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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
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Pezold, Mollee J.; Imgrund, Caitlin M.; Storkel, Holly L. – Language, Speech, and Hearing Services in Schools, 2020
Purpose: Although language sample analysis is widely recommended for assessing children's expressive language, few school-based speech-language pathologists routinely use it, citing a lack of time, resources, and training (Pavelko, Owens, Ireland, & Hahs-Vaughn, 2016). The purpose of this clinical tutorial is (a) to describe options for…
Descriptors: Computer Use, Preschool Children, Child Language, Language Usage
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Bassi, Merfat – Art Education, 2020
Recently, many studies have discussed the importance of meditation and artmaking in the art classroom (Ganley, 2017; Kohler, 2012; Patterson, 2015; Phillips, 2016; Rohloff, 2008). The practice of meditation and artmaking not only promotes the physical health of the body but also develops the inner attitude of self and identity. Often artmaking and…
Descriptors: Art Activities, Metacognition, Computer Software, Art Education
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Zhao, Siqian; Wang, Chunpai; Sahebi, Shaghayegh – International Educational Data Mining Society, 2020
Students acquire knowledge as they interact with a variety of learning materials, such as video lectures, problems, and discussions. Modeling student knowledge at each point during their learning period and understanding the contribution of each learning material to student knowledge are essential for detecting students' knowledge gaps and…
Descriptors: Learning, Knowledge Level, Models, Instructional Materials
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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
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Lloyd P. Rieber – International Journal of Designs for Learning, 2020
Q methodology provides a unique mixed-methods means of examining subjectivity through the use of an activity called a Q sort in which participants must sort a list of given items within a predetermined sorting form. Although Q methodology has a long history as a research tool, its use as an instructional tool has not been extensively explored.…
Descriptors: Q Methodology, Computer Software, Instructional Design, Teaching Methods
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Idit Adler; Scott Warren; Cathleen Norris; Elliot Soloway – Smart Learning Environments, 2025
Smart learning environments provide students with opportunities to engage in self-regulated learning (SRL). However, little research has examined how teachers leverage these opportunities. We employed a multiple-case study methodology to examine the SRL supporting instructional practices of five third-grade teachers as they implemented a science…
Descriptors: Elementary School Students, Elementary School Teachers, Grade 3, Independent Study
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Seyma Türen; Pinar Bagçeli Kahraman – Education and Information Technologies, 2025
The increasing prevalence of digital technologies has notably expanded children's accessibility to a diverse range of digital tools day by day. Consequently, this evolution has significantly influenced the gaming landscape, propelling the surge in popularity of digital games among children. This change has also led to the need for changes in the…
Descriptors: Predictor Variables, Preschool Children, Video Games, Computer Games
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Martinez, Brianna L.; Sweeder, Ryan D.; VandenPlas, Jessica R.; Herrington, Deborah G. – International Journal of STEM Education, 2021
Background: Engagement with particle-level simulations can help students visualize the motion and interactions of gas particles, thus helping them develop a more scientifically accurate mental model. Such engagement outside of class prior to formal instruction can help meet the needs of students from diverse backgrounds and provide instructors…
Descriptors: Chemistry, Scientific Concepts, Simulation, Visualization
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Byron, Justin; Sanetti, Lisa M. Hagermoser; Charbonneau, Sarah – International Journal of School & Educational Psychology, 2021
Available data indicate educators struggle to implement interventions consistently across time, which negatively impacts student outcomes. Implementation strategies have been developed to improve treatment fidelity, but many require time and staffing demands that can be unfeasible in practice. The primary purpose of this study was to extend the…
Descriptors: Fidelity, Intervention, Program Implementation, Planning
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Boussaha, Karima; Mokhati, Farid; Hanneche, Amira – International Journal of Web-Based Learning and Teaching Technologies, 2021
This article introduces a new learner's self-assessment environment as CEHL that allows comparison of learners' programs with those elaborated by the teacher. The subjacent idea is to indirectly compare programs through their graphical representations described by ontologies. So, CEHL developed so-called S_Onto_ALPPWA which allows comparing…
Descriptors: Self Evaluation (Individuals), Programming, Computer Uses in Education, Comparative Analysis
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Chang, Yu-Shan – British Journal of Educational Technology, 2021
This study explored the effects of virtual reality (VR) application on the process and outcome of skill learning. The participants consisted of 60 new employees in the customer network cable service division of a telecommunications company, and the study focused on the learning of optical-fibre fusion splicing skills. The skill-learning test…
Descriptors: Computer Simulation, Skill Development, Job Training, Job Skills
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Kaminska, Dorota; Zwolinski, Grzegorz; Wiak, Slawomir; Petkovska, Lidija; Cvetkovski, Goga; Barba, Paolo Di; Mognaschi, Maria Evelina; Haamer, Rain Eric; Anbarjafari, Gholamreza – Technology, Knowledge and Learning, 2021
This paper introduces, explains and illustrates real-life application of virtual training tool for electrical engineering education. The tool gives users the opportunity to interact with and manipulate 3D models of authentic devices. The users have a possibility to compare structural differences between devices, assemble and disassemble the…
Descriptors: Computer Simulation, Computer Uses in Education, Engineering Education, Electronics
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Runyon, David; Steffy, Christina J. – New Review of Academic Librarianship, 2021
COVID-19 did not disrupt higher education; it hastened the disruptions that have already been taking place. One particularly prominent disruption is the digital shift, or the move from primarily face-to-face operations to operations with a large digital component. In order to survive, higher education needs to fundamentally change. But how…
Descriptors: Academic Libraries, Computer Uses in Education, Educational Trends, Higher Education
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An, Jiwoo; Holme, Thomas A. – Journal of Chemical Education, 2021
Incorporation of previously reported AR technology (ARiEL) for a general chemistry laboratory was attempted for the second time, a replication effort designed to provide students with an option to read about the nature of instruments used in an experiment. Students' app usage was tracked to understand the type and amount of information accessed,…
Descriptors: Computer Simulation, Computer Uses in Education, Chemistry, Science Instruction
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