#PhD: importance of personalisation in #qualitative research

Although I know and understand the concept of trust in online communities, up until yesterday I underestimated the effect of being among participants to allow them to connect.

In my current main study, I am investigating online learning as it is done by experienced online learners. I look at how they learn inside of the course. I ask them to fill in and share learning logs to get an idea of their informal learning as well. The learning logs also try to capture who learners talk to, or reach out to, either to find additional answers, or simply to share learning experiences. And as the first learning logs are coming in, I read them with the utmost interest and enthusiasm. The learning logs capture the learning in self-reported descriptions coming from participants taking part in three different FutureLearn courses. Although my research is qualitative, I was not fully part of the courses, not as much as I wanted to at first. But then the importance of personalisation kicked in and now I adjusted my way of research a bit.

Increasing personalisation
The first steps I took to increase a personalized approach for each of the research participants was:

• building different documents, research instruments and communications for each course. Practically this means 14 different communications, 7 different research instruments, 6 different reference documents. Not taken into account the small adaptations I made to the documents (e.g. for those participants joining the research later on in the course, requiring a different research timing).
• ensure each document, communication, or research instrument was written in a personalized way (this is not always easy, but it turned out to be definitely worthwhile)
• providing a course recognizable unique identifier for each participant, creating a visible link between a number  and the course (the unique identifier is a number used to anonymise participant data)
• address each participant with the first name they provided in the informed consent. This I do for each communication going out from me to them.
• add the unique identifier to each outgoing communication, making sure it is connected to that participant

As you can imagine, all the above measures increase the mistakes that can be made. I have been mailing about 900 communications at this point in time, all personalized - or trying to. And indeed I have been making mistakes (e.g. forgetting attachments, referring to wrong online links that are actually from other courses under investigation). Rectifying these mistakes is necessary of course, but it means sometimes participants get multiple mails, which is tough on their time schedules.

How far can you go with personalisation?
Though the learning logs are coming in, I kept feeling I was not reaching out to my research participants in a way that I could reach out to them. I felt I was missing a step. As such I strolled through the three courses of which I had participants. After having taken a look at the courses, I took another look at my research instruments (the provided learning logs in particular). Then I realized that my instruments were not personal enough. Not personal as referencing to the participants, but personal in connection with the FutureLearn courses to which the learning logs were referring too. I suddenly realized I could make them fit each course more carefully, hence making them more meaningful, more trustworthy (or that was what I was thinking).

So I went back to the drawing board, and before the last of the three FutureLearn courses started, I made sure that I personalized some of the research instruments (mainly the learning log) to make it more recognisable to the participants of that specific course. This was really necessary, as the third FutureLearn course (Basic Science: Understanding Experiments), was a hands-on course, while the other two courses I am investigating were more classic study courses (no hands-on experimenting, just understanding): one on Decision making in a complex and uncertain world, and one on the Science of Medicines.

More time, better realisations, becoming more involved

While having adjusted the documents and instruments, and beginning to get more familiar with the communications that need to go out, I was beginning to breath again. Gaining time once again. So, I had a look at the courses once again. 

This is where I realized I had not engaged with the courses the way I intended. Granted, for the course on Science of Medicines, I had planned to follow the course week on Diabetes only, as I have diabetes type 1 and I feel that all knowledge can help by keeping in tune with my illness. 

The 

So I started to engage with the courses, and suddenly I realized that this extra layer of engagement provided me with a triple return! 

• First of all I participated in the same courses as my participants, I could understand some of their remarks in more detail. 
• Second I connected with some participants, hence becoming more of a 'real' person to them. Not the distant researcher, but the human sharing experiences.
• Thirdly I learned the content of the courses, and got motivated to learn more. 

Wondering what the limit is of this type of personalization?

Did this result in an extra return for my research? 

It seems so, as people seem to respond more on my requests to share their experiences. So now I have a potential paper taking shape in my mind on the importance of being their as a researcher, also for online phenomenological research (which is what I am doing), and pointing towards possible effects of being part of the learning environment in a non-formal role, simply as a participant but for no other reason then simply taking part in the course. A bit of ethnographic research presence, but with less impact on the proceedings in the learning environment. 

