Disciplinary Differences in Student Ratings of Teaching Quality

Comparisons of large samples of course and teaching evaluation questionnaire data show consistent disciplinary differences. The current study examined the disciplinary differences in a theoretical model positing the impact of the perceived nature of teaching and learning environment on the development of generic capabilities by testing of (1) whether a common model of good teaching operated across disciplines and (2) the extent of deployment of teaching variables and their impact on learning outcomes. The sample consisted of 3,305 first and third year Chinese undergraduates of a university in Hong Kong, divided into four broad disciplinary groupings. Multiple-group structural equation modelling analysis showed configural invariance of the hypothesised model, suggesting a common model of good teaching across disciplines; and significant differences in the magnitude of structural paths and latent mean values across the four disciplinary groups were obtained reflecting differences between disciplines in the extent to which elements within the teaching and learning environment were brought into play. Possible reasons in terms of the epistemological nature of the disciplines were given to explain for the disciplinary variations.

[1]  Carmel McNaught,et al.  Enhancing University Teaching: Lessons from Research into Award-Winning Teachers , 2007 .

[2]  Raymond P. Perry,et al.  The Scholarship of Teaching and Learning in Higher Education: An Evidence-Based Perspective , 2007 .

[3]  Bengt Muthén,et al.  Testing for the Equivalence of Factor Covariance and Mean Structures : The Issue of Partial Measurement In variance , 1989 .

[4]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[5]  H. Marsh.  Students’ Evaluations of University Teaching: Dimensionality, Reliability, Validity, Potential Biases and Usefulness , 1984 .

[6]  Joan S. Stark,et al.  Modifying the Major: Discretionary Thoughts from Ten Disciplines , 2017 .

[7]  A. Shapiro,et al.  On the multivariate asymptotic distribution of sequential Chi-square statistics , 1985 .

[8]  David Kember,et al.  Characterising a teaching and learning environment conducive to making demands on students while not making their workload excessive , 2006 .

[9]  J. S. Long,et al.  Testing Structural Equation Models , 1993 .

[10]  W. McKeachie.  Student ratings: The validity of use. , 1997 .

[11]  Janet Leckey,et al.  Right Tracks—Wrong Rails: The Development of Generic Skills in Higher Education , 1997 .

[12]  Raymond P. Perry,et al.  Effective teaching in higher education : research and practice , 1997 .

[13]  S. Barrie.  Understanding What We Mean by the Generic Attributes of Graduates , 2006 .

[14]  K. Feldman.  Identifying exemplary teaching: Using data from course and teacher evaluations , 1996 .

[15]  P. Abrami,et al.  Students' Evaluations of University Teaching: Research Findings, Methodological Issues, and Directions for Future Research , 1987 .

[16]  Kenneth A. Bollen,et al.  Structural Equations with Latent Variables , 1989 .

[17]  David Kember,et al.  Development of a questionnaire for assessing students’ perceptions of the teaching and learning environment and its use in quality assurance , 2009 .

[18]  L. M. Aleamoni.  Student Rating Myths Versus Research Facts from 1924 to 1998 , 1999 .

[19]  Stephen G. West,et al.  Structural equation models with non-normal variables: Problems and remedies , 1995 .

[20]  P. Bentler,et al.  Comparative fit indexes in structural models. , 1990, Psychological bulletin.

[21]  H. Marsh.  Students ' Evaluations of University Teaching : Dimensionality , Reliability , Validity , Potential Biases , and Utility , 2005 .

[22]  David Kember,et al.  The Influence of Teaching Approach and Teacher-Student Interaction on the Development of Graduate Capabilities , 2006 .

[23]  David Kember,et al.  The Influence of the Teaching and Learning Environment on the Development of Generic Capabilities Needed for a Knowledge-Based Society , 2005 .

[24]  Gary D. Fenstermacher,et al.  Approaches to Teaching , 1986 .

[25]  L. Shulman.  Those Who Understand: Knowledge Growth in Teaching , 1986 .

