As part of my applied linguistics learning, a context which I very recently experienced and observed, in which I think ethnography might be appropriate is medical treatment during COVID. Within that context, I would be interested in focusing on intercultural communication / intracultural diversity in healthcare. Ethnography would be appropriate in the context chosen because of the clear differences in clinical outcomes for particular ethnic groups in the NHS - ethnography as a social science. I will not go into the hundreds of studies on this. I will focus on COVID:
'...the failure to record the race and ethnicity of Covid-19 deaths, and the disproportionate mortality impact...on Black Asian and Minority Ethnic (BAME) communities, speaks to a systemic failure to account for the ...the social construction of race, the lived experience of racism, and its biological presentation as 'poor health' amongst the discriminated-against.'
(Fofana, 2020, p.1)
The care I received was better than good, I’d say excellent. I’d gone into the hospital partly as a precaution against COVID. I was given a test as a precaution. My test was negative (btw). I went home stable and very thankful to the doctors, nurses, paramedics who showed such sensitive and devoted care. But from the beginning, I felt that need to keep throwing out signals to them that I thought would creae a kind of 'one of us' effect and lessen the effect of society's blind spot in its care of BAME (hate that term) - especially African-Caribbean.
Green and Bloome’s categories (cited in Street, 2010 p.204), an ethnographic perspective would be most relevant - there has already been a lot proven and written on disparities in social services provision along race and ethnic lines. This would focus on staff-staff and staff-patient interactions that impact one control and one study group of patients - an ethnographic account, using theories, practices and ethnographic tools derived from anthropology and sociology (Green and Bloome, 2004). My paradigmatic perspective would be critical and should have a commitment to action and reform as it addressed long entrenched issues, that could end up providing a telling case study. The shortfall in care for BAME I believe is real, bourne out by consistent observations, no matter how heroic our NHS staff is in general, a problem exists. Green and Bloome provide some ethnographic questions (2004, p.2), they say as a way of ‘making visible what those who engage in ethnography mean by this term’ (2004, p.3) and I think these also provide a basis for criticality and reflection on the situatedness of ethnology when looking into the generalizability of the research ‘findings’.
I think that both black and white participant-observers who are sociolinguists would be great assets in this type of research – they can see first-hand how verbal communication is dealt with in interactions with someone of their ‘demographic’. The importance of NVB is crucial here too.
Did my ethnicity become an unwelcome part of my encounter and a possible sign of the above-mentioned cracks in society?
It did, but perhaps not from a negative care perspective. Race was brought up in a context that only presented a danger of misinterpretation in itself but seemed to point to issues below the surface. It was, once again, about how black men are seen as threatening or frightening and our 'physicality' often comes up. It's astonishing how frequently, once people relax with you it comes up. It's a linguistic ritual that accounts for people's knowledge of how BAME people are presented by society. In this case, it seemed to be a deliberate counter to stereotypes I think the staff member may have encountered herself at work. A lot of questions were left unanswered as I was not conducting research at the time.
'cultural differences may also contribute to stereotyping behaviour and biased or prejudicial attitudes toward patients and healthcare providers. At the same time, cultural beliefs and approaches to healthcare are deeply ingrained and most often not overtly communicated'. (Kirschbaum, 2017 p.1 ):
References
Fofana, M.O., 2020. Decolonising global health in the time of COVID-19. Global public health, pp.1-12.
Green, J. and Bloome, D. (2004) ‘Ethnography and ethnographers of and in education: A situated perspective’ Handbook of research on teaching literacy through the communicative and visual arts, pp.181-202.
Kirschbaum, K.A., 2017. Intercultural communication in healthcare. The International Encyclopedia of Intercultural Communication, pp.1-13.
Street, B. (2010) ‘Adopting an ethnographic perspective in research and pedagogy’ in Coffin, C., Lillis, T. and O’Halloran, K. (eds) Applied Linguistic Methods: A reader, Abingdon, Routledge, pp. 201–15.
I haven't posted in some time as I changed jobs, re-located internationally and started my third and final module of my 'MA in Online Education', so exciting times, considering we are still at the height of the pandemic; we seem to have found some real sound vaccine candidates and Trump has been voted out of office. But I think the obsessing over whether Americans truly want to go back to slavery and or segregation days is not going away because they voted for him again. Over 40% of US voters chose Nazism in 2020. As I am a person of colour, the fact he once again won white male and female Americans does not seem to me like racism is a thing of the past when so many people vote for someone who openly advocates it. The UK has parallels.