Well, just sharing so I can remember once I write my thesis. Research is such a learning journey!

Whistly Bird? Flappy bird with a whistle, procrastination

A friend of mine told me about his gaming project a couple of weeks ago. He was all excited, and almost could not wait for his game to be full proof in order to shout it out from the rooftops: Whistly Bird!!!! So I told him, just give me a hands-up when you finish testing it, and I will gladly try it out.

And finally he let me know - proud as a peacock - yesterday evening. And indeed it is fun (read: solid procrastination!). So I gladly send it out to the world, as that is what friends do, and the more we procrastinate, the more peace we all have :-)

Whistly bird is build around the concept of Flappy Bird, but with an audio twist. You need to whistle to direct the bird in between the pipes.

The game information and download options can be found here at OceanshipGames.

So find your microphone set, get a glass of water (to use in between whistles ... I needed it) and get whistling. As a bonus: it practices the mouth movements, so it must have a linguistic or speech specialist benefit as well. But I must confess I found it hard, and I wished it had an adjusted speed for whistling responses. I simply do not seem to have a steady whistle in me (yet).

The short trailer gives the idea behind the game.

#PhD qualitative versus quantitative #research: trials and tribulations

Why did not I simply stick to quantitative data, the beauty of numbers in simple, straight forward formulas ?!! That scream of despair kept me awake at night for weeks. Weeks filled with hopes and doubts on getting enough data for my PhD study, eagerly looking at mails and learning logs.

Up close and personal
Qualitative research brings along much more discussions with all stakeholders, for everyone needs to be willing to share. Due to the fickle nature of language, everyone also needs to understand what is meant by the researcher when ideas are investigated. A difficult endeavour.
Quantitative research is like watching ants. You track the colony, and you get a fairly good idea of what they are doing. In a way this is what happens with learning analytics or Big Data derived from watching humans as well. You get the facts of the human colony when studying learning analytics or quantitative research, but you do not get it’s spirit, it’s drive or reasons why.
I want to know more. I want to get into the minds of people, into the minds of online learners, and understand why they are doing what they are doing, and how they do it. But this means I need to get into a conversation with them. And as we all know not everyone wants to start a conversation with just anyone.

Finding what no wo/man has found before
The setting of my research is simple enough: finding out how experience online learners learn. To see whether the assumption of us ‘grand experienced learners’ is indeed filled with online connections (personal learning network), finding what no wo/man has found before (surfing the Web), and sharing (blogging our learned reflections, ideas and thoughts). But my chosen approach could not be anything else but qualitative. It had to be laboriously gathering written data from good, willing research volunteers who’s lives are already cramped with time staking demands. Why? Because there are no quantitative holistic tools available that will capture all learning (formal and informal), and offer insights into why these data emerge.

No holistic research tools, due to no learning blueprint
The research tools of today do not (yet) permit me to simply trace or track what a learner does while studying an online course. The course related resources can be tracked of course, but there is so much more that some of us do: connect with others (partners, face-to-face colleagues) to find solutions related to the course, gather extra information connected to the content of the course as well as our own contexts for the topic. Granted, xAPI provides some self-reported informal learning diaries. Twitter and blogs offer idea and diary options so personal learning reflections can be shared. But there is no holistic learning tool available yet. This is due to the fact that at this point we can only assume how people learn in such online environments (especially regarding informal/formal learning actions). So as long as we do not know what learners actually do to get to a full understanding of an online course in relation to their personal learning needs, no tool will grasp all that is needed. This of course provides a solid rationale for my research: getting a blueprint of how people learn in an online teaching environment.

