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Turgay Han; Elif Sari – Computer Assisted Language Learning, 2024
Feedback is generally regarded as an integral part of EFL writing instruction. Giving individual feedback on students' written products can lead to a demanding, if not insurmountable, task for EFL writing teachers, especially in classes with a large number of students. Several Automated Writing Evaluation (AWE) systems which can provide automated…
Descriptors: Foreign Countries, Automation, Feedback (Response), English (Second Language)
Anca Greere – Interpreter and Translator Trainer, 2024
Ethical awareness is arguably becoming ever more relevant with the increasing digitalisation of professional practice. Ethical dilemmas are changing in nature, becoming more diverse and more difficult to tackle, also as technologically infused realities give rise to more blurry boundaries. Language professionals, in training for the roles of the…
Descriptors: Ethics, Translation, Teaching Methods, Computational Linguistics
First, Do No Harm: Automated Detection of Abusive Comments in Student Evaluation of Teaching Surveys
Cunningham, Samuel; Laundon, Melinda; Cathcart, Abby; Bashar, Md Abul; Nayak, Richi – Assessment & Evaluation in Higher Education, 2023
Student evaluation of teaching (SET) surveys are the most widely used tool for collecting higher education student feedback to inform academic quality improvement, promotion and recruitment processes. Malicious and abusive student comments in SET surveys have the potential to harm the wellbeing and career prospects of academics. Despite much…
Descriptors: Student Evaluation of Teacher Performance, Written Language, Antisocial Behavior, Language Usage
Ferreira, Giselle Martins dos Santos; Lemgruber, Márcio Silveira; Cabrera, Thiago Leite – Journal of Interactive Media in Education, 2023
Although automation is not a novelty, high hopes are currently pinned on more and more ingenious devices built with Artificial Intelligence (AI). AI has become a key discussion point in the agendas of governments and multinational agencies, with particular interest in educational applications. This article explores parallels between ideas…
Descriptors: Artificial Intelligence, Educational Theories, Figurative Language, Persuasive Discourse
Klein, Ariel; Badia, Toni – Journal of Creative Behavior, 2015
In this study we show how complex creative relations can arise from fairly frequent semantic relations observed in everyday language. By doing this, we reflect on some key cognitive aspects of linguistic and general creativity. In our experimentation, we automated the process of solving a battery of Remote Associates Test tasks. By applying…
Descriptors: Language Usage, Semantics, Natural Language Processing, Test Items
Chen, Jing; Zhang, Mo; Bejar, Isaac I. – ETS Research Report Series, 2017
Automated essay scoring (AES) generally computes essay scores as a function of macrofeatures derived from a set of microfeatures extracted from the text using natural language processing (NLP). In the "e-rater"® automated scoring engine, developed at "Educational Testing Service" (ETS) for the automated scoring of essays, each…
Descriptors: Computer Assisted Testing, Scoring, Automation, Essay Tests
Sheehan, Kathleen M. – ETS Research Report Series, 2016
The "TextEvaluator"® text analysis tool is a fully automated text complexity evaluation tool designed to help teachers and other educators select texts that are consistent with the text complexity guidelines specified in the Common Core State Standards (CCSS). This paper provides an overview of the TextEvaluator measurement approach and…
Descriptors: Automation, Evaluation Methods, Reading Material Selection, Common Core State Standards
Gleason, Jesse – Hispania, 2014
Communicative approaches to language teaching that emphasize the importance of speaking (e.g., task-based language teaching) require innovative and evidence-based means of assessing oral language. Nonetheless, research has yet to produce an adequate assessment model for oral language (Chun 2006; Downey et al. 2008). Limited by automatic speech…
Descriptors: Scoring, Linguistics, Oral Language, Language Tests
Zipitria, I.; Arruarte, A.; Elorriaga, J. A. – Interactive Learning Environments, 2013
In the context of Learning Technologies, the need to be able to assess the learning and domain comprehension in open-ended learner responses has been present in artificial intelligence and education since its beginnings. The advantage of using summaries is that they allow teachers to diagnose comprehension and the amount of information remembered…
Descriptors: Languages, Grading, Connected Discourse, Language Usage
Ma, Hong; Slater, Tammy – CALICO Journal, 2016
This study utilized a theory proposed by Mohan, Slater, Luo, and Jaipal (2002) regarding the Developmental Path of Cause to investigate AWE score use in classroom contexts. This "path" has the potential to support validity arguments because it suggests how causal linguistic features can be organized in hierarchical order. Utilization of…
Descriptors: Scores, Automation, Writing Evaluation, Computer Assisted Testing
Attali, Yigal; Powers, Don – ETS Research Report Series, 2008
This report describes the development of grade norms for timed-writing performance in two modes of writing: persuasive and descriptive. These norms are based on objective and automatically computed measures of writing quality in grammar, usage, mechanics, style, vocabulary, organization, and development. These measures are also used in the…
Descriptors: Grade 4, Grade 6, Grade 8, Grade 10

O'Donnell, Holly – Journal of Reading, 1987
Explores the advantages and disadvantages of microcomputer text editors and spelling checkers and implications for their classroom use. (SRT)
Descriptors: Automation, Editing, Grammar, Language Usage
Quemada, Bernard – Meta, 1973
Paper presented at the Second International Conference on Linguistics and Translation, October 4-7, 1972, Montreal, Canada. (DD)
Descriptors: Automation, Computer Programs, Computer Storage Devices, Indexes