Which brings me to the topic of my post, which is sociolinguistics. This final module of my studies is about choosing a content area to match with the tech skills and online teaching concepts and principles I've been learning. I chose applied linguistics as my content area. This week was sociolinguistics - how more influential social context is than any other influence on language. In fact, language is a product of social interaction, forming everything we communicate using language tools. I can also apply what I learned to life and the language legacy I leave and am a product of.
Of course, one of the best known sociolinguists was Dell Hymes (1972), who made the point that most linguists are much less concerned with an ideal ‘linguistic competence’ than with ‘communicative performance’ - real world applications of language. Hymes’ ideas for communicative language teaching were part of an enrichment of approaches in education of the time, beginning in the 70s and 80s. Though his ideas ‘quickly became distorted and misinterpreted’ (Cook, 2003 p.46), they helped create the impetus towards sociolinguistics. There were some excellent examples from students on my course on the topic of code-switching for students of English applying Hymes’ proposed four types of knowledge (Cook, 2003 p. 42) to different life and work experiences. During exchanges with curse members Bolton (2020), our definition of code-switching was clarified, the relative benefits of accommodative speech strategies were debated.
It was good to receive a link from Fallows (2020 ) to a podcast (BBC, 2020) about code-switching among African-Caribbean people - a very common feature among my community in the UK. On the train yesterday, from Leicester to Nottingham, code-switching from standard English to an Anglo-Jamaican style rhythm and intonation was noticeable. The question of why many Black people feel uncomfortable speaking Creole or in Creole style is central in the podcast discussion and is related to the concept of agency, empowerment and identity that has come into applied linguistics research (see Carter and Sealy, 2007 below). As Carter and Sealy put it:
“people exercise (ing) agency with regard to … which language variety to use… are often interpreted as demonstrating national, ethnic or cultural affiliation”
Back to Trump, in America people speaking their mother tongue or a second language - not English - were routinely vilified for (in the mind of their abusers) 'showing affiliation to another culture, country or people'. When all they are doing is exactly that, which speaks to the racist aspect of it. Most Americans have a duel identity because most Americans are children of immigrants in a land built on genocide and slavery. YouTube videos do not appear of white people being attacked for speaking a foreign language.
Carter and Sealy lay out much of the new field of study of applied linguistics based and what is meant by social context:
“questions of linguistic identity, of linguistic exclusion or inclusion, of languages in contact, of languages in conflict, of language purity, of language conservation, of language prestige” (Wright, cited in Carter and Sealy, 2007 p. 24).
Prior to Covid-19, there had been an increase in migration brought about by, among other things, economic forces and conflict. It has added to the effects of globalisation, bringing diverse groups together and thus, language awareness is as crucial, as it has always been because is so closely tied to sensibilities of identity, culture, belief. Therefore, assumptions “about collectivities and about social agency” should be closely studied and challenged."
Growing awareness of this has opened up and inspired new and significant fields of study of language. Now, with developments in corpus linguistics, it is also possible to study in more depth how features of a language variety can vary to a greater or lesser extent than others in forming judgments about social significance; corpus linguistics also adds to greater attestedness in linguistics research in a way that will improve research in the future.
Bolton, N. (2020) ‘Accommodative speech for language learners Task 1’ in EE817 Tutor Group Forum [Online] Available at https://learn2.open.ac.uk/mod/forumng/discuss.php?d=3360704 Accessed 12 November 2020.
Carter, R. and Sealey, A. (2007) 'Languages, nations and identities', Methodological Innovations vol. 2, no. 2. [Online] Available at http://www.methodologicalinnovations.org.uk/wp-content/uploads/2013/11/3.-Cartersealey-formatted-20-31.pdf Accessed 05 November 2020.
Cook, G. (2003) Applied Linguistics, Oxford, Oxford University.
Hymes, D. (1972) On communicative competence. sociolinguistics, 269293, pp.269-293.
Robinson, H. (2020) ‘Code-switching Task 1’ in EE817 Tutor Group Forum [Online] Available at https://learn2.open.ac.uk/mod/forumng/discuss.php?d=3360704 accessed 12 November 2020.
image source: Jisc Learning analytics going live
We were asked to review this article in order to expand our understanding of social learning analytics. Rather than examining interactions by students in an online learning environment such as an institutional LMS, however, or another trail of start-up, demographic, disciplinary, course, log in, data, commonly analyzed, we focussed on research network analytics of some of the leaders in the field. A very different subject to what we had been looking at previously. Another usual thing was the way we approached the reading. We begin by looking at the abstract of this paper: Dawson et al. (2014), 'Current state and future trends: a citation network analysis of the learning analytics field' and noted the aims of the paper. That was the end of the conventional approach to reading, as we then were asked to skip to the fourth section of the paper that listed its practical implications (Section 4.3). These were that the analysis ...
provides an understanding of how key papers, thematics, and authors influencing a field emerge
raises awareness about the structure and attributes of knowledge in a discipline and the development of curriculum in the growing number of academic programs that include learning analytics as a topic
promotes under-represented groups and research methods to the learning analytics community
fosters the development of empirical work and decreased reliance on founding, overview and conceptual papers
improves connections to sister organizations such as the International Educational Data Mining Society
(Dawson et al 2014, 238)
The interesting thing about the paper was its crossover between an example of learning analytics and a paper about learning analytics.
