Learning From Buildings

How Buildings Learn: What Happens After Theyre Built by Steward Brand

How Buildings Learn: What Happens After They're Built by Stewart Brand

Buildings shelter, store, display, divide and unify people and their things. But buildings do something else as well that we don’t always think of: buildings learn. They adapt to the changes of their environments, take up new functions, and change their existing purpose. During a recent event of a book club for user experience (UX) professionals in San Francisco, we discussed the book, How Buildings Learn: What Happens After They’re Built by Stewart Brand (Penguin Books, 1995). Here are some of my thoughts about the book:

1. Cycle of life for buildings.
Run-down and abandoned low road buildings (i.e., vacant downtown office buildings, DIY terraces, left behind military barracks, vacant shopping malls) provide cheap alternative spaces for artists of all kinds to create their own workspaces, large exhibition halls, and highly personalized socializing environments. Examples can be found all around the world, including Detroit’s Heidelberg project, gentrification in East London’s Shoreditch neighbourhood, or Budapest youth’s preferred alternative nightlife spots (such as the Kuplung art bar). These buildings behave like adaptive biological host organisms that invite often low maintenance artists as their first inhabitants. The artistic ‘byproducts’ of these tenants will, in return, attract trendy shops, restaurants and eventually, rich estate developers who convert the run-down buildings into high social class homes and offices. New owners move in, artists move out.

Painted Ladies in San Franciscos Alamo Square

Painted Ladies in San Francisco's Alamo Square

2. Change is good, change is survival.
There are over 17,000 Victorian and Edwardian houses in San Francisco, the Painted Ladies being the most typical example. Even though their painted colours and ornaments reflect a distinct architectural style, they all changed with time and specific functions. The buildings evolved, and the changes took very distinct physical adaptations. Some became warm, cosy homes for individuals and families living in them, while others serve as community centers or retrofitted shops. The physical evolution of buildings is never finished – says Christopher Alexander, an architect interviewed in the book – they need to be flexible in order to survive and stand for hundreds of years. At the book club, we quickly came to an agreement that instructional or webdesign, although created for much shorter period of time, goes through the same iterative design process, ideally even after its deployment, whereby everything about the website gets constantly changed down to its very foundation.

3. Maintenance is the real ghost in haunted houses.
As we learn from Brand, the biggest enemy for buildings is water. He gives endless examples of damage caused by broken pipes, unventilated rooms, dripping ceilings, frozen windows. It becomes particularly dangerous when the structural changes effect the health of the inhabitants. Think of the allergic reaction triggered by mold due to water damage, or other risk factors, such as asbestos covering the pipes in your basement linked to cancer. Maintenance of buildings is costly and often overlooked aspect of initial building design. A study by Dr. Ambrose at the University of Sussex, quoted in the book, found that just 5% more money spent at the time of construction on implementing higher standards long-term safety measures could go far in preventing building related medical conditions, such as asthma and significantly reduce associated health treatment and educational costs. I wonder if such rule of thumb could be implemented to instructional/webdesign to advocate for better accessibility, human factors, ergonomics and related usability considerations.

Even if you don’t have time to read this book, I’d recommend the video version made by the BBC on the chapter related to Maintenance:

Creativity, dreams and mobile robots

Dennis Hong (RoMeLa, Virginia Tech) in his TedxNASA talk in September 2009 talked about biologically inspired tripedal robots, smart wall climber robots, cheap hydraulic arms, anthropomorphic football player humanoids, and even an unmemorably named artificial amoeba that is capable of chemically induced locomotion. His imagination of designing such autonomous mobile robots is not limited by the fact that very few of these exact motions exist in nature (i.e., take his 3-legged STriDER for example).

However for a cognitive psychologist, the really cool stuff is not these futuristic technological solutions, but Hong’s self-explanation about the source of his creative thinking when around 11:55 he asks himself a question: “Where do we come up with these ideas?”

He identified 5 sources of creativity:

  1. Dreams

Inspiration from one’s own dreams is what he calls out first. Every social scientist should be relieved that finally a real computer scientist dares to talk about the necessity of such soft human processes as dreams in the process of creative thinking. At nights when Hong goes to bed and about to fall asleep, he jots down on a paper notepad his wildest ideas (“..I scribble everything down and draw things before I go to bed”, 12:53). The next morning, he deciphers the ideas. Most days, there’s nothing on the page or nothing interesting, but occasionally he has something that he call a “Eureka moment”. When it happens, he logs these ideas carefully on his computer. What happens to these Eureka-ideas? Hong uses them to write RFPs (Request for Proposals) for his future research projects. In other words, he already has some answers for upcoming research questions and doesn’t have to wait for the inspirations to come.

