A model derived from the theory of planned behavior was empirically assessed for understanding faculty intention to use student ratings for teaching improvement. A sample of 175 professors participated in the study. The model was statistically significant and had a very large explanatory power. Instrumental attitude, affective attitude, perceived capability, and perceived controllability were statistically significant contributors in explaining directly variability in faculty intention. Past use of student ratings–intention relationship was mostly indirect.
AdamsJ.CochraneM.DunneL. (2012). Applying theory to educational research: An introductory approach with case studies. Malden, MA: Wiley-Blackwell.
2.
AjjanH.HartshorneR. (2008). Investigating faculty decisions to adopt Web 2.0 technologies: Theory and empirical tests. The Internet and Higher Education, 11, 71-80.
3.
AjzenI. (1988). Attitudes, personality, and behavior. Chicago, IL: Dorsey Press.
4.
AjzenI. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
5.
AjzenI. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32, 665-683.
AjzenI. (2011). The theory of planned behaviour: Reactions and reflections. Psychology & Health, 26, 1113-1127.
8.
AjzenI. (2015). The theory of planed behavior is alive and well, and not ready to retire: A commentary to Seniehotta, Presseau, and Araújo-Soares. Health Psychology Review, 9, 131-137. doi:10.1080/17437199.2014.883474
9.
Al-IssaA.SuleimanH. (2007). Student evaluation of teaching: Perceptions and biasing factors. Quality Assurance in Education, 15, 302-317.
10.
ArmitageC. J.ConnerM. (2001). Efficacy of the theory of planned behavior: A meta-analytic review. The British Journal of Social Psychology, 40, 471-499.
11.
BanduraA. (1997). Self-efficacy: The exercise of control. New York, NY: W. H. Freeman.
12.
BarnettC. W.MatthewsH. W. (1997). Student evaluation of classroom teaching: A study of pharmacy faculty attitudes and effects on instructional practices. American Journal of Pharmaceutical Education, 61, 345-350.
BeranT. N.RokoshJ. L. (2009). Instructors’ perspectives on the utility of student ratings of instruction. Instructional Science, 37, 171-184.
15.
BiesanzJ. C.FalkC. F.SavaleiV. (2010). Assessing mediational models: Testing and interval estimation for indirect effects. Multivariate Behavioral Research, 45, 661-701.
16.
BlairE.Valdez-NoelK. (2014). Improving higher education practice through student evaluation systems: Is student voice being heard?Assessment & Evaluation in Higher Education, 39, 879-894.
17.
BrydenP. J.FletcherP. C. (2007). Personal safety practices, beliefs and attitudes of academic faculty on a small university campus: Comparison of males and females (Part 1). College Student Journal, 41, 613-622.
18.
CentraJ. A. (1993). Reflective faculty evaluation: Enhancing teaching and determining faculty effectiveness. San Francisco, CA: Jossey-Bass.
19.
CinéasJ. K. (2008). A study of perceptions of the use of student evaluations of teaching in faculty assessments, promotion, and tenure decisions (Doctoral Dissertation, Lynn University). Available from ProQuest Dissertations and Theses. (UMI No. 3304610)
20.
CohenJ. (1992). A power primer. Psychological Bulletin, 112, 155-159.
21.
CohenP. A. (1980). Effectiveness of student-rating feedback for improving college instruction: A meta-analysis of findings. Research in Higher Education, 13, 321-341.
22.
CollazoA. (2011). Representaciones sociales de profesores universitarios acerca del cuestionario estudiantil sobre su desempeño en la enseñanza y el mejoramiento de la enseñanza a partir de los resultados obtenidos [Social representations of university professors about student questionnaire regarding their performance and teaching improvement based on its results]. Pedagogía, 44, 59-94.
23.
CollazoA. A. (2004). Theory-based predictors of intention to engage in precautionary sexual behavior among Puerto Rican high school adolescents. Journal of HIV/AIDS Prevention in Children & Youth, 6, 91-120.
24.
ConnerM.ArmitageC. J. (1998). Extending the theory of planned behavior: A review and avenues for further research. Journal of Applied Social Psychology, 28, 1429-1464.
