Reviewing my (digital) 2015

My digital 2015?

This post is inspired by Alexandra Samuel’s HBR article „Your Digital Year in Review„. She suggests reflecting on digital habits throughout the year by considering the four foci productivity, inspiration, socialisation and learning opportunities. Technology plays an important role in my daily routines and too seldom do I reflect on if I truly benefit from it the way I should. As Samuel puts it, when she is describing insightful online moments:

But those aha! moments probably won’t come from watching cat videos or taking Buzzfeed quizzes.

I catch myself watching and playing these, too. But honestly said, they did not make it to my reflection list. But if not the cat videos and quizzes – what are my online aha! – moments? Online and offline has become much more interwoven in my life. And the four foci symbolise this to a certain extend. Even if I have online aha! moments, they are worth nothing without applying them to my offline, analog me. No truly inspiring moment can happen purely on- or offline.

Productivity

Getting things done in a meaningful way. This is my definition of productivity. It’s not simply doing things. It is about finding the right way of getting things done and prioritise in a suitable manner. My personal blog is by far the most long-term productive tool I have ever started. Even though there were times I did not post frequently or did not know what to write about / how to formulate my thoughts, it was the progress that contributed to my productivity.

Personal Blog

A blog (a truncation of the expression weblog)[1] is a discussion or informational site published on the World Wide Web consisting of discrete entries („posts“) typically displayed in reverse chronological order (the most recent post appears first). [Wikipedia]

Becoming confident

Most and foremost, I remember the frustration when I hesitated to press the publish button when I started blogging. What would others think and how would they react? Now that my post is out there, I cannot take it back, can I? Insecurity was followed by bitter frustration and irritation after publishing a post. No one reads this anyway, so why should I keep writing? In the end I realised that this blog is what I called it. A personal blog. And that a personal blog is not about clicks and comments. But about my own learning process and my own experience. It gave me a lot of confidence to write, actually publish and share my thoughts and research. In addition, I reflected on my arguments, line of reasoning and wording.

Expressing quality

Blogging is not about frequency. Frequency is no indicator for quality. I catch myself judging a blog’s quality by the date of the last post published. This is definitely not fair. The aim of frequent post-publishing is only relevant if there is something resonable to write about. Blogging over a longer period enables me to remember and reflect on what I have done. It illustrates a process. In times where I questioned if I had done anything productive at all during the last days, weeks and month; my blog reminds me of all the great thoughts I had.

Reflecting, moving on and connecting blogging and productivity

My initial idea in 2015 was not to generates clicks and likes. It was a year of pushing things out and getting confident. I still have a hard time focussing on a theme and framing a reasonable amount of information. This is ongoing work for me. I still learn to balance between reworking a draft and deciding on when it is time to publish it. Writing about my thoughts feels meaningful and this is why I produce these artefacts I can refer to and reflect upon. In 2016 I want to work further on linking, tagging and spreading my posts to the right people. An important requirement for this is to generate ideas of topics I am interested in so I feel motivated to invest my time in.

Inspiration

For me inspiration comes in four steps. Find great sources which inspire me, get input from these sources, apply it to my own situation and get feedback on how that worked out. In retro perspective I decide if the identified resources are still inspirational. Great digital tools support me during all of these four steps. LinkedIn has done so in different ways. I used groups and following function to get the input I thought was most inspiring as well as my own profile content to keep reworking my biography.

LinkedIn

LinkedIn /ˌliŋkt.ˈɪn/ is a business-oriented social networking service. [Wikipedia]

Creating self-awareness

The overwhelming power of a professional network is the combination of a personal profile and the evolving network around it. LinkedIn is not your CV. I heard this during a talk on professional storytelling and couldn’t agree more. It became a continuous progress to change my profile and frame the person I am. My profile is (and probably will be) always in the making. It motivates me to ask questions like: who am I, where do I come from, where am I now, where do I want to go and how do others perceive me? Even though I might not have definite answers to all of these questions, there is this satisfactory feeling of being more certain with every saved edit.

Identifying the inspirers in my network

Inspiration, as I pointed out earlier, is a never ending process. It is about finding sources of inspiration, keeping them or moving on. This can be a very long and demanding development. In 2015 I realised what having a network and being part of a network means. I started identifying central actors of my network and how they contribute to this network. What does this person share, post or like – and do I consider this as inspirational? In 2016 I want to focus on how I can see more of those inspirational people and even on how I myself can become inspirational for others.

Socialisation

When moving to a new place it requires initiative to reach out to people. I realised that just going out and meeting up is completely different from connecting and networking with people. It feels like I was wasting my time browsing the web, instead of just getting out into the real world.

Lunchback

This is the reason that we started Lunchback, an app that can be used to find yourself a mentor in your local area. [Lunchback on The Local]

Being clear in what you want (and what not)

Until finding Lunchback, I really had become fed up with all the effort I put into networking. It always resulted in numerous, but loose connections. With Lunchback I realised that as important as socialization is – it’s even more important to be aware of what you want to get out of it and choose your events accordingly. I began to work on being concrete with my feedback requests. Why do I want to speak to this person? What do I want to have feedback on? How do I formulate my request concisely and precisely? Until today I have not received a „no“ but rather long-term intense contacts who support me in my personal development.

Daring to try something new

When it comes to socialisation, I tend to stick to my old habits. After all, they have worked out in different contexts and with different people. When time becomes a scarce resource however, I start wondering about with whom I really want to spend my time and why. This might be a good time to dare trying something new. I admit that it felt a bit scary to use the app at first. In the end, you are meeting a person for real, over lunch, spontaneously. But it’s worth it to go out there and try it. The matching process is thought through and all the people I met where and are supportive in so many ways.

