Journal of Intelligence

13 pages, 753 KB

Open AccessArticle

Organizational Implementation Capacity of Vocational Rehabilitation During Secondary Transition for Individuals with Intellectual Disabilities: A Preliminary Study in Al-Kharj, Saudi Arabia

by Hussain A. Almalky and Arwa M. Alwadei

J. Intell. 2026, 14(9), 230; https://doi.org/10.3390/jintelligence14090230 - 21 Sep 2026

Viewed by 566

Abstract

Vocational rehabilitation (VR) plays an important role in supporting successful school-to-work transitions for individuals with intellectual disabilities (IDs). However, the organizational conditions that enable effective implementation of VR practices remain insufficiently understood. Because participation outcomes among individuals with ID are influenced by interactions [...] Read more.

Vocational rehabilitation (VR) plays an important role in supporting successful school-to-work transitions for individuals with intellectual disabilities (IDs). However, the organizational conditions that enable effective implementation of VR practices remain insufficiently understood. Because participation outcomes among individuals with ID are influenced by interactions between intellectual functioning, adaptive abilities, and environmental supports, examining organizational implementation capacity provides an important systems-level perspective. This study examined professionals’ perceptions of organizational implementation capacity for VR during secondary transition in Saudi Arabia and explored differences according to institutional and professional characteristics. A cross-sectional survey was conducted among 89 professionals working in government secondary school programs and specialized education centers in Al-Kharj, Saudi Arabia. Participants completed the Vocational Rehabilitation Implementation Capacity Measure (VRICM), a context-specific, theoretically informed measure developed for this study. The VRICM examines four theoretically derived areas: Support and Related Services, Vocational Preparation Services, Collaborative Planning, and Workplace-Based Training. We conducted descriptive statistics and nonparametric group comparisons. Overall perceived organizational implementation capacity was moderate (M = 3.25, SD = 0.95). Support and Related Services and Vocational Preparation Services received higher ratings than Collaborative Planning and Workplace-Based Training. Differences were observed according to institutional sector and professional experience. Findings provide preliminary evidence regarding organizational factors supporting VR implementation within a Saudi Arabian secondary-city context. Further psychometric evaluation of the VRICM, including structural validity assessment, is required before broader application. Full article

(This article belongs to the Topic Diversity, Educational Inclusion, Emotional Intelligence, Coping, and Other Factors That Influence Psychological Health and Well-Being)

14 pages, 776 KB

Open AccessReview

Speech Perception in Noise: A Narrative Review of Cognitive Contribution and Hearing-Aid Signal Processing

by Daniele Monzani, Andrea Bianchino, Andrea Ciorba, Chiara Bianchini, Marianna Manuelli, Andrea Migliorelli and Silvia Palma

J. Intell. 2026, 14(9), 229; https://doi.org/10.3390/jintelligence14090229 - 21 Sep 2026

Viewed by 325

Abstract

Background: Environmental noise is one of the most pervasive ecological health issues in modern urban settings, contributing to the onset of hearing damage but also to the development of annoyance, sleep disturbance, cardiovascular diseases, and impaired communication. For people with hearing impairment of [...] Read more.

Background: Environmental noise is one of the most pervasive ecological health issues in modern urban settings, contributing to the onset of hearing damage but also to the development of annoyance, sleep disturbance, cardiovascular diseases, and impaired communication. For people with hearing impairment of any age, the main challenge posed by noisy environments is not merely detecting sound but understanding speech against a competing background—a task heavily related to cognition. Methods: Narrative review; the literature has been identified through searches of PubMed, Scopus, and Google Scholar, combining terms related to cognition, speech perception, speech in noise, hearing-aid signal processing, environmental health, and aging. Results: The role of cognitive abilities in speech perception in noise has been evaluated, with particular attention to how artificial intelligence supports the interplay between cognition and hearing-aid signal processing in adverse environments. Within the Ease of Language Understanding (ELU) model, this paper describes how degraded acoustic input shifts processing from rapid, implicit lexical access toward explicit working-memory-dependent reconstruction. The actual evidence indicates (i) that working memory, in particular, could predict aided speech recognition under adverse conditions, (ii) that aging dissociates these processes, and (iii) that longitudinal studies link hearing-aid use to slower cognitive decline. Conclusions: Speech perception in noise is a coordinated neurocognitive process rather than a purely auditory task. Working memory is a central cognitive contributor, with effects that become evident specifically under adverse conditions. In particular, fast-acting compression and frequency lowering may be counterproductive for listeners in case working memory or speech processing are reduced. The success of different algorithms applied to audio signal processing of hearing aid, designed to compensate for difficult comprehension of words and phrases in noisy scenarios is also strictly dependent on working memory, and artificial intelligence significantly contributes to this goal. Full article

23 pages, 4082 KB

Open AccessSystematic Review

Cognitive Load and Foreign-Language Anxiety in Second-Language Learning: A Systematic Review and Meta-Analysis

by Hong Yi, Wenqian Tang, Qiang Chen and Zhuo Wang

J. Intell. 2026, 14(9), 228; https://doi.org/10.3390/jintelligence14090228 - 21 Sep 2026

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Abstract

Cognitive load and foreign-language anxiety are often examined separately in second-language learning, although both may arise when limited processing resources are strained. This meta-analysis examined whether the two constructs covary and why their association matters for models of L2 performance. A PRISMA-guided review [...] Read more.

Cognitive load and foreign-language anxiety are often examined separately in second-language learning, although both may arise when limited processing resources are strained. This meta-analysis examined whether the two constructs covary and why their association matters for models of L2 performance. A PRISMA-guided review identified eleven eligible studies (N = 1250), which were synthesised using a random-effects model. Two independent machine coders repeated the full-text eligibility assessment, effect-size extraction, and quality appraisal; two of the authors then verified every coding against the source reports and resolved all discrepancies. This process recovered one wrongly excluded study and corrected one misextracted coefficient. Greater load was associated with greater anxiety, r = 0.41, 95% CI [0.29, 0.52], and the estimate was r = 0.37, 95% CI [0.27, 0.46], after the most influential study was removed. All included estimates were positive. A specification analysis that substituted every available alternative component, wave, subscale, subgroup, and path yielded pooled estimates from 0.38 to 0.45; setting all eleven studies simultaneously to their least and most favourable alternatives widened the range to 0.29–0.52. Heterogeneity was high, I² = 80.1%, and the 95% prediction interval [0.03, 0.69] extended almost to zero. The pooled estimate therefore represents the centre of a dispersed literature rather than an expected result for a new study. An exploratory contrast between real-time and self-paced tasks was not significant and was confounded with language skill. The review also identified a reporting gap: thirteen additional reports measured both constructs but provided no statistic linking them. Conventional publication-bias diagnostics cannot address this form of selective non-reporting, which means that the pooled estimate is best regarded as an upper bound. This first construct-specific synthesis of the load–anxiety association connects cognitive architecture and attentional control with research on L2 anxiety and indicates why instructional studies should assess cognitive and affective outcomes together. Because the evidence is concurrent, predominantly self-reported, and drawn almost entirely from Chinese-speaking settings, it cannot establish that either construct causes the other or that both reflect a single mechanism. Full article

(This article belongs to the Special Issue Cognitive Foundations of Language Comprehension and Production)

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28 pages, 3186 KB

Open AccessArticle

Exploring Pre-Service Mathematics Teachers’ Diagnostic Thinking During AI-Supported Task Design: A Configurational Mixed-Methods Pilot Study

by Chunxia Qi, Jingyu Lin, Leyao Wen and Qi Huang

J. Intell. 2026, 14(9), 227; https://doi.org/10.3390/jintelligence14090227 - 20 Sep 2026

Viewed by 368

Abstract

Developing pre-service mathematics teachers’ ability to understand students’ mathematical thinking and anticipate students’ difficulties remains a challenge in teacher education. This exploratory mixed-methods study involved 21 pre-service mathematics teachers in a six-week AI-supported mathematical task design module. The study combined pre–post assessment, fuzzy-set [...] Read more.

