It still feels good and we experience a strangely positive sensation when we flash back to 2010, when the University of Mauritius was announced as the winners of the prestigious award in distance education of the Commonwealth in the category "Interactive Materials Development". In 2016, our team participated in the PCF8 in Malaysia, and it was a really good feeling to see a team of young researchers reach a certain level of maturity presenting in front of an international audience. Their work was commended. PCF9 will now be held in Edinburg and the team is again working to submit proposals to present at the forum. The three abstracts submitted are provided below:
A Digital Learning Transformation Roadmap for the University of Mauritius
The University of Mauritius embarked on the open and distance learning journey in 1993 and engaged in the promotion of distance eLearning and technology-enhanced learning in 2001. At the same time the University’s development was impacted by the integration of technology within different other spheres of the institution’s activities such as financial management and student records. Gradually over the years the University had a well-established financial management system, student information system including online module registration system, the intranet mark posting system, and a human resource management system, an eLearning platform along with a number of other IT-enabled services such as the Google Suite and the Research Management Information System amongst others. However, it has been observed that there are certain gaps and challenges for the institution to achieve its strategic goals. While a number of IT systems have been developed over the past years, they are either operational in isolation or they are under-utilized and might not have not been developed within a coherent strategic context. The University has moved from a traditional credit system to the learner-centered credit system, inspired from the ECTS model in 2018. Such a model is heavily reliant on improved teaching and learning infrastructure, including technology-enabled educational practices as well as on smart and improved services to the academics and students. Within the 21st century context, the strategy of the university is to focus less on the term distance education as the digital technologies have helped to overcome the distance and real-time barrier through virtualization and two-way communication in real time. In this paper we carry out a qualitative analysis using mainly desk studies of existing documents and reports on the current operational model of the University of Mauritius. Based on the information gathered and available a digital transformation roadmap to primarily support the new educational system and the relevant support structures to achieve efficiency, improve learning and teaching and position the University as a key regional player in digital education. The roadmap includes key components such as (i) integration of learning management system with the student information system, (ii) blended learning suite using Google classroom, (iii) knowledge and document management system, (iv) intelligent classroom management through smart card-based services, (v) WebTV and Virtual Lecture Repository and (vi) Mobile Services suite. Within this digital transformation framework, the use predictive analytics through artificial intelligence and machine learning will be transversal to the different components to ensure better efficiency and decision-making processes. A coherent integration strategy and a well-defined action plan, timelines and roles definition are important to ensure a successful implementation of the digital learning transformation process.
Scenario-based Learning Design for Workplace eLearning
eLearning is making significant impact on workplace learning especially in settings where the employer cannot afford to release employees during working hours and where there is a need for rapid and specific personalized training on a particular product or service. In some cases, there are situations where the critical mass is not achieved to justify allocation of resources for presential training. On the other hand, workplace training and learning has to be contextually relevant and concise while achieving key learning outcomes within a specific time-frame. A typical development lifecycle of an eLearning course is a composed of a set of processes and phases depending on the chosen instructional design methods. Classic models such as ADDIE normally span over long periods of time following a waterfall development concept. These approaches or models are not appropriate for workplace eLearning in a professional development context. There is a need for rapid prototyping and development of interactive eLearning products. There are two different approaches for rapid eLearning development namely content-based learning and scenario-based learning. While the rapid eLearning development method can still be applied in a similar manner for each approach, the learning design process is different as one model is mainly centred on knowledge acquisition with some extent of application, while the other model is mainly centred on a complete cycle of knowledge acquisition and application. The former is relevant where a salesperson needs to know, for example, the detailed technical specs of a new computer system which is on sale, while the latter can focus on the development of the right skillset needed to convince a customer to purchase a computer system with the specific technical specs. In this paper we go through the learning design process for scenario-based eLearning using the rapid development methodology using an authentic case-study within the workplace. The main phases of scenario-based eLearning lifecycle is based on the following five phases namely (i) select a specific skillset, (ii) identify and describe a contextual relevant scenario , (iii) develop a storyboard (iv) implement the storyboard into interactive scenes, (v) publish the scenario and (vi) piloting and evaluation. Scenario-based eLearning design are fully SCORM compliant and can be fully integrated into broader course structures on platforms such as MOODLE. We finally demonstrate on the MOODLE Platform how scenario-based eLearning can be used in a hybrid outcomes-based learner centered virtual environment.
The use of learning analytics to improve online learning experiences: a systematic literature review
Information and Communication Technologies are transforming the educational landscape in such a way that there is a blurred line separating traditional teaching and learning and online education. Online education was seen as the logical evolution of distance education with the advances of the Internet and the world-wide web. However, ICTs are transforming the bricks and mortar institutional delivery methods with virtual learning and online learning converging to a such an extent that the learner can experience anytime, anywhere learning irrespective of the mode of education that he or she is engaged into. Such learning transactions occur in virtual environment which are extensively data-driven making educational data mining through learning analytics a useful and powerful tool to assist learning designers and teachers in making pedagogically sound decisions to improve the overall educational experience. Researchers have argued that understanding patterns in such wealth of available data could be of value to address drop-out issues in online learning, improve student engagement and performances as well as the overall learning experience leading to better student satisfaction. Learning analytics, as defined by Long & Siemens (2011), is the means to measure, collect and analyse volumes of data about learners’ progress in order to understand, optimize and improve their learning experiences. Researchers have expressed diverging views about the differences between educational data mining and learning analytics. In this paper we look at the foundations of these divergences, conduct a review of how learning analytics has been applied in online environments and how the field of educational data mining precisely using learning analytics as a method has evolved and impacted on learning experiences of students in terms of retention, performances and student satisfaction. We discuss how different types of analytics such as descriptive, prescriptive and predictive analytics can be used throughout the different phases of the student online learning lifecycle to improve the learning outcomes and experiences of the learner.
