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Gillani, Nabeel; Eynon, Rebecca; Chiabaut, Catherine; Finkel, Kelsey – Educational Technology & Society, 2023
Recent advances in Artificial Intelligence (AI) have sparked renewed interest in its potential to improve education. However, AI is a loose umbrella term that refers to a collection of methods, capabilities, and limitations--many of which are often not explicitly articulated by researchers, education technology companies, or other AI developers.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Educational Benefits
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Yung-Hsiang Hu; Jo Shan Fu; Hui-Chin Yeh – Interactive Learning Environments, 2024
Artificial intelligence aims to restructure and process re-engineering education and teaching processes and accelerate the evolution of the whole education system from information to intelligence. Robotic Process Automation (RPA) robots learn by observing people at work, analyzing user processes repeatedly, and adjusting or correcting automated…
Descriptors: Intelligent Tutoring Systems, Robotics, Automation, Instructional Effectiveness
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Rustam Shadiev; Yingying Feng – Interactive Learning Environments, 2024
Previous review studies do not have a broad and comprehensive perspective on the usage of ACF tools in language learning. To address this gap, we reviewed 82 articles on the use of ACF tools published in the last five years. Results indicate that 43 ACF tools were used in studies to assist writing, grammar, spelling, and collocation and word use.…
Descriptors: Automation, Feedback (Response), Educational Technology, Technology Uses in Education
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Odiel Estrada-Molina; Juanjo Mena; Alexander López-Padrón – International Review of Research in Open and Distributed Learning, 2024
No records of systematic reviews focused on deep learning in open learning have been found, although there has been some focus on other areas of machine learning. Through a systematic review, this study aimed to determine the trends, applied computational techniques, and areas of educational use of deep learning in open learning. The PRISMA…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Open Education, Educational Trends
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Helene Friis Ratner – Discourse: Studies in the Cultural Politics of Education, 2024
It is well-known that digital learning materials influence the classroom curriculum and didactics. At the same time, few studies examine the role of the data visualizations offered by digital learning materials. Data visualizations signpost the emergence of students as data subjects who can be observed and compared on a computer screen. They thus…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Secondary School Teachers
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Birgit Zeyer-Gliozzo – Journal of Education and Work, 2024
The automation of job tasks due to technological change increases the pressure on workers whose jobs consist largely of such activities. In this context, politics and science attach great importance to further training, although the benefits for affected workers have hardly been investigated. Drawing on human capital theory and the task-based…
Descriptors: Foreign Countries, Automation, Job Security, Skill Obsolescence
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Escudeiro, Paula; Galasso, Bruno; Teixeira, Dirceu; Gouveia, Márcia Campos; Escudeiro, Nuno – Cypriot Journal of Educational Sciences, 2022
The communication gap between deaf and non-deaf communities arises due to the use of distinct mother languages. A deaf student, who used to communicate in sign language, cannot read fluently materials written in spoken language. This fact causes serious difficulties to deaf students since most didactic materials in higher education are available…
Descriptors: Foreign Countries, Interpersonal Communication, Deafness, Online Courses
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Talebinamvar, Mobina; Zarrabi, Forooq – Language Testing in Asia, 2022
Feedback is an essential component of learning environments. However, providing feedback in populated classes can be challenging for teachers. On the one hand, it is unlikely that a single kind of feedback works for all students considering the heterogeneous nature of their needs. On the other hand, delivering personalized feedback is infeasible…
Descriptors: Feedback (Response), Writing Evaluation, Writing (Composition), Learning Analytics
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Renu Balyan; Tracy Arner; Tong Li; Ellen Orcutt; Reese Butterfuss; Panayiota Kendeou; Danielle McNamara – Grantee Submission, 2022
Speech technology (automated speech recognition -- ASR and text-to-speech) offers great promise in the field of automated literacy and reading tutors for children. Students in third and fourth grades struggle with generating longer strings of text on a QWERTY keyboard because they still "hunt and peck" for AQ1 the letters and symbols…
Descriptors: Assistive Technology, Technology Integration, Intelligent Tutoring Systems, Automation
Abhijit Suresh – ProQuest LLC, 2022
Over the past decade, robust literature focused on teacher "talk moves" that promote student argumentation has emerged, especially in mathematics education. Teachers and students can use talk moves to construct conversations in which students share their thinking, actively consider the ideas of others, and engage in sustained reasoning.…
Descriptors: Automation, Feedback (Response), Teacher Effectiveness, Discourse Modes
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Lv, Xiaoxuan; Ren, Wei; Xie, Yue – Asia-Pacific Education Researcher, 2021
Online feedback is frequently implemented during second/foreign language (SL/FL) writing tasks and assessments. This meta-analysis investigates the effectiveness of online feedback in SL/FL writing. After careful screening and the application of inclusion and exclusion criteria, this study synthesizes the results of 17 primary studies reporting on…
Descriptors: English (Second Language), Second Language Instruction, Feedback (Response), Computer Mediated Communication
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Haldeman, Georgiana; Babes-Vroman Monica; Tjang, Andrew; Nguyen, Thu D. – ACM Transactions on Computing Education, 2021
Autograding systems are being increasingly deployed to meet the challenges of teaching programming at scale. Studies show that formative feedback can greatly help novices learn programming. This work extends an autograder, enabling it to provide formative feedback on programming assignment submissions. Our methodology starts with the design of a…
Descriptors: Student Evaluation, Feedback (Response), Grading, Automation
Liang, Changhao; Majumdar, Rwitajit; Ogata, Hiroaki – Research and Practice in Technology Enhanced Learning, 2021
Collaborative learning in the form of group work is becoming increasingly significant in education since interpersonal skills count in modern society. However, teachers often get overwhelmed by the logistics involved in conducting any group work. Valid support for executing and managing such activities in a timely and informed manner becomes…
Descriptors: Automation, Cooperative Learning, Grouping (Instructional Purposes), Computer Assisted Instruction
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Means, Alexander J. – Critical Studies in Education, 2021
This paper examines how elite transnational policy and research organizations are framing emergent technologies as a hypermodern risk. It outlines how innovations in artificial intelligence and machine learning are feeding into global policy imaginaries and responses oriented to education and skills as adaption and minimization of potential…
Descriptors: Automation, Educational Policy, Artificial Intelligence, Global Approach
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Bojcetic, Nenad; Valjak, Filip; Zezelj, Dragan; Martinec, Tomislav – Education Sciences, 2021
The article describes an attempt to address the automatized evaluation of student three-dimensional (3D) computer-aided design (CAD) models. The driving idea was conceptualized under the restraints of the COVID pandemic, driven by the problem of evaluating a large number of student 3D CAD models. The described computer solution can be implemented…
Descriptors: Student Evaluation, Automation, Computer Assisted Design, Computer Uses in Education
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