How Many Classes and Students Should Ideally be Sampled When Assessing the Role of Classroom Climate via Student Ratings on a Limited Budget? An Optimal Design Perspective

A central question in educational research is how classroom climate variables, such as teaching quality, goal structures, or interpersonal teacher behavior, are related to critical student outcomes, such as students’ achievement and motivation. Student ratings are frequently used to measure classroom climate. When using student ratings to assess classroom climate, researchers first ask students to rate classroom climate characteristics and then aggregate the ratings on the class level. Multilevel latent variable modeling is then used to determine whether class-mean ratings of classroom climate are predictive of student outcomes and to correct for unreliability so that the relations can be estimated without bias. In this article, we adopt an optimal design perspective on this specific strategy. Specifically, after briefly recapping a prominent model in climate research, we show and explain (a) how statistical power can be maximized by choosing optimal numbers of classes and students per class given a fixed budget for conducting a study and (b) how the budget required to achieve a prespecified level of power can be minimized. Moreover, we present an example from research on teaching quality to illustrate the procedures and to provide guidance to researchers who are interested in studying the role of classroom climate. Also, we present a Shiny App that can be used to help find optimal designs for classroom climate studies. The app can be accessed at https://psychtools.shinyapps.io/optimalDesignsClassroomClimate

Linking teachers’ facial microexpressions with student-based evaluation of teaching effectiveness: A pilot study using FaceReader™

This study seeks to investigate the potential influence of facial microexpressions on student-based evaluations and to explore the future possibilities of using automated technologies in higher education. We applied a non-experimental correlational design to investigate if the number of videotaped university lecturers’ facial microexpressions recognized by FaceReader™ serves as a predictor for positive results on student evaluation of teaching effectiveness. Therefore, we analyzed five videotaped lectures with the automatic facial recognition software. Additionally, each video was rated by between 8 and 16 students, using a rating instrument based on the results of Murray´s (1983) factor analysis. The FaceReader™ software could detect more than 5.000 facial microexpressions. Although positive emotions bear positive influence on the “overall performance rating”, “emotions” is not predicting “overall performance rating”, b = .05, t(37) = .35, p > .05. The study demonstrates that student ratings are affected by more variables than just facial microexpressions. The study showed that sympathy as well as the estimated age of the lecturer predicted higher student ratings.

Linkages Between Grade Point Average and Student Ratings

In order to better understand the potential influence of high school students’ grades on how they rate their teachers and schools, we explored the relationship between student grade point average and student ratings of teacher and school effectiveness in 370 classes taught by 230 instructors with over 6,000 students in grades 9–12 in an Intermountain West school district. Teachers were evaluated with an 18-item student survey. Students also rated their schools with six additional items. The performance measure was the grade point average (GPA) for the quarter in which students evaluated their teachers and schools. ANOVAs showed that both year in school and GPA were positively linked with ratings of teacher effectiveness and ratings of school experiences. Seniors were more positively disposed toward their teachers and school experiences than students at lower grade levels. Most of the ratings of specific items on the teacher effectiveness and school-experience scales were significantly, though not strongly, correlated with GPAs. We discuss implications and suggestions for future research.

Linkages Between Grade Point Average and Student Ratings

In order to better understand the potential influence of high school students’ grades on how they rate their teachers and schools, we explored the relationship between student grade point average and student ratings of teacher and school effectiveness in 370 classes taught by 230 instructors with over 6,000 students in grades 9–12 in an Intermountain West school district. Teachers were evaluated with an 18-item student survey. Students also rated their schools with six additional items. The performance measure was the grade point average (GPA) for the quarter in which students evaluated their teachers and schools. ANOVAs showed that both year in school and GPA were positively linked with ratings of teacher effectiveness and ratings of school experiences. Seniors were more positively disposed toward their teachers and school experiences than students at lower grade levels. Most of the ratings of specific items on the teacher effectiveness and school-experience scales were significantly, though not strongly, correlated with GPAs. We discuss implications and suggestions for future research.

Developing a System for Teaching Effectiveness by Student Classification of Teacher Attributes at the University of Lahore College for Women University

As teaching effectiveness is crucial for achieving academic excellence, teachers' attributes contributing towards teaching effectiveness are worth exploring. This study examines 300 BS. Education and Economics students' perception of teachers' characteristics who have taught them. Accordingly, teachers are categorized based on scores of attributes obtained through student ratings. Association between teacher attributes and overall teaching effectiveness is found, and finally, a teaching effectiveness framework is designed based on characteristics, which were significantly associated with teaching effectiveness. The majority (>60%) of students rated all attributes under the medium category, with 54.64% and 50.61% of students placing (rating) overall teaching effectiveness under the high and medium sort respectively, with 17.61 % under the low category. Also, all attributes were found to be positively correlated with overall teaching effectiveness. Out of 30 items under all attributes, 22 items significantly associated with teaching effectiveness were included in the teaching effectiveness framework. In light of the findings, we give teachers suggestions regarding their teaching attributes as perceived by students.