Why writing 50,000 words doesn’t matter as much as writing one.
Posted: October 26, 2015 Filed under: Education, Opinion | Tags: blogging, community, education, educational research, goals, higher education, NaNoWriMo, thinking, tools, workload, writing 3 CommentsHave you heard of NaNoWriMo? National Novel Writing Month has been around since 1999 and is now far more widespread than national boundaries and has become relatively large, with 325,142 participants on six continents in 2014. The idea is simple: over the 30 days of November, you write 50,000 words that are (notionally) all directed towards a fictional novel.
I’ve taken part twice in the past and produced two … rapidly written works of fiction. I have never claimed to be a good writer, I’m certainly not a published writer, but I can put a number of words down on the page in a day. They even make sense, most of the time, and I’ve ended up with stories that real people have actually read and enjoyed!
I like NaNoWriMo. I like it as a concept, because it demystifies the concept of writing that many words by saying “Hey! Don’t get caught up on perfect prose, just start by writing.” I like the community because, despite the large number of people who show up and have no intention of doing it, there are enough like minds to give you support when you need it. I like it personally, as it’s a great way to get down a long draft of a work, even if you don’t do anything else with it. It’s a bit of external structure (and scaffolding) for those of us who aren’t professional authors.
Being me, of course, I’m all about seeing if we can get people doing something that they didn’t think possible, so I look at NaNoWriMo as a success for anyone who writes one more word than they otherwise would have in November. Sure, getting down a whole novel would be awesome but any steps forward are good steps.
We could talk a lot about how this kind of constrained activity can work in a creative setting but, if you know my work, you’ll have a fairly good idea that I think that everyone taking part should have “enjoyment” as their primary goal, with a possible outcome of their first long-form work as a happy side-effect. 50K shouldn’t be a burden but a guide. 1,700 words a day can be more manageable than many people think and, at the end of November, you may have done something you never thought possible.
Whatever happens, you’ll be thinking creatively and that, in my book, is always awesome. “Almighty creativity”, as the late Bob Ross might say.
I’ll be doing NaNo again this year and, if you’re thinking about it, check out the web site or my shortish guide to speed writing (AntifreezePub) that I’ve written based on my own experiences over the years. As always, if you think there should be a better speed writing guide, feel free to write it/find it and link to it in the comments!
I decided to have an outrageous book cover to inspire me and get me into the right mood. (Currently a working copy with placeholder artwork, as I have no idea what will make it into the final draft.)
Almost all of us benefit from writing practice and this is an interesting way to get a lot of practice in a short time. If you do it, have fun, and feel free to buddy up with me under the username jnick.
Nice one, Deloitte
Posted: October 12, 2015 Filed under: Education | Tags: advocacy, community, education, educational research, equality, equity, higher education, resources, thinking 3 CommentsGiven how much research there is to tell us that intrinsic bias is having a terrifying effect on hiring decisions and opportunity, it’s great to have some good news to report when a company decides to address the issue.
Deloitte U.K are going to start using a school-blind approach in its hiring process (WaPo link), which will potentially benefit thousands of school- and college-leavers who would have been perceived to come from “less suitable” educational pedigrees. They are also planning to work out how students performed relative to their peers in a given school, rather than against broad district or national levels. Deloitte are now part of a growing group of companies who have moved beyond “Am I getting the best people” to understanding that their biassed perception of best may be preventing them from seeing some candidates at all. They could be picking their “best” from a much broader range of better, if only they’d address those biases.
This is certainly not going to end bias overnight (there are so many other issues to address) but it’s a great start.
Updated previous post: @WalidahImarisha #worldcon #sasquan
Posted: August 24, 2015 Filed under: Education, Opinion | Tags: advocacy, authenticity, blogging, collaboration, community, curriculum, design, education, educational research, equity, fantasy, higher education, research, sasquan, science fiction, worldcon Leave a commentWalidah Imarisha very generously continued the discussion of my last piece with me on Twitter and I have updated that piece to include her thoughts and to provide vital additional discussion. As always, don’t read me talking about things when you can read the words of the people who are out there fixing, changing the narrative, fighting and winning.
Thank you, Walidah!
The Only Way Forward is With No Names @iamajanibrown @WalidahImarisha #afrofuturism #worldcon #sasquan
Posted: August 23, 2015 Filed under: Education | Tags: advocacy, AfroFuturism, Anonymous review, authenticity, blogging, collaboration, community, curriculum, design, education, educational research, equity, fantasy, higher education, research, sasquan, science fiction, SF&F, worldcon 5 CommentsEdit: Walidah Imarisha and I had a discussion in Twitter after I released this piece and I wanted to add her thoughts and part of our discussion. I’ve added it to the end so that you’ll have context but I mention it here because her thoughts are the ones that you must read before you leave this piece. Never listen to me when you can be listening to the people who are living this and fighting it.
I’m currently at the World Science Fiction Convention in Spokane, Washington state. As always, my focus is education and (no surprise to long term readers) equity. I’ve had the opportunity to attend some amazing panels. One was on the experience of women in art, publishing and game production of female characters for video gaming. Others were discussing issues such as non-white presence in fiction (#AfroFuturism with Professor Ajani Brown) and a long discussion of the changes between the Marvel Universe in film and comic form, as well as how we can use Science Fiction & Fantasy in the classroom to address social issues without having to directly engage the (often depressing) news sources. Both the latter panels were excellent and, in the Marvel one, Tom Smith, Annalee Flower Horne, Cassandra Rose Clarke, and Professor Brown, there was a lot of discussion of both the new Afro-American characters in movies and TV (Deathlok, Storm and Falcon) as well as how much they had changed from the comics.
I’m going to discuss what I saw and lead towards my point: that all assessment of work for its publishing potential should, where it is possible and sensible, be carried out blind, without knowledge of who wrote it.
I’ve written on this before, both here (where I argue that current publishing may not be doing what we want for the long term benefit of the community and the publishers themselves) and here, where we identify that systematic biases against people who are not western men is rampant and apparently almost inescapable as long as we can see a female name. Very recently, this Jezebel article identified that changing the author’s name on a manuscript, from female to male, not only included response rate and reduced time waiting, it changed the type of feedback given. The woman’s characters were “feisty”, the man’s weren’t. Same characters. It doesn’t matter if you think you’re being sexist or not, it doesn’t even matter (from the PNAS study in the second link) if you’re a man or a woman, the presence of a female name changes the level of respect attached to a work and also the level of reward/appreciation offered an assessment process. There are similar works that clearly identify that this problem is even worse for People of Colour. (Look up Intersectionality if you don’t know what I’m talking about.) I’m not saying that all of these people are trying to discriminate but the evidence we have says that social conditioning that leads to sexism is powerful and dominating.
Now let’s get back to the panels. The first panel “Female Characters in Video Games” with Andrea Stewart, Maurine Starkey, Annalee Flower Horne, Lauren Roy and Tanglwyst de Holloway. While discussing the growing market for female characters, the panel identified the ongoing problems and discrimination against women in the industry. 22% of professionals in the field are women, which sounds awful until you realise that this figure was 11% in 2009. However, Maurine had had her artwork recognised as being “great” when someone thought her work was a mans and “oh, drawn like a woman” when the true owner was revealed. And this is someone being explicit. The message of the panel was very positive: things were getting better. However, it was obvious that knowing someone was a woman changed how people valued their work or even how their activities were described. “Casual gaming” is often a term that describes what women do; if women take up a gaming platform (and they are a huge portion of the market) then it often gets labelled “casual gaming”.
