Some rough notes of some ideas I hope to work on, potentially as part of my PhD program.

My Masters degree thesis was based on the use of social network and discourse analysis in an online course to attempt to understand the differences in student activity and interactions in two different online platforms and course designs. Tools like Gephi and NodeXL are available to anyone teaching online, to feed the data (system-generated activity logs, raw discussion text, twitter hashtags, search queries etc.) and get a powerful visualization of how the students interacted. It struck me that the tools are so much richer for online interactions than they are for offline (or blended) face-to-face interactions.

Gathering links on ethnography, microethnography, etc. To help flesh out the ideas around computational microethnography in documenting and analyzing classroom interactions.

Ethnography links
Microethnography links

Some super-rough sketches of some ideas for documenting and visualizing interactions between people in a learning space. Lots of work left to refine the ideas and then to try implementing them…

These comments were started in response to a friend, who was taking a stand against Facebook and their take-it-or-leave-it end user license agreement (EULA). They're not the most profound comments, nor the most well-crafted, but I think they need to exist (also) outside of Facebook's corporate walled garden. Ironically, after I posted the first comment, the Facebook iPad app prompted me to take a survey about how (un)comfortable I was with the state of Facebook, with specific questions asking about the algorithmic feed. So, I filled it in to indicate that I am very (VERY) uncomfortable with the algorithmic news feed…

Klobas, J. E., & McGill, T. J. (2010). The role of involvement in learning management system success. Journal of Computing in Higher Education, 22(2), 114–134. http://doi.org/10.1007/s12528-010-9032-5

Notes:

p.129: Student involvement has a significant effect on students’ perceptions of the benefits of LMS use. The more involved a student is with the LMS site for a course, the stronger the benefits they report obtaining from use — Highlighted Jan 30, 2016

p.129: On the other hand, student involvement has no effect on LMS use — Highlighted Jan 30, 2016

The Taylor Institute has 5 learning studios, designed for active and collaborative learning. People who are using the space have access to some great technology to support their work, including 37 “collaboration stations” (we really need to come up with a better name for those…).

Here’s a quick-ish demo of the basic functionality provided by the stations, recorded using the lecture capture system built into the learning studios.

Technologies mentioned and/or used in the video:

