Moving beyond a fashion
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Moving beyond a fashion

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  • <!-- This snippet was inserted via the PollEv Presenter app --> <!-- The presence of this snippet is used to indicate that a poll will be shown during the slideshow --> <!-- TIP: You can draw a solid, filled rectangle on your slide and the PollEv Presenter will automatically display your poll in that area. --> <!-- The PollEv Presenter app must also be running and logged in for this to work. --> <!-- To remove this, simply delete it from the notes yourself or use the PollEv Presenter to remove it for you. --> What percentage of your institution's online courses do you consider good?
  • Let’s start with the obvious. Of course we want to do this. We know that senior management like to do this and that academics should (and like) to make decisions based on data and evidence. (Of course it’s also obvious that most human beings tend to fail badly at this)
  • Learning analytics is the new light that will help use achieve this goal of data-based decision making and deal with the uncertainty and change facing higher education.
  • Of course, all this is sounding exactly like a management fashion. Which has been defined as…
  • Over a decade ago Birnbaum wrote a book about fads in higher education and proposed this cycle. Which I tend to think is more pessimistic and consequently more realistic than the Gartner Hype Cycle which assumes that there every fad finds a Plateau of Productivity.
  • Brings me to our argument
  • We are excited about the possibilities of learning analytics. As a faculty member teaching a course with 300+ students – the majority of whom are online only – the possibilities provided by learning analytics is very exciting.
  • The trouble is that based on 20+ years of experience I expect the implementation to be screwed up. The last large scale information-based revolution in Universities was ERP systems. Promising to reduce costs, increase growth, improve business processes, heighten productivity and increase agility.Our aim is to talk about some options for how you might go about learning analytics.
  • While I don’t like this representation it helps express our aim to avoid this situation
  • And instead achieve this. Avoid the dissapointment and cost of the peak and trough and head straight to being productive.
  • The structure of the talk. The foundation for the argument is a particular perspective on learning analytics. So we spend some time on that. We then suggest that there will be three paths that institutions could adopt with learning analytics (as with most e-learning initiatives). Due to time constraints we’ll spend only very little time on the first two and try to focus a bit more on the third. Then some conclusions.
  • We know that it has certainly risen to the attention of the sector. We would argue that this is primarily because one conception of learning analytics aligns nicely with the tendency toward the techno-rationalist approach to management being adopted by Australian universities. We’re being rational by doing this, so we should do it.
  • In fact, not many institutions are doing it yet. Not a large scale. And if they are there’s often a real focus on retention.
  • But it’s also not the new. Most universities have been doing data warehouses for a while. But there’s been some problems there.
  • A problem that is being faced by “big data” projects.
  • And it seems that this lesson is forgotten. Success/failure is a complex thing. Most Australian Universities are using ERPs 10+ years after implementation but I doubt on any comparison between proposed ROI and actual results that any could be measured as successful. I certainly now as an academic user I am yet to see an ERP implementation result in a useful and usable set of functionality that is helping me in my job.
  • We should also mention that Birnbaum’s fad cycle isn’t just a single cycle. But it’s nested or hierarchical as a fad fails in one sector (e.g. business) the consultants and vendors take it to the next sector (government) and then the next (education)
  • We should also mention that Birnbaum’s fad cycle isn’t just a single cycle. But it’s nested or hierarchical as a fad fails in one sector (e.g. business) the consultants and vendors take it to the next sector (government) and then the next (education)
  • Learning analytics is hugely diverse – I don’t computational linguistics got a mention above – there are some many different perspectives/fields of knowledge that can inform the implementation of learning analytics. It remains a new field picking up methods and tools as it goes along.
