Learning materials recommendation using good learners’ ratings and content-based filtering

The enormity of the amount of learning materials in e-learning has led to the difficulty of locating suitable learning materials for a particular learning topic, creating the need for recommendation tools within a learning context. In this paper, we aim to address this need by proposing a novel e-learning recommender system framework that is based on two conceptual foundations—peer learning and social learning theories that encourage students to cooperate and learn among themselves. Our proposed framework works on the idea of recommending learning materials with a similar content and indicating the quality of learning materials based on good learners’ ratings. A comprehensive set of experiments were conducted to measure the system accuracy and its impact on learner’s performance. The obtained results show that the proposed e-learning recommender system has a significant improvement in the post-test of about 12.16% with the effect size of 0.6 and 13.11% with the effect size of 0.53 when compared to the e-learning with a content-based recommender system and the e-learning without a recommender system, respectively. Furthermore, the proposed recommender system performed better in terms of having a small rating deviation and a higher precision as compared to e-learning with a content-based recommender system.     

Learning path recommendation based on modified variable length genetic algorithm

With the rapid advancement of information and communication technologies, e-learning has gained a considerable attention in recent years. Many researchers have attempted to develop various e-learning systems with personalized learning mechanisms for assisting learners so that they can learn more efficiently. In this context, curriculum sequencing is considered as an important concern for developing more efficient personalized e-learning systems. A more effective personalized e-learning recommender system should recommend a sequence of learning materials called learning path, in an appropriate order with a starting and ending point, rather than a sequence of unordered learning materials. Further the recommended sequence should also match the learner preferences for enhancing their learning capabilities. Moreover, the length of recommended sequence cannot be fixed for each learner because these learners differ from one another in their preferences such as knowledge levels, learning styles, emotions, etc. In this paper, we present an effective learning path recommendation system (LPRS) for e-learners through a variable length genetic algorithm (VLGA) by considering learners’ learning styles and knowledge levels. Experimental results are presented to demonstrate the effectiveness of the proposed LPRS in e-learning environment.     

A review of using partial least square structural equation modeling in e-learning research

Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate statistical modeling technique that educational researchers frequently use. This paper reviews the uses of PLS-SEM in 16 major e-learning journals, and provides guidelines for improving the use of PLS-SEM as well as recommendations for future applications in e-learning research. A total of 53 articles using PLS-SEM published in January 2009–August 2019 are reviewed. We assess these published applications in terms of the following key criteria: reasons for using PLS-SEM, model characteristics, sample characteristics, model evaluations and reporting. Our results reveal that small sample size and nonnormal data are the first two major reasons for using PLS-SEM. Moreover, we have identified how to extend the applications of PLS-SEM in the e-learning research field.     

Dynamic learner profiling and automatic learner classification for adaptive e-learning environment

E-learning allows learners individually to learn “anywhere, anytime” and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to increase the results of the learning process. In addition, providing the same learning content to all the learners may lead to a reduction in the learner's performance. Hence, there is a need to classify the learners based on their performance and knowledge level. Learner profiles play an important role in making the e-learning environment adaptive. Providing an adaptive learning environment, catering to the changing needs and behavior of the learner can be achieved by evolving dynamic learner profiles. Navigation logs can be used to analyze learners’ behavior over a period of time. In this work, we propose dynamic learner profiling to cater to changing learner behaviors, styles, goals, preferences, performances, knowledge level, learner's state, content difficulty, and feedbacks. Based on the continuous observation of learner preferences and requirements, the learner profile is dynamically updated. Furthermore, we propose an automatic learner classification to construct the learner profile and identify the complexity level of learning content, using the Bayesian belief network and decision tree techniques. We evaluated our system with two traditional adaptive e-learning systems, using static profiles and behavioral aspects, through our performance evaluation method of different learner types. In addition, we compared the actual learners’ data with the system generated results for various types of learners, and showed the increased interest in their learning outcomes.     

The Experience of Collaborative Assessment in e-Learning

This paper examines the various ways in which students talk about their experience and perceptions of collaborative review and assessment as it occurs in e-learning environments. Collaborative review and assessment involves the student, their peers and tutor in thoughtful and critical examination of each student's course work. The process involves two stages: review and discussion of the student's work with a view to bringing different critical yet supportive perspectives to the work. This is followed by the use of two sets of criteria to make judgements on the student's work: one set provided by the student, the other by the tutor. The purpose of collaborative assessment is to foster a learning approach to assessment and to develop a shared power relationship with students. From analysis of face-to-face interviews, examination of e-learning discussions and student-completed questionnaires, a set of analytic categories was built describing the learners' experiences of collaborative e-assessment. These categories are: (1) the appropriateness of collaborative assessment; (2) collaborative assessment as a learning event; and (3) the focus for assessment. The paper focuses on analysing and discussing these categories of experience. The research shows that a positive social climate is necessary in developing and sustaining collaborative assessment and that this form of assessment helps students to reduce dependence on lecturers as the only or major source of judgement about the quality of learning. Students develop skill and know-how about self- and peer assessment and see themselves as competent in making judgements about their own and each other's work, which are surely good lifelong learning skills.     

