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A. Corinne Huggins-Manley; Brandon M. Booth; Sidney K. D'Mello – Grantee Submission, 2022
The field of educational measurement places validity and fairness as central concepts of assessment quality (AERA, APA, NCME, 2014). Prior research has proposed embedding fairness arguments within argument-based validity processes, particularly when fairness is conceived as comparability in assessment properties across groups (Chapelle, 2021; Xi,…
Descriptors: Educational Assessment, Persuasive Discourse, Validity, Artificial Intelligence
Suarez, Susan R. – ProQuest LLC, 2022
This action research study's primary purpose was to explore student and instructor experiences of chatbot use in online and hybrid undergraduate English composition courses. This qualitative study used structured and open-ended survey questions, interviews, and chat transcripts to collect data. The collaboration process among researcher and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Electronic Learning
Vladan Devedžic; Sonja D. Radenkovic; Mirjana Devedžic – International Association for Development of the Information Society, 2022
The paper presents ideas and initiatives from two ongoing Erasmus+ projects funded by the European Commission. Both projects use e-Learning as an enabler for communicating interesting and important learning contents that are believed to increase and improve employability prospects for the targeted groups of learners. The WINnovators project…
Descriptors: Employment Potential, Electronic Learning, Foreign Countries, STEM Education
Kyriakos Kouveliotis; Maryam Mansuri – International Association for Development of the Information Society, 2022
The world is changing at an incredible rate, and different processes are using technology more and more every day. One of the most widely used applications of artificial intelligence today is to simplify employee tasks and office automation. In the future, robots can, like an author, produce articles or create conferences and instructional videos.…
Descriptors: Artificial Intelligence, Electronic Learning, Technology Uses in Education, COVID-19
Genady Grabarnik; Luiza Kim-Tyan; Serge Yaskolko – International Association for Development of the Information Society, 2022
Any advanced class in Science, Technology, Engineering, and Mathematics fields requires prerequisite knowledge. Typically, different students will have different levels of knowledge in these prerequisite areas. A prerequisite (Linear Algebra for Machine Learning course) was implemented as an interactive online course using Jupyter Notebooks and…
Descriptors: STEM Education, Knowledge Level, Artificial Intelligence, Algebra
A. Corinne Huggins-Manley; Brandon M. Booth; Sidney K. D'Mello – Journal of Educational Measurement, 2022
The field of educational measurement places validity and fairness as central concepts of assessment quality. Prior research has proposed embedding fairness arguments within argument-based validity processes, particularly when fairness is conceived as comparability in assessment properties across groups. However, we argue that a more flexible…
Descriptors: Educational Assessment, Persuasive Discourse, Validity, Artificial Intelligence
Mallory L. Dobias; Michael B. Sugarman; Michael C. Mullarkey; Jessica L. Schleider – Administration and Policy in Mental Health and Mental Health Services Research, 2022
A large proportion of adolescents experiencing depression never access treatment. To increase access to effective mental health care, it is critical to understand factors associated with increased versus decreased odds of adolescent treatment access. This study used individual depression symptoms and sociodemographic variables to predict…
Descriptors: Adolescents, Depression (Psychology), Access to Health Care, Mental Health
Okan Bulut; Tarid Wongvorachan – OTESSA Conference Proceedings, 2022
Feedback is an essential part of the educational assessment that improves student learning. As education changes with the advancement of technology, educational assessment has also adapted to the advent of Artificial Intelligence (AI). Despite the increasing use of online assessments during the last decade, a limited number of studies have…
Descriptors: Feedback (Response), Artificial Intelligence, Technology Uses in Education, Natural Language Processing
European Union, 2025
The Digital Education Accelerator supported 21 digital education solutions over three years, providing structured guidance, expert mentorship, testing, showcasing, and validation opportunities. As part of the European Digital Education Hub, the programme aimed to foster innovation by helping teams refine their solutions, scale their impact, and…
Descriptors: Educational Innovation, Preschool Education, Elementary Secondary Education, Career and Technical Education
Namsoo Shin; Kevin Haudek; Joseph Krajcik – Community for Advancing Discovery Research in Education (CADRE), 2025
In this brief, authors Namsoo Shin, Kevin Haudek, and Joseph Krajcik explore how artificial intelligence (AI) can serve as a transformative learning partner in K-12 STEM education. They describe theoretical foundations of using AI in STEM education and the importance of fostering an integrated understanding of STEM content. The brief examines AI's…
Descriptors: Artificial Intelligence, STEM Education, Computer Uses in Education, Elementary Secondary Education
Xin Gong; Zhixia Li; Ailing Qiao – Education and Information Technologies, 2025
Feedback is crucial during programming problem solving, but context often lacks critical and difference. Generative artificial intelligence dialogic feedback (GenAIDF) has the potential to enhance learners' experience through dialogue, but its effectiveness remains sufficiently underexplored in empirical research. This study employed a rigorous…
Descriptors: Artificial Intelligence, Technology Uses in Education, Dialogs (Language), Feedback (Response)
Luciana Oliveira; Célia Tavares; Artur Strzelecki; Manuel Silva – Electronic Journal of e-Learning, 2025
As generative artificial intelligence tools like ChatGPT become increasingly integrated into educational environments, understanding their impact on critical thinking is crucial. Despite growing concerns about AI's potential to diminish students' independent reasoning, there is a lack of research tools specifically designed to evaluate students'…
Descriptors: Critical Thinking, Artificial Intelligence, Computer Software, Technology Integration
Christine Wusylko; Pavlo Antonenko; Brian Abramowitz; Jeremy Waisome; Victor Perez; Stephanie Killingsworth; Bruce MacFadden – Journal of Technology and Teacher Education, 2025
As artificial intelligence (AI) is rapidly being adopted and used in society, it is imperative that teachers feel supported to integrate AI and computer science (CS) into their coursework. To help support teachers to integrate CS and AI into their instruction, we designed and developed an innovative AI curriculum, Shark AI, for in-service science…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Technology Integration
Peer reviewedDevika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
OECD Publishing, 2025
The OECD Learning Compass offers a forward-looking framework to help students navigate an increasingly complex and fast-changing world. It highlights the importance of student agency, well-being, and the development of key competencies for shaping both personal and collective futures. However, for students to truly benefit from this vision,…
Descriptors: Teachers, Change Agents, Educational Change, Curriculum Development

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