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.     

eTeacher: Providing personalized assistance to e-learning students

In this paper we present eTeacher, an intelligent agent that provides personalized assistance to e-learning students. eTeacher observes a student’s behavior while he/she is taking online courses and automatically builds the student’s profile. This profile comprises the student’s learning style and information about the student’s performance, such as exercises done, topics studied, exam results. In our approach, a student’s learning style is automatically detected from the student’s actions in an e-learning system using Bayesian networks. Then, eTeacher uses the information contained in the student profile to proactively assist the student by suggesting him/her personalized courses of action that will help him/her during the learning process. eTeacher has been evaluated when assisting System Engineering students and the results obtained thus far are promising.     

Enhancing e-learning effectiveness using an intelligent agent-supported personalized virtual learning environment: An empirical investigation

Virtual learning environments (VLEs) developed under constructivism and embedded personalization learning functions have the potential to meet different requirements of different learners and thus increase e-Learning effectiveness. We formulated internal personalized learning mechanisms by implementing intelligent agents in a VLE under a constructivist learning model and further developed an e-learning effectiveness framework by integrating educational and IS theories. An empirical field experiment involving 228 university students was conducted. The findings suggested that personalized e-learning facilities enhance online learning effectiveness in terms of examination, satisfaction, and self-efficacy criteria.     

Practical guidelines for designing and evaluating educationally oriented recommendations

There is a need for designing educationally oriented recommendations that deal with educational goals as well as learners' preferences and context in a personalised way. They have to be both based on educators' experience and perceived as adequate by learners. This paper compiles practical guidelines to produce personalised recommendations that are meant to foster active learning in online courses. These guidelines integrate three different methodologies: i) user centred design as defined by ISO 9241-210, ii) the e-learning life cycle of personalised educational systems, and iii) the layered evaluation of adaptation features. To illustrate guidelines actual utility, generality and flexibility, the paper describes their applicability to design educational recommendations in two different contexts, which in total involved 125 educators and 595 learners. These applications show benefits for learners and educators. Following this approach, we are targeting to cope with one of the main challenges in current massive open online courses, which are expected to provide personalised education to an increasing number of students without the continuous involvement of educators in supporting learners during their course interactions.     

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.     

Distance learning in advanced military education: Analysis of joint operations course in the Taiwan military

High-ranking officers require advanced military education in war tactics for future combat. However, line officers rarely have time to take such courses on campus. The conventional solution to this problem used to take the inefficient correspondence courses. Whereas Internet technologies progress, online course is the current trend for military training. However, the question is what distance learning methodology best suits such a proprietary learning purpose.This study presents a sequential process of developing distance learning courses in advanced military education. Further, the Petri-Net analytical approach is adopted to discover the essential interaction requirements of advanced military education delivered via Internet. This study developed a systematic method for designing e-learning systems according to specific requirements of target courses. The proposed approach starts by comparing on-campus programs with the existing e-learning systems to identify the steps required to transform the program into an e-learning system. After first outlining the pedagogy of the on-campus program, its proposed teaching flow through the Internet is then sketched. Finally, the Petri-Net model was used for in-depth analysis of the stages affecting the learning curve of the line office taking e-learning courses. The example of a “Joint Operations” AME course elaborated the presented approach. An e-learning system prototype was also designed accordingly. Lastly, an experiment was conducted to verify the efficiency of the presented approach.     

The impact of learning design on student behaviour,satisfaction and performance: A cross-institutional comparison across 151 modules

Pedagogically informed designs of learning are increasingly of interest to researchers in blended and online learning, as learning design is shown to have an impact on student behaviour and outcomes. Although learning design is widely studied, often these studies are individual courses or programmes and few empirical studies have connected learning designs of a substantial number of courses with learning behaviour. In this study we linked 151 modules and 111.256 students with students' behaviour (<400 million minutes of online behaviour), satisfaction and performance at the Open University UK using multiple regression models. Our findings strongly indicate the importance of learning design in predicting and understanding Virtual Learning Environment behaviour and performance of students in blended and online environments. In line with proponents of social learning theories, our primary predictor for academic retention was the time learners spent on communication activities, controlling for various institutional and disciplinary factors. Where possible, appropriate and well designed communication tasks that align with the learning objectives of the course may be a way forward to enhance academic retention.     

EGameFlow: A scale to measure learners’ enjoyment of e-learning games

In an effective e-learning game, the learner’s enjoyment acts as a catalyst to encourage his/her learning initiative. Therefore, the availability of a scale that effectively measures the enjoyment offered by e-learning games assist the game designer to understanding the strength and flaw of the game efficiently from the learner’s points of view. E-learning games are aimed at the achievement of learning objectives via the creation of a flow effect. Thus, this study is based on Sweetser’s & Wyeth’s framework to develop a more rigorous scale that assesses user enjoyment of e-learning games. The scale developed in the present study consists of eight dimensions: Immersion, social interaction, challenge, goal clarity, feedback, concentration, control, and knowledge improvement. Four learning games employed in a university’s online learning course “Introduction to Software Application” were used as the instruments of scale verification. Survey questionnaires were distributed to students taking the course and 166 valid samples were subsequently collected. The results showed that the validity and reliability of the scale, EGameFlow, were satisfactory. Thus, the measurement is an effective tool for evaluating the level of enjoyment provided by e-learning games to their users.     