2. Collaborations

Dreams on a group level could be called brainstorming sessions. Since individual ideas are not enough, Hong and his group have group brainstorming sessions. To facilitate discussion and make sure that students don’t feel intimidated, the golden rule is that nobody can criticize the other person’s ideas. All sorts of wacky ideas fly around, just like in one’s dreams. Once these ideas are recorded, people can decide which idea to pursue.

3. Education

Does school education really kill creativity? The fact is that to challenge the grand questions of science, you need tools. These tools are maths, physics, linear algebra, biology, etc. (neuroscience and philosophy are my additions to this list). While schools may not promote creativity per se, they provide the essential basis for students.

4. Work hard

The really good indicator of a creative and productive researcher labs – according to Hong – is that students and researchers are working on their ideas 3am in the morning. Not because they have to, but because they enjoy it.

5. Play hard

Finally, he admits that having lots of fun is the key. No need to explain this to anyone who has ever felt the joyous moment of a research Eureka-moment in their life before…

What makes mobile education work?

Effective deployment of mobile learning technology seems to require sufficient parental involvement and other sociometric support, according to the main finding of our recently submitted paper at the Stanford POMI in ED group.

Mobile technology, in particular, with its low cost and accessibility, has great potential to provide access to or supplement education in underdeveloped areas. Given that mobile learning devices could be effective in supplementing education particularly in a community with a poor educational infrastructure; this study selected 80 second-grade (7-8 years old) primary school students from an urban slum area and another 80 students in a rural village near the Mexico-USA border in the state of Baja California, Mexico. Both schools lack educational and technology resources and the general socio-economic status of the students is low. We examined whether mobile learning devices could have a differential effect in supporting students’ literacy learning skills in these two schools with their unique socio-economical strata.

Students in the experimental groups in both schools were equipped with a mobile learning device called TeacherMate with a headphone, preloaded with 18 mobile e-books (see Figure 1).

Figure 1. Students helping each other with the mobile learning device

In contrast, the control groups were only participating in classroom lectures without the supplement of our mobile devices. A standard Spanish language literacy pretest assessed all students’ achievement scores in September 2008 and the same test was administered 16 weeks later in a posttest. In addition to these quantitative data, we interviewed parents and educators as well for qualitative purposes.

The findings suggest that students in the rural village have benefited substantially more from mobile technologies than urban school students (see Figure 2). These devices have contributed to better literacy scores and added an extra enrichment activity tool in class. Considering the fact that the availability of educational resources at the rural school was even less than at the urban slum school (i.e., books, computer, Internet access, etc.), the extra educational resources and learning opportunities served these children more effectively.

Figure 2. Significant difference between the Experimental posttest groups at the two schools demonstrating that students with the TeacherMate mobile learning device in the Rural school (Rural Experimental) had higher literacy achievement scores than Urban school children also using the mobile learning technology (Urban Experimental).

Figure 2. Significant difference between the Experimental posttest groups at the two schools demonstrating that students with the TeacherMate mobile learning device in the Rural school (Rural Experimental) had higher literacy achievement scores than Urban school children also using the mobile learning technology (Urban Experimental).

The interviews revealed that the rural school parents pay more attention to the education of their children. The number of answers reflected that 9 in 10 of the rural school parents were aware of the mobile learning project taking place at school, whereas only slightly more than 1 in 10 of the urban school parents knew about the project. Additionally, the rural school parental involvement in education is much higher with 5 hours a week spent with the children compared to the urban school average weakly less than 2 hours. Finally, the average combined income of the rural school is slightly higher (i.e., average $720/month) than that of the urban school (i.e., average $410/ month).

In contrast, there was no evidence of interaction with parental education levels (the overall education experience of the rural parents was less than that of the urban slum school parents), the experience of teachers or school principals (teacher in the rural school also had 2 years less teaching experiences than the teacher of the urban school), or the teacher’s perception or preparation of the technology (teacher in the rural school did not embrace technology in the classroom).