Learning Opportunites

Learning is understanding a concept, connecting it with what your already now and share it with others. I have taken many MOOCs (Massive Open Online Courses) in 2015. Not all of them where meaningful. But most of them did make a difference. I would say that they represent a new understanding of learning. The idea of life-long learning and individualised (micro) learning opportunities anytime anywhere.

MOOCS

A massive open online course (MOOC /mk/) is an online course aimed at unlimited participation and open access via the web. [Wikipedia]

Learning how to learn

I have always been fascinated by those people that strive for learning something new every day. When I first heard about MOOCs I was browsing the web on online learning. It is impressive how many resources are out in the WWW if you want to learn about something. However, I sometimes miss structure and quality of content. Even though, not all MOOCs I took provided these, they equipped me with guidance and a learning path. In the end, I learned a lot about how I learned best. By interacting with others, answering questions and producing my own learning artefacts.

Sharing is caring

Learning online was a new experience and I needed my time to adapt to a new environemnt. But during this process I learned what the buzz-phrase „sharing is caring“ means. By creating my own learning artifact and sharing it with my learning cohort, I could actually recieve meaningful feedback not only by the facilitator but by my peers. Especially in adult education this concept is valuable, because everybody comes with a backpack of prior knowledge and experience which contribute to the learning experience. Also, sharing knowledge means you are trying to verbalize what is in your head. This is a very demanding process and I truly believe by continuing doing so in 2016 I can contribute to others‘ learning experience as well.

My digital 2016!

Here is my digital bucket list which summarizes my want-to-do’s and will-do’s of 2016.

  • Join a network that inspires me on- and offline. Contribute to this network.
  • Desing, create and improve my social media appearance.
  • Work on my contact follow-up and reach out to inspiring people more proactively.
  • Organize my apps in a way I want them to use – not in a way I use them.
  • Reflect daily. And talk about it to someone I trust. Dare to talk about my dreams.

I encourage you to write your list, too. I would love to hear about it! If you don’t feel ready to share it, write it down for yourself. And who knows, you might share it in your digital review 2017?

 

Back on track

It has been a while since I published my last blog post. Many things have happened and new opportunities opened up. It was hard resisting the creation of a new post barely for the sake of writing something. What this period has taught me is that at times it is best to step back and wait patiently until it feels right to move on.

I spend my summer in South Korea, participating in Korea University’s International Summer Campus. It was an inspiring time, where I put my efforts into an Introduction to Computer Science and Brain Science, as well as a beginner’s course in Korean language. Besides the academic achievements it was a personal challenge for me, diving into a culture so different from what I am used to back in Gothenburg. I made new friends, got the opportunity to travel the country with old friends and am grateful to say that this experience helped me in focusing again on future challenges.

After a calm and quiet first week back in Sweden, things are moving a bit quicker now.

First of all, I decided to go „back to the roots“ by attending an entrepreneurship course at Handels in the autumn term. The optional 30 credits in our Master’s programme allow me to transfer these course credits as well as potentially the credits from an ICT policies course at Chalmers in the second half of the term.

Secondly, I am confident to have found an opportunity for my Master thesis supervision. The research question will be both – challenging and interesting – and I am looking forward to dig into the topic and clarify administrative details.

Thirdly, and very relieving for me, I decided to (and managed to – so far 😉 ) speak Swedish only from now on. I can rely on great support from my family and friends and I am happy that I managed to break my language-blockage, which put a lot of pressure on me without me consciously noticing it.

All in all, it feels good to be back – and I am looking forward to a new academic year!

About the Learning Through Life Inquiry into the Future for Lifelong Learning (IFLL)

This text was originally handed in as assignment 3 of course PDG083 V15 Contemporary Adult Education (Samtida vuxenutbildning) at Gothenburg University on March 1st 2015. 

In this assignment I am comparing two articles published in Volume 29 of the International Journal of Lifelong Learning in 2010: Learning through life: A response to a special issue written by Tom Schuller in Issue 6 and ‘The planet will not survive if it’s not a learning planet’: sustainable development within learning through life written by Shirley Walters in Issue 4. In my comparison I will focus on the problems discussed by the authors, how these are developed, what the conclusions are and which concepts are used. First of all, both articles refer to the Learning Through Life Inquiry into the Future for Lifelong Learning (IFLL); a report by the National Institute for Adult and Continuing Education (NIACE), which investigates lifelong learning in the UK and was published in 2009. Whereas Schuller is one of the authors and the director of the inquiry; Walters is professor and director of the Division for lifelong learning at the University of Western Cape, South Africa. Issue 4 of Volume 29 of the International Journal of Lifelong Learning is a special issue dedicated to commentaries on the IFLL report. In its introduction Jarvis closes by writing “[…] Schuller will write a response to the papers in this special issue” (p. 400). This emphasizes the intention to support the ‘style of interchange’ mentioned by Schuller, who calls for an active dialogue concerning the IFLL report (p. 757). Walters contributed her paper on the sustainable development theme to this special issue of the International Journal of Lifelong Learning and appeares as the third author in this volume.

Walters tackles the theme of sustainable development ‘from a ‘South’ perspective’ (p. 427) by criticizing the British lense as being rather a critique than a critical analysis, but finally commemorating her intention to constructively contributing to the discussion by looking for alternatives, “which can produce a more democratic, egalitarian learning planet, which can sustain life for centuries to come.”  Walters’ main critique regarding the sustainable development theme is that it firstly, reaches further than national borders and secondly, implies more than climate change. She points out a clear lack of defining the term sustainable development in the IFLL report. Furthermore, she argues that the report ignores the urgency of the “current global economic and environmental crises” (p. 430). Whereas she agrees on the four life stages developed by the report, she questions the transferability of demographics from countries of the North (e.g. the UK) to countries of the South. In addition, Walters points out the missing concept of ‘life deep learning’ (p. 432), within which learning embraces spiritual components as well. She additionally values the idea of the citizens’ curriculum, but identifies a need to elaborate it’s financial and applicable implications. Whereas she agrees with the importance of ‘joined-up cross-sectoral approaches’ (p. 434) being made by the report she identifies a need to discover the challenges of these approaches more thoroughly. All in all, she refers to Wallerstein in her final conclusion, where she evaluates the report (besides all its assets) as an interim-solution or intermediate result rather than pointing to a “‘[…] new successor system that we want’” (p. 435).