Some of its figures and tables thankfully were understandable even for a non-expert. Table 1 identifies the ten most-cited papers in the field. Interestingly, the numbers of citations in the learning analytics literature ranged between 10 and 16, whilst the Google Scholar citation counts vastly differed. This can be attributed to the equal currency placed on both old and new publications among specialist members of the field compared with researchers from a much wider range of fields and interests among the Google scholar audience.
In sum, the article is a reminder of how much more complex the learning analytics landscape is than a means to improve teaching and learning. In this case, it was used to aid in a complex understanding of how research gains prominence. A systemic and integrated response is required for the approach to do justice to its subject. As the authors note: 'while it is helpful to note that (more active) students...perform better than their less active peers, this information is not suitable for developing a focused response to poor-performing students. (p. 231)'
A more in-depth reading of the article would certainly have made the basis of that point much clearer to the reader. However, what I did gain from reading a paper in this way was an impression I could take with me to other readings and to my general knowledge of the breadth of the learning analytics field.
Dawson, S., Gašević, D., Siemens, G. and Joksimovic, S. (2014) Current state and future trends: A citation network analysis of the learning analytics field. In Proceedings of the fourth international conference on learning analytics and knowledge (pp. 231-240) [Online]. Available at: file:///C:/Users/robin/Desktop/Current%20State%20and%20Future%20Trends%20A%20Citation%20Network%20Analysis%20of%20the%20Learning%20Analytics%20Field.pdf (Accessed July 20 2020).image source: jisc.ac.uk
My last two blogs try to summarise my views and knowledge of ways Big data are used in learning and teaching (where it can be referred to as educational learning analytics) and ethical practices related to it.
The following tries to highlights the relatedness but also the differences between learning analytics (LA) that is learner/teacher focussed and when it is more informs the wider body of educators such as managers, administrators, the institution, government, other funding bodies. Also, the reasons why LA emerged in the 2000s.
Reasons for the emergence
The US has also seen a sharp improvement in school results over the same period and it could in part be put down to the increase and improvement in learning analytics initiatives and theory.
Used to benefit educators
Institutions are of course very interested in student performance because it reflects on the institution and its popularity and on their funding and staff jobs. They are trying to reach certain external and internal key indicators. For those reasons, they are also interested in things that are not about the individual, rather, they are interested in increasing student numbers, administrative, and academic productivity and cost-cutting for profitability and data related to this, a focus is known as academic analytics. They are interested in general account analytics, which allows them to see what students, teachers are doing within the account. Activity by date allows the admin to view student participation in Assignments, Modules, Discussions, and teachers' completion of Grades, Files, Collaborations, Announcements, Groups, Conferences, etc In general one can view how the users are interacting with the courses in the term. This means the content can be adapted to improve efficiency, productivity, and adherence to policy and practice based on deductions and predictions made from the use of content.
Used to benefit students
I categorize all the above (under benefitting the educator) as also benefitting the learner. The above would reach the learner via tutorials the teacher has with them and reports if any. However, the analytics that the student is likely to actually access mainly include only their grades and records of their assignments. Students can use these to track and assess their progress, this way they can see where they need to improve as they go along. Teachers should use educational data mining (EDM) - 'analysis of logs of student-computer interaction' (Ferguson, 2012) to improve learning and teaching. Romero and Ventura (2007 cited in Ferguson, 2012), identified the goal of EDM as ‘turning learners into effective better learners’ by evaluating the learning process, preferably alongside and in collaboration with learners. These data are often only available if the teacher makes them viewable.
In my situation, the LMS used is compatible with various apps such as Turnitin (a plagiarism checker), students also have access to its analytics, used at the drafting phase of the writing course, and at the end of the course only if students query their report writing score and plagiarism has some relevance.
Challenges
Some of the educational challenges in the environment that I work in include adapting to online as opposed to f2f teaching. A way to sum up the challenge is it is completely different because the contact and communication have technology running through it. One of the challenges involved in implementing learning analytics is mistrust of how data will be used. Students I work with sometimes avoid leaving digital traces for fear of it ending up being a means of covertly 'assessing' them. This is why their focus is on final tests, where they are fully aware of what performance data will be collected and how it will be used. 'Therefore, it is necessary to make the goals of the LA initiative transparent, clarifying exactly what is going to happen with the information and explicitly' (Leitner et al. 2019, p.5). Researchers also point to privacy and ethical issues.
