Meta-research on the influence of course, instructor, and student characteristics in student evaluation of teaching at universities

Yang, Kil Seok

doi:10.17927/tkjems.2014.26.2.293

Cited by 3 publications

(3 citation statements)

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“…According to a meta-analysis study by Yang [ 7 ], there are eight lecture factors, 11 student factors, and nine instructor factors that influence lecture evaluation. The lecture factor includes lecture level, class size, department, teaching method, academic year, time of day, regular/special class, and learning environment.…”

Section: Introductionmentioning

confidence: 99%

“…The student factor includes grade level, grade point average, gender, class participation, major, military service status, interest in lecture evaluation, motivation for taking the lecture, non-serious responses, and perceived difficulty of the lecture. The instructor factor includes academic rank, age, lecture structure and activities, department affiliation, class hours, and teaching experience [ 7 ]. Most studies have been conducted using a cross-sectional design, which does not allow for the determination of causality.…”

Section: Introductionmentioning

confidence: 99%

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Instructor factors associated with medical students’ lecture evaluation: a longitudinal analysis

Rhie¹,

Chae²,

Seokgun³

et al. 2023

Korean J Med Educ

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Purpose: This study identified factors that affect lecture evaluation by analyzing sophomores from Dankook University, examining each cluster’s characteristics, and comparing differences among trajectories.Methods: This study identified factors that affect lecture evaluation by analyzing sophomores from Dankook University, examining each cluster’s characteristics, and comparing differences among trajectories.Results: The lecture evaluation score decreased as the teaching hours per instructor in a year increased by an hour, and the number of instructors per lecture increased by one individual. During trajectory analysis, the first trajectory had lower lecture evaluation scores overall but relatively high appropriateness of the textbook and punctuality of class, whereas the second trajectory had higher lecture evaluation scores overall for all four items.Conclusion: The two trajectories showed differences in teaching methods (understanding of lecture content and usefulness of the lecture) rather than in external factors (appropriateness of the textbook and punctuality of class). Therefore, to improve lecture satisfaction, enhancing instructors’ instructional competencies through lectures and adjusting the teaching hours by assigning an adequate number of instructors per lecture are recommended.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Instructor factors associated with medical students’ lecture evaluation: a longitudinal analysis

Rhie¹,

Chae²,

Seokgun³

et al. 2023

Korean J Med Educ

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show abstract

“…The purpose of this is to categorize the types of potential profiles and to analyze the features of course evaluation made at the end of every semester from various angles, to set the direction for the improvement of education and knowledge programs to develop the excellence of university education, and to find ways to support knowledge. Earlier research on course evaluation have mainly focused on item development and evaluation methods (Ha, Jung, 2014;Park, 2012;Song, Lee, 2020), validity of evaluation items (Kim, Kim, 2008;Yun, 2008;Seol, 2007), weighting methods (Man, Cho, 2014;Yang, Park, 2012), and factors affecting evaluation results (Rhy, Ha, Rah, 2017), this study divided possible groups into categories based on the effects of course evaluation and looked at the features to determine a degree of dedication to academics for each group. The following research questions must be taken to fulfill the study's objectives.…”

Section: Introductionmentioning

confidence: 99%

The Relationship between Course Evaluation and Academic Achievement of University Students Using Latent Profile Analysis

Kim¹

2023

JCT

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This study was conducted with the purpose of deriving a heterogeneous potential profile through the results of university lecture evaluation, which is students' perception of class and the product of professor-student interaction in the classroom, and identified the factors that affect it. In addition, the degree of learning flow for each potential profile was investigated and the difference was verified. For the analysis, 83,069 cases were used because of the university A course evaluation organized in the second semester of 2020, and a total of 12,919 subjects were studied. As a result of analyzing the aspects of course evaluation through class plan, content delivery, communication, response, and evaluation system, that were the sub-factors of course evaluation, the miscellaneous material profiles were classified in four. It was named as the upper group. As factors determining the latent profile using physiological data analysis. It was discovered that significant differences existed between student features (grade, major field), professor features (position), and lecture variables (category of accomplishment, lecture size). Students with lesser grades have a greater chance of succeeding quickly in the top group than do those in the humanities and social sciences, science, or engineering professions. The likelihood of being in the upper group in a course assessment as well as the likelihood of being in the upper group with higher course evaluation outcomes for general education lectures as opposed to major lectures and smaller lecture sizes increases with decreasing professor status. The level of academic obligation was then examined by potential profile based on the course evaluation outline, and the results revealed that the greater the course evaluation result, the greater the level of educational obligation. This is a significant study because it examines the variables that affect the outcomes of the university's course evaluations, which are done at the end of every semester, as well as the relationship between the outcomes of the course evaluations and academic commitment. This study established a scientific basis for colleges to prepare measures to improve the quality of education through lecture evaluation and emphasized the importance of preparing concrete measures to improve students' learning outcomes in college education.

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Exploration of the Predictors of Lecture Evaluation in College of Engineering using Decision Tree Analysis

YeongJu¹

2018

journalofengineeringeducationresearch

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Meta-research on the influence of course, instructor, and student characteristics in student evaluation of teaching at universities

Cited by 3 publications

References 3 publications

Instructor factors associated with medical students’ lecture evaluation: a longitudinal analysis

Instructor factors associated with medical students’ lecture evaluation: a longitudinal analysis

The Relationship between Course Evaluation and Academic Achievement of University Students Using Latent Profile Analysis

Exploration of the Predictors of Lecture Evaluation in College of Engineering using Decision Tree Analysis

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