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John Ross – Region 8 Comprehensive Center, 2024
Artificial intelligence (AI) has been making considerable inroads into everyday lives, and AI applications and resources can be found in homes, businesses, entertainment venues, and--of course--in schools. The rapid rate at which AI is being integrated into education and placed in the hands of students, teachers, and other staff has prompted a…
Descriptors: Artificial Intelligence, Elementary Schools, Middle Schools, High Schools
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Saha, Sujan Kumar; Rao C. H., Dhawaleswar – Interactive Learning Environments, 2022
Assessment plays an important role in education. Recently proposed machine learning-based systems for answer grading demand a large training data which is not available in many application areas. Creation of sufficient training data is costly and time-consuming. As a result, automatic long answer grading is still a challenge. In this paper, we…
Descriptors: Middle School Students, Grading, Artificial Intelligence, Automation
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Anna Trifonova; Mariela Destéfano; Mario Barajas – Digital Education Review, 2024
This article proposes a comprehensive AI curriculum tailored for young learners aged 11 to 14, emphasizing a humanistic approach. We review other AI curricula proposals for children and young people and underline that they focus primarily on AI's technological benefits and on learning coding and logic. Our curriculum explores human cognition that…
Descriptors: Artificial Intelligence, Cognitive Processes, Children, Constructivism (Learning)
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Cathal Doyle; Stephen Ross; Cathy Buntting; Matt Boucher; Tanya Kotzé – set: Research Information for Teachers, 2023
This article reports on a case study from a larger project exploring ways in which online citizen science projects can enhance students' learning in science and in digital technology. In this case, two teachers integrated the digital technology curriculum with the science capability "interpreting representations" using the engaging…
Descriptors: Foreign Countries, Science Education, Grade 6, Grade 7
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Liu, Ruitao; Tan, Aixin – Journal of Educational Data Mining, 2020
In this paper, we describe our solution to predict student STEM career choices during the 2017 ASSISTments Datamining Competition. We built a machine learning system that automatically reformats the data set, generates new features and prunes redundant ones, and performs model and feature selection. We designed the system to automatically find a…
Descriptors: Career Choice, Prediction, Automation, Artificial Intelligence
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Le, Huixiao; Jia, Jiyou – Interactive Technology and Smart Education, 2022
Purpose: In intelligent tutoring systems (ITS), learners were often granted limited authority and are forced to obey the decision of the system which might not satisfy their needs. Failure to grant learners sufficient autonomy could yield unexpected effects that hinder learning, including undermining learners' motivation, priming learners'…
Descriptors: Intelligent Tutoring Systems, Design, Program Implementation, Personal Autonomy
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Juho Kahila; Henriikka Vartiainen; Matti Tedre; Eetu Arkko; Anssi Lin; Nicolas Pope; Ilkka Jormanainen; Teemu Valtonen – Informatics in Education, 2024
The integration of artificial intelligence (AI) topics into K-12 school curricula is a relatively new but crucial challenge faced by education systems worldwide. Attempts to address this challenge are hindered by a serious lack of curriculum materials and tools to aid teachers in teaching AI. This article introduces the theoretical foundations and…
Descriptors: Personal Autonomy, Data, Children, Creativity
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Heffernan, Neil T.; Heffernan, Cristina Lindquist – International Journal of Artificial Intelligence in Education, 2014
The ASSISTments project is an ecosystem of a few hundred teachers, a platform, and researchers working together. Development professionals help train teachers and get teachers to participate in studies. The platform and these teachers help researchers (sometimes explicitly and sometimes implicitly) simply by using content the teacher selects. The…
Descriptors: Intelligent Tutoring Systems, Educational Research, Formative Evaluation, Artificial Intelligence