In summary, the programmable open design of our mobile learning technology (i.e., Linux, Flash) enables the development of other mobile learning activities to increase phonemic awareness skills of children at multiple levels and offer opportunities to practice reading through interesting content and entertaining activities.

More people in a museum with Web 2.0

Nina Simon

Nina Simon

What makes a museum space good? For Nina Simon, the author of Museum 2.0 blog, the answer is simple: the more people use the exhibit spaces to interact with each other the better. Nina was giving an excellent talk recently at the BayCHI March meeting in the Palo Alto Research Center (PARC). She discussed issues of museum space design that engage visitors more by applying concepts from Web 2.0.

Museums are more and more looking for ways to break up with the image of being traditional and authoritative. In fact, most modern institutions shift towards a more participatory approach, where visitors are active part of the exhibits. Nina takes her examples from the social web (i.e., Facebook, Twitter, etc.) where the 3 core challenges are (1) participation inequality, (2) amateur content, and (3) limited tool for social interaction.

The Art of Participation exhibition at the SFMOMA (photo from SFMOMA website)

Social participation in a museum context refers to the use of the exhibited objects to facilitate interaction between the visitors. One simple example was The Art of Participation exhibition in the SFMOMA that opened in Winter 2008. What it did was to provide a social proxy (i.e., the use of different random objects) that allowed interaction. The key concept here is ‘scaffolding‘ or making the visitors feel safe about whatever they’re planning to do. Nina met a stranger at this exhibit, George, who went so far with participatory interaction that he took off his shirts for a photo (see half naked guy on her lecture slides with oranges in his hat).

Visitor feedback is another issue in museum spaces. A simple notebook where people can write their amateur thoughts is often turned into meaningless. The way to look at this problem for Nina is to take the Web 2.0 approach and allow the concept (i.e., notebook) to evolve into something better. In Worcester City Gallery and Museum, UK the weekly order of painting exhibits were determined by the votes of the visitors. It became so popular that people of the town queued every Saturday evening to see what the new order was. This is a great example of how to change ‘feedback 1.0′ into ‘feedback 2.0′

Entrance of the Facing Mars at the Ontario Science Centre (photo by Nina Simon)

Turnstile entrance at the Facing Mars exhibit at the Ontario Science Centre (photo from Museum 2.0 blog)

Asking a good question is another key to interaction. At the Ontario Science Centre, the turnstile was a voting mechanism to answer the simple question: “Would you go to Mars?” Needless to say, at the entrance, 2/3 of the visitors answer yes. It’s a personal (i.e., you), social (i.e., counting #) and fully participatory spatial design. As people learnt about the harsh physical conditions on Mars, and re-answered the question when exited the exhibition, 2/3 of the visitors didn’t anymore want to go to Mars. This is an objective and interactive way to assess visitors’ knowledge increase.

Exhibited objects themselves are perfect transitional spaces even for complete strangers to meet. Museum design needs to provide a scaffolding space that encourages social engagements. On the web, social profiling is a way to go about this. By giving visitors ‘social objects’ (e.g., a personality character badge — see Athena on Nina’s slide), it becomes acceptable to share experiences even if they don’t know each other. In social psychology, this is explained by the social identity theory (Tajfel & Turner, 1979). The key is giving social scaffolding to people that makes them feel comfortable. Human-Library.org project is another great example of how this can happen in a very simple but powerful way.

An audience question targeted the actionable implications of Nina’s work. She said that when she teams up with architects to design social museum spaces, she talks about how to create an exhibit space where people feel good together. Museums are just not optimal when there’s nobody inside, but they get better when a good deal of visitors are there. She paraphrased a quote by Tim O’Reilly saying that “web 2.0 is a software that gets better the more people use it.”

$60,000 for a life of happiness

Clearly, the scientific community has taken an increasing interest in the research of happiness and well-being. In February 2010, the Nobel prize laureate, behavioural economist Daniel Kahneman gave a TEDTalk in this topic. The main argument of this talk was that happiness and well-being are indeed two very different notions.

Kahneman introduces two types of self in his talk: the experiencing self and the remembering self, and he demonstrates with different examples that these selves need to be analyzed quite differently. To understand the difference between the two, consider the following thought experiment. Think of your next dream vacation spot! Now, what if you were told that you won’t have any pictures or videos afterward and you were injected with an amnesic drug to forget all that happened to you during that vacation. Would you still choose the same vacation spot or would you change your choice? The example demonstrates a conflict between your experiencing self and remembering self.