Analysing Schuller’s text, I will focus on these two text passages, which refer directly to Walters paper. However, for a general overview, in his paper he first makes some general comments on design and purpose of the IFLL and then focusses on some commentaries in the special issue, which he sees as most “fruitful” to enrich the dialogue on the report.

On page 760 Schuller acknowledges the underdevelopment of the theme sustainable development mentioned by Walters and the fact that this theme did not ‘get the weight, which it deserved’. In response to this critique, he points out three dimensions, which he sees as crucial for further investigations of the theme (and which the commission ‘would have liked to explore’ but was not in the position to). The first dimension is authority and how to select the powerful voices which influence policies. The second dimension is the connection between learning and action, in particular how awareness supports or depresses ‘people’s capacity for action’ (p. 760). As a third dimension, Schuller elaborates morality, asking “how do individuals and groups learn to grapple […], and to continue to live together even when there is no consensus?” (p. 760). All in all, Schuller stays close to the issues of climate change and global warming, contributing to Walters’ assumption that this is the perspective on sustainable development within the IFLL report.

Under the heading “A spiritual dimension” Schuller discusses commentaries from Walters, both referring to “the spiritual dimension of learning—‘life‐deep’ as Walters terms it” (p. 762). Schuller points out that by avoiding the term spirituality, the report aimed at avoiding a terminological debate. He accepts Walters’ challenging the transferability of the detected demographic trends from the UK to the South but reminds the reader that one “central thrusts of LTL is the need to take account of demographic trends in the UK” (p. 762). From Schuller’s point of view, demographic developments per se will shift the focus to a more central perspective on spirituality, where “intergenerational equity” comes into play (as opposed to individualization). More generally, it becomes important how older generations address spirituality and how they gain visibility is improving opportunities for other generations.

Hence, Schuller’s paper operates as a response to Walters’, focusing on two main commentaries (one of it being her main critique: the lack of defining the term sustainable development”). By doing so, Schuller himself fulfills his (and the IFLL report’s) claim for an ongoing constructive dialogue over the IFLL report. Both authors value each others work by evaluating as well as by giving recommendations for improvement. This is especially interesting when taking into account that the report has already been published when both papers are released. By saying so, Walters and Schuller contribute to an ongoing discussion on lifelong learning policies within the field of adult education independently of publication dates and deadlines. In addition, the authors abstain from criticising all possible aspects of the other’s work in detail but rather focus on specific themes that they find important and relevant. This offers the opportunity to evaluate the work through different lenses and thus allows an interpretation from different view angles.

 

References

Jarvis, P. (2010). Inquiry into the Future of Lifelong Learning. International Journal of Lifelong learning, 29(4), 397-400.

Schuller, T. (2010). Learning through life: A response to a special issue. International Journal of Lifelong Education, 29(6), 757-766.

Walters, S. (2010). ’The planet will not survive if it’s not a learning planet’: sustainable development within learning through life. International Journal of Lifelong learning, 29(4), 427-436

Remixing and -using of resources: Actor-Network Theory

Last week’s lecture on actor-network theory reminded me on my final paper written for my first course on „Technology, knowledge and learning: An introduction“. The resources and discussions in this course turned out to be a solid base for understanding the Actor-Network Theory (ANT). In fact, my final conclusion partly aimed at this theory, by saying that technology is neither fully determined nor neutral. However, this is only a scratch on the surface and this blog post is intended to support my personal reflection in the ANT and the collection of some useful material.

Actor-Network Theory in brief

ANT can be described as

[…] a vocabulary that does take the distinction between subjects and objects, the subjective and the objective, into consideration. […] an „actant“, for example, is more than a human actor. Both humans and nonhumans may be actants.

The important fact here is not that humans and nonhumans are treated symmetrically (a given in social semiotics and ecosocial dynamics) but that they are defined relationally as arguments or functors in the network, and not otherwise. This leads to a relational epistemology which rejects the naive positivist view of objects or actors as existing in themselves prior to any participation in ecosocial and semiotic networks of interactions (including the interactions by which they are observed, named, etc.).

This framework (network) is comprised of components (actors) not all of which are usually (if ever) considered by the academically oriented sociologists. The network consists not only of people and social groups, but also artifacts, devices, and entities. Engineers who elaborate a new technology as well as all those who participate at one time or anotherin it’s design, development, and diffusion constantly construct hypotheses and forms of argument that pull these participants into the field of sociological analysis. Whether they want to or not, they are transformed into sociologists, or what Callon calls engineer-sociologists. (Resource)

Given the fact, that I am fairly new to this theory, I found it very helpful to think about the following question: „Can technology force us to learn in a specific way?“ (adapted from a question our professor asked us during the lecture). I said, that without the motivation to learn there is no possibility for technology to force anyone. However, reflecting on my statement now, this assumed that technology would (be) develop(ed) in a „social vacuum“, where motivation is not considered but instead would possibly change the intended purpose of a technology. What is missing here, that it can be the other way around: technology could trigger motivation as well. By saying so, it could be an actant in the network.