Recommendations
1. Teachers should get training in the use of data analytics for use in the classroom
2. There should be an open dialogue about what learners' rights to their own learning analytics should be; what learning analytics should be available to them; how to give them access (including training in accessing their own data)
3. Analytics is too much management centred - data-mining and academic analytics and its often not shared with teachers. Learning analytics need to be much more classroom and teacher/student relationship centred.
I think the adoption of these recommendations could improve engagement, ownership, motivation to learn better, and also improve learning directly.
Cameron, K. and Smart, J., (1998) Maintaining effectiveness amid downsizing and decline in institutions of higher education. Research in Higher Education, 39(1), pp.65-86.Cameron, K. and Smart, J., 1998. Maintaining effectiveness amid downsizing and decline in institutions of higher education. Research in Higher Education, 39(1), pp.65-86.
image source: pngkey
LinkedIn's use of data analytics
Generally, I'm quite turned off by the fact that apps and sites can access Big Data and use it in ways I'd probably disagree with. Ironically, I never take the time to look at the policy and learn about what kind of data different sites take or why. When it comes to the superhighway robbery we see every day, I wish governments would simply say no to big companies (once again) unfairly accumulating Big Data for their commercial interests, making a huge profit out of data theft.
One 'exception' to my disapproval of Big Data might be Linkedin. Here's an example of a more or less symbiotic relationship between an ostensibly free provider and its clients. And here is a brief explanation of where and how LinkedIn uses Big Data to achieve its impressive results without necessarily ripping people off.
On the one hand, LinkedIn uses Big Data to very closely analyze what its members do when they are accessing its site so that it is able to provide the identity, learning, and networking services that comprise Linkedin's unique brand and drives its popularity. The features Linkedin offers would not be possible without the data its users provide. Of course, the huge amount of data also guides its future business decision-making.
As mentioned above, there are three wings of the Linkedin service. On the networking side, its algorithms prime the searches through comparatively small items of data to identify “people you may know” and to make suggestions for users to add to their personal networks. Machine-learning techniques enable LinkedIn to refine its algorithms based on user feedback (e.g. user uptake of suggestions) and this in turn is enabling better suggestions to be made. Customers benefit from this data usage by being able to build better and better personal networks that benefit them, socially, professionally, or educationally.
One of the ways Linkedin manages to keep re-designing itself, balancing its business and user interests is by its constant data collection and transformation of data into end-user displays. The data that keeps LinkedIn users engaged includes contacts' job, profile and connection updates. This drives the keeping up with the Jones impulse that drives users' need to further engage and connect. For this to work best, data needs to be live-streamed and analyzed simultaneously, using real-time stream-processing technology. The direct from source information LinkedIn is interested in includes items that are 'liked' shared, clicked, and contact who are messaged.
In short, the (open) secret of LinkedIn's success and the success of many other businesses using Big Data to drive success is its use of timely, on the fly, and personalized suggestions and recommendations.
Baumgartner, P. (2016) ‘Economic Aspects of OER’ [Online]. Available at:
https://slideplayer.com/slide/6599837/ (accessed 02 June 2020).
Image source: Dynomapper
The following is my reflection on my contribution to the writing/setting of the context behind a team assignment as part of my master's in online and distance learning. Our team's challenge (there are 7 teams) was to formulate an online response to the COVID-19 pandemic. We decided to focus on higher education institutions. In particular, to aid the ongoing widespread and partial transition to online teaching, and to support both educators and learners in this. For many who are unfamiliar with this mode of teaching /learning, the transition is a huge challenge, but solutions need to be found in order to secure their short term goals and long term survival.
Of course, the development of our website is a very long term thing and the preliminaries are still ongoing.
The site: Higher Education Open Education Resources, H817 COVID-19 RESPONSE TEAM
My contribution to the context
I think my contribution was substantial. I created the first draft of the aims, the context, the target audience. Basically, the idea was the following:
To help educators and learners the world over to respond to the COVID-19 epidemic by aiding the transition to online teaching by:
Creating an online repository for the sourcing of the open educational resources (OER) for independent learning of various subject areas.
In addition to teaching/learning materials in a range of subject areas, we will place materials that support knowledge and understanding of open educational practices (OEP), its technology, tools, and open pedagogy in all its forms.