So, point 1, assessing work at a professional level is apparently hard to do objectively when we know the gender of people. Moving on.
The first panel on Friday dealt with AfroFuturism, which looks at the long-standing philosophical and artistic expression of alternative realities relating to people of African Descent. This can be traced to the Egyptian origins of mystic and astrological architecture and religions, through tribal dances and mask ceremonies of other parts of Africa, to the P.Funk mothership and science-fiction works published in the middle of vinyl albums. There are strong notions of carving out or refining identity in order to break oppressive narratives and re-establish agency. AfroFuturism looks into creating new futures and narratives, also allowing for reinvention to escape the past, which is a powerful tool for liberation. People can be put into boxes and they want to break out to liberate themselves and, too often, if we know that someone can be put into a box then we have a nasty tendency (implicit cognitive bias) to jam them back in. No wonder, AfroFuturism is seen as a powerful force because it is an assault on the whole mean, racist narrative that does things like call groups of white people “protesters” or “concerned citizens”, and groups of black people “rioters”.
(If you follow me on Twitter, you’ve seen a fair bit of this. If you’re not following me on Twitter, @nickfalkner is the way to go.)
So point 2, if we know someone’s race, then we are more likely to enforce a narrative that is stereotypical and oppressive when we are outside of their culture. Writers inside the culture can write to liberate and to redefine identity and this probably means we need to see more of this.
I want to focus on the final panel, “Saving the World through Science Fiction: SF in the Classroom”, with Ben Cartwright, Ajani Brown (again!), Walidah Imarisha and Charlotte Lewis Brown. There are many issues facing our students on a day-to-day basis and it can be very hard to engage with some of them because it is confronting to have to address your own biases when you talk about the real world. But you can talk about racism with aliens, xenophobia with a planetary invasion, the horrors of war with apocalyptic fiction… and it’s not the nightly news. People can confront their biases without confronting them. That’s a very powerful technique for changing the world. It’s awesome.
Point 3, then, is that narratives are important and, with careful framing, we can discuss very complicated things and get away from the sheer weight of biases and reframe a discussion to talk about difficult things, without having to resort to violence or conflict. This reinforces Point 2, that we need more stories from other viewpoints to allow us to think about important issues.
We are a narrative and a mythic species: storytelling allows us to explain our universe. Storytelling defines our universe, whether it’s religion, notions of family or sense of state.
What I take from all of these panels is that many of the stories that we want to be reading, that are necessary for the healing and strengthening of our society, should be coming from groups who are traditionally not proportionally represented: women, People of Colour, Women of Colour, basically anyone who isn’t recognised as a white man in the Western Tradition. This isn’t to say that everything has to be one form but, instead, that we should be putting systems in place to get the best stories from as wide a range as possible, in order to let SF&F educate, change and grow the world. This doesn’t even touch on the Matthew Effect, where we are more likely to positively value a work if we have an existing positive relationship with the author, even if said work is not actually very good.
And this is why, with all of the evidence we have with cognitive biases changing the way people think about work based on the name, that the most likely approach to improve the range of stories that we will end up publishing is to judge as many works as we can without knowing who wrote it. If we wanted to take it further, we could even ask people to briefly explain why they did or didn’t like it. The comments on the Jezebel author’s book make it clear that, with those comments, we can clearly identify a bias in play. “It’s not for us” and things like that are not sufficiently transparent for us to see if the system is working. (Apologies to the hard-working editors out there, I know this is a big demand. Anonymity is a great start. 🙂 )
Now some books/works, you have to know who wrote it; my textbook, for example, depends upon my academic credentials and my published work, hence my identify is a part of the validity of academic work. But, for short fiction, for books? Perhaps it’s time to look at all of the evidence and to look at all of the efforts to widen the range of voices we hear and consider a commitment to anonymous review so that SF&F will be a powerful force for thought and change in the decades to come.
Thank you to all of the amazing panellists. You made everyone think and sent out powerful and positive messages. Thank you, so much!
Edit: As mentioned above, Walidah and I had a discussion that extended from this on Twitter. Walidah’s point was about changing the system so that we no longer have to hide identity to eliminate bias and I totally agree with this. Our goal has to be to create a space where bias no longer exists, where the assumption that the hierarchical dominance is white, cis, straight and male is no longer the default. Also, while SF&F is a great tool, it does not replace having the necessary and actual conversations about oppression. Our goal should never be to erase people of colour and replace it with aliens and dwarves just because white people don’t want to talk about race. While narrative engineering can work, many people do not transfer the knowledge from analogy to reality and this is why these authentic discussions of real situations must also exist. When we sit purely in analog, we risk reinforcing inequality if we don’t tie it back down to Earth.
I am still trying to attack a biased system to widen the narrative to allow more space for other voices but, as Walidah notes, this is catering to the privileged, rather than empowering the oppressed to speak their stories. And, of course, talking about oppression leads those on top of the hierarchy to assume you are oppressed. Walidah mentioned Katherine Burdekin & Swastika Nights as part of this. Our goal must be to remove bias. What I spoke about above is one way but it is very much born of the privileged and we cannot lose sight of the necessity of empowerment and a constant commitment to ensuring the visibility of other voices and hearing the stories of the oppressed from them, not passed through white academics like me.
Seriously, if you can read me OR someone else who has a more authentic connection? Please read that someone else.
Walidah’s recent work includes, with adrienne maree brown, editing the book of 20 short stories I have winging its way to me as we speak, “Octavia’s Brood: Science Fiction Stories from Social Justice Movements” and I am so grateful that she took the time to respond to this post and help me (I hope) to make it stronger.
Musings of an Amateur Mythographer I: Islands of Certainty in a Sea of Confusion
Posted: June 23, 2015 Filed under: Education, Opinion | Tags: advocacy, authenticity, blogging, Claude Lévi-Strauss, design, education, educational problem, educational research, evidence, higher education, Karl Popper, Lévi-Strauss, learning, moocs, myth, mythographer, reflection, resources, scientific thinking, teaching, teaching approaches, thinking, tools Leave a commentI’ve been doing a lot of reading recently on the classification of knowledge, the development of scientific thinking, the ways different cultures approach learning, and the relationship between myths and science. Now, some of you are probably wondering why I can’t watch “Agents of S.H.I.E.L.D.” like a normal person but others of you have already started to shift uneasily because I’ve talked about a relationship between myths and science, as if we do not consider science to be the natural successor to preceding myths. Well, let me go further. I’m about to start drawing on thinking on myths and science and even how the myths that teach us about the importance of evidence, the foundation of science, but for their own purposes.
Why?
Because much of what we face as opposition in educational research are pre-existing stereotypes and misconceptions that people employ, where there’s a lack of (and sometimes in the face of) evidence. Yet this collection of beliefs is powerful because it prevents people from adopting verified and validated approaches to learning and teaching. What can we call these? Are these myths? What do I even mean by that term?
It’s important to realise that the use of the term myth has evolved from earlier, rather condescending, classifications of any culture’s pre-scientific thinking as being dismissively primitive and unworthy of contemporary thought. This is a rich topic by itself but let me refer to Claude Lévi-Strauss and his identification of myth as being a form of thinking and classification, rather than simple story-telling, and thus proto-scientific, rather than anti-scientific. I note that I have done the study of mythology a grave disservice with such an abbreviated telling. Further reading here to understand precisely what Lévi-Strauss was refuting could involve Tylor, Malinowski, and Lévy-Bruhl. This includes rejecting a knee-jerk classification of a less scientifically advanced people as being emotional and practical, rather than (even being capable of) being intellectual. By moving myth forms to an intellectual footing, Lévi-Strauss allows a non-pejorative assessment of the potential value of myth forms.
