Confirming the Factor Structure of a Research-Based Mid-Semester Evaluation of College Teaching

Abstract

End-of-semester evaluations provide scalable data for university administrators, but typically do not provide instructors with timely feedback to inform their teaching practices. Midsemester evaluations have the potential to provide instructors with beneficial formative feedback that can contribute to improved teaching practices and student engagement. However, existing research on the construction of valid, reliable midsemester tools is rare, and there are no existing midsemester evaluation scales that were constructed using education research and psychometric analysis. To address this gap, we designed and piloted a midsemester evaluation of teaching with 29 instructors and 1,350 undergraduate students. We found evidence that our Mid-Semester Evaluation of College Teaching (MSECT) is a valid and reliable measure of four constructs of effective teaching: classroom climate, content, teaching practices, and assessment. Furthermore, our factor structure remained consistent across instructor genders, providing evidence that the MSECT may be less susceptible to gender bias than prior student evaluation measures.

Prediction Model of Piano Collective Class Teaching and Learning Effect Based on Deep Learning

“…Bhandari et al used the adaptive and self-learning principles of BPNN (Back propagation neural network) for instructional quality evaluation, and proposed an NN-based instructional quality evaluation model structure and an improved BP network learning algorithm [ 10 ]. Donlan and Byrne pointed out that the introduction of evaluation methods in the teaching of piano group lessons will help teachers to fully understand the whole process of teaching, adjust teaching strategies in time, improve students' self-confidence, and stimulate their inner learning motivation; thus realizing piano learning as soon as possible autonomy and the formation of quality education [ 11 , 12 ]. Capella-Peris et al pointed out that the diversified instructional methods, interactive teaching process, and comprehensive teaching content of piano group lessons in normal normal schools are conducive to cultivating students' keyboard performance application, cooperation, performance, and creativity; Comprehensive quality of music [ 13 ].…”

Evaluation method of college students' psychological quality of innovation and entrepreneurship based on big data analysis

“…According to the updated formula (11), the evaluation results of college students' psychological quality of innovation and entrepreneurship are divided into five grades, which are excellent (0.8~1), good (0.6~0.79), medium (0.4~0.59), poor (0.2~0.39) and very poor (0~0. 19). The methods of this paper, reference [9] and reference [10] are used to evaluate the psychological quality of innovation and entrepreneurship of the research object, and the results are shown in Figure 3.…”

“…The construction of the indicator system of college students' psychological quality of innovation and entrepreneurship should not only be based on theoretical analysis, but also consider the operability of statistical practice and the feasibility of practical data. Although from a theoretical point of view, it can design a relatively ideal indicator system [18][19], and use the most comprehensive indicators to reflect the measured problems, in practice, based on some objective reasons, some sampling data can not be obtained, or the acquisition of these samples requires a large cost, so it must follow the feasibility principle when designing the indicator system. Especially at the present stage, the research on the psychological quality of college students' innovation and entrepreneurship is still at the initial stage.…”

Construction of Artificial Intelligence Music Teaching Application Model Using Deep Learning

“…Spooren et al designed the instructional quality assurance system, extracted the important factors that affect the evaluation of instructional quality, and put forward the implementation countermeasures for the key factors, which provided a more reasonable and effective system for the guarantee of instructional quality [12]. Donlan and Byrne conducted research on the construction of practical teaching system in institution of higher learning, and provided reliable theoretical support for the evaluation of instructional quality in practical institution of higher learning through empirical research [13]. Hou et al combined with the actual situation of teaching evaluation, put forward the evaluation index suitable for teaching evaluation; e basic principle and algorithm of principal component analysis are introduced in detail [14].…”