In 2011-2013 the Australian Government Office for Learning and Teaching (OLT) provided funding for a project aimed at exploring Blended Synchronous Learning, which entails bringing together on-campus and distributed learners to partake in shared, real-time experiences. The project focused on three technologies—videoconferencing, web conferencing and 3D virtual worlds—as well as learning designs involving the use of these technologies to simultaneously engage students and teachers in collaborative activities irrespective of their location. An Australia and New Zealand-wide scoping survey was conducted, and seven case studies were followed and investigated through participatory evaluation.
The Blended Synchronous Learning project team is pleased to announce that the OLT has approved the Blended Synchronous Learning Handbook without condition and it is now freely available for download from http://blendsync.org/handbook .
The Handbook includes a Blended Synchronous Learning Design Framework that offers pedagogical, technological and logistical recommendations for teachers attempting to design and implement blended synchronous learning lessons (see Chapter 14). It also includes a Rich-Media Synchronous Technology Capabilities Framework to support the selection of technologies for different types of learning activities (see Chapter 4), as well as a review of relevant literature, a summary of the Blended Synchronous Learning Scoping Study results, detailed reports of each of the seven case studies, and a cross-case analysis.
For those who are interested, the BlendSync Final Report and External Evaluation Report are also from the OLT website at the following URLs:
A list of academic papers and links to recordings of presentations that have arisen out of the project is posted at http://blendsync.org/publications .
The project team would also like to take this opportunity to invite all those with an interest in area to join the Blended Synchronous Learning Collaborator Network to abreast of events and updates in the future. Instructions on how to do this can be found at http://blendsync.org/network . There is not a lot of traffic from the network mailing list (usually less than one message a month), and those who are on the list can unsubscribe at any stage.
The BlendSync Team: Matt Bower (Macquarie University), Gregor Kennedy (The University of Melbourne), Barney Dalgarno (Charles Sturt University), Mark J. W. Lee (Charles Sturt University)
Web: http://blendsync.org Email: firstname.lastname@example.org
Thanks for agreeing to do this interview, Nick. First of all, can you tell us a little about yourself and your research at Stanford & Ubisoft?
I’ve been study online games and virtual worlds for almost 15 years. I began with web surveys of online gamers, exploring player demographics, motivations, and in-game experience. At Stanford where I completed my graduate degree, I worked with Jeremy Bailenson to explore how avatars influence us in immersive virtual environments. And at the Palo Alto Research Center and Ubisoft, Nic Ducheneaut and I combine survey data with game server data to better understand players.
So is that right that your research in some ways ratified Richard Bartles’ work?
Player motivations in online games was a topic I explored in my early web surveys. I would say that Richard’s work formed the foundation for my statistical explorations. I wanted to create a robust tool for assessing those motivations and use factor analysis to understand the statistical structure behind player motivations. And that wouldn’t have been possible without Richard’s insightful work on the topic.
In the beginning part of your book you take some time to discuss the results of your Daedalus Project - an online survey of the motivations for why people play games - including hard work! There are some rather interesting and complex dynamics surrounding gender, culture, and stereotypes that people have that they bring into the online gaming world -- what lessons has your work revealed that might be of some use to educational researchers and those designing Games for Social Good?
Games and virtual worlds don’t necessarily encourage people to reimagine themselves or the world around them. For example, the presumed openness of Second Life has largely been used to create name brand knockoffs and exaggerated bodies. One of the central arguments I make in the book is that virtual worlds often encourage us to replicate the status quo.
One speculative direction that I think may be fruitful is to stop insisting that virtual worlds replicate human bodies in the everyday (or fantasy medieval) world. Almost all virtual worlds have one user controlling one avatar, and that avatar inevitable is human (or humanoid). Jaron Lanier’s early experiment of putting people into lobster avatars (i.e., 10 total legs and arms) seems so novel in comparison with how virtual worlds tend to used nowadays. What about putting students in red blood cell avatars in a human body? What about putting students in a virtual world where avatars get younger as they age (i.e, a Benjamin Button world)? How might society function differently in such a world?
