This study explores the application of communicative AI agents, specifically a network of customized generative pretrained transformer agents, in designing mathematical tasks. It focuses on how these AI agents, functioning as a multi-professional team, can perform mathematical task design (concerning a collection of task activities and not…

This article reports on the findings of a research study which has approached language learning motivation (LLM) following Ushioda's (2009) person-in-context relational view of L2 motivation, Consoli's life capital (2021, 2022), Dweck's mindset (2017) and Dörnyei's vision system (2009). Our study provides insights into how LLM research is key to…

Enemy items are two test items that should not be presented to a candidate on the same test. Identifying enemies is essential for personnel assessment, as they weaken the measurement precision and validity of a test. In this research, we examined the effectiveness of lexical and semantic natural language processing techniques for identifying enemy…

Research shows that when school professionals--such as administrators, teachers, and nurses--communicate with families, students have improved academic achievement and attendance and are less likely to drop out. This article addresses how to improve the effectiveness and efficiency of school-home communication at minimal cost, especially when a…

AI has been introduced into design courses to enhance student learning outcomes, foster creativity, provide personalised learning support and improve design productivity. This study integrated AI tools as a facilitative aid in a creative product design course, focusing on examining students' learning outcomes and the creativity of their final…

Generative AI (GenAI) challenges assessment validity by enabling students to complete tasks without demonstrating genuine capability. In response to this challenge, institutions have developed and implemented various approaches that aim to communicate permissible AI use to students. Familiar examples include the 'traffic light' approach now…

Although extensive research has focused on the perceptual abilities of second language (L2) learners, a significant gap persists in understanding how cognitive functions like phonological short-term memory (PSTM) and nonverbal intelligence (IQ) impact L2 speech perception. This study sets out to investigate the discrimination of L2 English…

The concept of differentiation holds immense significance in education, touching upon aspects like access, inclusion, justice, and equality. However, it is also a complex and elusive notion, which acquires different meanings across historical and cultural contexts. This article explores the shifting reasoning about differentiation in the Swedish…

Little attention has been paid to the role that low levels of cognitive development (or IQ) play among both left-behind children (LBCs) and children living with parents (CLPs) in the context of poor educational attainment in rural China. In this paper, we examine how general cognitive abilities contribute to the academic achievement gains of both…

The study reported on here was conducted to examine the consistency of the views of children and teachers in predicting the multiple intelligence areas of children at the end of the education programme provided in an enriched class based on multiple intelligence practices in a pre-school education institution. Using the…

Cognitive science has gathered robust evidence supporting the hypothesis that cognitive processes do not occur in an amodal format but take shape through the activation of the sensorimotor systems of the agent body, which works as simulation system upon which concepts, words, and thought are based. However, studies that have investigated the…

Short-form development is an important topic in psychometric research, which requires researchers to face methodological choices at different steps. The statistical techniques traditionally used for shortening tests, which belong to the so-called exploratory model, make assumptions not always verified in psychological data. This article proposes a…

Knowledge tracing is a well-known problem in AI for education, consisting of monitoring how the knowledge state of students changes during the learning process and accurately predicting their performance in future exercises. In recent years, many advances have been made thanks to various machine learning and deep learning techniques. Despite their…

Background: Previous literature suggests that children with Down syndrome (DS) have difficulties in cognitive and affective components of Theory of Mind (ToM). However, the nature of the distinction between cognitive and affective ToM has not yet been addressed in depth in this population. Aims: This work is aimed at studying the cognitive and…

The rapid advancement of generative AI technology offers new opportunities for the innovation and transformation of education. However, this also brings forth risks and challenges, including the potential to exacerbate educational inequality and integrity. This study aims to address the extensive controversies surrounding the application of…