20 January 2017

Using Wikipedia as a MOOC


Your prevailing experience of online education, for better and worse, is currently Google, Wikipedia and Youtube  (Alexa 2017, Me 2008, Head 2010Hrastinski et al 2012). So why do educational institutions spend so much time and resources developing MOOCs, and why do they predominantly do so in iTunesU, FutureLearn, Coursera or similar such way? Hiding teaching away like this makes it difficult for people to learn and to relate what is being taught into their everyday lives? (Caruana 2006Wesch 2007, Me 2016)

Consider this common scenario:
If you need to know something, chances are you'll Google search it. You might get a summary answer right there in the Google search result, or you might take a look at those results in Images, News, Maps, Scholar, Books etc.
Chances are a Wikipedia article was high up in that list of search results too, and you probably clicked into that Wikipedia article to skim read, maybe even another.
Not quite satisfied with the text and image based results so far, you might have committed to watching 2 minutes or so of a Youtube video you thought was relevant.

The outcomes of learning in that 5 minutes were probably as such:

  1. a correction or expansion on the keywords you were using in your research. 
  2. A realisation that the thing you were wanting to know about happens to connect with one or two things you already know a bit about. 
  3. A better idea of what you might be up for if you want to go deeper in your learning of that particular thing. 

The third outcome is of most interest to me. That range of emotions and motivations that people can feel at the end of their five minute inquiry. Did they feel frustrated or daunted? Where they inspired and impressed? Perhaps they were even semi consciously being sucked into a vortex of information, with a feeling of elation at so much at their fingertips.

It's in this third area that I think an opportunity is afforded teachers and educational designers who want to make information as useful and effective to learning as possible. But its equally here that the darker arts of marketeers and hucksters dwell and compete. (Sierra 2007, Me 2010Me again 2011)

You might have seen, in those 5 minutes of microlearning, that the Wikipedia article for the thing you were inquiring on was expansive and hyperlinked in all sorts of directions. You might have noticed that there were a series of videos on Youtube that you thought looked useful. You might have noticed a range of in depth publications listed in the Wikipedia article's references, or in the results on Google Scholar and Books. You might have even noticed links into forums where people who share an interest in the field have been discussing and answering questions for several years now.

But what if, say, back in the Wikipedia article you noticed in the "See Also" section links to courses and other curricula espousing to better guide your learning? Alongside Wikipedia are projects like Wikiversity and Wikibooks for example. If you curiously chose to look at those links, you might've found your topic of interest was included in a range of curricula including courses, study groups, projects and events. On Wikibooks you found a range of textbooks, some of which were being used in the Wikiversity courses that offer teaching around the thing your interested in learning.

But reading and navigating these wikis is labor intensive and tiresome. At the bottom of each of those courses or textbooks you noticed links to websites that brought it all into a nicely presented, up to the minute space. These sites make it apparent that people from a number of educational institutions are involved. You discovered that these people are pooling their resources to produce and maintain these sites, and their work on the wikis is their process space. The websites offer further connection to their Youtube channels, Facebook Groups, Wordpress sites, Wikipedia projects, Twitter handles, hashtags, events and meetups. Most of it was exposed to Google search, many commanding the first results in topical keyword searches - closing the loop on this scenario of access to information and learning.

Unfortunately, I've not come across many examples of this in my line of work. For what appear to be entirely similar motivations (exposure and promotion), educational institutions and their people have instead partnered up with much lessor known online learning initiatives, delivering resources to the competing commercial interests of iTunesU, FutureLearn, Udacity, Coursera, etc. As we realise, none of it enters the above scenario of prevailing online learning.

