Search results

To illustrate the value of using a learning management system to streamline training administration tasks and, especially, to provide evidence of compliance for the authorities in regulated industries.

The approach to this topic is via interviews with experts. Officials from five US‐based organisations – four health‐care and one pharmaceutical organisation – explain the value of a learning management system to their particular organisation. They also outline the additional benefits that they have experienced – such as medical staff being able to spend more time with patients. There are also comments from an industry analyst specialising in learning management systems.

Learning management systems not only enable training to be standardised and co‐ordinated within the largest and most fragmented organisations but also provide accurate records of learning and competence – which are vital in highly regulated industries.

These are that every organisation in a “regulated” industry – especially those in the health‐care sector – should use an enterprise‐wide learning management system to improve the efficiency of their staff training and development. Moreover, they should use the user‐monitoring and record‐keeping functions of the learning management system to keep automated, up‐to‐date records of knowledge, skills and competencies for that industry's regulatory bodies.

This paper demonstrates – albeit anecdotally – the value of a learning management system, not just for the training function but also in operational terms. As such, it should be of interest not only to training and HR professionals but also to those responsible for organisational strategy, planning and operation.

Experience shows that there are problems arising from the implementation of learning management systems (LMS). Indications are that they are too e‐learning technology driven, emphasising the virtual component and neglecting the precursory development of a vibrant and committed formal learning organisation culture and infrastructure. This article aims to investigate the benefits of applying a constructivist methodology in the implementation of new LMS.

This article is a reflective assessment on the benefits of applying a constructivist methodology when designing and implementing strategic new learning and knowledge‐based organisation development investments.

The paper reveals a corporate strategic learning management solution (SLMS) approach which is synthesised out of a successful macro‐educational intervention in the UK; that of the Foundation Degree Forward (fdf) initiative.

This process involves using a holistic stakeholder approach that connects with all the management, resourcing and underlying organisational activities which are essential for the creation of a well managed, cohesive and sustainable strategic learning intervention.

The purpose of this paper is to explore technology strategies and policies in the areas of standards, repositioning of technology, and service‐oriented architecture that focus on enabling innovation while retaining coherence and viability.

The paper uses the concepts of shearing layers and Personal Learning Environments to define appropriate boundaries between individual, departmental, institutional, national, and global network control.

Education systems today can be characterised as a recursive metasystem of separate systems. Each system uses innovation as part of strategic planning to try to realise its potential and release its latency. However, these strategic activities generate friction with the metasystem, which puts the brakes on innovation in its subsystems. The architectural concepts of shearing layers and flexible couplings provide a model for reducing this friction. One way of enabling shearing layers in educational technology is to offer polymodal access to services.

In managing technology, institutions should actively consider relocating functions to other layers of the education system, including technologies owned by individual learners and teachers. They should think of technology in terms of supporting flexible shearing layers between rapidly changing organisational structures. The concept of polymodal access should be used when looking to deploy services at any level of the organisation. Critical cross‐cutting issues of privacy, identity, and business intelligence need to be designed into the institutional and departmental service infrastructure. Institutions should develop innovation‐oriented technology policies. At the department or course level, policies should also reflect the position of the organisation with regard to the equitable experience of education.

The approach outlined demonstrates that institutions have the capacity to reinvent their technology strategies and policies in such a way as to unlock innovation at the departmental and personal level, without creating a crisis in IT service management. On the other hand, it also shows that the PLE perspective needs to be balanced with a broader view of student disposition and institutional goals to become recognised as part of the institutional technology strategy and policies.

Businesses need to make money and/or save money if they want to be successful. Organisations are now realising that they can do both if they implement software systems – known as learning management systems (LMS) – to collect and analyse data relating to the skills of their workforce. While, once, it was enough to have transferred some training materials from the classroom to CD‐ROM, people soon began to wonder whether anyone actually used the CD‐ROMs. With that realisation, the concept of a learning management system was born. One of the most advanced LMSs in the world – and a market leader, with some 2,500 users world‐wide – is the LMS produced by Pathlore. It lets companies plan, deliver and manage e‐learning, then assess learning performance by student, group, line of business or across the entire extended enterprise. The system also lets companies manage their organisational skills and competencies: employees assess themselves online and then go directly to prescribed online or classroom learning. Although this technology is not a panacea and will not pay dividends for every company, it can offer great benefits to those organisations with a large and/or widely geographically dispersed workforce.

This study aims to investigate factors that could predict the continued usage of e-learning systems, such as the learning management systems (LMS) at a Technical University in Ghana using machine learning algorithms.

The proposed model for this study adopted a unified theory of acceptance and use of technology as a base model and incorporated the following constructs: availability of resources (AR), computer self-efficacy (CSE), perceived enjoyment (PE) and continuance intention to use (CIU). The study used an online questionnaire to collect data from 280 students of a Technical University in Ghana. The partial least square-structural equation model (PLS-SEM) method was used to determine the measurement model’s reliability and validity. Machine learning algorithms were used to determine the relationships among the constructs in the proposed research model.