25.
ConnerM.WarrenR.CloseS.SparksP. (1999). Alcohol consumption and the theory of planned behavior: An examination of the cognitive mediation of past behavior. Journal of Applied Social Psychology, 29, 1676-1704.
26.
CorenA. (2012). The theory of planned behavior: Will faculty confront students who cheat?Journal of Academic Ethics, 10, 171-184.
27.
DonnonT.DelverH.BeranT. (2010). Student and teaching characteristics related to ratings of instruction in medical sciences and graduate programs. Medical Teacher, 32, 327-332.
28.
FishbeinM.BanduraA.TriandisH. C.KanferF. H.BeckerM. H.MiddlestadtS. E.. . . EichlerA. (2001). Factors influencing behavior and behavior change. In BaumA.RevensonT. A.SingerJ. E. (Eds.), Handbook of health psychology (pp. 3-17). Mahwah, NJ: Lawrence Erlbaum.
29.
FrancisJ. J.EcclesM. P.JohnstonM.WalkerA.GrimshawJ.FoyR.. . . BonettiD. (2004). Constructing questionnaires based on the Theory of planned behavior: A manual for health services researchers. Retrieved from http://openaccess.city.ac.uk
30.
FranklinJ.TheallM. (1989, March). Who reads ratings: Knowledge, attitude, and practice of users of student ratings of instruction (ERIC Document Reproduction Service No. ED306241). Paper presented at the Annual Meeting of the American Educational Research Association, San Francisco, CA.
31.
FranklinJ.TheallM. (2002). (Thinking about) Faculty thinking about teacher and course evaluation results. In HativaN.GoodyearP. (Eds.), Teacher thinking, beliefs and knowledge in higher education (pp. 151-177). Norwell, MA: Kluwer.
32.
FreskoB.NasserF. (2001). Interpreting student ratings: Consultation, instructional modification, and attitudes towards course evaluation. Studies in Educational Evaluation, 27, 291-305.
33.
GravestockP.Gregor-GreenleafE. (2008). Student course evaluations: Research, models and trends. Toronto: Higher Education Quality Council of Ontario
34.
HaggerM. S.ChatzisarantisN. L. D. (2005). First- and higher-order models of attitudes, normative influence, and perceived behavioral control in the theory of planned behavior. The British Journal of Social Psychology, 44, 513-535.
HemphillJ. F. (2003). Interpreting the magnitudes of correlation coefficients. American Psychologist, 58, 78-79.
37.
HuybersT. (2014). Student evaluation of teaching: The use of best-worst scaling. Assessment & Evaluation in Higher Education, 39, 496-513.
38.
IPEDS Data Center, National Center for Education Statistics. (n.d.). U.S. Department of Education. Retrieved from https://nces.ed.gov/ipeds
39.
KieltyL. (2010). Factors that influence faculty intentions to support the community college baccalaureate (Doctoral Dissertation, University of South Florida). Available from ProQuest Dissertations and Theses. (UMI No. 3427261)
40.
KlineR. B. (2011). Principles and practice of structural equation modeling. New York, NY: Guilford Press.
41.
KnolM. H.in’t VeldR.VorstH. C. M.van DrielJ. H.MellenberghG. J. (2013). Experimental effects of student evaluations coupled with collaborative consultation on college professors’ instructional skills. Research in Higher Education, 54, 825-850. doi:10.1007/s11162-013-9298-3
42.
KoganJ. R.SheaJ. A. (2007). Course evaluation in medical education. Teaching and Teacher Education: International Journal of Research and Studies, 23, 251-264. doi:10.1016/j.tate.2006.12.020
43.
MacKinnonD.FairchildA. J. (2009). Current directions in mediation analysis. Current Directions in Psychological Science, 18, 16-20. doi:10.1111/j.1467-8721.2009.01598.x
44.
MarshH. W.RocheL. A. (1993). The use of students’ evaluations and an individually structured intervention to enhance university teaching effectiveness. American Educational Research Journal, 30, 217-251.
