Justin Bruner

Research Associate, College of Education, Michigan State University

Justin is a research associate in the Office of the Hannah Chair in the College of Education at Michigan State University and joined the Pathways programme in October, 2014. Prior to this position he was appointed as an instructor teaching both elementary and secondary teacher education methods courses in the College of Education at Michigan State and also Business English courses, holding dual appointments in the Broad College of Business and English Language Center. Before coming to Michigan State Justin worked as a secondary social studies teacher. He currently works for Dr. Barbara Schneider on her international collaboration that uses experience sampling methods to measure secondary student engagement in their classes with a focus on science and use this information to help secondary science teachers improve their instructional pedagogy. This project is conducted in collaboration with the University of Helsinki and fellow Pathways members Dr. Katariina Salmela-Aro and Dr. Julia Moeller. Their work has been disseminated or is under review in leading science education, psychology, and teacher education journals around the world. They have also presented this work at conferences in United States, Finland, Canada, and United Kingdom with plans to present at two additional conferences in Europe later in the year. To date they have received two separate National Science Foundation grants for their work and were selected after two rounds of competition to submit a proposal for a scale up and expansion of the work in the United States in partnership with Finnish colleagues. Their results show that moments of student engagement (“optimal learning moments”) are very rare and can be influenced by the choices teachers make in the classroom so the team is working with teachers on using project based science pedagogy to help increase student engagement.

Justin’s research interest is in helping find compensatory mechanisms for disadvantaged students, especially students of low socio-economic status, that can help them achieve beyond what would be expected given their background. He uses international datasets such as TIMSS and PISA to explore for possible solutions both within and between countries by studying student, teacher, and school characteristics. His dissertation used the 2011 TIMSS 8th grade science dataset to explore how science achievement scores were distributed among student, teacher, and school characteristics and he currently has this work under review for publication. His results from this research indicate that there are large differences between countries in the amount of variation in student science achievement. Within countries, the magnitude of individual student, teacher, and school factors is related to the proportion of overall country level variance in student achievement and the significant factors driving the variation vary by country. This provides evidence against trying to transfer policies and procedures from one country to another. Currently Justin is preparing a manuscript that uses the 2012 PISA data from the United States to identify students classified as “resilient” which is defined as students that are in the bottom third of socio-economic status but in the top third of achievement. He is exploring the research question of what makes these students resilient compared to their equally disadvantaged peers. The preliminary results indicate that resilient students report greater levels of control and perseverance, as well as attend classrooms with more opportunities to learn content and less classroom disruptions.

Bruner, J. (under review). “A Six Country Comparison of Secondary Science Achievement: Exploring factors associated with inequality”

Schneider, B., Krajcik, J., Lavonen, J., Salmela-Aro, K., Broda, M., Judy, J., Bruner J., Moeller, J., Linnansaari, J., Juuti, K., & Viljaranta, J. (Revised and Resubmitted). “Investigating Optimal Learning Moments in U.S. and Finnish Science Classes”

AERA Grants Program Award: AERA Institute on Statistical Analysis: Causal Analysis Using International Data