Virtual learning environment – Open edX
In practice, the VLE included task related materials and the script for collaboration. The script followed the same form in most of the sessions. Students started by doing a retrospective evaluation considering their last lesson. A collaborative learning dashboard was provided to support this phase (see the gauges below). After this, students continued with answering orientation questions, and then moved on to collaboratively working on the task. At the end of the lessons, students reflected on their performance by answering a short survey.
Values for the dashboard and evaluation came from the survey students filled out during the previous session. In addition, the history of measures was provided for students to see the overall evolution of their group according to their own self-reports. The dashboard as a tool was evaluated using a questionnaire on usability, usefulness and user experience. A quick look at the results suggests that many of the students were interested in the gauges and considered them useful. Further analysis might reveal how it affected their learning process.
Over one hundred hours of video data will be compressed and coded in order to gain an insight into how students collaborated. The physiological data, recorded during collaborative learning situations, is being synchronized at both individual and group levels. Further signal-specific data processing and analysis will be carried out in collaboration with the Oulu University Biosignal Processing Team, led by Prof. Tapio Seppänen and with extensive expertise in this area. Events from the Open edX VLE are also to be synchronized with the physiological data, as an indispensable context-related complement. To this purpose, the raw data in the databases from the platform and text files with log data are being processed.
To sum it up, extensive, multimodal data has been collected from the February to June 2016 SLAM experiment. An exciting period is starting, as we start to focus on data analysis. We will keep you posted developments
 Keskinarkaus, A., Huttunen, S., Siipo, A., Holappa, J., Laszlo, M., Juuso, I., Väyrynen, E., Heikkilä, J., Lehtihalmes, M., Seppänen, T., & Laukka, S. (2015). MORE–a multimodal observation and analysis system for social interaction research. Multimedia Tools and Applications, 1-25.
 Garbarino, M., Lai, M., Bender, D., Picard, R. W., & Tognetti, S. (2014, November). Empatica E3—A wearable wireless multi-sensor device for real-time computerized biofeedback and data acquisition. In Wireless Mobile Communication and Healthcare (Mobihealth), 2014 EAI 4th International Conference on (pp. 39-42). IEEE.