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CHAPTER 3 LITERATURE REVIEW AND FOCUSING THE RESEARCH Although previous works have documented some of the challenges that African American males encounter in schools, there is a pressing need to examine the larger body of research on Black males and develop a comprehensive account of what we know about this population, what general trends exist in the literature about them, identify some of the strengths and problems with the current literature base, and be able to offer some recommendations for future research, theory, and practice on this population. —Howard, 2013, p. 56 How does it feel to be a problem? —W. E. B. Du Bois, 1903/2003, p. 7 In This Chapter Two major reasons for conducting a literature review are explained: as a basis for conducting your own research or as an end in itself. A nine-step process for conducting a literature review is outlined: Development of the focus of your research Review of secondary sources to get an overview of the topics Development of a search strategy, including identification...

What does it mean when a study is considered internally valid? This term refers to the design of the study, which allows you to be confident that the results are not open to alternative interpretations. No study is truly perfect, but there are ways you can maximize the integrity of an experiment. The examples of validity given in the introduction to Section 2 are worth revisiting. For example, if you want to get an idea of whether people prefer cats or dogs, you should not just sample people from the Cat Protection League because they are already biased towards cats. If you want to examine if introducing a specific teaching technique is effective at improving academic performance, you need a comparison group because it may be that students improve over time. If you do not have a comparison group, any improvements could be a natural improvement over time, referred to as maturation, a common error in research design. Studies that examine effectiveness without...

Beware of testing too many hypotheses; the more you torture the data, the more likely they are to confess, but confession obtained under duress may not be admissible in the court of scientific opinion. —Stigler (as cited in Mark & Gamble, 2009, p. 210) Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. —Greenland, Senn, Rothman, Carlin, Poole, Goodman, & Altman, 2016, p. 337 In This Chapter Common types of statistics used for quantitative data analysis are defined, along with methods for choosing among them. Computer software for quantitative analysis are discussed. Interpretation issues relevant to quantitative data analysis are discussed, including randomization, sample size, statistical versus practical significance, cultural bias, generalizability, and options for reporting quantitative results, such as effect sizes and variance accounted for, replication, use of nonparametric statistics, exploration of competing explanations, recognition of a study’s limitations, and a principled discovery strategy. Effect sizes as a part of statistical synthesis (i.e., meta-analysis) as a...

In the late 1800s, the prevailing myth held that men were more intelligent than women. Mary Calkins, a psychologist, conducted experiments at Wellesley College in 1887 that demonstrated that women are just as intelligent as men. —Furumoto, 1980 Compelling pedagogical interests require that each program prepare graduates to navigate cultural and individual differences in research and practice, including those that may produce value conflicts or other tensions arising from the intersection of different areas of diversity. —American Psychological Association Commission on Accreditation, 2016, p. 8 What clinical experiences have enhanced completer’s understanding of diversity and equity issues and their readiness to use that understanding in teaching situations? What applications of technology have prepared completers for their responsibilities on the job? —Council for the Accreditation of Educator Preparation, 2018, p. 37 How can school counselors help students in low-income schools get good grades? —Williams, Steen, Albert, Dely, Jacobs, Nagel, and Irick, 2018, p. 156 The ways of Indigenous research are as old as the hills and the valleys, the...

Beware of testing too many hypotheses; the more you torture the data, the more likely they are to confess, but confession obtained under duress may not be admissible in the court of scientific opinion. —Stigler (as cited in Mark & Gamble, 2009, p. 210) Misinterpretation and abuse of statistical tests, confidence intervals, and statistical power have been decried for decades, yet remain rampant. —Greenland, Senn, Rothman, Carlin, Poole, Goodman, & Altman, 2016, p. 337 In This Chapter Common types of statistics used for quantitative data analysis are defined, along with methods for choosing among them. Computer software for quantitative analysis are discussed. Interpretation issues relevant to quantitative data analysis are discussed, including randomization, sample size, statistical versus practical significance, cultural bias, generalizability, and options for reporting quantitative results, such as effect sizes and variance accounted for, replication, use of nonparametric statistics, exploration of competing explanations, recognition of a study’s limitations, and a principled discovery strategy. Effect sizes as a part of statistical synthesis (i.e., meta-analysis) as a...