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Dania Bilal; Li-Min Cassandra Huang – Information and Learning Sciences, 2025
Purpose: This paper aims to investigate user voice-switching behavior in voice assistants (VAs), embodiments and perceived trust in information accuracy, usefulness and intelligence. The authors addressed four research questions: RQ1. What is the nature of users' voice-switching behavior in VAs? RQ2: What are user preferences for embodied voice…
Descriptors: Undergraduate Students, Artificial Intelligence, Natural Language Processing, Information Retrieval
Susnjak, Teo; Ramaswami, Gomathy Suganya; Mathrani, Anuradha – International Journal of Educational Technology in Higher Education, 2022
This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our…
Descriptors: Learning Analytics, Computer Interfaces, Artificial Intelligence, Prediction
Yu, Zhonggen; Xu, Wei; Sukjairungwattana, Paisan – International Journal of Web-Based Learning and Teaching Technologies, 2022
Superstar Learning System, designed and developed by Superstar Company, is a learning platform where teachers and learners may have access to plentiful educational resources and interact with each other. Behavioral intention related to this platform has not been enough explored although many researchers have examined its use in education. A random…
Descriptors: Student Behavior, Educational Technology, Computer Interfaces, Technology Uses in Education
Ping, Lei; Liu, Katrina – Texas Education Review, 2020
Augmented reality (AR) has gained popularity in K-12 education in the past decades; researchers and educators generally agree that AR is a useful pedagogical tool in teaching because it is grounded on efficient teaching and learning models such as constructivist learning, situated learning, and inquiry-based learning. Research on AR in the K-12…
Descriptors: Computer Simulation, Educational Technology, Technology Uses in Education, Elementary Secondary Education
Kishabale, Bashir – International Journal of Education and Development using Information and Communication Technology, 2021
The current study, guided by the cross-sectional survey method, assessed interface design quality, and its predictive ability on E-learners' post-adoption behavior in E-learning course environments. DeLone and McLean's Information Systems Success Model, Khan's E-learning Framework, and Bhattacherjee's Information System Continuance Model formed…
Descriptors: Electronic Learning, Computer Interfaces, Design, Predictive Validity
Mentzer, Nathan – Technology and Engineering Teacher, 2014
This article describes an efficient peer evaluation process that can be implemented at the middle and high school levels, and that holds students accountable for their individual contributions in a team-based project. Teachers faced with this challenge will welcome the web-based peer-evaluation interface that was capable of soliciting student…
Descriptors: Middle School Students, High School Students, Peer Evaluation, Student Projects
Ghergulescu, Ioana; Muntean, Cristina Hava – International Journal of Artificial Intelligence in Education, 2016
Engagement influences participation, progression and retention in game-based e-learning (GBeL). Therefore, GBeL systems should engage the players in order to support them to maximize their learning outcomes, and provide the players with adequate feedback to maintain their motivation. Innovative engagement monitoring solutions based on players'…
Descriptors: Case Studies, Questionnaires, Electronic Learning, Educational Games
Chen, Gwo-Dong; Nurkhamid; Wang, Chin-Yeh; Yang, Shu-Han; Chao, Po-Yao – Educational Technology & Society, 2014
In a classroom, obtaining active, whole-focused, and engaging learning results from a design is often difficult. In this study, we propose a self-observation model that employs an instinctive interface for classroom active learning. Students can communicate with virtual avatars in the vertical screen and can react naturally according to the…
Descriptors: Models, Active Learning, Computer Uses in Education, Computer Interfaces
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2009
The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors), example-tracing tutors evaluate student behavior by flexibly comparing it against generalized examples of problem-solving behavior. Example-tracing…
Descriptors: Feedback (Response), Student Behavior, Intelligent Tutoring Systems, Problem Solving
Kennedy, Gregor E.; Judd, Terry S. – Computers & Education, 2007
Developers of educational multimedia programs have expectations about the way in which they will be used. These expectations can be broadly categorised as either functional (primarily related to the interface) or educational (related to learning designs, processes and outcomes). However, student users will not always engage with educational…
Descriptors: Learning Processes, Medical Students, Multimedia Materials, Computer Software

Wong, Chi Keun; Wong, Wai; Yeung, Chor Hung – Innovations in Education and Teaching International, 2001
Describes the development of a multimedia Web-based assessment system for computer literacy at Hong Kong Baptist University. Presents findings of a study that investigated students' behavior, performance, and perception in the use of this assessment system and discusses future plans which include improving the user interface. (Author/LRW)
Descriptors: Computer Interfaces, Computer Literacy, Evaluation Methods, Evaluation Research