In addition psychologists have documented various heuristics and biases that

In addition psychologists have documented various

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In addition, psychologists have documented various heuristics and biases that contribute to the misinterpretation of quantitative data (Gilovich et al., 2002), including SET scores (Boysen, 2015a, 2015b; Boysen et al., 2014). These skills enable psychologists to offer multiple solutions to the challenge posed by the need to objectively evaluate the quality of teaching and the impact of teaching on student learning. Online administration of SET forms presents multiple desirable features, including rapid feedback to instructors, economy, and support for environmental sustainability. However, institutions should adopt implementation procedures that do not undermine the usefulness of the data gathered. Moreover, institutions should be wary of emphasizing procedures that produce high response rates only to lull faculty into believing that SET data can be the primary (or only) metric used for high-stakes decisions about the quality of faculty teaching. Instead, decision makers should expect to use multiple measures to evaluate the quality of faculty teaching.
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COMPARISON OF STUDENT EVALUATIONS OF TEACHING 10 References Avery, R. J., Bryant, W. K., Mathios, A., Kang, H., & Bell, D. (2006). Electronic course evaluations: Does an online delivery system influence student evaluations? The Journal of Economic Education , 37 (1), 21–37. Berk, R. A. (2012). Top 20 strategies to increase the online response rates of student rating scales. International Journal of Technology in Teaching and Learning , 8 (2), 98–107. Berk, R. A. (2013). Top 10 flashpoints in student ratings and the evaluation of teaching . Stylus. Boysen, G. A. (2015a). Preventing the overinterpretation of small mean differences in student evaluations of teaching: An evaluation of warning effectiveness. Scholarship of Teaching and Learning in Psychology , 1 (4), 269–282. Boysen, G. A. (2015b). Significant interpretation of small mean differences in student evaluations of teaching despite explicit warning to avoid overinterpretation. Scholarship of Teaching and Learning in Psychology , 1 (2), 150–162. Boysen, G. A., Kelly, T. J., Raesly, H. N., & Casner, R. W. (2014). The (mis)interpretation of teaching evaluations by college faculty and administrators. Assessment & Evaluation in Higher Education , 39 (6), 641–656. Buller, J. L. (2012). Best practices in faculty evaluation: A practical guide for academic leaders . Jossey- Bass. Dewar, J. M. (2011). Helping stakeholders understand the limitations of SRT data: Are we doing enough? Journal of Faculty Development , 25 (3), 40–44. Dommeyer, C. J., Baum, P., & Hanna, R. W. (2002). College students’ attitudes toward methods of collecting teaching evaluations: In-class versus on-line. Journal of Education for Business , 78 (1), 11–15. Dommeyer, C. J., Baum, P., Hanna, R. W., & Chapman, K. S. (2004). Gathering faculty teaching evaluations by in-class and online surveys: Their effects on response rates and evaluations. Assessment & Evaluation in Higher Education , 29 (5), 611–623.
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