Most challenging
The things I found most challenging were working to a deadline while working full time and applying for jobs. Also, I learned more than anything about working with people - you have to be diplomatic and things seldom get off to a rip-roaring start when you don't know each other. I learned how to set up a website, which was important for me. Most important, perhaps, what huge incentive teamwork creates. Is it the competitive instinct? Is it the urge to please and help each other as well as learn together? A bit of everything really.
I recall exploring the concept of ‘digital natives versus digital immigrants’ (Prensky 2001) in a previous iteration of my journey into open learning/teaching and education as a now quaint idea that digital technology belonged to the millennials who grew up as Web 2.0 was taking hold and those born to earlier generations were immigrants, needing to pass some kind of naturalisation procedure to gain residency or full digital-age citizenship. The ageism aspect of it tended to go over our heads, as we realised that digital citizenship was more a matter of exposure and interest than age. Bennett, Maton, and Kervin (2008) found as much difference in technological know-how between those born during the coming of the full-on digital age of the late 90s to early 21st century as between those born earlier. Take my students, born in conservative Central Asia. My impression is there is a technology gap between girls and boys and between my students and western students of UK, US and Australia, as my region, emerges from its post-soviet isolation – very rapidly I might add. Kazakhstan ranks highest in terms of internet access of all Central Asian countries, however, behind Russia and much of the world. Internet only appeared in 1994 in Kazakhstan, but it ranks 61st place out of 177 countries for broadband Internet speed.
The concept of ‘digital natives versus digital immigrants’ has since been modernised and now the terms ‘digital visitors’ and ‘digital residents’ (White and Le Cornu 2011) are in currency – those that only occasionally use a technology and who have not developed much expertise in its use and those who use a tech often and who developed some expertise in its use. White on his website, and in an accompanying video describes his approach to mapping an individual’s level of acculturalisation to a technology, including the use of his openly licenced software.
I decided to map my own level of engagement with different technologies using White and Le Cornu’s ‘Visitors and Residents’ concept (e.g. including my use of, VLEs, blogs, Facebook, Skype, etc.), cross-referenced with my adaptation of their personal/institutional axis (I break it into social, professional and educational) as well as the visitors/resident one. I used Miro, the online collaborative whiteboard platform to create my grid. Click on this link to see my visualisation:
Henry’s Visitors and Residents’ concept (public)
Henry’s Visitors and Residents’ concept (course members – editable)
If you can, feel free to adapt the model I created in any way you please and send me an image or link of your version of the model!
I found it a useful way to reflect on my current use and to consider other technologies I do not use, especially when comparing my grid with others’ on my course, whose were often very different, based on their jobs, experience etc.
References
Prensky, M. (2001) ‘Digital natives, digital immigrants part 1’, On the horizon, 9(5), 1–6.
White, D. and Le Cornu, A. (2011) ‘Visitors and residents: a new typology for online engagement’, First Monday, vol. 16, no. 9, 5 September 2011 [Online]. Available at http://firstmonday.org/ojs/index.php/fm/article/view/3171/3049 (Accessed 21 October 2019).
When we define open learning, it is not always effective to do so in terms of the principles that underlie open education – education for all, empowerment of the disenfranchised, addressing inequality and stimulating educational achievement for individual self-efficacy and self-development and economic development through education (i.e. a more able and employable workforce), especially among women, the disabled and discriminated-against minorities. Nor should we just define open education as being education that is free, globally accessible and fulfilling the 5Rs of (able to) Retain, Reuse, Revise, Remix and Redistribute. We should also define OER in terms of its resources and technologies – ‘the 4 Qs’ (Robinson 2020) Where can we create it? How can we create it? Where can we get it and How can we get it?
Today, I want to focus on these in terms of the technology. To quickly summarise some of these….
HTML allowed the enriching of any site with the capacity to link seamlessly content with other content, whilst remaining in simultaneous touch with the source. One of the main components of what we call ‘web 2.0’. HTML coul be especially useful in edu-blogs for sharing educational content.
Blogs and its community of ‘edubloggers’, attracted to this format as a way of bypassing formal, rigid and it could be argued, antiquated forms of publishing on a global level to establish an academic identity. Blogs became popular as an OER because of its similarity to print sources – through which most educational materials were shared.
Social networks enable users to share personal ideas, thoughts, news and information through virtual networks and communities through messaging. One of their features is combining of multimedia to distribute documents, videos, and photos via computer, tablet or smartphone using downloaded to your devices or via web-based software or web applications. Beyond blogs, social networking tools exist in many more formats.; for example, Slideshare and YouTube each represent a different visual format extension of educational print dominated sources such as Twitter or Scribd.