Developing pre-service mathematics teachers’ ability to understand students’ mathematical thinking and anticipate students’ difficulties remains a challenge in teacher education. This exploratory mixed-methods study involved 21 pre-service mathematics teachers in a six-week AI-supported mathematical task design module. The study combined pre–post assessment, fuzzy-set Qualitative Comparative Analysis (fsQCA), and qualitative analysis of participants’ AI interactions and reflections. The key findings were as follows: (1) Participants showed significantly higher post-test scores in overall diagnostic thinking and in perception, interpretation, and judgement than at pre-test. (2) The configurational analysis identified a comparatively stable pattern associated with high post-intervention diagnostic thinking, combining lower initial diagnostic thinking with high AI acceptance and high prompting knowledge density. (3) Qualitative evidence further showed that AI served as an interactive resource for exploring mathematical and pedagogical considerations, evaluating generated suggestions, and revising task designs. Exploratory comparisons suggested that AI use could range from broader knowledge-oriented support to more selective verification and refinement. The findings highlight the heterogeneous nature of AI-supported professional learning and underscore the importance of critical evaluation and professional agency in teacher–AI collaboration. Full article

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27 pages, 2920 KB

Open AccessArticle

Second Language Learners’ Cognitive Evaluation of GenAI Interactive Learning Experience: Scale Development and Network Analysis

by Hanwei Wu, Gurpinder Singh Lalli and Yongliang Wang

J. Intell. 2026, 14(9), 226; https://doi.org/10.3390/jintelligence14090226 - 19 Sep 2026

Viewed by 314

Abstract

As generative artificial intelligence (GenAI) becomes increasingly integrated into second language (L2) learning, there is a growing need for reliable instruments to assess learners’ cognitive evaluation of GenAI-mediated interactive learning experiences. This study developed and validated the GenAI L2 Interactive Learning Experience Scale [...] Read more.

As generative artificial intelligence (GenAI) becomes increasingly integrated into second language (L2) learning, there is a growing need for reliable instruments to assess learners’ cognitive evaluation of GenAI-mediated interactive learning experiences. This study developed and validated the GenAI L2 Interactive Learning Experience Scale (AI-L2-ILES) among 1130 Chinese university students. Drawing on an interactive experience perspective and adapting it to L2 learning, the study conceptualized learners’ cognitive evaluation of GenAI interaction as comprising five dimensions: Effectiveness, Sociability, Novelty, Flow, and Seamlessness. Exploratory and confirmatory factor analyses supported this five-factor structure, with satisfactory evidence of reliability, validity, and measurement invariance across gender and academic disciplines. Network analysis further revealed that Flow was the most central dimension, Sociability showed the strongest association with Effectiveness, and Novelty occupied a relatively peripheral position. The network structure was stable across academic disciplines. Overall, the AI-L2-ILES provides a psychometrically sound measure of learners’ cognitive evaluation of GenAI-mediated interactive L2 learning experiences and captures five distinct but interconnected dimensions of this emerging construct. The scale offers a useful tool for examining how L2 learners cognitively evaluate their interactions with GenAI. Full article

(This article belongs to the Special Issue The Intelligent Language Learner: Cognitive Architectures of Second Language Acquisition)

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48 pages, 1166 KB

Open AccessArticle

Written Languaging with Direct Feedback in Beginner CSL Writing: A Crossover Study of Metacognitive Engagement and Transfer Effects

by Ming Lyu, Baoqian Yang and Wenting He

J. Intell. 2026, 14(9), 225; https://doi.org/10.3390/jintelligence14090225 - 19 Sep 2026

Viewed by 293

Abstract

Understanding the cognitive architectures that enable learners to process feedback and self-regulate is fundamental to fostering intelligent second language (L2) learning, particularly as AI-based pedagogies become prevalent. Direct written corrective feedback, while common in beginner L2 writing, often triggers only surface-level processing. This [...] Read more.

Understanding the cognitive architectures that enable learners to process feedback and self-regulate is fundamental to fostering intelligent second language (L2) learning, particularly as AI-based pedagogies become prevalent. Direct written corrective feedback, while common in beginner L2 writing, often triggers only surface-level processing. This study investigates whether written languaging (WL), a metacognitive activity where learners explain language problems in writing, can deepen feedback processing, thereby activating a more robust cognitive architecture for error correction. Using a within-subjects crossover design with 15 beginner Chinese-as-a-second-language (CSL) learners from a UK secondary school, we compared the immediate and transfer effects of direct feedback with WL versus direct feedback only. Results showed that the WL condition significantly reduced errors per 100 characters (Z = −2.556, p = .011, r = 0.66), with 86.7% of participants showing improvement, indicating enhanced cognitive regulation at the local level. However, the effect was hierarchical, with no significant impact on clause-level accuracy. General Certificate of Secondary Education (GCSE) writing scores improved significantly from pre-to-post-test (Z = −3.342, p = .001, r = 0.89), demonstrating transfer to subsequent performance. Qualitative analyses revealed that learners’ attention focused predominantly on characters (48.4%) and vocabulary (29.8%), with engagement moderated by proficiency and motivation. This study provides empirical evidence for a cognitive architecture of feedback processing, wherein WL functions as a metacognitive amplifier. This architecture is operationalised as a three-stage processing sequence noticing, hypothesis-testing, and metalinguistic reflection, with writing accuracy and WL texts serving as observable proxies for the underlying cognitive processes. Specifically, our findings reveal that WL’s facilitative effects are hierarchical, strongest at the level of local error reduction and not yet extending to clause-level syntactic accuracy, and are moderated by individual differences in proficiency and motivation. These empirical insights offer a cognitive-psychological foundation that could inform the future design of adaptive feedback systems; however, as this study did not involve any AI system, these implications are theoretical and await empirical validation in AI-mediated learning environments. Full article

(This article belongs to the Special Issue The Intelligent Language Learner: Cognitive Architectures of Second Language Acquisition)

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23 pages, 2934 KB

Open AccessArticle

Metric Quality of Intelligence Tests in Spain: Evidence from 13 National Test Commission Reviews

by Sergio Escorial

J. Intell. 2026, 14(9), 224; https://doi.org/10.3390/jintelligence14090224 - 18 Sep 2026

Viewed by 374

Abstract

Intelligence test scores underpin high-stakes educational, clinical, and occupational decisions, which makes the metric quality of these instruments a central concern for professional practice. This study aimed to evaluate the psychometric and documentary quality of intelligence tests reviewed by the Spanish National Test [...] Read more.

Intelligence test scores underpin high-stakes educational, clinical, and occupational decisions, which makes the metric quality of these instruments a central concern for professional practice. This study aimed to evaluate the psychometric and documentary quality of intelligence tests reviewed by the Spanish National Test Commission, compare this quality with that of tests measuring other psychological constructs, and examine the influence of publisher and evaluation cohort on quality. To this end, 37 intelligence tests and 78 tests of other constructs, reviewed across 13 editions (2010–2026) of the project, were coded using the Revised Test Review Questionnaire (CET-R), which comprises 14 quality characteristics grouped into four dimensions: General, Validity, Reliability, and Norms. Intelligence tests did not report more information than tests of other constructs, showing similar omission rates. However, when information was reported, intelligence tests obtained higher scores on the General, Validity, and Norms dimensions, with no differences in Reliability. Publisher accounted for a substantial share of the variance in quality, whereas the evaluation cohort showed no significant influence on any psychometric characteristic once corrected for multiple comparisons (FDR). Item bias analyses and item-response-theory-based reliability remained the most consistently underreported forms of evidence across the manuals of all tests analyzed. These findings underscore the need to uphold high, transparent standards in the documentation of intelligence tests and provide empirical criteria to support the responsible selection of instruments by practitioners. Full article

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39 pages, 4646 KB

Open AccessArticle

Cognitive Performance Under AI Advice: Development and Initial Validation of a CHC-Informed Assessment for Organizational Decision-Making

by Filiz Mizrak, Turhan Karakaya and Burcak Vatansever Durmaz

J. Intell. 2026, 14(9), 223; https://doi.org/10.3390/jintelligence14090223 - 16 Sep 2026

Viewed by 366

Abstract

Artificial intelligence (AI) is increasingly embedded in organizational decision-making, requiring employees not only to use AI-generated recommendations but also to evaluate their quality and determine when reliance is appropriate. Although established research examines behavioral reliance on algorithmic and AI advice, fewer studies have [...] Read more.