I still find this hard to grasps and will surely develop further on this. As a foundation, I attach my final assignment for reviewing purposes (not changes made, this is how it was handed in) and I hope some of you might find it useful.

The final assignment

The final paper was supposed to be an answer to a fictive friend, asking for advice regarding a planned university course. This covered the learning outcomes of the course, in particular (in the field of IT and learning) „identify epistemological differences and theoretical contributions, identify and critically examine current popular theories and applications in relation to major historical research traditions, demonstrate and problematize the relations between theories of learning, knowledge and technological change and contextualize technology use within different designs of learning and knowledge domains.“

I’ve heard you’re attending an International Master’s programme in IT and Learning – congratulations! I’m contacting to ask for some advice. I am a planning a similar introduction course you are attending at the moment (ours is part-time and offered in Swedish however). My problem is that my colleagues have different opinions on how we should design and plan for the course. Many think that the most important thing is that students have flexibility in time and possibility to take net-based self-study course modules. However, others think we should have more of live-streamed lectures and on-campus group work. Could you give me some pros and cons on whether to choose one or the other? Or rather, are there other aspects we should consider instead in our pedagogical approach or design of the course? We know our students are geographically spread and are working or studying part time, but we are also required to offer the students some on-campus meetings during the course.
You know I’m a novice here, but very curious about the insights into the field of IT and Learning – what are the big differences in ways of approaching designs for learning? And if you can, please update me on important movements, ideas, or technologies etc, relating to our dilemma, so that we might read about them in my work team.


Hej Peter,

thanks for your letter ­ I hope you find my explanations useful. Your requests consists of three main themes, asking for

(1) guidance in terms of your course design that is
(2) related to contrasting design approaches for learning within the field of IT & Learning in general
(3) and to input on important (current) developments concerning your situation.

Your course is designed for Swedish­speaking part­time students, which are geographically spread ­ however, on­campus meetings are required. The two views on the course design can be described as flexible (net­based self­study) and less flexible (live­stream lectures and on­campus group work). Each of these designs has its assets and drawbacks. You should be aware of common mistakes when designing a distance education programme (including false expectations, missing technical support, vague requirements, etc.) and of implications of terminology when it comes to distance and online education [Garrison, R. (2009)]. Let me emphasize the learners’ needs as the primary source for course design implications. By examining these constantly the course can be tailored to individual needs, improving both ­ the learner’s performance and the course quality. The emerging field of learning analytics facilitates this immediate feedback process and research on related phenomena such as predicting course drop­outs [Baker, R., & Siemens, G. (2014)]. In your letter you are missing this point ­ you are describing the participants in a broad manner. What are their expectations? Why do they choose your programme? How can you ensure that the expectations are met and that your course idea is communicated properly to the learner ­ before and throughout the course?

Comparing your proposed designs, the flexible programme offers more individual freedom with the possible shortcoming of a slower socialising process due to missing face­to­face meetings. In contrast, the less flexible programme limits individual freedom but attendance classes can support socialising and the group­work process. Due to the requiredattendance classes at least a mixture of net­based and on­campus meetings is useful. There are more pros and cons to be named when evaluating design approaches. I want to focus on the aspect of socialisation. The field of IT & Learning has changed over time recently specifically targeting the learner and his/her social learning environment. It has become important to evaluate interdependencies of technology and learning understanding their (historical) development plays a crucial role in it. In the science of learning we have come a long way from more or less radical behaviorists (e.g. Watson, Skinner, Thorndike) that believed in observable behavior as the true scientific approach to research on learning, over the serious study of mental functioning triggered by the new field of cognitive science in the late 1950s (e.g. Simon, Turkle) to the importance of the social and cultural contexts of learning. In addition we may not forget the focus on the processes of knowing in the new science of learning (e.g. Piaget, Vygotsky) [Committee on Developments in the Science of Learning, 2000]. Including the work of Suchmann we reach the level of defining human­machine­interaction and aliveness. The development from behaviorism over cognitivism to situative/pragmatistic­ sociohistoric views can be seen in educational technology as well. Some of the above mentioned authors state the potential of technology in the learning process. Learning theories can be related to paradigm shifts in instructional technology. Whereas CAI (computer assisted instruction) can be classified as behavioristic (how well can software support the learner to achieve specific knowledge), ITS (Intelligent Tutoring Systems) belong to the cognitivistic theory (how well does software mimic a real teacher). Logo­as­Latin can be arranged within the constructivistic tradition (how well can software support students in transferring knowledge) whereas CSCL (computer supported collaborative learning) is connected to situated learning (how well does the software support learners in engaging in knowledge communities) [Greeno, J. G., Collins, A. M. & Resnick, Lauren B. (1996); Koschmann, T. D. (1996)]. The major outcome of this development is that knowledge, learning and transfer are seen dissimilarly in learning theories and thus the role of technology is shifting, too. Likewise, the generations of distance education exemplify the changing roles of cognitive, social and teaching presence [Anderson, T. & Dron, J.; 2011].

