Text-based synchronous e-learning and dyslexia: Not necessarily the perfect match!

The introduction, in the United Kingdom, of the Special Education Needs and Disabilities Act (SENDA) published and approved in 2001, has removed the exemptions given to educational institutions by the Disabilities Discrimination Act (DDA) of 1995. This applies to learning web sites and materials that must now undergo “reasonable adjustments”, in order not to disadvantage students with learning disabilities as well as non-disabled students. This paper discusses how e-learning and the inherent use of online learning activities raises problems for students with dyslexia far beyond accessibility and web design. This paper aims at proposing that the so widely proclaimed advantages of e-learning to bridge distances, different learning paces and cognitive styles, is at the same time producing close to insurmountable barriers to students with cognitive disabilities in general, and dyslexia specifically. It presents the results of a research project aiming at uncovering evidence that students with dyslexia are in fact less likely to thrive in a synchronous e-learning environment. The paper reports on a set of experiments undertaken with students when engaged in online authentic synchronous learning activities. The paper focuses on text-based synchronous activities, since it is the widest and most commonly used synchronous technology, and provides clear evidence that it can marginalise, demotivate and disappoint students with dyslexia with difficulties in reading, spelling, word order and argumentation.     

The effects of organizational learning environment factors on e-learning acceptance

Workplace learning is an important means of employees’ continuous learning and professional development. E-learning is being recognized as an important supportive practice for learning at work. Current research on the success factors of e-learning in the workplace has emphasized on employees’ characteristics, technological attributes, and training design elements, with little attention to workplace contextual effects. The study aims to investigate the impacts of organizational learning environment factors, including managerial support, job support, and organizational support, on employees’ motivation to use a workplace e-learning system. A model was proposed based on the expectancy theory of training motivation and the social influences and facilitating conditions in technology acceptance models. The model was tested on sample data collected from mainland China using Structural Equation Modeling and Moderated Structural Equation Modeling. The results suggested that employees’ perceived managerial support and job support had a significant impact on their perceived usefulness of the e-learning system for individual learning, and that perceived organizational support had a significant influence on the perceived usefulness of the e-learning system for social learning. Perceived usefulness for individual learning was found to completely mediate the environmental influences on individuals’ motivation to use the system, while perceived usefulness for social learning made partial mediation in the effects of the environmental factors on intention to use. In addition, perceived job support was found to have moderating effects on the relationship between employees’ perceived usefulness of the e-learning system and their intention to use the system. Consistent with previous findings, employees’ perceptions about the usefulness of the e-learning system have significant effects on their intention to use the system in the work setting.     

Towards learner-constructed e-learning environments for effective personal learning experiences

Whilst a lot of research has been carried out on designing learning environments to meet the needs of learners, much of such research has focused on producing less flexible ready-made environments for learners to interact with. However, e-learning design and development could benefit from the lessons of the interaction of users with mobile devices, where users interact by selecting applications (Apps) they are interested in and hence engage with the device in an addictive way. By transposing the same interaction idea to the e-learning environment, if given the opportunity, learners will construct an environment that meets their needs with the tools that are available and hence will be motivated to engage more with such environment, possibly leading to improved performance. This article proposes FAUCLE (Flexible and Accessible User Constructed Learning Environment), a learner-centred model for a learner-constructed learning environment. It is hoped that this paper will encourage research interest on innovative ways of designing learner-centred learning environments that encourage active and inclusive learning.     

The influence of student characteristics on the use of adaptive e-learning material

Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive e-learning materials. Ninety-four students participated in the study. We determined characteristics in a heterogeneous student group by collecting demographic data and measuring motivation and prior knowledge. We also measured the learning paths students followed and learning strategies they used when working with adaptive e-learning material in a molecular biology course. We then combined these data to study if and how student characteristics relate to the learning paths and strategies they used. We observed that students did follow different learning paths. Gender did not have an effect, but (mainly Dutch) BSc students differed from (international) MSc students in the intrinsic motivation they had and the learning paths and strategies they followed when using the adaptive e-learning material.     

A study of learning performance of e-learning materials design with knowledge maps

This research investigated the application of knowledge maps in e-learning materials design and hypothesized that knowledge maps would be more effective than e-learning in general at improving the performance and satisfaction of e-learning. In order to test the hypotheses, we conducted an experiment with 175 participants and randomly assigned them into knowledge map-based and browse-based groups. Both groups of participants needed to acquire specific skills and knowledge to write the target ADO.NET program. In the end of each training session subjects received an assessment to understand their learning score, satisfaction level, and computer self-efficacy. Our statistical analysis result showed that knowledge map-based learning group outperformed browse-based group in these three measurements. Thus, the proposed hypotheses were supported. We concluded that if knowledge map-based materials design approach were employed novice users would acquire the ADO.NET programming in a more effective manner. In addition, the satisfaction and computer self-efficacy of users could be improved substantially as a result of knowledge map-based materials design approach.     

