"Opportunity to learn" has evolved into an umbrella phrase for describing a large range of settings, resources, structures, and processes. The aim of this study is to develop a conceptual framework that can accommodate a wide range of opportunities to learn, not just those provided by teachers in classrooms. An inclusive framework can…

To date, student issues with Massive Open Online Courses (MOOCs) have only been explored in context-specific environments. Mainstream problems such as declining student motivation during a course, massive student dropout rates, accountability, user experience, etc., persist due to the permutations and combinations of these issues. Literature is…

Cognitive diagnostic models (CDMs) provide pedagogically relevant information in the form of a student profile of multiple binary categorizations of students into mastery or nonmastery statuses on latent traits called attributes. Federal educational accountability requires accountability measures to designate students into one of at least three…

This study investigated teacher-driven change efforts. A review of existing literature posits that the current education system is largely driven by top-down mandates, such as the implementation of evidence-based practices generated by large scale and randomized controlled trials. While these approaches provide the field with important knowledge,…

Explainable Artificial Intelligence (XAI) refers to systems that make AI models more transparent, helping users understand how outputs are generated. XAI algorithms are considered valuable in educational research, supporting outcomes like student success, trust, and motivation. Their potential to enhance transparency and reliability in online…

Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and inaccessible for evaluation or modification by researchers and practitioners, limiting their accountability and ethical design. Moreover, predictive models are often opaque…

California is one of just two states (with Kansas) that does not use a student-level growth model to measure school performance. This brief lays out a number of common beliefs about growth models and provides evidence that these beliefs are inaccurate or unsupported. In so doing, the brief makes a positive case that the state should adopt such a…

Background/Context: Predictive analytics has emerged as an indispensable tool in the education sector, offering insights that can improve student outcomes and inform more equitable policies (Friedler et al., 2019; Kleinberg et al., 2018). However, the widespread adoption of predictive models is hindered by several challenges, including the lack of…

Higher education scholars often investigate the policy mechanisms of external accountability, but rarely explore institutional mechanisms of internal accountability. This chapter, which reports select findings from an in-depth case study of institutional budgeting at an American public research university, examines an underexplored mechanism of…

Panel or grouped data are often used to allow for unobserved individual heterogeneity in econometric models via fixed effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters additively and interacts with treatment variables. We present identification and estimation methods for…

AI tutors are promised to expand access to personalized learning, improving student achievement and addressing disparities in resources available to students across socioeconomic contexts. The rapid development and introduction of AI tutors raises fundamental questions of epistemic trust in education. What criteria should guide students' critical…

In response to the shifting educational landscape and the growing emphasis on responsibility and quality, quality assurance systems in higher education have experienced significant modification throughout time. These systems are essential for assuring the delivery of high-quality educational programmes and preserving the standing and reputation of…

Student growth percentiles (SGPs) have become a common means to measure and report on student academic growth for state education accountability, and some states have adopted SGP cutscores as a means of classifying student growth into categories like "high/medium/low" growth. It has therefore become important to understand properties of…

The widespread adoption of school autonomy with accountability reforms in education has generated debate regarding the relationship between autonomy, innovation and accountability. While at the policy design level, these three elements are highly related, several authors highlight the contradictions among them. By analyzing key documents and…

The effectiveness of the student conduct approaches of the mixed method model, a mixture of restorative justice and traditional sanctioning, and traditional sanctioning, known as the "model code," in student learning at historically Black colleges and universities (HBCUs) has been largely unexamined in existing literature. This…