In many situations, we consider myth and folklore as the same thing, from a Western post-Enlightenment viewpoint, only accepting those elements that we can validate. Thus, we choose not to believe that Olympus holds the Greek Pantheon as we cannot locate the Gods reliably, but the pre-scientific chewing of willow bark to relieve pain was validated once we constructed aspirin (and willow bark tea). It’s worth noting that the early location of willow bark as part of its scientific ‘discovery’ was inspired by an (effectively random) approach called the doctrine of signatures, which assumed that the cause and the cure of diseases would be located near each other. The folkloric doctrine of signatures led the explorers to a plant that tasted like another one but had a different use.
Myth, folklore and science, dancing uneasily together. Does this mean that what we choose to call myth now may or may not be myth in the future? We know that when to use it, to recommend it, in our endorsed and academic context is usually to require it to become science. But what is science?
Karl Popper’s (heavily summarised) view is that we have a set of hypotheses that we test to destruction and this is the foundation of our contemporary view of science. If the evidence we have doesn’t fit the hypothesis then we must reject the hypothesis. When we have enough evidence, and enough hypotheses, we have a supported theory. However, this has a natural knock-on effect in that we cannot actually prove anything, we just have enough evidence to support the hypothesis. Kuhn (again, heavily summarised) has a model of “normal science” where there is a large amount of science as in Popper’s model, incrementing a body of existing work, but there are times when this continuity gives way to a revolutionary change. At these times, we see an accumulation of contradictory evidence that illustrates that it’s time to think very differently about the world. Ultimately, we discover the need for a new coherency, where we need new exemplars to make the world make sense. (And, yes, there’s still a lot of controversy over this.)
Let me attempt to bring this all together, finally. We, as humans, live in a world full of information and some of it, even in our post-scientific world, we incorporate into our lives without evidence and some we need evidence to accept. Do you want some evidence that we live our lives without, or even in spite of, evidence? The median length for a marriage in the United States is 11 years and 40-50% of marriages will end in divorce yet many still swear ‘until death do us part’ or ‘all of my days’. But the myth of ‘marriage forever’ is still powerful. People have children, move, buy houses and totally change their lives based on this myth. The actions that people take here will have a significant impact on the world around them and yet it seems at odd with the evidence. (Such examples are not uncommon and, in a post-scientific revolution world, must force us to consider earlier suggestions that myth-based societies move seamlessly to a science-based intellectual utopia. This is why Lévi-Strauss is interesting to read. Our evidence is that our evidence is not sufficient evidence, so we must seek to better understand ourselves.) Even those components of our shared history and knowledge that are constructed to be based on faith, such as religion, understand how important evidence is to us. Let me give an example.
In the fourth book of the New Testament of the Christian Bible, the Gospel of John, we find the story of the Resurrection of Lazarus. Lazarus is sick and Jesus Christ waits until he dies to go to where he is buried and raise him. Jesus deliberately delays because the glory to the Christian God will be far greater and more will believe, if Lazarus is raised from the dead, rather than just healed from illness. Ultimately, and I do not speak for any religious figure or God here, anyone can get better from an illness but to be raised from the dead (currently) requires a miracle. Evidence, even in a book written for the faithful and to build faith, is important to humans.
We also know that there is a very large amount of knowledge that is accepted as being supported by evidence but the evidence is really anecdotal, based on bias and stereotype, and can even be distorted through repetition. This is the sea of confusion that we all live in. The scientific method (Popper) is one way that we can try to find firm ground to stand on but, if Kuhn is to be believed, there is the risk that one day we stand on the islands and realise that the truth was the sea all along. Even with Popper, we risk standing on solid ground that turns out to be meringue. How many of these changes can one human endure and still be malleable and welcoming in the face of further change?
Our problem with myth is when it forces us to reject something that we can demonstrate to be both valuable and scientifically valid because, right now, the world that we live in is constructed on scientific foundations and coherence is maintained by adding to those foundations. Personally, I don’t believe that myth and science have to be at odds (many disagree with me, including Richard Dawkins of course), and that this is an acceptable view as they are already co-existing in ways that actively shape society, for both good and ill.
Recently I made a comment on MOOCs that contradicted something someone said and I was (quite rightly) asked to provide evidence to support my assertions. That is the post before this one and what you will notice is that I do not have a great deal of what we would usually call evidence: no double-blind tests, no large-n trials with well-formed datasets. I had some early evidence of benefit, mostly qualitative and relatively soft, but, and this is important to me, what I didn’t have was evidence of harm. There are many myths around MOOCs and education in general. Some of them fall into the realm of harmful myths, those that cause people to reject good approaches to adhere to old and destructive practices. Some of them are harmful because they cause us to reject approaches that might work because we cannot find the evidence we need.
I am unsurprised that so many people adhere to folk pedagogy, given the vast amounts of information out there and the natural resistance to rejecting something that you think works, especially when someone sails in and tells you’ve been wrong for years. The fact that we are still discussing the nature of myth and science gives insight into how complicated this issue is.
I think that the path I’m on could most reasonably be called that of the mythographer, but the cataloguing of the edges of myth and the intersections of science is not in order to condemn one or the other but to find out what the truth is to the best of our knowledge. I think that understanding why people believe what they believe allows us to understand what they will need in order to believe something that is actually, well, true. There are many articles written on this, on the difficulty of replacing one piece of learning with another and the dangers of repetition in reinforcing previously-held beliefs, but there is hope in that we can construct new elements to replace old information if we are careful and we understand how people think.
We need to understand the delicate relationships between myth, folklore and science, our history as separate and joined peoples, if only to understand when we have achieved new forms of knowing. But we also need to be more upfront about when we believe we have moved on, including actively identifying areas that we have labelled as “in need of much more evidence” (such as learning styles, for example) to assist people in doing valuable work if they wish to pursue research.
I’ll go further. If we have areas where we cannot easily gain evidence, yet we have competing myths in that space, what should we do? How do we choose the best approach to achieve the most effective educational outcomes? I’ll let everyone argue in the comments for a while and then write that as the next piece.
Designing a MOOC: how far did it reach? #csed
Posted: June 10, 2015 Filed under: Education, Opinion | Tags: advocacy, authenticity, blogging, collaboration, community, computer science education, constructivist, contributing student pedagogy, curriculum, data visualisation, design, education, educational problem, educational research, ethics, feedback, higher education, in the student's head, learning, measurement, MOOC, moocs, principles of design, reflection, resources, students, teaching, teaching approaches, thinking, tools Leave a commentMark Guzdial posted over on his blog on “Moving Beyond MOOCS: Could we move to understanding learning and teaching?” and discusses aspects (that still linger) of MOOC hype. (I’ve spoken about MOOCs done badly before, as well as recording the thoughts of people like Hugh Davis from Southampton.) One of Mark’s paragraphs reads:
“The value of being in the front row of a class is that you talk with the teacher. Getting physically closer to the lecturer doesn’t improve learning. Engagement improves learning. A MOOC puts everyone at the back of the class, listening only and doing the homework”
My reply to this was:
“You can probably guess that I have two responses here, the first is that the front row is not available to many in the real world in the first place, with the second being that, for far too many people, any seat in the classroom is better than none.
But I am involved in a, for us, large MOOC so my responses have to be regarded in that light. Thanks for the post!”
