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Tejas R. Shah; Poonam Chhaniwal – International Journal of Learning Technology, 2024
This study empirically tested a model examining the effect of four e-learning quality dimensions, i.e., information quality, system quality, service quality, and instructor quality as well as students' self-efficacy on e-learning behaviour--satisfaction and continued intentions that further affect students' academic performance. The research model…
Descriptors: Electronic Learning, Educational Quality, Self Efficacy, Student Behavior
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Xundiao Ma; Yueguang Xie; Xin Yang; Hanxi Wang; Jia Lu – Education and Information Technologies, 2024
Teacher-student interaction (TSI) is the core element and important teaching method of smart classroom. Improving the quality of smart classroom teaching and developing higher-order thinking (HOT) among students requires strengthening research on the TSI structure in smart classroom. At present, the structure model of TSI in smart classroom mainly…
Descriptors: Teacher Student Relationship, Interaction, Virtual Classrooms, Electronic Learning
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Wang Jing Hao; Zaidatun Tasir – Journal of Information Technology Education: Research, 2024
Aim/Purpose: This study aims to develop a theoretical framework for enhancing students' higher-order thinking skills (HOTS) by integrating massive open online courses (MOOCs) with gamification elements. Background: There is a growing demand to develop students' innovative thinking abilities through MOOCs, focusing on higher-order thinking skills…
Descriptors: MOOCs, Gamification, Thinking Skills, Skill Development
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Takeshi Higeta – Educational Studies in Japan: International Yearbook, 2024
The relationship between time preference and high school students' career choices was analyzed using the cross-lagged effects model. A significant relationship was found between time preference in the first year of high school and educational expectations in April of the third year. Furthermore, time preference in the first year of high school was…
Descriptors: High School Students, Time Factors (Learning), Expectation, Career Choice
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Linda Hämmerle; Daniela Hlavka; Michael Kiehn; Peter Pany; Peter Lampert – American Biology Teacher, 2024
Especially within the light of the current loss of biodiversity, we want our students to gain a better understanding of the issues at stake in order to take action and support plants and their pollinators. Many educational approaches focus on honeybees, disregarding the vast diversity in the context of pollination systems and the complex…
Descriptors: Biodiversity, Plants (Botany), Teaching Methods, Scientific Concepts
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Julie Rattray – Higher Education: The International Journal of Higher Education Research, 2024
Higher education is facing increasing calls to engage in a process of intellectual decolonisation. This process necessitates that we take time to consider both the content of our curriculum and the pedagogic practices used to facilitate its understanding. Drawing on discussions of both intellectual decolonisation and its underpinning principles of…
Descriptors: Higher Education, Power Structure, Decolonization, Justice
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Somayeh B. Shafiei; Saeed Shadpour; Farzan Sasangohar; James L. Mohler; Kristopher Attwood; Zhe Jing – npj Science of Learning, 2024
The existing performance evaluation methods in robot-assisted surgery (RAS) are mainly subjective, costly, and affected by shortcomings such as the inconsistency of results and dependency on the raters' opinions. The aim of this study was to develop models for an objective evaluation of performance and rate of learning RAS skills while practicing…
Descriptors: Robotics, Surgery, Eye Movements, Medicine
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Denisa Gandara; Hadis Anahideh – Society for Research on Educational Effectiveness, 2024
Background/Context: Predictive analytics has emerged as an indispensable tool in the education sector, offering insights that can improve student outcomes and inform more equitable policies (Friedler et al., 2019; Kleinberg et al., 2018). However, the widespread adoption of predictive models is hindered by several challenges, including the lack of…
Descriptors: Prediction, Learning Analytics, Ethics, Statistical Bias
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Shiyi Liu; Juan Zheng; Tingting Wang; Zeda Xu; Jie Chao; Shiyan Jiang – AERA Online Paper Repository, 2024
This study introduces a novel approach for predicting student engagement levels in a language-based AI curriculum. The curriculum was integrated into English Language Arts classrooms, in which 106 students from five classes participated five web-based machine learning and text mining modules for 2 weeks. Sentiment and categorical analyses,…
Descriptors: Learner Engagement, Artificial Intelligence, Technology Uses in Education, Language Arts
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Zoeller, Emily; Briceño, Allison – Reading Teacher, 2022
When working with bilingual readers, teaching for equity means building on students' linguistic strengths. To do so, we must provide intentionally designed holistic literacy instruction that encourages students to use their full literacy and linguistic repertoire. This article describes an asset-oriented approach called "Transliteracy"…
Descriptors: Bilingualism, Reading Instruction, Teaching Methods, Native Language
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Desoete, Annemie; Baten, Elke – International Electronic Journal of Elementary Education, 2022
Several factors seem important to understand the nature of mathematical learning. Byrnes and Miller combined these factors into the Opportunity-Propensity model. In this study the model was used to predict the number-processing factor and the arithmetic fluency in grade 4 (n = 195) and grade 5 (n = 213). Gender, intelligence and affect (positive…
Descriptors: Mathematics Education, Elementary School Mathematics, Elementary School Students, Grade 4
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Gürses, Ahmet; Sahin, Elif; Günes, Kübra – Education Quarterly Reviews, 2022
This study aims to reveal the effectiveness of the problem-based learning (PBL) model in teaching the concepts of heat, temperature and pressure, as well as the effect of the activities on the development of scientific process skills. For this purpose, the change in the academic achievement levels of the students constituting the sampling group…
Descriptors: Problem Based Learning, Science Instruction, Instructional Effectiveness, Scientific Concepts
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Iskhakova, Marina; Bradly, Andrew – Journal of Management Education, 2022
Short-term study abroad (STSA) programs are the fastest growing segment of experiential learning programs in management education and the least studied. This is the first systematic review of STSA research, which focuses on 156 studies on STSA published between 2000 and 2019 and proposes a conceptual model to guide STSA research scholars. Through…
Descriptors: Study Abroad, Research Reports, Experiential Learning, Management Development
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Tzur, Sharon; Davidovich, Nitza; Katz, Adi – International Journal of Higher Education, 2022
This study involves e-learning skills via educational software, compared to instruction via educational software with the mediation of an instructor. In the last two decades, the role of the teacher-lecturer has changed, from teaching to guidance and instruction. The technological tools have changed the nature of the learning space and the manner…
Descriptors: Teaching Skills, Electronic Learning, Educational Technology, Computer Software
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Forthmann, Boris; Förster, Natalie; Souvignier, Elmar – Journal of Intelligence, 2022
Monitoring the progress of student learning is an important part of teachers' data-based decision making. One such tool that can equip teachers with information about students' learning progress throughout the school year and thus facilitate monitoring and instructional decision making is learning progress assessments. In practical contexts and…
Descriptors: Learning Processes, Progress Monitoring, Robustness (Statistics), Bayesian Statistics
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