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Barrot, Jessie S. – Computer Assisted Language Learning, 2023
Despite the building up of research on the adoption of automated writing evaluation (AWE) systems, the differential effects of automated written corrective feedback (AWCF) on errors with different severity levels and gains across writing tasks remain unclear. Thus, this study fills in the vacuum by examining how AWCF through Grammarly affects…
Descriptors: Automation, Written Language, Error Correction, Feedback (Response)
Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
Figen Durkaya – Shanlax International Journal of Education, 2023
The present study has been developed in order to inquire the cognitive awareness of the 2nd grade-level students of the Science Teaching program on "sensors", which has an important place in the development of the robotic and automation systems. In the study, the method of case study, which is one of the qualitative research motifs, was…
Descriptors: Preservice Teachers, Science Teachers, Grade 2, Teacher Education Programs
Tom Bleckmann; Gunnar Friege – Knowledge Management & E-Learning, 2023
Formative assessment is about providing and using feedback and diagnostic information. On this basis, further learning or further teaching should be adaptive and, in the best case, optimized. However, this aspect is difficult to implement in reality, as teachers work with a large number of students and the whole process of formative assessment,…
Descriptors: Concept Mapping, Formative Evaluation, Automation, Feedback (Response)
Kornwipa Poonpon; Paiboon Manorom; Wirapong Chansanam – Contemporary Educational Technology, 2023
Automated essay scoring (AES) has become a valuable tool in educational settings, providing efficient and objective evaluations of student essays. However, the majority of AES systems have primarily focused on native English speakers, leaving a critical gap in the evaluation of non-native speakers' writing skills. This research addresses this gap…
Descriptors: Automation, Essays, Scoring, English (Second Language)
Shuxin Tan; Young Woo Cho; Wensi Xu – Interactive Learning Environments, 2023
With the rapid advance in educational technology, electronic feedback (e-feedback) has found its way to EFL writing process. The aim of this study is to investigate the effects of three e-feedback modes, that is, automated written corrective feedback (AWCF), asynchronous computer-mediated communication (ACMC), and their combination on EFL…
Descriptors: Foreign Countries, English (Second Language), Second Language Learning, Feedback (Response)
Tessa Charles; Carl Gwilliam – Journal for STEM Education Research, 2023
STEM fields, such as physics, increasingly rely on complex programs to analyse large datasets, thus teaching students the required programming skills is an important component of all STEM curricula. Since undergraduate students often have no prior coding experience, they are reliant on error messages as the primary diagnostic tool to identify and…
Descriptors: Automation, Feedback (Response), Error Correction, Physics
Lautt, Marinela; Asumadu, Eunice; Abdul, Nurdin; Korzaan, Melinda – Information Systems Education Journal, 2019
Atrium Limited Liability Partnership (LLP), an architectural company with over 3,000 partners, addresses the business need to collect and organize signed tax forms to assist its international partners. This case discusses the challenges associated with the current manual process, the pursuit of a solution to automate and simplify this process and…
Descriptors: Business, Taxes, Automation, Records (Forms)
Finkelman, Matthew D.; de la Torre, Jimmy; Karp, Jeremy A. – International Journal of Testing, 2020
Cognitive diagnosis models (CDMs) have been studied as a means of providing detailed diagnostic information about the skills that have been mastered, and the skills that have not, by examinees. Prior research has examined the use of automated test assembly (ATA) alongside CDMs; however, no previous study has investigated how to perform ATA when a…
Descriptors: Cognitive Measurement, Models, Automation, Test Construction
Noyes, Keenan; McKay, Robert L.; Neumann, Matthew; Haudek, Kevin C.; Cooper, Melanie M. – Journal of Chemical Education, 2020
Computer-assisted analysis of students' written responses to questions is becoming a possibility due to developments in technology. This could make such constructed response questions more feasible for use in large classrooms where multiple choice assessments are often considered a more practical option. In this study, we use a previously…
Descriptors: Automation, Artificial Intelligence, Computer Uses in Education, Classification
Cole, Brian S.; Lima-Walton, Elia; Brunnert, Kim; Vesey, Winona Burt; Raha, Kaushik – Journal of Applied Testing Technology, 2020
Automatic item generation can rapidly generate large volumes of exam items, but this creates challenges for assembly of exams which aim to include syntactically diverse items. First, we demonstrate a diminishing marginal syntactic return for automatic item generation using a saturation detection approach. This analysis can help users of automatic…
Descriptors: Artificial Intelligence, Automation, Test Construction, Test Items
El Sherif, Reem; Langlois, Alexis; Pandu, Xiao; Nie, Jian-Yun; Thomas, James; Hong, Quan Nha; Pluye, Pierre – Education for Information, 2020
Mixed studies reviews include empirical studies with diverse designs (qualitative, quantitative and mixed methods). To make the process of identifying relevant empirical studies for such reviews more efficient, we developed a mixed filter that included different keywords and subject headings for quantitative (e.g., cohort study), qualitative…
Descriptors: Automation, Classification, Qualitative Research, Statistical Analysis
Hilal Yildiz; S. Ipek Kuru Gonen – Turkish Online Journal of Distance Education, 2024
It is imperative to use new technologies in a supportive manner to meet the learners' and teachers' demanding needs as educational environments change in the digital age. The continuous expansion of online learning and distance education opportunities responds to the demands of learners and teachers while pioneering the use of technology in…
Descriptors: Writing Evaluation, Automation, Feedback (Response), Electronic Learning
Agata Guskaroska – ProQuest LLC, 2024
Improving pronunciation in second language (L2) learning requires timely and personalized feedback but educators have limited time to dedicate in the classroom. While there are many educational tools available, educators are still struggling to integrate technology in their practices. To address this challenge, this study explores repurposing a…
Descriptors: Pronunciation, Adoption (Ideas), Second Language Learning, Technology Uses in Education
Gulnihan Altinay; Selami Aydin – Online Submission, 2024
Writing achievement is crucial for English as a foreign language (EFL) learners due to its impact on language skills, overall proficiency, academic success, creativity, and critical thinking. However, the teacher feedback may be problematic due to timing, subjectivity, overemphasis, and alignment with learning goals. Automated feedback, on the…
Descriptors: College Students, Automation, Feedback (Response), Foreign Countries

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