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.     

Comparing the social knowledge construction behavioral patterns of problem-based online asynchronous discussion in e/m-learning environments

In recent years, researchers have conducted various studies on applying wireless networking technology and mobile devices in education settings. However, research on behavioral patterns in learners' online asynchronous discussions with mobile devices is limited. The purposes of this study are to develop a mobile learning system, mobile interactive teaching feedback system (MITFS), linked to both mobile devices and the internet, to support learners with online asynchronous discussion, and combine content analysis and sequential analysis to compare and contrast the social knowledge construction behavioral patterns of problem-based asynchronous discussion in e-learning and m-learning environments. This study investigated four weeks of online discussions in an “Introduction to Computer Science” course involving forty first year university students. The control group (online asynchronous discussion without mobile devices) and the experimental group (online asynchronous discussion with mobile devices) in the group discussions were explored. By using content analysis and sequential analysis for the problem-based online asynchronous discussion of the behavioral patterns and differences between students in control and experimental group, the results showed that using mobile devices in online asynchronous discussion influenced students' learning performance. Some interesting results were found. Firstly, when the students used mobile devices in discussion situations, they could more engage in reflecting thinking, sharing more information, and further facilitating social knowledge construction among group members. Secondly, the experimental group performed better than the control group in terms of participation and diversity in knowledge construction behavioral patterns. Finally, based upon the findings, some implications are proposed for further research.     

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.     

Which social elements are visible in virtual groups? Addressing the categorization of social expressions

Learning is a social process. That is why it is extremely important to understand how students interact socially in online courses and how it affects the learning process. However, social aspects, understood as those expressions or comments that go beyond strictly academic interaction, i.e. the need to carry out group work, are not clearly defined. Researchers have proposed different models of categories to observe or measure social aspects. This paper contributes to this field through addressing the categorization of social expression in online groups through a qualitative research procedure. Specifically, 19 indicators have been identified and organized into 4 categories: formal, attitudinal, emotional and informal. The findings suggest that those indicators related to formal and attitudinal aspects appear more often than emotional and informal ones. Different profiles (Psychology or Computer Engineering) as well as different levels of experience in online learning (beginners or experts) have also been analyzed, concluding that Psychology students turn to social expressions more often than Computer Engineering ones. As students progress in their undergraduate studies, social expressions are perceived and used to the extent that they ease the learning process.     

Investigating critical success factors in online learning environments in higher education systems in the Caribbean*

ABSTRACT

Online learning has grown as a key method in education management over the last couple of decades. Studies have shown that significant investments in this technology are being made by universities, yet the full benefits expected have not been realized due to issues and challenges experienced by stakeholders such as learners and instructors in adopting and effectively using e-learning. This is especially true in developing economies where they may be attempting online delivery modes for the first time. In this study, we explore the question “What are the factors that influence university students’ adoption and use of an e-learning system in the context of the English-speaking Caribbean?” using an extended technology acceptance model framework. Partial least squares analysis was used to test the derived research model and found that critical success factors influencing students’ perception and use in online learning settings, particularly those within a developing economy conditions, include supportive cultural practices, access to computers, system or online environment availability, computer and online learning self-efficacy, user perception of usefulness and ease of use. These results have significant implications for university executives and policy-makers as they consider adopting online learning delivery modalities for users.     

Effects of social-interactive engagement on the dropout ratio in online learning: insights from MOOC

In online learning, the high dropout ratio is a serious problem and reflects a poor level of motivation in e-learning programmes. Social-interactive engagement may greatly affect users’ attitudes and choices in many fields; among these, online learning is inevitably impacted by factors such as social connections. To study the impact of social-interactive engagement on the dropout ratio and learning progress, iMOOC was employed as the study object using data from 619 courses and 2,071,147 learners, as well as 19,451,428 learning records. As engagement is a process of collecting experiences, the learner’s experience plays a significant role in reducing the dropout ratio. Social-interactive engagement helps to reduce the dropout ratio; thus, learners should be encouraged to engage in online activities, such as discussions, note sharing, commenting and Q&A, to alleviate the feelings of being disconnected and isolated. Through an empirical study, we also find that the longer a learner's registered time is, the lower the dropout ratio. From the perspective of the courses themselves, the dropout ratios of shorter or more difficult courses are lower than those of longer or less-difficult courses. This paper provides theoretical and practical recommendations for reducing the dropout ratio in online learning and improving learning efficiency.     

eTeacher: Providing personalized assistance to e-learning students

In this paper we present eTeacher, an intelligent agent that provides personalized assistance to e-learning students. eTeacher observes a student’s behavior while he/she is taking online courses and automatically builds the student’s profile. This profile comprises the student’s learning style and information about the student’s performance, such as exercises done, topics studied, exam results. In our approach, a student’s learning style is automatically detected from the student’s actions in an e-learning system using Bayesian networks. Then, eTeacher uses the information contained in the student profile to proactively assist the student by suggesting him/her personalized courses of action that will help him/her during the learning process. eTeacher has been evaluated when assisting System Engineering students and the results obtained thus far are promising.     

