Archive for category Papers
‘Developing a strategic approach to MOOCs’ uses the work carried out at these universities to identify nine priority areas for MOOC research and how these can be developed in the future:
I was invited to write a paper for Distance Education in China, a journal which reaches out to Western academics and is willing to take on the task of translating papers from English. My paper was based on work published in Augmented Education, written by me, Kieron Sheehy and Gill Clough, which was published by Palgrave in 2014.
Digital technologies are becoming cheaper, more powerful and more widely used in daily life. At the same time, opportunities are increasing for making use of them to augment learning by extending learners’ interactions with and perceptions of their environment. Augmented learning can make use of augmented reality and virtual reality, as well as a range of technologies that extend human awareness. This paper introduces some of the possibilities opened up by augmented learning and examines one area in which they are currently being employed: the use of virtual realities and tools to augment formal learning. It considers the elements of social presence that are employed when augmenting learning in this way, and discusses different approaches to augmentation.
数字化技术的价格越来越便宜,功能越来越强大,在日常生活中用途越来越广泛。与此同时,利用数字化技术进一步促进学习者与他们所处环境的互动以及对环境的 感知以增强学习的机会也越来越多。增强学习可以利用增强现实和虚拟现实以及许多能提高人类意识的技术。本文介绍增强学习的一些可能性并讨论目前正在应用增 强学习的一个领域:运用虚拟现实和工具增强正式学习。文章分析了基于虚拟现实和工具的增强学习所需的社交临场成分,并讨论不同的增强方法。
Ferguson, Rebecca (2016). 增强学习的可能性与挑战 [Possibilities and challenges of augmented learning]. Distance Education in China, 6 pp. 5–13.
This paper explores the potential of analytics for improving accessibility of e-learning and supporting disabled learners in their studies. A comparative analysis of completion rates of disabled and non-disabled students in a large five-year dataset is presented and a wide variation in comparative retention rates is characterized. Learning analytics enable us to identify and understand such discrepancies and, in future, could be used to focus interventions to improve retention of disabled students. An agenda for onward research, focused on Critical Learning Paths, is outlined. This paper is intended to stimulate a wider interest in the potential benefits of learning analytics for institutions as they try to assure the accessibility of their e-learning and provision of support for disabled students.
Cooper, Martyn; Ferguson, Rebecca and Wolff, Annika (2016). What Can Analytics Contribute to Accessibility in e-Learning Systems and to Disabled Students’ Learning? In: 6th International Learning Analytics and Knowledge (LAK) Conference, 25-29 April 2016, Edinburgh, Scotland.
New paper out in the Journal of Learning Analytics Research, building on our previous papers dealing with how learners engage with MOOCs.
Massive open online courses (MOOCs) are being used across the world to provide millions of learners with access to education. Many who begin these courses complete them successfully, or to their own satisfaction, but the high numbers who do not finish remain a subject of concern. In 2013, a team from Stanford University analysed engagement patterns on three MOOCs run on the Coursera platform. They found four distinct patterns of engagement that emerged from MOOCs based on videos and assessments. Subsequent studies on the FutureLearn platform, which is underpinned by social-constructivist pedagogy, indicate that patterns of engagement in these massive learning environments are influenced by decisions about pedagogy and learning design. This paper reports on two of these studies of learner engagement with FutureLearn courses. Study One first tries, not wholly successfully, to replicate the findings of the Coursera study in a new context. It then uses the same methodological approach to identify patterns of learner engagement on the FutureLearn platform, and indicates how these patterns are influenced by pedagogy and elements of learning design. Study Two investigates whether these patterns of engagement are stable on subsequent presentations of the same courses. Two patterns are found consistently in this and other work: samplers who visit briefly, and completers who fully engage with the course. The paper concludes by exploring the implications for both research and practice.
Ferguson, Rebecca, & Clow, Doug. (2016). Consistent commitment: patterns of engagement across time in massive open online courses (MOOCs). Journal of Learning Analytics, 2(3), 63-88.
Doug Clow and I took a new approach to presenting at ECTEL 2015. Our paper Moving through MOOCS: pedagogy, learning design and patterns of engagement was jointly authored with researchers from Edinburgh, Leeds and Birmingham. It combined a number of studies, involving cluster analysis of different MOOCs. An enormous amount of information to cram into a 20-minute talk.
So we produced two sets of slides. The first, available on my Slideshare account, takes viewers through the paper in detail. The MOOCs, the methods, the clusters. The second, available on Doug’s account, focuses on a simpler message – that massive open online courses vary enormously in pedagogy and in learning design. Before making grandiose claims for generalisability, we need to check whether our findings really apply widely – or if they actually only apply to MOOCs on our platform or in our subject area, or within our university. While almost all the people in our audience had visited at least one MOOC, the majority had not visited more than one MOOC platform.
