Professional judgment is required whenever conditions are uncertain. This article provides an analysis of professional judgment and describes sources of error in decision making.
Barnett, D. W. (1988). Professional judgment: A critical appraisal. School Psychology Review., 17(4), 658-672.
This article examines issues relating to the use of websites popular with educators. This article offers guidelines for maximizing the usefulness of such sites and for avoiding many of the pitfall educators may face.
Beahm, L. A., Cook, B. G., & Cook, L. (2019). Proceed With Caution: Using Web-Based Resources for Instructing Students With and at Risk for EBD. Beyond Behavior, 28(1), 13-20.
This web site reviews, assesses, and provides guidelines on how to decide which are trustworthy, whether you want to submit articles, serve as an editor, or serve on an editorial board. The web site provides a list that mostly consists of open access journals, although, a few non-open access publishers whose practices match those of predatory publishers have been added to the list.
Beall, J. (2012). Predatory publishers are corrupting open access. Nature, 489(7415), 179.
This paper predicted that out-group empathy would inhibit inter-group harm and promote inter-group helping, whereas in-group empathy would have the opposite effect. In all samples, in-group and out-group empathy had independent, significant, and opposite effects on inter-group outcomes, controlling for trait empathic concern.
Bruneau, E. G., Cikara, M., & Saxe, R. (2017). Parochial empathy predicts reduced altruism and the endorsement of passive harm. Social Psychological and Personality Science, 8(8), 934-942.
Judgements are influenced by multiple factors. This paper explores how information about outcomes influences judgments.
Fischhoff, B. (1975). Hindsight is not equal to foresight: The effect of outcome knowledge on judgment under uncertainty. Journal of Experimental Psychology: Human perception and performance, 1(3), 288-299.
Conventional wisdom holds that heuristics and biases lead to flawded decision making. This paper makes the case that under some conditions they actually make decision-making more efficient.
Gigerenzer, G., & Brighton, H. (2009). Homo heuristicus: Why biased minds make better inferences. Topics in Cognitive Science, 1, 107-143. doi:10.1111/j.1756-8765.2008.01006.
This Article introduces implicit bias-an aspect of the new science of unconscious mental processes that has substantial bearing on discrimination law.
Greenwald, A. G., & Krieger, L. H. (2006). Implicit bias: Scientific foundations. California Law Review, 94(4), 945-967.
Many writers who are not scientists themselves are trading on the prestige of science and the authority of scientists. Reference to “peer-reviewed research” and to an alleged “scientific consensus” are regarded as veritable knock-out blows by many commentators.
Higgs, R. (2007). Peer review, publication in top journals, scientific consensus, and so forth. The Independent Institute, 7.
The Percentage of Proficient Students (PPS) has become a ubiquitous statistic under the No Child Left Behind Act. The author demonstrates that the PPS metric offers only limited and unrepresentative depictions of large-scale test score trends, gaps, and gap trends. The author shows how the statistical shortcomings of these depictions extend to shortcomings of policy, from exclusively encouraging score gains near the proficiency cut score to shortsighted comparisons of state and national testing results. The author proposes alternatives for large-scale score reporting and argues that a distribution-wide perspective on results is required for any serious analysis of test score data, including “growth”-related results under the recent Growth Model Pilot Program.
Ho, A. D. (2008). The problem with “proficiency”: Limitations of statistics and policy under No Child Left Behind. Educational researcher, 37(6), 351-360.
A meta-analysis on the relationship between the Implicit Association Test (IAT) and corresponding explicit self-report measures was conducted.
Hofmann, W., Gawronski, B., Gschwendner, T., Le, H., & Schmitt, M. (2005). A meta-analysis on the correlation between the Implicit Association Test and explicit self-report measures. Personality and Social Psychology Bulletin, 31(10), 1369-1385.
