Jonna Malmberg, a Post-Doctoral researcher from the SLAM project is visiting at the School of Informatics, University of Edinburgh, Scotland. The research visit will strengthen already existing networks with Prof. Dragan Gasevic and his research team.

Dragan Gasevic is a Professor and the Chair in Learning Analytics and Informatics in the Schools of Education and Informatics at the University of Edinburgh since February 2015.
Since SLAM research project builds in for interdisciplinary research, Dragan Gasevic and his team can provide and add valuable methodological knowledge in terms of how to process multichannel data that consists of physiological reactions and their associations for self-regulated learning. Specifically, they focus of investigating how machine learning methods can self-regulated in the context of collaboration.
During the research visit, Jonna has been working intensely with Postgraduate Student Oliver Fincham, who is a member of Institute for Adaptive and Neural Computation and Markus Hörmann.  He is a research fellow at the chair of Teaching and Learning with Digital Media at the University of Technology Munich and works closely with Prof Maria Bannert. 

The research visit at the beautiful and old city of Edinburgh provides Jonna a great opportunity to learn about state of the art research projects dealing with, for example Natural Language Processing (NLP)  and machine-learning methods that can definitely be useful and valuable for the progress of the SLAM research project.  

The SLAM research will continue!
Oulu University EUDAIMONIA strategic funding was given to our research proposal for the years 2018-2021:
 
Making Complex Learning processes Visible for Enabling Regulation: 
Change human behavior for learning success (CLEVER change)
 
The PI is Sanna Järvelä and co-PI Paul Kirschner, and the SLAM team will contribute.
Our collaborators are Ass. Prof. Allyson Hadwin, University of Victoria Canada and Prof. Roger Azevedo from North Carolina State University.

In addition to recharging our batteries during the summer, the SLAM team has steadily progressed with its research. During the summer, the observational video analysis continued for the second round and several publications have taken great steps forward. A variety of challenges has been tackled in collaboration with the expertise of the Center for Machine Vision and Signal Analysis at the University of Oulu. Now, it’s time again to present some of the results and to get valuable feedback from colleagues around the world. What is a better place for that than the 17th EARLI conference in Tampere?
Every second year the European Association for Research on Learning and Instruction (EARLI) organizes a major conference for educational researchers. This year the EARLI conference will be hosted by the University of Tampere and most of the major names in learning sciences will be there. The SLAM team brings its contribution not only to the EARLI conference but also to the preceding Junior Researchers of Earli (JURE) conference with a variety of presentations (listed below).
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​SLAM at the 2017 EARLI CONFERENCE

TUESDAY, 29 AUGUST 2017

Multimodal data to measure students’ cognitive, metacognitive and motivation during learning - Sanna Järvelä, University of Oulu, Finland,
INVITED SYMPOSIUM, Time: 13:15-14:45, Location: Pinni B - B1097

Physiological synchrony during monitoring in collaborative learning - Márta Sobocinski, University of Oulu, Finland; Jonna Malmberg, University of Oulu, Finland; Sanna Järvelä, University of Oulu, Finland
SINGLE PAPER, Time: 15:15-16:45, Location: Main Building A - A4

How physiological data visualizations can be used to track socially shared regulation of learning - Jonna Malmberg, University of Oulu, Finland; Sanna Järvelä, University of Oulu, Finland; Ilkka Juuso, University of Oulu, Finland; Iman Alikhani, University of Oulu, Finland; Tapio Seppänen, University of Oulu, Finland
SYMPOSIUM, Time: 15:15-16:45, Location: Virta - 120

​WEDNESDAY, 30 AUGUST 2017

Electrodermal Activity Arousal throughout a Full Physics Course: A Clue for Learning Regulation? - Héctor Javier Pijeira Díaz, University of Oulu, Finland; Paul A. Kirschner, Open University of the Netherlands, Netherlands; Sanna Järvelä, University of Oulu, Finland; Hendrik Drachsler, Open University of the Netherlands, Netherlands
POSTER PRESENTATION, Time: 08:30-10:00, Location: Main Building E - E222