Painting by Norman Rockwell (1894-1978), American painter
Triple Self-Portrait by Norman Rockwell (1894-1978)

However, it is unclear for me whether these mechanisms of our consciousness are functionally separate from one another or they are rather two sides of the same coin. It may well be that the experiencing self focuses on the ‘here-and-now’ with the acquisition, filtering and comprehension of the information; whereas the remembering self is concerned with the organization of ‘past’ events. But does this mean that one can exist without the other? Would this be the basis of amnesia? Wouldn’t it be more plausible to assume a single episodic memory that consolidates new information with existing self-knowledge?

Kahneman -the ultimate expert about human cognitive biases- also talks about the ‘happiness bias’. His example, is that people are happier in California not because of the good climate, but because they contrast themselves with living conditions elsewhere, for example in Ohio. Although Californians’ experiencing self might not be happier at all compared to Ohioans, people’s remembering self here in the West coast generally think that we are happier. Sort of a confirmation bias, whereby one interprets information in a way that confirms one’s preconceptions.

Finally, we hear in the lecture about a new Gallup study (couldn’t find the reference…does anyone have it?) that finds that in the US, the average income of $60,000 is a cut-off point for experiencing happiness. Above this income, the experienced levels of happiness is flat, but below this amount, the perception drops linearly. This shows that “money doesn’t buy you happiness, but the lack of money buys you misery”. For the life-evaluating remembering self, it’s a different story and the more money you had in your life the happier you remembered yourself.

POMI2020 retreat from a non-techsavvy perspective

Programmable Open Mobile Internet (POMI2020) is an interdisciplinary research program at Stanford University. It is part of a larger initiative called CleanSlate and funded by the NSF. The key players in POMI2020 are Stanford professors largely from the computer sciences, such as Guru Parulkar and from other auxiliary departments, such as the School of Education.

In today’s POMI retreat meeting in Palo Alto, CA the presentations were promising more interconnected and highly decentralized technological frameworks by 2020. Interestingly, however, the issues that advisors such as Bob Iannucci (formerly Nokia), Rick Rashid (founder of Microsoft Research) and Bill Raduchel (formerly AOL) brought up were fundamentally human-related questions, not so techsavvy ones.

In the first set of presentations, Monica Lam (Stanford Computer Science Dept.) and her team of graduate students presented an open-access database platform (SocialLite) that is being developed in order to collect and formalize social and personal information such as friendships, emails, and photos. This is an effort to overcome the limitations in FaceBook-type social networks that only provide “shallow friendships on a centralized datapark and does all this for profit”. Monica’s suggestion is to build more ad-hoc, mobile, multi-player apps that sit on decentralized personal cloud butlers (as opposed to a single public cloud) and communicates with each other via formalized data queries (e.g., FriedOfAFriend-queries; FOAF). The advisors, however, raised the issue that this effort comes down to the ages-old question of how to standardize representations digitally? Or as Bob Ianucci asked which one wins, the algorithm or the human eye? Until the researchers focus merely on computer-to-computer and not as much on computer-to-human communications, there is little hope for a revolution.

Our group from the School of Education, led by Paul Kim (CTO at Stanford) led the second set of presentations. The starting point was an analysis of the mobile industy (based on the evolution model by Fine, 1evolution of mobile market998). A recent survey of industry leaders and developers suggest that the currently expensive and integral mobile technologies will move into a cheaper and more modular market phase, inviting more mobile users (well exceeding the currently already 4 billion!) and trigger even greater interest in content development communities. This cheap and modular market will make mobile technologies increasingly available, especially in underdeveloped countries of the World, like Africa or parts of India. A project paper about this model-based prediction is on its way to publication soon.

Current in-progress educational applications were presented accordingly by Aiditi Goyal and Theresa Johnson (two grad students in our PomiED group): WeClick – an open-source, platform independent clicker app to be used in classrooms; Environmental Sensing Network (ESN) is a sensor-based science project utilizing design-based teaching methods. Questions from the audience were focusing on the costs and wireless communication issues. I was glad -but slightly disappointed at the same time- that the usability and educational aspects (two that I had some impact) did not gain any criticism.

