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Connective Comprehension: An individual differences study ...
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Considering Commonsense in Solving QA: Reading Comprehension with Semantic Search and Continual Learning
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4099 (2022)
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Re-Evaluating Early Memorization of the Qurʾān in Medieval Muslim Cultures
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In: Religions; Volume 13; Issue 2; Pages: 179 (2022)
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Knowledge Representation and Reasoning with an Extended Dynamic Uncertain Causality Graph under the Pythagorean Uncertain Linguistic Environment
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4670 (2022)
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A Deep Fusion Matching Network Semantic Reasoning Model
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In: Applied Sciences; Volume 12; Issue 7; Pages: 3416 (2022)
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OntoDomus: A Semantic Model for Ambient Assisted Living System Based on Smart Homes
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In: Electronics; Volume 11; Issue 7; Pages: 1143 (2022)
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Is Early Bilingual Experience Associated with Greater Fluid Intelligence in Adults?
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In: Languages; Volume 7; Issue 2; Pages: 100 (2022)
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Design of an Artificial Intelligence of Things Based Indoor Planting Model for Mentha Spicata
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In: Processes; Volume 10; Issue 1; Pages: 116 (2022)
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Formalization of AMR Inference via Hybrid Logic Tableaux ...
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Child Social Understanding: How Theory of Mind Development is Influenced by Socio-Cultural Factors
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Abstract:
It is widely recognised that possessing a theory of mind is a cornerstone of human social interaction. While theory of mind has been extensively researched over the past three decades, it was not until much more recently that researchers began to consider deontic reasoning (reasoning about social rules and regulations) as another critical part of social understanding. Research has not comprehensively investigated the relationship between theory of mind and deontic reasoning development in young children. Likewise, research has not yet focused on the influence of parental self-construal (i.e., how the parent views themselves in relation to others) on child theory of mind development, and how this relationship may be mediated by parental language use. Our sample comprised 55 children aged between 3 and 7 years (M= 5.2 years) and their primary caregiver, with each parent-child dyad participating in either one or two experimental sessions consisting of six theory of mind and seven deontic reasoning tasks. Parents completed a cultural self-construal questionnaire, an autonomy-relatedness questionnaire, and a parenting goals questionnaire. Parent and child language use was assessed through the completion of a picture description task. The results suggested that there is no clear distinction between theory of mind and deontic reasoning tasks, and that deontic reasoning may be a part of the broader theory of mind construct. Results also demonstrated that parents with more interdependent self-construals had children who performed better on the false belief tasks. Lastly, results indicated that parents who were more interdependent had children who, on average, had an increase in theory of mind ability due to the parental tendency to use more cognitive language. These findings illustrate the importance of socio-cultural factors in child social understanding.
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Keyword:
child development; culture; deontic reasoning; parental language; self-construal; theory of mind
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URL: http://hdl.handle.net/10523/12716
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Neural-based Knowledge Transfer in Natural Language Processing
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Ranking Semantics for Argumentation Systems With Necessities
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In: IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence ; https://hal.archives-ouvertes.fr/hal-03002056 ; IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence, Jan 2021, Yokohama / Virtual, Japan. pp.1912-1918, ⟨10.24963/ijcai.2020/265⟩ (2021)
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| 18 |
Ontological Formalisation of Mathematical Equations for Phenomic Data Exploitation
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In: The Semantic Web: ESWC 2021 Satellite Events ; https://hal.inrae.fr/hal-03408000 ; Ruben Verborgh; Anastasia Dimou; Aidan Hogan; Claudia d'Amato; Ilaria Tiddi; Arne Bröring; Simon Mayer; Femke Ongenae; Riccardo Tommasini; Mehwish Alam. The Semantic Web: ESWC 2021 Satellite Events, 12739, Springer International Publishing, pp.176-185, 2021, Lecture Notes in Computer Science, 978-3-030-80417-6. ⟨10.1007/978-3-030-80418-3_30⟩ (2021)
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| 19 |
Multimodal Conversation Modeling via Neural Perception, Structure Learning, and Communication
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| 20 |
How Do Language Intensity and Artificial Intelligence (AI) Affect Perceptions of Fact-checking Messages and Evaluations of Fact-checking Agencies?
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Xue, Haoning. - : eScholarship, University of California, 2021
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