THURSDAY, 31 AUGUST 2017

How regulation evolves during collaborative learning ? – triangulation of multimodal dataset - Sanna Järvelä, University of Oulu, Finland; Jonna Malmberg, University of Oulu, Finland; Márta Sobocinski, University of Oulu, Finland; Eetu Haataja, University of Oulu, Finland; Paul A. Kirschner, Open University of the Netherlands, Netherlands
SYMPOSIUM, Time: 10:15-11:45, Location: Main Building C - C8

FRIDAY, 1 SEPTEMBER 2017

Interplay of temporal changes in self-regulation, academic success and perceived group challenges -  Muhterem Dindar, University of Oulu, Finland; Jonna Malmberg, University of Oulu, Finland; Sanna Järvelä, University of Oulu, Finland; Paul A. Kirschner, Open University of the Netherlands, Netherlands
SINGLE PAPER, Time: 17:30-19:00, Location: Linna - Väinö Linna (K104)

SATURDAY, 2 SEPTEMBER 2017

Designing and implementing retrospective dashboards for socially shared regulated learning - Sanna Järvelä, University of Oulu, Finland; Jonna Malmberg, University of Oulu, Finland; Hanna Jarvenoja, University of Oulu, Finland; Héctor Javier Pijeira Díaz, University of Oulu, Finland; Muhterem Dindar, University of Oulu, Finland; Paul A. Kirschner, Open University of the Netherlands, Netherland
SYMPOSIUM, Time: 10:30-12:00, Location: Pinni B - B3118
 
JURE CONFERENCE

SUNDAY, 27 AUGUST 2017

Monitoring in collaborative learning and physiological synchrony – How they co-occur? - Eetu Haataja, University of Oulu, Finland; Jonna Malmberg, University of Oulu, Finland; Sanna Järvelä, University of Oulu, Finland
POSTER PRESENTATION, Time: 14:45-16:15, Location: Pinni B 3118

MONDAY, 28 AUGUST 2017

Progress in research on regulated learning: self-, co-, and socially shared regulation of learning - Sanna Järvelä, University of Oulu, Finland; Hanna Jarvenoja, University of Oulu, Finland
INVITED WORKSHOP, Time: 16:45-18:15, Location: Pinni B 4113
 
Please come to the sessions and discuss with us about the SLAM research!

The 7th International Learning Analytics and Knowledge (LAK) Conference is being held in Vancouver. Here Professor Järvelä's keynote presentation slides from the conference.

The Learning and Educational Technology (LET) research unit of the University of Oulu, where the SLAM research takes place, has a systematic research collaboration relationship with the Welten Institute of Open Universiteit in Heerlen, the Netherlands. Both groups share an interest in advancing our understanding of learning and the role of technology in supporting technology enhanced learning innovations.

As part of this ongoing collaboration, a PhD student in the SLAM project, Héctor J. Pijeira Díaz, visited the Welten Institute in the week of February 6th to 10th. There, Héctor had the opportunity to present the SLAM research to the overall audience, to the WEKIT project (http://wekit.eu/) team, and more specifically, the line of his PhD studies to the Technology Enhanced Learning Innovations (TELI) group at Welten Institute. These three presentations gave Héctor the opportunity to interact with the PhDs and staff there, be exposed to different viewpoints on his and other research, and receive constructive feedback on how to progress in a direction meaningful to the community.

Apart from these group presentations, Héctor was honoured to have 1:1 insightful meetings with researchers at different stages in their careers, from early stage PhD students to accomplished professors. The expertise of these researchers varied from learning sciences to learning technology to teaching as they belong to the three different groups the Welten Institute is comprised of, Fostering Efficient, Effective and Enjoyable Learning (FEEEL), TELI, and Teachers and Teachers’ Profesionalisation (T2P).

SLAM’s PhD student Héctor had the chance to learn about other relevant projects such as the abovementioned Wekit, the MOOQ project dealing with the quality of MOOC courses, and projects dealing with the biopsychology of learning and the impact of lifestyle on learning.

In a hands-on approach, Héctor was invited to an eye-tracking training session by the expert in the field Dr. Halszka Jarodzka (the SLAM first experiment data collection included eye-tracking); and also to try the latest version of the award-winning Presentation Trainer, which uses Microsoft Kinect Sensor technology to provide immediate feedback based on experts’ recommendations, on presentations aspects such as posture, hand position and movement, voice pitch and cadence, and more. The presentation trainer is developed by Dr. Jan Schneider.

