Bias assessment and prevention in noncognitive outcome measures in context assessments.

Autor/inn/en	Vijver, Fons J. R. van de; He, Jia
Titel	Bias assessment and prevention in noncognitive outcome measures in context assessments.
Quelle	Aus: Kuger, Susanne (Hrsg.); Klieme, Eckhard (Hrsg.); Jude, Nina (Hrsg.); Kaplan, David (Hrsg.): Assessing contexts of learning. An international perspective. Cham: Springer (2016) S. 229-253 PDF als Volltext Link als defekt meldenVerfügbarkeit
Reihe	Methodology of Educational Measurement and Assessment
Sprache	englisch
Dokumenttyp	online; gedruckt; Sammelwerksbeitrag
ISBN	978-3-319-45356-9; 978-3-319-45357-6
DOI	10.1007/978-3-319-45357-6_9
Schlagwörter	Erhebungsinstrument; Fragebogen; Methodologie; Äquivalenz; Gleichheit; Sozialwissenschaften; Internationaler Vergleich; Strategie; PISA (Programme for International Student Assessment)
Abstract	Assessing students' personal characteristics, as well as the structures and processes of teaching and learning, is an integral part of the Programme for International Student Assessment (PISA). Providing input for solid evidence-based educational policies, one of the main aims of PISA, creates huge methodological challenges: Various biases in self-reported data across cultures pose a persistent challenge in unpacking the black box of student learning; these biases jeopardize PISA's scope for evidence-based policy making. This chapter focuses on challenges in the design and analysis of PISA background questionnaires, especially in noncognitive outcome measures. Our conceptual background however is not primarily PISA-related but is comparative work in the social and behavioral sciences more broadly. We first review sources of bias at construct, method, and item levels, as well as levels of equivalence (construct, metric, and scalar invariance), using examples from educational surveys. We then illustrate the strategies used in the PISA project to deal with different types of bias. Specifically, qualitative, non-statistical strategies such as instrument development (adaptation), standardization of assessment procedures, and statistical strategies to mitigate bias are outlined. State-of-the-art psychometric procedures to examine the comparability of these noncognitive outcome data, including partial invariance and approximate invariance, are also discussed. We conclude by suggesting future research topics. (DIPF/Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2017/4