the effectiveness of this e-learning case. Prospects for scientific research are focused on developing a strategy for the development of gamification in the educational sphere in general and in the context of e-learning in particular. Conclusion. Thus, gamification has gained positions in the e-learning system and is forming its own niche in the educational paradigm. The rapid digitalisation of the socio-cultural space causes the diversity and disorder of the organisation of the e-learning game case (especially in the context of the educational and pedagogical status), which is expressed in the scientific discourse of the last five years.

Collaborative E-Learning Application with Course Recommendation in Cloud Computing

Cloud computing is quickly expanding, with applications in practically every industry, including education. E-learning systems often necessitate a large number of hardware and software resources. Many educational institutions cannot afford such investments, thus cloud computing is the best solution. Here, the Matrix Factorisation-based maximum rate recommendation system (MatFac-Maxirate RS) is utilised to recommend the courses for students to choose their career. According to user access, the e-learning application server is acquired from the E-Khool dataset which is subjected to learner or course agglomerative matrix calculation. The E-learning application server is executed based on Minkowski and Kumar Hasebrook’s distance to retrieve learner preference items. The recommended course having the maximum rating is considered which is forecasted with matrix factorisation considering the course ID and learner ID. The MatFac-Maxirate RS generated the finest efficacy with the best precision of 88.9%, recall of 88.2% and F-measure of 87.5%.

Personalized and adaptive e-learning systems for semantic Web: a systematic review and roadmap

Purpose The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems. Design/methodology/approach Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners. Findings The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes. Research limitations/implications The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process. Social implications E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status. Originality/value A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.

An innovative distance learning platform for mathematics education in secondary schools: Design, development and preliminary studies

AbstractThis study addresses the emerging challenges in mathematics education, emphasizing the integration of innovative teaching strategies and tools amidst the evolving educational landscape. The study begins with an analysis of prevalent e-learning and communication systems in distance education, pinpointing their limitations and identifying the gaps in effective remote mathematics instruction. In response, we introduce a novel educational platform designed to facilitate real-time mathematics teaching over the Internet, aiming to replicate the interactive essence of traditional classroom settings within a digital domain. The system features a suite of tools including a mathematical editor, a virtual whiteboard, audio-video communication capabilities, a virtual library, and an evaluation support module, all accessible via a standard web browser. The platform’s effectiveness was assessed through its application in regular mathematics classes at two secondary schools in Romania, as well as in a private tutoring scenario. The paper presents the findings of these preliminary studies, offering insights into the usefulness and usability of the platform and its potential to seamlessly integrate into existing educational frameworks without compromising the quality of instruction.

Internet of things enabled E-learning system for academic achievement among university students

The rise of the Internet of Things (IoT) represents a burgeoning frontier in educational innovation, particularly in the realm of e-learning. Despite its expanding capabilities, the integration of IoT technologies into e-learning within higher educational institutions (HEIs) faces numerous challenges and constraints. Limited research has delved into the implementation of IoT in e-learning, especially in developing nations. Consequently, this study seeks to explore the determinants influencing the adoption of IoT for e-learning in HEIs. The aim of the innovative ICT classroom is to assist students in acquiring new skills, adapting to new situations, and utilizing technology in a manner that leads to enhanced learning outcomes and extensive knowledge. Our suggested e-learning system, integrated with IoT technology, gauges student engagement and attentiveness throughout online lectures. The proposed technology integrates electroencephalography (EEG) with IoT. The IoT is a collection of technologies that allow embedded real-world objects to connect to the Internet and is widely used by humans to support a variety of activities. IoT should be taught using developmental learning approaches and included in higher education teaching projects. EEG devices are used to track the psychological movements of students taking online courses. Our findings demonstrate how the proposed method can be used to detect the user’s level of concentration and the required level of educational strategy. A collection of informational indexes for student attention. By using a BiLSTM network to predict undergraduate recall and temporary memory, we can accurately predict undergraduate preferred learning styles. The findings of the research demonstrate that IoT systems and devices play a pivotal role in enhancing access to education. They facilitate easier teaching and learning processes while democratizing education. When employed as educational tools, IoT devices contribute significantly to creating highly engaging learning experiences for students.

Person's Temperament and Character Type Detection Based on Modern Information and Communication Technologies

The popularity of e-learning systems is growing because of their effectiveness. It is necessary to adjust learning/training scenarios for every trainee, using advanced information and communication technologies (ICT) tools to achieve this. However, it is not often respected that people have different perceptions of information. A learning system should consider the temperament and character of an applicant/trainee. Since people with the same temperament have approximately the same ability to perceive and process information, as well as similar labour skills, the learning system must first determine the applicant's temperament and after that, based on this, determine how long it will take him to absorb a certain amount of information from the training course. Testing is used for recognition of the applicant’s temperament. But traditional tests–questionnaires are long and the applicant can manipulate with answers. Apart from those, there are other types of tests: color tests, picture tests, figures tests, drawing tests, etc. The advantage of such tests is that they are based on the subconscious processes and thus, are more free from manipulations with answers, take far less time, and less depend on the mood swings. Moreover, according to S. Dellinger, the applicant's temperament type represents a fuzzy set, because a person has one dominant temperament and one secondary temperament, with relevantly different credibility levels. This means, that the determination of a person’s temperament should be implemented in a fuzzy environment, not in a classical environment. For this reason, we want to implement the first part of the teaching system, using this paper. Particularly, we aimed to create a quick and free-from-manipulations test-program, which would allow, determine the type of applicant’s temperament for e-learning individualization needs and determin the innate working skills. The specific fuzzy method is applied. The program was successfully tested on different people.

Only a matter of time? Using logfile data to evaluate temporal motivation theory in university students' examination preparation.

While previous research has emphasized the importance of personal beliefs (expectancy-value theories) for achievement-motivated behaviour, it lacks the integration of temporal factors that are also discussed as important drivers of achievement-motivated behaviour. Temporal Motivation Theory (TMT) combines both approaches in a formalized manner. Although TMT is supported by empirical studies with self-reported academic procrastination, it has not been tested on actual achievement-motivated behaviour. We evaluated the predictive power of the TMT on N = 2351 learning days of 127 psychology students' self-regulated examination preparation for statistics over the course of one semester using logfile data of an e-learning system. The proposed TMT score, incorporating expectancy and value beliefs, sensivitiy to delay, and actual time till examination predicted students' achievement-motivated behaviour significantly. Further analyses revealed that not the trait compositions of the TMT, but the temporal proximity of the statistics examination was the main driver of this association. The results have important implications for understanding the factors that shape students' motivation to learn and subsequent academic success in actual learning situations. Thus, research should continue to take situational aspects, especially the temporal proximity of goals more into account.