Modeling Student Engagement in the Classroom

Student's Name

Sarah Painter, Minnesota State University, MankatoFollow

1st Student's Major

Mathematics and Statistics

1st Student's College

Science, Engineering and Technology

Students' Professional Biography

Sarah Painter graduated from Minnesota State University, Mankato with a B.S. in Mathematics and French in 2013. She worked under Dr. Rebecca Bates as part of her STEM education research. Previous project include statistical analysis of STEM student learning styles and self-efficacy. She plans to return to MSU in pursuit of an M.A. in Mathematics in the fall of 2014.

Mentor's Name

Rebecca Bates

Mentor's Email Address

rebecca.bates@mnsu.edu

Mentor's Department

Integrated Engineering

Mentor's College

Science, Engineering and Technology

Abstract

Connections to Community is a multi-institutional study that looks at the influence of community on post-secondary, science and engineering students and their engagement in academic activity. This paper focuses specifically on student engagement within the classroom as a follow-up to a previous paper by Wendy Hoffman, Identifying Influential Variables of Student Academic Engagement (Hoffman, 2013). The goal of this work is to model student engagement in the classroom using classroom observation data that has been cleaned and then compare the results with those found in Hoffman’s paper which used pre-cleaning data. The cleaned data is used to create two data sets, one with any observations with missing values removed completely and one with the use of the variable median to replace missing values. These sets are then used to create 12 predictor constructs and one response construct that are thought to be valid according to education experts. Two starting models are created from each data set for a total of four starting models. A form of backward elimination linear regression is used on the four starting models to create four reduced models. The residuals of each reduced model are tested using the D’Agostino-Pearson test statistic, and then the models are compared using the PRESS and SSE statistics. We find that Students’ Reluctance to Leave and Students’ Discussions with Peers are influential in determining student engagement within the classroom. Also, the level students are at within their program and whether students are automotive engineering technology or chemistry students is important. The results found here generally coincide with the findings from the previous paper, but there are differences in the data set that uses the median to replace missing values. Where Hoffman found reliable results for models using this data set, this paper finds results less credible. More work is needed to understand what happened during the cleaning process to create these differences.

Recommended Citation

Painter, Sarah (2014) "Modeling Student Engagement in the Classroom," Journal of Undergraduate Research at Minnesota State University, Mankato: Vol. 14, Article 6.
DOI: https://doi.org/10.56816/2378-6949.1050
Available at: https://cornerstone.lib.mnsu.edu/jur/vol14/iss1/6

Creative Commons License

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