“CHAPTER 18 2011 Personal Learning Environments” in “25 Years of Ed Tech”
CHAPTER 18
2011
Personal Learning Environments
Personal Learning Environments (PLE) were an outcome of the proliferation of services that suddenly became available following the Web 2.0 boom, combined with the thinking around distributed learning that we looked at in the previous chapter. Learners and educators began to gather a set of tools to realize a number of functions. The collection of these learning-support tools, both formally and informally, began to be referred to as a Personal Learning Environments or PLE. Educause (2009) defined them as “tools, communities, and services that constitute the individual educational platforms that learners use to direct their own learning and pursue educational goals” (p.1). They could be viewed as a useful term for what people were doing with the tools, a framework for educators in how to approach social media in education, or a technical solution that sought to integrate tools. They can also be viewed as a reaction against Learning Management Systems (LMS), arising from some of the dissatisfaction with those tools we saw in chapter 9. Dabbagh and Kitsantas (2012) claimed that
LMS have always been under the control of the institution, its faculty and administrators, leaving little room for learners to manage and maintain a learning space that facilitates their own learning activities as well as connections to peers and social networks across time and place. (p. 4)
PLE were seen as a means of allowing greater learner control and personalization, in keeping with the learner-centred approaches to education. Van Harmelan (2006) identified four motivations for their adoption:
Life-long learning — Allows users to have a system that persists beyond formal education and that also interfaces to institutional e-learning systems.
Beyond the LMS — A reaction to the perception that LMS do not offer the required flexibility or usability of many of the tools that constitute a PLE.
Pedagogy related — According to many of the pedagogic approaches being adopted, there was a strong emphasis on the learner’s control of their environment.
Offline learning — Some learners needed to perform learning activities offline, without connectivity to a server, and a range of tools in a PLE could facilitate this.
Similarly, Attwell (2007) saw PLE as a response to changes in the nature of education, including an increased emphasis on lifelong learning, increased possibilities for informal learning, the development of new approaches to assessment and the recognition of learning such as e-portfolios, and the changing technological landscape.
PLEs were often visualized in terms of a spoke diagram (Leslie, 2012), showing the range of tools the individual used in an everyday learning context. In ed tech circles, the conversation turned to whether these tools could be somehow “glued” together in terms of data. Norman (2008) stated the central challenge as a question:
How can software provide what appears to be a centralized service, based on the decentralized and distributed publishings [sic] of the members of a group or community, and honour the flexible and dynamic nature of the various groups and communities to which a person belongs? (para. 1)
Instead of talking about one LMS provided to all students, the vision was how each learner could create their own particular blend of tools.
Wilson et al. (2007) set out a model for how this might be realized through an open application programming interface (API) and through standards such as Atom, FOAF (Friend-of-a-Friend), and RSS (Rich Site Summary, or Really Simple Syndication) for feeds. They contrast this type of learning environment with the conventional LMS on a number of dimensions, emphasizing that “the system should focus instead on coordinating connections between the user and a wide range of services offered by organizations and other individuals” (p. 31). This approach would go on to form the basis of the PLEX (Personal Learning Environment X) project (http://www.reload.ac.uk/plex), a prototype tool from the University of Bolton that allowed users to glue together different elements. The social network system Elgg also met many of the PLE requirements, providing users with tools such as blogging, podcast support, user profiles, content aggregation, community building tools, tagging, and so on. Sharma (2008) stated that “Elgg can also be set up to integrate with other popular web-based tools like blogs and wikis. It can also be expanded with plug-ins to provide a calendar, a wiki, or advertisement” (p. 13).
By 2014, the PLE had largely faded from conversation. As with other ed tech innovations that have a solid theoretical basis but fail to realize their potential, it is worth exploring the reasons for this. Here are some possible reasons why the PLE didn’t gain mainstream adoption:
The concept became absorbed, so it was seen as an extension of the LMS, or rather the LMS was just one other part of it. People don’t differentiate between tools for different settings because the boundaries between personal and professional have been blurred.