Artificial intelligence (AI) is increasingly embedded in organizational decision-making, requiring employees not only to use AI-generated recommendations but also to evaluate their quality and determine when reliance is appropriate. Although established research examines behavioral reliance on algorithmic and AI advice, fewer studies have approached performance under AI advice as an individual-differences assessment problem integrating psychometric structure, cognitive correlates, process indicators, and criterion-related evidence. This study developed and initially validated a CHC-informed, performance-based assessment of cognitive performance under AI advice using 24 organizational decision scenarios. The assessment was designed around three closely related content/performance dimensions—AI error detection, evidence integration, and cognitive control and adaptive reliance—while also capturing confidence, response time, and reliance behavior. The validation sample comprised 780 employed adults in Türkiye. Psychometric analyses included confirmatory factor analysis, multidimensional item response theory, response-time analyses, scenario-level logistic regression, measurement invariance, differential item functioning, and internal cross-validation. Results indicated a dominant general cognitive-performance component together with additional structure corresponding to the three theoretically specified dimensions. Assessment performance was positively associated with established cognitive measures, including ICAR-16 reasoning performance, working memory, processing speed, and attentional control, whereas associations with AI-related self-reports were generally weaker. Dimension-aligned analyses supported the expected associations of ICAR-16 with AI error detection and working memory with evidence integration. Performance was also moderately associated with concurrently assessed organizational decision quality (r = 0.408) and explained additional variance in this criterion beyond demographic and work characteristics, AI experience, conventional cognitive-performance measures, and AI-related self-reports (ΔR² = 0.103, p < .001). In contrast, several hypothesized scenario-specific associations involving AI confidence, time pressure, interruptions, and resistance to confidently inaccurate advice were not supported. Overall, the findings provide initial evidence for a performance-based approach to assessing how employees evaluate and respond to AI advice, while indicating that the proposed scenario-specific mechanisms and group-comparability findings require further replication before consequential applications are considered. Full article

(This article belongs to the Special Issue Cognitive Abilities Testing and Assessments: Neurocognitive and Psychometric Perspectives)

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16 pages, 866 KB

Open AccessArticle

Sports Emotional Intelligence and Exercise Adherence in Adolescents: The Chain Mediating Role of Exercise Enjoyment and Exercise Identity

by Donghuan Bai, Xuerui Li, Pengwei Song and Jia Zhang

J. Intell. 2026, 14(9), 222; https://doi.org/10.3390/jintelligence14090222 - 15 Sep 2026

Viewed by 359

Abstract

Objective: This study explores the relationship between sports emotional intelligence and exercise adherence in adolescents and constructs a sequential mediation model through the mediating roles of exercise enjoyment and exercise identity. Methods: Using a school-based cross-sectional survey, 1278 adolescents aged 12–18 [...] Read more.

Objective: This study explores the relationship between sports emotional intelligence and exercise adherence in adolescents and constructs a sequential mediation model through the mediating roles of exercise enjoyment and exercise identity. Methods: Using a school-based cross-sectional survey, 1278 adolescents aged 12–18 years from Anhui, Henan, Guangxi, and Chongqing were recruited and completed the Sports Emotional Intelligence Scale, Exercise Enjoyment Scale, Exercise Identity Scale, and Exercise Adherence Scale. Data were analyzed using Mplus 8.1 and SPSS 25.0. Common method bias was assessed with Harman’s single-factor test. The measurement model was tested via confirmatory factor analysis, and chain indirect effects were examined using the bootstrap method. Results: The measurement model demonstrated good fit, and all scales showed satisfactory reliability and validity. (1) Sports emotional intelligence was significantly associated with exercise adherence (β = 0.44, p < 0.001); (2) exercise enjoyment (indirect effect = 0.109) and exercise identity (indirect effect = 0.094) each mediated the relationship, and the sequential path from sports emotional intelligence through exercise enjoyment to exercise identity and then to adherence was also significant (indirect effect = 0.079), with all bias-corrected bootstrap 95% confidence intervals excluding 0. Conclusion: Sports emotional intelligence was positively associated with exercise adherence in adolescents, and this association was partly explained by indirect associations involving exercise enjoyment and exercise identity. The findings suggest that affective valuation and exercise-related self-concept are important correlates within the proposed model. Full article

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15 pages, 1223 KB

Open AccessArticle

Generative AI-Assisted Academic Writing Experience and University Students’ Academic Self-Efficacy: Parallel Indirect Associations Through Academic Emotions

by Tingzhi Han, Yiwen Yuan, Nitong Zhou and Zijing Fan

J. Intell. 2026, 14(9), 221; https://doi.org/10.3390/jintelligence14090221 - 15 Sep 2026

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Abstract

Generative artificial intelligence (GenAI) is increasingly used in academic writing, yet its associations with students’ broader academic emotions and capability beliefs remain unclear. Drawing on control–value theory and social cognitive theory, this cross-sectional study examined positive and negative academic emotions as parallel statistical [...] Read more.

Generative artificial intelligence (GenAI) is increasingly used in academic writing, yet its associations with students’ broader academic emotions and capability beliefs remain unclear. Drawing on control–value theory and social cognitive theory, this cross-sectional study examined positive and negative academic emotions as parallel statistical pathways between GenAI-assisted writing experience and general academic self-efficacy. Participants were 1128 students from universities in eastern China. A covariate-adjusted parallel pathway model was estimated with 5000 bootstrap resamples. GenAI-assisted writing experience was positively associated with self-efficacy (total association B = 0.733, β = 0.670) and broader positive emotions (B = 0.778, β = 0.631), and negatively associated with broader negative emotions (B = −0.457, β = −0.298). The positive-emotion indirect association was 0.471 (standardized β = 0.431), 95% CI [0.409, 0.531], whereas the negative-emotion indirect association was 0.033 (standardized β = 0.030), 95% CI [0.018, 0.052]. The direct association remained positive (B = 0.229, β = 0.209). After positive academic emotions were controlled, the coefficient linking GenAI-writing experience with negative emotions changed from negative to positive, indicating a statistical suppression pattern. A sensitivity model excluding emotional-motivation items reproduced both indirect associations. Given the limited discriminant validity between positive emotions and self-efficacy and the concurrent self-report design, the larger positive indirect association warrants cautious interpretation. The findings indicate that GenAI-assisted writing experience is associated with broader academic emotions and efficacy beliefs while retaining a smaller residual negative-emotion component. Full article

(This article belongs to the Section Studies on Cognitive Processes)

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23 pages, 1892 KB

Open AccessArticle

From Confidence to Commitment: Self-Perceived Competence and the Motivational Pathways to Intellectual Engagement with AI Learning Tools

by Fahad Alsudairi, Arwa Mohammed Asiri, Mohammed Khojah, Sabah Abdullah Al-Somali, Dana Bakry, Khalid Alqarni and Mohammed Alsaigh

J. Intell. 2026, 14(9), 220; https://doi.org/10.3390/jintelligence14090220 - 14 Sep 2026

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Abstract

Artificial intelligence (AI) tools are becoming part of how students think, not only what they use. Whether a learner engages with such a tool or delegates to it is a decision about how their own cognitive resources are deployed, which places that decision [...] Read more.