Attitudes of college students enrolled in 2-year health care programs towards online learning

Colleges offering 2-year diplomas to high-school graduates were among the forefront leaders in online learning however studies illustrating appropriate course construction for such student populations are scarce. Pharmacy Math (MATH16532) is a core course for students enrolled in the Practical Nursing (PN) and Pharmacy Technician (PT) programs at Sheridan Institute. PT and PN students enrolled in MATH16532 during their first term were surveyed to determine student attitudes and skills gained from participating in an online course. Students were then followed up during their second term studies to determine transferability of skills gained. Initially, students did not exhibit a positive attitude towards the online version of Math16532. Participation in the online version of MATH16532 however allowed students to enhance their written ability and critical appraisal skills, gain time management skills, and become independent learners. PT and PN students preferred an orientation session at the beginning of the course and a well organized, easy-to-navigate course. Even though considered as predominantly digital native students, both student groups remained anxious throughout the course regarding the online delivery and preferred a hybrid mode of delivery. Despite the initial resistance to an online math course, students indicated that they would retake the course again in an online format towards the end of the course and there appeared to be a trend to enrol in another online course. Several recommendations regarding the design and construct of online courses in a 2-year college program are provided to facilitate acceptance of online learning for students enrolled in such programs.     

Mobile learning: A framework and evaluation

Wireless data communications in form of Short Message Service (SMS) and Wireless Access Protocols (WAP) browsers have gained global popularity, yet, not much has been done to extend the usage of these devices in electronic learning (e-learning). This project explores the extension of e-learning into wireless/handheld (W/H) computing devices with the help of a mobile learning (m-learning) framework. This framework provides the requirements to develop m-learning applications that can be used to complement classroom or distance learning. A prototype application was developed to link W/H devices to three course websites. The m-learning applications were pilot-tested for two semesters with a total of 63 students from undergraduate and graduate courses at our university. The students used the m-learning environment with a variety of W/H devices and reported their experiences through a survey and interviews at the end of the semester. The results from this exploratory study provide a better understanding on the role of mobile technology in higher education.     

Learning styles' recognition in e-learning environments with feed-forward neural networks

Abstract People have unique ways of learning, which may greatly affect the learning process and, therefore, its outcome. In order to be effective, e-learning systems should be capable of adapting the content of courses to the individual characteristics of students. In this regard, some educational systems have proposed the use of questionnaires for determining a student learning style; and then adapting their behaviour according to the students' styles. However, the use of questionnaires is shown to be not only a time-consuming investment but also an unreliable method for acquiring learning style characterisations. In this paper, we present an approach to recognize automatically the learning styles of individual students according to the actions that he or she has performed in an e-learning environment. This recognition technique is based upon feed-forward neural networks.     

Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach

The use of animation and multimedia for learning is now further extended by the provision of entire Virtual Reality Learning Environments (VRLE). This highlights a shift in Web-based learning from a conventional multimedia to a more immersive, interactive, intuitive and exciting VR learning environment. VRLEs simulate the real world through the application of 3D models that initiates interaction, immersion and trigger the imagination of the learner. The question of good pedagogy and use of technology innovations comes into focus once again. Educators attempt to find theoretical guidelines or instructional principles that could assist them in developing and applying a novel VR learning environment intelligently. This paper introduces the educational use of Web-based 3D technologies and highlights in particular VR features. It then identifies constructivist learning as the pedagogical engine driving the construction of VRLE and discusses five constructivist learning approaches. Furthermore, the authors provide two case studies to investigate VRLEs for learning purposes. The authors conclude with formulating some guidelines for the effective use of VRLEs, including discussion of the limitations and implications for the future study of VRLEs.     

OLES: an instrument for refining the design of e-learning environments

Abstract Designing and implementing effective e-learning is a complex process, which involves many factors. Lecturers need to constantly consider, evaluate and adjust these factors to provide effective e-learning environments for students. In this paper, we report on the design and development of the Online Learning Environment Survey (OLES), an instrument which can be used to gather and represent data on students' 'actual' (experienced) and 'preferred' (ideal) learning environments. We describe the use of this instrument in blended learning environments with university classes, illustrating how OLES can be used by educators striving for good practice in the design of effective online learning environments.