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• Burgard, W., Cremers, A. B., Fox, D., & Hähnel, D. (1998). The interactive museum tour-guide robot. Aaai/Iaai.
• Castellano, G., Paiva, A., Kappas, A., Aylett, R., Hastie, H., Barendregt, W., et al. (2013). Towards Empathic Virtual and Robotic Tutors. In Artificial Intelligence in Education (Vol. 7926, pp. 733-736). Berlin, Heidelberg: Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-642-39112-5_100
• Corrigan, L. J., Peters, C., & Castellano, G. (2013). Identifying Task Engagement: Towards Personalised Interactions with Educational Robots. 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII), 655-658. http://doi.org/10.1109/ACII.2013.114
• Dautenhahn, K. (2007). Socially intelligent robots: dimensions of human-robot interaction. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 362(1480), 679-704. http://doi.org/10.1098/rstb.2006.2004
• Ganeshan, K. (2007). Teaching Robots: Robot-Lecturers and Remote Presence (Vol. 2007, pp. 252-260).
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• Harteveld, C., & Sutherland, S. C. (2015). The Goal of Scoring: Exploring the Role of Game Performance in Educational Games. the 33rd Annual ACM Conference (pp. 2235-2244). New York, New York, USA: ACM. http://doi.org/10.1145/2702123.2702606
• Howley, I., Kanda, T., Hayashi, K., & Rosé, C. (2014). Effects of social presence and social role on help-seeking and learning. the 2014 ACM/IEEE international conference (pp. 415-422). New York, New York, USA: ACM. http://doi.org/10.1145/2559636.2559667
• Kanda, T., Hirano, T., Eaton, D., & Ishiguro, H. (2004). Interactive Robots as Social Partners and Peer Tutors for Children: A Field Trial. Human-Computer Interaction, 19(1), 61-84. http://doi.org/10.1207/s15327051hci1901&2_4
• Kardan, S., & Conati, C. (2015). Providing Adaptive Support in an Interactive Simulation for Learning: An Experimental Evaluation. the 33rd Annual ACM Conference (pp. 3671-3680). New York, New York, USA: ACM. http://doi.org/10.1145/2702123.2702424
• Kennedy, J., Baxter, P., & Belpaeme, T. (2015). The Robot Who Tried Too Hard: Social Behaviour of a Robot Tutor Can Negatively Affect Child Learning. the Tenth Annual ACM/IEEE International Conference (pp. 67-74). New York, New York, USA: ACM. http://doi.org/10.1145/2696454.2696457
• Kenny, P., Hartholt, A., Gratch, J., & Swartout, W. (2007). Building Interactive Virtual Humans for Training Environments. Presented at the Proceedings of I/ “.
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• Kopp, S., Jung, B., Lessmann, N., & Wachsmuth, I. (2003). Max - A Multimodal Assistant in Virtual Reality Construction. Ki.
• Lee, D.-H., & Kim, J.-H. (2010). A framework for an interactive robot-based tutoring system and its application to ball-passing training. 2010 IEEE International Conference on Robotics and Biomimetics (ROBIO) (pp. 573-578). IEEE. http://doi.org/10.1109/ROBIO.2010.5723389
• Leyzberg, D., Spaulding, S., & Scassellati, B. (2014). Personalizing robot tutors to individuals’ learning differences. the 2014 ACM/IEEE international conference (pp. 423-430). New York, New York, USA: ACM. http://doi.org/10.1145/2559636.2559671
• Leyzberg, D., Spaulding, S., Toneva, M., & Scassellati, B. (2012). The physical presence of a robot tutor increases cognitive learning gains.
• Lin, R., & Kraus, S. (2010). Can automated agents proficiently negotiate with humans? Communications of the ACM, 53(1), 78-88. http://doi.org/10.1145/1629175.1629199
• Mitnik, R., Recabarren, M., Nussbaum, M., & Soto, A. (2009). Collaborative robotic instruction: A graph teaching experience. Computers & Education, 53(2), 330-342. http://doi.org/10.1016/j.compedu.2009.02.010
• Mubin, O., Stevens, C. J., Shahid, S., Mahmud, A. A., & Dong, J.-J. (2013). A REVIEW OF THE APPLICABILITY OF ROBOTS IN EDUCATION. Technology for Education and Learning, 1(1). http://doi.org/10.2316/Journal.209.2013.1.209-0015
• Nkambou, R., Belghith, K., Kabanza, F., & Khan, M. (2005). Supporting Training on a Robotic Simulator using a Flexible Path Planner. AIED.
• Nomikou, I., Pitsch, K., & Rohlfing, K. J. (Eds.). (2013). Robot feedback shapes the tutor’s presentation: How a robot’s online gaze strategies lead to micro-adaptation of the human’s conduct. Interaction Studies, 14(2), 268-296. http://doi.org/10.1075/is.14.2.06pit
• Peterson, I. (1992). Looking-Glass Worlds. Science News, 141(1), 8-10+15. http://doi.org/10.2307/3976251?ref=search-gateway:0b99b4ee4ada2716135055fafcfc8c8d