NasserF.FreskoB. (2002). Faculty views of student evaluation of college teaching. Assessment & Evaluation in Higher Education, 27, 187-198.
48.
NorwichB.DuncanJ. (1990). Attitudes, subjective norms, perceived preventive factors, intentions, and learning science. British Journal of Educational Psychology, 60, 312-321.
49.
NunnallyJ. C.BernsteinI. H. (1994). Psychometric theory. New York, NY: McGraw-Hill.
50.
OryJ. C.RyanK. (2001). How do student ratings measure up to a new validity framework? In TheallM.AbramiP. C.MetsL. A. (Eds.), New directions for institutional research (Vol. 109, pp. 27-44). San Francisco, CA: Jossey-Bass.
51.
PennyA. R. (2003). Changing the agenda for research into students’ views about university teaching: Four shortcomings of SRT research. Teaching in Higher Education, 8, 399-411.
52.
PennyA. R.CoeR. (2004). Effectiveness of consultation on student ratings feedback: A meta-analysis. Review of Educational Research, 74, 215-253.
53.
PeughJ. L.EndersC. K. (2004). Missing data in educational research: A review of reporting practices and suggestions for improvement. Review of Educational Research, 74, 525-556.
54.
PreacherK. J.HayesA. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879-891.
RhodesR. E.BlanchardC. M.MathesonD. H. (2006). A multicomponent model of the theory of planned behavior. British Journal of Health Psychology, 11, 119-137.
57.
RhodesR. E.CourneyaK. S. (2003). Investigating multiple components of attitude, subjective norm, and perceived control: An examination of the theory of planned behavior in the exercise domain. The British Journal of Social Psychology, 42, 129-146.
58.
SafaviS. A.BakarK. A.TarmiziR. A.AlwiN. H. (2013). Faculty perception of improvements to instructional practices in response to student ratings. Educational Assessment, Evaluation and Accountability, 25, 143-153.
59.
SchaferJ. L. (1999). NORM (Windows version 2.03) [Computer software]. University Park: Department of Statistics, Pennsylvania State University. Available from http://methodology.psu.edu
60.
SchaferJ. L.OlsenM. K. (1998). Multiple imputation for multivariate missing data problems: A data analyst’s perspective. Multivariate Behavioral Research, 33, 545-571.
61.
SmithJ. R.TerryD. J.MansteadA. S. R.LouisW. R.KottermanD.WolfsJ. (2008). The attitude-behavior relationship in consumer conduct: The role of norms, past behavior, and self-identity. The Journal of Social Psychology, 148, 311-333.
62.
SpencerP. A.FlyrM. L. (1992). The formal evaluation as an impetus to classroom change: Myth or reality. Riverside, CA: University of California, (ERIC Document Reproduction Service No. 349053).
63.
SteinS. J.SpillerD.TerryS.HarrisT.DeakerL.KennedyJ. (2013). Tertiary teachers and student evaluations: Never the twain shall meet?Assessment & Evaluation in Higher Education, 38, 892-904.
64.
SuttonS. (1998). Predicting and explaining intentions and behavior: How well are we doing?Journal of Applied Social Psychology, 28, 1317-1338.
65.
SuttonS. (2002). Using social cognition models to develop health behavior interventions: Problems and assumptions. In RutterD.QuineL. (Eds.), Intervention research with social cognition models (pp. 193-208). Buckingham, UK: Open University Press.
66.
WrightS. L.Jenkins-GuarnieriM. A. (2012). Student evaluations of teaching: Combining the meta-analyses and demonstrating further evidence for effective use. Assessment & Evaluation in Higher Education, 37, 683-699.
67.
YaoY.WeissingerE.GradyM. (2003). Faculty use of student evaluation feedback. Practical Assessment, Research & Evaluation, 8(21). Retrieved from http://PAREonline.net/getvn.asp?v=8&n=21
68.
ZuberiR. W.BordageG.NormanG. R. (2007). Validation of the SETOC instrument—Student evaluation of teaching in outpatient clinic. Advances in Health Science Education, 12, 55-69. doi:10.1007/s10459-005-2328-y