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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
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
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
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
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
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
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
de Roock, Roberto Santiago – Theory Into Practice, 2021
This article argues that digital writing pedagogy needs to prepare students to deal with underlying oppressive realities within the range of everyday digital writing practices as opposed to simply focusing on affordances as unfettered opportunities. In particular, digital writing is increasingly mediated through digital apps and other interactive…
Descriptors: Technological Literacy, Technology Uses in Education, Writing (Composition), Racial Bias
Lee, Hee-Sun; Gweon, Gey-Hong; Lord, Trudi; Paessel, Noah; Pallant, Amy; Pryputniewicz, Sarah – Journal of Science Education and Technology, 2021
A design study was conducted to test a machine learning (ML)-enabled automated feedback system developed to support students' revision of scientific arguments using data from published sources and simulations. This paper focuses on three simulation-based scientific argumentation tasks called Trap, Aquifer, and Supply. These tasks were part of an…
Descriptors: Artificial Intelligence, Automation, Feedback (Response), Persuasive Discourse
Davis, Larry; Papageorgiou, Spiros – Assessment in Education: Principles, Policy & Practice, 2021
Human raters and machine scoring systems potentially have complementary strengths in evaluating language ability; specifically, it has been suggested that automated systems might be used to make consistent measurements of specific linguistic phenomena, whilst humans evaluate more global aspects of performance. We report on an empirical study that…
Descriptors: Scoring, English for Academic Purposes, Oral English, Speech Tests
Myers, Matthew C.; Wilson, Joshua – International Journal of Artificial Intelligence in Education, 2023
This study evaluated the construct validity of six scoring traits of an automated writing evaluation (AWE) system called "MI Write." Persuasive essays (N = 100) written by students in grades 7 and 8 were randomized at the sentence-level using a script written with Python's NLTK module. Each persuasive essay was randomized 30 times (n =…
Descriptors: Construct Validity, Automation, Writing Evaluation, Algorithms
Gong, Kaixuan – Asian-Pacific Journal of Second and Foreign Language Education, 2023
The extensive use of automated speech scoring in large-scale speaking assessment can be revolutionary not only to test design and rating, but also to the learning and instruction of speaking based on how students and teachers perceive and react to this technology. However, its washback remained underexplored. This mixed-method study aimed to…
Descriptors: Second Language Learning, Language Tests, English (Second Language), Automation
Wei-Yan Li; Kevin Kau; Yi-Jiun Shiung – SAGE Open, 2023
Automated Writing Evaluation (AWE) software has been viewed as a promising tool for assisting writing. This study integrated AWE and its combination with peer review discussion into writing practice in a large college writing class in the Asian context. Adopting a mixed-method approach, this study employed a quantitative questionnaire to…
Descriptors: Feedback (Response), Writing Evaluation, Computer Software, Automation

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