Journal of Intelligence

This study investigates the developmental trajectories of transcription and oral language skills in kindergarten students over the course of an academic year, with a focus on the influence of executive functions (EF) and home literacy practices (HLP). Hierarchical linear modeling (HLM) analyses revealed significant growth in transcription skills, with both EF and independent home literacy practices positively influencing baseline transcription scores. The interaction between independent home literacy practices and formal literacy practices at home further enhanced transcription skill development. In contrast, oral language skills were not influenced by either HLP or EF. These results suggest that EF plays a more prominent role in transcription development than oral language skills in early childhood, especially in transparent orthographic systems. The findings highlight the importance of cognitive and environmental factors in early literacy development, suggesting implications for educational practices, particularly in fostering effective home literacy environments

Individuals with mild nonspecific intellectual disability (NSID) often exhibit delayed literacy development. Unfortunately, how cognitive–linguistic processing profiles influence literacy in this population lacks clarity. This study investigated literacy development in this population, considering the cognitive–linguistic mechanisms. The Specialist Battery for the Diagnosis of Cognitive Abilities and School Skills was used to assess cognitive–linguistic abilities and literacy-related skills in 122 participants. Fuzzy C-means clustering was used to identify processing profiles. Developmental age equivalents in literacy were estimated using local regression models and matched comparisons with typically developing peers. Two cognitive–linguistic profiles emerged: globally weaker and moderately developed. Those with NSID performed significantly lower than their peers in all domains. Their literacy skills aligned with those of children 2–4 years younger, and plateaued after age 15. Cognitive–linguistic heterogeneity in students with NSID should guide targeted literacy interventions. The findings inform ICD-11 educational expectations for individuals with mild NSID.

The widespread application of Generative Artificial Intelligence (Gen-AI) is transforming educational practices and driving pedagogical innovation. While cultivating higher-order thinking (HOT) represents a central educational goal, its achievement remains an ongoing challenge. Current evidence regarding the impact of Gen-AI on HOT is relatively fragmented, lacking systematic integration, particularly in the analysis of moderating variables. To address this gap, a meta-analysis approach was employed, integrating data from 29 experimental and quasi-experimental studies to quantitatively assess the overall impact of Gen-AI on learners’ HOT and to examine potential moderating factors. The analysis revealed that Gen-AI exerts a moderate positive effect on HOT, with the most significant improvement observed in problem-solving abilities, followed by critical thinking, while its effect on creativity is relatively limited. Moderation analyses further indicated that the impact of Gen-AI is significantly influenced by experimental duration and learners’ self-regulated learning (SRL) abilities: effects were strongest when interventions lasted 8–16 weeks, and learners with higher SRL capacities benefited more substantially. Based on the research findings, this study proposed that Gen-AI should be systematically integrated as a targeted instructional tool to foster HOT. Medium- to long-term interventions (8–16 weeks) are recommended to enhance learners’ problem-solving and critical thinking abilities. At the same time, effective approaches should also be explored to promote creative thinking through Gen-AI within existing pedagogical frameworks. Furthermore, individual learner differences should be accounted for by adopting dynamic and personalized scaffolding strategies to foster SRL, thereby maximizing the educational potential of Gen-AI in cultivating innovative talents.