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Capability Assessment of Cultivating Innovative Talents for Higher Schools Based on Machine Learning
Rongjie Huang; Yusheng Sun; Zhifeng Zhang; Bo Wang; Junxia Ma; Yangyang Chu – International Journal of Information and Communication Technology Education, 2024
The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive assessment of innovation cultivation capability is an important basis of higher schools for continuous improvement. Thus, this paper focuses on assessing…
Descriptors: Models, Innovation, Higher Education, Evaluation
Bao Wang; Philippe J. Giabbanelli – International Journal of Artificial Intelligence in Education, 2024
Knowledge maps have been widely used in knowledge elicitation and representation to evaluate and guide students' learning. To effectively evaluate maps, instructors must select the most informative map features that capture students' knowledge constructs. However, there is currently no clear and consistent criteria to select such features, as…
Descriptors: Concept Mapping, Evaluation Methods, Student Evaluation, Algorithms
R. Thapa; A. Garikipati; M. Ciobanu; N.P. Singh; E. Browning; J. DeCurzio; G. Barnes; F.A. Dinenno; Q. Mao; R. Das – Journal of Autism and Developmental Disorders, 2024
Purpose: Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic criteria has changed from DSM-IV to DSM-5, which can make diagnosing a disorder on the autism spectrum…
Descriptors: Autism Spectrum Disorders, Symptoms (Individual Disorders), Clinical Diagnosis, Artificial Intelligence
Xiang Feng; Keyi Yuan; Xiu Guan; Longhui Qiu – Interactive Learning Environments, 2024
Datasets are critical for emotion analysis in the machine learning field. This study aims to explore emotion analysis datasets and related benchmarks in online learning, since, currently, there are very few studies that explore the same. We have scientifically labeled the topic and nine-category emotion of 4715 comment texts in online learning…
Descriptors: MOOCs, Psychological Patterns, Artificial Intelligence, Prediction
Shang Shanshan; Geng Sen – Journal of Computer Assisted Learning, 2024
Background: Artificial intelligence-generated content (AIGC) has stepped into the spotlight with the emergence of ChatGPT, making effective use of AIGC for education a hot topic. Objectives: This study seeks to explore the effectiveness of integrating AIGC into programming learning through debugging. First, the study presents three levels of AIGC…
Descriptors: Artificial Intelligence, Educational Technology, Technology Integration, Programming
Hao Tran; Annita Stell – Australian Review of Applied Linguistics, 2024
Generative Artificial Intelligence (GenAI) has been offering unprecedented opportunities for language education. However, its capacity to embrace linguistic diversity, particularly for learners of dialect-rich languages like Vietnamese and Mandarin, remains underexamined. Without careful consideration, GenAI risks reinforcing language hegemonies,…
Descriptors: Artificial Intelligence, Land Settlement, Vietnamese, Dialects
Idam Ragil Widianto Atmojo; Roy Ardiansyah; Joko Tri Widianto – Elementary School Forum (Mimbar Sekolah Dasar), 2024
This study aims to determine whether there is a relationship between linguistic intelligence and computational thinking. The research method employed is quantitative, utilizing a correlational research design. The research sample comprised 73 students from 4 elementary schools in the Laweyan District, Surakarta City. Data collection involved a…
Descriptors: Intelligence, Linguistics, Computation, Grade 5
Dezziree Harrell – ProQuest LLC, 2024
This mixed model study set out to investigate the burnout and self-efficacy of school counselors. It also examined the emotional intelligence of school principals and the self-efficacy of school counselors. Burnout may occur due to the rise in stress related to one's employment. According to Mullen and Gutierrez (2016), there may be a reduction in…
Descriptors: Burnout, Self Efficacy, Principals, Emotional Intelligence
Giulio F. Marchena Sekli; Amy Godo; José Carlos Véliz – Journal of Information Technology Education: Research, 2024
Aim/Purpose: This paper aims to address the gap in comprehensive, real-world applications of Generative Artificial Intelligence (GenAI) in education, particularly in higher education settings. Despite the evident potential of GenAI in transforming educational practices, there is a lack of consolidated knowledge about its practical effectiveness…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Educational Research
Liunian Li – ProQuest LLC, 2024
To build an Artificial Intelligence system that can assist us in daily lives, the ability to understand the world around us through visual input is essential. Prior studies train visual perception models by defining concept vocabularies and annotate data against the fixed vocabulary. It is hard to define a comprehensive set of everything, and thus…
Descriptors: Artificial Intelligence, Visual Stimuli, Visual Perception, Models
Jinsook Lee; Yann Hicke; Renzhe Yu; Christopher Brooks; René F. Kizilcec – British Journal of Educational Technology, 2024
Large language models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education…
Descriptors: Artificial Intelligence, Technology Uses in Education, Equal Education, Algorithms
Kalervo N. Gulson; Sam Sellar – Journal of Education Policy, 2024
The growing use of artificial intelligence in education extends and intensifies technologies of governing, including datafication, performativity and accountability. In this article, we outline how the use of AI and data science has the disruptive potential to create new norms in education policy and governance. We report on an ethnographic…
Descriptors: Artificial Intelligence, Educational Policy, Governance, Evidence
Karlis Kanders; Louis Stupple-Harris; Laurie Smith; Jenny Louise Gibson – Infant and Child Development, 2024
Generative artificial intelligence (GAI) is rapidly becoming ubiquitous in many contexts. There is limited scholarship, however, in the fields of Developmental Psychology and Early Childhood Education exploring the implications of generative AI for babies and young children. In this Perspectives piece, we discuss potential use cases,…
Descriptors: Artificial Intelligence, Early Childhood Education, Child Development, Infants
Richard Raymond Freda – ProQuest LLC, 2024
Despite studies showing that individuals with higher levels of emotional intelligence report higher job satisfaction and happiness, relatively few studies have looked at the relationship between higher levels of emotional intelligence and lower levels of teacher burnout, especially among music teachers. With so many music teaching positions going…
Descriptors: Correlation, Emotional Intelligence, Teacher Burnout, Music Teachers
Yang Shi; Tiffany Barnes; Min Chi; Thomas Price – International Educational Data Mining Society, 2024
Knowledge tracing (KT) models have been a commonly used tool for tracking students' knowledge status. Recent advances in deep knowledge tracing (DKT) have demonstrated increased performance for knowledge tracing tasks in many datasets. However, interpreting students' states on single knowledge components (KCs) from DKT models could be challenging…
Descriptors: Algorithms, Artificial Intelligence, Models, Programming

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