MOOCs and VLEs can act as explicitly open education sources because they act as virtual classrooms or academies, while all the others are often used for many different purposes – not just educational, like entertainment. They can combine with any of the above to enrich the educational or training learning environments they represent.
Image source: curiosmos
The
following is my discussion
of the relationship between technology and pedagogic theory and practice,
drawing on my own teaching/learning context and experience.
Some have come to see the relationship between technology and pedagogic theory as a chicken versus egg paradox. Personally, I don’t see it. For me, the only issue is what to teach and the method - the pedagogy, which ideally can be aided by technology. The only non-disposable aspect of teaching is what we know to be the traditional methods - word of mouth, physical instruction some guidance and facilitation and signing, which can all be aided by the printed word - the most basic technology, which is nevertheless close to 2000 years old.
As Weller suggests (2011), and I agree, the chicken and egg conundrum exists only in our minds and it can arise from our being too techno-centric. On the other hand, technology and pedagogy drive each other and can be equally dominant in turn or co-constructive of each other. In other words, just like the University of Queensland and NÉEL Institute quantum physicists who concluded that the chicken and the egg can both come first, pedagogy and technology can also both come first. It’s just that, when it comes to choosing, it needs to be pedagogy every time. Drawing on my own context and experience, however, I must point out how an inexperienced or untrained teacher will use technology as a prop – this is where it becomes technological determinism. That has to be seen on a continuum, however. We might become a tech determinist to try out something, but an experienced practitioner will not continue to let tech guide his/her behaviour regardless. They will be able to weigh up properly its pedagogical benefits (or lack of).
I regard pedagogy as more significant than technology because for me it makes sense that effective learning is about adopting the right approach, notwithstanding of the tools you have at your disposal.
In terms of how technology and pedagogy influence each other, I am in complete agreement with our own course documentation (drafted by Weller) ‘Technology opens up new possibilities and is used in ways that its designers never intended, which in turn drives theoretic development which feeds back into technology development, and so on.’ (The Open University 2020) and of course this is in line with Weller’s (2011) belief in Chapter 1 of The Digital Scholar: ‘In this book it is the complex co-construction of technology and associated practice that is intended, with an iterative dialogue between the technology and the practices that it can be used for’
I think I am guilty every day of giving technology more weight than pedagogy because there is a temptation to use technology because its there, because its fashionable and because I think it engages learners ((in the short term and often superficially) and makes me look digitally literate, which is sometimes equated with competence. When I reflect on the lesson though, I am usually willing to replace technology with traditional or non-traditional approaches that do not reply on technology, because my aim is effective learning and task fulfillment.
References
Weller, M. (2011) The Digital Scholar: How Technology is Transforming Academic Practice [Online], London, Bloomsbury Academic. Available at https://www.bloomsburycollections.com/ book/ the-digital-scholar-how-technology-is-transforming-scholarly-practice/ (Accessed 21 October 2019).
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I do look for opportunities, however, to create and manage courses at least partly based on connectivist principles. And right now, when ALL teaching is online because of COVID-19, is an ideal opportunity to be more experimental. The current educational climate may be a great time to explore the rhizomatic learning (Cormier 2008) strand of connectivist thinking. Here, the focus is even more on the process more than the product, when compared with connectivism, to the extent that learners are seen as the curriculum - they decide the learning goals and the journey to those goals is a large part of what is studied. describing rhizomatic learning, Cormier (2008) writes:
'A rhizomatic plant has no centre and no defined boundary; rather, it is made up of a number of semi-independent nodes, each of which is capable of growing and spreading on its own, bounded only by the limits of its habitat' (Cormier, 2008).
References
Reference
DeRosa R. (2016) ‘My open textbook: pedagogy and practice’ [Online]. Available at: http://robinderosa.net/ uncategorized/ my-open-textbook-pedagogy-and-practice/ (Accessed 21 October 2019).
