Student learning outcomes and online engagement in time of crisis: the role of e-learning system usability and teacher behavior

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khalid Abed Dahleez ◽  
Ayman A. El-Saleh ◽  
Abrar Mohammed Al Alawi ◽  
Fadi Abdel Muniem Abdel Fattah
Keyword(s):  
Learning Outcomes ◽  
Teacher Behavior ◽  
Learning System ◽  
Equation Modeling ◽  
Research Approach ◽  
Content Type ◽  
Online Engagement ◽  
System Usability ◽  
E Learning

PurposeThis research explores the effect of e-learning Moodle-based system usability on students' learning outcomes with the possible intervening role of teacher's behavior and online engagement.Design/methodology/approachIn this research, the authors followed a quantitative methodology and a deductive research approach. Data were collected from 433 students at different study levels and academic specializations in higher education institutions (HEIs) in Oman. The data have been analyzed using partial least squares structural equation modeling via Smart-PLS.FindingsThe findings of this research show that e-learning system usability affects students' learning outcomes. Moreover, the relationship between these two variables is mediated by teacher behavior and students' online engagement.Originality/valueThis study is important as it adds to the understanding of the role of e-learning system usability in predicting student outcomes. From practical perspectives, especially during the spread of the COVID-19 pandemic, this study also helps practitioners at private HEIs use e-learning systems more efficiently and effectively to improve students' engagement and learning outcomes.

Higher education student engagement in times of pandemic: the role of e-learning system usability and teacher behavior

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khalid Abed Dahleez ◽  
Ayman A. El-Saleh ◽  
Abrar Mohammed Al Alawi ◽  
Fadi Abdelmuniem Abdelfattah
Keyword(s):  
Higher Education ◽  
Student Engagement ◽  
Cognitive Engagement ◽  
Teacher Behavior ◽  
Learning System ◽  
Emotional Engagement ◽  
Education Student ◽  
Content Type ◽  
System Usability ◽  
E Learning

PurposeThis research examined the factors affecting several types of student engagement, namely agentic, behavioral, emotional and cognitive engagement. Specifically, it examined the effect of e-learning system usability on student engagement and explored teacher behavior's possible intervening impact on this relationship.Design/methodology/approachData were collected from 418 students studying at different specializations at Omani private academic institutions. This study employed a quantitative methodology and utilized the Smart-PLS for data analyses.FindingsThe findings showed that e-learning system usability influenced significantly and positively agentic, behavioral and cognitive engagement. However, the link between e-learning system usability and emotional engagement was not significant. Moreover, teacher behavior mediated the relationship between e-learning system usability and the four types of engagement.Originality/valueThis study improves one’s understanding of how the interaction of e-learning system usability and teacher behavior affects several aspects of student engagement. It also helps higher education administrators and policymakers by exploring the influential effects of e-learning systems usability and teacher behavior on facilitating students' engagement.

How does task-technology fit influence cloud-based e-learning continuance and impact?

2019 ◽  
Vol 61 (4) ◽  
pp. 480-499 ◽  
Author(s):  
Yung-Ming Cheng
Keyword(s):  
Structural Equation ◽  
Educational Institution ◽  
Perceived Usefulness ◽  
Learning System ◽  
Equation Modeling ◽  
Comprehensive University ◽  
Content Type ◽  
E Learning ◽  
Task Technology Fit ◽  
Perceived Impact

Purpose According to expectation–confirmation model (ECM) and task-technology fit (TTF) model, the purpose of this paper is to examine the role of TTF in students’ cloud-based e-learning continuance and evaluate whether TTF affects students’ perceived impact on learning of the cloud-based e-learning system within the educational institution. Design/methodology/approach Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 500 questionnaires were distributed in the campus, and 391 (78.2 percent) usable questionnaires were analyzed using structural equation modeling in this study. Findings This study’s results verified that both task characteristics and technology characteristics affected students’ perceived TTF, which significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, and these in turn directly or indirectly led to their continuance intention of the system and perceived impact on learning; essentially, the results strongly supported the research model integrating ECM and TTF model via positioning key constructs as the drivers with all hypothesized links being significant. Originality/value This study contributes to an understanding of the TTF in explaining students’ cloud-based e-learning continuance that is difficult to explain with only their utilitarian perception of the cloud-based e-learning system, and further places considerably more emphasis upon students’ perceived impact on learning greatly driven by their TTF in the system. Thus, this study’s empirical evidence on incorporating ECM and TTF model can shed light on the outcome for cloud-based e-learning continuance and enhance better understanding of a richer post-adoption model.