• Rizzo, A., Lange, B., Buckwalter, J. G., Forbell, E., Kim, J., Sagae, K., et al. (n.d.). SimCoach: an intelligent virtual human system for providing healthcare information and support. International Journal on Disability and Human Development, 10(4). http://doi.org/10.1515/IJDHD.2011.046
• Ros, R., Coninx, A., Demiris, Y., Patsis, G., Enescu, V., & Sahli, H. (2014). Behavioral accommodation towards a dance robot tutor. the 2014 ACM/IEEE international conference (pp. 278-279). New York, New York, USA: ACM. http://doi.org/10.1145/2559636.2559821
• Saerbeck, M., Schut, T., Bartneck, C., & Janse, M. D. (2010). Expressive robots in education: varying the degree of social supportive behavior of a robotic tutor. the 28th international conference (pp. 1613-1622). New York, New York, USA: ACM. http://doi.org/10.1145/1753326.1753567
• Satake, S., Kanda, T., Glas, D. F., Imai, M., Ishiguro, H., & Hagita, N. (2009). How to approach humans?-strategies for social robots to initiate interaction. ” -Robot Interaction ( “, 109-116. http://doi.org/10.1145/1514095.1514117
• Serholt, S., Basedow, C. A., Barendregt, W., & Obaid, M. (2014). Comparing a humanoid tutor to a human tutor delivering an instructional task to children. 2014 IEEE-RAS 14th International Conference on Humanoid Robots (Humanoids 2014), 1134-1141. http://doi.org/10.1109/HUMANOIDS.2014.7041511
• Shin, N., & Kim, S. (n.d.). Learning about, from, and with Robots: Students’ Perspectives. RO-MAN 2007 - the 16th IEEE International Symposium on Robot and Human Interactive Communication, 1040-1045. http://doi.org/10.1109/ROMAN.2007.4415235
• Swartout, W. (2010). Lessons Learned from Virtual Humans. AI Magazine, 31(1), 9-20. http://doi.org/10.1609/aimag.v31i1.2284
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• Vollmer, A.-L., Lohan, K. S., Fischer, K., Nagai, Y., Pitsch, K., Fritsch, J., et al. (2009). People modify their tutoring behavior in robot-directed interaction for action learning. 2009 IEEE 8th International Conference on Development and Learning (pp. 1-6). IEEE. http://doi.org/10.1109/DEVLRN.2009.5175516
• Walters, M. L., Dautenhahn, K., Koay, K. L., Kaouri, C., Boekhorst, R., Nehaniv, C., et al. (2005). Close encounters: spatial distances between people and a robot of mechanistic appearance. 5th IEEE-RAS International Conference on Humanoid Robots, 2005., 450-455. http://doi.org/10.1109/ICHR.2005.1573608
• Yannier, N., Israr, A., Lehman, J. F., & Klatzky, R. L. (2015). FeelSleeve : Haptic Feedback to Enhance Early Reading. the 33rd Annual ACM Conference (pp. 1015-1024). New York, New York, USA: ACM. http://doi.org/10.1145/2702123.2702396
• You, S., Nie, J., Suh, K., & Sundar, S. S. (2011). When the robot criticizes you…: self-serving bias in human-robot interaction. the 6th international conference (pp. 295-296). New York, New York, USA: ACM. http://doi.org/10.1145/1957656.1957778

A student practiced in the gallery for a bit today. Not bad. Love the acoustics of the gallery/loft/atrium space.

[audio m4a="https://darcynorman.net/wp-content/uploads/2016/06/student-practicing.m4a"][/audio]

I just sat in the atrium and shaped this soundscape as people were walking through, trying to simulate some kind of response to motion. It’s still pretty muddy, but I think there’s something there. The trick will be in getting it to be unobtrusive and ambient while still providing information…

I’m still amazed at how intense the last several months have been. The Taylor Institute construction was completed, the AV systems were installed and integrated, and an seemingly endless series of high profile events have taken place. The past 6 months have been by far the most intense, high stress, high energy, high profile, and chaotic that I’ve ever experienced. And we’re currently on the last major event for awhile.

I’ve been without work email for almost a week, as a result of a rather large-scale malware incident that took many systems on campus offline. Many folks in IT have been working around the clock to restore hundreds of computers and systems, and I’m thankful for their efforts. It’s a heroic, thankless task, and they are likely getting some steam from people despite the fact that they’re working flat-out to resolve this.

The forum in the Taylor Institute converts from a gymnasium-sized flat-floor active learning classroom into a 336-seat theatre for keynotes and special events.

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