Artificial intelligence (AI) tools are becoming part of how students think, not only what they use. Whether a learner engages with such a tool or delegates to it is a decision about how their own cognitive resources are deployed, which places that decision within the realm of study of human intelligence. Investment accounts of intellectual development hold that ability is built through motivated engagement with cognitively demanding material, yet technology acceptance frameworks emphasize utility judgments and underrepresent the motivational processes that drive such engagement. This study tests an extended Technology Acceptance Model in which self-efficacy shapes perceived usefulness through motivation and enjoyment. Survey data from 185 undergraduate School of Business students at a Saudi university who used generative AI tools during coursework were analyzed using partial least squares structural equation modeling. All nine hypotheses were supported. Self-efficacy strongly predicted both motivation and enjoyment, but motivation was the dominant mediating pathway to perceived usefulness (β = 0.295, p < 0.001), with enjoyment a weaker affective route (β = 0.086, p < 0.05), alongside a significant serial pathway from self-efficacy through motivation to enjoyment (β = 0.113, p < 0.001). The model explained 54.4% of the variance in behavioral intention. The findings indicate that beliefs about one’s own technical competence, rather than appraisal of the tool alone, govern how students commit to intelligent systems, with implications for whether AI use develops or displaces learners’ own intellectual capacity. Full article

(This article belongs to the Special Issue Cognitive Processes in Technology-Enhanced Learning: Integrating Technology with Human Cognitive Architecture)

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19 pages, 1603 KB

Open AccessArticle

Humans Outperform Multimodal Large Language Models (MLLMs) in Non-Verbal Tests of Mental Rotation and Figural Reasoning

by Jonas Lesigang and Jakob Pietschnig

J. Intell. 2026, 14(9), 219; https://doi.org/10.3390/jintelligence14090219 - 11 Sep 2026

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Abstract

Multimodal large language models (MLLMs) have become increasingly proficient at solving complex problems. Here, we systematically compare performance between humans and two of the currently most widely used MLLMs, ChatGPT-5 and Gemini 3, on mental rotation and figural reasoning tests using identical instructions [...] Read more.

Multimodal large language models (MLLMs) have become increasingly proficient at solving complex problems. Here, we systematically compare performance between humans and two of the currently most widely used MLLMs, ChatGPT-5 and Gemini 3, on mental rotation and figural reasoning tests using identical instructions for humans and online interface-instructed MLLMs. Furthermore, we aimed to assess the effect of prompting configurations (self-consistency, segmented uploads, different contexts, explicit Chain-of-Thought prompting, German vs. English prompts) on MLLM performance. To this end, we assessed a human online sample (total N = 430) as well as ChatGPT-5 and Gemini 3 performance on five mental rotation and figural reasoning tests in a cross-sectional comparative design. MLLM performance was evaluated via percentile ranks. The human online sample outperformed MLLMs in both mental rotation (MLLM percentile rank ranges 0 to 7 on most tests and conditions) as well as figural reasoning (MLLM percentile ranks ranges 0 to 79) tests. Prompting configuration changes increased ChatGPT-5 but not unequivocally Gemini 3 performance (mean score change ranges: 0.67 to 2.33 and −1.67 to 1.50 points, respectively). Combining best-performing prompting configurations in single comparisons yielded largest increases in both models (3.83 and 2.33 points, respectively). Our results indicate that humans may currently outperform widely used MLLMs in mental rotation and figural reasoning tasks, especially if they require complex visuospatial abilities. Full article

(This article belongs to the Section Contributions to the Measurement of Intelligence)

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22 pages, 2661 KB

Open AccessReview

Evaluation of Large Language Models as Tools, Models, and Partners in Creative Thinking Research: A Selective Narrative Review with the GCA Framework

by Kexin Huang, Chunlei Liu and Jiaqin Yang

J. Intell. 2026, 14(9), 218; https://doi.org/10.3390/jintelligence14090218 - 11 Sep 2026

Viewed by 416

Abstract

Creativity research faces three persistent bottlenecks: divergent-thinking scoring is labour-intensive, cognitive models of creativity remain underspecified, and laboratory tasks fall short of real-world creative achievement. Large language models (LLMs) offer potential solutions, but the field lacks a structured framework for evaluating them. This [...] Read more.

Creativity research faces three persistent bottlenecks: divergent-thinking scoring is labour-intensive, cognitive models of creativity remain underspecified, and laboratory tasks fall short of real-world creative achievement. Large language models (LLMs) offer potential solutions, but the field lacks a structured framework for evaluating them. This selective narrative review (January 2018–June 2026) applies the generation–capability–assessment (GCA) framework, whose three axes are operationalised through descriptive criteria with provisional heuristic thresholds. On the generation axis, LLMs exceed average human performance on divergent-thinking tasks in most independent comparisons (Hedges’ g ≈ 0.5–2.6), an advantage qualified by fluency dependency, the superiority of top-performing humans at scale, and a novelty–typicality trade-off. On the capability axis, LLMs simulate some task-level associative behaviour and can generate hypotheses for human research, but there is no evidence that they instantiate human-like creative mechanisms. On the assessment axis, automated scoring shows promising reliability and convergent validity for specific languages and tasks (ICC ≥ 0.80 and r ≥ 0.70 in selected studies), but cross-language generalisation is largely untested and individual-level use is unsupported. Human–AI co-creativity may benefit from a division of labour, although social–affective dimensions may matter more than cognitive support. We provide a GCA reporting protocol and identify research priorities. Full article

(This article belongs to the Special Issue The Intersection of Creativity and Intelligence: Multidisciplinary Perspectives)

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26 pages, 1005 KB

Open AccessReview

Generative Constraint: How Baroque Musical Structures Scaffold Creativity in Neurodiverse Learners

by Seçil Soytok Nalçacı and Kutup Ata Tuncer

J. Intell. 2026, 14(9), 217; https://doi.org/10.3390/jintelligence14090217 - 9 Sep 2026

Viewed by 306

Abstract

Creativity is a central educational aim, yet learners in special education are too often left out of discussions of how to cultivate it. Music is frequently proposed to support them, and Baroque music especially, but the usual rationale, that such music directly improves [...] Read more.

Creativity is a central educational aim, yet learners in special education are too often left out of discussions of how to cultivate it. Music is frequently proposed to support them, and Baroque music especially, but the usual rationale, that such music directly improves cognition, rests on the discredited Mozart-effect literature. This paper offers a different foundation. It advances the thesis of generative constraint: structured musical environments do not enhance cognition but establish the affective and attentional conditions, principally through regulation, under which everyday (mini-c) creativity can emerge in neurodiverse learners. Baroque architecture, including the ground bass, theme and variation, and the historical pedagogy of partimento, is a paradigmatic instance. What sets it apart from a mere repeating background is its functional-harmonic directionality: unlike a static ostinato, a Baroque ground carries an implied motion of tension and resolution, and it is this directional pull, not repetition as such, that a learner’s choices engage, and that offers a controlled means of working against rigidity rather than reinforcing sameness. Because neurodiverse learners differ, the model treats sensory and arousal profiles as moderators, specifies when the approach may fail or do harm, and measures creative variation to separate it from stereotyped behaviour. The contribution is conceptual: a testable model and a single-case research agenda. Full article

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41 pages, 5708 KB

Open AccessArticle

Real-Time Dynamic Adaptive Test Assembly for Personalized Measurement of Cognitive Abilities Under Continuous Item Bank Growth

by Jiawei Xiong, Cheng Tang, Qidi Liu and Feiming Li

J. Intell. 2026, 14(9), 216; https://doi.org/10.3390/jintelligence14090216 - 6 Sep 2026

Viewed by 465

Abstract

The accurate measurement of individual cognitive abilities in educational settings increasingly relies on personalized assessment systems that adapt to the learner’s current standing on the measured ability. These systems generate and use assessment items continuously and in real-time, bypassing the field-test cycle that [...] Read more.