Current developments in IT & Learning emphasize learner­centered learning environments and scaffolding. Learner­centeredness describes the focus on the learner’s psychological learning process or her/his participation in a sociocultural learning process [Hoadley, C. & Van Haneghan, J. (2012)]. Although the notion of scaffolding has changed over time one of it’s main implication is individual cognitive growth through a more competent tutor adapting to evolving knowledge and skills of a less competent tutee [Puntambekar, S., & Hübscher, R. (2005)]. These current developments point towards the individual learner and his/her learning needs. I am referring back to the beginning of my letter, where I emphasized these needs as well. Learning technologies become tailor­made and can adapt flexibly to different users. Some examples of emerging trends in education are gaming, MOOCS and EduPunk. [Open University (2013), Liyanagunawardena, T.R., Adams, A. A. & Williams, S A. (2013), Innovation Unit (no date), Kamenetz, A. (2010)]. This broad range speaks for itself and is reflected and linked to the aspect of the crossdisciplinarity of the field [Kalz, M. and Specht, M. (2014)]. As many fields of research, IT & Learning does not withstand critique on e.g. it’s methodical capacity [Bulfin, S., Henderson, Johnson, N F, Selwyn, N. (2014)] or technological determinism [Oliver, M. (2011)]. Selwyn, N. & Fracer, K. (2013) cover the critical use of digital technology in education from a broader perspective, by analysing the stakeholders in educational technology, the use of technology in education and how it should be used for which educational causes. Gaming as a panacea has been criticized [Linderoth, J. (2012) as well as the underestimated use of procedural rhetoric [Bogost, I. (2007)].

After understanding where the learning sciences and the implications for educational design come from, we need to emphasize the evaluation of interdependencies between learning and technology. There is an ongoing discussion on the question if technology influences education or if education influences technology. In my opinion, the most critical item is avoiding technological neutralism and determinism at the same time. Technology is not just a tool that can be added to educational approaches nor does it have an undefined impact we can’t grasps. What is it then? I think as educators we are in the position to evaluate technology more critical ­ not to give one definite answer.

Related to your letter, I can understand your request for practical and applied guidance towards solving your course design question. Yet, you are mostly taking into account the design itself and how to implement it with the help of technology. As a researcher in the field of IT & Learning let me tell you that a good course design depends on more factors than being flexible . Do new approaches in IT & Learning change the way of learning or do they try to change the learner? How do we ensure keeping the focus on the learners’ needs and on implementing the social aspect of learning with the support of technology? How do we define digital literacy and how to we implement a critical and evaluating view on educational technology?

Best regards
Hannelore

References

Anderson, T. & Dron, J. (2011). Three generations of distance education pedagogy. International review of Research on Distance and Open Learning, 12(3), 80­97.

Baker, R., & Siemens, G. (2014). Educational data mining and learning analytics. Cambridge Handbook of the Learning Sciences.

Bogost, I. (2007). The rhetoric of video games. In Salen, K. (Ed.), The Ecology of Games: Connecting Youth, Games, and Learning (pp. 117­140). Cambridge, MA: MIT Press.

Bulfin, S., Henderson, Johnson, N F, Selwyn, N. (2014). Methodological capacity within the field of “educational technology” research: an initial investigation. British Journal of Educational Technology, 45(3), 403­414.

Committee on Developments in the Science of Learning (2000). How People Learn: Brain, Mind, Experience, and School.

Garrison, R. (2009). Implications of Online Learning for the Conceptual Development and Practice of Distance Education. Journal of Distance Education, 23(2), 93­104.

Greeno, J. G., Collins, A. M. & Resnick, Lauren B. (1996). Cognition and learning. In D. Berliner & R. Calfee (Eds.), Handbook of Educational Psychology (pp. 15–46). New York: Macmillan.

Hoadley, C. & Van Haneghan, J. (2012). The Learning Sciences: Where they came from and what it means for instructional designers. In R. A. Reiser & J. V. Dempsey (Eds.),
Trends and Issues in Instructional Design and Technology (3rd ed., pp. 53­63). New York: Pearson.

Innovation Unit (no date). Ten ideas for 21st century education.Kalz, M. and Specht, M. (2014). Assessing the crossdisciplinarity of technology­enhanced learning with science overlay maps and diversity measures. British Journal of Educational Technology, 45(3), 415­427.

Kamenetz, A. (2010). DIY U: Edupunks, edupreneurs, and the coming transformation of higher education

Koschmann, T. D. (1996). Paradigm shifts and instructional technology: An introduction. In T. D. Koschmann (Ed.), CSCL: Theory and practice of an emerging paradigm (pp. 1–23). Mahwah, NJ: Erlbaum.

Linderoth, J. (2012). Why gamers don t learn more. An ecological approach to games as learning environments. Journal of Gaming and Virtual Worlds, 4(1), 45­61.

Liyanagunawardena, T.R., Adams, A. A. & Williams, S A. (2013). MOOCs: A Systematic Study of the Published Literature 2008­2012. International Review of Research on Distance and Open Learning, 14(3), 202­227.

Oliver, M. (2011). Technological determinism in educational technology research: some alternative ways of thinking about the relationship between learning and technology. Journal of Computer Assisted Learning, 27, 373–384.

Open University (2013). Innovating pedagogy 2013 OU.

Puntambekar, S., & Hübscher, R. (2005). Tools for Scaffolding Students in a Complex Learning Environment: What Have We Gained and What Have We Missed?.Educational
Psychologist, 40(1), 1­12. doi:10.1207/s15326985ep4001_1

Selwyn, N. & Fracer, K. (2013). Introduction. The need for a Politics of Education and Technology. In. N. Selwyn, & K. Facer: (Eds.). The Politics of Education and Technology: Conflicts, Controversies, and Connections. New York, London: Palgrave MacMillan.

UTArlingtonX: LINK5.10x Data, Analytics, and Learning or #DALMOOC (Week 7) – Part I

If I was a Text Mining Expert …

I would work on a model that could predict not only spelling and grammar mistakes but that could help investigating why these mistakes were made. And I would ban the words „mistake“ & „error“ from this model because defining something as such has drastic consequences: the assumption that there is only (a predefined) right or wrong. (Whereas I have to admit that I am still looking for an adequate substitute). Questioning why is made so much harder – because obviously simply choosing the right answer by a right click in the spelling check software saves a lot of time.

