Category: Video-based research in learning and instruction
At first, it was just a matchmaking workshop bringing together partners from Universität Hamburg, Macquarie University in Sydney and Fudan University in Shanghai for joint research projects. My team in Hamburg had some advantage here because I have been working with Matt Bower at Macquarie for a long time. We were surprised and all the more pleased that Xuanjing Huang also wanted to join our team. Now, after exchanging ideas, presenting methods and techniques and developing a project plan at a second workshop, our goals have become even more ambitious.
Our aim of cooperation is to develop procedures for automated recognition and analysis of teaching and learning behaviour in the classroom, maybe also of lesson quality. Our experiences match perfectly: My team in Hamburg has several years of experience in video analysis of lessons and developing coding schemes. Our colleagues at Fudan have ongoing projects addressing the automated analysis of teaching and learning behaviour and Macquarie University is specialised in technology-based learning and instruction.
Writing research proposals, we have a great deal of work ahead of us!
What is it that determines how effectively students work on a task in the open phases of a school lesson? At the European Conference for Educational Research (ECER) in Budapest we presented our latest research results on this. Of course, a student’s own motivation can explain his or her effectiveness to a large extent. But what is surprising is the strong influence the learning partner has on the learning results. Also similarities between the learning partners have an impact on their effectiveness: The more similar the learning partners’ motivations are, the better they learn together.
Knigge, M., Siemon, J., & Scholkmann, A. (2014, september). Die Erfassung der Qualität sozialer Interaktionen zwischen Schülerinnen und Schülern im Klassenraum am Beispiel von Dyaden beim simulationsbasierten Lernen [Assessing the quality of social interactions between students in the classroom by the example of dyads during game-based learning]. Lectured at AEPF, Hamburg.
Download (pdf, German version): Knigge_Siemon_Scholkmann_AEPF_2014_09_09a_MK
Siemon, J., Boom, K.-D., & Scholkmann, A. (2015). Multimodale Video-und Audioauswertungen (MuVA) [multimodal video and audio analysis (MuVA)]. Script presentet at 3. Frankfurter Tagung zu Videoanalysen in der Unterrichts- und Bildungsforschung [3. Conference on video analysis in classroom and educational research, Frankfurt am Main].
Download (pdf, German version): Siemon, Boom & Scholkmann 2015_Multimodale Video-und Audioauswertungen MuVA
Our coding scheme for video-analysis of learning time (time on task) is now ready, tested and available for free download:
German version (pdf): Siemon et al. 2015_Kodiermanual Lernzeitnutzung v2
English version (pdf):Siemon et al. 2015_Coding Manual Time on Task v2
Please cite as:
Siemon, J., Scholkmann, A., Boom, K.-D., & Knigge, M. (2016, Juni 27). Kodiermanual Lernzeitnutzung (Time on Task). Zur Analyse von Schülerverhalten anhand von Videodaten.
Please cite as: Siemon, J., Scholkmann, A., Boom, K. D. & Knigge, M. (2016). Time on Task Coding Scheme for Student Learning Behaviour in Videos. Universität Hamburg: Institute for Business and Vocational Education (to be requested through the authors).