In public debate, online teaching is often presented in a negative light, but when planned and delivered properly, it can work well and support students’ learning, according to studies by Professor Erkko Sointu, Professor Laura Hirsto and Professor Teemu Valtonen, and by the OAHOT learning analytics research group led by Hirsto.
In the autumn of 2020 and 2021, Professor Erkko Sointu was teaching a course on quantitative research methods to preservice teachers. The course in question is very challenging even in normal times, but now, due to the pandemic, students also had to cope with an online mode of study.
“Generally speaking, pre-service teachers find mathematical and statistical topics very challenging. And since the course in question has a reputation for being challenging, students often have negative feelings about taking it,” Sointu says.
An additional challenge was posed by the online approach to study, with a lack of means for physical interaction, it was more difficult to interpret and follow students’ learning processes and emotions while online.
The researchers set out to design the course as part of the research project, aiming to determine whether learning analytics, well-planned online teaching, and versatile and new ways of interaction, teaching, and guidance could provide solutions to the challenges posed by the course and COVID-19.
“In our study, learning analytics refers to the fact that, while operating in a digital learning environment, each student leaves traces of their activity that the teacher can use to support the student,” Laura Hirsto says.
These traces refer, for example, to how a student uses the materials given, how they progress in their studies, where they spend time on, and where they face challenges.
“Analytics also allows students to easily monitor their own learning.”
During the course, students also filled out brief questionnaires about their emotions towards studying, and about topics they found particularly interesting on the course. These data are referred to as extended learning analytics.
Avoidance of difficult contents, and negative emotions, decreased
Sointu employed the flipped learning approach during the course. Materials prepared by the teacher, such as short videos and video-related notes, were made available to students in the digital learning environment for use at their convenience. In addition, students were able to discuss things on the digital platform with everyone on the course, in small groups, or privately with the teacher.
“Given the lack of physical interaction on the course, learning analytics provided the teacher with an additional insight into how students were coping with online teaching. With the help of analytics, I was able to monitor each student’s progress and emotions towards studying,” Sointu says.
Based on initial findings from the course, students’ time management skills improved and their avoidance of difficult contents, and negative emotions towards studying quantitative methods, decreased.
Given the lack of physical interaction on the course, learning analytics provided the teacher with an additional insight into how students were coping with online teaching.
Erkko Sointu
Professor
Emotions as activators for learning
Another study by Sointu and colleagues looked at analytics data on student progress and studies-related emotions experienced during the course. The results showed that students who experienced the most negative emotions were in fact, based on analytics data, the most active students on the course.
“Emotions can be activating or deactivating. Even if there are negative emotions towards the course, successful online teaching can be used to activate students to succeed in their studies,” Sointu explains.
In yet another study, the researchers analysed course feedback provided by students. The feedback showed that students were pleased with the teaching delivered, with the course atmosphere, and with the course interaction. They estimated their own commitment and learning to be on a good level.
“These findings are encouraging. In addition, the feedback from students and the discussions on how to develop teaching for the future have been very fruitful,” Sointu says, delighted.
According to Sointu, the potential of learning analytics in supporting teaching and learning is great, but more research and practical examples for teachers at different levels are needed to mobilise that potential.
Research articles:
Sointu, E., Valtonen, T., Hallberg, S., Kankaanpää, J., Väisänen, S., Heikkinen, L., Saqr, M., Tuominen V., & Hirsto, H. (2022). Learning analytics and Flipped Learning in online teaching for supporting preservice teachers’ learning of quantitative research methods. Seminar.net, 18(1).
Sointu, E., Saqr, M., Valtonen, T., Hallberg, S., Väisänen, S., Kankaanpää, J., Tuominen, V. & Hirsto, L. (2022). Emotional behavior in quantitative research methods course for preservice teachers. Learning analytics approach. In E. Langran (Ed.) Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 1880-1889). San Diego, CA, United States: Association for the Advancement of Computing in Education (AACE). *
*Society for Information Technology and Teacher Education Conference Outstanding Paper Award, San Diego, US, April 2022.
Sointu., E., Valtonen, T., Väisänen, S. & Hirsto, L. (2022). Flipped Online Approach with Learning Analytics for Supporting Higher Education Students’ Learning. Course Feedback Results. In L. Hirsto, S. López-Pernas, M. Saqr, E. Sointu, T. Valtonen & S. Väisänen (Eds.) Proceedings of the Finnish Learning Analytics and Artificial Intelligence in Education (FLAIEC22), Joensuu, Finland.
