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Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
Ethan Prihar; Adam Sales; Neil Heffernan – Grantee Submission, 2023
This work proposes Dynamic Linear Epsilon-Greedy, a novel contextual multi-armed bandit algorithm that can adaptively assign personalized content to users while enabling unbiased statistical analysis. Traditional A/B testing and reinforcement learning approaches have trade-offs between empirical investigation and maximal impact on users. Our…
Descriptors: Trust (Psychology), Learning Management Systems, Learning Processes, Algorithms
Matthew Mauntel; Michelle Zandieh – International Journal of Research in Undergraduate Mathematics Education, 2024
In this article we analyze how students reason about linear combinations across multiple digital environments. We present the work of three groups of undergraduate students in the Southeast United States (US) who were considered ready to take linear algebra. The students played the game "Vector Unknown," reflected upon aspects of their…
Descriptors: Video Games, Algebra, Mathematics Instruction, Teaching Methods
Chen, Wenli; Tan, Jesmine S. H.; Zhang, Si; Pi, Zhongling; Lyu, Qianru – Educational Technology Research and Development, 2023
Nurturing twenty-first-century competency is one important agenda in this era, especially in developing collaborative learning and critical thinking skills. Yet, facilitating such a computer-supported collaborative learning (CSCL) environment is challenging. Although several technological platforms from past research studies were developed to…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Learning Analytics, Educational Technology
Cukurova, Mutlu; Khan-Galaria, Madiha; Millán, Eva; Luckin, Rose – Journal of Learning Analytics, 2022
One-to-one online tutoring provided by human tutors can improve students' learning outcomes. However, monitoring the quality of such tutoring is a significant challenge. In this paper, we propose a learning analytics approach to monitoring online one-to-one tutoring quality. The approach analyzes teacher behaviours and classifies tutoring sessions…
Descriptors: Learning Analytics, Tutoring, Educational Quality, Behavior Patterns
Arnbjörnsdóttir, Birna, Ed.; Bédi, Branislav, Ed.; Bradley, Linda, Ed.; Friðriksdóttir, Kolbrún, Ed.; Garðarsdóttir, Hólmfríður, Ed.; Thouësny, Sylvie, Ed.; Whelpton, Matthew James, Ed. – Research-publishing.net, 2022
The 2022 EUROCALL conference was held in Reykjavik on 17-19 August 2022 as a fully online event hosted by the Vigdís Finnbogadóttir Institute for Foreign Languages, the University of Iceland, and the Árni Magnússon Institute for Icelandic Studies. The conference theme was "Intelligent CALL, granular systems and learner data." This theme…
Descriptors: Learning Analytics, Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Experience
Zhou, Yuhao; Li, Xihua; Cao, Yunbo; Zhao, Xuemin; Ye, Qing; Lv, Jiancheng – International Educational Data Mining Society, 2021
In educational applications, "Knowledge Tracing" (KT) has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT…
Descriptors: Online Courses, Computer Assisted Instruction, Networks, Learning Analytics
Viberg, Olga; Kukulska-Hulme, Agnes; Peeters, Ward – International Journal of Mobile and Blended Learning, 2023
Mobile-assisted language learning (MALL) research includes examination and development of second language learners' cognitive and metacognitive self-regulated learning skills, but the affective learning component of self-regulation in this context remains largely unexplored. Support for affective learning, which is defined by learners' beliefs,…
Descriptors: Metacognition, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
Jaeho Jeon – Computer Assisted Language Learning, 2024
Professionals within the field of language learning have predicted that chatbots would provide new opportunities for the teaching and learning of language. Despite the assumed benefits of utilizing chatbots in language classrooms, such as providing interactional chances or helping to create an anxiety-free atmosphere, little is known about…
Descriptors: Computer Assisted Instruction, Artificial Intelligence, Learning Analytics, Computer Software
Andy Ding-Xuan Ng; Aloysius Ong; Alwyn Vwen Yen Lee; Chew Lee Teo – Pedagogies: An International Journal, 2024
Research and development of Learning Analytics (LA) have created new ways to support students' learning. However, our understanding of teachers' roles when implementing LA in classroom practices remains nascent. This study investigates how teachers can implement LA to support students' agency in directing their own inquiry, when engaging in a…
Descriptors: Learning Analytics, Grade 5, Elementary School Students, Grade 6
Nina Spada – Language Learning & Language Teaching, 2024
This volume presents the second edition of the "Communicative Orientation of Language Teaching (COLT) Observation Scheme." Since the book's original publication, COLT has become well established as a research instrument in L2 teaching and learning. This new edition brings COLT into the 21st century by introducing digital versions of the…
Descriptors: Second Language Learning, Second Language Instruction, Web Based Instruction, Teaching Methods
Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks
Cohen, Anat; Ezra, Orit; Hershkovitz, Arnon; Tzayada, Odelia; Tabach, Michal; Levy, Ben; Segal, Avi; Gal, Kobi – Educational Technology Research and Development, 2021
Personalizing the use of educational mathematics applets to fit learners' characteristics poses a great challenge. The present study adopted a unique approach by comparing personalization processes implemented by a machine to those implemented by a human teacher. Given the different affordances--the machine's access to historical log file data,…
Descriptors: Mathematics Instruction, Comparative Analysis, Pedagogical Content Knowledge, Teaching Methods
Yuan, Chia-Ching; Li, Cheng-Hsuan; Peng, Chin-Cheng – Interactive Learning Environments, 2023
Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization…
Descriptors: Artificial Intelligence, Man Machine Systems, Technology Uses in Education, Educational Technology
Kenneth Holstein; Gena Hong; Mera Tegene; Bruce M. McLaren; Vincent Aleven – Grantee Submission, 2018
When used in classrooms, personalized learning software allows students to work at their own pace, while freeing up the teacher to spend more time working one-on-one with students. Yet such personalized classrooms also pose unique challenges for teachers, who are tasked with monitoring classes working on divergent activities, and prioritizing…
Descriptors: Middle School Teachers, Mathematics Teachers, Technology Uses in Education, Educational Technology
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