A competency-based guided-learning algorithm applied on adaptively guiding e-learning

This paper presents a new algorithm called competency-based guided-learning algorithm (CBGLA), which can be applied on adaptively guiding e-learning. Computational process analysis and mathematical derivation of competency-based learning (CBL) were used to develop the CBGLA. The proposed algorithm could generate an effective adaptively guiding learning path in order that it would guide the learners to study adaptively without requiring teacher involvement. In order to verify the effectiveness for the CBGLA, a system is implemented. Using statistical methods, the data of which are collected from the students' learning activities on the system, we have verified the efficiency of the CBGLA by the comparison of the pre-test and post-test scores of students. While the learning materials possess fixed scope and could be classified into several categories, students could even learn more effective under the guidance of CBGLA system than a teacher. Analyzing the questionnaire, it also has been shown that learners were very satisfied with the design of the system user interface and the guided-learning mechanism.     

网上教学对医学教育的影响

作者介绍了网上教学及其在医学教育中扮演的角色,概述了网上教学的关键术语、教学内容、教学效果,网上教学的实施对师资的要求,网上教学及相关技术的评估以及如何对参与网上教学的教师的学术成就加以认定等。     

What leads people to keep on e-learning? An empirical analysis of users' experiences and their effects on continuance intention

User retention is a major goal for higher education institutions running their teaching and learning programmes online. This is the first investigation into how the senses of presence and flow, together with perceptions about two central elements of the virtual education environment (didactic resource quality and instructor attitude), facilitate the user's intention to continue e-learning. We use data collected from a large sample survey of current users in a pure e-learning environment along with objective data about their performance. The results provide support to the theoretical model. The paper further offers practical suggestions for institutions and instructors who aim to provide effective e-learning experiences.     

Authorware中视频文件的使用

Authorware是Macromedia公司开发的基于设计图标和流程线进行创作的多媒体开发平台。在多媒体创作过程中,使用视频可以增强作品的直观性、形象性和生动性。文章介绍了在Authorware中如何通过数字电影图标来使用和设置视频文件,同时介绍了使用MovieController知识对象来控制视频文件播放的方法。     

A Vocabulary Learning Tool for L2 Undergraduates Reading Science and Technology Textbooks

Students of English as a second language who major in science and technology use English-language textbooks to ensure that they can read English materials upon graduation. Research indicates that teachers spend little time helping these students on the linguistic complexity of such textbooks. Vocabulary, grammar, and article structure are elements of this complexity, but to many students, these elements can be akin to locked doors. This study presents MyVLS-Reader, which focuses on unlocking the first of these doors—vocabulary—while assisting in reading. With explicit vocabulary learning, students learn and memorize individual vocabulary, but the context is lost if the depth of learning discards context. In implicit vocabulary learning, students acquire vocabulary through repeated exposure to contexts, but repeated encounters with new words are required. Few e-learning systems combine both vocabulary-learning approaches. MyVLS-Reader achieves such synergy by (1) using a keyword setting to provide context-matched vocabulary explanation while reading and (2) embedding multiple learning choices, such as keyword setting, the review and memorization of explicit vocabulary, and the option to ask instructors. This study includes two rounds of evaluations: (1) an evaluation of the learning achievements of control and treatment groups and (2) a quantitative and qualitative investigation of perceptions regarding the use of MyVLS-Reader. The evaluation results indicate that the treatment group developed a better vocabulary than the control group in significantly less time. The use of MyVLS-Reader also slightly improved higher-order thinking skills. This result suggests that MyVLS-Reader can effective assist students in building their vocabulary while reading.     

How can organisations learn: an information systems development perspective

This article sets out to argue that organisations can learn but that they cannot do so in their own right without infrastructural support. This article further examines the notion that individuals in organisations also require the cognitive participation of the organisation itself as a learning entity to learn. The close reliance and affiliation required between individuals and organisations to enable their learning from one another are discussed. In continuation of this, specific examples are provided through the industry sector of information systems development (ISD) projects to illustrate of how organisations can learn. Finally, the question of how one identifies organisational learning is analysed. Following on from the ISD and its use in the analogy of organisational learning, the article discusses an organisational empirical research project currently being undertaken by the authors, which utilises blogs. Though there are many potential organisational learning connotations associated with blogs, they could be perceived as a type of information system. The ongoing research being undertaken with the company using the blogs will attempt to identify indicators of learning at the individual, group and organisational levels. The significance of the issues explored in this article lies in the fact that it addresses an ISD approach to study how an organisation learns, and why this perspective is useful towards understanding the process of organisational learning. This article contributes to the organisational learning debate through an illustrative industry example of ISD projects. In doing so, we wish to argue that though individual learning can occur in ISD projects, the collective nature of projects primarily engenders the interpretive aspect of organisational learning. We further believe that it is the interactive nature of an ISD project that allows an organisation to learn in tandem with project members as exemplified through the stages of a project life cycle. We feel that this article contributes to the ISD and organisational learning literature in terms of linking both concepts together.     

