Different administrative directions and student ratings of instruction: Cognitive versus affective effects

1978 ◽  
Vol 9 (2) ◽  
pp. 161-167 ◽  
Author(s):  
Robert M. Pasen ◽  
Peter W. Frey ◽  
Robert J. Menges ◽  
Gustave J. Rath
Keyword(s):  
Student Ratings ◽  
Student Ratings Of Instruction

Relationship of Curriculum Area and Course Format with Student Ratings of Instruction

1978 ◽  
Vol 15 (4) ◽  
pp. 483-487 ◽  
Author(s):  
Isaac I. Bejar ◽  
Kenneth O. Doyle
Keyword(s):  
Multivariate Analysis ◽  
Analysis Of Variance ◽  
Significant Relationship ◽  
Student Ratings ◽  
Multivariate Analysis Of Variance ◽  
Student Ratings Of Instruction ◽  
Course Format ◽  
Curriculum Area ◽  
Relationship Of

Multivariate analysis of variance revealed a significant relationship between student ratings and curriculum area but not between ratings and course format. The technical and practical ramifications of these findings are discussed.

Student Ratings of Instruction in Distance Learning and On-Campus Classes

1999 ◽  
Vol 92 (3) ◽  
pp. 132-140 ◽  
Author(s):  
Fred Spooner ◽  
Luann Jordan ◽  
Bob Algozzine ◽  
Melba Spooner
Keyword(s):  
Distance Learning ◽  
Student Ratings ◽  
Student Ratings Of Instruction

scholarly journals Addressing Common Concerns about Online Student Ratings of Instruction: A Research-Informed Approach

2017 ◽  
Vol 46 (4) ◽  
pp. 115-131
Author(s):  
Laura R. Winer ◽  
Lina Di Genova ◽  
Andre Costopoulos ◽  
Kristen Cardoso
Keyword(s):  
Student Ratings ◽  
Student Body ◽  
Online Student ◽  
Student Responses ◽  
Student Ratings Of Instruction ◽  
Student Academic Performance ◽  
Final Exams ◽  
Academic Units ◽  
Canadian Research ◽  
Over Time

Concerns over the usefulness and validity of student ratings of instruction (SRI) have continued to grow with online processes. This paper presents seven common and persistent concerns identified and tested during the development and implementation of a revised SRI policy at a Canadian research-intensive university. These concerns include bias due to insufficient sample size, student academic performance, polarized student responses, disciplinary differences, class size, punishment of rigorous instructor standards, and timing of final exams. We analyzed SRI responses from two mandatory Likert scale questions related to the course and instructor, both of which were consistent over time and across all academic units at our institution. The results show that overall participation in online SRIs is representative of the student body, with academically stronger students responding at a higher rate, and the SRIs, themselves, providing evidence that may moderate worries about the concerns.   

scholarly journals Student Ratings of Teaching Effectiveness: Student Engagement and Course Characteristics

2010 ◽  
Vol 39 (1) ◽  
Author(s):  
Tanya Beran ◽  
Claudio Violato
Keyword(s):  
Student Engagement ◽  
Latent Variable ◽  
Teaching Effectiveness ◽  
Student Ratings ◽  
Path Model ◽  
Course Characteristics ◽  
Student Ratings Of Instruction ◽  
Fit Index ◽  
Student Ratings Of Teaching ◽  
Latent Variable Path

Characteristics of university courses and student engagement were examined in relation to student ratings of instruction. The Universal Student Ratings of Instruction instrument was administered to students at the end of every course at a major Canadian university over a three-year period. Using a two-step analytic procedure, a latent variable path model was created. The model showed a moderate fit to the data (Comparative Fit Index = .88), converged in _0 iterations, with a standardized residual mean error of .03, χ2 (_49) = _988.59, p < .05. The model indicated that course characteristics such as status and description are not directly related to student ratings. Rather, they are mediated by student engagement, which is measured by student attendance and expected grade. It was concluded that, although the model is statistically adequate, many other factors determine how students rate their instructors.  

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