Advancing video research methodology to capture the processes of social interaction and multimodality

• Published in: ZDM Vol. 54; no. 2; pp. 433 - 443
• Main Authors: Hannula, Markku S., Haataja, Eeva, Löfström, Erika, Garcia Moreno-Esteva, Enrique, Salminen-Saari, Jessica F. A., Laine, Anu
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2022; Springer; Springer Nature B.V
• Subjects: Camcorders; Cameras; Classrooms; Collaboration; Collaborative learning; Colleges & universities; Communication; Cooperative Learning; Data analysis; Data management; Education; Educational technology; Ethics; Eye movements; Faculty Development; Foreign Countries; Information Management; Information Security; Instructional design; Interaction; Learning; Learning Processes; Mathematical analysis; Mathematics; Mathematics Education; Original Article; Privacy; Problem Solving; Professional development; Research Methodology; Researchers; Social factors; Social interaction; Students; Teachers; Technical services; Technology Uses in Education; Universities; Video data; Video Technology; Zooming; Australia; Finland (Helsinki)
• ISSN: 1863-9690; 1863-9704
• DOI: 10.1007/s11858-021-01323-5

In this reflective methodological paper we focus on affordances and challenges of video data. We compare and analyze two research settings that use the latest video technology to capture classroom interactions in mathematics education, namely, The Social Unit of Learning (SUL) project of the University of Melbourne and the MathTrack project of the University of Helsinki. While using these two settings as examples, we have structured our reflections around themes pertinent to video research in general, namely, research methods, data management, and research ethics. SUL and MathTrack share an understanding of mathematics learning as social multimodal practice, and provide possibilities for zooming into the situational micro interactions that construct collaborative problem-solving learning. Both settings provide rich data for in-depth analyses of peer interactions and learning processes. The settings share special needs for technical support and data management, as well as attention to ethical aspects from the perspective of the participants’ security and discretion. SUL data are especially suitable for investigating interactions on a broad scope, addressing how multiple interactional processes intertwine. MathTrack, on the other hand, enables exploration of participants’ visual attention in detail and its role in learning. Both settings could provide tools for teachers’ professional development by showing them aspects of classroom interactions that would otherwise remain hidden.