Causal inferences with large scale assessment data: using a validity framework

Rutkowski, David; Delandshere, Ginette

doi:10.1186/s40536-016-0019-1

Cited by 28 publications

(13 citation statements)

References 21 publications

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“…Internal validity signifies whether causal inferences can be drawn from the covariation between predictor and outcome variables (Shadish et al, 2002). Given the observational and cross-sectional nature of TIMSS and PISA data, the optimal conditions for making strong causal claims are rarely met (Rutkowski & Delandshere, 2016). Thus, although empirical findings from this PhD project point to some relationships between variables, the directions of these relationships cannot be established.…”

Section: Validitymentioning

confidence: 97%

More isn't always better: The curvilinear relationship between inquiry-based teaching and student achievement in science

Teig

Scherer

Nilsen

2018

Learning and Instruction

100

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Considerable research has demonstrated that teachers' self-efficacy plays a major role in implementing instructional practices. Only few studies, however, have examined the interplay between how teachers' self-efficacy and the challenges that lie outside their influence are related to their implementation of cognitive-activation strategies (CASs), especially in science classrooms. Using the Trends in Mathematics and Science Study 2015 data from science teachers in Grades 4, 5, 8, and 9, we explored the extent to which teachers' self-efficacy in science teaching and the perceived time constraints explained variations in the enactment of general and inquiry-based CAS. Findings from the overall sample showed that highly self-efficacious teachers reported more frequent implementation of both general and inquiry-based CAS, whereas those who perceived strong time constraints reported a less frequent use of inquiry-based CAS. These relationships also existed across grade levels, except on the relations between perceived time constraint and inquiry-based CAS, which was only significant for the science teachers in Grade 9. We discuss these findings in light of variations in the core competencies of science curriculum, teachers' competences, and the resources for science activities between primary and secondary education. We also point to the theoretical implications of this study for enhancing the conceptual understanding of generic and specific aspects of CAS and the practical implications for teacher education, professional development, and educational policy.

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Section: Validitymentioning

confidence: 97%

More isn't always better: The curvilinear relationship between inquiry-based teaching and student achievement in science

Teig

Scherer

Nilsen

2018

Learning and Instruction

100

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“…A review of casual research in economics (or at least among many economists), which claims epistemic superiority in the social sciences (Fourcade, Ollion, & Algan, ), formalised causal inference as the product of the following equation: ‘Outcome for treated − Outcome for untreated = 1⁄2 Outcome for treated − Outcome for treated if not treated + 1⁄2 Outcome for treated if not treated − Outcome for untreated = Impact of treatment on treated + selection bias’ (Varian, , p. 7311). To make causal claims within this idea, researchers must limit the scope of the claim because of the obligation to focus on a particular cause and a particular effect in order to establish a relationship between them, holding everything else equal (Rutkowski & Delandshere, , p. 3). This concept of causation assumes directionality ( x causes y ), and regularity ( x always causes y in a given condition).…”

Section: What Is a Cause?mentioning

confidence: 99%

Explanatory accounts in international and comparative higher education research

Cantwell

2020

Higher Education Quarterly

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Developing plausible explanations rooted in theory and supported by evidence is a challenge for comparative higher education studies. The purpose of this article is to consider how comparative studies in higher education might develop accounts that allow the research community to enhance explanatory power. Higher education studies can advance explanations about what is happening and why, as well as interpret the meaning of occurrences by drawing broadly on realist scholarly traditions. Rather than prioritising a methodology, the field should prioritise essential questions and address them with all appropriate empirical tools. Avenues for explanatory research include bounded case studies, multi‐method investigations into specific phenomena, mechanism‐based approaches and macro‐social analysis.

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“…In addition, Figure highlights that the most common strategy employed in the cited studies is DiD closely followed by IV. Although the work with different cross‐sectional waves complicates the use of DiD (Rutkowski and Delandshere, ), the assumptions required for adopting this strategy are less demanding than for other methods. As a result, we find that a considerable number of papers use this approach.…”

Section: Summary Of Empirical Studiesmentioning

confidence: 99%

Causal Inference on Education Policies: A Survey of Empirical Studies Using Pisa, Timss and Pirls

Ferrera

Cristóbal

Santín

2017

Journal of Economic Surveys

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The identification of the causal effects of educational policies is the top priority in recent education economics literature. As a result, a shift can be observed in the strategies of empirical studies. They have moved from the use of standard multivariate statistical methods, which identify correlations or associations between variables only, to more complex econometric strategies, which can help to identify causal relationships. However, exogenous variations in databases have to be identified in order to apply causal inference techniques. This is a far from straightforward task. For this reason, this paper provides an extensive and comprehensive overview of the literature using quasiexperimental techniques applied to three well-known international large-scale comparative assessments, such as PISA, PIRLS or TIMSS, over the period 2004-2016. In particular, we review empirical studies employing instrumental variables, regression discontinuity designs, difference in differences and propensity score matching to the above databases. Additionally, we provide a detailed summary of estimation strategies, issues treated and profitability in terms of the quality of publications to encourage further potential evaluations. The paper concludes with some operational recommendations for prospective researchers in the field.

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Causal inferences with large scale assessment data: using a validity framework

Cited by 28 publications

References 21 publications

More isn't always better: The curvilinear relationship between inquiry-based teaching and student achievement in science

More isn't always better: The curvilinear relationship between inquiry-based teaching and student achievement in science

Explanatory accounts in international and comparative higher education research

Causal Inference on Education Policies: A Survey of Empirical Studies Using Pisa, Timss and Pirls

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