Building on solid foundations: establishing criteria for e-learning development

In recent years, advances in technology and changes in the market place for education and learning have resulted in a rapid growth of interest in e-learning. Early experiments in the area have indicated that e-learning may not be the apparent panacea to issues of cost effectiveness and widening participation that was initially mooted. Undoubt edly, e-learning provides the opportunity for wider access to learning at all levels, however, such promise is not always fulfilled. E-learning is often construed as simply putting existing teaching materials ‘on the Web’. A shift towards learner-oriented developments requires a major paradigm shift for learning providers, both at the institutional and individual level. Institutions need to be aware of the commitment required to make e-learning effective, while individuals need to accommodate a shift towards greater learner control and responsiveness to the flexibility requirements. Many of the issues surrounding the effectiveness of e-learning initiatives stem from inadequate consideration of whether e-learning is an appropriate solution to a learning need and insufficient consideration of the design and implementation of the resulting product. This paper proposes a set of criteria for those new to e-learning design to consider when exploring whether and how to implement e-learning. These criteria relate to the appropriateness of an e-learning strategy, the interaction between the proposed market and the design of an e-learning product, the nature of student–faculty interaction within the e-learning environment and issues of evaluation. The relationships between these criteria at a generic level are outlined and guiding principles for the development of e-learning proposed.     

Do cultural differences affect users’ e-learning adoption? A meta-analysis

The great advantages of e-learning have been recognized, and efforts have been made to promote e-learning adoption. Despite valuable research achievements from technology adoption, previous studies built their models from different perspectives. In this study, to offer a comprehensive research model on e-learning adoption, we integrated these models (ie, TAM, TPB and IDT) and included culture as a moderator. Based on 45 relevant empirical research, this study conducted a meta-analysis to explore key determinants of users’ attitude and behavioral intention to adopt e-learning. Combined with traditional technology acceptance theories and innovation diffusion theory, we developed a comprehensive model and explored the moderating role of culture. The results indicate that this integrated technology acceptance model can be applied to better understand e-learning adoption. The moderator analysis shows that the influence of subjective norms and self-efficacy on users’ behavior intention is more salient in the collectivistic culture, whereas perceived usefulness is more important for online learners in an individualistic culture.     

Development and evaluation of an e-learning course for deaf and hard of hearing based on the advanced Adapted Pedagogical Index method

Web-based and adapted e-learning materials provide alternative methods of learning to those used in a traditional classroom. Within the study described in this article, deaf and hard of hearing people used an adaptive e-learning environment to improve their computer literacy. This environment included streaming video with sign language interpreter video and subtitles. The courses were based on the learning management system Moodle, which also includes sign language streaming videos and subtitles. A different approach is required when adapting e-learning courses for the deaf and hard of hearing: new guidelines must be developed concerning the loading and display of video material. This is shown in the example of the e-learning course, ECDL (European Computer Driving Licence). The usability of the e-learning course is analyzed and confirmed using two methods: first, the Software Usability Measurement Inventory (SUMI) evaluation method, and second, the Adapted Pedagogical Index (AdaPI), which was developed as part of this study, and gives an index to measure the pedagogical effectiveness of e-learning courses adapted for people with disabilities. With 116 participants, of whom 22 are deaf or hard of hearing, the e-learning course for the target group has been found suitable and appropriate according to both evaluation methods.     

Rich data,poor information? Teachers’ perceptions of mean differences in graphical feedback from statewide tests

Data-based decision making in schools aims to address students’ needs and improve their performance by leveraging the information contained in data. However, to learn from data, teachers are required to transform them into actionable information. In two studies, we focused on how teachers can learn about the strengths and weaknesses of their class performance from statewide test data by investigating how sensitively, efficiently, and accurately they are able to judge the magnitude of mean differences. The results indicate that teachers can judge mean differences with very high accuracy (τ = .85) but only consider moderate and large effects to be meaningful, indicating low sensitivity. By systematically varying different graph types, we also found that participants quickly increased their efficiency in terms of dwell time when repeatedly confronted with a specific graph type and were most sensitive to the use of stacked or clustered bar graphs.     