Here are some examples that almost get there:

Wiki Project Med is an impressive campaign to improve Wikipedia coverage on all medicine related articles in all languages.
the Wikipedia Education Program offers support for people interested in using Wikipedia in their teaching and learning.
The State Library of Queensland uploaded 50000 out-of-copyright images to Wikimedia Commons for people to use in Wikipedia editing and the like.
WikiJournal of Medicine is an impressive initiative establishing a peer reviewed open medical journal on Wikiversity, integrated to Wikipedia. Good to see La Trobe University is involved. I doubt it has anything to do with my efforts.
The History of the Australian Paralympic Movement in Australia was an initiative out of the University of Canberra. It focuses on getting quality images of athletes on Wikimedia Commons, and creating articles on Wikipedia.
Business Politics and Sport is a course at the University of Canberra that became publicly available on Wikiversity in 2010. It set up its own website and asked students to write, review and publish their essays into a sport research journal on Wikiversity as well.
Motivation and Emotion is another course at the University of Canberra, publicly available on Wikiversity. It asks students to write or edit chapters in the course's student written open textbook.
Oral Health is a program at La Trobe University. It asks students to edit Wikipedia articles to demonstrate their critical reasoning.
Investigative Journalism is a course at the University of Wollongong. It asks students to write stories for Wikinews.
Health Informatics - Electronic Health Records is a course at La Trobe University, and in 2013 the coordinator Dennis Wollersheim asked students to collaborate in Wikipedia for their assignment. Dennis offers an exceptional example for how to draw resources together and create a project space inside Wikipedia.


References


Alexa, Top Sites. (2017). Retrieved January 20, 2017, from http://www.alexa.com/topsites
Caruana, R. & Niculescu-mizil, A (2006) An Empirical Comparison of Supervised Learning Algorithms. Retrieved January 20, 2017, from http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.122.5901

Blackall, L. (2008). The Disconnect Between Learning And Education - SlideShare. Retrieved January 20, 2017, from http://www.slideshare.net/leighblackall/the-disconnect-between-learning-and-education-429513

Blackall, L. (2010). A crisis for institutions, opportunities for teachers. Retrieved January 20, 2017, from http://leighblackall.blogspot.com/2010/10/crisis-for-institutions-opportunities.html

Blackall, L. (2011). Lucrative teaching? A quick look at Josh Kaufman's .... Retrieved January 20, 2017, from http://leighblackall.blogspot.com/2011/01/lucrative-teaching-quick-look-at-josh.html

Blackall, L. (2016). Can we teach the machine to teach?. Retrieved January 20, 2017, from http://leighblackall.blogspot.co.nz/2016/06/can-we-teach-machine-to-teach.html

Head, A. & Eisenberg, M. (2010). How today's college students use Wikipedia for course related-research - First Monday. Retrieved January 20, 2017, from http://firstmonday.org/article/view/2830/2476

Hrastinski, S. & Aghaee, N.M (2012). How are campus students using social media to support their studies? An explorative interview study - Springer. Retrieved January 20, 2017, from http://link.springer.com/article/10.1007/s10639-011-9169-5

Wesch, M. (2007). The Machine is Us/ing Us (Final Version) - YouTube. Retrieved January 20, 2017, from https://www.youtube.com/watch?v=NLlGopyXT_g

Sierra, K. (2007). Creating Passionate Users: Marketing should be education, education .... Retrieved January 20, 2017, from http://headrush.typepad.com/creating_passionate_users/2007/02/marketing_shoul.html


25 November 2016

UX Design Methodologies


Some UX Design methods can be helpful in some situations in education, such as when a team of teachers and people supporting them need a shared understanding to coordinate their efforts.

Can the library use UX Design with Subject Guides?


I'm involved in a project with the library her at RMIT, to look at their Subject Guides. Part of that project is to use a range of UX Design methodologies to try and make explicit the range of assumptions, premises, processes, experiences and relatable experiences and outcomes around subject guides.

This post is an annotated list* of a range of methods, mostly borrowed from other research domains, loosely brought together under the banner of UX Design. We have used some of these in the past, primarily in course and curriculum design and development.

