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Jiang, Lianjiang; Yu, Shulin – Computer Assisted Language Learning, 2022
While automated feedback is becoming readily accessible to student writers, how students employ resources and strategies to use such feedback remains largely unexplored. Informed by activity theory and the construct of appropriation, this study conceptualizes students' use of automated feedback as social appropriation mediated by resources and…
Descriptors: Automation, Feedback (Response), Second Language Learning, Writing Instruction
Link, Stephanie; Mehrzad, Mohaddeseh; Rahimi, Mohammad – Computer Assisted Language Learning, 2022
Recent years have witnessed an increasing interest in the use of automated writing evaluation (AWE) in second language writing classrooms. This increase is partially due to the belief that AWE can assist teachers by allowing them to devote more feedback to higher-level (HL) writing skills, such as content and organization, while the technology…
Descriptors: Automation, Writing Evaluation, Feedback (Response), Revision (Written Composition)
Chen, Dandan; Hebert, Michael; Wilson, Joshua – American Educational Research Journal, 2022
We used multivariate generalizability theory to examine the reliability of hand-scoring and automated essay scoring (AES) and to identify how these scoring methods could be used in conjunction to optimize writing assessment. Students (n = 113) included subsamples of struggling writers and non-struggling writers in Grades 3-5 drawn from a larger…
Descriptors: Reliability, Scoring, Essays, Automation
Jessica Andrews-Todd; Jonathan Steinberg; Samuel L. Pugh; Sidney K. D'Mello – Grantee Submission, 2022
New challenges in today's world have contributed to increased attention toward evaluating individuals' collaborative problem solving (CPS) skills. One difficulty with this work is identifying evidence of individuals' CPS capabilities, particularly when interacting in digital spaces. Often human-driven approaches are used but are limited in scale.…
Descriptors: Problem Solving, Cooperation, Grade 7, Grade 8
Lottridge, Sue; Burkhardt, Amy; Boyer, Michelle – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Sue Lottridge, Amy Burkhardt, and Dr. Michelle Boyer provide an overview of automated scoring. Automated scoring is the use of computer algorithms to score unconstrained open-ended test items by mimicking human scoring. The use of automated scoring is increasing in educational assessment programs because it allows…
Descriptors: Computer Assisted Testing, Scoring, Automation, Educational Assessment
Botarleanu, Robert-Mihai; Dascalu, Mihai; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2020
A key writing skill is the capability to clearly convey desired meaning using available linguistic knowledge. Consequently, writers must select from a large array of idioms, vocabulary terms that are semantically equivalent, and discourse features that simultaneously reflect content and allow readers to grasp meaning. In many cases, a simplified…
Descriptors: Natural Language Processing, Writing Skills, Difficulty Level, Reading Comprehension
McCarthy, Kathryn S.; Allen, Laura K.; Hinze, Scott R. – Grantee Submission, 2020
Open-ended "constructed responses" promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students' cognition. This study examined how students' constructed responses, generated at different points during learning, relate to their later comprehension outcomes.…
Descriptors: Reading Comprehension, Prediction, Responses, College Students
Wang, Cong; Liu, Xiufeng; Wang, Lei; Sun, Ying; Zhang, Hongyan – Journal of Science Education and Technology, 2021
Assessing scientific argumentation is one of main challenges in science education. Constructed-response (CR) items can be used to measure the coherence of student ideas and inform science instruction on argumentation. Published research on automated scoring of CR items has been conducted mostly in English writing, rarely in other languages. The…
Descriptors: Automation, Scoring, Accuracy, Responses
Forkosh-Baruch, Alona; Phillips, Michael; Smits, Anneke – Educational Technology Research and Development, 2021
This article focuses on preservice and in-service teachers' pedagogical reasoning, decision making and action concerning technology integration for learning. We examine this topic in light of three contemporary barriers in policy, practice and research, namely: the lack of an integrative model that considers how teachers come to shape their…
Descriptors: Decision Making, Thinking Skills, Technology Integration, Preservice Teachers
de Jong, Nivja H.; Pacilly, Jos; Heeren, Willemijn – Assessment in Education: Principles, Policy & Practice, 2021
Fluency in terms of speed of speech and (lack of) hesitations such as silent and filled pauses ('uhm's) is part of oral proficiency. Language assessment rubrics therefore include aspects of fluency. Measuring fluency, however, is highly time-consuming because of the manual labour involved. The current paper aims to automatically measure aspects of…
Descriptors: Language Fluency, Speech Skills, Second Languages, Indo European Languages
Farrell, Lesley; Newman, Trent; Corbel, Christopher – Discourse: Studies in the Cultural Politics of Education, 2021
The Fourth Industrial Revolution is widely acknowledged as a digital technological revolution building on the convergence of Robotics, the Internet of Things, and the Internet of Services. What is less often acknowledged is that it is also a revolution in the social practice of work. Literacy is a core social technology of work and it is changing…
Descriptors: Workplace Literacy, World History, Industry, Job Skills
Lu, Chang; Cutumisu, Maria – International Educational Data Mining Society, 2021
Digitalization and automation of test administration, score reporting, and feedback provision have the potential to benefit large-scale and formative assessments. Many studies on automated essay scoring (AES) and feedback generation systems were published in the last decade, but few connected AES and feedback generation within a unified framework.…
Descriptors: Learning Processes, Automation, Computer Assisted Testing, Scoring
Wood, Scott; Yao, Erin; Haisfield, Lisa; Lottridge, Susan – ACT, Inc., 2021
For assessment professionals who are also automated scoring (AS) professionals, there is no single set of standards of best practice. This paper reviews the assessment and AS literature to identify key standards of best practice and ethical behavior for AS professionals and codifies those standards in a single resource. Having a unified set of AS…
Descriptors: Standards, Best Practices, Computer Assisted Testing, Scoring
Demszky, Dorottya; Liu, Jing; Hill, Heather C.; Jurafsky, Dan; Piech, Chris – Annenberg Institute for School Reform at Brown University, 2021
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource intensive in most educational contexts. We develop an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage teaching practice that…
Descriptors: Automation, Feedback (Response), Online Courses, Teaching Methods
Veronika Timpe-Laughlin; Tetyana Sydorenko; Judit Dombi – Computer Assisted Language Learning, 2024
To examine the utility of spoken dialog systems (SDSs) for learning and low-stakes assessment, we administered the same role-play task in two different modalities to a group of 47 tertiary-level learners of English. Each participant completed the task in an SDS setting with a fully automated agent and engaged in the same task with a human…
Descriptors: Second Language Learning, In Person Learning, Standard Spoken Usage, Role Playing