Rereading your sources with fresh eyes: Hooray for Triangulation!

Just to give some context, Rebecca and I have chosen to study perceptions of achievement for boys of color who attend the Independent Schools Program at the Boys’ Club of New York. We decided to split up our research among articles on the influences of teacher, parent, student perceptions, and also existing literature on the differences and reasons for these differences in achievement among Asians and black American boys.

I read an article that explores how cultural and social structural factors influence the achievement of White and Chinese American students as they move periodically from elementary, middle and high schools through to higher education and eventually professional careers. The study attempts to use quantitative measures to explain the, “influence of cultural and structural factors on achievement among White and Chinese Americans at specific educational transition points and identify those factors that mediate the adverse affects of transitions” (Pearce, 2006, p. 76).

The researcher uses the cultural capital theory and social structural theory to create his theoretical perspective. So it is clear that theoretical triangulation (Mathison, 1998) has been addressed. With respect to data triangulation, the researcher relies on data collected from the National Education Longitudinal Study (NELS) from 2000 in his analysis. These data allowed the researcher to study responses from students as they transitioned from elementary school to high school and into college and/or professional careers. The researcher reports the numbers used in the NELS sample and acknowledges that the study utilized a weighted sample. However, I wonder if the fact that the researcher did not collect his own data presents itself as data triangulation gap.

In my opinion, methodology emerged as main strength of this research. The researcher explicitly operationalized all the variables used. But now that I’m thinking about it, I question if the researcher used multiple methods. He made a purposeful decision to depart from qualitative research, but were there other avenues to collect and analyze more quantitative data? Perhaps data triangulation is an issue here. Additionally it appears that investigator triangulation may also present itself as a validation gap. The researcher does not mention cross-checking with colleagues to analyze the same data. Can one simply assume that a researcher has done this if he or she fails to mention this?

This assignment, although challenging for me personally because I tend to take articles at face value, gave me the opportunity to read research with a fresh eye with particular regard to validation. As I reread the “Discussion” portion, I think about how Mathison (1998) describes triangulation as a tool to understand what is found with “plausible explanations…” (p. 79). The researcher confronts inconsistency in the data at several points and provides logical reasons to account for them.

I wasn't sure but I figured I should include the reference for the article. My apologies for the weird formatting!

Pearce, R, R. (2006). Effects of Cultural and Social Structural Factors on the Achievement of White and

Chinese American Students at School Transition Points. American Educational Research Journal,

43(1) 75-101.