Methods

  1. Video ethnography could be used along with remote usability testing, and involves:
    • Observation, including extensive filming of practitioners,
    • Allowing practitioners to view the video recorded material and reflexively discuss their practice,
    • Transforming practice through practitioner led change, and
    • Building the capacity for the ongoing and critical appraisal of practice.
  2. Semi structured interviews are open, allowing new ideas to be brought up during the interview as a result of what the interviewee says. The interviewer generally has a framework of themes to be explored. It is generally beneficial for interviewers to have an interview guide prepared, which is an informal grouping of topics and questions that the interviewer can ask in different ways for different participants. Interview guides help researchers to focus an interview on the topics at hand without constraining them to a particular format. This freedom can help interviewers to tailor their questions to the interview context/situation, and to the people they are interviewing.
  3. Personas represent the goals and behaviour of a hypothesised group of users. In most cases, personas are synthesised from data collected from interviews with users. They are captured in 1–2-page descriptions that include behaviour patterns, goals, skills, attitudes, and the environment, with a few fictional personal details to make the persona a realistic character. We use personas in our course design workshops.
  4. Scenarios describe ways that a system is or is envisaged to be used in the context of activity in a defined time-frame. The time-frame for a scenario could be (for example) a single transaction; a business operation; a day or other period; or the whole operational life of a system. Similarly the scope of a scenario could be (for example) a single system or piece of equipment; an equipped team or department; or an entire organisation.
  5. Information mapping is writing clear and user focused information flows and connections, based on the audience's needs and the purpose of the information. We use a sort of information mapping in course mapping.
  6. Digital prototyping changes the traditional product development cycle from design>build>test>fix to design>analyse>test>build. In this context, we might consider a form of rapid prototyping to illustrate and test radically varied concepts of subject guiding.
  7. Agile software development  is primarily a set of principles for software development (including UX Design) under which requirements and solutions evolve through the collaborative effort of self-organising cross-functional teams. It advocates adaptive planning, evolutionary development, early delivery, and continuous improvement, and it encourages rapid and flexible response to change. We have attempted to use these principles across many of our methods over the past 2 years.
  8. Participatory action research is similar to agile development in that is an approach to research and development. It encompasses methods that are set within groups or communities and emphasises participation and action. It seeks to understand problems or situations by trying to act on them, collaboratively and following reflection. PAR emphasises collective inquiry and experimentation grounded in experience and history. PAR could be deployed within a program of professional development.
  9. Usability testing involves carefully creating a scenario, or realistic situation, wherein the person performs a list of tasks using the product being tested while observers watch and take notes. Several other test instruments such as scripted instructions, paper prototypes, and pre- and post-test questionnaires are also used to gather feedback on the product being tested. For example, to test the attachment function of an e-mail program, a scenario would describe a situation where a person needs to send an e-mail attachment, and ask him or her to undertake this task. The aim is to observe how people function in a realistic manner, so that developers can see problem areas, and what people like.

*Unabashedly drawing from Wikipedia, checked against personal experience.

24 November 2016

Mind mapping networked learning thesis 001

Back to the Open and Networked PhD, Jon Mason emailed me a link to a quite helpful guide to writing a research proposal, by DR Rowland for the University of Queensland.

One of the first suggestions it makes is mind mapping. I've always been reluctant to use mind mapping, given its limited use communicating to others and primary use of internal organisation of thoughts.. but this time I gave it a go.. I'm not sure if it has helped me, perhaps a little, but I still feel a bit perplexed on direction and focus..

11 November 2016

Badges: identify talent and brand by association


In 2015 we used RMIT University’s Graduate Futures Careers Fund to pilot badges as a possible way to improve the employment prospects of graduates from the Advertising Degree. Through iterative action research we developed, tested and reviewed: infrastructural support for badges; teacher, student and practitioner understanding of badge concepts and value and; what appropriate and meaningful implementation of badges might look like in the advertising industry. Despite the difficulties that other Australian educational institutions have found when trying to implement badges, we’ve identified three areas of value for badging in the domains of advertising education and practice specifically:
  1. Badges can highlight an individual’s talent and experience where formal accreditation does not, such as in co and extracurricular activities, work experience and peer relations and esteem
  2. Badges carry a form of ‘brand-by-association’ both for the issuer and the receiver, and that value intersects with notions of online identity management
  3. Badges present opportunities for unique methods of advertising, and these methods are potentially new content to be taught in the advertising program
The technology and infrastructure that presently facilitates badging remains precarious, disjointed and competitive. Institutional, teacher/student and industry/practitioner awareness and understanding of the use and value of badges remains low to nonexistent. The developing fields of ‘big data’, ‘artificial intelligence’, ‘blockchain’ and ‘online identity management’ are likely to displace the current value propositions of badges. More consideration around the notion of brand-by-association and identity management is needed - for example, institution-branded badges can highlight a person’s recent-graduate status, possibly at the expense of their work experience or specific skill sets. This can have a negative impact on employability in the advertising sector, where crude levels of professional ability are still used.