In defining 'personal learning network' or 'personal learning ecosystem' (similar to the concept of 'personal learning environment') I referred to several sources and my own experience as a teacher and researcher to arrive at my definition. But to do so more deliberately than perhaps I have done before, I reflected how far I have come since my years as a Ph.D. candidate when I was still an initiate in the world of online research and learning communities when understanding what the term really meant and entailed was much easier said than done. I wanted this new reflection to be partly based on my experience of learning on MOOCs, partly professional, (I am a teacher) partly more general (a source not referring to any specific community of practice or learning environment) and from the forum – learning from one of my colleagues on a course I am currently taking. I looked at her definition, that she had formulated after referring to Downes (2007) and I found it work for me. Downes is one of the pioneers of research on emerging technologies and learning innovation which have afforded learners access to educational literature and tasks at all times, which allow users to fit the course into their own pace, place and Personal Learning Environment (Attwell cited in Fournier et al. 2019). But I believe, the ability to go beyond shaping an artificial environment to one’s own construct is what brought the focus more networks because networks are what the learner became able to create and forge - ‘a place or community where people feel comfortable, trusted, and valued, as part of critical learning on an open network’ which became theoretical basis for connectivist-type MOOCs (cMOOCs) and what is now referred to as new learning ecosystems’ (Fournier et al. 2019) and which ‘are are more reliable producers of learning and knowledge’ (Downes 2007, p.1). As Arzu Ekoç (2020) points out, teachers nowadays ‘don’t want to be restricted to their isolated classrooms and schools’ (their Personal Learning Environments PLEs) but to extend it into a world where they have the greatest capacity to learn. Speaking more generally, Tour (2017, p.183) describes a PLN as ‘an informal group of likeminded people who share their knowledge and provide resources and advice to guide a learner in independent learning experiences in different digital spaces’ but notes how in most cases, participants in her research see PLNs as professional ventures.
With all this in mind, my own definition of a PLN is......
‘a personal-professional digital ecosystem best suited to the individuals’ socio-ethical approaches to learning and knowledge creation’.
My visualization of my own PLN is here (click)
References
Fournier, H., Molyneaux, H. and Kop, R., 2019, July. Human factors in new personal learning ecosystems: Challenges, ethical issues, and opportunities. In International Conference on Human-Computer Interaction (pp. 230-238). Springer, Cham.
Arzu Ekoç (2020) No teacher is an island: technology-assisted personal learning network (PLN) among English language teachers in Turkey, Interactive Learning Environments, DOI: 10.1080/10494820.2020.1712428
Ekaterina Tour (2017) Teachers’ self-initiated professional learning through Personal Learning Networks, Technology, Pedagogy and Education, 26:2, 179-192, DOI: 10.1080/1475939X.2016.1196236
Downes, S (2017) 'Learning networks in Practice' [Online] Available at: https://www.academia.edu/2869500/Learning_networks_in_practice
Even in the last five years, definitions of MOOCs (Massive Open Online Courses) have evolved. I say definitions because I think it is widely agreed that there are different types of MOOCs, serving different purposes for the users and for providers. Originally, since the early part of the 21st century (though some will argue that MOOCs existed before then), most observers could probably agree that a MOOC was a course provided through an online platform, using tools such as videos, and discussion forums, and with the emergence of web 2.0 apps, the ability to integrate with social networks. Some of the main characteristics of a MOOC were that they were often provided free, open to anyone and were offered by internationally known institutions or their faculty and did not offer a formal accreditation system.
cMOOCs (including task-based and networked-based)
Prior to 2015, we had seen the emergence of two major strands of MOOCs: cMOOCs and xMOOCs. The theoretical basis of cMOOCs was seen as “connectivism, openness, and participatory teaching” (Jacoby, cited in Veletsianos and Shepherdson 2016, p. 199- 200), emphasizing the active part learners play in knowledge creation, through their connections with other learners and their learning environment via networks facilitated by online technology. Canadian researchers George Siemens, Stephen Downes, and Dave Cormier based their MOOCs on the connectivist principles that everyone should determine their own learning goals, and structure and manage their own learning via personal learning networks. The learner is free throughout the whole learning process. These principles are still followed through in the task-based (Lane, 2012) MOOC, d106 facilitated by Jim Groom and Rhizomatic 15 by Dave Cormier, both supported by leading lights in connectivism theory. Cormier describes Rhizomatic as ‘a story for how we can think about learning and teaching’ where the learning community is the ‘curriculum’ or ‘challenge’. He asks participants to think of the learning environment as ‘’a research lab’, in which where participants are ‘researching along with me’. In terms of technology, the emphasis on social networking tools is clear when he talks about his communication with learners: ‘I’ll post it in the newsletter, I’ll tweet it … I’ll post it in the Facebook group and I’ll post it on the course blog.’ Similarly, d106 is described as 'Digital Storytelling’ where ‘you can join in whenever you like and leave whenever you need’ and describes how they ran a course ‘where… there was no teacher’. Communication is via a blog feed. Due to their open nature (where is no set ‘curriculum’, learners define ‘success’ and learning path, it is difficult to formally assess a learner’s progress and therefore to acquire monetary gain from these types of MOOC.
