The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…

With the 5th Edition of Data Analysis for Continuous School Improvement, best-selling Victoria Bernhardt has written the go-to-resource for data analysis in your school! By incorporating collaborative structures to implement, monitor, and evaluate the vision and continuous improvement plan, this book provides a framework to show learning…

Analysis of symmetrically predicted endogenous subgroups (ASPES) is an approach to assessing heterogeneity in an ITT effect from a randomized experiment when an intermediate variable (one that is measured after random assignment and before outcomes) is hypothesized to be related to the ITT effect, but is only measured in one group. For example,…

The "Building Your Research Data Management Toolkit" was developed to provide introductory research data management skills training to liaisons in academic libraries. This paper assesses the participants' perceived change in knowledge, behaviors and attitudes as a result of participation in the RoadShow program. Long term changes in…

A reproducible analysis is one in which an independent entity, using the same data and the same statistical code, would obtain the exact same result as the previous analyst. Reproducible analyses utilize script-based analyses and open data to aid in the reproduction of the analysis. A reproducible analysis does not ensure the same results are…

With the rapid development of internet technology, the importance of data in various industries has become increasingly prominent. However, in the field of domestic education, especially the research on teaching quality evaluation is relatively sparse. This paper aims to build an evaluation model of physical education teaching quality with big…

University rankings have become commonplace in higher education. Traditional quantified rankings do not merely measure educational performance: they equally grant status, enforce competition between institutions, and are emblematic for the ongoing capitalization of higher education. Drawing on the field of Science and Technology Studies, this…

Policymakers have expressed increased interest in program-level higher education accountability measures as a supplement to, or in place of, institution-level metrics. But it is unclear what these measures should look like. In this report, we assess the ways program-level data could be developed to facilitate federal accountability. Evidence shows…

The process of quantification is a powerful development shaping many domains of life today. In the area of education, for example, performance measurement, testing and ranking have become common tools of governance. Quantification is not a neutral way of describing society, but a process of valorisation. It has three sociologically relevant…

In this article we present a general approach not relying on item response theory models (non-IRT) to detect differential item functioning (DIF) in dichotomous items with presence of guessing. The proposed nonlinear regression (NLR) procedure for DIF detection is an extension of method based on logistic regression. As a non-IRT approach, NLR can…

This paper reports on the findings of an ESRC funded project that contributes to the evidence base underpinning contextualised approaches to undergraduate admissions in England. We show that the bolder use of reduced entry requirements for disadvantaged learners is necessary if ambitious new widening access targets set by the Office for Students…

The increased use of quantitative education data is often regarded by scholars as evidence of the emergence of 'governing by numbers'. These scholars ascribe major stakeholders such as the OECD and nation states agency as they produce, distribute and consume data, and respond to these with policy and management initiatives. This paper argues that…

This paper presents a critical analysis, from the point of view of a statistician, of the methodology used by Hattie in "Visible Learning," and explains why it must absolutely be called pseudoscience. We first discuss what appears to be the intentions of Hattie's approach. Then we describe the major mistakes in "Visible…

When undertaking quantitative hypothesis testing, social researchers need to decide whether the data with which they are working is suitable for parametric analyses to be used. When considering the relevant assumptions they can examine graphs and summary statistics but the decision making process is subjective and must also take into account the…