Reward-predictive items capture attention even when task-irrelevant. While value-driven attention typically generalizes to stimuli sharing critical reward-associated features (e.g., red), recent evidence suggests an alternative generalization mechanism based on feature relationships (e.g., redder). Here, we investigated whether relational coding…

Sport analytics remains a growing area in the sport industry. As such, the demand for skills and knowledge in this area has grown. This demand includes off-field data, such as marketing trends, as well as financial data related to sport organizations. There has been a trickle-down effect in sport management (and other) education programs to teach…

Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…

In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…

Employment in science, technology, engineering, and mathematics (STEM) fields will continue to grow in the coming years. Those entering the STEM workforce will be expected to demonstrate proficiency in areas such as literacy and problem solving, among other domains. Early access to STEM concepts such as coding may support skill development and…

In the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that…

This study investigates ChatGPT's perspectives on coding education for preschool children to provide a comprehensive understanding that is valuable for educators in early childhood education. An instrumental case study approach was employed, utilizing qualitative research design and case study methods. Data were gathered using a structured…

Procedural fidelity is an important component of behavioral intervention programs. The "Train-to-Code" software was used to teach skilled observation of implementation of three types of discrete-trial programs, and improvement to procedural fidelity was assessed. Participants completed a training package that involved coding video…

The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…

We conduct an impact analysis on a unique technology certificate and apprenticeship program offered by LaunchCode. We merge administrative data containing entrance exam scores with survey data for individuals that were (a) not accepted, (b) accepted but did not complete the course, (c) completed the course but not the apprenticeship, and (d)…

Robotics has emerged as a popular interdisciplinary pedagogical approach in the field of education to teach children STEM concepts. By providing playful learning experiences, the use of robots engages children in an active learning process, making it an effective tool to promote their targeted knowledge, skills, and disposition towards STEM,…

Over the past decade, social scientists have adapted computational methods for qualitative text analysis, with the hope that they can match the accuracy and reliability of hand coding. The emergence of GPT and open-source generative large language models (LLMs) has transformed this process by shifting from programming to engaging with models using…

This case study centers on the issues associated with defining and coding multiple variables from a large set of special education due process hearing officer decision documents as part of an investigation into predictors of due process hearing timeliness. Legal studies of court or hearing officer decisions generally require document content…

Background: Analyzing student short-answer written justifications to conceptually challenging questions has proven helpful to understand student thinking and improve conceptual understanding. However, qualitative analyses are limited by the burden of analyzing large amounts of text. Purpose: We apply dense and sparse Large Language Models (LLMs)…

Teaching coding and computational thinking is an emerging educational imperative, now embedded in compulsory curriculum in the United States, Finland, the UK, Germany, Belgium, the Netherlands, New Zealand, and Australia. This meta-synthesis of 49 studies critically reviews recent international research (2009-2022) of coding and computational…