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Laura Butler; Louise Starkey – Technology, Pedagogy and Education, 2024
Artificial intelligence (AI) will be in the future lives of children at school today. Voice-activated intelligent personal assistant devices are used in the home and could be useful in the classroom. This article explores how two groups of New Zealand children aged 7-12 engaged with Google Home devices in their classroom. Interactions recorded…
Descriptors: Audio Equipment, Computers, Technology Integration, Artificial Intelligence
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Micah Watanabe; Tracy Arner; Danielle McNamara – Reading Teacher, 2024
Students in the 3rd and 4th grade often encounter what has been called a reading "slump" when their class curriculums increasingly ask them to comprehend and learn from texts. Students are more likely to struggle if they have not been offered sufficient opportunities to build world and domain knowledge and engage in challenging…
Descriptors: Reading Instruction, Reading Strategies, Elementary School Students, Grade 3
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Luiz Rodrigues; Guilherme Guerino; Thomaz E. V. Silva; Geiser C. Challco; Lívia Oliveira; Rodolfo S. da Penha; Rafael F. Melo; Thales Vieira; Marcelo Marinho; Valmir Macario; Ig I. Bittencourt; Diego Dermeval; Seiji Isotani – International Journal of Artificial Intelligence in Education, 2025
Intelligent Tutoring Systems (ITS) possess significant potential to enhance learning outcomes. However, deploying ITSs in global south countries presents challenges due to their frequent lack of essential technological resources, such as computers and internet access. The concept of AIED Unplugged has emerged to bridge this digital divide,…
Descriptors: Teacher Attitudes, Intelligent Tutoring Systems, Numeracy, Mathematics Education
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Shih, Shu-Chuan; Chang, Chih-Chia; Kuo, Bor-Chen; Huang, Yu-Han – Education and Information Technologies, 2023
A one-on-one dialogue-based mathematics intelligent tutoring system (ITS) for learning multiplication and division of fractions was developed and evaluated in this study. This system could identify students' error types and misconceptions in real-time by using a block-based matching method. The adaptive dialogue-based instruction was supported by…
Descriptors: Mathematics Instruction, Intelligent Tutoring Systems, Multiplication, Division
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Han, Jian-Hua; Shubeck, Keith; Shi, Geng-Hu; Hu, Xiang-En; Yang, Lei; Wang, Li-Jia; Zhao, Wei; Jiang, Qiang; Biswas, Gautum – Educational Technology & Society, 2021
Intelligent learning technologies are often applied within the educational industries. While these technologies can be used to create learning experiences tailored to an individual student, they cannot address students' affect accurately and quickly during the learning process. This paper focuses on two core research questions. How do students…
Descriptors: Intelligent Tutoring Systems, Emotional Adjustment, Grade 7, Middle School Students
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Greenberg, Daphne; Miller, Christine; Graesser, Arthur C. – Adult Literacy Education, 2023
This article is written by two researchers and a teacher involved with the development and implementation of a web-based intelligent tutoring system for adults reading at elementary levels. A description of the tool is provided, followed by some of the challenges faced in designing, developing, and using the tool in adult literacy classrooms.
Descriptors: Intelligent Tutoring Systems, Adult Students, Adult Basic Education, Reading Comprehension
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Rashmi Khazanchi; Daniele Di Mitri; Hendrik Drachsler – Journal of Computers in Mathematics and Science Teaching, 2023
This quasi-experimental research study examines whether the use of Assessment and Learning in Knowledge Spaces (ALEKS), an ITS, shows a statistically significant improvement in students' mathematics achievement than traditional teacher-led instructions. This non-randomized research study measured the efficacy of ALEKS on ''underachieving students'…
Descriptors: Intelligent Tutoring Systems, Mathematics Achievement, Low Achievement, Grade 8
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Husni Almoubayyed; Stephen E. Fancsali; Steve Ritter – International Educational Data Mining Society, 2023
Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…
Descriptors: Prediction, Models, Reading Ability, Computer Software
Micah Watanabe; Tracy Arner; Danielle McNamara – Grantee Submission, 2023
David Stephens, a 4th grade teacher in Washington State, was preparing a lesson plan about desert wildlife (all names are pseudonyms). He was planning on assigning his students the chapter book, "Desert Giant: The World of the Saguaro Cactus." The students had divergent knowledge about the topic. For example, Maryam had grown up in…
Descriptors: Reading Instruction, Reading Strategies, Intelligent Tutoring Systems, Elementary School Students
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Linxuan Yi; Di Liu; Tiancheng Jiang; Yucheng Xian – International Journal of Science and Mathematics Education, 2025
Artificial intelligence (AI) shows increasing potential to improve mathematics instruction, yet integrative quantitative evidence currently is lacking on its overall effectiveness and factors influencing success. This systematic review and meta-analysis investigate the effectiveness of AI on improving mathematics performance in K-12 classrooms…
Descriptors: Program Effectiveness, Artificial Intelligence, Technology Uses in Education, Elementary School Students
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Gang Yang; Xiao-Qian Zheng; Qian Li; Miao Han; Yun-Fang Tu – Interactive Learning Environments, 2024
In Chinese, writing is a basic competency that pupils should possess. But it is still challenging for teachers to improve pupils' writing abilities. Therefore, this study proposes an intelligence-based cognitive diagnostic feedback strategy to improve pupils' writing ability and writing learning quality by analyzing their writing performance,…
Descriptors: Foreign Countries, Elementary School Students, Vocabulary Skills, Comparative Analysis
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del Olmo-Muñoz, Javier; González-Calero, José Antonio; Diago, Pascual D.; Arnau, David; Arevalillo-Herráez, Miguel – British Journal of Educational Technology, 2022
Problem solving is often regarded as one of the most essential cognitive functions in our daily lives, and, for that reason, educational theorists have long stressed the need for its development. As cognitive flexibility is a fundamental characteristic necessary throughout the problem-solving process, the purpose of this study is to analyse…
Descriptors: Problem Solving, Arithmetic, Grade 5, Grade 6
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Seongyune Choi; Yeonju Jang; Hyeoncheol Kim – Interactive Learning Environments, 2024
Intelligent Personal Assistants (IPAs) are becoming more prevalent in daily and educational contexts, increasing the possibility of using them as learning partners that can provide more personalized and learner-centric learning opportunities. However, research has primarily focused on educational advantages that IPAs may provide, overlooking…
Descriptors: Intelligent Tutoring Systems, Foreign Countries, Technology Uses in Education, Independent Study
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Elif Polat; Yunus Emre Bastug; Sinan Hopcan; Simge Cepdibi Sibiç; Nazli Ceren Isikligil – Journal of Learning and Teaching in Digital Age, 2024
This study investigates the primary school teachers' perceptions towards the Intelligent Material System (IMS), which was developed to enhance the quality of inclusive environments and support the academic skills of students with Special Educational Needs (SEN). Within this scope, IMS training was conducted with 84 classroom teachers who worked at…
Descriptors: Teacher Attitudes, Elementary School Teachers, Inclusion, Special Education
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Wan, Haipeng; Yu, Shengquan – Interactive Learning Environments, 2023
Most online learning researchers use resource recommendation and retrieve based on learning performance and learning style to provide accurate learning resources, but it is a closed and passive adaptive way. Learners always do not know the recommendation rationale and just receive the result-oriented recommended resources without having a chance…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Artificial Intelligence, Cognitive Mapping
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