After the first coffee break, Gabriel Takacs’ (Stanford) from the lab of Bernd Girod (Stanford Electrical Engineering; on the picture) presentation was about an automated image tracking & recognition algorithm that performed locally on a mobile phone. His algorithm is quicker and less data heavy than existing solutions which usually send full images over the network. Graduate students of the team demonstrated mobile applications that recognized foreign DVDs or labeled parts of a building. After identification, the system also linked the information with how much others in the person’s social network liked it. Neat! Check out their cool YouTube demo here. My association about this project was that they are doing what the human eye does — preprocess the information before it arrives to the visual cortex and makes it quick and easy for higher level cognition to match features.

The final presentation block of the morning session was by John Mitchel (Stanford Computer Science). He talked about http://courseware.stanford.edu, a work-in-progress collaborative and decentralized CMS. The idea is to work between institutions (e.g., Stanford & USD) and have open-access materials. What I’m not sure was how different this approach is to other systems, say Moodle. Bill Raduchel raised another issue about copyrights, which could be a real issue for open-access. Eric Conner presented a Mobile Courseware application that is an iPhone equivalent of our team’s weClick approach. Three major features: vote, Q&A and course-notes. I’m really looking forward to see this in action and potentially collaborate with John & Eric!

I wish I could have stayed for the afternoon session, as I really enjoyed interacting with these amazing professors and grad students, but I had to get back to San Francisco before the Sun went down.

Life-logging

Scientific studies on memory are usually focusing on how people remember things. Applied technologies are using these models to increase how much or how well we can recall about the information that surrounds us. As both theory and technology develop at an increasing speed, we see how the human mind becomes extended and embodied into its environment (Clark, 2008).

My PhD supervisor, Itiel Dror and Steven Harnad (2008) explained this process as a natural continuation of how all cognizing agents -let them be biological or artificial- are offloading their cognition into different cognitive technologies. The boundaries between the memories in my head and the ones on this blog have become fuzzy. Please, don’t think of me as a cyborg with microchips on my temporal lobe, but rather someone, who searches unfamiliar things in Wikipedia and keeps a good amount of his data in the Cloud.

Total Recall by Gordon Bell & Jim GemmellA new book with the cheesy title of Total Recall, written by Gordon Bell and Jim Gemmell, two senior researchers at Microsoft, show how far this offloading can push the limits of our imagination. They present their MyLifeBits project that digitized all documents, photos, external memories of Bell so that he could truly become paperless and uncluttered ‘both in his head and on his desk’. But they went further and since 2001, Bell has also attached a SenseCam and a GPS on his body to record and log all life events, meetings, trips, emails and telephone conversations that he faces. This is his personal life’s chronicle, which he calls ‘life-logging’. Here’s a long interview video with the authors.

As I’m reading through the book, arguments are firing to convince me that being able to life-log gigabytes of information per month about my own life and smart-search it back in its exactness all that happened with me via time-place concept tags are the best things the modern human can do. To overcome our mind’s limited memory capacity and extend it into a perfect e-memory is the revolution on our doorstep. It is the deliberation of humankind from its mortal biological chains.

Why is it that it somehow makes me feel uneasy? Because it’s just new as computers or televisions were in their times? Maybe. But the first thing that I could think of was a very human psychological mechanism: forgetting. I feel blessed that I can forget and that every day I do so. Even if the research on repression and trauma is still controversial, I feel reassured that most parts of my life will disappear from myself and from other human beings. Not because I’m not happy with my life, but because in most times, I want to reconstruct and not review my own memories.

Memory reconstruction gives me integrity and a sense of who I am. I think the source of my uneasiness about Total Recall comes from a lack of trust in the SenseCam, in contrast to a self-deceitful comfort that my limited mind’s distorted camera has provided to me in the past almost thirty years.

Lastly, the anecdotal evidence which suggests that those who survived a near-death moment experienced a video of their life flickering in front of their eyes makes me suspicious that our mind is in fact not as much limited in its capacity as we thought. It may actually record everything that we encounter, but perhaps what makes us human is that we’re not capable (yet) to do a Total Recall. The real question is still : why?

Kurzokurtic development

Ray Kurzweil knows the future. He’s the oracle of technological development or as he likes to call it technological singularity. The New Oxford American Dictionary defines singularity as “a point in the future (often set at or around 2030 A.D.) beyond which overwhelming technical changes (especially the development of superhuman artificial intelligence) make reliable predictions impossible.” But what exactly those reliable predictions?