  • In passing, the necessary mention of change. Universities – as with most parts of society – are having to deal with an environment of on-going change. Just one of the sources of that change is technology. It’s necessary to reflect that much of that change is going to require more than first order change – where you do the same stuff with new tools – it’s going to require second order (and perhaps third order change)
  • Analytics is about examining the data you have and to reveal interesting insights. It only tells you about what’s already in the data. i.e. the stuff you already do. If you try something new, then you’ll need to be gathering new data and analysing it in a new way. The quality of the data you have is important. If you’re using analytics on existing data, and your existing practice is questionable
  • Link this to the results of the poll. <!-- This snippet was inserted via the PollEv Presenter app --> <!-- The presence of this snippet is used to indicate that a poll will be shown during the slideshow --> <!-- TIP: You can draw a solid, filled rectangle on your slide and the PollEv Presenter will automatically display your poll in that area. --> <!-- The PollEv Presenter app must also be running and logged in for this to work. --> <!-- To remove this, simply delete it from the notes yourself or use the PollEv Presenter to remove it for you. --> What percentage of your institution's online courses do you consider good?
  • And we don’t really have a good handle on how yet to do this.
  • And we don’t really have a good handle on how yet to do this.
  • If learning analytics doesn’t improve learning, then what’s the point. In order for it to improve learning, learning analytics has to be embedded in the practice of learning and teaching. It has to be used.
  • Some folk at the instituional level make some plans
  • Make changes to the L&T context. A new system, new policies etc.
  • Make changes to the L&T context. A new system, new policies etc.
  • Make changes to the L&T context. A new system, new policies etc.
  • Make changes to the L&T context. A new system, new policies etc.
  • Make changes to the L&T context. A new system, new policies etc.
  • In terms of many institutional uses of learning analytics – especially the retention work – this can tend to avoid the teaching staff entirely. In other cases, it will impact what teachers do, but not necessarily their thinking. Where academic staff seek to corrupt and workaround those changes.
  • There are a range of pitfalls associated with this approach. But it’s positive is that it gives concrete KPIs. Finish project X by time Y and show Z.
  • Brings me to our argument
  • One of the problems is that this approach uses planning approach. NEED TO WORK ON THIS SLIDE
  • Brings me to our argument
  • Another group of folk get together. In this case, they also make some conclusions about learning analytics
  • They also make changes to the L&T context, but in this case it’s the addition of some new plugins for the LMS and/or some staff development activities where academic staff learn about this new thing called learning analytics.
  • The assumption being that this will change the way teaching staff think and then set off a cascade
  • The assumption being that this will change the way teaching staff think and then set off a cascade
  • And we don’t really have a good handle on how yet to do this.
  • “Do it with” is having a range of different people with different skills and abilities engaged closely to the context of teaching and learning aiming to observe and learn from what is going on and design and develop new tools, features, approaches, policies etc in response to what is found.
  • “Do it with” is having a range of different people with different skills and abilities engaged closely to the context of teaching and learning aiming to observe and learn from what is going on and design and develop new tools, features, approaches, policies etc in response to what is found.
  • “Do it with” is having a range of different people with different skills and abilities engaged closely to the context of teaching and learning aiming to observe and learn from what is going on and design and develop new tools, features, approaches, policies etc in response to what is found.
  • “Do it with” is having a range of different people with different skills and abilities engaged closely to the context of teaching and learning aiming to observe and learn from what is going on and design and develop new tools, features, approaches, policies etc in response to what is found.
  • “Do it with” is having a range of different people with different skills and abilities engaged closely to the context of teaching and learning aiming to observe and learn from what is going on and design and develop new tools, features, approaches, policies etc in response to what is found.
  • “Do it with” is having a range of different people with different skills and abilities engaged closely to the context of teaching and learning aiming to observe and learn from what is going on and design and develop new tools, features, approaches, policies etc in response to what is found.
  • Brings me to our argument
  • But increasingly the context in which teachers find themselves is incredibly complex. Existing institutional and individual approaches aren’t dealing with this well. Teaching staff can’t deal with this by themselves. The institutional environment needs to have teams engaged in the day to day teaching context. Not in designing courses, but involved, helping and responding to situations during the teaching process.
