Query: e-learning

title: EMOTION AND E LEARNING
abstract: Traditionally, emotion and cognition have been viewed as polar opposites and this view has been incorporated into theories of learning. One reason for this may be a lack of clarity in defining emotion. In fact there are other perspectives on how emotion and cognition, emotion and learning, are related. These considerations emerge with renewed vigor with the move to online education. Theauthor interviewed eleven students studying online. These students identified emotions which were critical to their online learning. Evidence from the literature and from the interviews positions emotion as central and essential to the teaching/ learning process.

title: E learning success determinants: Brazilian empirical study
abstract: E learning is a web based learning ecosystem for the dissemination of information, communication, and knowledge for education and training. Understanding the impact of e learning on society, as well as its benefits, is important to link e learning systems to their success drivers. The aim of this study is to find the determinants of user perceived satisfaction, use, and individual impact of e learning. This study proposes a theoretical model integrating theories of information systems' satisfaction and success in the e learning systems. The model was empirically validated in higher education institutions and university centers in Brazil through a quantitative method of structural equation modeling. Collaboration quality, information quality, and user perceived satisfaction explain e learning use. The drivers of user perceived satisfaction are information quality, system quality, instructor attitude toward e learning, diversity in assessment, and learner perceived interaction with others. System quality, use, and user perceived satisfaction explain individual impact.

title: Factors affecting the E learning acceptance: A case study from UAE
abstract: The main objective of this article is to study the factors that affect university students' acceptance of E learning systems. To achieve this objective, we have proposed a new model that aims to investigate the impact of innovativeness, quality, trust, and knowledge sharing on E learning acceptance. Data collection has taken place through an online questionnaire survey, which was carried out at The British University in Dubai (BUiD) and University of Fujairah (UOF) in the UAE. There were 251 students participated in this study. Data were analyzed using SmartPLS and SPSS. The Structural Equation Modelling (SEM) has been used to validate the proposed model. The outcomes revealed that knowledge sharing and quality in the universities have a positive influence on E learning acceptance among the students. Innovativeness and trust were found not to significantly affect the E learning system acceptance. By identifying the factors that influence the E learning acceptance, it will be more useful to provide better services for E learning. Other implications are also presented in the study.

title: E learning for health professionals.
abstract: The use of e learning, defined as any educational intervention mediated electronically via the Internet, has steadily increased among health professionals worldwide. Several studies have attempted to measure the effects of e learning in medical practice, which has often been associated with large positive effects when compared to no intervention and with small positive effects when compared with traditional learning (without access to e learning) However, results are not conclusive.  To assess the effects of e learning programmes versus traditional learning in licensed health professionals for improving patient outcomes or health professionals' behaviours, skills and knowledge.  We searched CENTRAL, MEDLINE, Embase, five other databases and three trial registers up to July 2016, without any restrictions based on language or status of publication. We examined the reference lists of the included studies and other relevant reviews. If necessary, we contacted the study authors to collect additional information on studies.  Randomised trials assessing the effectiveness of e learning versus traditional learning for health professionals. We excluded non randomised trials and trials involving undergraduate health professionals.  Two authors independently selected studies, extracted data and assessed risk of bias. We graded the certainty of evidence for each outcome using the GRADE approach and standardised the outcome effects using relative risks (risk ratio (RR) or odds ratio (OR) or standardised mean difference (SMD) when possible.  We included 16 randomised trials involving 5679 licensed health professionals (4759 mixed health professionals, 587 nurses, 300 doctors and 33 childcare health consultants).When compared with traditional learning at 12 month follow up, low certainty evidence suggests that e learning may make little or no difference for the following patient outcomes: the proportion of patients with low density lipoprotein (LDL) cholesterol of less than 100 mg/dL (adjusted difference 4.0% 95% confidence interval (CI) 0.3 to 7.9, N 6399 patients, 1 study) and the proportion with glycated haemoglobin level of less than 8% (adjusted difference 4.6% 95% CI 1.5 to 9.8, 3114 patients, 1 study) At 3 to 12 month follow up, low certainty evidence indicates that e learning may make little or no difference on the following behaviours in health professionals: screening for dyslipidaemia (OR 0.90, 95% CI 0.77 to 1.06, 6027 patients, 2 studies) and treatment for dyslipidaemia (OR 1.15, 95% CI 0.89 to 1.48, 5491 patients, 2 studies) It is uncertain whether e learning improves or reduces health professionals' skills (2912 health professionals; 6 studies; very low certainty evidence) and it may make little or no difference in health professionals' knowledge (3236 participants; 11 studies; low certainty evidence).Due to the paucity of studies and data, we were unable to explore differences in effects across different subgroups. Owing to poor reporting, we were unable to collect sufficient information to complete a meaningful 'Risk of bias' assessment for most of the quality criteria. We evaluated the risk of bias as unclear for most studies, but we classified the largest trial as being at low risk of bias. Missing data represented a potential source of bias in several studies.  When compared to traditional learning, e learning may make little or no difference in patient outcomes or health professionals' behaviours, skills or knowledge. Even if e learning could be more successful than traditional learning in particular medical education settings, general claims of it as inherently more effective than traditional learning may be misleading.

