Session Information
09 SES 11 A, Findings From International Comparative Achievement Studies (Part 2): Investigating Construct Dimensions and Relations in Comparative and Contrastive Perspectives
Symposium continued from 09 SES 10 A
Contribution
This study aims to explore a learning effect on problem solving skills acquisition in technology-rich environment focusing on young adult population (25-34 aged adults) among OECD countries. Given that the problem solving skills can be acquired through ongoing learning activities after completing formal schooling, it builds up a conceptual model which explores societal and individual antecedents of adult learning. Also, the authors examine the adult learning effect on problem skill in technology-rich environment by controlling for the level of initial education Another key purpose of this study is to identify the specific features of national contexts that influence the relationship between adult learning and skill. For this, we use the data sources available from the recent international assessment, the Programme for the International Assessment of Adult Competencies (PIAAC) survey data 2008-2013, the OECD data lab, World Bank data, and Hofstede’s study. Considering the observed variations attributed to different sociocultural environments, we use multilevel logistic regression model to estimate the propensity score which predicts participation in adult learning. The multilevel technique specifies the propensity score for two different levels, assuming the variation may depend on country-level characteristics. Key national indicators in terms of labor market policy and education system come from the OECD data and economic status will be measured by World Bank’s GDP data. National culture will be operationalized by Hofstede’s cultural dimensions. The PIAAC survey data will be used to consider adults backgrounds and to measure achievement of problem solving skill. After taking account of both individual-level and country-level factors, adult learning effects will be examined by the average difference of the achievement outcome between participants and non-participants. This study will contribute to urging a critical reflection of problem solving ability as the new life skills.
References
Arpino, B., & Mealli, F. (2011). The specification of the propensity score in multilevel observational studies. Computational Statistics & Data Analysis, 55(4), 1770-1780. Haddad, W.D., & Draxler, A. (2002). Technologies for education: Potential, parameters, and prospects. Retrieved from http://ict.aed.org/infocenter/pdfs/TechEdBook.pdf. Hanushek, E.A., Schwerdt, G., Wiederhold, S., & Woessmann, L. (2013). Returns to skills around the world: Evidence from PIAAC. Cambridge, MA: National Bureau of Economic Research. Jonassen, D. H. (2011). Learning to solve problems: A handbook for designing problem-solving learning environments. Routledge: New York. OECD. (2013). OECD skills outlook 2013: First results from the survey of adult skills. Paris: OECD.
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