You can investigate our research further, taking the detailed route via one presentation, or the route with a simpler message and better pictures via the other, or the complex but clearly mapped route by reading the paper. Or, if you have the energy, you can explore a combination of routes and find out which works best for you.
Of course, this isn’t a fair test. The presentations aren’t offered in the same way and in the same place. Nevertheless, Doug and I will be looking at the stats for each of them, and making anecdotal use of those figures for some time – so choose your route wisely.
As I type, one of the Slideshares has 636 views, 5 likes, 5 downloads, 5 LinkedIn shares, 1 Facebook share and 24 Tweets.
The other has 571 views, 3 likes, 0 downloads, 0 shares on LinkedIn or Facebook and 25 Tweets.
The paper, following the link above, has 99 downloads and 2 Tweets
This special issue, edited by Yishay Mor, Barbara Wasson and myself, developed from an Alpine Rendezvous workshop we ran in 2013 that dealt with the connections between learning design, learning analytics and teacher inquiry.
This special issue deals with three areas. Learning design is the practice of devising effective learning experiences aimed at achieving defined educational objectives in a given context. Teacher inquiry is an approach to professional development and capacity building in education in which teachers study their own and their peers’ practice. Learning analytics use data about learners and their contexts to understand and optimise learning and the environments in which it takes place. Typically, these three—design, inquiry and analytics—are seen as separate areas of practice and research. In this issue, we show that the three can work together to form a virtuous circle. Within this circle, learning analytics offers a powerful set of tools for teacher inquiry, feeding back into improved learning design. Learning design provides a semantic structure for analytics, whereas teacher inquiry defines meaningful questions to analyse.
BRITISH JOURNAL OF EDUCATIONAL TECHNOLOGY
VOL 46; NUMB 2 (2015)
Editorial: Learning design, teacher inquiry into student learning and learning analytics: A call for action
Mor, Y.; Ferguson, R.; Wasson, B.
Informing learning design with learning analytics to improve teacher inquiry
Persico, D.; Pozzi, F.
A method for teacher inquiry in cross-curricular projects: Lessons from a case study
Avramides, K.; Hunter, J.; Oliver, M.; Luckin, R.
Supporting teachers in data-informed educational design
McKenney, S.; Mor, Y.
Forward-oriented designing for learning as a means to achieve educational quality
Ghislandi, P. M.; Raffaghelli, J. E.
Analysing content and patterns of interaction for improving the learning design of networked learning environments
Haya, P. A.; Daems, O.; Malzahn, N.; Castellanos, J.; Hoppe, H. U.
How was the activity? A visualization support for a case of location-based learning design
Melero, J.; Hernndez-Leo, D.; Sun, J.; Santos, P.; Blat, J.
Scripting and monitoring meet each other: Aligning learning analytics and learning design to support teachers in orchestrating CSCL situations
Rodrguez-Triana, M. J.; Martnez-Mons, A.; Asensio-Prez, J. I.; Dimitriadis, Y.
Mor, Yishay, Ferguson, Rebecca, & Wasson, Barbara. (2015). Editorial: learning design, teacher inquiry into student learning and learning analytics: a call for action. British Journal of Educational Technology, 46(2), 221-229.
My main paper at LAK15 analysed engagement patterns in FutureLearn MOOCs. In it, Doug Clow and I began by carrying out a replication study, building on an earlier study of Coursera MOOCs by Kizilcec and his colleagues. Although our cluster analysis found two clusters that were very similar to those found in the earlier study, our other clusters did not match theirs. The different clusters of learners on the two platforms appeared to relate to the pedagogy (approach to learning and teaching) underlying the courses.
Ferguson, Rebecca, & Clow, Doug. (2015). Examining engagement: analysing learner subpopulations in massive open online courses (MOOCs). Paper presented at LAK 15 (March 16-20), Poughkeepsie, USA.
Massive open online courses (MOOCs) are now being used across the world to provide millions of learners with access to education. Many learners complete these courses successfully, or to their own satisfaction, but the high numbers who do not finish remain a subject of concern for platform providers and educators. In 2013, a team from Stanford University analysed engagement patterns on three MOOCs run on the Coursera platform. They found four distinct patterns of engagement that emerged from MOOCs based on videos and assessments. However, not all platforms take this approach to learning design. Courses on the FutureLearn platform are underpinned by a social-constructivist pedagogy, which includes discussion as an important element. In this paper, we analyse engagement patterns on four FutureLearn MOOCs and find that only two clusters identified previously apply in this case. Instead, we see seven distinct patterns of engagement: Samplers, Strong Starters, Returners, Mid-way Dropouts, Nearly There, Late Completers and Keen Completers. This suggests that patterns of engagement in these massive learning environments are influenced by decisions about pedagogy. We also make some observations about approaches to clustering in this context.