Learning analytics and flipped learning in online teaching for supporting preservice teachers’ learning of quantitative research methods

Forfattere

DOI:

https://doi.org/10.7577/seminar.4686

Emneord (Nøkkelord):

Research methods, Quantitative methods, Preservice teacher, Learning analytics, Flipped Learning, Online teaching

Sammendrag

Research methods, including those of a quantitative nature, are an important part of preservice teacher training in Finland. However, quantitative research methods are considered challenging, often feared, and even hated among preservice teachers. This may be due to previous negative experiences and emotions associated with their use, which also influence other aspects of learning such as self-regulation, self-efficacy, and orientations. Given such circumstances, new ways to teach and support the learning of quantitative methods are needed. Here, we investigate the self-regulation, self-efficacy, orientations, and emotions of preservice teachers (N = 38) enrolled in a quantitative methods online course incorporating learning analytics and a flipped learning approach. Dispositional learning analytics data from five measurement points were used, and data were analyzed via descriptive statistics, internal consistency (Cronbach alpha), bootstrapped paired sample t-test (between first and final measurement point), and profiles based on mean. The results demonstrate that in this teaching context, preservice teachers’ time management skills can be improved, and task avoidance, anxiety, and boredom towards quantitative methods decreased. The meaning of these results from the teaching context perspective are also examined, as are the limitations and implications of this study.

Forfatterbiografier

Erkko Sointu, University of Eastern Finland

Erkko Sointu (PhD, Education) works as a Professor of Special Education at the School of Educational Sciences and Psychology, University of Eastern Finland. His current research efforts focus on research studies of higher education students, teacher education, learning analytics, as well as students’ behavioral and emotional challenges and strengths.

Teemu Valtonen, University of Eastern Finland

Teemu Valtonen (PhD, Education) works as a Professor at the School of Applied Educational Science and Teacher Education, University of Eastern Finland. His research interests lie in the use of Information and Communication Technology (ICT) in education, targeting especially on pre-service teachers’ skills and readiness to use ICT in education, mainly within Technological Pedagogical Content Knowledge (TPACK) and Theory of Planned Behavior (TPB) frameworks.

Susanne Hallberg , University of Eastern Finland

Susanne Hallberg (M. A., Ed.) is a Project Researcher and a Doctoral Student at the School of Applied Educational Science and Teacher Education, University of Eastern Finland. Susanne’s research interests comprise pedagogical usability aspects of innovative physical and digital learning environments, and educational technology.

Jenni Kankaanpää , University of Eastern Finland

Jenni Kankaanpää (M. A., Ed.) is a Project Researcher and a Doctoral Student at the School of Applied Educational Science and Teacher Education, University of Eastern Finland. Her research interests lie in higher education teachers’ pedagogical development work, flipped and blended learning, and learning analytics.

Sanna Väisänen , University of Eastern Finland

Sanna Väisänen (PhD, Education) works as a Postdoctoral Researcher at the School of Applied Educational Science and Teacher Education, University of Eastern Finland. Her research interests are in learning analytics, self-regulated learning, and well-being.

Lasse Heikkinen , University of Eastern Finland

Lasse Heikkinen (PhD) is a University Lecturer at the Department of Applied Physics, University of Eastern Finland. His research background is in computational physics and especially in inverse problems. Since 2010, he has been teaching-focused position by teaching physics courses. He has introduced a flipped classroom model in his own courses in 2015 and developed courses specifically for learning assessment and student guidance.

Mohammed Saqr , University of Eastern Finland

Mohammed Saqr (PhD, learning analytics) works as a Senior Researcher at the School of Computing, University of Eastern Finland. His research interested focus on and big data in education, network science and science of science. His research in learning analytics focuses on social and temporal networks, machine learning, process- and sequence mining as well as temporal processes in general.

Ville Tuominen , Valamis Group. University of Eastern Finland

Ville Tuominen (MSc) works as Principal Learning Consultant at Valamis Group and Project Researcher at the School of Applied Educational Science and Teacher Education, University of Eastern Finland (UEF). His background is in vocational distance learning. He also has long career on many different educational institutes and levels. Focus areas are the development of learning design, learning and development in a corporate context, and measuring and analyzing the learning as a business key indicator.

Laura Hirsto, University of Eastern Finland

Laura Hirsto (PhD, Education) is a Professor of Educational Science at the School of Applied Educational Science and Teacher Education, University of Eastern Finland. Her research has focused on the contextual research-based development of teaching, the contextual learning and motivational processes of university students. Her current research focuses on contextualized teaching-learning processes and self-regulated learning supported by learning analytics in various contexts from primary level to higher education. She is the leader of the learning analytics OAHOT project.

Nedlastinger

Publisert

2022-07-01

Hvordan referere

Sointu, E., Valtonen, T., Hallberg , S., Kankaanpää , J., Väisänen , S., Heikkinen , L., Saqr , M., Tuominen , V., & Hirsto, L. (2022). Learning analytics and flipped learning in online teaching for supporting preservice teachers’ learning of quantitative research methods . Seminar.net, 18(1). https://doi.org/10.7577/seminar.4686

Utgave

Vol 18 Nr. 1 (2022): Special Issue MEC21

Seksjon

Articles

Lisens

Opphavsrett 2022 Erkko Sointu, Teemu Valtonen, Susanne Hallberg , Jenni Kankaanpää , Sanna Väisänen , Lasse Heikkinen , Mohammed Saqr , Ville Tuominen , Laura Hirsto

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