While this might appear to be an unsolvable quest at first sight, I think there are numerous patterns that could help to develop such a model. This text is written in English. But I am not a native speaker. I do speak 3.5 languages. Starting a new one is always a special challenge. Because the more languages you learn, the more context exists to frame the new language. This can be good. You know, which words you have to learn first for daily conversations, which grammar structures are particularly useful. You know where to start.

But one thing always stays the same: I am trying to find out WHY I make certain mistakes. This goes beyond simply knowing THAT I made a mistake. It is to find out WHERE I got the structure or word from I am not applying adequatly. It is to understand that the mistake could possibly be correct in another language, make the connection to the current language and store this connection.

(This is how it works for me. And I think that others can benefit from this as well. I am not a professional linguist so this is not grounded on any well-established theory or such. I guess there might be several research undermining or supporting this idea.)

Bist du das? ≠ = Are you it?

Literal interpretation is one example. While the English native would understand at least what „Are you it?“ is supposed to mean („Is it you?“) – does this mean that the translation is wrong? Yes – says the English teacher. No – I say.  I speak both languages and thus can make sense out of it and know what the other person wanted to ask. Isn’t that weird? At first it seemed so plain that the question „Are you it?“ is wrong – but why would some people then understand it? Because of the similar background/ context (of language) they have. Because they understand WHY someone translated the question this way.

We have so much data sources to choose from for translations. Why can’t we make the spelling check process more individual? One could implement settings to choose native language and other languages learned so far. When a mistake is detected, a model could be applied to detect if this is a simple typo or a systematic error that can / can not be connected to another language. Imagine the potential of evaluating writing patterns (e.g. as already available for messaging in Android systems: the system is guessing your next word): You could get a summary of frequently occurring mistakes and working on these in future.

Until my breakthrough with my „why-you-made-this-mistake-model“

Could I ask you for a favor? If you know someone in your social environment who is learning a new language and he/she is asking for a word: Please don’t just translate the word into a language that is easier for him/her! Try to explain the word in the language he/she is learning and give as much context as possible. It helps a lot. I know, it’s not always easier. Because the faster way is a simple translation (like the right-click in your spell-check). But on the long-run, putting language in context is worth the additional expenditure of time.

UTArlingtonX: LINK5.10x Data, Analytics, and Learning or #DALMOOC (Week 4)

Social Network Analysis in the area of conflict between being analytic & considering educational research

Discussing assets and drawbacks of learning analytics (LA) and social network analysis (SNA) in particular leads to discussing the objectivity of data collection. Applying these methods not only enables live-data tracking and analysis (as opposed to self-reported pre-/post-course surveys) but the objective analysis of learner’s traces in the learning environment (though this does not account for a complete picture of the learning which takes place). However, the potential stays untapped if underlying pedagogical and epistemological assumptions are not taken into account.

Gašević, D., Dawson, S., Siemens, G. (2015) point this out as they claim LA to connect existing research on learning, teaching, educational research and practice. They bemoan missing studies which evaluate the concept of the established lead indicators of LA. Three major themes in their paper are the detailed description of how tools are used, looking beyond frequency of activity and time spent on task by analyzing individual learning strategies and products  and the connection of internal and external conditions for data. Within this context the base for effective LA visualizations lies in the consideration of instructional, learning and sense-making benefits – foundations in distributed cognition and self-regulated learning being a potential direction of future research.

„The Epistemology–Assessment–Pedagogy triad“

Knight, S. et al. (2014) identify LA as implicitly or explicitly promoting particular assessment regimes in the epistemology, assessment and pedagogy triad. A wonderful, more detailed reflection on this triad in connection to learning analytics can be found here (authored by Classroomaid). Suthers, D. D. & Verbert, K. (2013) define LA as the „middle space“ between learning and analytics. In their paper they elaborate three main themes for future research in the field of LA: „the middle space“ (focus on the intersection between learning and analytics, avoiding the emphasis of one of these themes), „productive multivocality“ (facing the challenge of unifying a multifaceted research field by focusing on analyzing a common data ground) and „the old and the new“ (enhancing learning as a century-old idea that is continuously accompanied by new tools) (pp1). Given the rich online learning landscape, clustering learning environments can be the first step of detecting characteristics, underlying epistemology-assessment-pedagogy beliefs and thus identifying the appropriate measures of learning analytics.

"The Epistemology–Assessment–Pedagogy triad", adapted from Knight, S. et al. (2014), p4

„The Epistemology–Assessment–Pedagogy triad“, adapted from Knight, S. et al. (2014), p4

For example Rodriguez (2012) classified MOOCs as either c-MOOCs (following the connectivist tradition) or x-MOOCs („AI-Standford like courses“, following the cognitive-behaviorist tradition). It is important to note here, that the term „x-MOOCs“ was not coined by Rodriguez, but Liyanagunawardena, T., et al. (2013) establish ties to Daniel (2012), where they detected similar definitions and thus combined both papers. For his classification Rogriguez used Anderson & Dron’s (2011) paper on „Three Generations of Distance Education Pedagogy“ where they coin three DE pedagogy concepts. Bringing the triad back into focus: it’s the pedagogy concept that supports his classification – differentiating between connectivistic and cognitive-behavioristic pedagogy.

The implication of this classification is a different view on teaching, social and cognitive presence in the online learning environment. This view needs to be considered when analyzing the underlying epistemological concept and the assessment formats. Besides common features, this relates especially to the role of course instructors, the definition of openness (access vs. openness to personalized learning), connectedness and guidance. Knowledge is either generative (c-MOOC) or declarative (x-MOOC). By saying so, without a coherent triad the best assessment strategy does not tackle the real learning happening. Furthermore, the triad can be used to continuously challenge the assumptions of each corner.