We therefore make the general recommendation that RMIT University not move into badges until an open standard format is reliably and more widely supported; until people can effectively incorporate badges into their identity management; and until wider understanding of the value of badges exists - especially in the idea of brand by association. We instead recommend that a range of niche experiments be conducted, each addressing these initial ideas and areas of concern, but from different discipline perspectives. From these experiments, a stronger understanding can be developed in the institution, and across its relevant industry partners, to help ensure better impact at a university wide implementation.



Link to report on Google docs

02 November 2016

A hackathon: Commons to Wikidata to Open Street Maps

Originally posted on DLDSC.team

Here's what we made:

A map of public art within 500m of the RMIT Campus

After photographing instances of public art around the RMIT Melbourne City campus, uploading them to Wikimedia Commons and creating entries for each instance of public art on Wikidata, we then used Query to visualise the Wikidata entries and discussed next steps into Open Street Maps and more.

Here's the map (link above) embedded below. Click the red dots to reveal content:



Our map uses live, open, user generated, linked Wikidata, including media loaded to Wikimedia Commons, visualised with the Wikidata Query tool. From this foundation we're aiming develop the presentation, exploring various functional and aesthetic dimensions.

Since hearing about the Wikidata project from Andrew Mabbett earlier this year, we've been looking for a time we could spend getting hands on, working with an expert, to quickly learn about creating and using Wikidata. Thanks to Alex Lum joining the Hackathon we hosted in October, we had our Wikidata expert on hand for the two days, generously showing us what he knows.

I wholeheartedly recommend Alex for workshops on anything Wikimedia related, especially Wikidata, as well as Open Street Maps. He is a modest, approachable and very patient teacher with a passion for Commons based open data. For the entire 2 days he patiently taught us everything from how to structure Wikidata through to how to visualise it in Query and Open Street Maps.

We documented our work over the two days in this Google Doc. There you'll find much more detail.

Other projects were proposed for the Hackathon too, but the Wikidata project won the most interest this time. Please refer to the planning and notes document for more information about those proposals.

What next?

First of all, we hope to show this as a proof of concept to the College and the University. We think of it as a potential Student as Producer curriculum project, perhaps in the School of Art most obviously, but any number of other subject areas could consider this.

This map will update as more and more people create Wikidata entries that use the genre property "public art" as well as the coordinate location with a well formed longitude and latitude. To see an example of such a Wikidata entry, click any of the red dots on the above map, and then click the link that begins with "wd..." In that example. The resulting page is a Wikidata entry with a range of property statements.

We will keep building this map, first using it as a professional development activity with our colleagues to inform them on Wikidata, Wikimedia Commons and Open Street Maps. We will spend a few hours walking around Melbourne's CBD photographing instances of public art and uploading to Wikimedia Commons using the Category: Public art in Melbourne, Victoria. We will then create Wikidata entries for each instance we document, making sure to include "genre" and "coordinate locations" to ensure the map grows.

Cathy Leahy is experimenting with more advanced visualisations of the data, and hopefully we can forge a collaboration with people in ICT or students learning programming, and will follow this post with another detailing her perspectives.

More detailed notes and resources

Please refer to the notes made during the hackathon for more details on what we create and what we used to create it.

11 October 2016

Using Youtube to create learning networks

Here's an audio recording of a discussion about this project at the RMIT Learning and Teaching Conference for 2016.