The accurate measurement of individual cognitive abilities in educational settings increasingly relies on personalized assessment systems that adapt to the learner’s current standing on the measured ability. These systems generate and use assessment items continuously and in real-time, bypassing the field-test cycle that traditional calibration requires. Item banks therefore contain a growing share of items whose parameters must be predicted first, and each test form must be assembled in real time to match the learner’s current ability level and content needs for effective personalized instruction. This study proposes an Ising framework that addresses both requirements by predicting item parameters from text with calibrated uncertainty estimates and assembling personalized test forms within the time budget of the assessment loop. This framework is validated through a factorial simulation and an empirical study on state-level English Language Arts items across Grades 3 through 12. In the simulation, the proposed uncertainty-aware method achieves a mean test information function (TIF) gap of 0.226, compared with 1.171 for the conventional baseline that ignores prediction uncertainty. The proposed method also produces feasible forms across the full operational region, whereas the chance-constrained and robust baselines become infeasible at high prediction error combined with a high share of predicted items. In the empirical study, predictive intervals achieve coverage within ten percentage points of the nominal level in the pooled condition, and the uncertainty-aware assembly reduces the TIF gap relative to the baseline, with the largest gains at the extremes of the ability distribution where accurate measurement matters most for instructional placement decisions. By separating prediction uncertainty from true individual differences in ability, this framework preserves the interpretability of cognitive ability estimates and provides a foundation for personalized assessment systems that support differentiated instruction under continuous item bank growth. Full article

(This article belongs to the Special Issue New Advances of Intelligence Measurement in the AI Era: Theory, Methods and Applications)

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26 pages, 2739 KB

Open AccessArticle

From Willingness to Practice: A Person-Centered Study of Primary Teachers’ Critical-Thinking Readiness and the Enactment Gap

by Zhen Qiang, Hong Yi and Zhuo Wang

J. Intell. 2026, 14(9), 215; https://doi.org/10.3390/jintelligence14090215 - 6 Sep 2026

Viewed by 377

Abstract

Critical thinking (CT) is a core competence that schools are expected to cultivate, yet whether it reaches classrooms depends on teachers’ readiness to teach it. Using an explanatory sequential mixed methods design, we surveyed 312 primary English-as-a-foreign-language teachers in Shandong Province, China, across [...] Read more.

Critical thinking (CT) is a core competence that schools are expected to cultivate, yet whether it reaches classrooms depends on teachers’ readiness to teach it. Using an explanatory sequential mixed methods design, we surveyed 312 primary English-as-a-foreign-language teachers in Shandong Province, China, across seven dimensions of readiness and interviewed five teachers. Latent profile analysis identified four profiles organized by two weakly related dimensions—the capacity teachers bring to CT teaching and the constraints they perceive around them: Empowered-Engaged (15%), Willing-but-Constrained (28%), Moderate-Unobstructed (20%), and Committed-but-Under-resourced (37%). Endorsement of CT was near-universal, so the profiles differed in capacity and circumstance rather than in commitment. The central finding is a disconnection between what teachers believe and what they report doing: Willing-but-Constrained teachers wanted further professional learning as much as their Empowered-Engaged peers did, yet reported teaching CT less often. The divergence held under methods that account for classification uncertainty and under alternative measurement specifications, though not under all of them, and profile membership was largely unrelated to teachers’ background characteristics. The interview findings help explain why positive beliefs about CT did not always correspond to classroom practice. Teachers reported limited CT-specific training, examination pressure, time constraints, and norms that discouraged questioning, despite generally recognizing the value of CT. This suggests that the main barriers to CT instruction may lie not in teachers’ attitudes toward CT, but in their opportunities, preparation, and working conditions for implementing it. Full article

(This article belongs to the Section Studies on Cognitive Processes)

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19 pages, 1101 KB

Open AccessArticle

Emotional Intelligence and Creative Performance in the Information and Communication Technology (ICT) Sector: The Mediating Role of Psychological Well-Being and the Moderating Role of Cultural Intelligence

by Ibrahim Yikilmaz, Lutfi Surucu, Mustafa Bekmezci, Bulent Cetinkaya and Kemal Erogluer

J. Intell. 2026, 14(9), 214; https://doi.org/10.3390/jintelligence14090214 - 5 Sep 2026

Viewed by 299

Abstract

Emotional intelligence is the capacity to understand, regulate, and manage one’s emotions, and it has significant effects on employees’ psychological adjustment, interpersonal relationships, and job performance. However, the specific psychological mechanisms by which emotional intelligence influences employees’ creative performance, and the conditions under [...] Read more.

Emotional intelligence is the capacity to understand, regulate, and manage one’s emotions, and it has significant effects on employees’ psychological adjustment, interpersonal relationships, and job performance. However, the specific psychological mechanisms by which emotional intelligence influences employees’ creative performance, and the conditions under which this relationship is strengthened, remain not fully understood. The aim of this study is to examine the mediating role of psychological well-being and the moderating role of cultural intelligence in the relationship between emotional intelligence and creative performance among individuals working in the information and communication technology (ICT) sector. Research data were obtained from 409 participants working in large-scale information and communication technology companies operating in Turkey, and the research hypotheses were tested using the bootstrap method with the Hayes PROCESS Macro. The findings show that emotional intelligence is positively related to psychological well-being and creative performance. Furthermore, psychological well-being significantly mediates the relationship between emotional intelligence and creative performance. The results show that cultural intelligence strengthens this indirect effect, and the contribution of emotional intelligence to creative performance is more pronounced at higher levels of cultural intelligence. The findings indicate that emotional intelligence is associated with creative performance both directly and indirectly through psychological well-being. However, the strength of this indirect association appears to vary across employees’ levels of cultural intelligence, which is considered an individual capability rather than a characteristic of the work environment. In this respect, the study contributes to the literature by examining psychological well-being as an explanatory pathway and cultural intelligence as an individual-level boundary condition in the association between emotional intelligence and creative performance. Full article

(This article belongs to the Special Issue The Influence of Emotional Intelligence on Individual Development)

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20 pages, 2576 KB

Open AccessArticle

AI Learning Self-Efficacy and Self-Perceived Digital Creative Functioning: A Conditional Indirect-Association Model

by Yihui Liu, Jinming Sun and Weida Zhang

J. Intell. 2026, 14(9), 213; https://doi.org/10.3390/jintelligence14090213 - 5 Sep 2026

Viewed by 379

Abstract

Generative artificial intelligence (GenAI) is increasingly embedded in higher education, but the association between students’ efficacy beliefs for AI-supported learning and their self-perceived digital creative functioning remains under-specified. This cross-sectional study tested a domain-specific efficacy account and examined a broad, study-specific AI learning [...] Read more.

Generative artificial intelligence (GenAI) is increasingly embedded in higher education, but the association between students’ efficacy beliefs for AI-supported learning and their self-perceived digital creative functioning remains under-specified. This cross-sectional study tested a domain-specific efficacy account and examined a broad, study-specific AI learning risk-awareness measure as an exploratory boundary condition. Survey data from 920 Chinese higher education students were analyzed using confirmatory factor analysis and regression-based conditional process analysis with 5000 bootstrap resamples. The four focal measures showed a statistically distinguishable four-factor structure, although digital creative self-efficacy and self-perceived digital creative functioning remained conceptually close. AI learning self-efficacy was positively associated with self-perceived digital creative functioning, with a smaller statistical indirect association through digital creative self-efficacy. At mean risk awareness, the model-implied indirect point estimate was 0.177, compared with a direct association of 0.612. Conditional indirect point estimates decreased modestly from 0.196 to 0.157 as risk awareness increased. The conventional index of moderated mediation was negative and small and is interpreted here only as a statistical index of change in the conditional indirect association. These findings are consistent with a domain-specific efficacy account while indicating that the indirect component was meaningful but non-dominant. Single-wave self-reports preclude causal inference and do not constitute evidence of objectively rated creativity. Full article

(This article belongs to the Special Issue The Intersection of Creativity and Intelligence: Multidisciplinary Perspectives)

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45 pages, 8109 KB

Open AccessArticle

Implementing a Cognitively Grounded Artificial Moral Advisor: A Multi-LLM Multi-Agent Approach Based on the Cognitive–Reflective Equilibration Model

by Chulmin Kim and Seongjin Ahn

J. Intell. 2026, 14(9), 212; https://doi.org/10.3390/jintelligence14090212 - 2 Sep 2026

Viewed by 2049

Abstract

Large language model (LLM)-based artificial intelligence is increasingly used in ethically consequential human decision-making, yet fully autonomous machine ethics remains unrealistic, motivating architectures that support rather than replace human ethical judgment. This study introduces the Cognitive–Reflective Equilibration Architecture (CREA), a cognitively grounded artificial [...] Read more.