  • Not only is the quality questionable, but there are suggestions that workload is overwhelming. A range of literature arising that questions workload from online learning. Lecturers who move into the online learning environment often discover that the workload involved not only changes, but can be overwhelming as they cope with using digital technologies. Questions arise, given the dissatisfaction of lecturers with lowering morale and increasing workload, whether future expansion of this teaching component in tertiary institutions is sustainable. Bright, S. (2012). eLearning lecturer workload: working smarter or working harder? In M. Brown, M. Hartnett, & T. Stewart (Eds.), ASCILITE’2012. Wellington, NZ.
  • This focus on context is echoed in the learning analytics literature. University e-learning is not exactly the same as big data. Knowledge of the specifics of individual students, courses and pedagogies is essentially to getting value
  • In fact, it is from bricolage that organisations gain advantage. You do not get any significant advantage from adopting and using the same systems and processes as every other university (i.e. “best” practice).
  • So let’s talk about frameworks and learning analytics. Ways to understand what is going on.
  • This model of analytics comes from George Siemens latest journal article giving an overview of the field of learning analytics. I recommend the article and I like this model in that it captures what passes for current understandings of learning analytics. But I also have an issue with it. To me it smacks to much of “do it to and for” and not enough of do it with.It also, for me, illustrates a criticism that Col, myself and Damien Clark our colleague have of current approaches to learning analytics which we try to capture in our own framework – called the IRAC framework. Come along to our workshop this afternoon to learn more.
  • The I in IRAC is for information. This seems to be almost the complete focus of learning analytics projects. How to get the information? What information is there and how to analyse it. These are important questions you have to ask. But I hope you can see given this talk that we think this is really on the start.
  • The R in IRAC is representation. You’ve gathered your information and analysed, now you have to represent it so that people can understand and act upon it. The trouble is that most institutional mplementation of learning analytics pays too little attention to representation. Though the research literature does have some people doing some interesting things.This is perhaps the first adoption barrier for learning analytics. If the representation is hard to understand or hard to access (or inappropriate) it won’t be used.
  • As mentioned above, we believe that learning analytics is only useful if it leads to changes in learning and teaching. It has to lead to action. The A in RAC is affordances. Or what sort of actions does the learning analytics application afford? Make more likely or less likely. How is it likely to be used to improve learning and teaching?For us, this is probably the most difficult and most important problem to be overcome and one where the least attention has been paid
  • The C in IRAC stands for change and the cyclical nature of George’s model captures this nicely. However, I wonder if the fact that it is not an explicit part of the model – more implicit in the circle – will lead people to overlook or forget about it.Certainly for us Change is an absolutely essential part of an learning analytics project. And for us that change has to apply to any and all components of the model. It’s not just practice that has to change. The information you are gathering must change as hopefully your learning analytics projects lead to improved practices and the need to ask difference questions.As these changes happen and as you learn more the Representations will change…..Affordances
  • Our last advice is that you should also pay attention to the relative amount of funding, resources and time your institution is placing on each of the components of the IRAC framework. The relative sizes of the components on this slide are not a good distribution. For us Change, Affordances, and Representation should receive a great deal more attention.If you would like to hear more specific recommendations and details about these ideas. We’ll expand a little in our workshop this afternoon but we’ll be hanging around.
  • A response to George Siemens’ email request for examples of institutions doing something. AN approach that certainly resonates with what we’re trying to suggest here.We go a few steps further in terms of identifying the limitations of the top-down approach. The very nature of learning analytics – and of e-learning and trying to encourage improvements in learning and teaching – should be seen much more as a part of the “learning” approach, than the “planning” approach.
