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Peer reviewed
Download full textEyüp Yurt – International Society for Technology, Education, and Science, 2024
This study examines teachers' motivations for using artificial intelligence (AI) applications in education from the perspective of Expectancy-Value Theory. The Expectancy-Value Theory is a framework used to explain the key factors that influence individuals' motivation to perform a specific task. In this study, the two main components of the…
Descriptors: Teacher Attitudes, Teacher Motivation, Artificial Intelligence, Computer Software
Direct linkPolicy and Global Affairs, Contributor; Health and Medicine Division, Contributor; Division of Behavioral and Social Sciences and Education, Contributor; Science and Technology for Sustainability Program, Contributor; Board on Health Care Services, Contributor; Board on Science Education, Contributor; Franklin Carrero-Martínez, Rapporteur; Jennifer Saunders, Rapporteur; Emi Kameyama, Rapporteur – National Academies Press, 2024
The pandemic and overlapping global crises, including climate change, have increased attention to the importance of mental health and well-being as foundational for humans. Similarly, COVID-19 significantly exacerbated gaps in education, leaving children one to three years behind. Artificial intelligence (AI) has demonstrated potential to be…
Descriptors: Artificial Intelligence, Technology Uses in Education, Sustainability, Pandemics
Julia K. VanderMolen; Courtney Ward-Sutton – Rehabilitation Research, Policy, and Education, 2024
Background: An employer's attitude is essential in the workplace. It is often associated with hiring behaviors, in addition to their required awareness and knowledge of providing reasonable assistive technology (AT) and workplace accommodations (WA) for persons with disabilities (PwDs). Objective: The study aimed to draw out knowledge and feedback…
Descriptors: Human Resources, Personnel Management, Assistive Technology, Accessibility (for Disabled)
Ying Zhang; Yan Zhang; Wei Xu; Zhifeng Wang; Jianwen Sun – International Educational Data Mining Society, 2024
Knowledge tracing (KT) aims to model a learner's knowledge mastery level through his historical exercise records to predict future learning performance. Using this technology, learners can get appropriate customized exercises based on their current knowledge states, and thus the great potential of personalized teaching services such as intelligent…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Knowledge Level, Music Education
Matthew S. Taylor; Eileen M. Glavey – Journal of Special Education Technology, 2024
Science, technology, engineering, and mathematics (STEM) curriculum and learning activities may help students learn social-emotional learning (SEL) competencies needed to support independence and community living, as well as 21st-century career development skills. Including robotics and coding curriculum in elementary classrooms can offer all…
Descriptors: Robotics, Coding, Social Emotional Learning, Autism Spectrum Disorders
Yuya Asano; Diane Litman; Quentin King-Shepard; Tristan Maidment; Tyree Langley; Teresa Davison – International Educational Data Mining Society, 2024
One of the keys to the success of collaborative learning is balanced participation by all learners, but this does not always happen naturally. Pedagogical robots have the potential to facilitate balance. However, it remains unclear what participation balance robots should aim at; various metrics have been proposed, but it is still an open question…
Descriptors: Cooperative Learning, Tutoring, Artificial Intelligence, Interpersonal Relationship
Gökçe, Semirhan; Güner, Pinar – Education and Information Technologies, 2022
The purpose of this study was to investigate the trends of GeoGebra related studies. We focused on the articles published between 2009 and 2021 and existed in Web of Science database. The bibliometric analysis of the GeoGebra related articles exposed four-clustered structure according to the degree of relationships among terms that reflect the…
Descriptors: Educational Technology, Mathematics Education, Use Studies, Bibliometrics
Klein, Christian – International Journal of Technology in Education and Science, 2022
In the chemical industry, a new generation of decision-makers is emerging in the next 5 to 10 years with a higher affinity for the use of videos to find information and to connect with other individuals. Through the digital transformation, an "on-demand" culture has become usual. As individuals want to access information at any time, B2B…
Descriptors: Chemistry, Industry, Access to Information, Video Technology
Rice, Margaret L.; Beavers, Bernadette; McNeill, Laura; Benson, Angela – TechTrends: Linking Research and Practice to Improve Learning, 2022
The purpose of this qualitative study was to gain in-depth understanding of students' experiences in a cohort-based hybrid instructional technology Ph.D. program at a Research 1 University. Participants were 14 current and former students in the Instructional Technology Ph.D. program from the 2016 through 2020 cohorts. Participants completed an…
Descriptors: Grouping (Instructional Purposes), Blended Learning, Educational Technology, Doctoral Students
Pata, Kai; Tammets, Kairit; Väljataga, Terje; Kori, Külli; Laanpere, Mart; Rõbtsenkov, Romil – Technology, Knowledge and Learning, 2022
This study explores schools' digital maturity self-evaluation reports' data from Estonia. Based on quantitative data (N = 499) the schools that attempt digital transformation were clustered into three successive digital improvement types. The paper describes 3 main patterns of school improvement in different phases of innovative change: classroom…
Descriptors: Educational Improvement, Educational Innovation, Technology Uses in Education, Foreign Countries
Okanda, Mako; Taniguchi, Kosuke – Infant and Child Development, 2022
The present study investigated whether Japanese 3-, 4-, and 5-year-old children exhibit a yes bias to questions from a physically present humanoid robot, Nao. The robot asked the children yes-no questions about familiar and unfamiliar objects. To both types of questions, the 3-year-old children exhibited a yes bias while the 5-year-old children…
Descriptors: Preschool Children, Bias, Robotics, Responses
Bos, Rogier; Doorman, Michiel; Drijvers, Paul; Shvarts, Anna – Teaching Mathematics and Its Applications, 2022
We study the augmented reality sandbox (ARSB) as an embodied learning environment to foster meaning making in the context of bivariable calculus. We present the case of Tiago, a first-year bachelor chemistry student, performing a series of tasks based on embodied design, including perception-based, action-based and incorporation-based tasks.…
Descriptors: Computer Simulation, Calculus, Mathematical Concepts, Thinking Skills
Shaw, Alicia; Hux, Annette; Covey, Nicole – International Journal on E-Learning, 2022
The purpose of this quantitative study was to examine the preferences and practices of students enrolled in online graduate programs regarding instructional video or visual tools used by instructors. Graduate students enrolled in online courses were surveyed to determine their perceptions of the best and worst instructional video or visual tools…
Descriptors: Graduate Students, Student Attitudes, Electronic Learning, Video Technology
Chiu, Thomas K. F. – Educational Technology Research and Development, 2022
Teacher technology integration research on persistence is needed. Teachers' persistence is strongly associated with their autonomous motivation, as defined by self-determination theory (SDT); however, most SDT-based studies have focused on teachers' support and students' motivation and well-being. SDT founders also recently suggested that future…
Descriptors: Technology Integration, Self Determination, Persistence, Professional Autonomy
Salehudin, Imam; Alpert, Frank – Education & Training, 2022
Purpose: This study analyzed segment differences of student preference for video use in lecture classes and university use of video lecture classes. The authors then conducted novel gap analyses to identify gaps between student segments' preferences for videos versus their level of exposure to in-class videos. Multivariate analysis of variance…
Descriptors: Preferences, Video Technology, Class Activities, College Students