Will personalized e-Learning increase deep learning in higher education?

2019 ◽  
Vol 47 (1) ◽  
pp. 53-63 ◽  
Author(s):  
María Consuelo Sáiz-Manzanares ◽  
César Ignacio García Osorio ◽  
José Francisco Díez-Pastor ◽  
Luis Jorge Martín Antón
Keyword(s):  
Higher Education ◽  
Student Satisfaction ◽  
Learning Outcomes ◽  
Teaching Practice ◽  
Learning Management Systems ◽  
Learning System ◽  
Management Systems ◽  
Content Type ◽  
E Learning ◽  
Learning Management

PurposeRecent research in higher education has pointed out that personalized e-learning through the use of learning management systems, such as Moodle, improves the academic results of students and facilitates the detection of at-risk students.Design/methodology/approachA sample of 124 students following the Degree in Health Sciences at the University of Burgos participated in this study. The objectives were as follows: to verify whether the use of a Moodle-based personalized e-learning system will predict the learning outcomes of students and the use of effective learning behaviour patterns and to study whether it will increase student satisfaction with teaching practice.FindingsThe use of a Moodle-based personalized e-learning system that included problem-based learning (PBL) methodology predicted the learning outcomes by 42.3 per cent, especially with regard to the results of the quizzes. In addition, it predicted effective behavioural patterns by 74.2 per cent. Increased student satisfaction levels were also identified through the conceptual feedback provided by the teacher, arguably because it facilitated a deeper understanding of the subject matter.Research limitations/implicationsThe results of this work should be treated with caution, because of the sample size and the specificity of the branch of knowledge of the students, as well as the design type. Future studies will be directed at increasing the size of the sample and the diversity of the qualifications.Originality/valueLearning methodology in the twenty-first century has to be guided towards carefully structured work from the pedagogic point of view in the learning management systems allowing for process-oriented feedback and PBL both included in personalized e-learning systems.

Unleashing the role of e-learning in student engagement practices and accounting professional competencies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Munther Al-Nimer ◽  
Ghaith Alsheikh
Keyword(s):  
Student Engagement ◽  
Graduate Students ◽  
Structural Equation ◽  
Sem Analysis ◽  
Professional Competencies ◽  
Equation Modeling ◽  
Content Type ◽  
Mediating Role ◽  
E Learning

PurposePresently, there is a need for graduate students to be well prepared with accounting professional competencies (APCs) as the market is characterized by intensive activities and rare job opportunities. In relation to this is the significant role of student engagement (SE) practices and e-learning. Thus, the present study examined the mediating role of e-learning on the relationship between SE practices and APC, as well as the moderating role of student's demographics on the same relationship.Design/methodology/approachThe study used a structured questionnaire distributed to 428 accounting students enrolled in institutions in Jordan and the obtained response rate was 65.84%. The formulated hypotheses were tested using structural equation modeling in PLS-SEM analysis Version 3.2.7.FindingsOn the basis of the results, there is a significant relationship between SE and e-learning and APC, with e-learning partially mediating the SE-APC relationship. The results also showed that students' demographics have a significant moderating relationship between the same.Originality/valueThe author recommends that universities employ advanced technologies with SE practices for the mobilization of accounting graduate students, with the prerequisite APC skills so they will become competitive and thrive in their professional and practical lives.

