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Hans Humenberger – Teaching Statistics: An International Journal for Teachers, 2025
In the last years special "ovals" appear increasingly often in diagrams and applets for discussing crucial items of statistical inference (when dealing with confidence intervals for an unknown probability p; approximation of the binomial distribution by the normal distribution; especially in German literature, see e.g. [Meyer,…
Descriptors: Computer Oriented Programs, Prediction, Intervals, Statistical Inference
Jennifer Billinson – New Directions for Student Leadership, 2025
This article analyzes how TikTok can be situated as a space for learning and analyzing critical leadership skills in the classroom and beyond. While the platform has earned criticism from a variety of angles (including fears over media effects and the pervasiveness of the algorithm), I argue the popularity of the app positions it as one of the…
Descriptors: Leadership Training, Social Media, Leadership Qualities, Computer Oriented Programs
Peer reviewedIshrat Ahmed; Paul Alvarado; Siddharth Jain; Tracy Arner; Elizabeth Reilley; Danielle S. McNamara – Grantee Submission, 2025
The rapid evolution of artificial intelligence (AI) has created an unprecedented opportunity for innovation across industries, but its complexity often presents a steep learning curve for many (Roberts & Candi, 2024; Gunner, 2025). This highlights the need for user-friendly tools that bridge the gap between AI's potential and its practical…
Descriptors: State Universities, Artificial Intelligence, Usability, Innovation
Michael C. Robbins; Zhuping Li – Field Methods, 2025
The Nolan Index (NI) is a normed, quantitative measure for comparing the degree of resemblance (similarity or dissimilarity) between free listings with an Excel program for calculating it. This article enhances that effort with the addition of an R program and additional applications. Free-list resemblance measures have been used to investigate…
Descriptors: Computation, Norm Referenced Tests, Comparative Analysis, Spreadsheets
Jack Thomas-Colwell; Ramya S. Pathuri; Aaron H. Shoemaker; Michael G. Hill; Bryan M. Hunter – Journal of Chemical Education, 2025
The study of coordination complexes in general and inorganic chemistry courses is facilitated by theoretical frameworks such as crystal field theory (CFT) and ligand field theory (LFT). The angular overlap model (AOM) is alternative approach that quantifies metal-ligand interactions based on the geometric configuration of a given complex. In this…
Descriptors: Computer Oriented Programs, Organic Chemistry, Inorganic Chemistry, Scientific Concepts
Billur Aksoy; Lester R. Lusher; Scott E. Carrell – National Bureau of Economic Research, 2025
Phone usage in the classroom has been linked to worsened academic outcomes. We present findings from a field experiment conducted at a large public university in partnership with an app marketed as a soft commitment device that provides incentives to reduce phone use in the classroom. We find that app usage led to improvements in classroom focus,…
Descriptors: Attention Control, Telecommunications, Handheld Devices, Universities
Justin Zumwalt; Ashley Keener – Discover Education, 2025
The first two years of undergraduate medical education include foundational science and clinical training such as accurately interpreting electrocardiograms (ECGs). ECG education is traditionally delivered via lecture-based presentations in a formal classroom setting. However, students are increasingly finding mobile apps to be instructive to use…
Descriptors: Undergraduate Students, Medical Students, Medical Education, Computer Oriented Programs
Yuting Mu; Yuqi Gao; Yanmin Zhao – International Journal on E-Learning, 2025
With the increasing use of mobile applications for educational purposes among university students, enhancing the efficiency of mobile instruction and learning is a key concern in higher education. It is, therefore, necessary to explore students' mobile learning habits and to identify the factors that influence their mobile learning to further…
Descriptors: College Students, Student Attitudes, Handheld Devices, Computer Oriented Programs
Acceptance and Use of App-Based Language Learning among Young Adolescents in a Self-Directed Context
Hyun-Bin Hwang – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2025
App-based language learning has gained attention for its potential to promote L2 learning beyond the classroom. However, few learners use L2 learning apps long enough to fully benefit from this learning method. Using the unified theory of acceptance and use of technology, I explored the acceptance and use of a commercially available language…
Descriptors: Computer Oriented Programs, Computer Uses in Education, Second Language Learning, Independent Study
Nicolas Pope; Juho Kahila; Henriikka Vartiainen; Matti Tedre – IEEE Transactions on Learning Technologies, 2025
The rapid advancement of artificial intelligence and its increasing societal impacts have turned many computing educators' focus toward early education in machine learning (ML). Limited options for educational tools for teaching novice learners about the mechanisms of ML and data-driven systems presents a recognized challenge in K-12 computing…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Computer Science Education, Grade 4
Sharon R. Mittiga; Nerelie C. Freeman; Brett E. Furlonger; Perrin Chan; Erin S. Leif – Journal of Positive Behavior Interventions, 2025
This study evaluated the quality and behavior change techniques (BCTs) included in 11 freely available mobile classroom behavior management applications (mCBM apps). We found that mCBM apps included a limited number of BCTs, with an average of 9 of 21 possible BCTs. Consequence-based BCTs like rewards and feedback were common, while…
Descriptors: Behavior Modification, Student Behavior, Computer Uses in Education, Positive Behavior Supports
Manus Phuttawong; Pinanta Chatwattana – Higher Education Studies, 2025
The educational guidance platform via artificial intelligence chatbot to promote vocational aptitude for vocational students or the educational guidance platform via AI Chatbot is a research tool that was designed with the combination of educational guidance process, artificial intelligence technology, and chat platforms like LINE and Messenger.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Vocational Aptitude, Career and Technical Education
Christopher Antoun; Xin Yang; Brady T. West; Ai Rene Ong – Field Methods, 2025
The objective of our project was to develop a smartphone app for administering shorter ("modular") surveys. Given the paucity of research on this topic, we decided to use "co-design" techniques to generate design solutions. To implement these techniques, we recruited respondents in the survey target population to work in small…
Descriptors: Test Construction, Surveys, Computer Oriented Programs, Design
Soyoung Choi; Deepthi Vasudevan; Apoorva Bhole; Jaeyi Hong; Krystal Steg; Jacqueline Marquez; Inna Chong; Erica Cai – Journal of American College Health, 2025
Objectives: The purpose of this study was to understand current research on the utilization of mobile health (mHealth) technologies for college students with disabilities. Methods: We conducted a bibliometric analysis to understand the longitudinal research trends and dominant topics in mHealth research for college students. Next, we performed a…
Descriptors: College Students, Students with Disabilities, Health Services, Educational Research
Ambroise Baillifard; Maxime Gabella; Pamela Banta Lavenex; Corinna S. Martarelli – Education and Information Technologies, 2025
Effective learning strategies based on principles like personalization, retrieval practice, and spaced repetition are often challenging to implement due to practical constraints. Here we explore the integration of AI tutors to complement learning programs in accordance with learning sciences. A semester-long study was conducted at UniDistance…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Instructional Effectiveness, Learning Strategies

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