Multi-level analysis of peer support,Internet self-efficacy and e-learning outcomes – The contextual effects of collectivism and group potency

The present study intends to explore the role of collectivism and group potency at group level in predicting individual Internet self-efficacy (ISE) and individual e-learning outcomes for people aged over 45. Group learning has been widely discussed in the research into online formats. However, less study has been carried out about how collectivism and collective group potency affect individual learning decisions, especially using the technique of Hierarchical Linear Modeling (HLM) for cross-level analysis, which provides the solution of case dependency between group members. This study examines the mediation effects of ISE between peer support and e-learning outcomes. It also explores the contextual effects of group potency, and the moderation effects of collectivism and group potency at an individual level. The results show that ISE fully mediates the relationship between peer support and learners’ persistence in e-learning, and partially mediates learners’ perceived learning and satisfaction. It is noteworthy that the findings do not support direct group-level contextual effects of group potency. Instead, the results suggest that group potency moderates ISE-perceived learning and ISE-satisfaction relationships. On the other hand, collectivism also moderates the relationship between peer support and ISE. This study highlights the group-level effects of group potency, and suggests that adult educators design and deliver e-learning courses with an emphasis on facilitating group processes.     

When humans form media and media form humans: An experimental study examining the effects different digital media have on the learning outcomes of students who have different learning styles

A set of computer-based experiments are reported that investigate the understanding achieved by learners when studying a complex domain (statistics) in a real e-learning environment using three different media combinations—Text only, Text and Diagrams and Spoken Text and Diagrams, and the results agree with earlier work carried out on more limited domains. The work is then extended to examine how student interaction and student learning styles affect the learning outcomes. Different responses to the media combinations are observed and significant differences occur between learners classified as Sensing and Reflective learners. The experiment also identified some important differences in performance with the different media combinations by students registered as Dyslexic. The experiment was therefore repeated with a much larger sample of Dyslexic learners and the earlier effects were found to be significant. The results were surprising and may provide useful guidance for the design of material for Dyslexic students.     

Impact of media richness and flow on e-learning technology acceptance

Advances in e-learning technologies parallels a general increase in sophistication by computer users. The use of just one theory or model, such as the technology acceptance model, is no longer sufficient to study the intended use of e-learning systems. Rather, a combination of theories must be integrated in order to fully capture the complexity of e-learners, who are both system users and learners. The current research presents an integrated theoretical framework to study users’ acceptance of streaming media for e-learning. Three streams of research provide the basis for this integrated framework: the technology acceptance model, flow theory and media richness theory. Students enrolled in an online section of an information systems course used one of three different combinations of text, streamed audio and streamed video. Regression analysis was used to test the hypotheses in this field experiment. Perceived ease of use was a predictor of perceived usefulness; both the perceived usefulness and the attitude of the user were predictors of intention to use. Richer content-presentation types were positively correlated with higher concentration levels but showed mixed results when correlated with perceived usefulness. Results from this study have practical implications for those interested in integrating streaming media into e-learning.     

基于自组织社区发现的协作学习算法

远程学习者通常很难判断哪些学习资源最适合他们的阅读需要,同时对教师来说,针对每个学习者重新组织不同的学习资源几乎是不可能的。基于此,提出一种新颖的学习偏好建模方法,通过将动态学习数据映射为“资源、评估”的方式实现对学习特征的综合评估;通过构建智能代理来监控学习者的动态学习行为;提出组隶属度奖励机制和组成员交换机制,实现对分布式环境下的相似学习者的社区自组织;同时,基于JADE智能代理平台开发了一个协作学习平台,使得具有相似学习偏好的学习者能够进行学习资源和经验的共享。实验证明,算法具有较高的匹配准确性和社区构建效率,并能够切实提高协作学习的有效性。     

What type of learning style leads to online participation in the mixed-mode e-learning environment? A study of software usage instruction

Learning style is traditionally assumed to be a predictor of learning performance, yet few studies have identified the mediating and moderating effects between the two. This study extends previous research by proposing and testing a model that examines the mediating processes in the relationship between learning style and e-learning performance and the moderating effects of prior knowledge. The results show that the sensory/intuitive dimension of learning style predicts learning performance indirectly through the mediation of online participation. However, other types of learning styles do not affect online participation. Sensory students demonstrate a higher level and intuitive students a lower level of online participation. Prior knowledge plays an important role as a moderator between online participation and learning performance. This study was conducted in the context of software usage instruction using empirical data from 219 undergraduate students.     