Since only Kurzweil knows how to look forward in time, everyone else is left with one option: look back to the past. Take for example February 2005, when Kurzweil gave an inspiring talk at Monterey, CA as part of TedTalk.

This talk teaches us about our current present in 2010. Let us see how did the kurzweilian utopia with exponential developmental curves realized itself. Apparently, we have cheap, decentralized, renewable solar panels transforming the Sun’s power into local energy banks for each households. No families worry anymore about gas prices. We barely hear about those  infamous oil giants, whose lobby of certain political agendas used to set gas prices and decided which country deserves democracy and which don’t.

We have almost reached the end of Moore’s law, and surely by 2022 the prediction of the famous founding father of Intel will be outdated. Microchips will soon stop halving in size and doubling in their processing performance. Lucky for us, however, the end of Moore’s law doesn’t mean the end of exponential (or as these days we often refer to kurzokurtic) technological development. A paradigm shift is knocking on our door in the form of nano-biotechnology, whereby not only our bloodstream will be populated with tiny robots that make us swim much faster than today, but biochips will change motherboard architecture – probably until 202* (TBA date).

Computers have definitely disappeared from our lives. To be precise, they didn’t disappear, they shrunk, got embedded into our clothing, or we don’t really perceive them as we’re by now fully immersed in virtual realities. I’m actually typing this on a keyboard in SecondLife that only exists for me since it’s projected directly onto my retina and the only thing that reminds me of the physical city of San Francisco is an augmented image of the Golden Gate bridge – part real, part virtual.

Naturally, we know that this is only the beginnings. The latest deadline for a “full maturity of these predictions” is 2029. By that date, we’ll have finished the full merge of human-computer technologies. Our brain will be fully reverse engineered, recreated and entangled. Once and for all Hofstadter will be proven wrong: our brain is smart enough to understand its complexity.

P.S.: If your reality in 2010 is not as described above, adjust your own reality to a more kurzokurtic one… Send me an email and I reply how… Maybe in 2029.

GPS truth to be revealed

Unlike most of the blogsphere today, I’m not going to come up with another witty joke about how poor Apple’s name choice was for the iPad. Instead, let’s focus on a recent news about a research initiative to investigate the “the impacts of sat navs on spatial attention and memory while undertaking a complex task such as driving” (Agarwal quoted by The Press Association).

These researchers in the UK look into one of my favourite topics of human navigation: the dynamic balance between learning about and acting upon our spatial environment. When visiting a new city or driving on unfamiliar roads, our brain takes up information in a distinctively different fashion than when we travel the same well-known route to our parents’ house as we have done thousands of times since our childhood (literally, different neural formations and pathways are activated in our brain, see Hartley et al., 2003).

Exploring new side streets versus steering towards familiar neighbourhoods, either consciously or not, is a choice that we make every time we travel. The analysis of the patterns in which human explorers make these choices show that in addition to the obvious constraints of the environment (e.g., availability of alternative roads), people also have a personal preference of how they like to get to their destinations (Makany, 2009). Some of us prefer the shortest routes, while others are more adventurous types. This diversity of individual navigation choices creates beautiful complexity for social mobility patterns (Gonzales et al., 2008).

What is it have to do with GPS and sat navs? Most of these technologies eliminate this ‘personal touch’ from our travels. It offers the most optimal routes, shortest time, distance, avoiding traffic, toll-ways, etc. So far, however, I have not seen an optimization algorithm that implements the real human factor in spatial navigation. Such system should analyze route choices previously taken by the driver and determine what kind of route plan will be not only the most economic but also the most satisfactory. I keep my fingers crossed that Agarwal and her colleagues will have this previously ignored human perspective included in their new research initiative.

Now also on Academia.edu

Other than being another great social networking resource for academics, Academia.edu did a wonderful job with interest lists. If you are like me, and have multiple research interests, sometimes it can be difficult to put yourself under a single category.

Their site provides a nice (I assume, user-generated) list of a growing number of academic interests linked to other researchers in that field. Here is a sample of my list – slightly reorganised – under 3 main categories:

1. Cognitive Psychology

Spatial Cognition
Learning & Memory
Applied Psychology
Cognitive Neuroscience
Evaluation Research
Forensic Psychology

2. Behavioural Architecture

Architecture and learning spaces
Linking Pedagogy and Space
Space Syntax

3. Technology

Academic Technology
Learning Spaces
Human Computer Interaction
Serious Gaming
Virtual Worlds
Web 2.0