Investigating medical professionals' continuance intention of the cloud-based e-learning system: an extension of expectation–confirmation model with flow theory

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ming Cheng
Keyword(s):  
Structural Equation ◽  
Flow Theory ◽  
Learning System ◽  
Theoretical Development ◽  
Equation Modeling ◽  
Medical Professionals ◽  
Continuance Intention ◽  
Content Type ◽  
E Learning ◽  
Expectation Confirmation

PurposeThe purpose of this study is to propose an integrated model based on expectation–confirmation model (ECM), flow theory and human–organization–technology fit framework to examine whether human, organizational and technology factors as antecedents to medical professionals' beliefs can affect their continuance intention of the cloud-based e-learning system.Design/methodology/approachSample data for this study were collected from medical professionals at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 368 (73.6%) useable questionnaires were analyzed using structural equation modeling in this study.FindingsSynthetically speaking, human, organizational and technology factors, as antecedents to medical professionals' continuance intention of the cloud-based e-learning system have been examined, and the results strongly support the research model with all hypothesized links being significant.Originality/valueParticularly, it is worth mentioning that the application of capturing both ECM and flow theory for completely explaining three types of factors (i.e. human, organizational and technology factors) as external variables to medical professionals' cloud-based e-learning continuance intention is well documented, that is, information systems (IS) and nonIS determinants are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into consideration in this study's theoretical development of medical professionals' cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

scholarly journals The research trends in recommender systems for e-learning

2019 ◽  
Vol 14 (1) ◽  
pp. 12-27
Author(s):  
Jiemin Zhong ◽  
Haoran Xie ◽  
Fu Lee Wang
Keyword(s):  
Learning Outcomes ◽  
Recommender Systems ◽  
Learning Systems ◽  
Learning System ◽  
Future Research ◽  
Content Type ◽  
Evaluation Indicator ◽  
Recommendation Algorithms ◽  
E Learning ◽  
Key Indicators

Purpose A recommendation algorithm is typically applied to speculate on users’ preferences based on their behavioral characteristics. The purpose of this paper is to provide a systematic review of recommendation systems by collecting related journal articles from the last five years (i.e. from 2014 to 2018). This paper aims to study the correlations between recommendation technologies and e-learning systems. Design/methodology/approach The paper reviews the relevant articles using five assessment aspects. A coding scheme was put forward that includes the following: the metrics for the e-learning system, the evaluation metrics for the recommendation algorithms, the recommendation filtering technology, the phases of the recommendation process and the learning outcomes of the system. Findings The research indicates that most e-learning systems will adopt the adaptive mechanism as a primary metric, and accuracy is a vital evaluation indicator for recommendation algorithms. In existing e-learning recommender systems, the most common recommendation filtering technology is hybrid filtering. The information collection phase is an important process recognized by most studies. Finally, the learning outcomes of the recommender system can be achieved through two key indicators: affections and correlations. Originality/value The recommendation technology works effectively in closing the gap between the information producer and the information consumer. This technology could help learners find the information they are interested in as well as send them a valuable message. The opportunities and challenges of the current study are discussed; the results of this study could provide a guideline for future research.

Can tasks and learning be balanced? A dual-pathway model of cloud-based e-learning continuance intention and performance outcomes

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ming Cheng
Keyword(s):  
Structural Equation ◽  
Performance Outcomes ◽  
Learning System ◽  
Equation Modeling ◽  
Medical Professionals ◽  
Continuance Intention ◽  
Content Type ◽  
E Learning ◽  
Perceived Impact ◽  
And Performance

Purpose The purpose of this paper is to examine the roles of task-technology fit (TTF), learning-technology fit (LTF) and cognitive absorption (CA) in determining medical professionals’ cloud-based electronic learning (e-learning) system continuance intention and performance outcomes and evaluate whether medical professionals’ perceived impact on learning can affect their perceived impact on tasks within medical institutions. Design/methodology/approach Sample data for this study were collected from medical professionals at six hospitals in Taiwan. A total of 600 questionnaires were distributed, and 373 (62.2%) usable questionnaires were analyzed using structural equation modeling in this study. Findings In this study, medical professionals’ perceived TTF and LTF as antecedents to their cloud-based e-learning continuance intention and performance outcomes were validated, and medical professionals’ perceived impact on learning had a positive effect on their perceived impact on tasks. Synthetically speaking, this study’s results strongly support the research model with all hypothesized links being significant. Originality/value It is particularly worth mentioning that this study introduces a new construct, “LTF,” to conceptualize, define and measure it, and further contributes to the application of capturing both expectation–confirmation model and CA (i.e. an intrinsic motivator) for completely explaining medical professionals’ perceived TTF and LTF as external variables to their cloud-based e-learning continuance intention and performance outcomes.