Assessing effects of information architecture of digital libraries on supporting E-learning: A case study on the Digital Library of Nature & Culture

Modern digital libraries not only contain rich digital resources, they are also required to provide an environment which integrates collection provision, information services, and academic activities to support effective learning. This work chose the Digital Library of Nature and Culture established by the National Museum of Natural Science in Taiwan to investigate whether the design of the information architecture of a digital library influences learning performance and whether learners with different learning styles have different information usage behaviors and learning performance when they use the digital library to support e-learning. This work suggested that e-learning supported by a digital library resulted in excellent learning performance. Regarding the influence of information architecture on learning performance, this work found that the organization system was crucial to learning performance. Further, learners with different learning performance exhibit different behaviors when they use the information architecture of the digital library. Another finding was that the learning performance of global learners was better than that of sequential learners. Global learners and those learners with superior learning performance relied more heavily on the organization system, while sequential learners and those learners with inferior learning performance relied more heavily on the search system.     

Appropriate media choice for e-learning effectiveness: Role of learning domain and learning style

As the number of online education and training programs increase, researchers and practitioners are interested in investigating ways to design and develop effective e-learning programs. One of the major design decisions that affects learning effectiveness is the choice of media to present the contents of such programs. The prevailing tendency seems to be to use “richer” medium, in the progression from text to graphics to audio to video, for designing and developing e-learning programs. It is not clear, however, if a “richer” medium provides proportionately higher learning effectiveness. To investigate this gap in our understanding, we developed an integrated research model and tested it empirically. Our results showed that the relationship between media choice in an e-learning program and the effectiveness of that program is moderated by the learning domain of the program and the learning styles of learners.     

Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit

The objective of this study is to propose a research framework that investigates the relation between perceived fit and system factors that can motivate learners in continuing utilizing an e-learning system in blended learning instruction. As learners have the face-to-face learning opportunity in interacting with lecturers, the study aims at investigating the critical features the e-learning system can provide in assisting learning. Both quantitative (survey) and qualitative (focus group interview) methods are applied in this paper. Results reveal that the information quality and task-technology fit influence the confirmation of system acceptance. Perceived usefulness and system satisfaction have major impacts on continuance intentions. Notions from contingency theory are used to interpret these findings.     

A method toward dynamic e-learning services modeling and the cooperative learning mechanism

The advanced information technologies have made it possible for individuals to carry out cooperative learning efficiently and effectively from anywhere and at any time. To capitalize on the individual need and address the issues associated with the late entry into the e-learning area, it has great significance to study the service mechanism of CSCL on e-learning service and e-learning service computing modeling. This paper proposes an e-learning service model supporting for the life-cycle process management. The proposed model is developed by considering the learner’s behaviours during e-learning services, the scheduling policies, and the monitoring mechanism of learning activities. Business process modeling for e-learning services can be taken according to the study ordering of the knowledge points by using workflow modeling technology and process enactment mechanism. The overall life-cycle process management of knowledge is addressed by combining knowledge product modeling, knowledge resource modeling, and credit polices for member selection in research team by considering trust value of learners, advisers and providers in e-learning services. The proposed method can be used for supporting the sustainable development of e-learning services from planning and design, organizing e-learning process, maintenance of the e-learning process, to process improvement, as well as to support learners and advisers to effectively complete innovative team study and complex computation study. Lastly, an extended topic map tool has been developed by adding a knowledge requirement level and an information extraction tool to validate the proposed methodology. These tools can used to guide learners to concentrate on the required knowledge topics and drive knowledge providers to redevelop outdated knowledge hierarchy.     

How family support and Internet self-efficacy influence the effects of e-learning among higher aged adults – Analyses of gender and age differences

Gender and age differences in the effects of e-learning, including students’ satisfaction and Internet self-efficacy, have been supported in prior research. What is less understood is how these differences are shaped, especially for higher aged adults. This article examines the utility of family support (tangible and emotional) and Internet self-efficacy (general and communication) in predicting middle aged (aged 50–64) and older adults’ (over the age of 65) perceived effects of e-learning. A total of 290 adult participants aged over 50 who were registered in community college and senior learning center courses completed the measure of perceived family support, Internet self-efficacy and the effects of e-learning. By using structural equation modeling (SEM) and model invariance analysis, the results indicate that emotional family support plays a main role in predicting the effects of e-learning, mediated by general and communication Internet self-efficacy. Emotional family support has both direct and indirect influences on adults’ perceived effects of e-learning. Tangible support significantly predicts adults’ perceived effects of e-learning, mediated by Internet self-efficacy. Compared to male adult learners, female adults rely more on tangible family support for increasing their Internet self-efficacy. Similar patterns were presented by older participants. The similarities between women and older adults imply that the gender issue is not specifically related to sex itself, but relates to the complexity of the social context of these disadvantaged learners. The findings provide researchers, adult education practitioners and e-learning program planners with a direction towards understanding e-learning for middle and older aged adults.     