We've been working with teachers and students in the School of Fashion and Textiles, trying to get the most out of Youtube and other social media. This work stems from the Fashion Youtube project.

We've shown teachers and students how to:
  1. set up and manage YouTube channels;
  2. use a smart phone to record effective video;
  3. produce screen recordings;
  4. edit video with YouTube;
  5. add closed captioning;
  6. create and manage Youtube playlists
  7. generate QR codes that link to playlists
  8. understand the networking and machine learning capacity in YouTube.
We've collected our posts about this work here.

Example Youtube Channels

Here's a playlist of video from some of the teachers we have been working with:

https://www.youtube.com/playlist?list=PLuaWh26AwcxAV3nfbE8biM-VX4pLl_efj

Laura Holmes Brown and Travis Hart manage their own Youtube channels for distributing a range of screen recordings they produced for their Computer Aided Design courses.

Sharon Koenig, Julie Wood and Betty Kanzurovski co manage the Fashion Stitched Up Youtube channel, to distribute a large collection of instructional videos to support their Garment Construction courses.

Andrew Robinson manages his own Youtube channel to distribute instructional videos and industry interviews for his courses in Custom Made Footwear. He has also lead the way in modelling how to use Youtube in combination with other websites and social media, to develop an online professional network and web presence for small businesses.

Developing a professional/learning network

The longer term goal with this work is to establish a professional network across the various disciplines of the School of Fashion and Textiles. This network connects teachers, students, industry and public. Here's a series of screengrabs from a network map of what's developed so far in Youtube:



This shows all the people we have worked with to set up Youtube channels, as well as the connections they've made in Youtube since. You can see two major nodes here, Andrew Robinson who teaches footwear, and Digital Learning DSC who support teachers and students with digital learning. Around Andrew you can see lots of two way connection between Andrew, students and industry. The nodes between Andrew's network and DL DSC are the people who 'bridge' both. This accurately reflects the relations that DLDSC people have with Andrew and the School of Fashion and Textiles.

Here's just the teachers and the students

fashion-network-teachers-and-students-october-2016

In this view we are looking only at those labelled "teacher" or "student". You can see Digital Learning DSC's network disappears, leaving the teachers and students who networked around DLDSC disconnected. Andrew's network remains in tact of course, just thinner without the industry connections showing, and revealing very little connection between students. Here we can see more work needs to be done connecting across nodes in a network, decentralising from any one node.

Here's just teachers and industry

fashion-network-teacher-and-industry-october-2016



In this view, we can see a stronger network of teachers connected through DLDSC again, where DLDSC is labelled as "industry". A smaller but not insignificant network remains around Andrew, showing that Andrew is facilitating a connection with industry and other teachers in Youtube.

Here's just the students and industry

fashion-network-students-and-industry-october-2016

And in this view, where teachers are no longer included, just students and industry, we can see that the students in Andrew's network have almost no connection to industry or each other in Youtube. There are just 2 students in this map who share a connection with one industry channel.

This shows us connection and disconnection

The loss of connection in the network when key nodes are removed shows us what we need to start focusing on. We will start activities that cause teachers and students to subscribe to each other's channels, and to explore more industry channels.

We've already shown the sort of impact these sorts of activities have on the associations and recommendations that Youtube then makes to a user, arguably assisting them in their informal and serendipitous learning during and after the course, as well as further online networking.

We will map this network as it exists in Facebook, Instagram, LinkedIn and possibly Pinterest - all of which are commonly used in the fashion industry.

Our hope is that by visualising it like this we will discover more about the network functionality, and inspire others to want to join in.

