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Fu, Qian; Zheng, Yafeng; Zhang, Mengyao; Zheng, Lanqin; Zhou, Junyi; Xie, Bochao – Educational Technology Research and Development, 2023
Providing appropriate feedback is important when learning to program. However, it is still unclear how different feedback strategies affect learning outcomes in programming. This study designed four different two-step programming feedback strategies and explored their impact on novice programmers' academic achievement, learning motivations, and…
Descriptors: Feedback (Response), Academic Achievement, Novices, Programming
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Zheng, Xudong; Ma, Yunfei; Yue, Tingyan; Yang, Xianmin – Educational Technology Research and Development, 2023
The purpose of this study was to investigate the effects of different types of cues and self-explanation prompts in instructional videos on intrinsic motivation, learning engagement, learning outcomes, and cognitive load, which were indicators to measure deep learning performance. Seventy-two college students were randomly assigned to one of the…
Descriptors: Cues, Reflection, Prompting, Video Technology
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Qiufang Zheng – Educational Technology Research and Development, 2025
In the context of process-oriented writing instruction, the significance of engaging students in draft revision is widely acknowledged (McGarrell and Verbeem, ELT Journal 61:228-236, 2007). Nevertheless, L2 learners often exhibit limited motivation for writing, leading to inadequate revision efforts. This quasi-experimental study investigates the…
Descriptors: Technology Uses in Education, Computer Assisted Instruction, Writing Instruction, Writing Evaluation
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Lee, Yen-Fen; Hwang, Gwo-Jen; Chen, Pei-Ying – Educational Technology Research and Development, 2022
Review strategies after learning new knowledge are essential for students to consolidate the key points, understand the subject content, analyze aspects of the learning topics, and summarize the knowledge content of learning while mastering new knowledge. However, educators have found that students generally have difficulties seeking help when…
Descriptors: College Students, Control Groups, Foreign Countries, Artificial Intelligence
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Valle, Natercia; Antonenko, Pavlo; Valle, Denis; Sommer, Max; Huggins-Manley, Anne Corinne; Dawson, Kara; Kim, Dongho; Baiser, Benjamin – Educational Technology Research and Development, 2021
Based on the achievement goal theory, this experimental study explored the influence of predictive and descriptive learning analytics dashboards on graduate students' motivation and statistics anxiety in an online graduate-level statistics course. Participants were randomly assigned into one of three groups: (1) predictive dashboard; (2)…
Descriptors: Online Courses, Graduate Students, Statistics Education, Anxiety
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Zhu, Yue; Zhang, Jia Hua; Au, Wing; Yates, Greg – Educational Technology Research and Development, 2020
Studies have been conducted on university students' continuous intention to learn online from the perspectives of learning motivation and capability, perceptions or attitudes, and online learning experiences. However, few have examined how the above factors will relate to each other and contribute to students' online learning intention. This…
Descriptors: College Students, Student Attitudes, Online Courses, Blended Learning
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Makransky, Guido; Lilleholt, Lau – Educational Technology Research and Development, 2018
Virtual reality (VR) is projected to play an important role in education by increasing student engagement and motivation. However, little is known about the impact and utility of immersive VR for administering e-learning tools, or the underlying mechanisms that impact learners' emotional processes while learning. This paper explores whether…
Descriptors: Computer Simulation, Computer Uses in Education, Psychological Patterns, Emotional Response
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Broadbent, Jaclyn; Fuller-Tyszkiewicz, Matthew – Educational Technology Research and Development, 2018
This study examines a person-centered approach to self-regulated learning among 606 University students (140 online, and 466 in blended learning mode). Latent profile analysis revealed five distinct profiles of self-regulated learning: minimal regulators, restrained regulators, calm self-reliant capable regulators, anxious capable collaborators,…
Descriptors: Metacognition, Blended Learning, Online Courses, Profiles
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Novak, Elena; Daday, Jerry; McDaniel, Kerrie – Educational Technology Research and Development, 2018
This empirical study used Keller's (Technol Instr Cogn Learn 16:79-104, 2008b) motivation, volition, and performance (MVP) theory to develop and statistically evaluate a mathematical MVP model that can serve as a research and policy tool for evaluating students' learning experiences in digital environments. Specifically, it explored undergraduate…
Descriptors: Mathematical Models, Learning Motivation, Electronic Learning, Learning Experience
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Makransky, Guido; Mayer, Richard; Nøremølle, Anne; Cordoba, Ainara Lopez; Wandall, Jakob; Bonde, Mads – Educational Technology Research and Development, 2020
There is great potential in making assessment and learning complementary. In this study, we investigated the feasibility of developing a desktop virtual reality (VR) laboratory simulation on the topic of genetics, with integrated assessment using multiple choice questions based on item response theory (IRT) and feedback based on the cognitive…
Descriptors: Student Evaluation, Feedback (Response), Computer Simulation, Computer Uses in Education
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Shadiev, Rustam; Huang, Yueh-Min; Hwang, Jan-Pan – Educational Technology Research and Development, 2017
In this study, the effectiveness of the application of speech-to-text recognition (STR) technology on enhancing learning and concentration in a calm state of mind, hereafter referred to as meditation (An intentional and self-regulated focusing of attention in order to relax and calm the mind), was investigated. This effectiveness was further…
Descriptors: Assistive Technology, Learning, Attention, Metacognition
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Lee, Eunbae; Hannafin, Michael J. – Educational Technology Research and Development, 2016
Student-centered learning (SCL) identifies students as the owners of their learning. While SCL is increasingly discussed in K-12 and higher education, researchers and practitioners lack current and comprehensive framework to design, develop, and implement SCL. We examine the implications of theory and research-based evidence to inform those who…
Descriptors: Student Centered Learning, Learner Engagement, Elementary Secondary Education, Higher Education
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Lin, Hao-Chiang Koong; Chao, Ching-Ju; Huang, Tsu-Ching – Educational Technology Research and Development, 2015
According to Krashen's affective filter hypothesis, students who are highly motivated have their self-consciousness. When they enter a learning context with a low level of anxiety, they are much more likely to become successful language acquirers than those who do not. Affective factors such as motivation, attitude, and anxiety, have a direct…
Descriptors: Anxiety, Tutoring, Second Language Learning, College Students
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McNaught, Carmel; Lam, Paul; Cheng, Kin Fai – Educational Technology Research and Development, 2012
This article reports a study of eLearning in 21 courses in Hong Kong universities that had a blended design of face-to-face classes combined with online learning. The main focus of the study was to examine possible relationships between features of online learning designs and student learning outcomes. Data-collection strategies included expert…
Descriptors: Foreign Countries, Electronic Learning, Blended Learning, Internet
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Whipp, Joan L.; Chiarelli, Stephannie – Educational Technology Research and Development, 2004
Little is known about how successful students in Web-based courses self-regulate their learning. This descriptive case study used a social cognitive model of self-regulated learning (SRL) to investigate how six graduate students used and adapted traditional SRL strategies to complete tasks and cope with challenges in a Web-based technology course;…
Descriptors: Case Studies, Web Based Instruction, Online Courses, Social Cognition