Mark, of course, called my bluff and responded with:
“Nick, I know that you know the literature in this space, and care about design and assessment. Can you say something about how you designed your MOOC to reach those who would not otherwise get access to formal educational opportunities? And since your MOOC has started, do you know yet if you achieved that goal — are you reaching people who would not otherwise get access?”
So here is that response. Thanks for the nudge, Mark! The answer is a bit long but please bear with me. We will be posting a longer summary after the course is completed, in a month or so. Consider this the unedited taster. I’m putting this here, early, prior to the detailed statistical work, so you can see where we are. All the numbers below are fresh off the system, to drive discussion and answering Mark’s question at, pretty much, a conceptual level.
First up, as some background for everyone, the MOOC team I’m working with is the University of Adelaide‘s Computer Science Education Research group, led by A/Prof Katrina Falkner, with me (Dr Nick Falkner), Dr Rebecca Vivian, and Dr Claudia Szabo.
I’ll start by noting that we’ve been working to solve the inherent scaling issues in the front of the classroom for some time. If I had a class of 12 then there’s no problem in engaging with everyone but I keep finding myself in rooms of 100+, which forces some people to sit away from me and also limits the number of meaningful interactions I can make to individuals in one setting. While I take Mark’s point about the front of the classroom, and the associated research is pretty solid on this, we encountered an inherent problem when we identified that students were better off down the front… and yet we kept teaching to rooms with more student than front. I’ll go out on a limb and say that this is actually a moral issue that we, as a sector, have had to look at and ignore in the face of constrained resources. The nature of large spaces and people, coupled with our inability to hover, means that we can either choose to have a row of students effectively in a semi-circle facing us, or we accept that after a relatively small number of students or number of rows, we have constructed a space that is inherently divided by privilege and will lead to disengagement.
So, Katrina’s and my first foray into this space was dealing with the problem in the physical lecture spaces that we had, with the 100+ classes that we had.
Katrina and I published a paper on “contributing student pedagogy” in Computer Science Education 22 (4), 2012, to identify ways for forming valued small collaboration groups as a way to promote engagement and drive skill development. Ultimately, by reducing the class to a smaller number of clusters and making those clusters pedagogically useful, I can then bring the ‘front of the class’-like experience to every group I speak to. We have given talks and applied sessions on this, including a special session at SIGCSE, because we think it’s a useful technique that reduces the amount of ‘front privilege’ while extending the amount of ‘front benefit’. (Read the paper for actual detail – I am skimping on summary here.)
We then got involved in the support of the national Digital Technologies curriculum for primary and middle school teachers across Australia, after being invited to produce a support MOOC (really a SPOC, small, private, on-line course) by Google. The target learners were teachers who were about to teach or who were teaching into, initially, Foundation to Year 6 and thus had degrees but potentially no experience in this area. (I’ve written about this before and you can find more detail on this here, where I also thanked my previous teachers!)
The motivation of this group of learners was different from a traditional MOOC because (a) everyone had both a degree and probable employment in the sector which reduced opportunistic registration to a large extent and (b) Australian teachers are required to have a certain number of professional development (PD) hours a year. Through a number of discussions across the key groups, we had our course recognised as PD and this meant that doing our course was considered to be valuable although almost all of the teachers we spoke to were furiously keen for this information anyway and my belief is that the PD was very much ‘icing’ rather than ‘cake’. (Thank you again to all of the teachers who have spent time taking our course – we really hope it’s been useful.)
To discuss access and reach, we can measure teachers who’ve taken the course (somewhere in the low thousands) and then estimate the number of students potentially assisted and that’s when it gets a little crazy, because that’s somewhere around 30-40,000.
In his talk at CSEDU 2014, Hugh Davis identified the student groups who get involved in MOOCs as follows. The majority of people undertaking MOOCs were life-long learners (older, degreed, M/F 50/50), people seeking skills via PD, and those with poor access to Higher Ed. There is also a small group who are Uni ‘tasters’ but very, very small. (I think we can agree that tasting a MOOC is not tasting a campus-based Uni experience. Less ivy, for starters.) The three approaches to the course once inside were auditing, completing and sampling, and it’s this final one that I want to emphasise because this brings us to one of the differences of MOOCs. We are not in control of when people decide that they are satisfied with the free education that they are accessing, unlike our strong gatekeeping on traditional courses.
I am in total agreement that a MOOC is not the same as a classroom but, also, that it is not the same as a traditional course, where we define how the student will achieve their goals and how they will know when they have completed. MOOCs function far more like many people’s experience of web browsing: they hunt for what they want and stop when they have it, thus the sampling engagement pattern above.
(As an aside, does this mean that a course that is perceived as ‘all back of class’ will rapidly be abandoned because it is distasteful? This makes the student-consumer a much more powerful player in their own educational market and is potentially worth remembering.)
Knowing these different approaches, we designed the individual subjects and overall program so that it was very much up to the participant how much they chose to take and individual modules were designed to be relatively self-contained, while fitting into a well-designed overall flow that built in terms of complexity and towards more abstract concepts. Thus, we supported auditing, completing and sampling, whereas our usual face-to-face (f2f) courses only support the first two in a way that we can measure.
As Hugh notes, and we agree through growing experience, marking/progress measures at scale are very difficult, especially when automated marking is not enough or not feasible. Based on our earlier work in contributing collaboration in the class room, for the F-6 Teacher MOOC we used a strong peer-assessment model where contributions and discussions were heavily linked. Because of the nature of the cohort, geographical and year-level groups formed who then conducted additional sessions and produced shared material at a slightly terrifying rate. We took the approach that we were not telling teachers how to teach but we were helping them to develop and share materials that would assist in their teaching. This reduced potential divisions and allows us to establish a mutually respectful relationship that facilitated openness.
(It’s worth noting that the courseware is creative commons, open and free. There are people reassembling the course for their specific take on the school system as we speak. We have a national curriculum but a state-focused approach to education, with public and many independent systems. Nobody makes any money out of providing this course to teachers and the material will always be free. Thank you again to Google for their ongoing support and funding!)
Overall, in this first F-6 MOOC, we had higher than usual retention of students and higher than usual participation, for the reasons I’ve outlined above. But this material was for curriculum support for teachers of young students, all of whom were pre-programming, and it could be contained in videos and on-line sharing of materials and discussion. We were also in the MOOC sweet-spot: existing degreed learners, PD driver, and their PD requirement depended on progressive demonstration on goal achievement, which we recognised post-course with a pre-approved certificate form. (Important note: if you are doing this, clear up how the PD requirements are met and how they need to be reported back, as early on as you can. It meant that we could give people something valuable in a short time.)
The programming MOOC, Think. Create. Code on EdX, was more challenging in many regards. We knew we were in a more difficult space and would be more in what I shall refer to as ‘the land of the average MOOC consumer’. No strong focus, no PD driver, no geographically guaranteed communities. We had to think carefully about what we considered to be useful interaction with the course material. What counted as success?
To start with, we took an image-based approach (I don’t think I need to provide supporting arguments for media-driven computing!) where students would produce images and, over time, refine their coding skills to produce and understand how to produce more complex images, building towards animation. People who have not had good access to education may not understand why we would use programming in more complex systems but our goal was to make images and that is a fairly universally understood idea, with a short production timeline and very clear indication of achievement: “Does it look like a face yet?”