Teaching Youtube to Teach

This approach to using Youtube to try and establish a School wide learning network is lead by some of our thinking described in Can we teach the machine to teach, where we are keen to find out if there are things we can do – activities we can undertake, that all together improves the usefulness of Youtube to the user – both teacher and learner. We're approaching this by paying attention to the sorts of data that impacts how videos are recommended in Youtube. For example, we’re observing how the titles, descriptions, tags and closed captions of a video or a playlist impact on the sorts of videos that Youtube recommends along side the video being played. We’re finding that these recommendations are made more relevant and useful if care is taken with the titles, descriptions, tags and closed captions - especially the closed captions. Longer term we’re interested to find out what happens when people subscribe and interact with each other's channels. We expect such interaction will have a rapidly useful impact on the sorts of videos and channels that Youtube recommends. Critical to the success of this is that users create channels that separate away their professional use from their everyday personal use. This way, we can keep the usage data focused on particular interest areas, and train Youtube to make recommendations that take us deeper into that interest area and connect us with other users. This same practice works for Facebook, Instagram, Pinterest and other socially networked media.

29 July 2016

Learning analytics, even student dashboards, are they the wrong way round?


In a recent session discussing a learning analytics project, I seemed to be the only person in the room who was anxious about the whole idea again. I've been this way ever since George Siemens started the Google Group some 10 years ago. That anxiety culminated in a presentation I made to the University Analytics forum in Melbourne in 2012, which I'm sad to say, along with my posts to the forum, has generated little to no response. Is it just me and my tin foil hat, or is there a general reluctance to talk about an elephant in the room with learning analytics?


The best I've seen from the over all movement is a general agreement that it is ethical and progressive to develop analytics as a "student dashboard", that is to say that the effort is first and foremost about collecting data so that the individuals that the data is about can see and reflect on their own patterns, and in relation to the demographic groups that seem relevant to them, presently and historically. The antithesis of this is the collection of data for teachers and administrators to roughly calibrate their behaviouralist experiments - what most learning analytics projects are about.

But in this session recently, it occurred to me that even the projects that describe themselves as "student dashboard" projects, seem to be allowing themselves to be drawn a very long way away from the principles of why they are developing that way. Most of these projects that I have seen seem frustrated by the difficulty of obtaining useful data, and end up narrowing scope in on a single environment like an LMS or a handful of online social platforms, within a single course. They accept that this then renders the project an unscalable proof of concept, and acknowledge that they leave far too much out of a person's wider context to really get any useful insights. Is there another way to try and uncover insights about learning? A way that better fits the principle of student dashboard, and potentially encompasses that wider context that seems impossible to account for?

I'm suggesting a closer affiliation with the field of QuantifiedSelf. Who in the learning analytics world is investigating the large range of mobile applications designed to assist with time management and task completion, for example? It could be that one of these, or a combination of them, offer students an optional way to record and manage their own data, and to even pool in with an online community or collection for comparison and bigger pictures. This seems to be an approach that would inherently deal with many of the ethical concerns of a university gathering data on students - often without even a research ethics application!

It seems to me that this suggestion is to at least qualify the data currently being collected in the more top down approaches, if not control for it. But I suspect it's more than that. With the right additions, the voluntary and guided use of such apps and methods might be the very idea that "student dashboard" projects set out to achieve. The outcomes of projects that take this approach might be a range of suggested apps and guided activities to help participants make the most of logging their lives around learning; how to pool data for comparisons; and how to better design course curriculum to help students manage time and task completion.

A search for "time management" in Google Play reveals quite a few useful candidates to try out, many with data export ability. Learning designers could design weekly time management schedules around a course for example, for participants to run in something like TimeTune to stay on task. We could suggest that participants try using an application like Working Time Management, that tracks the time spent on projects, including communications with people in the project, similar with aTimeLogger, and simple activities where the group compares records. These are just the first few apps available in a search for Time Management.

I've recently started using the application Headspace, a charming application which isn't a life logger at all, though it has some optional features that could be used like that. It's primarily a 10 step course in meditation and mindfulness. It's pretty popular it seems, and interesting as a format for a course. The various tools and techniques for managing time, focus and headspace could conceivably be combined into one, as layers around a course on any topic, where students (if they like) can turn off and on those features, some of which offer guidance in time management, others an opportunity to measure, manage and compare their engagement with topics and projects.

Does anyone know of a learning analytics project that takes this approach? Such an approach would alleviate some of my anxieties about the field and its elephants, especially if they were to dgo as far as to investigate the source of the applications and determine what the companies do with the data collected.