title: E learning continuance satisfaction in higher education: a unified perspective from instructors and students
abstract: This study aims to determine the key factors affecting students' and instructors' continuance satisfaction with e learning in the higher education context. In order to identify the factors that impact e learning continuation in higher education institutions, a systematic review of the literature was conducted, revealing that the majority of studies have reported the essential role of satisfaction in mediating the relationship between 11 factors and users' decisions to continue using e learning systems. This study then proposed that users, both students and instructors, must continually be satisfied with the e learning systems offered by higher education institutions if they are to continue using them. We term this 'e learning continuance satisfaction. The formation of a unified perspective of instructors and students on the core factors that impact e learning continuance was then investigated, in addition to the causal relationships between these factors and e learning continuance satisfaction. The Fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method was used to analyze data collected from 9 instructors and 38 students via an interview survey and the results yielded five core factors information quality, task technology fit, system quality, utility value, and usefulness that influence users' e learning continuance satisfaction. Several different causal relationships between the factors identified from both students' and instructors' perspectives were also identified and used to form a single viewpoint. Our findings provide new insights into how higher education institutions can promote continuance satisfaction in order to ensure continuation of e learning.

title: The role of textbook learning resources in e learning: A taxonomic study
abstract: While textbooks are crucial to learning in the traditional classroom based setting, their role in e learning environment might be different. Through a categorical analysis, this study investigates if the currently available learning resources provided by textbooks are suitable for e learning purpose. An e learning framework incorporating different stages of learning and usage of learning resources was first developed as a guide. Then, a sample of learning resources that came with 100 commonly used textbooks in the disciplines of logistics/supply chain management and information systems were classified using the framework. To corroborate the classification, cluster analysis was also conducted to identify major clusters of learning resources along two dimensions complexity of content and ease of use. The findings show that most of the sampled textbook learning resources are only suitable for low order to mid order learning according to the revised Bloom's taxonomy. The majority of the resources investigated lack the sophistication and complexity to support high order learning that involves a great deal of interaction and collaboration among learners and facilitators on e learning platforms. In other words, existing textbook learning resources might contribute well to self regulated low order and mid order e learning involving basic to intermediate cognitive processes, such as remembering, understanding, applying and analysing. They are generally ill designed to facilitate high order e learning involving advanced cognitive processes, such as evaluating and creating, which require extensive interaction and collaboration among learners and facilitators in an e learning environment. An e learning framework incorporating usage of learning resources is presented.Learning resources of 100 commonly used textbooks are classified using the framework.Cluster analysis is conducted to corroborate the outcome of the classification.Textbook resources are found mainly suitable for low order to mid order e learning.There is a need for e learning resources supporting online interaction among peers.

title: Use of E Learning by University Students in Malaysian Higher Educational Institutions: A Case in Universiti Teknologi Malaysia
abstract: This paper examines university students' intention to utilize e learning. In this paper, we apply and use the theory of a technology acceptance model. We employ the structural equation modeling approach with a SmartPLS software to investigate students' adoption process. Findings indicate that the content of e learning and self efficacy has a positive impact and substantially associated with perceived usefulness and student satisfaction, which impact university students' intention to utilize e learning. Although e learning has gained acceptance in universities around the world, the study of the intention to use e learning is still largely unexplored in Malaysia. The developed model is employed to explain the university student's intention to utilize e learning. The study concludes that university students in Malaysia have positive perceptions toward e learning and intend to practice it for educational purposes.

