09 SES 03 A, Research into the Predictive Validity of Individual and Contextual Characteristics for Academic Success and Returns on Education
Traditionally, high school grades and entrance exams such as SAT and ACT are widely in effect as admission criteria to higher education across the world (see e.g., Kappe & Flier, 2012; Clercq et al., 2013). Research in this admission context highlights the potentially adverse impact of using achievement measures on admission prospects for disadvantaged students because these achievement measures are correlated or intertwined with students’ socioeconomic characteristics and school attributes (see e.g., Geiser and Santelices, 2007). The simple predictive validity of standardized tests for an individual student is likely an overestimate (see e.g. Roth, 2004) as within-school score differences have less predictive power than between-school differences. Such results hint at the importance of considering contextual factors that reflect students’ differences in opportunities to learn (OTL).
High school students in Ethiopia face many challenges that can hinder their academic achievements and hence, a large part of the differences in academic achievement is probably to be attributed to differences in OTL. In particular, socio-economic status, gender, and quality of teaching facilities can be expected to be important determinants of OTL in the Ethiopian context. This difference is explicitly observed in national examination results and the ministry of education has for instance acknowledged the effect of traditional gender role expectation for females and committed to implement a system that applies positive discrimination in terms of a differentially lower cut score for girls than boys when considering admission to higher education in the country. A similar system is in effect for students coming from emerging regions in the country, as these have limited access to proper school facilities and quality teaching and teachers. Yet other unacknowledged factors can still play a role. For example students from high SES families tend to attend high quality private schools, whereas others only have access to the default public school in the neighbourhood.
Thus, the national examinations in Ethiopia are administered to students from diverse background with likely different OTL. The national examinations are high stakes in Ethiopia for both the students and the government. They are high stakes for the students because the results determine the students’ future careers; They are high stakes for the government because the results are used to evaluate the educational system.
Key Objective. Given these high stakes and large societal impact, it is therefore paramount to adopt a proper differential perspective (see e.g., Young, 2001) that accounts for differences in OTL when studying the predictive validity of high school grades for future success in higher education in Ethiopia.
Theoretical Framework & Research Questions (RQ)
In line with Cattel’s investment theory (Cattell, 1987), the predictive validity of high school grades or test scores for future academic success will decrease for students with fewer OTL: These students lack the opportunities to fully invest their fluid intelligence in acquiring the necessary crystallized intelligence that is beneficial for academic achievement (see e.g., Kvist & Gustafsson, 2008). Following this investment theory, we would expect both (i) lower scores on standardized admission tests for students with fewer OTL as well as a (ii) decrease in predictive validity of high school grades for students with fewer OTL.
The study has the following research questions for the case of Ethiopia.
- Are differences in academic achievement in high school a function of OTL?
- Are differences in academic achievement in the higher education preparatory program a function of OTL?
- How well does high school GPA predict performance of students in the higher education preparatory programs (i.e., predictive validity)?
- Is this predictive validity a function of OTL?
Cattell, R.B. (1987). Intelligence: Its structure, growth and action. New York: North-Holland. Clercq, M. D., Galand, B., Dupont, S., & Frenay, M. (2013). Achievement among first-year university students: an integrated and contextualized approach. European Journal of Psychology of Education 28 (3), 641-662. Geiser, S., & Santelices, M. V. (2007). Validity of high-school grades in predicting student success beyond the freshman year: High-school record vs. standardized tests as indicators of four- year college outcomes. University of California, Berkeley. Kappe, R., & Flier, H.V.D. (2012). Predicting academic success in higher education: what’s more important than being smart? European Journal of Psychology of Education 27(4), 605-619. Kvist, A. V., & Gustafsson, J.-E. (2008). The relation between fluid intelligence and the general factor as a function of cultural background: A test of Cattell’s investment theory. Intelligence, 36, 422-436. Rothstein, J. (2004). College performance predictions and the SAT. Journal of Econometrics, 121,97-317. Young, J.W. (2001). Differential validity, differential prediction and college admission testing: A comprehensive Review and analysis. New York: College Entrance Examination Board.
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
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