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Natacha Hoareau; Céline Bagès; Alain Guerrien – International Journal of Bullying Prevention, 2023
More and more adolescents are using information and communication technologies (i.e., ITCs) in a massive and addictive way (e.g., by sending aggressive messages on social networks), driving cyberbullying trends (Fanti et al., in European Journal of Developmental Psychology, 9, 168-181, 2012). Little is known about the relationship between young…
Descriptors: Early Adolescents, Bullying, Computer Mediated Communication, Computer Use
Jamal, Bakht; Rizvi, Syed Asad Abbas – Pakistan Journal of Distance and Online Learning, 2023
This paper intended to analyze the practices of digital citizenship among university student in Pakistan. The quantitative descriptive survey research design was adopted for this study. The population of the study was 800 students of BS (Education) program in ten public sector universities in Punjab, Pakistan. Simple random sampling technique was…
Descriptors: Foreign Countries, Technological Literacy, College Students, Computer Use
Bahari, Akbar – Interactive Learning Environments, 2023
The purpose of this systematic review was three-fold: (a) to convey technology-assisted language learning (TALL) affordances that facilitate catering to the nonlinearity and dynamicity of the second language (L2) motivational factors, (b) to identify TALL challenges that inhibit the integration of educational technologies to enhance L2 motivation…
Descriptors: Affordances, Barriers, Technology Uses in Education, Second Language Learning
Parks, Rodney; Hayes, Casey; Heggie, Mary; Taylor, Alexander – College and University, 2020
Engaging students and developing interest can be challenging--and not always successful on the first couple of tries. With the help of Elon University's Information Technology team, the Office of the Registrar created a technology solution to give faculty more data about the students registered for their classes in the upcoming term. Using…
Descriptors: Computer Uses in Education, Profiles, College Students, Learner Engagement
Bolenbaugh, Mallory; Foley-Nicpon, Megan; Young, Rachel; Tully, Melissa; Grunewald, Nikki; Ramirez, Marizen – Psychology in the Schools, 2020
Cyberbullying is a major health concern for today's youth and a pervasive stressor for adolescents and their families. This study offers qualitative insights into how parents perceive their children's technology use and engagement in cyberbullying based on gender. Eight focus groups were conducted with 48 parents of adolescents ages 10-17.…
Descriptors: Parent Attitudes, Gender Differences, Computer Mediated Communication, Bullying
Harrow, Christopher; Merchant, Nurfatimah – Mathematics Teacher: Learning and Teaching PK-12, 2020
Sinusoidal functions are difficult for students: Periodicity is a new concept, transferring information from the unit circle can be confusing, and computations with multiple solutions can be overwhelming. Many struggle with both the unfamiliar "waviness" of sinusoidal graphs and their transformations (translations, dilations, and…
Descriptors: Graphs, Mathematics, Transformations (Mathematics), Computer Uses in Education
Meeken, Luke – Art Education, 2020
In teaching digital artmaking in a public high school, a regular challenge faced by students and teachers is overcoming the ways that the software and hardware systems in the lab often fail to accommodate the learning needs of all students. The perceived immutability and infallibility of digital systems and the resultant tendencies of self-blame…
Descriptors: Art Education, Computer Uses in Education, Access to Computers, Accessibility (for Disabled)
Hod, Yotam; Twersky, Daniel – International Journal of Computer-Supported Collaborative Learning, 2020
This research examines small group collaboration on the Augmented Reality (AR) Sandbox, an interactive, real-time topographical simulator that provides a color layer of augmentation showing depths and height, contour lines, and hydrology vis-a-vis the terrain of sand in a box. Prior research has focused on AR Sandbox activity designs, outcome…
Descriptors: Topography, Computer Simulation, Spatial Ability, Computer Uses in Education
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
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
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
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
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
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
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