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Lee, Hee-Sun; Gweon, Gey-Hong; Lord, Trudi; Paessel, Noah; Pallant, Amy; Pryputniewicz, Sarah – Journal of Science Education and Technology, 2021
A design study was conducted to test a machine learning (ML)-enabled automated feedback system developed to support students' revision of scientific arguments using data from published sources and simulations. This paper focuses on three simulation-based scientific argumentation tasks called Trap, Aquifer, and Supply. These tasks were part of an…
Descriptors: Artificial Intelligence, Automation, Feedback (Response), Persuasive Discourse
Gudiño Paredes, Sandra; Jasso Peña, Felipe de Jesús; de La Fuente Alcazar, Juana María – Distance Education, 2021
After almost a year of COVID-19, distance education mediated by digital tools prevails as an ideal way to study given the flexibility, ubiquity, and a variety of tools that make the process more acceptable. Remote proctored exams have become an important tool to ensure integrity and academic honesty in distance education. This mixed methods study…
Descriptors: Distance Education, Computer Assisted Testing, Integrity, Electronic Learning
Chiu, Thomas K. F. – TechTrends: Linking Research and Practice to Improve Learning, 2021
Artificial intelligence (AI) education in K-12 schools is currently very popular, but educators and experts have found designing AI-related curricula a challenge. Few studies have been conducted that can inform practitioners about how to design and implement AI-related curricula, and thus sustainable approaches that can inform the planning of…
Descriptors: Artificial Intelligence, Elementary Secondary Education, Curriculum Design, Curriculum Development
Jones, Joshua – Mathematics Teacher: Learning and Teaching PK-12, 2021
Aside from being culturally relevant, artificial intelligence is also supporting companies in making business decisions. Consequently, "workforce needs have shifted rapidly," resulting in a demand for applicants who are skilled in "data, analytics, machine learning, and artificial intelligence" (Miller and Hughes 2017). This…
Descriptors: Man Machine Systems, Artificial Intelligence, Educational Technology, Technology Uses in Education
Yan, Shouxuan; Yang, Yun – ECNU Review of Education, 2021
Purpose: This article aims to shed light on a latest education informatization policy blueprint in China, titled "Education Informatization 2.0 Action Plan," which was promulgated by the Ministry of Education in China on April 18, 2018. Design/Approach/Methods: The study is an analytical policy review based on the policy documents,…
Descriptors: Foreign Countries, Educational Policy, Technology Uses in Education, Educational Technology
Gurcan, Fatih; Ozyurt, Ozcan; Cagiltay, Nergiz Ercil – International Review of Research in Open and Distributed Learning, 2021
E-learning studies are becoming very important today as they provide alternatives and support to all types of teaching and learning programs. The effect of the COVID-19 pandemic on educational systems has further increased the significance of e-learning. Accordingly, gaining a full understanding of the general topics and trends in e-learning…
Descriptors: Educational Trends, Electronic Learning, Models, Learning Analytics
Lin, Chun-Hung; Yu, Chih-Chang; Shih, Po-Kang; Wu, Leon Yufeng – Educational Technology & Society, 2021
This article describes STEM education with artificial intelligence (AI) learning, particularly for non-engineering undergraduate students. In the designed three-week learning activities, students were encouraged to put their ideas about AI into practice through two hands-on activities, utilizing a provided deep learning-based web service. This…
Descriptors: STEM Education, Artificial Intelligence, General Education, Nonmajors
Silvervarg, Annika; Wolf, Rachel; Blair, Kristen Pilner; Haake, Magnus; Gulz, Agneta – Journal of Research on Technology in Education, 2021
Does a teachable agent influence the uptake or neglect of 'critical constructive feedback' and learning within a digital environment? 285 middle-school students engaged with a history learning game in a 2x2 study design. One dimension was inclusion of a teachable agent. Orthogonal was whether critical constructive feedback was presented…
Descriptors: Teaching Methods, Feedback (Response), Middle School Students, History Instruction
Shi, Zhixing; Ma, Junjie – Online Submission, 2021
The development and popularization of online classroom is an inevitable trend given the tremendous progress of science and technology and the advent of 5G information era. In this special period, if possible, most of the offline classes are converted to online classes, using tablets or computers for online classes. Online classes are divided into…
Descriptors: Educational Technology, Educational Innovation, Online Courses, Technology Uses in Education
Geoffrey Converse – ProQuest LLC, 2021
In educational measurement, Item Response Theory (IRT) provides a means of quantifying student knowledge. Specifically, IRT models the probability of a student answering a particular item correctly as a function of the student's continuous-valued latent abilities [theta] (e.g. add, subtract, multiply, divide) and parameters associated with the…
Descriptors: Item Response Theory, Test Validity, Student Evaluation, Computer Assisted Testing
Aryadoust, Vahid – Language Testing, 2023
Construct validity and building validity arguments are some of the main challenges facing the language assessment community. The notion of construct validity and validity arguments arose from research in psychological assessment and developed into the gold standard of validation/validity research in language assessment. At a theoretical level,…
Descriptors: Testing Problems, Test Validity, Second Language Learning, Construct Validity
Dahlkemper, Merten Nikolay; Lahme, Simon Zacharias; Klein, Pascal – Physical Review Physics Education Research, 2023
This study aimed at evaluating how students perceive the linguistic quality and scientific accuracy of ChatGPT responses to physics comprehension questions. A total of 102 first- and second-year physics students were confronted with three questions of progressing difficulty from introductory mechanics (rolling motion, waves, and fluid dynamics).…
Descriptors: Physics, Science Instruction, Artificial Intelligence, Computer Software
Sanusi, Ismaila Temitayo; Oyelere, Solomon Sunday; Vartiainen, Henriikka; Suhonen, Jarkko; Tukiainen, Markku – Education and Information Technologies, 2023
The increasing attention to Machine Learning (ML) in K-12 levels and studies exploring a different aspect of research on K-12 ML has necessitated the need to synthesize this existing research. This study systematically reviewed how research on ML teaching and learning in K-12 has fared, including the current area of focus, and the gaps that need…
Descriptors: Elementary Secondary Education, Artificial Intelligence, Educational Research, Research Needs
Kuo, Yu-Chen; Chen, Yun-An – Education and Information Technologies, 2023
With the development of science and technology, the demand for programmers has increased. However, learning computer programs is not an easy task. It might cause a significant impact on programming if misconceptions exist at the beginning of the study. Hence, it is important to discover and correct them immediately. Chatbots are effective teaching…
Descriptors: Programming, Artificial Intelligence, Computer Science Education, Misconceptions
Liang, Jia-Cing; Hwang, Gwo-Jen; Chen, Mei-Rong Alice; Darmawansah, Darmawansah – Interactive Learning Environments, 2023
This study explores the roles and research foci of AILEd (Artificial Intelligence in Language Education). The AILEd studies published from 1990 to 2020 in the WOS (Web of Science) database were included in the present study. Based on the well-recognized Technology-based Learning Review model, several dimensions, such as research methods, research…
Descriptors: Artificial Intelligence, Technology Uses in Education, Second Language Learning, Educational Trends

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