Time is of the essence
Which brings me back to the tension between qualitative versus quantitative research. Up until now, and for this type of exploratory research the qualitative research options seem to be the best option to get an idea of how experienced online learners learn.
However, I do get the impression that all of us are losing out on time. Our time is under pressure. We work, have hobbies, care for our families, … and now with MOOCs rising, we learn as part of our lifelong learning or leisure learning realities. And this is where my research comes in, with yet another demand on precious time of learners that simply want to get on with life. This lack of time, manifests itself in people willing to engage in research, but finding they simply cannot do it (if they want to stay sane and on top of their lives). Some volunteers get slightly cross due to questions that they find irrelevant, others interpret the words I write in a different way than they were intended… and all of them have a point, as language is fluid, as is any meaning making. So, as a researcher I listen and try to find adaptations that can make life easier for my willing research volunteers. This is not always an easy task, but I owe it to them to try and make it work, or to make participation in my research easier.

Big Data or Big Emotions?
So now, with questions and discussions rising (on questions and instruments used), inevitably emotions come into the research and into the hearts of all volunteers. Inevitably people discuss ideas, have an opinion on what is asked and they feel positively or negatively inclined towards what is asked from them.
Sometimes this gets to me. I really want people to get a positive feeling from sharing their experiences, and in turn use their experience to provide guidelines to new learners, as well as insights to course facilitators and teachers. That way we all grow, and – hopefully – make learning a more intuitive, natural act. The way it is supposed to be.

Luckily most volunteers know this, they put their efforts in, knowing it will help others. And I am deeply indebted to all of them. The data keep pouring in … I am grateful.

(Another great cartoon by Nick D Kim: http://www.lab-initio.com/)

presentation on eLearning and #mobile influences for #ICT4D

Sharing a presentation I gave for the Deutsche Welle Akademie in Bonn, Germany. It was a wonderful talk thanks to all the input and questions the attendees shared, and the wonderful facilitation provided by Holger Hank and his team.

The questions were multiple, and gladly sharing those that are posed frequently.
One of the reoccurring challenges in every type of online learning (elearning, mooc, mobile...) is:

• motivating learners to take and keep up with the training (possible answers: use an 'earn as you learn' approach where you provide extra incentives for those who participate, only develop learning that answers a real need indicated by the trainees, build a learning community, enable offline or at least asynchronous learning - synchronous can demotivate for those learners living in unstable connected regions)
• how to attract your intended learner audience: that is difficult an in many cases (as Holger mentioned) also the case with MOOCs, attracting the right learners is part of providing a very clear course description, sharing the learning outcomes and the prior knowledge needed. The more specific the course description is, the higher the success rate for attracting the right learner profiles. And of course let your own network promote your course, they know who you are, they know your excellence. 
• the connected learner as superlearner: is it a myth or a reality? This is of course a difficult assumption to test, but there is a very natural way in which most of us connect to like minded, or professionally interested colleagues (connecting through old school face-to-face meet-ups). This natural flair to connect (if you are such a type of person) is reflected in the virtual environment as well. But this does not mean that the 'best learner' is indeed a networked, connected learner. It could well be that you only need to have very specific connections (limited) or even that you can be really good without having connections, but ... that remains to be proven (and yes, I intend to proof it with some of my research).  And when you live in a developing region, it can be quite tough to be a fully connected learner as well (infrastructure, life and reality), which would mean an additional digital dividing factor turns up. For me, the connected learner is a good thing to be, but then I do have specific personal traits that would set me up with favorable inclinations towards being virtually connected to attain my knowledge goals. Big Five personality traits makes up good reading for this. 
• what is a good way to plan and test new online or mobile trainings? Planning means: working on a need before anything else, get all stakeholders around the table (participation and knowing what everyone REALLY wants), define the learning goals and learning outcomes needed with everyone, involve strong, experienced instructional designers that know with which learner/teacher dynamics these learning outcomes can be reached (and still be creative and engaging), and test it in a similar, yet safe environment (e.g. in a flipped classroom approach prior to a workshop moment, enabling you to test what you have by people you know, and get feedback in real life enabling to see their expression as they give feedback). 

These were my shared slides:

Presentation eLearning and ICT4D changing realities and challenges from Inge Ignatia de Waard