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Noyes, Keenan; McKay, Robert L.; Neumann, Matthew; Haudek, Kevin C.; Cooper, Melanie M. – Journal of Chemical Education, 2020
Computer-assisted analysis of students' written responses to questions is becoming a possibility due to developments in technology. This could make such constructed response questions more feasible for use in large classrooms where multiple choice assessments are often considered a more practical option. In this study, we use a previously…
Descriptors: Automation, Artificial Intelligence, Computer Uses in Education, Classification
Cole, Brian S.; Lima-Walton, Elia; Brunnert, Kim; Vesey, Winona Burt; Raha, Kaushik – Journal of Applied Testing Technology, 2020
Automatic item generation can rapidly generate large volumes of exam items, but this creates challenges for assembly of exams which aim to include syntactically diverse items. First, we demonstrate a diminishing marginal syntactic return for automatic item generation using a saturation detection approach. This analysis can help users of automatic…
Descriptors: Artificial Intelligence, Automation, Test Construction, Test Items
Zhang, Lian; Weitlauf, Amy S.; Amat, Ashwaq Zaini; Swanson, Amy; Warren, Zachary E.; Sarkar, Nilanjan – Journal of Autism and Developmental Disorders, 2020
Existing literature regarding social communication outcomes of interventions in autism spectrum disorder (ASD) depends upon human raters, with limited generalizability to real world settings. Technological innovation, particularly virtual reality (VR) and collaborative virtual environments (CVE), could offer a replicable, low cost measurement…
Descriptors: Interpersonal Communication, Cooperation, Autism, Pervasive Developmental Disorders
Yang, Xi; Zhou, Guojing; Taub, Michelle; Azevedo, Roger; Chi, Min – International Educational Data Mining Society, 2020
In the learning sciences, heterogeneity among students usually leads to different learning strategies or patterns and may require different types of instructional interventions. Therefore, it is important to investigate student subtyping, which is to group students into subtypes based on their learning patterns. Subtyping from complex student…
Descriptors: Grouping (Instructional Purposes), Learning Strategies, Artificial Intelligence, Learning Analytics
Kashyap, Ramgopal, Ed.; Kumar, A. V. Senthil, Ed. – IGI Global, 2020
Machine learning allows for non-conventional and productive answers for issues within various fields, including problems related to visually perceptive computers. Applying these strategies and algorithms to the area of computer vision allows for higher achievement in tasks such as spatial recognition, big data collection, and image processing.…
Descriptors: Artificial Intelligence, Man Machine Systems, Video Technology, Computer Uses in Education
Doug Ward; Heidi G. Loshbaugh; Alison L. Gibbs; Tim Henkel; Greg Siering; Jim Williamson; Mark Kayser – Change: The Magazine of Higher Learning, 2024
In this article, the authors posit that generative artificial intelligence offers universities an opportunity to make long-needed structural changes in teaching and learning. Given the complexities of generative AI, faculty need time and resources to learn to use it effectively and to adapt classes in ways that help students approach AI ethically…
Descriptors: Artificial Intelligence, Faculty, Digital Literacy, Ethics
Region 17 Comprehensive Center, 2024
Goals and policy related to artificial intelligence (AI) will focus on improving learning for each learner. State Education Agencies (SEAs) must determine how to begin the journey to this outcome. The steps in this report outline in depth the first steps SEAs can take to begin development of an AI-related vision and strategic objectives that will…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Educational Policy
Oscar Yecid Aparicio-Gómez; Olga Lucia Ostos-Ortiz; Constanza Abadía-García – Journal of Technology and Science Education, 2024
In today's educational environment, the convergence of emerging technologies and active methodologies has become a fundamental driver of change in university education. Emerging technologies, such as artificial intelligence, virtual reality, machine learning, and data analytics, are redefining the dynamics of higher education. Active…
Descriptors: Technological Advancement, Technology Uses in Education, Higher Education, Problem Based Learning
Patric R. Spence; Renee Kaufmann; Kenneth A. Lachlan; Xialing Lin; Stephen A. Spates – Communication Education, 2024
As technologies such as artificial intelligence (AI) and other forms of machine communication become more popular and readily available, the opportunities for use in an online class increase. This replication and extension sought to understand and test the use of AI versus human communication in an online learning space--specifically the learning…
Descriptors: Online Courses, Artificial Intelligence, Technology Uses in Education, Electronic Learning
Dan Sun; Azzeddine Boudouaia; Chengcong Zhu; Yan Li – International Journal of Educational Technology in Higher Education, 2024
ChatGPT, an AI-based chatbot with automatic code generation abilities, has shown its promise in improving the quality of programming education by providing learners with opportunities to better understand the principles of programming. However, limited empirical studies have explored the impact of ChatGPT on learners' programming processes. This…
Descriptors: Computer Science Education, Computer Software, Feedback (Response), Artificial Intelligence
S.J. Shi; J.W. Li; R. Zhang – Asia Pacific Journal of Education, 2024
The rapid advancement of Generative Artificial Intelligence Technology has increasingly drawn attention to its potential applications in the educational sector. This study aims to investigate the effects of Situational Interactive Teaching, facilitated by generative artificial intelligence, on students' learning outcomes and flow experiences. A…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, Teaching Methods
Weipeng Yang; Xinyun Hu; Ibrahim H. Yeter; Jiahong Su; Yuqin Yang; John Chi-Kin Lee – Journal of Computer Assisted Learning, 2024
Background: Artificial Intelligence (AI) literacy is a crucial part of digital literacy that all individuals should possess in today's technologically advanced world. Despite the potential benefits that AI education offers, little research has been done on how to teach AI literacy to children. Objectives: This study aimed to fill that gap by…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Digital Literacy
Guan-Yu Lin; Ciao-Chun Jhang; Yi-Shun Wang – Education and Information Technologies, 2024
The use of AI-based social robots has been shown to be beneficial for learning English as a Second Language (ESL). Not much is known, however, about the drivers of parental intention to use those robots in support of their children's ESL learning. This study aims to explore the factors that drive parental intention to adopt AI-based social robots…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
Andie Tangonan Capinding; Franklin Tubeje Dumayas – Problems of Education in the 21st Century, 2024
Artificial Intelligence (AI) has become a transformative force in education, significantly influencing students. This research explores AI's impact on learning experiences, academic performance, career guidance, motivation, self-reliance, social interaction, and AI dependency. Utilizing a descriptive-comparative design, 194 student respondents…
Descriptors: Transformative Learning, Teaching Methods, Artificial Intelligence, Influence of Technology
Zeynep Turan; Rabia Meryem Yilmaz – Journal of Engineering Education, 2024
Background: Massive open online courses (MOOCs) have gained popularity as a form of distance education, highlighting the need for additional research. Various studies have systematically examined scholarly research on MOOCs. However, the reviewed academic publications on the use of MOOCs in engineering education are limited.…
Descriptors: MOOCs, Engineering Education, Distance Education, Program Implementation

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