Large language model (LLM)-based artificial intelligence is increasingly used in ethically consequential human decision-making, yet fully autonomous machine ethics remains unrealistic, motivating architectures that support rather than replace human ethical judgment. This study introduces the Cognitive–Reflective Equilibration Architecture (CREA), a cognitively grounded artificial moral advisor that operationalizes the Cognitive–Reflective Equilibration Model (CREM), in which reflective reasoning guides ethical judgment from intuitive cognition toward a more advanced equilibrium among competing values, drawing on Piaget and Rawls. CREA implements CREM’s 20-step process through four stage-aligned reasoning agents—Cognitive, Reflective, Equilibration, and Evaluation—coordinated via multi-LLM orchestration, in which auxiliary models independently explore principles, generate counterarguments, and score supporting and opposing considerations to externalize reflective deliberation. The architecture was empirically evaluated by comparing four configurations—single-agent, multi-agent, multi-LLM, and multi-LLM with knowledge- and reasoning-bank augmentation—across four indicators of advice quality using 500 matched execution units per configuration. All comparisons are system-internal: advice quality was scored by CREA’s own multi-LLM measurement pipeline rather than by human ethicists, so the findings reflect relative differences among architectures under LLM-based self-evaluation, not normative validity. Within that scope, distributing reflective reasoning across multiple models was associated with higher reason-giving (justifiability) and normative-alignment scores relative to simpler configurations. CREA therefore offers an empirically characterized, auditable advisor architecture whose potential to scaffold human ethical judgment remains a hypothesis for user-centered validation rather than a demonstrated outcome. Full article

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20 pages, 1054 KB

Open AccessArticle

The Eyes as a Mirror of the Unconscious: What Pupil Dilation Reveals About Unconscious Analytic Thought in Insight Problem Solving

by Laura Macchi, Manuela Turco, Daniele Inglese and Laura Caravona

J. Intell. 2026, 14(9), 211; https://doi.org/10.3390/jintelligence14090211 - 2 Sep 2026

Viewed by 485

Abstract

Recent studies suggest forms of unconscious processing in classical insight problem solving. In particular, the unconscious analytic thought (UAT) approach speculates that the creative act of restructuring such very demanding problems implies a form of high-level unconscious thought, mainly active during incubation. The [...] Read more.

Recent studies suggest forms of unconscious processing in classical insight problem solving. In particular, the unconscious analytic thought (UAT) approach speculates that the creative act of restructuring such very demanding problems implies a form of high-level unconscious thought, mainly active during incubation. The present study aims to investigate whether pupillary dilation, typically associated with conscious cognitive effort, can also represent an indicator of unconscious cognitive effort (UAT). In the experimental condition, participants attempted to solve the problem and, during the incubation phase, performed a series of single-digit arithmetic calculations. In the control condition, participants only performed the arithmetic calculations. Results showed a significant interaction between group (solvers, non-solvers and control) and temporal course on pupillary dilation. In particular, solvers, conversely to the other two groups, showed high and constant pupillary dilation during all the incubation phase, suggesting the maintenance of constant cognitive effort at an unconscious layer not attributable to anything other than the processing of the insight problem solution. In the other two groups, instead, the pupil size—starting at the same level as solvers—progressively decreased during the execution of the arithmetic task. Our results are discussed in the light of the debate on dual process theories. Full article

(This article belongs to the Special Issue Metacognition of Insight and Creative Cognition)

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31 pages, 5634 KB

Open AccessArticle

Conceptualizing and Measuring Mindfulness in School Settings: A Mixed Methods Study and Development of Mindfulness in School Scale

by Ziyaeddin Halid İpek and Ferudun Sezgin

J. Intell. 2026, 14(9), 210; https://doi.org/10.3390/jintelligence14090210 - 1 Sep 2026

Viewed by 574

Abstract

This study aimed to explore how mindfulness is perceived and experienced by teachers and to develop and validate the Mindfulness in School Scale (MSS) for use in school settings. An exploratory sequential mixed methods design was employed. In the qualitative phase, phenomenological interviews [...] Read more.

This study aimed to explore how mindfulness is perceived and experienced by teachers and to develop and validate the Mindfulness in School Scale (MSS) for use in school settings. An exploratory sequential mixed methods design was employed. In the qualitative phase, phenomenological interviews were conducted with 23 teachers selected through purposive maximum variation sampling. Content analysis identified six themes: Self-Observation, Environmental Observation, Self-Awareness, Environmental Awareness, Acceptance, and Reactive Control. These findings informed the development of the MSS. In the quantitative phase, the scale was administered to 663 teachers. Exploratory and Confirmatory Factor Analyses supported a five-dimensional structure comprising Self-Observation, Environmental Observation, Self-Awareness, Environmental Awareness, and Acceptance, explaining 51.46% of the total variance. Standardized CFA factor loadings ranged from 0.50 to 0.90, and the measurement model demonstrated satisfactory fit (χ²/df = 1.20, RMSEA = 0.028, CFI = 0.984, TLI = 0.981). The five dimensions also demonstrated satisfactory internal consistency, with Cronbach’s alpha coefficients ranging from 0.80 to 0.93. Correlations among the dimensions were generally low to moderate, indicating that the MSS captures related but distinct aspects of mindfulness in school settings rather than a single underlying construct. The findings further suggest that mindfulness in schools is shaped by both intrapersonal and interpersonal processes, with environmental awareness emerging as a contextually salient dimension. Overall, the MSS provides initial evidence for the validity and reliability of its five dimensions as a multidimensional instrument for assessing mindfulness among teachers in school settings while offering a context-specific framework for future research examining the relationship between mindfulness and emotional intelligence. Full article

(This article belongs to the Topic Personality, Emotions, and Emotional Intelligence Assessments: New Applications and Instruments)

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24 pages, 1040 KB

Open AccessArticle

Psychometric Evaluation of the Naglieri Nonverbal Ability Test (NNAT-I) in Turkish Middle School Students Aged 10–14 Years

by Sevinç Zeynep Kavruk and Ahmet Bildiren

J. Intell. 2026, 14(9), 209; https://doi.org/10.3390/jintelligence14090209 - 1 Sep 2026

Viewed by 402

Abstract

The Naglieri Nonverbal Ability Test–Individual Form (NNAT-I) is widely used to assess nonverbal reasoning while minimizing language demands, yet evidence regarding its psychometric properties in Turkish middle school students is limited. This study examined the reliability, convergent validity, internal structure, item functioning, and [...] Read more.

The Naglieri Nonverbal Ability Test–Individual Form (NNAT-I) is widely used to assess nonverbal reasoning while minimizing language demands, yet evidence regarding its psychometric properties in Turkish middle school students is limited. This study examined the reliability, convergent validity, internal structure, item functioning, and differential item functioning (DIF) of the NNAT-I in 1130 students aged 10–14 years attending schools across socioeconomic development strata in Aydın, Türkiye. Internal consistency, test–retest and alternate-form reliability, convergent validity, confirmatory factor analysis (CFA), Rasch analyses, multiple-group Rasch DIF analyses, and linear mixed-effects modeling were conducted. The NNAT-I demonstrated high internal consistency (Cronbach’s α = 0.93; McDonald’s ω = 0.94), strong test–retest and alternate-form reliability, and strong correlations with the Test of Nonverbal Intelligence–Third Edition (TONI-3) and Raven’s Standard Progressive Matrices (RSPM). CFA provided qualified rather than unequivocal evidence for a predominantly unidimensional structure, with model fit varying according to item response distributions and the treatment of structurally nonadministered responses. Rasch analyses of the calibrated items supported an ordered hierarchy of item difficulty, with all items showing Infit values within the prespecified descriptive reference range. After adjustment for multiple comparisons, DIF analyses identified significant gender-related DIF for only one item, while no items showed significant age-related DIF. Linear mixed-effects modeling showed that grade level and gender were significantly associated with NNAT-I scores, whereas chronological age was not independently associated with performance. These findings provide evidence regarding the reliability, convergent validity, internal structure, and item functioning of the NNAT-I in this Turkish middle-school sample, while also indicating that conclusions regarding unidimensionality should remain qualified. The findings underscore the importance of local psychometric evaluation before applying nonverbal measures in new educational and cultural contexts. Full article

(This article belongs to the Section Contributions to the Measurement of Intelligence)

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16 pages, 1148 KB

Open AccessArticle

Enhancing or Hindering? The Moderating Role of Self-Regulated Learning in the Relationship Between GenAI Usage and Higher-Order Thinking Skills Among Chinese University Students

by Shuangshuang Li, Jin Tian, Mengting Chen and Ziyue Wang

J. Intell. 2026, 14(9), 208; https://doi.org/10.3390/jintelligence14090208 - 1 Sep 2026

Viewed by 981

Abstract

The rapid integration of generative artificial intelligence (GenAI) into educational settings has raised growing concerns regarding its potential influence on students’ higher-order thinking skills. However, existing findings remain inconclusive, and the role of individual factors in shaping these effects has received limited attention. [...] Read more.