[26]  B. Byrne.  Structural equation modeling with EQS : basic concepts, applications, and programming , 2000 .

[27]  Kam-por Kwan,et al.  How Fair are Student Ratings in Assessing the Teaching Performance of University Teachers , 1999 .

[28]  N. Entwistle,et al.  Understanding Student Learning , 1983 .

[29]  Kenneth A. Feldman,et al.  Course characteristics and college students' ratings of their teachers: What we know and what we don't , 1978 .

[30]  David Kember,et al.  The influence of the part time study experience on the development of generic capabilities , 2005 .

[31]  H. Tait,et al.  Defining and Assessing Competence in Generic Skills , 1999 .

[32]  Tony Becher,et al.  Academic Tribes and Territories: Intellectual Enquiry and the Cultures of Disciplines , 2001 .

[33]  P. Lachenbruch.  Statistical Power Analysis for the Behavioral Sciences (2nd ed.) , 1989 .

[34]  K. Trigwell,et al.  How approaches to teaching are affected by discipline and teaching context , 2006 .

[35]  L. Shulman.  Knowledge and Teaching: Foundations of the New Reform , 1987 .

[36]  N. Entwistle,et al.  EFFECTS OF ACADEMIC DEPARTMENTS ON STUDENTS' APPROACHES TO STUDYING , 1981 .

[37]  M. Browne,et al.  Alternative Ways of Assessing Model Fit , 1992 .

[38]  Yoram Neumann,et al.  Determinants of Students' Instructional Evaluation: A Comparison of Four Levels of Academic Areas -A , 1985 .

[39]  K. Feldman.  Identifying Exemplary Teachers and Teaching: Evidence from Student Ratings 1 , 2007 .

[40]  David Kember,et al.  Comparability of Data Gathered from Evaluation Questionnaires on Paper and Through the Internet , 2005 .

[41]  H. G. Murray,et al.  Disciplinary differences in classroom teaching behaviors , 1995 .

[42]  John A. Centra,et al.  Will Teachers Receive Higher Student Evaluations by Giving Higher Grades and Less Course Work? , 2003 .

[43]  S. Green,et al.  Control of Type I Errors with Multiple Tests of Constraints in Structural Equation Modeling. , 1997, Multivariate behavioral research.

[44]  N. Schmitt.  Uses and abuses of coefficient alpha. , 1996 .

[45]  Shân Wareing.  Disciplines, discourse and Orientalism: the implications for postgraduate certificates in learning and teaching in higher education , 2009 .

[46]  A. Biglan.  The characteristics of subject matter in different academic areas. , 1973 .

[47]  Carmel McNaught,et al.  Excellent University Teaching , 2006 .

[48]  John M. Braxton,et al.  AFFINITY DISCIPLINES AND THE USE OF PRINCIPLES OF GOOD PRACTICE FOR UNDERGRADUATE EDUCATION , 1998 .

[49]  R. Hoyle.  Structural equation modeling: concepts, issues, and applications , 1997 .

[50]  Peter M. Bentler,et al.  EQS : structural equations program manual , 1989 .

[51]  Nira Hativa,et al.  Disciplinary differences in teaching and learning : implications for practice , 1995 .

[52]  B. Byrne,et al.  Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. , 1989 .

[53]  David Kember,et al.  The influence of active learning experiences on the development of graduate capabilities , 2005 .

[54]  William E. Cashin.  Students do rate different academic fields differently , 1990 .

[55]  Philip C. Candy,et al.  Lifelong Learning: An Enduring Mandate for Higher Education , 1991 .

[56]  J. Biggs.  Student Approaches to Learning and Studying , 1987 .

[57]  John C. Smart,et al.  Disciplinary and institutional differences in undergraduate education goals , 1995 .

[58]  R. Vandenberg,et al.  A Review and Synthesis of the Measurement Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research , 2000 .

[59]  David Kember,et al.  Characterizing Learning Environments Capable of Nurturing Generic Capabilities in Higher Education , 2007 .

[60]  D. Schoen.  Educating the reflective practitioner , 1987 .