In terms of useful interaction, if someone wrote a single program that drew a face, for the first time – then that’s valuable. If someone looked at someone else’s code and spotted a bug (however we wish to frame this), then that’s valuable. I think that someone writing a single line of correct code, where they understand everything that they write, is something that we can all consider to be valuable. Will it get you a degree? No. Will it be useful to you in later life? Well… maybe? (I would say ‘yes’ but that is a fervent hope rather than a fact.)
So our design brief was that it should be very easy to get into programming immediately, with an active and engaged approach, and that we have the same “mostly self-contained week” approach, with lots of good peer interaction and mutual evaluation to identify areas that needed work to allow us to build our knowledge together. (You know I may as well have ‘social constructivist’ tattooed on my head so this is strongly in keeping with my principles.) We wrote all of the materials from scratch, based on a 6-week program that we debated for some time. Materials consisted of short videos, additional material as short notes, participatory activities, quizzes and (we planned for) peer assessment (more on that later). You didn’t have to have been exposed to “the lecture” or even the advanced classroom to take the course. Any exposure to short videos or a web browser would be enough familiarity to go on with.
Our goal was to encourage as much engagement as possible, taking into account the fact that any number of students over 1,000 would be very hard to support individually, even with the 5-6 staff we had to help out. But we wanted students to be able to develop quickly, share quickly and, ultimately, comment back on each other’s work quickly. From a cognitive load perspective, it was crucial to keep the number of things that weren’t relevant to the task to a minimum, as we couldn’t assume any prior familiarity. This meant no installers, no linking, no loaders, no shenanigans. Write program, press play, get picture, share to gallery, winning.
As part of this, our support team (thanks, Jill!) developed a browser-based environment for Processing.js that integrated with a course gallery. Students could save their own work easily and share it trivially. Our early indications show that a lot of students jumped in and tried to do something straight away. (Processing is really good for getting something up, fast, as we know.) We spent a lot of time testing browsers, testing software, and writing code. All of the recorded materials used that development environment (this was important as Processing.js and Processing have some differences) and all of our videos show the environment in action. Again, as little extra cognitive load as possible – no implicit requirement for abstraction or skills transfer. (The AdelaideX team worked so hard to get us over the line – I think we may have eaten some of their brains to save those of our students. Thank you again to the University for selecting us and to Katy and the amazing team.)
The actual student group, about 20,000 people over 176 countries, did not have the “built-in” motivation of the previous group although they would all have their own levels of motivation. We used ‘meet and greet’ activities to drive some group formation (which worked to a degree) and we also had a very high level of staff monitoring of key question areas (which was noted by participants as being very high for EdX courses they’d taken), everyone putting in 30-60 minutes a day on rotation. But, as noted before, the biggest trick to getting everyone engaged at the large scale is to get everyone into groups where they have someone to talk to. This was supposed to be provided by a peer evaluation system that was initially part of the assessment package.
Sadly, the peer assessment system didn’t work as we wanted it to and we were worried that it would form a disincentive, rather than a supporting community, so we switched to a forum-based discussion of the works on the EdX discussion forum. At this point, a lack of integration between our own UoA programming system and gallery and the EdX discussion system allowed too much distance – the close binding we had in the R-6 MOOC wasn’t there. We’re still working on this because everything we know and all evidence we’ve collected before tells us that this is a vital part of the puzzle.
In terms of visible output, the amount of novel and amazing art work that has been generated has blown us all away. The degree of difference is huge: armed with approximately 5 statements, the number of different pieces you can produce is surprisingly large. Add in control statements and reputation? BOOM. Every student can write something that speaks to her or him and show it to other people, encouraging creativity and facilitating engagement.
From the stats side, I don’t have access to the raw stats, so it’s hard for me to give you a statistically sound answer as to who we have or have not reached. This is one of the things with working with a pre-existing platform and, yes, it bugs me a little because I can’t plot this against that unless someone has built it into the platform. But I think I can tell you some things.
I can tell you that roughly 2,000 students attempted quiz problems in the first week of the course and that over 4,000 watched a video in the first week – no real surprises, registrations are an indicator of interest, not a commitment. During that time, 7,000 students were active in the course in some way – including just writing code, discussing it and having fun in the gallery environment. (As it happens, we appear to be plateauing at about 3,000 active students but time will tell. We have a lot of post-course analysis to do.)
It’s a mistake to focus on the “drop” rates because the MOOC model is different. We have no idea if the people who left got what they wanted or not, or why they didn’t do anything. We may never know but we’ll dig into that later.
I can also tell you that only 57% of the students currently enrolled have declared themselves explicitly to be male and that is the most likely indicator that we are reaching students who might not usually be in a programming course, because that 43% of others, of whom 33% have self-identified as women, is far higher than we ever see in classes locally. If you want evidence of reach then it begins here, as part of the provision of an environment that is, apparently, more welcoming to ‘non-men’.
We have had a number of student comments that reflect positive reach and, while these are not statistically significant, I think that this also gives you support for the idea of additional reach. Students have been asking how they can save their code beyond the course and this is a good indicator: ownership and a desire to preserve something valuable.
For student comments, however, this is my favourite.
I’m no artist. I’m no computer programmer. But with this class, I see I can be both. #processingjs (Link to student’s work) #code101x .
That’s someone for whom this course had them in the right place in the classroom. After all of this is done, we’ll go looking to see how many more we can find.
I know this is long but I hope it answered your questions. We’re looking forward to doing a detailed write-up of everything after the course closes and we can look at everything.
EduTech AU 2015, Day 2, Higher Ed Leaders, “Assessment: The Silent Killer of Learning”, #edutechau @eric_mazur
Posted: June 3, 2015 Filed under: Education | Tags: assessment, educational problem, educational research, edutech2015, edutechau, eric mazur, feedback, harvard, higher education, in the student's head, learning, peer instruction, plagiarism, student perspective, students, teaching, teaching approaches, thinking, time banking, tools, universal principles of design, workload 3 CommentsNo surprise that I’m very excited about this talk as well. Eric is a world renowned educator and physicist, having developed Peer Instruction in 1990 for his classes at Harvard as a way to deal with students not developing a working physicist’s approach to the content of his course. I should note that Eric also gave this talk yesterday and the inimitable Steve Wheeler blogged that one, so you should read Steve as well. But after me. (Sorry, Steve.)
I’m not an enormous fan of most of the assessment we use as most grades are meaningless, assessment becomes part of a carrot-and-stick approach and it’s all based on artificial timelines that stifle creativity. (But apart from that, it’s fine. Ho ho.) My pithy statement on this is that if you build an adversarial educational system, you’ll get adversaries, but if you bother to build a learning environment, you’ll get learning. One of the natural outcomes of an adversarial system is activities like cheating and gaming the system, because people start to treat beating the system as the goal itself, which is highly undesirable. You can read a lot more about my views on plagiarism here, if you like. (Warning: that post links to several others and is a bit of a wormhole.)
Now, let’s hear what Eric has to say on this! (My comments from this point on will attempt to contain themselves in parentheses. You can find the slides for his talk – all 62MB of them – from this link on his website. ) It’s important to remember that one of the reasons that Eric’s work is so interesting is that he is looking for evidence-based approaches to education.
Eric discussed the use of flashcards. A week after Flashcard study, students retain 35%. After two weeks, it’s almost gone. He tried to communicate this to someone who was launching a cloud-based flashcard app. Her response was “we only guarantee they’ll pass the test”.
*low, despairing chuckle from the audience*
Of course most students study to pass the test, not to learn, and they are not the same thing. For years, Eric has been bashing the lecture (yes, he noted the irony) but now he wants to focus on changing assessment and getting it away from rote learning and regurgitation. The assessment practices we use now are not 21st century focused, they are used for ranking and classifying but, even then, doing it badly.