  • Some some quick conclusions
  • There’s a very smart guy. Interaction designer, programmer, engineer, ex-Apple guy called Brett Victor. He recently gave a talk on the “Future of Programming” given on the assumption he was a programmer in the early 1970s. He introduced four or so really recent (for the 1970s) ways of thinking about programming. He then extrapolated what those would mean for programming into the future. His extrapolations illustrated many of the major flaws and limitations of current approaches to programming. Illustrating that even a very tech-heavy profession as computer programming has failed to take full advantage of many of the earlier ideas. In fact, there’s a danger that many in the profession are not even aware of these ideas.For me, this resonates a lot with institution e-learning
  • These are two of the points Victor made in his talk which I think are useful.The first connects to the on-going horseless carriage approach to the use of technology by our educational institutions. I see this when I observe colleagues beavering away recording their online lectures and attending online tutorials in Blackboard Collaborate. I see the same problem with institutions and how they approach the management and governance of e-learning and recent innovations such as learning analytics. Rather than re-think what is possible. They put the old wine in new bottles.Too much of what I see from management and its approaches to learning analytics (or any other technical innovation) is the assumption that they know what they are doing, or slightly better, that they must learn “the answer” ASAP. Rather than keeping an open mind and creating institutions that are continually exploring and experimenting with how technology can enhance and transform the practice of learning and teaching.
  • Brings me to our argument
  • These are two of the points Victor made in his talk which I think are useful.The first connects to the on-going horseless carriage approach to the use of technology by our educational institutions. I see this when I observe colleagues beavering away recording their online lectures and attending online tutorials in Blackboard Collaborate. I see the same problem with institutions and how they approach the management and governance of e-learning and recent innovations such as learning analytics. Rather than re-think what is possible. They put the old wine in new bottles.Too much of what I see from management and its approaches to learning analytics (or any other technical innovation) is the assumption that they know what they are doing, or slightly better, that they must learn “the answer” ASAP. Rather than keeping an open mind and creating institutions that are continually exploring and experimenting with how technology can enhance and transform the practice of learning and teaching.
  • Which is way we recommend that you focus your attention on lots of different and on-going safe-fail experiments with learning analytics where you are working with the academics down in the dirty realities of learning and teaching. That you use the insights you gain from this to inform the environment in which learning and teaching operates at your institution.There does need to be a level of “do it to” and “do it for” to complement this, but for us, for a field as unknown, diverse, and ever-changing as learning analytics. This is really the only way to go.
  • Our last advice is that you should also pay attention to the relative amount of funding, resources and time your institution is placing on each of the components of the IRAC framework. The relative sizes of the components on this slide are not a good distribution. For us Change, Affordances, and Representation should receive a great deal more attention.If you would like to hear more specific recommendations and details about these ideas. We’ll expand a little in our workshop this afternoon but we’ll be hanging around.
  • Of course, given that the field is so new, diverse and ever changing you are right to question everything we’ve just told you. And now is your first opportunity. Questions?
  • References to be added
  • References to be added

Moving beyond a fashion Moving beyond a fashion Presentation Transcript

  • http://www.flickr.com/photos/albertogp123/5843577306/