Overall, the visit was a fruitful exchange of ideas from the SLAM project research and a variety of projects being carried out at the Welten Institute, all with the common goal of advancing our understanding of learning and the role of technology to support learning research and practice.

SLAM project is lucky to have Assistant Professor Omid Noroozi joining the team with his strong expertise. Below you can read his introduction:

"I am currently an assistant professor of Educational Technology at Wageningen University in the Netherlands. In my works, I design, implement and evaluate various Computer-Supported Collaborative Learning (CSCL) environments for argumentation-based learning. Specifically, I design various types of instructional interventions, e.g. scaffolding and scripting approaches, and test their effects on a variety of learning process and outcome aspects in both real educational and control-based laboratory settings. My projects covers a wide range of advanced qualitative and quantitative methods to analyze various aspects of learning processes and outcomes in CSCL environments.

It is an honour to be part of the SLAM project and work with a great team. Working on SLAM project provides me with the opportunity to be involved in a cutting-edge research domain in the learning sciences. What inspires me most about this project is the application of advanced technologies and the learning analytics to enhance regulation of individual and collaborative learning. I will start on the SLAM project with redrafting a paper on designing learning analytics dashboard feedback. In this paper the aim is to provide a conceptual framework for dashboards, by grounding feedback theories in the learning sciences and more precisely on regulatory mechanisms underlying learning processes. I hope to bring added value for this great project."

We have also been exploring facial expression analysis opportunities in our collaborative learning session video data with Assoc. Prof. Guoying Zhao and Dr. Xiaohua Huang. This machine learning based method holds great potential for us to study and work with the data. The first experiments with parts of the video data are promising and the next step is to refine and apply the method to a larger set of data.

Assoc. Prof. Zhao will also present a keynote lecture at the forthcoming EARLI Special Interest Group 27, Online Measures of Learning Processes conference held in Oulu from November 29 through December 1. Members of the SLAM team are responsible for the local arrangements of the conference. We are also looking forward to presenting our first results and to contact with other researchers working with similar kinds of data-sets.

This year EARLI Metacognition Sig 16 was held in Nijmegen Netherlands. The SLAM team presented a poster in a workshop Using Data Visualizations to Understand and Reason about Self-Regulated Learning organized  by Prof. Roger Azevedo, NC State university.

The SLAM team members, Dr Jonna Malmberg and Prof. Sanna Järvelä also presented their initial findings of using multichannel data to understand regulated learning in the context of collaboration in the symposiums 'Advances in scaffolding metacognition with advanced learning technologies' and E-CIR invited Symposium: Measuring and supporting students' self-regulated learning in adaptive educational technologies.

Encouraging feedback was received and many questions arised. Our discussant Prof. Phil Winne concluded that symposium represents state of the art in SRL research, but also reminded that it is important to consider what are the standards for new methodology. 

Spring was a hectic period for the SLAM team due to intense data collection. The team collected data from two high school Advanced Physics courses involving a total of 43 students and 36 sessions. During the courses the students solved physics related problems using experimental equipment including lasers, lenses and online simulations. Twelve of the sessions were held in LeaForum research laboratory  equipped with the MORE system [1] for high quality audio and video recording and twelve Empatica E4 sensors [2] were used to track students’ physiological signals. This yielded 101 hours of video, 266,216,000 (more the a quarter of a billion) data points of physiological data and 236,000 (almost a quarter of a million) log events from the virtual learning environment.

During the courses, Open edX served as the virtual learning environment (VLE). Taking advantage of its open source character, the SLAM team installed and hosted its own instance of the platform on a dedicated server. One of the main reasons why the team decided to use edX was its built-in event tracking system. It made it possible to track students’ navigation and interactions with the platform.

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.

The next challenge for the SLAM team is to continue the analysis with the extensive, multimodal dataset. Combining very different modalities of data isn’t easy and each data type also has its own challenges. The pilot study carried out during the spring in 2015 gave some useful ideas on where to start, which will be developed and enriched with the vast amount of newly collected data.

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



References

[1] 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.

[2] 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.