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Shruti Priya; Shubhankar Bhadra; Sridhar Chimalakonda; Akhila Sri Manasa Venigalla – Interactive Learning Environments, 2024
Owing to the predominant role of Machine Learning(ML) across domains, it is being introduced at multiple levels of education, including K-12. Researchers have leveraged games, augmented reality and other ways to make learning ML concepts interesting. However, most of the existing games to teach ML concepts either focus on use-cases and…
Descriptors: Artificial Intelligence, Secondary School Students, Video Games, Visual Aids
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Munise Seçkin Kapucu; I?brahim Özcan; Hülya Özcan; Ahmet Aypay – International Journal of Technology in Education and Science, 2024
Our research aims to predict students' academic performance by considering the variables affecting academic performance in science courses using the deep learning method from machine learning algorithms and to determine the importance of independent variables affecting students' academic performance in science courses. 445 students from 5th, 6th,…
Descriptors: Secondary School Students, Science Achievement, Artificial Intelligence, Foreign Countries
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Anas Husain – Journal of Information Technology Education: Research, 2024
Aim/Purpose: This study aims to investigate the perceptions of programming instructors among the Information Technology faculty members at AL al-Bayt University regarding the effectiveness of ChatGPT in supporting the programming instructional process. This study also aims to explore their experiences concerning the potential benefits and adverse…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Programming
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Abhijit Guha; Dhruv Grewal; Stephen Atlas – Journal of Marketing Education, 2024
To understand why and how marketing educators can best use generative artificial intelligence (AI), such as ChatGPT, this article integrates a literature survey, interviews with both marketing educators and managers, and surveys of both marketing educators and students. In leveraging these inputs, the authors argue that generative AI can…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Business Administration Education
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Boyd H. Davis; Meredith Troutman-Jordan; Margaret Maclagan – International Journal of Language & Communication Disorders, 2024
Background: This study reports on new contexts in which formulaic language has been used in the years since 2013 when the last synthesis was carried out. The background presents an old but still useful definition and lists themes under which research was arranged in 2013 and which continue to be used. Aims: This study has a particular emphasis on…
Descriptors: Phrase Structure, Language Variation, Computational Linguistics, Pragmatics
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Dandan Zhou; Adrienne Sansom – Compare: A Journal of Comparative and International Education, 2024
Educational reform in China has brought about many Western educational approaches for teachers to consider as part of their pedagogy. An example of this is the theory of multiple intelligences (MI theory). This paper presents how a theory grounded in a Western context is locally reconceptualised by kindergarten teachers who grew up in a different…
Descriptors: Multiple Intelligences, Teacher Attitudes, Context Effect, Educational Theories
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Ha Tien Nguyen; Conrad Borchers; Meng Xia; Vincent Aleven – Grantee Submission, 2024
Intelligent tutoring systems (ITS) can help students learn successfully, yet little work has explored the role of caregivers in shaping that success. Past interventions to support caregivers in supporting their child's homework have been largely disjunct from educational technology. The paper presents prototyping design research with nine middle…
Descriptors: Middle School Mathematics, Intelligent Tutoring Systems, Caregivers, Caregiver Attitudes
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Qing Wang; Xizhen Cai – Journal of Statistics and Data Science Education, 2024
Support vector classifiers are one of the most popular linear classification techniques for binary classification. Different from some commonly seen model fitting criteria in statistics, such as the ordinary least squares criterion and the maximum likelihood method, its algorithm depends on an optimization problem under constraints, which is…
Descriptors: Active Learning, Class Activities, Classification, Artificial Intelligence
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Margaret A.L. Blackie – Teaching in Higher Education, 2024
Large language models such as ChatGPT can be seen as a major threat to reliable assessment in higher education. In this point of departure, I argue that these tools are a major game changer for society at large. Many of the jobs we now consider highly skilled are based on pattern recognition that can much more reliably be carried by fine-tuned…
Descriptors: Artificial Intelligence, Synchronous Communication, Science and Society, Evaluation
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Faruk Bulut; I?lknur Dönmez; I?brahim Furkan I?nce; Pavel Petrov – International Online Journal of Primary Education, 2024
A homogeneous distribution of students in a class is accepted as a key factor for overall success in primary education. A class of students with similar attributes normally increases academic success. It is also a fact that general academic success might be lower in some classes where students have different intelligence and academic levels. In…
Descriptors: Elementary School Students, Grade 1, Teaching Methods, Supervision
Skylar McBride – ProQuest LLC, 2024
The purpose of this phenomenological qualitative study was to explore how educators describe the impact of SEL instruction provided by the guidance counselor. Additionally, this study also sought to explore how educators perceive the supporting role they play in the delivery of SEL instruction alongside the guidance counselor. The overarching two…
Descriptors: Social Emotional Learning, Emotional Intelligence, Private Schools, Phenomenology
Matthew Christopher Myers – ProQuest LLC, 2024
This study uses an experimental comparative design to accomplish two primary goals related teachers' perceptions of automated writing evaluation (AWE) performance. First, it quantitatively and qualitatively examines teachers' perceptions of the accuracy and trustworthiness of differentially performing AWE models. Second, it synthesizes interview…
Descriptors: Language Arts, Teacher Attitudes, English Teachers, Automation
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Ramon Mayor Martins; Christiane Gresse Von Wangenheim; Marcelo Fernando Rauber; Jean Carlo Rossa Hauck; Melissa Figueiredo Silvestre – Informatics in Education, 2024
Knowledge about Machine Learning (ML) is becoming essential, yet it remains a restricted privilege that may not be available to students from a low socio-economic status background. Thus, in order to provide equal opportunities, we taught ML concepts and applications to 158 middle and high school students from a low socio-economic background in…
Descriptors: Middle School Students, High School Students, Low Income Students, Socioeconomic Status
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E. Gothai; S. Saravanan; C. Thirumalai Selvan; Ravi Kumar – Education and Information Technologies, 2024
In recent years, online education has been given more and more attention with the widespread use of the internet. The teaching procedure divides space and makes time for online learning; though teachers cannot control the learners accurately, the state of education calculates learners' learning situation. This paper explains that the discourse…
Descriptors: Artificial Intelligence, Discourse Analysis, Classification, Comparative Analysis
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Bing Mei; Wenya Qi; Xiao Huang; Shuo Huang – RELC Journal: A Journal of Language Teaching and Research, 2024
Recent years have witnessed the growing presence of artificial intelligence in language learning apps. Against this backdrop, this technology review provides an overview of the affordances of Speeko and discusses its potential in developing English-as-a-foreign-language students' public speaking skills.
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Speech Communication, Speech Skills
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