The SICSS Helsinki partner site was organized in Helsinki, Finland. We organized it as a two-week institute: the first week was focused on lectures and the second week on group projects. We had a total of 19 participants, an instructor and two TAs. Participants were both from Finland (University of Helsinki, Aalto University, Tampere University of Technology, Turku University) as well as from other European countries (Netherlands, Poland, Germany, Denmark) and rest of the world (India, Turkey). The overall net promoter score (based on the after-course evaluation) was 9 – indicating that the participants considered the course successful and would recommend it to their colleagues. Similarly, the textual feedback suggested that the course was found helpful, engaging and even fun.
This is a final reflection document for the SICSS organized at Helsinki. Similar reflection documents have been written in all SICSS sites.
Group dynamics
We had made a deliberate decision at Helsinki to take the student group to an offsite location for the first week in Tvärminne. Beyond providing a fabulous venue in terms of scenery, outdoor activities and food, it also forced participants to have an on-campus experience for the first week, and socialize. Based on my random observations, this seemed to be happening during the evenings, after the classes. Similarly, we chose to organize after work activities during the second week, which aimed to help to mitigate some of the challenges of lack of residential accommodation and social activities which emerges from that collocation.
What I found challenging and surprising was the need to facilitate group processes during the second week focused on group work. This was not extensive, and rather often groups seemed to manage on their own with this. We were rather pressed for time during the second week, but I’m thinking should we organize dailies similar to agile software production: each team member would speak for a few minutes what they are doing next, what have they done and if they have any major challenges. It might help us to intervene quickly in the group processes facilitation to potential problems and help the groups to manage the time and workload of such a short project. Ideally, over the week, we should move the responsibility of organizing these dailies to the groups.
Something I was disappointed myself was lack of a “global” community of SICSS in the course Slack community. I believe that majority of comments from Helsinki to the public channel came from me or our TAs. Reasons for this may include the time difference between Europe and the US – but maybe also some failures to motivate and incentive this correctly by my side. Maybe next year, the Slack community management could consider establishing smaller channels for particular topics (“communities of practices”) to help people finding smaller venues where they can collaborate and share ideas and comments. Another aspect which I think might be helpful would be to start the online community building way before the event, also content wise. For example, maybe we could create for some of the pre-readings cross-national reading groups or other activities which would encourage them to speak with people from other communities?
Instruction and activities during the first week
Something we spend a lot of time discussing with my TAs (in our debrief after SICSS) was the scope of the instruction. We covered many different things during the first week to provide a general overview of several different method families in computational social science. However, the question was if there should be a more extensive discussion about some methods to ensure that students are able to fully understand them and not just rush through them. It was even proposed that we should really go through some basics of algorithms and computer science for the students.
However, I believe that the current idea of providing a rich overview of different methods is a good choice. It will familiarize students with many opportunities and help them to rethink social research. However, this is a communication challenge: this type of pedagogical choice needs to be explained and articulated. I did a few rounds of talks focused on this topic, but having that mentioned already on day one would be nice. (For example, one student commented in the feedback form that we could have a separate institute on any of these topics – which is true – and thus indicating that we should have been much more clear on the scope and idea behind that scope).
The second aspect which we discussed with my TAs and some participants explicitly commented: the course was a good crash course for people entering computational social science from a social science background, but for people coming from computer sciences and familiar with data science things many aspects of these lectures were rather boring and even useless. We tried to introduce to some activities (ad hoc) refocus on aspects such as teaching qualitative research methods to those not familiar with them or directing them to consider social science theory of their data analysis. These types of aspects could be more baked into the activities material next year (and I’m happy to help editing them towards this goal).
I will discuss video lectures later, but we had a mix of content coming from Helsinki (i.e., I was instructing the content) and some parts we choose to take as video lectures. Something I found difficult when instructing was to find the correct balance between audience participation and me lecturing topics. (To be honest, I actually don’t usually enjoy lecturing that much.) In some of my regular computational social science classes at the University of Helsinki, I usually ask students to read a case study before the class which applies the approach or method we are learning. It serves two aspects: first, we can use that article to develop fruitful discussions with the students and therefore, I don’t need to lecture as much. Second and more importantly, the case studies provide the students with an opportunity to see how “social science theory” (whatever that means) is integrated into the computational work – which I also believe to be a core skill in computational social sciences. If I’m organizing a class like this next year, I would integrate a component like this to balance the me-speaking – students-speaking a bit.