Active Learning – an example for effective college classroom practice

One example of this triangular interplay is active learning. Grunspan et al. (2014) mention the effectiveness of active learning in college classrooms and as a result they explore this practice with the support of Social Network Analysis. However, the triad does not implicitly determine direction and interdependencies. Critical reflection of all intersections is necessary. This exemplifies the importance of meta studies, e.g. „What makes great teaching? Review of the underpinning research“ by Robert Coe, Cesare Aloisi, Steve Higgins and Lee Elliot Major (2014). A call for a constant challenge of learning assumptions, the participation in the on-going research process and the relation and integration of own research efforts go hand in hand with the importance of comparing different underlying concepts and critically questioning if researchers are particularly considering the same concepts. As one example of this meta study, active learning and its outcomes for the learning progress seem to contradict Grundspan et. al. By relating to a learning pyramid, Coe et al. argue that memory and remembering is not evidently based on being better when participating actively or passively („Ensure learners are always active, rather than listening passively, if you want them to remember (p24)). Simply the different level of complexity of both concepts (active learning and active/passive listening in relation to memorizing) discloses that we are not exposed to the same ideas here. However, these approaches seem to be connected and point in opposing directions of sound research evidence. When validating and examining existing research, it becomes more and more important to nail the underlying assumptions and research questions to create reliable conclusions for further research.

Six different case studies: Learning design can influence learner’s decision

The course presents six different case studies which emphasize the claim that learning design can influence learner’s decision. By doing so, the above triad is underpinned again – not only focusing on practical applications but also giving a direction for future research approaches that critically question underlying concepts of epistemology, pedagogy and assessment.

1. Instructor-centered network: Bringing together SNA and learning design [Lockyer, L., Heathcote, E., & Dawson, S. (2013)]

Lockyer et al. explore how the framework for the interpretation of LA might lie in the learning design. By using case-based learning they examine a concept of checkpoint and process analytics to analyse learning design embedded in a context, in real-time and behavior-based (a more narrowed-down application of LA). Hence, learning design and analytic design are connected to support learning and teaching decisions. They also propose different directions for future research including „engaging teachers and students in understanding and using visual patterns of interaction as a means to encourage learning activity; scaling up to larger numbers of classes, providing a base for comparing statistically the observed to expected analytics of behaviors and interactions; and using results to provide meaningful feedback to teachers on how their learning design is meeting their pedagogical goal and to assist them in decisions around design and pedagogical change in real time.“ (p1455)

2. Sense of community [Dawson, S. (2008)]

The research question in this study is „Is the composition of social networks evolving from a unit discussion forum related to the sense of community experienced among the student cohort?“ (p226). In general, this deals with the question of belonging vs. isolation, or better: with the extend to which learners benefit educationally from belonging and how this can operate as a predictor for students success (as social integration is strongest predictor for retention and completing university degree). The underlying educational concept is community-centered teaching practise, based on social-constructivistic ideas of Dewey and Vygotsky. The novelty with this study is that self-reported surveys are not the only data source anymore. It is a mixed method approach used here which focuses on quantitative (Classroom Community Scale, SNA centrality measures) and qualitative measures (discussion forum content, student interviews). As a result, Dawson found a association between the network position and the sense of community, in detail a positive association with closeness and degree centrality; a negative with betweenness centrality (dilemma of brokerage). In addition, pre-existing external social networks influence the type of support/information required. Concerning future research Dawson points towards the investigation of the relation between social networks and other measures having an influence on the learning environment such as pedagogy, practitioner personality and cohort demographic profiles.

3. Network brokers associated with achievement and creativity [Dawson, S., Tan, J. P. L., & McWilliam, E. (2011)]

Dawson, S. et al. discuss the correlation of cognitive playfulness to the network position where degree and betweenness centrality are oppositional to closeness (as they are positive indicators of a learner’s creative capacity) . By answering their research questions „What is the relationship between a student’s social network position and perceived creative capacity? To what extent do discussion forum mediated social networks allow for the identification and development of student creativity?“ they claim that SNA can provide insight in the creativity of students as well as a tool for instructors to monitor the learner’s creative capacity level. The individual’s self-reported creativity score thus corresponds with the overall social network position. Creativity is perceived as highly valued graduate asset.

4. SNA for understanding and predicting academic performance [Gašević, D., Zouaq, A., Jenzen, R. (2013)]

Gašević, D. et al. studied cross-class networks and the importance of weak ties by considering the relationship between academic performance and socal ties. The base for this study is social capital and network learning research. Two hypothesis where investigated: (1) „students’ social capital accumulated through their course progression is positively associated with their academic performance“; and (2) „students with more social capital have a significantly higher academic performance.“ Based on the ideas of Vygotsky one practical implication is the conception of new social ties in each course during degree programs.

5. SNA and social presence (What is the association between network position and social presence?) [Kovanović, V., Joksimović, S., Gašević, D., Hatala, M.]

This study focuses on the Community of Inquiry model, specifically on the social presence as one contributor to educational experience. Social presence consists of three parts, namely affectivity and expression, interactivity and open communication and cohesiveness. By analyzing the underlying social processes that contribute to the development of social capital, Kovanović, V. et al. give an insight in how affective, cohesive and interactive facets of social presence significantly predict the network centrality measures commonly used for measurement of social capital. Social constructivist pedagogies and the shift towards collaborative learning can be seen as underlying educational concepts. The research question „What is the relationship between the students’ social capital, as captured by social network centrality measures, and students’ social presence, as defined by the three categories in the Community of Inquiry model?“ (p3) leads to the results that interactive social present is „most strongly associated with all of the network centrality measures, indicating a significant relation with the development of the students’ social capital.“ In conclusion, in-degree and out-degree centrality measures were predicted by all categories of  social presence whereas betweenness centrality was predicted by interactive and affective categories.

