A literature synthesis of personalised technology-enhanced learning: what works and why

Personalised learning, having seen both surges and declines in popularity over the past few decades, is once again enjoying a resurgence. Examples include digital resources tailored to a particular learner’s needs, or individual feedback on a student’s assessed work. In addition, personalised technology-enhanced learning (TEL) now seems to be attracting interest from philanthropists and venture capitalists indicating a new level of enthusiasm for the area and a potential growth industry. However, these industries may be driven by profit rather than pedagogy, and hence it is vital these new developments are informed by relevant, evidence-based research. For many people, personalised learning is an ambiguous and even loaded term that promises much but does not always deliver. This paper provides an in-depth and critical review and synthesis of how personalisation has been represented in the literature since 2000, with a particular focus on TEL. We examine the reasons why personalised learning can be beneficial and examine how TEL can contribute to this. We also unpack how personalisation can contribute to more effective learning. Lastly, we examine the limitations of personalised learning and discuss the potential impacts on wider stakeholders

Personalisation in MOOCs: a critical literature review

The advent and rise of Massive Open Online Courses (MOOCs) have brought many issues to the area of educational technology. Researchers in the field have been addressing these issues such as pedagogical quality of MOOCs, high attrition rates, and sustainability of MOOCs. However, MOOCs personalisation has not been subject of the wide discussions around MOOCs. This paper presents a critical literature survey and analysis of the available literature on personalisation in MOOCs to identify the needs, the current states and efforts to personalise learning in MOOCs. The findings illustrate that there is a growing attention to personalisation to improve learners’ individual learning experiences in MOOCs. In order to implement personalised services, personalised learning path, personalised assessment and feedback, personalised forum thread and recommendation service for related learning materials or learning tasks are commonly applied

Innovating Pedagogy 2015: Open University Innovation Report 4

This series of reports explores new forms of teaching, learning and assessment for an interactive world, to guide teachers and policy makers in productive innovation. This fourth report proposes ten innovations that are already in currency but have not yet had a profound influence on education. To produce it, a group of academics at the Institute of Educational Technology in The Open University collaborated with researchers from the Center for Technology in Learning at SRI International. We proposed a long list of new educational terms, theories, and practices. We then pared these down to ten that have the potential to provoke major shifts in educational practice, particularly in post-school education. Lastly, we drew on published and unpublished writings to compile the ten sketches of new pedagogies that might transform education. These are summarised below in an approximate order of immediacy and timescale to widespread implementation

The MOOC and learning analytics innovation cycle (MOLAC): a reflective summary of ongoing research and its challenges.

This article describes the MOOCS and Learning Analytics framework (MOLAC). Based on a brief review of ongoing challenges in the field, the article develops a vision for the future use of MOOCs and Learning Analytics to foster educational innovation

How learners’ interactions sustain engagement: a MOOC case study

In 2015, 35 million learners participated online in 4,200 MOOCs organised by over 500 universities. Learning designers orchestrate MOOC content to engage learners at scale and retain interest by carefully mixing videos, lectures, readings, quizzes, and discussions. Universally, far fewer people actually participate in MOOCs than originally sign up with a steady attrition as courses progress. Studies have correlated social engagement to completion rates. The FutureLearn MOOC platform specifically provides opportunities to share opinions and to reflect by posting comments, replying, or following discussion threads. This paper investigates learners’ social behaviours in MOOCs and the impact of engagement on course completion. A preliminary study suggested that dropout rates will be lower when learners engage in repeated and frequent social interactions. We subsequently reviewed the literature of prediction models and applied social network analysis techniques to characterise participants’ online interactions examining implications for participant achievements. We analysed discussions in an eight week FutureLearn MOOC, with 9855 enrolled learners. Findings indicate that if learners starts following someone, the probability of their finishing the course is increased; if learners also interact with those they follow, they are highly likely to complete, both important factors to add to the prediction of completion model

Demographic Indicators Influencing Learning Activities in MOOCs: Learning Analytics of FutureLearn Courses

Big data and analytics for educational information systems, despite having gained researchers’ attention, are still in their infancy and will take years to mature. Massive open online courses (MOOCs), which record learner-computer interactions, bring unprecedented opportunities to analyse learner activities at a very fine granularity, using very large datasets. To date, studies have focused mainly on dropout and completion rates. This study explores learning activities in MOOCs against their demographic indicators. In particular, pre-course survey data and online learner interaction data collected from two MOOCs, delivered by the University of Warwick, in 2015, 2016, and 2017, are used, to explore how learnerdemographic indicatorsmay influence learner activities. Recommendations for educational information system development and instructional design, especially when a course attracts a diverse group of learners, are provided

Opportunities and challenges in personalized MOOC experience

To provide MOOC participants with efficient learning resources and feedback according to the unique needs of each learner is obvious a greater challenge. In this paper, we describe the top five challenges that have the power to hinder the overall personalize MOOC experience. In addition to that, we suggest new opportunities considering individual differences in order to support personalized MOOC experienc

Next generation pedagogy: IDEAS for online and blended higher education. Final report of the FUTURA (Future of university teaching: update and a roadmap for advancement) project

Next generation pedagogy: IDEAS for online and blended higher education. Final report of the FUTURA (Future of university teaching: update and a roadmap for advancement) projec