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Opper, Isaac M. – RAND Corporation, 2020
Researchers often include covariates when they analyze the results of randomized controlled trials (RCTs), valuing the increased precision of the estimates over the potential of inducing small-sample bias when doing so. In this paper, we develop a sufficient condition which ensures that the inclusion of covariates does not induce small-sample bias…
Descriptors: Artificial Intelligence, Man Machine Systems, Educational Technology, Technology Uses in Education
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Paquette, Luc; Baker, Ryan S. – Interactive Learning Environments, 2019
Learning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of…
Descriptors: Comparative Analysis, Student Behavior, Models, Case Studies
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Sennott, Samuel C.; Akagi, Linda; Lee, Mary; Rhodes, Anthony – Topics in Language Disorders, 2019
Artificially intelligent tools have given us the capability to use technology to address ever more complex challenges. What are the capabilities, challenges, and hazards of incorporating and developing this technology for augmentative and alternative communication (AAC)? "Artificial intelligence" (AI) can be defined as the capability of…
Descriptors: Augmentative and Alternative Communication, Artificial Intelligence, Knowledge Representation, Thinking Skills
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Rosé, Carolyn P.; McLaughlin, Elizabeth A.; Liu, Ran; Koedinger, Kenneth R. – British Journal of Educational Technology, 2019
Using data to understand learning and improve education has great promise. However, the promise will not be achieved simply by AI and Machine Learning researchers developing innovative models that more accurately predict labeled data. As AI advances, modeling techniques and the models they produce are getting increasingly complex, often involving…
Descriptors: Discovery Learning, Man Machine Systems, Artificial Intelligence, Models
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Jones, Joshua – Mathematics Teacher: Learning and Teaching PK-12, 2021
Despite the importance of artificial intelligence in our daily lives, it has yet to be integrated into K-12 classrooms in a meaningful way. This article explores a lesson in which geometry students use Euclidean distance to implement a functional machine learning algorithm in Google Sheets™. The assignment requires students to apply the distance…
Descriptors: Geometry, Mathematics Instruction, Artificial Intelligence, Geometric Concepts
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Omid Noroozi; Saba Soleimani; Mohammadreza Farrokhnia; Seyyed Kazem Banihashem – International Journal of Technology in Education, 2024
Recently, ChatGPT, a cutting-edge large language model, has emerged as a powerful Generative Artificial Intelligence (GenAI) tool with the capacity to influence education. ChatGPT provides ample opportunities for learners, researchers, educators, and practitioners to achieve the intended learning outcomes in various disciplines. This special issue…
Descriptors: Artificial Intelligence, Technology Uses in Education, Teaching Methods, Educational Theories
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Hsiao-Ling Hsu; Howard Hao-Jan Chen; Andrew G. Todd – Interactive Learning Environments, 2023
With advances in technology, intelligent personal assistants (IPAs) have become available to assist users with a variety of tasks using voice commands. Because IPAs may induce dialogic interactions, researchers speculated that they may benefit second language learning, especially regarding pronunciation, listening and speaking skills. So far, very…
Descriptors: Foreign Countries, College Students, English (Second Language), Artificial Intelligence
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Yang, Zongkai; Yang, Juan; Rice, Kerry; Hung, Jui-Long; Du, Xu – IEEE Transactions on Learning Technologies, 2020
This article proposes two innovative approaches, the one-channel learning image recognition and the three-channel learning image recognition, to convert student's course involvements into images for early warning predictive analysis. Multiple experiments with 5235 students and 576 absolute/1728 relative input variables were conducted to verify…
Descriptors: Distance Education, At Risk Students, Artificial Intelligence, Man Machine Systems
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Biehler, Rolf; Fleischer, Yannik – Teaching Statistics: An International Journal for Teachers, 2021
This paper reports on progress in the development of a teaching module on machine learning with decision trees for secondary-school students, in which students use survey data about media use to predict who plays online games frequently. This context is familiar to students and provides a link between school and everyday experience. In this…
Descriptors: Secondary School Students, Artificial Intelligence, Man Machine Systems, Educational Technology
Chen, Carol – ProQuest LLC, 2021
Most Taiwanese English language learners have been exposed to traditional approaches to acquiring English as a second or foreign language. Studies demonstrate current/traditional teaching practices are not the most effective for struggling English language learners, and the rate of improvement has been limited. Therefore, this study explores…
Descriptors: Foreign Countries, Bilingual Education, Blended Learning, Intervention
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Singer, Judith D. – Journal of Research on Educational Effectiveness, 2019
The arc of quantitative educational research should not be etched in stone but should adapt and change over time. In this article, I argue that it is time for a reshaping by offering my personal view of the past, present and future of our field. Educational research--and research in the social and life sciences--is at a crossroads. There are many…
Descriptors: Educational Research, Research Methodology, Longitudinal Studies, Evaluation
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Stefan Küchemann; Steffen Steinert; Natalia Revenga; Matthias Schweinberger; Yavuz Dinc; Karina E. Avila; Jochen Kuhn – Physical Review Physics Education Research, 2023
The recent advancement of large language models presents numerous opportunities for teaching and learning. Despite widespread public debate regarding the use of large language models, empirical research on their opportunities and risks in education remains limited. In this work, we demonstrate the qualities and shortcomings of using ChatGPT 3.5…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Physics
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Leaton Gray, Sandra – London Review of Education, 2020
The introduction of artificial intelligence in education (AIED) is likely to have a profound impact on the lives of children and young people. This article explores the different types of artificial intelligence (AI) systems in common use in education, their social context and their relationship with the growth of commercial knowledge monopolies.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Privacy, Data Use
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Pelzer, Elena; Turner, Benjamin O. – Communication Teacher, 2022
With the increase in demand for online learning, machine teachers are becoming an important technology in higher education, since they are expected to improve teaching effectiveness and student learning outcomes. However, machine teachers require an aptitude for technology and are associated with high initial costs. Thus, here, we use a more basal…
Descriptors: Electronic Learning, Technology Uses in Education, Interaction, In Person Learning
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Marques, Lívia S.; Gresse von Wangenheim, Christiane; Hauck, Jean – Informatics in Education, 2020
Although Machine Learning (ML) is integrated today into various aspects of our lives, few understand the technology behind it. This presents new challenges to extend computing education early to ML concepts helping students to understand its potential and limits. Thus, in order to obtain an overview of the state of the art on teaching Machine…
Descriptors: Artificial Intelligence, Man Machine Systems, Elementary Secondary Education, Educational Technology
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