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Leonora Kaldaras; Kevin Haudek; Joseph Krajcik – International Journal of STEM Education, 2024
We discuss transforming STEM education using three aspects: learning progressions (LPs), constructed response performance assessments, and artificial intelligence (AI). Using LPs to inform instruction, curriculum, and assessment design helps foster students' ability to apply content and practices to explain phenomena, which reflects deeper science…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, STEM Education, Learning Trajectories
Curby Alexander; Liran Ma; Ze-Li Dou; Zhipeng Cai; Yan Huang – Journal of Cybersecurity Education, Research and Practice, 2024
Recent advances in Artificial Intelligence (AI) have brought society closer to the long-held dream of creating machines to help with both common and complex tasks and functions. From recommending movies to detecting disease in its earliest stages, AI has become an aspect of daily life many people accept without scrutiny. Despite its functionality…
Descriptors: Students, Teachers, Inquiry, Computer Security
Lisa A. Dieker; Rebecca Hines; Ilene Wilkins; Charles Hughes; Karyn Hawkins Scott; Shaunn Smith; Kathleen Ingraham; Kamran Ali; Tiffanie Zaugg; Sachin Shah – Journal of Special Education Preparation, 2024
The options for Artificial intelligence (AI) tools used in teacher education are increasing daily, but more is only sometimes better for teachers working in already complex classroom settings. This team discusses the increase of AI in schools and provides an example from administrators, teacher educators, and computer scientists of an AI virtual…
Descriptors: Artificial Intelligence, Elementary Schools, Preservice Teachers, Preservice Teacher Education
Venkatesh S. Amin; Padmanabha C. H. – Journal on School Educational Technology, 2024
This paper explains how to prepare students to learn faster, as learning is not directly connected to classroom teaching. Learning can happen in various forms, and hence, experiential teaching connects students well. The learning could be faster and far greater than expected. This study follows a process incorporated for betterment and advancement…
Descriptors: Best Practices, Teaching Methods, Teacher Effectiveness, Educational Quality
Boussaha, Karima; Boussouf, Raouf Amir – International Journal of Virtual and Personal Learning Environments, 2022
Several researchers studied the impact of collaboration between the learners, but few studies have been carried out on the impact of collaboration between teachers. In the previous work, the authors have studied the impact of the collaboration among the learners with a specific collaborative CEHL(K. Boussaha et al.,2015). In this work, the authors…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Coaching (Performance), Intelligent Tutoring Systems
R. Alex Smith; Erin Smith; Madeline D. Price – Intervention in School and Clinic, 2024
Mathematical writing (MW) can support students' mathematical learning and is common in mathematics assessment. However, MW is known to be particularly challenging for students with learning disabilities. While the use of model compositions of both high- and low-quality writing and the act of revision are evidence-based practices in writing…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Writing Instruction, Students with Disabilities
Ruth Li – Thresholds in Education, 2025
In this article, I introduce a collaborative annotation activity that supports students in critically examining AI-generated writing in relation to criteria including specificity and complexity. I engage students in collaboratively annotating the AI-generated essays, guiding students to identify instances in which the essays could be more…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Assisted Instruction, Writing Instruction
Andrew Potter; Joshua Wilson; Rod D. Roscoe; Tracy Arner; Danielle S. McNamara – Grantee Submission, 2023
This chapter provides an overview of research in computer-based writing instruction (CBWI). CBWI may entail any type of writing instruction with computers and may refer specifically to technologies that provide computer-generated feedback and instruction. The purpose of CBWI is to support students in improving their written products and writing…
Descriptors: Computer Assisted Instruction, Writing Instruction, Feedback (Response), Writing Improvement
Seren, Mehmet; Ozcan, Zeynel Ersin – International Journal of Curriculum and Instruction, 2021
The concept of distance education has become even more substantial in the days when humanity is having difficult times with pandemic. Besides, there is an idea that education will have transformed when the life after pandemic starts. Aim of this research is to discuss artificial intelligence-supported or artificial intelligence-based education,…
Descriptors: COVID-19, Pandemics, Distance Education, Artificial Intelligence
Kolchenko, Vasiliy – HAPS Educator, 2018
Artificial intelligence (AI) is transforming many fields, including education. Can modern AI replace teachers? We discuss some popular AI applications for adaptive learning, how they are related to personalized education, what makes these applications "intelligent," and how the quality and quantity of student-generated data changes the…
Descriptors: Artificial Intelligence, Individualized Instruction, Computer Assisted Instruction, Student Reaction
Sreenivasulu Reddy Mogali; Olivia Ng; Jia Xin Tan; Thu Htet San; Kian Bee Ng – Anatomical Sciences Education, 2024
The COVID-19 pandemic revealed the pivotal role of digital learning and online lecture videos, leading a shift toward blended and flipped classrooms in the post-pandemic era. This shift calls for development and (or) refreshment of novel online educational resources, such as Voice-Over PowerPoint (VOPPT) presentations, specifically designed for…
Descriptors: Undergraduate Students, Medical Students, Medical Education, Anatomy
Baosen Zhang; Ariana Frkonja-Kuczin; Zhong-Hui Duan; Aliaksei Boika – Journal of Chemical Education, 2023
Computer vision (CV) is a subfield of artificial intelligence (AI) that trains computers to understand our visual world based on digital images. There are many successful applications of CV including face and hand gesture detection, weather recording, smart farming, and self-driving cars. Recent advances in computer vision with machine learning…
Descriptors: Classification, Laboratory Equipment, Visual Aids, Optics
Johann Engelbrecht; Marcelo C. Borba – ZDM: Mathematics Education, 2024
In this paper we review selected significant developments in the use of digital technology in the teaching and learning of mathematics over the last five years. We focus on a number of important topics in this field, including the evolvement of STEAM and critical making as well as the process of redefining learning spaces in the transformation of…
Descriptors: STEM Education, Art Education, COVID-19, Pandemics
Rogerson-Revell, Pamela M. – RELC Journal: A Journal of Language Teaching and Research, 2021
This viewpoint essay considers the current status of computer-assisted pronunciation training (CAPT) before examining some of the current issues and future directions in the field. The underlying premise is the pedagogic potential of CAPT systems and resources for teaching and learning, and the need for greater synergy between technological design…
Descriptors: Computer Assisted Instruction, Pronunciation Instruction, Individualized Instruction, Feedback (Response)
Satar, Müge – Research-publishing.net, 2021
This piece explores technologies for freer communication "with" machines, i.e. bots (chatbots or conversational agents), rather than the concept of speaking "to" machines, such as Intelligent Assistants (IA) like "Alexa." Bots are computer programmes which simulate natural intelligent communication using text or…
Descriptors: Teaching Methods, Learning Processes, Second Language Learning, Second Language Instruction