The findings from the study confirmed that AR, CSE, PE, performance expectancy, effort expectancy and social influence predicted students’ continuance intention to use the LMS. In addition, CIU and facilitating conditions predicted the continuance use of the LMS.

The use of machine learning algorithms in e-learning systems literature has been rarely used. Thus, this study contributes to the literature on the continuance use of e-learning systems using machine learning algorithms. Furthermore, this study contributes to the literature on the continuance use of e-learning systems in developing countries, especially in a Ghanaian higher education context.

Although multiple studies examine institutional transitions of learning management systems (LMS) or compare their merits, studies examining students' free choice of access on parallel LMSs for the same course are absent from the literature. In order to investigate usage in a free‐choice situation, identical content was posted at the same time to two different LMSs in a large enrollment class with a diversity of majors.

Two prevalent LMSs were utilized in the study: WebCT, which was in existence at a university‐wide level previously, and Moodle, which will become the new university‐wide system in the 2012‐13 academic year onwards. Both student self‐reports and LMS log usage data were analyzed. LMS preferences and usage groups were categorized.

Although this inquiry revealed that most students chose to use the WebCT system (85 per cent WebCT users, 15 per cent Moodle users; both self‐reported and log‐verified), the reasons given for WebCT preference pertained largely to habit and that most other courses are using the WebCT LMS. In contrast, the reasons given for using Moodle spoke directly to the attributes of the LMS itself, namely the interface quality and the way it is organized.

This study indicates that institutions should look beyond student usage patterns in making LMS choices, and that LMS quality is sometimes, and perhaps unfortunately, overshadowed by student habit and familiarity.

The purpose of this paper is to demonstrate a process of faculty utilization of learning analytics by evaluating students’ course objective achievement results to enable student reflection, student remediation and faculty curriculum evaluation.

Upon the completion of a backward curriculum design process, the authors utilized learning analytics to improve advising, student reflection, remediation and curriculum evaluation. The learning management system incorporated the learning analytics tool to assist the learning analytics process. The course faculty, student advisors and students utilized the learning analytics throughout the academic year.

Unlike relying merely on student grades and other proxy indicators of learning, the learning analytics tool provided immediate and direct data to multiple stakeholders for advising, student reflection, student remediation and course curriculum evaluation. The authors believe it was a meaningful endeavor. It enabled meaningful conversations focusing on course learning objectives and provided detailed information on each student. The learning analytics tool also provided detailed information regarding which areas faculty needed to improve in the curriculum.

Most of the literature on learning analytics present the cases that administrators utilized learning analytics to make higher level decisions and researchers to explore the factors involved in learning. This paper provides cases to faculty regarding how learning analytics can benefit the faculty and the students.

The purpose of this paper is to compare the perceptions of educators and students with a learning management system (LMS). The comparison is based on survey data collected from 185 educators and 249 students in a Finnish university who use a popular LMS, Moodle.

The analysis of the survey data follows a two-phase strategy. In the first phase, perceptions of educators and students regarding ease of use, result demonstrability, usefulness, access, reliability, compatibility, satisfaction, and continuance intention were compared using one way analysis of variance (ANOVA). In the second phase, partial least squares (PLS) technique is employed to compare the path values and explained variances of satisfaction, and continuance intention by putting relevant variables as predictors.

The ANOVA results suggest that students have higher positive perceptions regarding ease of use, usefulness, access, reliability, and compatibility of the LMS than the educators. The PLS analysis results revealed that the amount of variance of students’ satisfaction explained by its predictors was 9 percentage points lower than that of educators. It also revealed that the variance of students’ continuance intention explained by satisfaction and usefulness was 12 percentage points lower than that of educators.

The study concludes with both theoretical and managerial implications.

While prior research has investigated either educators’ or students’ perspective, the authors have investigated both and presented a comparison. The authors have reported several differences that help practitioners make customized intervention plan.

Students' satisfaction with e-learning outcomes is a vital component in determining the adoption of e-learning systems. Understanding the antecedent factors impacting students' satisfaction with e-learning outcomes helps decision-makers at the higher education to take the necessary actions to enhance the quality of students' performance, especially during the exceptional times, such as the COVID-19 pandemic.

This paper aims to determine and analyse the antecedent factors influencing students' satisfaction with e-learning outcomes during the pandemic. Structural equation modelling (SEM) is used to analysis a proposed research model.

The SEM results show that digital communities in e-learning, information technology (quality and accessibility) and the online course design quality directly influence students' satisfaction with e-learning outcomes. More interestingly, results show that the COVID-19-related factors (1) awareness of the COVID-19, (2) perceived challenges (negatively) and (3) the educational institutions' preparedness also influence e-learning outcomes.

The results suggest that the decision-makers at the educational institutions should consider adopting a blended learning system approach to deliver e-learning during the emergency, such as the COVID-19 outbreak situation.

This is one of the first studies in higher education context, which seek to identify the antecedent factors that influence students' satisfaction with e-learning outcomes during the COVID-19 pandemic.