  • Moving beyond a fashion: Likely paths and pitfalls for learning analytics David Jones (USQ) Colin Beer (CQU) http://bit.ly/18hOYGB http://www.flickr.com/photos/dragnfly78/235652252/
  • http://www.flickr.com/photos/johnhaydon/5042881685/ Basing decisions on data and evidence seems stunningly obvious (Siemens and Long, 2011, p. 31) http://bit.ly/18hOYGB
  • http://www.flickr.com/photos/rchughtai/2121560287/ Learning analytics is essential for penetrating the fog that has settled over much of higher education (Siemens and Long, 2011, p. 40) http://bit.ly/18hOYGB
  • http://flickr.com/photos/boskizzi/3241710/ http://flickr.com/photos/boskizzi/3241710/ Management fashion is "relatively transitory collective beliefs, disseminated by the discourse of knowledge entrepreneurs, that a management technique is at the forefront of rational management progress” (Abrahamson and Fairchild, 2003) Amplified by hyperbole…, the fashionable vision may exert a strong, if transitory, normative pull among managers. (Swanson and Ramiller, 2004)
  • Fad cycle http://www.flickr.com/photos/moriza/308483890/ 1. Technological spark 2. Growing revolution 3. Minimal impact 4. Resolution of dissonance (Birnbaum, 2000)
  • http://www.flickr.com/photos/tambako/8592709246/
  • Learning Analytics !=
  • How universities will implement analytics ==
  • http://www.flickr.com/photos/lucgaloppin/6074160455/
  • http://www.flickr.com/photos/lucgaloppin/6074160455/
  • What we know about learning analytics http://www.flickr.com/photos/mikelove/2526016742/ Three paths Do it to Do it for Do it with Conclusions
  • What we know about learning analytics http://www.flickr.com/photos/mikelove/2526016742/ Three paths Do it to Do it for Do it with Conclusions
  • http://flickr.com/photos/boskizzi/3241710/ http://flickr.com/photos/boskizzi/3241710/ Oz/NZ Horizon Report Year Time Frame Label 2010 4 to 5 years Visual data analysis 2012 1 year or less (#2) Learning analytics 2013 1 year or less (#1) Learning analytics Oz/NZ Horizon Report
  • http://www.flickr.com/photos/mikecogh/5959192031/ I’m not familiar with (m)any universities that have taken a systems-level view of LA. http://bit.ly/16uz8vU Most of what I’ve encountered to date is specific research projects or small deployments of LA. I have yet to see a systemic approach to analytics use/adoptio
  • http://www.flickr.com/photos/micurs/6118627854/ data warehouses “have been around for quite some time, they have been plagued by high failure rates and limited spread or use (Ramamurthy, Sen and Sinha, 2008, p. 976)
  • http://www.flickr.com/photos/micurs/6118627854/ the vast majority of big data and magical business analy projects fail. Not in a great big system-won’t-work way… They fail because the users don’t use them. (Schiller, 2012)
  • http://www.flickr.com/photos/ktpupp/508647245/ The majority of information systems developments are unsuccessful. The larger the development, the more likely it will be unsuccessful. (Goldfinch, 2006, p. 917)
  • Fad cycle http://www.flickr.com/photos/moriza/308483890/ 1. Technological spark 2. Growing revolution 3. Minimial impact 4. Resolution of dissonance (Birnbaum, 2000)
  • Fad cycle http://www.flickr.com/photos/moriza/308483890/ 1. Technological spark 2. Growing revolution 3. Minimial impact 4. Resolution of dissonance (Birnbaum, 2000) Next sector
  • http://www.flickr.com/photos/chrisjfry/323461344/ LAK 2012 .. multidisciplinary conference for learning scientists; (computer) scientists and data/knowledge engineers; researchers in education, sociology, psychology, information science; educators at all levels; … data analysts; training and development professionals; educational and academic leaders; business leaders; [and] course management system developers and leaders (Suthers & Verbert, 2013, p. 1) It is a ‘jackdaw’ field of enquiry (Clow, 2013, p. 3)
  • http://www.flickr.com/photos/londonmatt/3163571645/ Environment Technology Teaching fundamental DSS principles like evolutionary development (Arnot & Pervan, 2005) …
  • http://www.flickr.com/photos/doug88888/4627497417/ Analytics…is about identifying and revealing what already exists The tension between innovation (generating something new) and analytics (evaluating what exists in data) is one that will continue to exist in the foreseeable future. (Siemens, 2013, p. 16)