An empirical examination of factors contributing to the creation of successful e-learning environments

Although existing models of e-learning effectiveness in information systems (IS) have increased our understanding of how technology can support and enhance learning, most of our models do not take into account the importance of social presence. Thus, this study extends previous research by developing a model of e-learning effectiveness which adds social presence to other oft studied variables including application-specific computer self-efficacy (AS-CSE), perceived usefulness, course interaction, and e-learning effectiveness. Using data from 345 individuals, this model was validated through a field study in an introductory IS survey course. Results indicate that AS-CSE and perceived usefulness were related to course performance, course satisfaction, and course instrumentality. In addition, course interaction was related to course performance and satisfaction. Finally, social presence was related to course satisfaction and course instrumentality. Implications for research and practice are discussed.     

Critical success factors for e-learning in developing countries: A comparative analysis between ICT experts and faculty

This study identifies the critical success factors that influence the acceptance of e-learning systems in developing countries. E-learning is a popular mode of delivering educational materials in higher education by universities throughout the world. This study identifies multiple factors that influence the success of e-learning systems from the literature and compares the relative importance among two stakeholder groups in developing countries, ICT experts and faculty. This study collected 76 usable responses using the Delphi method and Analytic Hierarchy Process (AHP) approach. The results reveal 6 dimensions and 20 critical success factors for e-learning systems in developing countries. Findings illustrate the importance of curriculum design for learning performance. Technology awareness, motivation, and changing learners’ behavior are prerequisites for successful e-learning implementations. Several recommendations are provided to aid the implementation of e-learning systems for developing countries which have relevance for researchers and practitioners. Limitations as well as possible research directions are also discussed.     

Acceptance of competency-based workplace e-learning systems: Effects of individual and peer learning support

Current endeavors to integrate competency-based learning approaches with e-learning systems designed for delivery of training to adult learners in the workplace are growing. However, academic efforts in examining learners’ perceptions of, and reactions toward, this technology-delivered pedagogical innovation are limited. Drawing together perspectives from the literature on training and instructional design and technology acceptance, this research proposed a conceptual model to examine the influences of perceived individual and social learning support on employees’ acceptance of competency-based e-learning systems. Structural equation modeling and multi-group structural equation modeling techniques were applied to sample data collected from work settings in Mainland China. The results show the positive effects of perceived individual learning support and perceived support for promoting a norm of cooperation on employees’ intention to use the competency-based e-learning system. It was also found that perceived support for enhancing social ties had a negative effect on employees’ behavioral intention. The gender, age, prior experience, and work experience differences in the main effects were also investigated. Besides, qualitative data collected via semi-structured in-depth interview provide complementary evidence to the findings.     

Student Behavior Modeling for an E-Learning System Offering Personalized Learning Experiences

With the advent of computing and communication technologies, it has become possible for a learner to expand his or her knowledge irrespective of the place and time. Web-based learning promotes active and independent learning. Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process. This digital learning improves the quality of teaching and also promotes educational equity. However, the challenges in e-learning platforms include dissimilarities in learner’s ability and needs, lack of student motivation towards learning activities and provision for adaptive learning environment. The quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional strategy. It is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning course. It is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest level. In this research work, a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective attainment. Catering to the demands of e-learner, an intelligent model is presented in this study for e-learning system that apply supervised machine learning algorithm. An adaptive e-learning system suits every category of learner, improves the learner’s performance and paves way for offering personalized learning experiences.     

A learning style classification mechanism for e-learning

With the growing demand in e-learning, numerous research works have been done to enhance teaching quality in e-learning environments. Among these studies, researchers have indicated that adaptive learning is a critical requirement for promoting the learning performance of students. Adaptive learning provides adaptive learning materials, learning strategies and/or courses according to a student’s learning style. Hence, the first step for achieving adaptive learning environments is to identify students’ learning styles. This paper proposes a learning style classification mechanism to classify and then identify students’ learning styles. The proposed mechanism improves k-nearest neighbor (k-NN) classification and combines it with genetic algorithms (GA). To demonstrate the viability of the proposed mechanism, the proposed mechanism is implemented on an open-learning management system. The learning behavioral features of 117 elementary school students are collected and then classified by the proposed mechanism. The experimental results indicate that the proposed classification mechanism can effectively classify and identify students’ learning styles.