Evaluating Training Outcomes in Corporate E-Learning and Classroom Training

The study contributes to training evaluation research by systematically comparing training outcomes between corporate e-learning and classroom training. We investigated a sample of vocational trainees (N?=?86) in a field experiment with a time-lag design and examined their subjective as well as objective training success. While training success was subjectively perceived to vary in effectiveness depending on the setting right after the training, with higher scores for trainees in classroom training, it was perceived similarly effective in both training settings after six to eight weeks. With regard to objective training success, we found that whereas declarative and procedural knowledge scores increased for e-learning trainees, they decreased for trainees in classroom training. However, strengths of e-learning become more prevalent six to eight weeks after the training. Thus in the end, e-learning is as effective as classroom training for procedural knowledge and more effective than classroom training for declarative knowledge as e-learning trainees catch up on previous differences across time. We conclude that it is not the training setting or delivery media per se that leads to higher levels of trainings success in the long run but in order to be effective, trainings should be designed taking especially the type of learning content (declarative or procedural knowledge) into account.     

The dimensions of e-learning quality: from the learner’s perspective

The present study was designed to identify the quality dimensions as perceived by adult learners who had taken one or more e-learning courses offered by higher education institutions in South Korea and to identify and confirm the structural features of these quality dimensions. The results of the exploratory factor analysis arising from a survey of 299 learners revealed that from their perspective, there were seven dimensions in evaluating the e-learning quality: Interaction, Staff Support, Institutional Quality Assurance Mechanism, Institutional Credibility, Learner Support, Information and Publicity and Learning Tasks. And the confirmatory factor analysis with responses obtained from another set of 496 adult learners confirmed a good fit of the seven-factor model to the observed data. While most of these seven dimensions are supported by previous studies, some dimensions, such as technology support, content and evaluation/assessment that e-learning providers had highlighted did not appear to be important for Korean adult learners. Possible explanations for these findings are discussed in relation to learner characteristics, e-learning design, and culture, and further research topics are suggested.     

Chinese students’ perceptions of a collaborative e-learning environment and factors affecting their performance: implementing a Flemish e-learning course in a Chinese educational context

This study was set up in a Chinese university in Beijing by implementing a Flemish e-learning course in a Chinese setting. A main feature of the e-learning environment is the asynchronous ‘task-based’ online group discussion. The purpose of the study is to understand Chinese students’ perceptions of a collaborative e-learning environment and the factors that affect their online performance and academic achievement. The results of the study indicate that the students had less positive perceptions of the e-learning environment as compared to their perceptions of a more conventional environment. However, the students reported to a higher level of preferences of peer learning, critical thinking, and problem-based learning (PBL) after one semester e-learning experience. In addition, we examined variables that might have affected students’ performance in e-learning environments. The results show that students with higher motivational orientations perform better in the online group discussions.     

数字化学习在高等教育中的创新应用——访泰国网络大学项目专家查瓦勒·勒查罗兰教授

记者:勒查罗兰教授您好,首先感谢您百忙中抽出时间接受我们的访谈.我们知道您来自泰国,现任泰国教育部高等教育委员会下属的泰国网络大学(TCU)项目专家.您能否简要介绍一下泰国的教育制度以及现状. 勒查罗兰:非常高兴接受你们的访谈.泰国的教育分为普通教育、职业教育和成人教育三类.普通教育分学前教育、初等教育(分初小和高小)、中等教育、高等教育四个阶段,初等教育是强制性的义务教育,中等教育是非强制性的义务教育.泰国的高等教育比较发达,分公立和私立两类.公立高校由当地政府开办,私立高校由私人出资兴办,但二者皆由泰国教育部高等教育委员会管理.     

E-learning in Chinese higher education: the view from inside

Despite the upsurge in interest in e-learning (or online learning) in Chinese higher education, little is known about the ways in which lecturers design and run their online courses, or about how they perceive e-learning. This paper reports the results of interviews with higher education teachers in China working in conventional, campus-based universities, concerning their conceptions and beliefs of e-learning. The interviews were analysed from a grounded theory perspective that gave rise to seven emerging themes, namely: the ‘centrality of the lecture’, ‘online cooperative learning’, ‘network learning’, ‘student learning’, ‘lecture plus online work’, ‘infrastructure and access’ and ‘professional development’. Discussion of these emerging themes helps us understand the ways in which these teachers think about e-learning and teaching, the beliefs they hold about their ‘e’ practice, the ways in which they implement e-learning, the problems they face in incorporating e-learning into their courses and the ways in which they perceive e-learners. This provides a fascinating and unique insight into e-learning in Chinese higher education. Evidence shows that it is a complex area with many influences, some of which can be attributed to social, cultural and Confucian-heritage factors. It is concluded that, despite enthusiasm by some for innovating e-learning, the dominance of traditional teaching methods in China suggest that the conditions for mainstreaming e-learning in the near future are not strong.