  • http://www.flickr.com/photos/albertogp123/5843577306/
  • E-learning’s a bit like teenage sex. Everyone says they’re doing it but not many people really are and those that are doing it are doing it very poorly. Mark Brown - http://bit.ly/165UHP5 http://www.flickr.com/photos/tifotter/80099532/
  • http://www.flickr.com/photos/tifotter/80099532/
  • http://www.flickr.com/photos/tifotter/80099532/
  • http://www.flickr.com/photos/atoach/2929229111/ ..the challenge posed by learning analytics is interpreting the resulting data against pedagogical intent and the local context to evaluate the success or otherwise (Lockyer et al., 2013, p. 2) ..dearth of studies that have investigated the relationship between learning analytics and data requirements that would better assist teachers in the design and evaluation of learning and teaching practice (Dawson et al., 2011, p. 4)
  • http://www.flickr.com/photos/atoach/2929229111/ ..currently available research tools do not yet answer many questions of teachers…..causes for these shortcomings are insufficient involvement of teachers in the design and development of indicators.. (Dyckhoff et al., 2013, p. 227)
  • http://www.flickr.com/photos/sidewalk_flying/3534131757/ Learning analytics, the analysis and representation of data about learners in order to improve learning (Clow, 2013, p. 1) 1. the development of new processes and tools aimed at improving learning and teaching for individual students and instructors 2. The integration of these tools and processes into the practice of teaching and learning (Elias, 2011, p. 5)
  • What we know about learning analytics http://www.flickr.com/photos/mikelove/2526016742/ Three paths Do it to Do it for Do it with Conclusions
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • http://flickr.com/photos/tonymangan/754511201/ Pitfalls Complex and likely to fail Resistance Compliance Failures of rationality Disappearing data Loss of information Tail wagging the dog
  • http://www.flickr.com/photos/tambako/8592709246/ School of process thought Planning Learning
  • http://flickr.com/photos/tonymangan/754511201/ Author Planning Learning Weick & Quinn (1999) Episodic change Continuous change Brews & Hunt (1999) Planning school Learning school Seely Brown & Hagel (2005) Push system Pull systems Hutchins (1991) Supervisor reflection and intervention Local adjustment Truex et al (2000) Traditional design Emergent design March (1991) Exploitation Exploration Boehm & Turner (2003) Plan-driven Agile Mintzberg (1989) Deliberate strategy Emergent Strategy Kurtz & Snowden (2007) Idealistic Naturalistic
  • http://www.flickr.com/photos/tambako/8592709246/ School of process thought Planning Learning extreme pre-occupation with either can trap organisations in an unproductive state (March, 1991)
  • What we know about learning analytics http://www.flickr.com/photos/mikelove/2526016742/ Three paths Do it to Do it for Do it with Conclusions
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • http://flickr.com/photos/tonymangan/754511201/ Pitfalls The chasm Blackbox We don’t know how?
  • http://flickr.com/photos/tonymangan/754511201/ Pitfalls The chasm (Geoghegan, 1994)
  • http://flickr.com/photos/tonymangan/754511201/ Pitfalls The chasm 1. Ignorance of the gapHomogeneity 2. The technologists alliance Early adopters IT Staff Vendors 3. Alienation of the mainstream 4. Lack of a compelling reason to adopt (Geoghegan, 1994)
  • http://flickr.com/photos/tonymangan/754511201/ Pitfalls The chasm 1. Ignorance of the gapHomogeneity 2. The technologists alliance Early adopters IT Staff Vendors 3. Alienation of the mainstream 4. Alienation of the mainstream (Geoghegan, 1994) voices which promote the adoption of technology become privileged and established. These rhetorical claims espousing technology appealed to readers’ ‘vision’ and consistently emphasised innovation at the expense of reflection on teachers’ thinking and practices. (Convery, 2009, p. 25)
  • http://flickr.com/photos/tonymangan/754511201/ Pitfalls The chasm 1. Ignorance of the gapHomogeneity 2. The technologists alliance Early adopters IT Staff Vendors 3. Alienation of the mainstream 4. Alienation of the mainstream Early adopters Early majority Like radical change Like gradual change Visionary Pragmatic Project oriented Process oriented Risk takers Risk averse Willing to experiment Need proven uses Self sufficient Need support Relate horizontally (interdisciplinary) Relate vertically (within discipline) (Geoghegan, 1994)