Can you tell us about your Research Methods and your data?
I think one of the pivotal moments in my research career happened in my sophomore year psych methods sequence in college. In the personality psychology section, my professor, Doug Davis, taught us how to hand-code HTML and create web pages (this was 1998) alongside the Big 5 personality factors. Ever since then, I saw technology as both a thing to study as well as a tool to study things with.
When I ran my own web surveys of online gamers, I picked up MySQL and PHP to create the web frontend for sharing the findings. At Stanford, I learned and honed my existing graphics and programming skills to design the logic and flow of my experiments in immersive reality. And the same thing happened at PARC and Ubisoft, I further developed my database skills and data analysis skills in a big data setting.
So the scale of the data kept changing, and the tools I was using kept changing, but that intersection of technology and psychology (as both the research topic and the research tool) has always fascinated me.
On the Proteus Effect, specifically - if I might quote from your book, that “we unconsciously and automatically observe our own behavior to make sense of how we feel about something” -- this for some reason when I read it brought to mind the James Lange Theory of Emotion -- that perhaps what’s going on is that people experience a “physiological change” that they witness through their avatar and that creates a biological reaction. I don’t know, what do you think is going on here: what are the mechanisms at play for the Proteus Effect? ha ha:
I base the effect on Self Perception Theory. So studies in the physical world have found, for example, that athletes wearing black uniforms are more aggressive in the field. That’s what led me to wondering if avatars were a sort of “super” uniform and what the effects might be.
Your book goes into some detail about what you & your team have identified as various tools and techniques for modifying people’s thoughts and behaviors. I think this is of real interest to those of us working on immersive learning environments. Can you tell us more about that?
We’ve looked broadly at two directions: putting someone in a virtual body that isn’t theirs, and replicating someone virtually with some degree of control taken away (a doppelganger of sorts).
So under the first direction, we’ve found that people put in attractive avatars walk closer to and disclose more information to virtual strangers. And people put in taller avatars negotiate more aggressively in a bargaining task.
In the second direction, my colleagues have found that watching your virtual doppelganger exercise in a virtual world makes you more likely to exercise in the physical world. And seeing a digitally aged version of yourself encourages you to save up more for your retirement.
In traditional psych experiments, researchers have to carefully construct their questions and their experiments because they don’t get second chances and they only get what they ask for. In immersive environments, as you know, we have the opposite problem: researchers are DROWNING in data. How do you delimit your data and parse through it to make sense out of it?
I think big data tends to scare psychologists used to lab studies with 50 samples and a small handful of dependent variables, but the discipline that psychologists are trained with actually comes in handy.
One of these is starting with the research hypotheses rather than the research data. Big data actually forces us to be more disciplined about how we approach the questions of interest, how to prioritize them, and which variables are crucial. A psychologist is used to testing hypotheses, finding incongruences, and reformulating the question or adding control variables. This discipline comes in handy with big data.
Another is the often unassuming practice of shifting quickly between conceptual variables and operationalized variables. The things we care about in psychology—learning, fear of death, trust—are all abstract things that cannot be directly measured. So we learn to operatonalize to measurable proxies. In big data, it is easy to get swamped with the debris and the flotsam. What’s critical is understanding how to abstract up to meaningful conceptual variables and making sure that your analysis and thinking happens at the conceptual level rather than being stuck at the ground level.
Do you have any advice for early career research professionals looking to get into immersive environments? What would you recommend?
Develop a unique combination of skills to approach research questions and industry problems. These are often combinations of technical and theoretical expertise that are uncommon due to the way that academia and industry are currently structured.
For example, Nic Ducheneaut and I at Ubisoft are constantly on the lookout for people who have a social science grounding as well as the ability to handle big data. That kind of skillset is rare but crucial for making sense of game data.