In this article, we respond at length to recent critiques of research on implicit bias, especially studies using the Implicit Association Test (IAT). These studies reveal that students, nurses, doctors, police officers, employment recruiters, and many others exhibit implicit biases with respect to race, ethnicity, nationality, gender, social status, and other distinctions.
Jost, J. T., Rudman, L. A., Blair, I. V., Carney, D. R., Dasgupta, N., Glaser, J., & Hardin, C. D. (2009). The existence of implicit bias is beyond reasonable doubt: A refutation of ideological and methodological objections and executive summary of ten studies that no manager should ignore. Research in organizational behavior, 29, 39-69.
What, if anything, should we do about implicit bias in the courtroom? The authors comprises legal academics, scientists, researchers, and even a sitting federal judge who seek to answer this question in accordance with behavioral realism.
Kang, J., Bennett, M., Carbado, D., & Casey, P. (2011). Implicit bias in the courtroom. UCLa L. rev., 59, 1124.
The chapter focuses on the historically perceived poor methodological rigor and low scientific credibility of most educational/psychological intervention research.
Levin, J. R., & Kratochwill, T. R. (2012). Educational/psychological intervention research circa 2012. Handbook of Psychology, Second Edition, 7.
Lin, M., Lake, V. E., & Rice, D. (2008). Teaching anti-bias curriculum in teacher education programs: What and how. Teacher Education Quarterly, 35(2), 187-200.
This study investigated communicative strategies for helping female students cope with ‘‘stereotype threat’’. The results demonstrate that priming a positive achieved identity (e.g., private college student) can subdue stereotype threat associated with an ascribed identity (e.g., female).
McGlone, M. S., & Aronson, J. (2007). Forewarning and forearming stereotype-threatened students. Communication Education, 56(2), 119-133.
A variety of researches are examined from the standpoint of information theory. It is shown that the unaided observer is severely limited in terms of the amount of information he can receive, process, and remember. However, it is shown that by the use of various techniques, e.g., use of several stimulus dimensions, recoding, and various mnemonic devices, this informational bottleneck can be broken.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological review, 63(2), 81.
This article reports a meta-analysis of studies examining the predictive validity of the Implicit Association Test (IAT) and explicit measures of bias for a wide range of criterion measures of discrimination.
Oswald, F. L., Mitchell, G., Blanton, H., Jaccard, J., & Tetlock, P. E. (2013). Predicting ethnic and racial discrimination: A meta-analysis of IAT criterion studies. Journal of personality and social psychology, 105(2), 171.
The authors extend Mangan's account of fringe consciousness by discussing their work on processing experiences. This research shows that variations in speed at different stages of perceptual processing can jointly contribute to subjective processing ease, supporting Mangan's notion that different mental processes condense into one subjective experience.
Reber, R., Fazendeiro, T. A., & Winkielman, P. (2002). Processing fluency as the source of experiences at the fringe of consciousness. Psyche, 8(10), 1-21.
Current systems for listing empirically supported therapies (ESTs) provide recognition to treatment packages, many of them proprietary and trademarked, without regard to the principles of change believed to account for their effectiveness.
Rosen, G. M., & Davison, G. C. (2003). Psychology should list empirically supported principles of change (ESPs) and not credential trademarked therapies or other treatment packages. Behavior modification, 27(3), 300-312.
The National Assessment of Educational Progress is widely viewed as the most accurate and reliable yardstick of U.S. students’ academic knowledge. But when it comes to many of the ways the exam’s data are used, researchers have gotten used to gritting their teeth.
Sawchuk, S. (2013). When bad things happen to good NAEP data. Education Week, 32(37), 1-22.
This paper examines the types of research to consider when evaluating programs, how to know what “evidence’ to use, and continuums of evidence (quantity of the evidence, quality of the evidence, and program development).
Twyman, J. S., & Sota, M. (2008). Identifying research-based practices for response to intervention: Scientifically based instruction. Journal of Evidence-Based Practices for Schools, 9(2), 86-101.