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Kaili Lu; Jianrong Zhu; Feng Pang; Rustam Shadiev – Educational Technology Research and Development, 2025
Artificial Intelligence (AI) has brought about significant changes in our lives, making AI literacy a crucial endeavor for the future. Despite its growing importance in academia, there is limited empirical research on its impact on college students' higher order thinking skills (HOTS). The present study systematically and comprehensively explores…
Descriptors: College Students, Artificial Intelligence, Digital Literacy, Thinking Skills
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Bekir Yildirim; Ahmet Tayfur Akcan – Journal of Education in Science, Environment and Health, 2024
This study aimed to propose a Professional Development Model (PDM) for chemistry teachers to enhance their professional development in Artificial Intelligence (AI). The research group consisted of 17 chemistry teachers. The study was designed using a particular case study suitable for qualitative research methods. Document review, teacher…
Descriptors: Artificial Intelligence, Faculty Development, Science Teachers, Chemistry
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Du, Yunfei; Gao, Han – Education and Information Technologies, 2022
Artificial Intelligence (AI) has been exerting a revolutionary and profound impact on the teaching of English as Foreign Language (EFL) for decades. In spite of these acknowledged advances, teachers have numerous reservations and objections against the adoption of AI-based applications. In order to facilitate the proper use and produce an…
Descriptors: Artificial Intelligence, English (Second Language), Second Language Learning, Second Language Instruction
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Deliang Wang; Cunling Bian; Gaowei Chen – British Journal of Educational Technology, 2024
Deep neural networks are increasingly employed to model classroom dialogue and provide teachers with prompt and valuable feedback on their teaching practices. However, these deep learning models often have intricate structures with numerous unknown parameters, functioning as black boxes. The lack of clear explanations regarding their classroom…
Descriptors: Artificial Intelligence, Dialogs (Language), Discourse Analysis, Trust (Psychology)
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Binh Nguyen Thanh; Diem Thi Hong Vo; Minh Nguyen Nhat; Thi Thu Tra Pham; Hieu Thai Trung; Son Ha Xuan – Australasian Journal of Educational Technology, 2023
In this study, we introduce a framework designed to help educators assess the effectiveness of popular generative artificial intelligence (AI) tools in solving authentic assessments. We employed Bloom's taxonomy as a guiding principle to create authentic assessments that evaluate the capabilities of generative AI tools. We applied this framework…
Descriptors: Artificial Intelligence, Models, Performance Based Assessment, Economics Education
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Yik, Brandon J.; Dood, Amber J.; Cruz-Ramirez de Arellano, Daniel; Fields, Kimberly B.; Raker, Jeffrey R. – Chemistry Education Research and Practice, 2021
Acid-base chemistry is a key reaction motif taught in postsecondary organic chemistry courses. More specifically, concepts from the Lewis acid-base model are broadly applicable to understanding mechanistic ideas such as electron density, nucleophilicity, and electrophilicity; thus, the Lewis model is fundamental to explaining an array of reaction…
Descriptors: Artificial Intelligence, Models, Formative Evaluation, Organic Chemistry
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Nurul Ashikin Izhar; Wendy Ven Ye Teh; Anita Adnan – Journal of Information Technology Education: Innovations in Practice, 2025
Aim/Purpose: This study investigates the key factors influencing the adoption and use of artificial intelligence (AI) applications among researchers, focusing on effort expectancy, satisfaction, perceived ease of use, and perceived usefulness, which shaped attitudes and drove AI adoption as a research assistant. Background: AI tools have rapidly…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Technology Integration
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Ouyang, Fan; Wu, Mian; Zheng, Luyi; Zhang, Liyin; Jiao, Pengcheng – International Journal of Educational Technology in Higher Education, 2023
As a cutting-edge field of artificial intelligence in education (AIEd) that depends on advanced computing technologies, AI performance prediction model is widely used to identify at-risk students that tend to fail, establish student-centered learning pathways, and optimize instructional design and development. A majority of the existing AI…
Descriptors: Technology Integration, Artificial Intelligence, Performance, Prediction
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Liu, Xinyang; Ardakani, Saeid Pourroostaei – Education and Information Technologies, 2022
The purpose of this study is to propose an e-learning system model for learning content personalisation based on students' emotions. The proposed system collects learners' brainwaves using a portable Electroencephalogram and processes them via a supervised machine learning algorithm, named K-nearest neighbours (KNN), to recognise real-time…
Descriptors: Foreign Countries, Undergraduate Students, Electronic Learning, Artificial Intelligence
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Polak, Julia; Cook, Dianne – Journal of Statistics and Data Science Education, 2021
Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…
Descriptors: Artificial Intelligence, Data Analysis, Models, Competition
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Maulini, Claudia; Kuvacic, Goran; Savani, Wlady; Zanelli, Vanessa; Padovan, Anna Maria; Bocciolesi, Enrico; De Giorgio, Andrea – Education Sciences, 2021
Literature highlights how education in the twenty-first century begins to advocate multiple new concepts, such as new technology, new pedagogies, interdisciplinary curricula, open learning, etc. Among these concepts, the recognition and awareness about one's character strengths are demonstrated to improve emotional management and…
Descriptors: Models, Emotional Intelligence, Metacognition, Preadolescents
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Dongkawang Shin; Yuah V. Chon – Language Learning & Technology, 2023
Considering noticeable improvements in the accuracy of Google Translate recently, the aim of this study was to examine second language (L2) learners' ability to use post-editing (PE) strategies when applying AI tools such as the neural machine translator (MT) to solve their lexical and grammatical problems during L2 writing. This study examined 57…
Descriptors: Second Language Learning, Second Language Instruction, Translation, Computer Software
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Jee, Benjamin D.; Anggoro, Florencia K. – Grantee Submission, 2019
Models are central to the practice and teaching of science. Yet people often fail to grasp how scientific models explain their observations of the world. Realizing the explanatory power of a model may require aligning its relational structure to that of the observable phenomena. The present research tested whether "relational…
Descriptors: Scaffolding (Teaching Technique), Children, Comprehension, Models
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Okur-Berberoglu, Emel – International Electronic Journal of Environmental Education, 2018
Ecoliteracy is to understand and internalise sustainable ecological relationship in the nature and to transfer this sustainable lifestyle to daily life despite the fact that ecoliteracy does not have only one and unique definition. However, it is difficult to measure ecoliteracy due to it being a complex concept. There are many subsets of…
Descriptors: Literacy, Structural Equation Models, Sustainability, Life Style
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Oh Neill, Sam – Canadian Journal of Action Research, 2014
I have worked with students at-risk for the greater majority of my career. The term has a number of meanings. Officially, it means they are at-risk of failing, but often the risks are much greater. At one extreme they are at-risk of losing their lives to substance abuse or suicide. Less drastically they are at-risk of making their way through the…
Descriptors: At Risk Students, Interpersonal Competence, Student Needs, Student Development
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