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Showing 1 to 15 of 19 results Save | Export
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Anna Rechtácková; Radek Pelánek; Tomáš Effenberger – ACM Transactions on Computing Education, 2025
Code quality is a critical aspect of programming, as high-quality code is easier to maintain, and code maintenance constitutes the majority of software costs. Consequently, code quality should be emphasized in programming education. While previous research has identified numerous code quality defects commonly made by students, the current state…
Descriptors: Programming, Computer Science Education, Error Patterns, Automation
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Owen Henkel; Hannah Horne-Robinson; Libby Hills; Bill Roberts; Josh McGrane – International Journal of Artificial Intelligence in Education, 2025
This paper reports on a set of three recent experiments utilizing large-scale speech models to assess the oral reading fluency (ORF) of students in Ghana. While ORF is a well-established measure of foundational literacy, assessing it typically requires one-on-one sessions between a student and a trained rater, a process that is time-consuming and…
Descriptors: Foreign Countries, Oral Reading, Reading Fluency, Literacy
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Arinjoy Basak; Nicole P. Pitterson; Clifford A. Shaffer; Sneha Patel Davison; David A. Dillard; Jacob Grohs – Advances in Engineering Education, 2025
Motivated by the benefits of repeated deliberate practice, we created an interactive exercise system for use in an undergraduate engineering mechanics class that focuses on practicing learned fundamental concepts. These exercises take the form of traditional word problems commonly found in mechanics courses, involving things like selecting and…
Descriptors: Usability, Electronic Learning, Computer Mediated Communication, Engineering Education
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Olaperi Okuboyejo; Sigrid Ewert; Ian Sanders – ACM Transactions on Computing Education, 2025
Regular expressions (REs) are often taught to undergraduate computer science majors in the Formal Languages and Automata (FLA) course; they are widely used to implement different software functionalities such as search mechanisms and data validation in diverse fields. Despite their importance, the difficulty of REs has been asserted many times in…
Descriptors: Automation, Feedback (Response), Error Patterns, Error Correction
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Bei Cai; Ziyu He; Hong Fu; Yang Zheng; Yanjie Song – IEEE Transactions on Learning Technologies, 2025
Much research has applied automated writing evaluation (AWE) systems to English writing instruction; however, understanding how students internalize and apply this feedback to reduce writing errors is difficult, largely due to the personal and private nature of this process. Therefore, this research utilized eye-tracking technology to explore the…
Descriptors: Undergraduate Students, Majors (Students), Writing (Composition), Writing Evaluation
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Bordewieck, Martin; Elson, Malte – Applied Cognitive Psychology, 2021
Troubleshooting is a particular problem-solving process comprising error detection, fault diagnosis, and system restoration. Since automation of systems has become increasingly complex and ubiquitous, troubleshooting skills are crucial to maintain safety and security in a variety of contexts. The planned study aims at examining troubleshooting…
Descriptors: Problem Solving, Error Patterns, Visual Aids, Cognitive Style
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Dillon, Thomas; Wells, Donald – English Teaching, 2023
This study examined effects of pronunciation training using automatic speech recognition technology on common pronunciation errors of Korean English learners. Participants were divided into two groups. One group was given instruction and training about the use of automatic speech recognition for pronunciation practice. The other group was not…
Descriptors: Pronunciation, English (Second Language), Second Language Instruction, English Language Learners
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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
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Zhang, Mo; Chen, Jing; Ruan, Chunyi – ETS Research Report Series, 2016
Successful detection of unusual responses is critical for using machine scoring in the assessment context. This study evaluated the utility of approaches to detecting unusual responses in automated essay scoring. Two research questions were pursued. One question concerned the performance of various prescreening advisory flags, and the other…
Descriptors: Essays, Scoring, Automation, Test Scoring Machines
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Qian, Yizhou; Lehman, James – Journal of Educational Computing Research, 2020
This study implemented a data-driven approach to identify Chinese high school students' common errors in a Java-based introductory programming course using the data in an automated assessment tool called the Mulberry. Students' error-related behaviors were also analyzed, and their relationships to success in introductory programming were…
Descriptors: High School Students, Error Patterns, Introductory Courses, Computer Science Education
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Xiao, Wenqi; Park, Moonyoung – International Journal of Computer-Assisted Language Learning and Teaching, 2021
With the advancement of automatic speech recognition (ASR) technology, ASR-based pronunciation assessment can diagnose learners' pronunciation problems. Meanwhile, ASR-based pronunciation training allows more opportunities for pronunciation practice. This study aims to investigate the effectiveness of ASR technology in diagnosing English…
Descriptors: Automation, Computer Software, Handheld Devices, Diagnostic Tests
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Paul John; Nina Wolf – CALICO Journal, 2020
Our study examines written corrective feedback generated by two online grammar checkers (GCs), Grammarly and Virtual Writing Tutor, and by the grammar checking function of Microsoft Word. We tested the technology on a wide range of grammatical error types from two sources: a set of authentic ESL compositions and a series of simple sentences we…
Descriptors: English (Second Language), Feedback (Response), Automation, Grammar
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Harteis, Christian; Fischer, Christoph; Töniges, Torben; Wrede, Britta – Frontline Learning Research, 2018
Preventing humans from committing errors is a crucial aspect of man-machine interaction and systems of computer assistance. It is a basic implication that those systems need to recognise errors before they occur. This paper reports an exploratory study that utilises eye-tracking technology and automated face recognition in order to analyse test…
Descriptors: Learning Processes, Error Patterns, Error Correction, Eye Movements
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Mao, Liyang; Liu, Ou Lydia; Roohr, Katrina; Belur, Vinetha; Mulholland, Matthew; Lee, Hee-Sun; Pallant, Amy – Educational Assessment, 2018
Scientific argumentation is one of the core practices for teachers to implement in science classrooms. We developed a computer-based formative assessment to support students' construction and revision of scientific arguments. The assessment is built upon automated scoring of students' arguments and provides feedback to students and teachers.…
Descriptors: Computer Assisted Testing, Science Tests, Scoring, Automation
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Smith, Chad; Allman, Tamby; Crocker, Samantha – Online Learning, 2017
This study and discussion center upon the use of "YouTube's" automatic captioning feature with college-age adult readers. The study required 75 participants with college experience to view brief middle school science videos with automatic captioning on "YouTube" and answer comprehension questions based on material presented…
Descriptors: Educational Technology, Technology Uses in Education, Video Technology, Middle Schools
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