Valencia College

Issues of Implicit Bias in SFIWhat are implicit biases? Implicit biases are unconscious beliefs developed based upon “automatic tendencies to associate certain traits with members of particular social groups, in ways that lead to some very disturbing errors” (Saul, 2013). As Saul notes, “We tend to judge members of stigmatized groups more negatively,” even if it happens on a subconscious level (Saul, 2013). In short, these are biases that occur independent of our own will — learned beliefs that are absorbed through exposure to diverse media, cultural beliefs, and interpersonal relationships, which inevitably impact our ability to evaluate and assess others. There will be an inherent bias that occurs in all faculty evaluation, particularly for women, faculty of diverse races and nationalities, older faculty, faculty who suffer from disabilities, and even faculty who do not conform to traditional standards and norms of beauty (Baldwin and Blattner, 2003). For example, gender bias was evident when evaluating male/female teaching teams (Wagner, Matthias, and Voorvelt, 2016), as well as in online classes where different genders were assigned to identical sections of a course; in both cases, significantly different SFI was the result (Machnell, Driscoll, and Hunt, 2015). What must Valencia do about implicit bias in faculty evaluation? Controlling the effects of implicit bias on faculty is crucial. If SFI is used for faculty evaluations for promotion, tenure, or other teaching awards, women and people of underrepresented groups are immediately placed at a disadvantage to their white, male cisgender peers (Deo, 2015; Wagner, Matthias, and Voorvelt, 2016). Connecting SFI to tenure or compensation should be especially dubious given the study by Uttl, White, and Wong Gonzalez, which showed no relationship between SFI and faculty effectiveness or student learning (2016). Managing implicit bias can occur through careful training of both faculty and administration, and in noting that student evaluation of faculty effectiveness is only a small component in the overall assessment of faculty performance. When SFI is discussed with an adjunct or NSE faculty, the same expectations should be held of the evaluator.SFI should inform faculty on their teaching practice, rather than being a high stakes test that some are inherently more likely to score lower on than others. Offering administrators reviewing student evaluations of faculty performance specialized training, such as negation training or forms of training that help to identify patterns of implicit bias, might help minimize the effects of implicit bias within faculty evaluation (Kawakami, et al., 2000). Ultimately, however, this is only a stopgap, and won’t serve to completely remove implicit bias from the evaluation process.What strategies might Valencia utilize to best control for implicit bias? Effective methods to alleviate implicit bias, according to Baldwin and Blattener, may include the use of varied teaching evaluation methods, the use of formative assessments, consideration of a teaching portfolio, and the ability to place results into the context of the classroom composition (Baldwin and Blattener, 2003). Valencia currently has just begun a system for allowing evaluation through a holistic teaching practices — namely, our use of Annual Faculty Evaluation and Post Tenure Review. Any faculty or administration involved in this assessment process should be given specialized training in identifying the role of implicit bias in the evaluation process, regardless of seemingly objective standards in the process. Finally, even in the event of objective questions in the SFI, we as an institution must acknowledge that implicit bias will be a factor; we must consider this when deciding what information to make public, versus what information to keep confidential. It is an uncontrollable factor that will inevitably be a part of the process. Works CitedBaldwin, T., & Blattner, N. (2003). “Guarding Against Potential Bias in Student Evaluations.” College Teaching, 51(1), 27.Deo, M. E. (2015). “A better tenure battle: fighting bias in teaching evaluations.” Columbia Journal of Gender and Law, 31(1), 7+.Germain, M.-L., & Scandura, T. A. (2005). “Grade inflation and student individual differences as systematic bias in faculty evaluations.” Journal of Instructional Psychology, 32 (1), 58+.Kawakami, K., Moll, J., Hermsen, S., Dovidio, J. F., & Russin, A. (2000). “Just Say No (to Stereotyping): Effects of Training in the Negation of Stereotypic Associations on Stereotype Activation.” Journal of Personality and Social Psychology, 78 (5), 871. Macnell, L., Driscoll, A., & Hunt, A. (2015). “What’s in a Name: Exposing Gender Bias in Student Ratings of Teaching.” Innovative Higher Education, 40 (4), 291-303.Nowell, C., Gale, L., & Kerkvliet, J. (2014). “Non-response Bias in Student Evaluations of Teaching.” International Review of Economics Education, 17, 30-38.Reisenwitz, T. (2016). "Student Evaluation of Teaching.” Journal of Marketing Education, 38 (1), 7-17.Saul, J. (2013). "Scepticism And Implicit Bias.” Disputatio: International Journal Of Philosophy, 5 (37), 243-263.Uttl, B., White, C., & Gonzalez, D. (2016). "Meta-analysis of Faculty's Teaching Effectiveness: Student Evaluation of Teaching Ratings and Student Learning Are Not Related.” Studies in Educational Evaluation, n. pag.Wagner, N., Rieger, M., & Voorvelt, K. (2016). "Gender, Ethnicity and Teaching Evaluations: Evidence from Mixed Teaching Teams.” Economics of Education Review, 54, 79-94.Wolbring, T., & Treischl, E. (2016). "Selection Bias in Students' Evaluation of Teaching.” Research in Higher Education, 57 (1), 51-71.

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