Determinants of virtual classroom adoption in Jordan: the case of princess Sumaya university for technology

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Kasem Alrousan ◽  
Amro Al-Madadha ◽  
Mohammad Hamdi Al Khasawneh ◽  
Adiy Adel Tweissi
Keyword(s):  
Organizational Support ◽  
Behavioral Intentions ◽  
Virtual Classroom ◽  
Arab Countries ◽  
Learning System ◽  
Equation Modeling ◽  
Survey Method ◽  
Virtual Classrooms ◽  
Content Type ◽  
E Learning

Purpose The purpose of this study is to investigate the factors that affect students’ behavioral intentions to use virtual classrooms at Princess Sumaya University for Technology (PSUT) in Jordan. Design/methodology/approach A quantitative research approach was adopted, an online survey method was used and the data were collected among students at PSUT in Jordan. A total of 511 responses were usable for analysis. A structural equation modeling partial least squares technique was used to examine the hypothesized model. Findings The findings reveal that the proposed factors have direct and indirect relationships with behavioral intentions to use virtual classrooms. They show that students’ satisfaction has a direct influence on behavioral intention, while other variables such as instructor characteristics, virtual classroom quality, perceived self-efficacy, perceived organizational support, perceived ease of use and perceived usefulness have an indirect effect on behavioral intentions to use virtual classrooms. Research limitations/implications The study was conducted at PSUT in Jordan, which could limit the generalizability of the findings. Furthermore, the present study measured students’ behavioral intentions to use virtual classrooms and future research should consider the actual use of virtual classrooms. Practical implications The findings of this study offer significant and useful information to policymakers, instructors, developers and students regarding the use of virtual classrooms in universities. Based on students’ needs and readiness, the findings identify which factors to consider when developing an e-learning system to enhance learning and teaching performance. Originality/value This study extends existing knowledge by developing a conceptual model to identify the key factors of virtual classroom adoption in higher education institutions in Arab countries. This study contributes to the literature in the context of e-learning by validating an extended technology acceptance model from an Arab countries perspective and considering the differences in culture, learning style and physical environment compared to developed countries.

Intellectual capital as a predictor of cooperative prominence through human capital in the Spanish agrifood industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
M. Isabel Sánchez-Hernández ◽  
Francisca Castilla-Polo
Keyword(s):  
Human Capital ◽  
Intellectual Capital ◽  
Structural Equation ◽  
Equation Modeling ◽  
Research Approach ◽  
Model Assessment ◽  
Cross Sectional ◽  
Content Type ◽  
Research And Innovation

PurposeIntellectual capital (IC) has been shown to play a crucial role in promoting competitive success among cooperatives as well as in other types of organizations. However, cooperatives are rarely included in this line of research. This paper aims to analyze how IC in agrifood cooperatives influences their prominence by fostering responsible research and innovation (RRI), reputation and performance.Design/methodology/approachA theoretical model was developed based on a literature review, and a quantitative study was conducted, including a representative sample of the current most prominent Spanish agrifood cooperatives. Structural equation modeling (SEM) was used to examine the validity of constructs, path relationships and recent advances in the predictive model assessment.FindingsThis study’s findings show the specific role of human capital (HC) for enhancing social and structural capital in cooperatives. It was concluded that there is a need to revise and reconsider the role-played by IC in the cooperative movement.Research limitations/implicationsThe main practical contribution is to offer a specific vision of IC for agrifood cooperatives in order to maximize their market prominence. Since the study was conducted in Spain and based on a cross-sectional research approach, even though the new methodological tool partial least squares (PLS) predict was used, the authors cannot affirm whether IC will have the long-term expected effects as assumed in this research and in all contexts of the agrifood industry.Originality/valueThis is the first empirical study that has examined IC in agrifood cooperatives in Spain, with attention focused on the role of HC as a predictor of market success.

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