The accurate detection of children's truthful and dishonest reports is essential as children can serve as important providers of information. Research using automated facial coding and machine learning found that children who were asked to lie about an event were more likely to look surprised when hearing the first question during an interview…

Large language models (LLMs) have significantly advanced smart education in the artificial general intelligence era. A promising application lies in the automatic generalization of instructional design for curriculum and learning activities, focusing on two key aspects: 1) customized generation: generating niche-targeted teaching content based on…

Academic dishonesty remains a persistent concern for educational institutions, threatening the reputation of universities. The emergence of Artificial Intelligence (AI) tools exacerbates this challenge as they can be used for chatting but also for cheating. Several scientific papers have analyzed the advantages and risks of using AI tools like…

The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…

Excellence in research is essential for advancing knowledge, fostering innovation, and addressing societal challenges. This article proposes the INDEX Strategy Framework as a structured, evidence-based guide to optimize the research process. The framework encompasses five critical phases: Identify Focus Areas, Network and Collaborate, Design…

Background: Developing treatment goals and hierarchies is fundamental to effective intervention. Despite this, interventions are often vaguely or ambiguously described, negatively impacting outcome measurement, client engagement, and team communication. THIMS (Target, Hierarchy, Ingredients, Measures, Success Criterion) is a novel intervention…

Purpose: Sentence repetition (SR) is a promising task for identifying children at risk for developmental language disorder (DLD) but is unclear how to calibrate the task for adults. In verbal recall, the frequency of language structures affects adults with DLD differently from peers with typical language (TL), particularly near the limits of…

University Examination Timetabling Problem is the most important combinational problem to develop a conflict-free timetable to execute all of the exams in and with the limited timeslots and other resources for universities, colleges or schools. It is also an important Nondeterministic Polynomial Time (NP)-hard problem that has no deterministic…

Generative Artificial Intelligence (GenAI) chatbots provide teachers with opportunities to enhance their expertise by exploring topics relevant to their practice. However, studies have raised concerns about ChatGPT's mathematical accuracy. This pilot study evaluated ChatGPT's Pedagogical Content Knowledge (PCK) and Content Knowledge (CK),…

Upper elementary students with reading disabilities (RD) require intensive interventions to accelerate their reading achievement, as they often demonstrate deficits in basic reading skills and comprehension strategies. This paper reviews a series of three studies examining reading interventions of varying intensities for students with RD. Study 1…

Background: Large language models (LLMs) are increasingly deployed in educational contexts for content generation (Diwan et al., 2023), assessment (Ouyang et al., 2023), and tutoring support (Lin et al., 2023). Reasoning models represent an important development in LLM development (DeepSeek-AI et al., 2025; OpenAI et al., 2024), distinctively…

Operational definitions have a significant history in applied behavior analysis. The practice's importance stems from the role operational definitions play in detecting an event, human thought, or action. While operationalizing target behaviors has enjoyed widespread practice, some concerns have recently arisen with translation validity and…

Metacognitive monitoring, recognizing when one is accurate or not, is important because judgments of one's performance or knowledge often relate to control decisions, such as help seeking. Unfortunately, children and adults struggle to accurately monitor their performance during number-magnitude estimation. People's accuracy in estimating number…

Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing…

Reading fluency has been a tenacious problem in our schools. Studies have addressed the national decline in reading fluency in elementary schools. Tennessee's data outlines a similar pattern of findings. Approximately one third of Tennessee students complete third grade without becoming fluent readers (Tennessee Department of Education, 2023). New…