The organizational change framework is a tool for understanding and facilitating organizational change and success, grounded in the principles of design thinking and the foundational leadership and organizational wellness (FLOW) model. This article dives into the components of the organizational change framework--collect the information, connect…

Decision makers and strategy leaders in states often lack the information they need to make decisions that will support learners' success. Many lack information on what data their states already collect and publicize, and many are unsure of what data might tell a more meaningful story about student success. Responding to this need, researchers and…

High-quality feedback requires understanding of a student's work, insights into what concepts would help them improve, and language that matches the preferences of the specific teaching team. While Large Language Models (LLMs) can generate coherent feedback, adapting these responses to align with specific teacher preferences remains an open…

A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…

In this article, we argue for increased participant choice in early years research and beyond. Drawing on relevant literature and our own empirical work, we demonstrate that giving participants more choice leads to richer data and more robust findings. We also show that more choice for participants is closely aligned with co-creation and…

Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

With the advent of closed-circuit television systems (CCTV) in the era of technology, a massive amount of video data is generated daily. CCTV are installed at several educational institutions to monitor students' behavior and ensure their safety. Human activity monitoring is done manually. Abnormal human actions refer to rare or unusual actions in…

Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…

Possible selves is a theory of self-concept and behaviour motivation. Methods of exploring possible selves have focused on interviews and questionnaires. This article introduces the Possible Me Tree model and explains how the model was adapted and used for research. The Possible Me Tree model was implemented with young people between 17 and 18…

This paper reports on a study that adopted a systematic approach to school-level early warning. The study examined areas where research consistently shows schools commonly experience decline: (1) leadership stability; (2) talent management; (3) organizational culture; (4) financial operations; and (5) instructional programming. Rather than relying…

One part of COVID-19's staggering impact on education has been to suspend or fundamentally alter ongoing education research projects. This article addresses how to analyze the simple but fundamental example of a multi-cohort study in which student assessment data for the final cohort are missing because schools were closed, learning was virtual,…