The rapid integration of generative artificial intelligence (GenAI) into educational settings has raised growing concerns regarding its potential influence on students’ higher-order thinking skills. However, existing findings remain inconclusive, and the role of individual factors in shaping these effects has received limited attention. Drawing on self-regulated learning theory, this study examined the relationships between GenAI usage and three higher-order thinking skills, critical thinking, creative thinking, and computational thinking, and investigated the moderating role of self-regulated learning. The results indicated that the associations between GenAI use and higher-order thinking skills varied across levels of self-regulated learning. Specifically, among students with lower levels of self-regulated learning, GenAI use was negatively associated with critical thinking, creative thinking, and computational thinking. In contrast, among students with higher levels of self-regulated learning, GenAI use was positively associated with critical thinking and computational thinking, while its association with creative thinking was not significant. Furthermore, self-regulated learning was positively associated with all three higher-order thinking skills and significantly moderated the relationships between GenAI use and critical thinking, creative thinking, and computational thinking. These findings highlight the complex cognitive consequences of GenAI usage and underscore the importance of self-regulated learning in shaping students’ cognitive outcomes in AI-assisted learning environments. The study contributes to a more nuanced understanding of how GenAI influences higher-order thinking and provides implications for promoting effective and responsible AI use in education. Full article

(This article belongs to the Special Issue Metacognition and Self-Regulated Learning in Diverse Educational Contexts)

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20 pages, 1937 KB

Open AccessArticle

Profiles or Continua? Reproducible but Redundant Creativity-Resource Configurations in PISA 2022

by Faye Antoniou and Mohammed Alghamdi

J. Intell. 2026, 14(9), 207; https://doi.org/10.3390/jintelligence14090207 - 1 Sep 2026

Viewed by 294

Abstract

Assessed creative thinking is a cognitive individual-difference construct—related to, but not equivalent to, conventional intelligence—that PISA 2022 measured directly at scale. We asked how its associated resources are structured, and whether discrete student “types” or continuous dimensions better predict creative-thinking performance. Using 44 [...] Read more.

Assessed creative thinking is a cognitive individual-difference construct—related to, but not equivalent to, conventional intelligence—that PISA 2022 measured directly at scale. We asked how its associated resources are structured, and whether discrete student “types” or continuous dimensions better predict creative-thinking performance. Using 44 education systems (306,704 students; complete-indicator sample 235,240), we estimated senate-weighted Gaussian mixtures of nine within-system standardized creativity indicators and related them to performance (10 plausible values; Fay balanced repeated replication). A six-profile solution was reproducible given adequate optimization (mean adjusted Rand index 0.95 across 12 subsamples), yet no class count was selected—information criteria improved monotonically from 2 to 12 classes—and the profiles were predictively redundant: in leakage-safe cross-validation they explained less variance (R² = 0.028) than the nine continuous indicators (0.044) or a flexible continuous model (0.068) across K = 2–12 and under hard or soft classification. After a validated classification-error correction, performance-proximal dispositions and curiosity, more than relational perceptions, predicted creative-thinking performance. For measuring and modeling creative ability, continuous resource dimensions were more informative than discrete types, which amounted to an enumeratively underdetermined, predictively redundant re-description of continuous variation. Full article

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23 pages, 1968 KB

Open AccessArticle

Individual Differences in Problem-Solving Behavior in Reasoning Tests: The Role of Item Difficulty and Item Position

by Helene M. von Gugelberg

J. Intell. 2026, 14(9), 206; https://doi.org/10.3390/jintelligence14090206 - 1 Sep 2026

Viewed by 569

Abstract

Matrix reasoning performance is often treated as a static indicator of cognitive ability, although it reflects a dynamic process that unfolds across items. The present study examined how reasoning ability and visuospatial working memory (vsWM) interact with item difficulty and item position to [...] Read more.

Matrix reasoning performance is often treated as a static indicator of cognitive ability, although it reflects a dynamic process that unfolds across items. The present study examined how reasoning ability and visuospatial working memory (vsWM) interact with item difficulty and item position to shape problem-solving behavior. Eye movements were recorded from 300 participants during a figural matrices test. Three indices of problem-solving behavior were analyzed using Bayesian multilevel models: toggle rate (ToR), proportional time on matrix (PoM), and proportional time to first fixation on response alternatives (PoFA). Results showed that higher reasoning was consistently associated with behavior indicative of constructive matching, reflected in lower ToR, higher PoM, and higher PoFA. Further, individuals with higher reasoning ability showed stronger adaptations in problem-solving behavior in response to changing task demands. Evidence regarding vsWM was more nuanced, revealing selective interactions with reasoning ability and test characteristics rather than a consistent main effect across measures. Item position revealed substantial between-person variability, which exceeded the variability associated with item difficulty. This suggests that individuals differ more strongly in how their behavior evolves across the test than in their responses to increasing difficulty. Overall, the findings highlight that problem-solving behavior in reasoning tests reflects a dynamic interplay between individual characteristics and test characteristics, emphasizing the importance of modeling both simultaneously when investigating reasoning performance. Full article

(This article belongs to the Special Issue Recent Advances, Challenges, and Achievements in Human Intelligence)

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16 pages, 2127 KB

Open AccessArticle

Effects of Combined Physical and Cognitive Stimulation on Go/No-Go Performance in Older Women: A Pilot and Feasibility Study

by Mauricio Barramuño-Medina, Pablo Valdés-Badilla, Pablo Aravena-Sagardia, Jordan Hernandez-Martínez, Edgar Vásquez-Carrasco, Esteban Fariña-Hermosilla, Wilson Pastén-Hidalgo and Germán Gálvez-García

J. Intell. 2026, 14(9), 205; https://doi.org/10.3390/jintelligence14090205 - 1 Sep 2026

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Abstract

This study aimed to examine within-subject changes associated with a 12-week multicomponent training program combined with cognitive stimulation in cognitive–motor performance in older women, and to evaluate changes in cognitive status and health-related quality of life (HRQoL). Thirty-three participants aged 70.24 (4.32) years [...] Read more.

This study aimed to examine within-subject changes associated with a 12-week multicomponent training program combined with cognitive stimulation in cognitive–motor performance in older women, and to evaluate changes in cognitive status and health-related quality of life (HRQoL). Thirty-three participants aged 70.24 (4.32) years were assessed at baseline, 6 weeks, and 12 weeks. Cognitive–motor performance was evaluated using a Go/No-Go task, including reaction time (RT), omission errors, and commission errors. Cognitive status was assessed using the Memory, Fluency, and Orientation (MEFO) score, and HRQoL was evaluated with the 36-Item Short Form Health Survey (SF-36). Mixed-effects models showed a significant reduction in RT (Δ = 51.5 ms, p < 0.001; d = 0.50) and omission errors (OR = 0.04, p < 0.001), and an increase in commission errors (OR = 2.06, p = 0.008). Cognitive status improved significantly (Δ = 0.45, p = 0.021; d = 0.34), whereas HRQoL improved only in the general health dimension (Δ = 6.82, p = 0.004; d = 0.53). Overall, the intervention was associated with a reorganization of Go/No-Go performance, characterized by faster responding, but increased commission errors, indicating no improvement in motor inhibition. These findings suggest that this multidomain approach is feasible and warrants evaluation in randomized controlled trials. Full article

(This article belongs to the Special Issue Exercise and Intelligence: Cognitive, Emotional, and Neural Mechanisms)

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21 pages, 834 KB

Open AccessArticle

AI-Mediated Informal Digital Learning of English for Speaking Development: Longitudinal Effects on Ability and Affect and Implications for Adaptive Intelligence

by Difei Jia, Xi Chen and Yunsong Wang

J. Intell. 2026, 14(9), 204; https://doi.org/10.3390/jintelligence14090204 - 1 Sep 2026

Cited by 1 | Viewed by 946

Abstract

Generative artificial intelligence (GenAI) has expanded opportunities for English learning beyond formal classroom settings. From an intelligence perspective, speaking in English as a foreign language (EFL) represents an applied domain in which learners must adaptively retrieve, integrate, monitor, and deploy linguistic knowledge under [...] Read more.

