American Vocational Education Research Association Members' Perceptions of Statistical Significance Tests and Other Statistical Controversies

2001 ◽  
Vol 26 (2) ◽  
pp. 244-271 ◽  
Author(s):  
Howard R. D. Gordon
1998 ◽  
Vol 21 (2) ◽  
pp. 221-222
Author(s):  
Louis G. Tassinary

Chow (1996) offers a reconceptualization of statistical significance that is reasoned and comprehensive. Despite a somewhat rough presentation, his arguments are compelling and deserve to be taken seriously by the scientific community. It is argued that his characterization of literal replication, types of research, effect size, and experimental control are in need of revision.


2015 ◽  
Vol 46 (3) ◽  
pp. 371-376
Author(s):  
Edna O. Schack ◽  
Molly H. Fisher ◽  
Jonathan N. Thomas

“Noticing matters” (p. 223). Through these words in the concluding chapter, Alan Schoenfeld succinctly captures the theme of this seminal book, Mathematics Teacher Noticing: Seeing Through Teachers' Eyes. The book received the American Education Research Association 2013 Exemplary Research in Teaching and Teacher Education Award. It addresses a variety of meanings and interpretations of teacher noticing from Dewey's earlier work of inner and outer attention to more specific variations such as that of professional noticing, as defined by Jacobs, Lamb, and Philipp. Chapter contributors have provided the foundation and framing of teacher noticing as a construct for studying and improving teaching.


2016 ◽  
Vol 21 (1) ◽  
pp. 102-115 ◽  
Author(s):  
Stephen Gorard

This paper reminds readers of the absurdity of statistical significance testing, despite its continued widespread use as a supposed method for analysing numeric data. There have been complaints about the poor quality of research employing significance tests for a hundred years, and repeated calls for researchers to stop using and reporting them. There have even been attempted bans. Many thousands of papers have now been written, in all areas of research, explaining why significance tests do not work. There are too many for all to be cited here. This paper summarises the logical problems as described in over 100 of these prior pieces. It then presents a series of demonstrations showing that significance tests do not work in practice. In fact, they are more likely to produce the wrong answer than a right one. The confused use of significance testing has practical and damaging consequences for people's lives. Ending the use of significance tests is a pressing ethical issue for research. Anyone knowing the problems, as described over one hundred years, who continues to teach, use or publish significance tests is acting unethically, and knowingly risking the damage that ensues.


2013 ◽  
Vol 12 (3) ◽  
pp. 345-351 ◽  
Author(s):  
Jessica Middlemis Maher ◽  
Jonathan C. Markey ◽  
Diane Ebert-May

Statistical significance testing is the cornerstone of quantitative research, but studies that fail to report measures of effect size are potentially missing a robust part of the analysis. We provide a rationale for why effect size measures should be included in quantitative discipline-based education research. Examples from both biological and educational research demonstrate the utility of effect size for evaluating practical significance. We also provide details about some effect size indices that are paired with common statistical significance tests used in educational research and offer general suggestions for interpreting effect size measures. Finally, we discuss some inherent limitations of effect size measures and provide further recommendations about reporting confidence intervals.


Author(s):  
H. S. Styn ◽  
S. M. Ellis

The determination of significance of differences in means and of relationships between variables is of importance in many empirical studies. Usually only statistical significance is reported, which does not necessarily indicate an important (practically significant) difference or relationship. With studies based on probability samples, effect size indices should be reported in addition to statistical significance tests in order to comment on practical significance. Where complete populations or convenience samples are worked with, the determination of statistical significance is strictly speaking no longer relevant, while the effect size indices can be used as a basis to judge significance. In this article attention is paid to the use of effect size indices in order to establish practical significance. It is also shown how these indices are utilized in a few fields of statistical application and how it receives attention in statistical literature and computer packages. The use of effect sizes is illustrated by a few examples from the research literature.


2021 ◽  
Vol 34 (3) ◽  
pp. 78-84
Author(s):  
Richard P. Phelps

Like many science-related professional associations founded on the principles of unbiased research, nonpartisanship, and best practices, the American Educational Research Association (AERA) has become thoroughly politicized.


2006 ◽  
Vol 2 (6) ◽  
pp. 1277-1292
Author(s):  
P. D. Ditlevsen ◽  
K. K. Andersen ◽  
A. Svensson

Abstract. The significance of the apparent 1470 years cycle in the recurrence of the Dansgaard-Oeschger (DO) events, observed in the Greenland ice cores, is debated. Here we present statistical significance tests of this periodicity. The detection of a periodicity relies strongly on the accuracy of the dating of the DO events. Here we use both the new NGRIP GICC05 time scale based on multi-parameter annual layer counting and the GISP2 time scale where the periodicity is most pronounced. For the NGRIP dating the recurrence times are indistinguishable from a random occurrence. This is also the case for the GISP2 dating, except in the case where the DO9 event is omitted from the record. Whether or not the record shows a truly periodic beating has strong implications for identifying the underlying cause. If the recurrence is periodic it suggests an external cause. If the recurrence of DO events is not periodic it points to triggering mechanisms internal to the climate system being manifested at the millennial timescale.


1998 ◽  
Vol 15 (2) ◽  
pp. 103-118 ◽  
Author(s):  
Vinson H. Sutlive ◽  
Dale A. Ulrich

The unqualified use of statistical significance tests for interpreting the results of empirical research has been called into question by researchers in a number of behavioral disciplines. This paper reviews what statistical significance tells us and what it does not, with particular attention paid to criticisms of using the results of these tests as the sole basis for evaluating the overall significance of research findings. In addition, implications for adapted physical activity research are discussed. Based on the recent literature of other disciplines, several recommendations for evaluating and reporting research findings are made. They include calculating and reporting effect sizes, selecting an alpha level larger than the conventional .05 level, placing greater emphasis on replication of results, evaluating results in a sample size context, and employing simple research designs. Adapted physical activity researchers are encouraged to use specific modifiers when describing findings as significant.


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