  • http://flickr.com/photos/tonymangan/754511201/ Pitfalls Curriculum & Learning design Opinion Course Offering Results Satisfaction Based on (Lodge & Lewis, 2012)
  • http://www.flickr.com/photos/atoach/2929229111/ ..dearth of studies that have investigated the relationship between learning analytics and data requirements that would better assist teachers in the design and evaluation of learning and teaching practice (Dawson et al., 2011, p. 4)
  • What we know about learning analytics http://www.flickr.com/photos/mikelove/2526016742/ Three paths Do it to Do it for Do it with Conclusions
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • http://www.flickr.com/photos/tambako/8592709246/ School of process thought Planning Learning
  • Arguably, teachers are the primary change agents in any educational system. Teachers operate in a complex and dynamic domain the background knowledge and practices of their students constantly change, the technologies and resources at their disposal are perpetually evolving, and the guidance and directives they receive are frequently updated (Mor & Mogilevsky, 2013, p.1 ) http://www.flickr.com/photos/davidking/2202649444/
  • http://www.flickr.com/photos/joseeivissa2012/8201332964/ Lecturers who move into the online learning environment often discover that the workload involved not only changes, but can be overwhelming as they cope with using digital technologies. Questions arise, given the dissatisfaction of lecturers with lowering morale and increasing workload, whether future expansion of this teaching component in tertiary institutions is sustainable. (Bright, 2012)
  • http://www.flickr.com/photos/psd/9116635297/ ..underlined the importance of understanding context, and of involving teachers in the process of developing and deploying analytics (Sharples et al, 2013, p. 15)
  • http://www.flickr.com/photos/psd/9116635297/ Any attempt to introduce wide- scale educational analytics and accountability processes thus requires a thorough understanding of the pedagogical and technical context in which the data are generated. (Lockyer et al., 2013, p. 2)
  • http://www.flickr.com/photos/9422878@N08/7788404750/ Competitive advantage related to ICTs can only stem from the cognitive and organisational capability to convert such systems, applications and data into practical, situated, and unique knowledge for action. (Ciborra, 2002 )
  • http://www.flickr.com/photos/53825985@N02/7471463464/
  • http://www.flickr.com/photos/53825985@N02/7471463464/ (Siemens, 2013, p. 13)
  • http://www.flickr.com/photos/53825985@N02/7471463464/ (Siemens, 2013, p. 13) Information
  • http://www.flickr.com/photos/53825985@N02/7471463464/ (Siemens, 2013, p. 13) Information Representation
  • http://www.flickr.com/photos/53825985@N02/7471463464/ (Siemens, 2013, p. 13) Information Representation Affordances
  • http://www.flickr.com/photos/53825985@N02/7471463464/ (Siemens, 2013, p. 13) Information Representation Affordances Change
  • http://www.flickr.com/photos/53825985@N02/7471463464/ (Siemens, 2013, p. 13) Information Representation Affordances Change
  • http://www.flickr.com/photos/53825985@N02/7471463464/ At Emory University….encourages the proliferation of various approaches to learning analytics, empowering faculty, students and administration to use analytics in a way that acknowledges the idiosyncrasies associated with disciplinary differences and stakeholder perspectives. A top-down systemic … approach…has the potential to alienate faculty (and learners), while at the same time limiting itself to institutional outcomes that are common and measurable (i.e. GPA and retention rates) http://bit.ly/16uz8vUTimothy Harfield
  • What we know about learning analytics http://www.flickr.com/photos/mikelove/2526016742/ Three paths Do it to Do it for Do it with Conclusions
  • http://worrydream.com/ http://worrydream.com/#!/db
  • http://worrydream.com/ http://worrydream.com/#!/db 1. Technology changes quickly, peoples’ minds change slowly Organisations change even slower