So why are we assessing? What are the problems that are rampant in our assessment procedure? What are the improvements we can make?
How many different purposes of assessment can you think of? Eric gave us 90s to come up with a list. Katrina and I came up with about 10, most of which were serious, but it was an interesting question to reflect upon. (Eric snuck
- Rate and rank students
- Rate professor and course
- Motivate students to keep up with work
- Provide feedback on learning to students
- Provide feedback to instructor
- Provide instructional accountability
- Improve the teaching and learning.
Ah, but look at the verbs – they are multi-purpose and in conflict. How can one thing do so much?
So what are the problems? Many tests are fundamentally inauthentic – regurgitation in useless and inappropriate ways. Many problem-solving approaches are inauthentic as well (a big problem for computing, we keep writing “Hello, World”). What does a real problem look like? It’s an interruption in our pathway to our desired outcome – it’s not the outcome that’s important, it’s the pathway and the solution to reach it that are important. Typical student problem? Open the book to chapter X to apply known procedure Y to determine an unknown answer.
Shout out to Bloom’s! Here’s Eric’s slide to remind you.
Eric doesn’t think that many of us, including Harvard, even reach the Applying stage. He referred to a colleague in physics who used baseball problems throughout the course in assignments, until he reached the final exam where he ran out of baseball problems and used football problems. “Professor! We’ve never done football problems!” Eric noted that, while the audience were laughing, we should really be crying. If we can’t apply what we’ve learned then we haven’t actually learned i.
Eric sneakily put more audience participation into the talk with an open ended question that appeared to not have enough information to come up with a solution, as it required assumptions and modelling. From a Bloom’s perspective, this is right up the top.
Students loathe assumptions? Why? Mostly because we’ll give them bad marks if they get it wrong. But isn’t the ability to make assumptions a really important skill? Isn’t this fundamental to success?
Eric demonstrated how to tame the problem by adding in more constraints but this came at the cost of the creating stage of Bloom’s and then the evaluating and analysing. (Check out his slides, pages 31 to 40, for details of this.) If you add in the memorisation of the equation, we have taken all of the guts out of the problem, dropping down to the lowest level of Bloom’s.
But, of course, computers can do most of the hard work for that is mechanistic. Problems at the bottom layer of Bloom’s are going to be solved by machines – this is not something we should train 21st Century students for.
But… real problem solving is erratic. Riddled with fuzziness. Failure prone. Not guaranteed to succeed. Most definitely not guaranteed to be optimal. The road to success is littered with failures.
But, if you make mistakes, you lose marks. But if you’re not making mistakes, you’re very unlikely to be creative and innovative and this is the problem with our assessment practices.
Eric showed us a stress of a traditional exam room: stressful, isolated, deprived of calculators and devices. Eric’s joke was that we are going to have to take exams naked to ensure we’re not wearing smart devices. We are in a time and place where we can look up whatever we want, whenever we want. But it’s how you use that information that makes a difference. Why are we testing and assessing students under such a set of conditions? Why do we imagine that the result we get here is going to be any indicator at all of the likely future success of the student with that knowledge?
Cramming for exams? Great, we store the information in short-term memory. A few days later, it’s all gone.
Assessment produces a conflict, which Eric noticed when he started teaching a team and project based course. He was coaching for most of the course, switching to a judging role for the monthly fair. He found it difficult to judge them because he had a coach/judge conflict. Why do we combine it in education when it would be unfair or unpleasant in every other area of human endeavour? We hide between the veil of objectivity and fairness. It’s not a matter of feelings.
But… we go back to Bloom’s. The only thinking skill that can be evaluated truly objectively is remembering, at the bottom again.
But let’s talk about grade inflation and cheating. Why do people cheat at education when they don’t generally cheat at learning? But educational systems often conspire to rob us of our ownership and love of learning. Our systems set up situations where students cheat in order to succeed.
- Mimic real life in assessment practices!
Open-book exams. Information sticks when you need it and use it a lot. So use it. Produce problems that need it. Eric’s thought is you can bring anything you want except for another living person. But what about assessment on laptops? Oh no, Google access! But is that actually a problem? Any question to which the answer can be Googled is not an authentic question to determine learning!
Eric showed a video of excited students doing a statistic tests as a team-based learning activity. After an initial pass at the test, the individual response is collected (for up to 50% of the grade), and then students work as a group to confirm the questions against an IF AT scratchy card for the rest of the marks. Discussion, conversation, and the students do their own grading for you. They’ve also had the “A-ha!” moment. Assessment becomes a learning opportunity.
Eric’s not a fan of multiple choice so his Learning Catalytics software allows similar comparison of group answers without having to use multiple choice. Again, the team based activities are social, interactive and must less stressful.
- Focus on feedback, not ranking.
Objective ranking is a myth. The amount of, and success with, advanced education is no indicator of overall success in many regards. So why do we rank? Eric showed some graphs of his students (in earlier courses) plotting final grades in physics against the conceptual understanding of force. Some people still got top grades without understanding force as it was redefined by Newton. (For those who don’t know, Aristotle was wrong on this one.) Worse still is the student who mastered the concept of force and got a C, when a student who didn’t master force got an A. Objectivity? Injustice?
- Focus on skills, not content
Eric referred to Wiggins and McTighe, “Understanding by Design.” Traditional approach is course content drives assessment design. Wiggins advocates identifying what the outcomes are, formulate these as action verbs, ‘doing’ x rather than ‘understanding’ x. You use this to identify what you think the acceptable evidence is for these outcomes and then you develop the instructional approach. This is totally outcomes based.
- resolve coach/judge conflict
In his project-based course, Eric brought in external evaluators, leaving his coach role unsullied. This also validates Eric’s approach in the eyes of his colleagues. Peer- and self-evaluation are also crucial here. Reflective time to work out how you are going is easier if you can see other people’s work (even anonymously). Calibrated peer review, cpr.molsci.ucla.edu, is another approach but Eric ran out of time on this one.
If we don’t rethink assessment, the result of our assessment procedures will never actually provide vital information to the learner or us as to who might or might not be successful.
I really enjoyed this talk. I agree with just about all of this. It’s always good when an ‘internationally respected educator’ says it as then I can quote him and get traction in change-driving arguments back home. Thanks for a great talk!
EduTech AU 2015, Day 2, Higher Ed Leaders, “Innovation + Technology = great change to higher education”, #edutechau
Posted: June 3, 2015 Filed under: Education | Tags: advocacy, collaboration, community, connectivity, design, education, educational problem, educational research, edutech2015, edutechau, ethics, grand challenge, higher education, learning, market forces, measurement, mit, mit media lab, Nicholas, nicholas negroponte, olpc, one laptop per child, principles of design, public education, resources, seymour papert, students, teaching, teaching approaches, thinking, tools Leave a commentBig session today. We’re starting with Nicholas Negroponte, founder of the MIT Media Lab and the founder of One Laptop Per Child (OLPC), an initiative to create/provide affordable educational devices for children in the developing world. (Nicholas is coming to us via video conference, hooray, 21st Century, so this may or not work well in translation to blogging. Please bear with me if it’s a little disjointed.)
Nicholas would rather be here but he’s bravely working through his first presentation of this type! It’s going to be a presentation with some radical ideas so he’s hoping for conversation and debate. The presentation is broken into five parts:
- Learning learning. (Teaching and learning as separate entities.)
- What normal market forces will not do. (No real surprise that standard market forces won’t work well here.)