6. SNA and understanding of MOOCS [Skrypnyk, O., Joksimović, S. Kovanović, V., Gasevic, D., Dawson, S. (2014)]

Skrypnyk, O. et al. explore the learning environment of a cMOOC to identify and understand important key actors. Although in this study the facilitators continued to occupy a central role, other actors emerged and complemented this picture. This was based on the two research questions „What is the influence of original course facilitators, course participants (ie., learners) technological affordances on information flows in different stages of a cMOOC?“ and „What are the major factors that influence the formation of communities of learners within the social network developed around a cMOOC?“. As a result, types of authorities can be classified as „hyperactive aggregators“ and „less visible yet influential authorities“. For the former, there might be an existing connection to natural personality traits. Another outcome is the importance of hashtags for information flow and community construction within a more learner-centered environment supported by software.

Application in Gephi and Tableau

By combining Gephi and Tableau I created a dashboard, where it is possible to see different ways of visualizing the same data source. Please click the image to enlarge it and see descriptions for the single sheets on the dashboard. As my first attempt, this dashboard shall illustrate how conclusions could be drawn from one single glance.

For example, the network analysis with Gephi detects the network structure and reveals node 3 as a central key actor when it comes to the measure of degree (top right). 9, 10 and 11 follow with some distance. The same pattern can be detected in the top left visualization, where size represents degree as well, but the color reveals betweenness. We can conclude, that degree and betweenness are correlated, as a decreasing quantity of connected nodes goes hand in hand with a decreasing betweenness (not surprisingly, but due to the image more visual). The Degree sheet down left specifies in- and out-degree values – again we see the network key players 3, 9, 10, 11 but here we can specify their communication patterns. Whereas 3 has the highest out-degree but the smallest in-degree, it’s actor 11 that has the highest in-degree and the smallest out-degree. Dependent on the underlying question, we could draw better conclusions at a glance from this data.

First dashboard trial

Still, there are some open questions regarding Gephi from my last post but I found a nice point of departure from @Edu_k ’s blog post on Gephi Layouts.

Resources

Anderson, T. and Dron, J. (2011). Three Generations of Distance Education Pedagogy,International Review of Research in Open and Distance Learning, Volume 12, Number 3. Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/890/1663

Classroomaid (2014-11-14). Our Learning Analytics are Our Pedagogy, Are They? (#xAPI, #dalmooc), retrieved on 2014/10/23 from http://classroom-aid.com/2014/11/14/our-learning-analytics-are-our-pedagogy-are-they-xapi-dalmooc/

Daniel, J 2012. Making Sense of MOOCs: Musings in a Maze of Myth, Paradox and Possibility.Journal of Interactive Media in Education 2012(3):18, DOI: http://dx.doi.org/10.5334/2012-18

Dawson, S. (2008). A study of the relationship between student social networks and sense of community. Educational Technology & Society, 11(3), 224–238 (full text).

Dawson, S., Tan, J. P. L., & McWilliam, E. (2011). Measuring creative potential: Using social network analysis to monitor a learners’ creative capacity. Australasian Journal of Educational Technology27(6), 924-942 (full text).

Edu_k (2014/11/14). Social capital in SNA for LA – too much focus on individuals at a cost of the group, retrieved on 2014/11/24 from http://nauczanki.wordpress.com/2014/11/14/social-capital-in-sna-for-la-too-much-focus-on-individuals-at-a-cost-of-the-group/

Gašević, D., Dawson, S., Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends (in press),http://www.sfu.ca/~dgasevic/papers_shared/techtrends2015.pdf

Gašević, D., Zouaq, A., Jenzen, R. (2013). Choose your Classmates, your GPA is at Stake!’ The Association of Cross-Class Social Ties and Academic Performance. American Behavioral Scientist, 57(10), 1459-1478. doi: 10.1177/0002764213479362 (full text).

Grunspan, D. Z., Wiggins, B. L., & Goodreau, S. M. (2014). Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research. CBE-Life Sciences Education, 13(2), 167–178. doi:10.1187/cbe.13-08-0162 (full text)

Knight, Simon; Buckingham Shum, Simon and Littleton, Karen (2014). Epistemology, assessment, pedagogy:
where learning meets analytics in the middle space. Journal of Learning Analytics (In press).

Kovanović, V., Joksimović, S., Gašević, D., Hatala, M., “What is the source of social capital? The association between social network position and social presence in communities of inquiry,” In Proceedings of 7thInternational Conference on Educational Data Mining – Workshops, London, UK, 2014 (full text).

Liyanagunawardena, T., Adams, A., & Williams, S. (2013). MOOCs: A systematic study of the published literature 2008-2012. The International Review Of Research In Open And Distance Learning, 14(3), 202-227. Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/1455/2531

Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing pedagogical action: Aligning learning analytics with learning design. American Behavioral Scientist, 57(10), 1439-1459, doi:10.1177/0002764213479367 (full text).

Rodriguez, C. O. (2012). MOOCs and the AI-Stanford like courses: Two successful and distinct course formats for massive open online courses. European Journal of Open, Distance and E-Learning. Retrieved from http://www.eurodl.org/?p=Special&sp=init2&article=516

Suthers, D. D., & Verbert, K. (2013). Learning analytics as a “middle space.” In Proceedings of the Third International Conference on Learning Analytics and Knowledge (pp. 1–4). New York, NY, USA: ACM. doi:10.1145/2460296.2460298

Skrypnyk, O., Joksimović, S. Kovanović, V., Gasevic, D., Dawson, S. (2014). Roles of course facilitators, learners, and technology in the flow of information of a cMOOC. British Journal of Educational Technology(submitted) (full text).