title: Investigating users' perspectives on e learning: An integration of TAM and IS success model
abstract: This study investigates an integrated model of TAM and IS success model.E learning satisfaction and usage intention both are explained with four variables.Intention and satisfaction both predict the actual use of e learning.System quality and information quality are found to be the most important drivers.Perceived usefulness mediates the relationship between ease of use and intention. The purpose of this paper is to examine an integrated model of TAM and D&M to explore the effects of quality features, perceived ease of use, perceived usefulness on users' intentions and satisfaction, alongside the mediating effect of usability towards use of e learning in Iran. Based on the e learning user data collected through a survey, structural equations modeling (SEM) and path analysis were employed to test the research model. The results revealed that "intention" and "user satisfaction" both had positive effects on actual use of e learning. "System quality" and "information quality" were found to be the primary factors driving users' intentions and satisfaction towards use of e learning. At last, "perceived usefulness" mediated the relationship between ease of use and users' intentions. The sample consisted of e learning users of four public universities in Iran. Past studies have seldom examined an integrated model in the context of e learning in developing countries. Moreover, this paper tries to provide a literature review of recent published studies in the field of e learning.

title: Exploring the role of e learning readiness on student satisfaction and motivation in flipped classroom
abstract: Decrease in student satisfaction and motivation in flipped classroom (FC) model of instruction is among frequently observed problems. And these problems could reduce the efficiency of FC model. It is believed that the problems related to student satisfaction and motivation in FC model of instruction are related to the e learning readiness of the students. The purpose of the current study was to explore the impact of the e learning readiness of the students on student satisfaction and motivation in FC model of instruction. The study was carried out with 236 undergraduate students taking Computing I class taught using FC model of instruction. Data were collected from three self report instruments: E learning Readiness Scale (subscales: computer self efficacy, internet self efficacy, online communication self efficacy, self directed learning, learner control and motivation towards e learning) Satisfaction Scale and Motivated Strategies for Learning Questionnaire. The path analyses with structural equation modelling (SEM) further verified that students' e learning readiness were related to their satisfaction and motivation while undertaking academic tasks in FC model of instruction. The results of the study indicated that students' e learning readiness was a significant predictor of their satisfaction and motivation in FC model of instruction. Findings were presented and discussed for future studies and applications. Satisfaction (SS) and motivation (MSLQ) in flipped classroom (FC) were examined.E learning readiness has an important role in FC.E learning readiness positively affect SS and MSLQ in FC.

title: Knowledge based recommendation: a review of ontology based recommender systems for e learning
abstract: Recommender systems in e learning domain play an important role in assisting the learners to find useful and relevant learning materials that meet their learning needs. Personalized intelligent agents and recommender systems have been widely accepted as solutions towards overcoming information retrieval challenges by learners arising from information overload. Use of ontology for knowledge representation in knowledge based recommender systems for e learning has become an interesting research area. In knowledge based recommendation for e learning resources, ontology is used to represent knowledge about the learner and learning resources. Although a number of review studies have been carried out in the area of recommender systems, there are still gaps and deficiencies in the comprehensive literature review and survey in the specific area of ontology based recommendation for e learning. In this paper, we present a review of literature on ontology based recommenders for e learning. First, we analyze and classify the journal papers that were published from 2005 to 2014 in the field of ontology based recommendation for e learning. Secondly, we categorize the different recommendation techniques used by ontology based e learning recommenders. Thirdly, we categorize the knowledge representation technique, ontology type and ontology representation language used by ontology based recommender systems, as well as types of learning resources recommended by e learning recommenders. Lastly, we discuss the future trends of this recommendation approach in the context of e learning. This study shows that use of ontology for knowledge representation in e learning recommender systems can improve the quality of recommendations. It was also evident that hybridization of knowledge based recommendation with other recommendation techniques can enhance the effectiveness of e learning recommenders.