Generative artificial intelligence (GenAI) has expanded opportunities for English learning beyond formal classroom settings. From an intelligence perspective, speaking in English as a foreign language (EFL) represents an applied domain in which learners must adaptively retrieve, integrate, monitor, and deploy linguistic knowledge under communicative demands. The present study examined the effects of a pedagogically guided form of AI-mediated informal digital learning of English (AI-IDLE) on Chinese university EFL learners’ speaking ability, speaking anxiety, and speaking enjoyment. To this end, 89 Chinese university EFL learners participated in a 12-week intervention and were assigned to an experimental group (EG) or a control group (CG). Pre- and post-intervention evaluations were administered to assess the results, including standardized speaking skills and valid questionnaires regarding enjoyment and speaking anxiety. The English-speaking skills test and the two questionnaires were administered at post-test and again 10 weeks after the intervention as the delayed post-test. Mixed-effects modeling (MEM) was used, and the findings showed that the EG demonstrated significantly greater improvements in speaking ability and enjoyment and a greater reduction in speaking anxiety than the CG, with these between-group advantages evident at the post-test. Overall, the findings suggest that structured AI-IDLE can provide a digitally mediated context for intelligence-relevant adaptive learning by supporting communicative performance while fostering affective conditions conducive to its development. These findings have implications for understanding how digitally mediated informal learning environments may support adaptive intelligence in applied language-learning contexts. Full article

(This article belongs to the Special Issue Informal Digital Language Learning as a Site for Activating and Developing Intelligence)

31 pages, 3301 KB

Open AccessArticle

Beyond Problem-Solving: Interactive Worked Examples as Pathways to Dual Teacher Expertise

by Tikva Ovadiya

J. Intell. 2026, 14(9), 203; https://doi.org/10.3390/jintelligence14090203 - 1 Sep 2026

Viewed by 695

Abstract

Teacher learning presents a unique cognitive challenge: educators must simultaneously develop mathematical expertise and pedagogical knowledge for teaching. This study examines how interactive worked examples function as cognitive tools to support this dual learning process. Using a qualitative, exploratory case-study design, I investigated [...] Read more.

Teacher learning presents a unique cognitive challenge: educators must simultaneously develop mathematical expertise and pedagogical knowledge for teaching. This study examines how interactive worked examples function as cognitive tools to support this dual learning process. Using a qualitative, exploratory case-study design, I investigated how 30 in-service mathematics teachers engaged with interactive worked examples of non-routine problems in a professional development setting designed to reduce extraneous cognitive load while promoting germane processing. Drawing on Cognitive Load Theory, expertise development frameworks, and recent perspectives on cognitive offloading and affective engagement in multimedia learning, I analyzed the cognitive and emotional mechanisms underlying teachers’ acquisition of both mathematical content knowledge and pedagogical content knowledge. Results from teachers’ journals, reflective protocols, and self-assessed cognitive load measurements reveal three key findings: First, teachers experienced analyzing worked examples not as passive observation but as active problem-solving, engaging in self-explanation and schema construction. Second, the interactive format enabled them to discover new mathematical relationships and solution strategies that were previously unavailable to them. Third, and notably, teachers simultaneously developed pedagogical insights—recognizing instructional approaches and anticipating student difficulties—while working through the mathematical content. These findings extend worked example theory by demonstrating that carefully designed interactive examples can support dual-domain learning in professional contexts. By managing cognitive load through scaffolded interactivity, worked examples enable teachers to construct both mathematical and pedagogical schemas concurrently, suggesting a cognitively efficient pathway for teacher professional development. Given the study’s exploratory, single-setting design, these mechanisms are offered as a theoretically grounded account to be tested in future comparative research rather than as definitive causal claims. Full article

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17 pages, 1278 KB

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Motivational Self-Regulation Strategies and Their Relationship with Academic Adjustment Across Adolescent High-Ability, Learning-Disability, and Regular Students

by Zeltia Martínez-López, Mª Emma Mayo, Jose Eulogio Real and Carolina Tinajero

J. Intell. 2026, 14(9), 202; https://doi.org/10.3390/jintelligence14090202 - 1 Sep 2026

Viewed by 607

Abstract

Motivational self-regulation strategies (MRSs) play a key role in how students initiate, sustain, and direct effort during learning. However, little is known about their use among adolescents with different educational profiles. This study aimed to explore possible differences in the use of MRSs [...] Read more.

Motivational self-regulation strategies (MRSs) play a key role in how students initiate, sustain, and direct effort during learning. However, little is known about their use among adolescents with different educational profiles. This study aimed to explore possible differences in the use of MRSs among adolescent students with varying learning potential (high-ability, learning-disability and regular students) and to examine whether the relationship between MRSs and academic adjustment differed across these educational profiles. We recruited a sample of 2191 students enrolled in compulsory secondary education, comprising regular students (81.8%, N = 1792), students with learning disabilities (15.8%, N = 347), and high-ability students (2.4%, N = 52). The participants completed self-report measures of MRSs and academic adjustment. Path models were used to examine cross-sectional direct and indirect associations among the study variables, and they revealed different patterns across the three groups. High-ability status was directly and positively associated with academic adjustment, while learning-difficulty status showed a direct negative relationship with adjustment. The three groups of students showed indirect associations with adjustment via various types of MRSs. Full article

(This article belongs to the Special Issue Metacognition and Self-Regulated Learning in Diverse Educational Contexts)

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35 pages, 1990 KB

Open AccessArticle

Comparing Human Ability with Generative AI: Self-Evaluation, Appraisal, and Adaptive Professional Intelligence Among Journalism and Communication Students

by Juan Wang, Zichen Liu and Jiaying Huang

J. Intell. 2026, 14(9), 201; https://doi.org/10.3390/jintelligence14090201 - 1 Sep 2026

Viewed by 626

Abstract

Generative artificial intelligence (AI) is reshaping how students evaluate their abilities, occupational prospects, and the continuing value of professional education. This study examined how ability-based comparison with AI is associated with perceived professional value among journalism and communication students and why the same [...] Read more.

Generative artificial intelligence (AI) is reshaping how students evaluate their abilities, occupational prospects, and the continuing value of professional education. This study examined how ability-based comparison with AI is associated with perceived professional value among journalism and communication students and why the same comparison may be linked to both threatening and adaptive responses. An explanatory sequential mixed-methods design was used. Survey data from 507 students in China were analyzed using partial least squares structural equation modeling, with PROCESS analyses as robustness checks, followed by semi-structured interviews with 20 students. Ability-based comparison with AI was positively associated with job replacement anxiety, which was negatively associated with perceived professional value, and with AI learning motivation, which was positively associated with perceived professional value. A positive direct association with perceived professional value also remained. AI hindrance appraisal strengthened the comparison–anxiety association, whereas AI challenge appraisal did not significantly moderate the comparison–motivation association. Interviews indicated that these relationships were task- and criterion-dependent and shaped by occupational interpretation and concrete learning demands. Human–AI comparison may therefore relate to professional value through simultaneous threat- and adaptation-oriented pathways rather than a uniformly positive or negative process. Full article

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