xMOOCs (including content-based)
In contrast to cMOOCS, xMOOCs follow a cognitivist-behaviourist approach (Hew & Cheung, cited in Veletsianos and Shepherdson 2016, p.199) resembling ‘traditional teacher-directed course[s]’ (Kennedy, cited in Veletsianos and Shepherdson 2016, p.200). The number of xMOOCs delivered has been growing rapidly, whilst any cMOOCS that still have some connectivist aspects to them (use of social media, group tasks) have adopted more and more of the features of xMOOCs (a fixed content is ‘delivered’ – hence the term content-based), to the extent they can be called hybrids. The UK company FutureLearn, for example, offers free, open MOOCS but its platforms are also used to promote fee-paying degrees with The Open University, microcredits and badges and the courses are structured by Futurelearn to quite a large extent. FutureLearn’s free courses also offer ‘extra benefits’ for a price, so students can gain extended access to materials. None of these are offered for a fee on the cMOOCS discussed above, as any course benefits are extended free of charge. The ‘open’ aspect on Futurelearn courses is more about students’ freedom to study at their own pace, than on unfettered access to materials. In terms of technology, however, Futurelearn has a more varied offering. On its online educator course, students use video, interactive quizzes and polls that are a fixed part of the course offering, as well as various social media that are used on the cMOOC courses, ds106 and Rhizomatic.
In 2020, there are more than 900 universities around the world offering over 11,400 MOOCs and the emphasis is on monetary gain – accounting for the emphasis on a cognitivist-behaviourist, where institutions can ask for payment based on the learners’ achievement of specific goals. So, whilst, d106 and Rhizomatic, offering free courses, make very little money each year, by contrast, Coursera's 2018 estimated revenue is around $150 million and FutureLearn made around $10million. This means there is a corresponding focus on formal accreditation of learning. Perhaps partly for the same reason, the concept of free and openness, very apparent in former approaches to MOOCs, has now evolved to mean anyone can apply from anywhere. More and more courses are asking for formal proof of prior learning, such as a diploma or degree and fees are being charged in return for globally recognised certificates. However, the term ‘open’ has always been defined differently by different observers. FutureLearn course, I can speak to all aspects of one of its MOOCs.
Hew, K. F., & Cheung, W. S. (2014). Students’ and instructors' use of massive open online courses (MOOCs): Motivations and challenges. Educational Research Review, 12, 45.
Jacoby, J. (2014). The disruptive potential of the massive open online course: A literature review. Journal of Open, Flexible and Distance Learning, 18(1), 73-85.
Kennedy, J. (2014). Characteristics of massive open online courses (MOOCs): A research review, 2009–2012. Journal of Interactive Online Learning, 13(1), 1–16.
Lane, L.M. (2012) ‘Three Kinds of MOOCs’ Blog. [Online]. Available at http://lisahistory.net/wordpress/musings/three-kinds-of-moocs/ (Accessed March 29, 2020)
Veletsianos and Shepherdson (2016), A Systematic Analysis and Synthesis of the Empirical MOOC Literature Published in 2013–2015.
What are MOOCs?
Massive Open Online Course (MOOC ) is a term first coined by Cormier (Cormier 2008; Cormier and Siemens 2010) while he as conducting the "Connectivism and Connective Knowledge" course, which was 'the first to incorporate open learning with distributed content, making it the first true MOOC' (Downes n.d.). MOOCs are an evolution of OpenCourseWare (see my previous blog), of which first was arguably the one created by the Massachusetts Institute of Technology (MIT) in 2001 one of the leaders in the development of MOOCs (e.g. edX).
Use of MOOCs in a Secondary / Pre-undergraduate Educational Context
Partly because of the need for quite a high level of learner independence and peer support in MOOCs it is very questionable whether they can work in their 'pure' form in secondary level education but there are quite a few other reasons why using them would be a challenge, not least because this phase of a young person's learning is dealt with on a compulsory face-to-face basis in most instances. There is room and incentive for a blended learning approach, therefore. Other issues are the use of smart devices and web technology inside or outside of the classroom, where the school or parents may have a policy against it. There are issues of safety, security, and privacy of minors. I have attempted it on a small scale and was met with mixed results for all of these reasons but every teacher in schools should attempt it for professional development reasons as well as for their students' development as learners.
Course content and Target Audience
The target audience of a MOOC in my learning context would be mainly (but not exclusively) STEM students who want to improve their research skills, their digital literacy, and their knowledge of mobile technologies as learning tools in English. They would be non-native speakers on EAP (English for academic purposes) foundation courses or students of Global Perspectives and Research (GPR), which is similar to an EAP foundation course. Both courses seek to prepare students for university studies in English. GPR is a social studies focus, with global issues and global citizenship at its core. Two key GPR topics are ‘Education for all’ and ‘The Digital World’. Because the students are mainly planning to study sub-disciplines of engineering, there would also be a strong multidisciplinary aspect to the course.