The video lectures
Overall, given the time difference organizing the video lectures was somewhat challenging. For the guest lectures (given at Duke in the evening) we opted to watch them delayed the next day. This reduced some aspects of their liveliness, which many students commented in a somewhat negative tone. We tried to stop these lectures when possible to discuss the lectures in our group (a proposal by one of the students) and this seemed to make them somewhat more engaging. I would recommend the similar idea to other locations which must follow lectures in non-live format.
On the instruction (given at Duke during the morning), we chose some topics where we followed the Duke stream while on other topics I chose to hold the lectures myself. The student feedback suggested that they liked these locally provided lectures more than following live streams from Duke, so I think we made the right decision to develop some instruction on our own. Naturally, the challenge with this is that the quality and content between the institutes may vary somewhat (for example, for text analysis, I chose to start the lecture by speaking about traditional qualitative research methods). However, I think that some quality bonus we had from organizing these locally – such as a high level of interactivity and ability to react to local situations – was worth of this extra investment. In future years, I would examine to replace even more of these lectures when possible and to support on that, produce the materials early enough to allow discussions of them within the instructor community to find potential areas of improvements.
The project week
My only concerns which emerged from the project week related to the group dynamics and lack of proper theoretical reflections during them. I think our group creation process could have been clearer for people; we asked everyone to list topics they find interesting and in collaborative manner, mark which of them they might consider working on. Initial groups were formed based on that and even while I tried to encourage participants to not stay in what seemed like the local optimum, these groupings were set. I think next time, I would force people to change the groups and have similar discussions once or twice to show them the range of opportunities. Furthermore, facilitation of the project management as discussed above may have helped in this. Similarly, on the theoretical reflection, I did ask people to produce a mind map on the first day about theoretical concepts and literature and relationship between those and what they planned to do. Sadly, this itself did not seem to help students enough to engage in this thinking and follow that throughout the week. Again, scaffolding and facilitation may provide helpful in this.
Facilities
While the first week facilities were excellent, the second-week facilities were in our use daily only from 8am to 4pm. This limited some activities and influenced our scheduling. As the summer institute is during summer, many spaces at the University of Helsinki just closed a bit too early. Next year, I would reconsider the second-week location to have a few more hours of shared time. Also, I would have a clear single location for all non-Helsinki visitors and recommend they stay there to reduce some extra coordination efforts.
Negotiating interdisciplinary and cultural boundaries
Something I tried to bring you in fishbowl discussions was the interdisciplinary nature of computational social science and some of the challenges and problems related to this. Sadly, while I enjoyed these discussions, their intention may not have been as clear for participants as it was to me. I have been working across different academic communities for a long time and thus, rather familiar in interdisciplinary collaborations. They take time and often require a lot of flexibility and openness. However, I think that I understand the difficulties of these jumps as I’m so familiar with them and thus, didn’t provide as much support as one could have provided during the two weeks. For example, the fact that I rarely addressed traditional social science theories and methods in the instruction could have helped participants to follow the teaching more and made the classes more engaging to people from computer science background as well.
Similarly, the problem with teaching interdisciplinary groups is their internal heterogeneity in terms of skills. One solution worth of consideration could be to separate the group based on skills or provide even more modular learning activities, where we could assign different participants and groups slight variations of the same tasks to make them more engaging or to allow participants to enter the zone of proximal development. This again would most likely push us to reconsider the role of lectures and instruction.
Finally, people did come from different cultures (not only country wise, but also academic cultures), which meant that their understandings of – among other things – research contributions, the value of group work and ideas of good instruction differed. These were not something major challenges in the project. However, for me better managing this boundary work in the future is critical and having tools and approaches to facilitate students with these is necessary. Sadly, I don’t yet have a clear and good solution to this problem.
Conclusion
The aim of this reflection has been to pinpoint potential areas for improvement, both for myself as well as other SICSS communities and their organization. Therefore, I have aimed to address challenges and problems and discuss them in an extensive manner. However, as said in the beginning, most participants had a positive and engaging experience with this summer institute. The ideas and comments throughout this text may help to further improve the learning and clarify some of the difficulties observed.
We thank the support from Russell Sage Foundation, Alfred P. Sloan Foundation and Helsinki Institute for Information Technology HIIT for their generous financial support.
