Kinetic energy is usually the entry point for the study of energy in physics and is often perceived as unproblematic. We present evidence, however, that some learners who seem to have accepted the concept, from elementary school students to college physics majors and in-service teachers, nevertheless do not consistently attribute kinetic energy to…

Latent growth models (LGMs) are an application of structural equation modeling and frequently used in developmental and clinical research to analyze change over time in longitudinal outcomes. Maximum likelihood (ML), the most common approach for estimating LGMs, can fail to converge or may produce biased estimates in complex LGMs especially in…

Binary item response theory (IRT) models are widely used in educational testing data. These models are not perfect because they simplify the individual item responding process, ignore the differences among different response patterns, cannot handle multidimensionality that lay behind options within a single item, and cannot manage missing response…

Learning management systems (LMSs) have been widely adopted in K-12 and higher education to support online and blended learning (Black et al. 2007; Graham 2005). One relatively new and untested LMS is Google Classroom, which has received widespread adoption in K-12 learning, but not in higher education (Fenton 2017; Hill 2018). In the current…

The Beer-Lambert law is a fundamental relationship in chemistry that helps connect macroscopic experimental observations (i.e., the amount of light exiting a solution sample) to a symbolic model composed of system-level parameters (e.g., concentration values). Despite the wide use of the Beer-Lambert law in the undergraduate chemistry curriculum…

This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue--a key task for teaching diagnosis and quality improvement. Traditional qualitative methods are both knowledge- and labour-intensive. This research investigates the potential of LLMs to streamline and enhance this process. Using…

Education in the 21st century has experienced many advances that are adjusted to the demands of the times. Thinking skills are in high demand in the 21st century, especially critical thinking and creative thinking skills for students. This study aims to determine the effectiveness of POPBL model learning in improving critical and creative thinking…

Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…

In this research, quotient strategies and their influence on decision-making in situations that involve the comparison of probabilities are analyzed. In order to achieve this, classical probability situations modeled with urns were designed. In each situation, two urns with simple extraction, involving or not proportional relationships, were…

Developmental researchers often have research questions about cross-lag effects--the effect of one variable predicting a second variable at a subsequent time point. The cross-lag panel model (CLPM) is often fit to longitudinal panel data to examine cross-lag effects; however, its utility has recently been called into question because of its…

In learning diagnostic assessments, the attribute hierarchy specifies a sequential network of interrelated attribute mastery processes, which makes a test blueprint consistent with the cognitive theory. One of the most important functions of attribute hierarchy is to guide or limit the developmental direction of students and then form a…

This study invested 24 effective and 16 ineffective problem-solving kindergarten children's awareness of metacognitive self-regulated learning (MSRL) while watching other child's problem-solving behaviors. The model in a video performed a task with a trial-and-error approach and finally asked for help. After watching the video, children were asked…

The forced-choice (FC) item formats used for noncognitive tests typically develop a set of response options that measure different traits and instruct respondents to make judgments among these options in terms of their preference to control the response biases that are commonly observed in normative tests. Diagnostic classification models (DCMs)…

The ongoing literacy crisis in the U.S. highlights an urgent need for effective, scalable literacy instruction. REED Charitable Foundation (RCF) is a non-profit organization that provides structured literacy training informed by Orton-Gillingham, along with ongoing professional coaching and comprehensive implementation support to help all students…

Standard models for network meta-analysis simultaneously estimate multiple relative treatment effects. In practice, after estimation, these multiple estimates usually pass through a formal or informal selection procedure, eg, when researchers draw conclusions about the effects of the best performing treatment in the network. In this paper, we…