- Education without curricula. (Learning comes from many places and situations. Understanding and establishing credibility.)
- Where do new ideas come from? (How do we get them, how do we not get in the way.)
- Connectivity as a human right. (Is connectivity a human right or a means to rights such as education and healthcare? Human rights are free so that raises a lot of issues.
Nicholas then drilled down in “Learning learning”, starting with a reference to Seymour Papert, and Nicholas reflected on the sadness of the serious accident of Seymour’s health from a personal perspective. Nicholas referred to Papert’s and Minsky’s work on trying to understand how children and machines learned respectively. In 1968, Seymour started thinking about it and on April, 9, 1970, he gave a talk on his thoughts. Seymour realised that thinking about programs gave insight into thinking, relating to the deconstruction and stepwise solution building (algorithmic thinking) that novice programmers, such as children, had to go through.
These points were up on the screen as Nicholas spoke:
- Construction versus instruction
- Why reinventing the wheel is good
- Coding as thinking about thinking
How do we write code? Write it, see if it works, see which behaviours we have that aren’t considered working, change the code (in an informed way, with any luck) and try again. (It’s a little more complicated than that but that’s the core.) We’re now into the area of transferable skills – it appeared that children writing computer programs learned a skill that transferred over into their ability to spell, potentially from the methodical application of debugging techniques.
Nicholas talked about a spelling bee system where you would focus on the 8 out of 10 you got right and ignore the 2 you didn’t get. The ‘debugging’ kids would talk about the ones that they didn’t get right because they were analsysing their mistakes, as a peer group and as individual reflection.
Nicholas then moved on to the failure of market forces. Why does Finland do so well when they don’t have tests, homework and the shortest number of school hours per day and school days per year. One reason? No competition between children. No movement of core resources into the private sector (education as poorly functioning profit machine). Nicholas identified the core difference between the mission and the market, which beautifully summarises my thinking.
The OLPC program started in Cambodia for a variety of reasons, including someone associated with the lab being a friend of the King. OLPC laptops could go into areas where the government wasn’t providing schools for safety reasons, as it needed minesweepers and the like. Nicholas’ son came to Cambodia from Italy to connect up the school to the Internet. What would the normal market not do? Telecoms would come and get cheaper. Power would come and get cheaper. Laptops? Hmm. The software companies were pushing the hardware companies, so they were both caught in a spiral of increasing power consumption for utility. Where was the point where we could build a simple laptop, as a mission of learning, that could have a smaller energy footprint and bring laptops and connectivity to billions of people.
This is one of the reasons why OLPC is a non-profit – you don’t have to sell laptops to support the system, you’re supporting a mission. You didn’t need to sell or push to justify staying in a market, as the production volume was already at a good price. Why did this work well? You can make partnerships that weren’t possible otherwise. It derails the “ah, you need food and shelter first” argument because you can change the “why do we need a laptop” argument to “why do we need education?” at which point education leads to increased societal conditions. Why laptops? Tablets are more consumer-focused than construction-focused. (Certainly true of how I use my tech.)
(When we launched the first of the Digital Technologies MOOCs, the deal we agreed upon with Google was that it wasn’t a profit-making venture at all. It never will be. Neither we nor Google make money from the support of teachers across Australia so we can have all of the same advantages as they mention above: open partnerships, no profit motive, working for the common good as a mission of learning and collegial respect. Highly recommended approach, if someone is paying you enough to make your rent and eat. The secret truth of academia is that they give you money to keep you housed, clothed and fed while you think. )
Nicholas told a story of kids changing from being scared or bored of school to using an approach that brings kids flocking in. A great measure of success.
Now, onto Education without curricula, starting by talking public versus private. This is a sensitive subject for many people. The biggest problem for public education in many cases is the private educational system, dragging out caring educators to a closed system. Remember Finland? There are no public schools and their educational system is astoundingly good. Nicholas’ points were:
- Public versus private
- Age segregation
- Stop testing. (Yay!)
The public sector is losing the imperative of the civic responsibility for education. Nicholas thinks it doesn’t make sense that we still segregate by ages as a hard limit. He thinks we should get away from breaking it into age groups, as it doesn’t clearly reflect where students are at.
Oh, testing. Nicholas correctly labelled the parental complicity in the production of the testing pressure cooker. “You have to get good grades if you’re going to Princeton!” The testing mania is dominating institutions and we do a lot of testing to measure and rank children, rather than determining competency. Oh, so much here. Testing leads to destructive behaviour.
So where do new ideas come from? (A more positive note.) Nicholas is interested in Higher Ed as sources of new ideas. Why does HE exist, especially if we can do things remotely or off campus? What is the role of the Uni in the future? Ha! Apparently, when Nicholas started the MIT media lab, he was accused of starting a sissy lab with artists and soft science… oh dear, that’s about as wrong as someone can get. His use of creatives was seen as soft when, of course, using creative users addressed two issues to drive new ideas: a creative approach to thinking and consulting with the people who used the technology. Who really invented photography? Photographers. Three points from this section.
- Children: our most precious natural resource
- Incrementalism is the enemy of creativity
- Brain drain
On the brain drain, we lose many, many students to other places. Uni are a place to solve huge problems rather than small, profit-oriented problems. The entrepreneurial focus leads to small problem solution, which is sucking a lot of big thinking out of the system. The app model is leading to a human resource deficit because the start-up phenomenon is ripping away some of our best problem solvers.
Finally, to connectivity as a human right. This is something that Nicholas is very, very passionate about. Not content. Not laptops. Being connected. Learning, education, and access to these, from early in life to the end of life – connectivity is the end of isolation. Isolation comes in many forms and can be physical, geographical and social. Here are Nicholas’ points:
- The end of isolation.
- Nationalism is a disease (oh, so much yes.) Nations are the wrong taxonomy for the world.
- Fried eggs and omelettes.
Fried eggs and omelettes? In general, the world had crisp boundaries, yolk versus white. At work/at home. At school/not at school. We are moving to a more blended, less dichotomous approach because we are mixing our lives together. This is both bad (you’re getting work in my homelife) and good (I’m getting learning in my day).
Can we drop kids into a reading environment and hope that they’ll learn to read? Reading is only 3,500 years old, versus our language skills, so it has to be learned. But do we have to do it the way that we did it? Hmm. Interesting questions. This is where the tablets were dropped into illiterate villages without any support. (Does this require a seed autodidact in the group? There’s a lot to unpack it.) Nicholas says he made a huge mistake in naming the village in Ethiopia which has corrupted the experiment but at least the kids are getting to give press conferences!
Another massive amount of interesting information – sadly, no question time!
EduTECH AU 2015, Day 1, Higher Ed Leaders, “Revolutionising the Student Experience: Thinking Boldly” #edutechau
Posted: June 2, 2015 Filed under: Education | Tags: AI, artificial intelligence, blogging, collaboration, community, data visualisation, deakin, design, education, educational research, edutech2015, edutecha, edutechau, ethics, higher education, learning, learning analytics, machine intelligence, measurement, principles of design, resources, student perspective, students, teaching, thinking, tools, training, watson Leave a commentLucy Schulz, Deakin University, came to speak about initiatives in place at Deakin, including the IBM Watson initiative, which is currently a world-first for a University. How can a University collaborate to achieve success on a project in a short time? (Lucy thinks that this is the more interesting question. It’s not about the tool, it’s how they got there.)
Some brief facts on Deakin: 50,000 students, 11,000 of whom are on-line. Deakin’s question: how can we make the on-line experience as good if not better than the face-to-face and how can on-line make face-to-face better?
