Techno Brief

Mid-Atlantic Regional Technology in Education Consortium  
1301 Cecil B. Moore Ave.
Ritter Annex 9th Floor
Temple University - CRHDE
Philadelphia, PA 19122

800-892-5550
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General Inquires:
Laurence Peters
Johann Sarmiento
Judith Stull  
Technical Assistance:
Barry Mansfield  
Professional Development:
Joan Pasternak

Temple University Temple University Center for Research in Human Development and Education


The fourth and final component of scientifically based research is the need for a peer review process to establish persuasiveness. Although the most rigorous form of peer review is publication in a professional journal, one should at least have access to qualified colleagues who can carefully examine and critique the completed research project. Furthermore, one must define what “persuasiveness” means in one’s specific context, and who, exactly, must be persuaded for the research to be accepted (e.g., does the district superintendent have final say, or is it equally important to consider the responses of parents and community members?)

Clearly, conducting scientifically based research is a time-consuming and often demanding process that must balance meeting the required components with sensitivity to the complex human factors that exist in any research setting. Not surprisingly, keeping that balance in check can be immensely challenging in research contexts such as schools. But given the potential for scientifically based research to identify and support educational strategies that truly work in the service of students’ learning needs, the challenge seems well worth the effort.

 



References:

Darlington, R. (1990). Regression and linear models. New York: McGraw-Hill Publishing Company.

NCLB Act of 2001, Pub.L. No. 107–110, 115 Stat 1425 (2002). Retrieved May 2004, from http://www.ed.gov/policy/elsec/leg/esea02/107-110.pdf

Onwuegbuzie, A. J., & Daniel L. G. (2003, February).Typology of analytical and interpretational errors in quantitative and qualitative educational research. Current Issues in Education. 6(2). Retrieved May 2004, from http://cie.asu.edu/volume6/number2

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin.



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