There was a consolidation in the market after the Web 2.0 bust, so most people settled on the same few tools: Twitter, YouTube, WordPress, Wikipedia, plus some other specific ones. One PLE began to look similar to any other PLE, which meant it was no longer personal. Just as with the early days of search engines, we no longer talk about whether you prefer Lycos or WebCrawler now, we just Google it.
It wasn’t a useful term or approach. Some projects attempted to get data passed between LMS and PLE tools, or to set these up for people and, in the end, people just opted for tools they found useful and didn’t feel the need to go further.
The overhead for learners was too high. For learners engaged in formal education, coping with the conceptual challenges of their particular field of study is difficult enough without requiring them to construct their own learning environment.
It was too complex. The appeal of an LMS is that it easily meets a demand and is geared towards the type of procurement process in place at most institutions. Implementing an enterprise version of a PLE that would not only integrate all of the third-party tools but link effectively with university registration, timetabling, and accreditation systems was too complex for too little gain.
It was likely a combination of all of these factors. Combined with this was increasing wariness about applications that shared data. Providing a uniform offering and technical support for learners was difficult when they were all using different tools. Ultimately, as with other developments we have seen, the return on investment from an individual or an institution was not significant enough, the benefits too abstract, and the immediate difficulties too obstructive. Looking at the motivations for the PLE interest, though, it marks a high point of educational technologists reflecting on the environment that technology creates and its implications for learning.
The use of the term PLE may have faded, but it has been replaced by a more people-focused version, with the term PLN (Personal Learning Network). As social media became ubiquitous, so the ability to develop a network of people that could enhance learning became a common practice. These needn’t be people the individual interacts with; they can be those they follow on social media, read blogs by, listen to podcasts by, and so on, who aid learning. This really is personal, as it will often include people the individual knows locally, professionally, as well as those they encounter online. Although a PLN can include resources, it is a much more social, human-focused interpretation.
Further to the PLE and the PLN, personalized learning remains one of the dreams of ed tech, with learners enjoying a personalized curriculum, based on analytics. Indeed, personalization is often presented as an obvious, and unquestionable improvement, with Facebook founder Mark Zuckerberg, for example, announcing it as one of his key areas of philanthropy (Zuckerberg, 2017). While flexibility in a system and modification to meet the needs of different learners is undoubtedly desirable, complete personalization may not be as beneficial as is often believed. For example, Pane et al. (2017) report that students in personalized schools felt less positive about their school experience than those in traditional schools. Perhaps personalization erodes the sense of a cohort and shared experience with others, which is a significant part of the educational process. It may also place stress on students to feel like they need to direct their own learning as well as undertake it, when doing just one of those might be enough. Similarly, at the Open University of the Netherlands, Schlusmans, van den Munckhof, and Nielissen (2017) reported that their previously highly personal, flexible model, which involved a “start any time, take an exam any time” approach, was in fact, too flexible. It worked for highly independent learners, but since switching to a more structured approach there has been an improvement in retention, and this more tightly controlled model has allowed for more interactive pedagogy.
Personalization is a challenge for higher education, which the advent of networked technologies has brought to the fore. When students are accustomed to personalization in all aspects of their lives, from their Starbucks order to their music playlists in Spotify, then they may well expect the same in higher education. One of the technologies this book has not covered is the student portal, which can be seen as an attempt to provide this at a convenient, if superficial, level by allowing students to personalize what news and feeds they receive. Personalizing learning is more complex, however. It might be desirable to have a system that can automatically suggest OER to students if they are struggling, based on their preferences so far, but even in this case there is an argument for developing the skills to find OER by developing learning to learn skills. An automated system would remove this process. As the findings above suggest, fully personalized learning may not be as desirable as is often implied, because learning is often a social process and individualization can remove the opportunities for this.
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