  • http://www.flickr.com/photos/tambako/8592709246/ School of process thought Planning Learning
  • http://worrydream.com/ http://worrydream.com/#!/db 1. Technology changes quickly, peoples’ minds change slowly 2. The most dangerous thought you can have as a creative person is to think you know what you’re doing Organisations change even slower
  • Student Teachers’ Strategies Teaching/ Learning Context Model of university teaching (Trigwell, 2001) http://www.flickr.com/photos/dnorman/177883109/ Teachers’ Planning Teachers’ Thinking
  • http://www.flickr.com/photos/53825985@N02/7471463464/ (Siemens, 2013, p. 13) Information Representation Affordances Change
  • http://www.flickr.com/photos/dullhunk/202872717/ http://bit.ly/18hOYGB
  • http://www.flickr.com/photos/stuckincustoms/4326541391/ Abrahamson, E., & Fairchild, G. (1999). Management fashion: Lifecycles, triggers and collective learning processes. Administrative Science Quarterly, 44(4), 708–740. Arnott, D., & Pervan, G. (2005). A critical analysis of decision support systems research. Journal of Information Technology, 20(2), 67–87. doi:10.1057/palgrave.jit.2000035 Birnbaum, R. (2000). Management Fads in Higher Education: Where They Come From, What They Do, Why They Fail. San Francisco: Jossey-Bass. Bright, S. (2012). eLearning lecturer workload: working smarter or working harder? In M. Brown, M. Hartnett, & T. Stewart (Eds.), ASCILITE’2012. Wellington, NZ. Ciborra, C. (2002). The Labyrinths of Information: Challenging the Wisdom of Systems. Oxford, UK: Oxford University Press. Clow, D. (2012). The learning analytics cycle. Proceedings of the 2nd International Conference on Learning Analytics and Knowledge - LAK ’12, 134–138. doi:10.1145/2330601.2330636 Clow, D. (2013). An overview of learning analytics. Teaching in Higher Education, (August), 1–13. doi:10.1080/13562517.2013.827653 Dawson, S., Bakharia, A., Lockyer, L., & Heathcote, E. (2011). “Seeing” networks : visualising and evaluating student learning networks Final Report 2011. Main. Canberra. Dyckhoff, a. L., Lukarov, V., Muslim, A., Chatti, M. a., & Schroeder, U. (2013). Supporting action research with learning analytics. In Proceedings of the Third International Conference on Learning Analytics and Knowledge - LAK ’13 (pp. 220–229). New York, New York, USA: ACM Press. doi:10.1145/2460296.2460340 Elias, T. (2011). Learning Analytics: Definitions, Processes and Potential. Learning. Geoghegan, W. (1994). Whatever happened to instructional technology? In S. Bapna, A. Emdad, & J. Zaveri (Eds.), (pp. 438–447). Baltimore, MD: IBM. Goldfinch, S. (2007). Pessimism, computer failure, and information systems development in the public sector. Public Administration Review, 67(5), 917–929.
  • http://www.flickr.com/photos/stuckincustoms/4326541391/ Lockyer, L., Heathcote, E., & Dawson, S. (2013). Informing Pedagogical Action: Aligning Learning Analytics With Learning Design. American Behavioral Scientist, XX(X), 1–21. doi:10.1177/0002764213479367 Lodge, J., & Lewis, M. (2012). Pigeon pecks and mouse clicks : Putting the learning back into learning analytics. In Mark Brown, M. Hartnett, & T. Stewart (Eds.), Future challenges, sustainable futures. Proceedings ascilite Wellington 2012 (pp. 560–564). Wellington, NZ. March, J. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. Mor, Y., & Mogilevsky, O. (2013). The learning design studio: collaborative design inquiry as teachers’ professional development. Research in Learning Technology, 21. Sharples, M., Mcandrew, P., Weller, M., Ferguson, R., Fitzgerald, E., & Hirst, T. (2013). Innovating Pedagogy 2013: Open University Innovation Report 2. Milton Keynes: UK. Siemens, G. (2013). Learning Analytics: The Emergence of a Discipline. American Behavioral Scientist, (August). doi:10.1177/0002764213498851 Siemens, George, & Long, P. (2011). Penetrating the Fog: Analytics in Learning and Education. EDUCAUSE Review, 46(5). Suthers, D., & Verbert, K. (2013). Learning analytics as a middle space. In Proceedings of the Third International Conference on Learning Analytics and Knowledge - LAK ’13 (pp. 2–5). Swanson, E. B., & Ramiller, N. C. (2004). Innovating mindfully with information technology. MIS Quarterly, 28(4), 553–583. Trigwell, K. (2001). Judging university teaching. The International Journal for Academic Development, 6(1), 65– 73.