In the realm of K-12 Education, the growing significance of Computational Thinking has sparked extensive inquiry into its nature and instructional methodologies. Despite a wealth of literature on the subject, ongoing debates persist regarding its fundamental components. Across global educational landscapes, Computational Thinking is being…

Although there is growing social science research examining how generative AI models can be effectively and systematically applied to text-based tasks, whether and how these models can be used to analyze images remain open questions. In this article, we introduce a framework for analyzing images with generative multimodal models, which consists of…

In this third edition of "Data Wise," Kathryn Parker Boudett and Candice Bocala update the research-based eight-step collaborative inquiry process and demonstrate how it can be used to build more equitable schools. As Boudett and Bocala define it, equity occurs when each student has access to rigorous learning opportunities and is…

The 1989 Convention on the Rights of the Child reflects the role and status of children in society as being competent and capable participants on matters that affect them. The Convention is foundational in understanding children's rights to participate in all aspects of everyday life, including in research in which children are participants. This…

The aim of this paper is to provide tools to teachers for monitoring student work and understanding practices in order to help student and possibly adapt exercises in the future. In the context of an online programming learning platform, we propose to study the attempts (i.e., submitted programs) of the students for each exercise by using…

This paper examines outsourced call center interactions to illustrate how these contexts can enhance pronunciation analysis and training. Public opinion in the United States and the United Kingdom regarding the perceived "pronunciation problems" of agents based in call centers in Outer-Circle English-speaking countries is typically…

Multimodal learning analysis emphasizes using diverse data from various sources and forms for precise examination of learning patterns. Despite recent rapid advancements in this field, conventional learning analysis remains predominantly cross-sectional and group-focused, which is insufficient for understanding continuous and personalized learning…

Purpose: School leaders are critical to organizational change and school improvement, particularly through their role in facilitating teacher development. Yet the literature is thin regarding the extent to which various sources of evidence influence school leaders' decisions and regarding conditions that may shape differences in school leader…

Interest in understanding creativity through Programme for International Student Assessment (PISA) data is on the rise, yet researchers face methodological challenges in synthesizing findings across various constructs, measures, and datasets. Meta-analysis--a valuable methodology for synthesizing quantitative data--remains underutilized in…

The increasing use of learning management systems (LMSs) generates vast amounts of clickstream data, opening new avenues for predicting learner performance. Traditionally, LMS predictive analytics have relied on either supervised machine learning or Markov models to classify learners based on predicted learning outcomes. Machine learning excels at…

This technical report provides detailed information about the sample, survey instruments, and resultant data for the Fall 2024 Pre-Kindergarten Teacher Survey (PKTS) which was administered via RAND's American Teacher Panel (ATP). The ATP is a nationally representative sample of public school teachers and part of the broader American Educator…

Chinese universities face a persistent paradox: Despite substantial investments in R&D and strong knowledge production performance, their socioeconomic impact remains limited. To address this disconnect, we develop a dual-stage efficiency framework distinguishing knowledge production (KPE) from knowledge transformation (KTE) and implement a…

Since the COVID-19 pandemic, online interviews have become a cheap and practical way to collect research data with no need to travel, from the comfort of your office or home. In 2023, we interviewed online 15 academics working in initial teacher education using an unstructured interview approach, without a schedule of interview questions or…

The study and analysis of enzymatic reactions are essential for characterizing various biological systems. As part of these procedures, it is important to understand how to quantify the biological activity of these proteins in terms of enzymatic activity. This work proposes a general equation for determining enzymatic activity based on…

Machine learning-based automatic scoring faces challenges with imbalanced student responses across scoring categories. To address this, we introduce a novel text data augmentation framework that leverages GPT-4, a generative large language model specifically tailored for imbalanced datasets in automatic scoring. Our experimental dataset consisted…