Part of Deakin’s Student Experience focus was on delighting the student. I really like this. I made a comment recently that our learning technology design should be “Everything we do is valuable” and I realise now I should have added “and delightful!” The second part of the student strategy is for Deakin to be at the digital frontier, pushing on the leading edge. This includes understanding the drivers of change in the digital sphere: cultural, technological and social.
(An aside: I’m not a big fan of the term disruption. Disruption makes room for something but I’d rather talk about the something than the clearing. Personal bug, feel free to ignore.)
The Deakin Student Journey has a vision to bring students into the centre of Uni thinking, every level and facet – students can be successful and feel supported in everything that they do at Deakin. There is a Deakin personality, an aspirational set of “Brave, Stylish, Accessible, Inspiring and Savvy”.
Not feeling this as much but it’s hard to get a feel for something like this in 30 seconds so moving on.
What do students want in their learning? Easy to find and to use, it works and it’s personalised.
So, on to IBM’s Watson, the machine that won Jeopardy, thus reducing the set of games that humans can win against machines to Thumb Wars and Go. We then saw a video on Watson featuring a lot of keen students who coincidentally had a lot of nice things to say about Deakin and Watson. (Remember, I warned you earlier, I have a bit of a thing about shiny videos but ignore me, I’m a curmudgeon.)
The Watson software is embedded in a student portal that all students can access, which has required a great deal of investigation into how students communicate, structurally and semantically. This forms the questions and guides the answer. I was waiting to see how Watson was being used and it appears to be acting as a student advisor to improve student experience. (Need to look into this more once day is over.)
Ah, yes, it’s on a student home page where they can ask Watson questions about things of importance to students. It doesn’t appear that they are actually programming the underlying system. (I’m a Computer Scientist in a faculty of Engineering, I always want to get my hands metaphorically dirty, or as dirty as you can get with 0s and 1s.) From looking at the demoed screens, one of the shiny student descriptions of Watson as “Siri plus Google” looks very apt.
Oh, it has cheekiness built in. How delightful. (I have a boundless capacity for whimsy and play but an inbuilt resistance to forced humour and mugging, which is regrettably all that the machines are capable of at the moment. I should confess Siri also rubs me the wrong way when it tries to be funny as I have a good memory and the patterns are obvious after a while. I grew up making ELIZA say stupid things – don’t judge me! 🙂 )
Watson has answered 26,000 questions since February, with an 80% accuracy for answers. The most common questions change according to time of semester, which is a nice confirmation of existing data. Watson is still being trained, with two more releases planned for this year and then another project launched around course and career advisors.
What they’ve learned – three things!
- Student voice is essential and you have to understand it.
- Have to take advantage of collaboration and interdependencies with other Deakin initiatives.
- Gained a new perspective on developing and publishing content for students. Short. Clear. Concise.
The challenges of revolution? (Oh, they’re always there.) Trying to prevent students falling through the cracks and make sure that this tool help students feel valued and stay in contact. The introduction of new technologies have to be recognised in terms of what they change and what they improve.
Collaboration and engagement with your University and student community are essential!
Thanks for a great talk, Lucy. Be interesting to see what happens with Watson in the next generations.
EduTECH AU 2015, Day 1, Higher Ed Leaders, Panel Discussion “Leveraging data for strategic advantage” #edutechau
Posted: June 2, 2015 Filed under: Education | Tags: analytics, blogging, data analytics, education, educational problem, educational research, edutech2015, edutechau, ethics, higher education, learning analytics, measurement, principles of design, reflection, students, teaching, teaching approaches Leave a commentA most distinguished panel today. It can be hard to capture panel discussions so I will do what I can to get the pertinent points down. However, the fact that we are having this panel gives you some indication of the importance of this issue. Getting to know your data will make it easier for you to work out what to do in the future.
University of Wollongong (UoW) have set up a University-wide approach to Learning Analytics, with 30 courses in an early adopter program, scaling up over the next two years. Give things that they have learned.
- You need to have a very clear strategic approach for learning analytics. Learning analytics are built into key strategies. This ties in the key governing bodies and gives you the resources.
- Learning analytics need to be tied into IT and data management strategies – separating infrastructure and academics won’t work.
- The only driver for UoW is the academic driver, not data and not technology. All decisions are academic. “what is the value that this adds to maximums student learning, provide personalised learning and early identification of students at risk?”
- Governance is essential. UoW have a two-tier structure, a strategic group and an ethical use of data group. Both essential but separate.
- With data, and learning analytics, comes a responsibility for action. Actions by whom and, then, what action? What are the roles of the student, staff and support services? Once you have seen a problem that requires intervention, you are obliged to act.
I totally agree with this. I have had similar arguments on the important nature of 5.
The next speaker is from University of Melbourne (UoM), who wanted to discuss a high-level conceptual model. At the top of the model is the term ‘success’, a term that is not really understood or widely used, at national or local level. He introduced the term of ‘education analytics’ where we look at the overall identity of the student and interactions with the institution. We’re not having great conversations with students through written surveys so analytics can provide this information (a controversial approach). UoM want a new way, a decent way, to understand the student, rather than taking a simplistic approach. I think he mentioned intersectionality but not in a way that I really understood it.
Most of what determines student success in Australia isn’t academic, it’s personal, and we have to understand that. We also can’t depend on governments to move this, it will have to come out of the universities.
The next speaker is from University of Sydney, who had four points he wanted to make.
He started by talking about the potential of data. Data is there but it’s time to leverage it. Why are institutions not adopting LA as fast as they could? We understand the important of data-backed decision making.
Working with LA requires a very broad slice across the University – IT, BI, Academics, all could own it and they all want to control it. We want to collaborate so we need clear guidance and clear governance. Need to identify who is doing what without letting any one area steal it.
Over the last years, we have forgotten about the proximity of data. It’s all around us but many people think it’s not accessible. How do we get our hands on all of this data to make information-backed decisions in the right timeframe? This proximity applies to students as well, they should be able to see what’s going on as a day-by-day activity.
The final panellist is from Curtin University. Analytics have to be embedded into daily life and available with little effort if they’re going to be effective. At Curtin, analytics have a role in all places in the Uni, library, learning, life-long learning, you name it. Data has to be unified and available on demand. What do users want?
Curtin focused on creating demand – can they now meet that demand with training and staffing, to move to the next phase of attraction?
Need to be in a position of assisting everyone. This is a new world so have to be ready to help people quite a lot in the earlier stages. Is Higher Ed ready for the type of change that Amazon caused in the book market? Higher Ed can still have a role as validator of education but we have to learn to work with new approaches before our old market is torn out form underneath us.
We need to disentangle what the learner does from what the machine does.
That finished off the initial panel statements and then the chair moved to ask questions to the panel. I’ll try and summarise that.
One question was about the issue of security and privacy of student information. Can we take data that we used to help a student to complete their studies and then use that to try and recruit a new student, even anonymised? UoW mentioned that having a separate data ethics group for exactly this reason. UoW started this with a student survey, one question of which is “do you feel like this is Big Brother”. Fortunately, most felt that it wasn’t but they wanted to know what was going to happen with the data and the underlying driver had to be to help them to succeed.
Issuing a clear policy and embracing transparency is crucial here.
UoM made the point that much work is not built on a strong theoretical basis and a great deal of it is measuring what we already think we care about. There is a lot of value in clearly identifying what works and what doesn’t.
That’s about it for this session. Again, so much to think about.



