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Tang, Jingwan; Zhou, Xiaofei; Wan, Xiaoyu; Daley, Michael; Bai, Zhen – International Journal of Artificial Intelligence in Education, 2023
The advances of machine learning (ML) in scientific discovery (SD) reveal exciting opportunities to utilize it as a cross-cutting tool for inquiry-based learning in K-12 STEM classrooms. There are, however, limited efforts on providing teachers with sufficient knowledge and skills to integrate ML into teaching. Our study addresses this gap by…
Descriptors: STEM Education, Artificial Intelligence, Elementary School Teachers, Secondary School Teachers
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Ottenbreit-Leftwich, Anne; Glazewski, Krista; Jeon, Minji; Jantaraweragul, Katie; Hmelo-Silver, Cindy E.; Scribner, Adam; Lee, Seung; Mott, Bradford; Lester, James – International Journal of Artificial Intelligence in Education, 2023
With accelerating advances in artificial intelligence, it is clear that introducing K-12 students to AI is essential for preparation to interact with and potentially develop AI technologies. To succeed as the workers, creators, and innovators of the future, we argue students should encounter core concepts of AI as early as elementary school.…
Descriptors: Elementary School Students, Grade 4, Grade 5, Artificial Intelligence
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Myers, Matthew C.; Wilson, Joshua – International Journal of Artificial Intelligence in Education, 2023
This study evaluated the construct validity of six scoring traits of an automated writing evaluation (AWE) system called "MI Write." Persuasive essays (N = 100) written by students in grades 7 and 8 were randomized at the sentence-level using a script written with Python's NLTK module. Each persuasive essay was randomized 30 times (n =…
Descriptors: Construct Validity, Automation, Writing Evaluation, Algorithms
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Touretzky, David; Gardner-McCune, Christina; Seehorn, Deborah – International Journal of Artificial Intelligence in Education, 2023
This article provides an in-depth look at how K-12 students should be introduced to Machine Learning and the knowledge and skills they will develop as a result. We begin with an overview of the AI4K12 Initiative, which is developing national guidelines for teaching AI in K-12, and briefly discuss each of the "Five Big Ideas in AI" that…
Descriptors: Electronic Learning, Artificial Intelligence, Elementary School Students, Secondary School Students
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Hou, Xinying; Nguyen, Huy Anh; Richey, J. Elizabeth; Harpstead, Erik; Hammer, Jessica; McLaren, Bruce M. – International Journal of Artificial Intelligence in Education, 2022
Digital learning games are designed to foster both student learning and enjoyment. Given this goal, an interesting research topic is whether game mechanics that promote learning and those that promote enjoyment have different effects on students' experience and learning performance. We explored these questions in "Decimal Point," a…
Descriptors: Models, Learner Engagement, Computer Games, Educational Games
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Karumbaiah, Shamya; Ocumpaugh, Jaclyn; Baker, Ryan S. – International Journal of Artificial Intelligence in Education, 2022
Educational technology (EdTech) designers need to ensure population validity as they attempt to meet the individual needs of all students. EdTech researchers often have access to larger and more diverse samples of student data to test replication across broad demographic contexts as compared to either the small-scale experiments or the larger…
Descriptors: Educational Technology, Student Diversity, Student Needs, Educational Research
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Zhang, Ningyu; Biswas, Gautam; Hutchins, Nicole – International Journal of Artificial Intelligence in Education, 2022
Strategies are an important component of self-regulated learning frameworks. However, the characterization of strategies in these frameworks is often incomplete: (1) they lack an operational definition of strategies; (2) there is limited understanding of how students develop and apply strategies; and (3) there is a dearth of systematic and…
Descriptors: Learning Strategies, Student Behavior, Educational Environment, Grade 6
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Wilson, Joshua; Huang, Yue; Palermo, Corey; Beard, Gaysha; MacArthur, Charles A. – International Journal of Artificial Intelligence in Education, 2021
This study examined a naturalistic, districtwide implementation of an automated writing evaluation (AWE) software program called "MI Write" in elementary schools. We specifically examined the degree to which aspects of MI Write were implemented, teacher and student attitudes towards MI Write, and whether MI Write usage along with other…
Descriptors: Automation, Writing Evaluation, Feedback (Response), Computer Software
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Jennifer K. Olsen; Nikol Rummel; Vincent Aleven – International Journal of Artificial Intelligence in Education, 2021
Educational technologies are often developed such that students work on specific social levels (e.g., individual, small group, whole class) at specific times. However, in the reality of the classroom, learning activities are not so cleanly divided, with transitions occurring between social levels for students at different times. To support these…
Descriptors: Individual Instruction, Small Group Instruction, Educational Technology, Elementary School Teachers
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Tärning, Betty; Silvervarg, Annika; Gulz, Agneta; Haake, Magnus – International Journal of Artificial Intelligence in Education, 2019
This study examines the effects of teachable agents' expressed self-efficacy on students. A total of 166 students, 10- to 11-years-old, used a teachable agent-based math game focusing on the base-ten number system. By means of data logging and questionnaires, the study compared the effects of high vs. low agent self-efficacy on the students'…
Descriptors: Self Efficacy, Elementary School Students, Intelligent Tutoring Systems, Mathematics Instruction
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Stevenson, Claire E. – International Journal of Artificial Intelligence in Education, 2017
This study contrasted the effects of tutoring, multiple try and no feedback on children's progression in analogy solving and examined individual differences herein. Feedback that includes additional hints or explanations leads to the greatest learning gains in adults. However, children process feedback differently from adults and effective…
Descriptors: Tutoring, Feedback (Response), Children, Short Term Memory
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Rau, M. A.; Aleven, V.; Rummel, N.; Pardos, Z. – International Journal of Artificial Intelligence in Education, 2014
Providing learners with multiple representations of learning content has been shown to enhance learning outcomes. When multiple representations are presented across consecutive problems, we have to decide in what sequence to present them. Prior research has demonstrated that interleaving "tasks types" (as opposed to blocking them) can…
Descriptors: Intelligent Tutoring Systems, Visual Aids, Mathematics, Mixed Methods Research
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Lenat, Douglas B.; Durlach, Paula J. – International Journal of Artificial Intelligence in Education, 2014
We often understand something only after we've had to teach or explain it to someone else. Learning-by-teaching (LBT) systems exploit this phenomenon by playing the role of "tutee." BELLA, our sixth-grade mathematics LBT systems, departs from other LTB systems in several ways: (1) It was built not from scratch but by very slightly…
Descriptors: Artificial Intelligence, Knowledge Level, Mathematics Instruction, Teaching Methods
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Pareto, Lena – International Journal of Artificial Intelligence in Education, 2014
In this paper we will describe a learning environment designed to foster conceptual understanding and reasoning in mathematics among younger school children. The learning environment consists of 48 2-player game variants based on a graphical model of arithmetic where the mathematical content is intrinsically interwoven with the game idea. The…
Descriptors: Concept Formation, Mathematical Concepts, Mathematics Instruction, Educational Games
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Arroyo, Ivon; Woolf, Beverly Park; Burelson, Winslow; Muldner, Kasia; Rai, Dovan; Tai, Minghui – International Journal of Artificial Intelligence in Education, 2014
This article describes research results based on multiple years of experimentation and real-world experience with an adaptive tutoring system named Wayang Outpost. The system represents a novel adaptive learning technology that has shown successful outcomes with thousands of students, and provided teachers with valuable information about students'…
Descriptors: Intelligent Tutoring Systems, Multimedia Instruction, Mathematics Instruction, Learner Engagement
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