"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…

The international nature of doctoral education creates interesting tensions where national systems, institutional policies, disciplinary customs, individual supervisor preferences, and doctoral researcher needs meet. The Thesis by Publication (TBP), a model where published works are included within the thesis, is available to doctoral researchers…

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…

In 2023, a group of district and school leaders and other education constituents convened by the Delaware Department of Education raised questions about the growth metric in the state's accountability system. They wondered whether the state's growth model was too highly related to achievement and, therefore, not rewarding schools for helping…

Although the role of international organizations in the diffusion of education policy is widely acknowledged, their role in the articulation of policy ideas remains comparatively underresearched. This article addresses this gap through a case study on the role of the OECD in the construction of the School Autonomy with Accountability policy…

With over 1.1 million credentials available but only 12 percent delivering significant wage gains, learners face a chaotic marketplace that lacks effective oversight. The right credentials can be transformative, as credentials in the top decile yield annual wage gains of nearly $5,000, increase career switching success sixfold, and boost the…

This article examines effective strategies for transitioning from strategic enrollment management (SEM) planning to execution. It offers insights into project organization, KPI measurement, leadership alignment, and budget considerations, providing practical guidance for higher education professionals to successfully implement and sustain SEM…

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…

As the higher education market becomes both more competitive and fragmented (as well as controlled through uncertain and changing regulatory regimes), and as those whom the higher education market serves become more discerning as consumers who apply proven customer behaviors within the market, universities must re-evaluate their internal…

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…

While high-accuracy machine learning (ML) models for predicting student learning performance have been widely explored, their deployment in real educational settings can lead to unintended harm if the predictions are biased. This study systematically examines the trade-offs between prediction accuracy and fairness in ML models trained on the…

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…