Implementing an automated feedback program for a foreign language writing course
A learner‐centric study
Bibliographic Data
| ID | 21499133 |
|---|---|
| Authors | Mohammad Hassanzadeh (0000-0003-1510-1149, Department of English Language and Literature Vali‐e‐Asr University of Rafsanjan Rafsanjan Iran, corresponding author), Samira Fotoohnejad (Department of English Language and Literature Vali‐e‐Asr University of Rafsanjan Rafsanjan Iran, corresponding author) |
| Year | 2021 |
| Volume | 37 |
| Issue | 5 |
| Pages | 1494-1507 |
| Publication date | 2021-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Computer Assisted Learning (JOURNAL) |
| Journal identifiers | ISSN: 0266-4909 • E-ISSN: 1365-2729 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/jcal.12587 |
| OpenAlex | W3189169916 |
| Language | EN |
| Citations received | 11 |
| References cited | 27 |
Considering the prominence attached to written corrective feedback (WCF) within the domain of second/foreign language (L2) acquisition, automated writing evaluation (AWE) tools have steadily gained ground over the last two decades. The current study was an attempt to investigate the extent incorporating an AWE program, known as Criterion®, within a process writing framework would affect learners' writing quality in an English as a foreign language context. Moreover, we drew a comparison between the overall effects of computer‐ versus teacher‐generated WCF. Participants consisted of 53 tertiary level students from two intact essay‐writing classes. The within‐group findings revealed that the experimental group's writing scores rose significantly from the pretest to posttest after receiving automated WCF over several weeks. Significant progress was also noticed on all rounds of scores obtained from five essays assigned to this group except between the first and the second. As for the comparison between computer‐ and teacher‐administered WCF, the former condition was found to be more efficient. Overall, the findings provide a deeper insight into the workings of an automated evaluation tool and how it was employed in the L2 classroom to impart consistency to the assessment procedure and ease the burden traditionally placed upon teachers
Collaborative writing · Computer-Assisted Instruction · Corrective Feedback · Foreign language · Human–computer interaction · Linguistics · Mathematics education · Pedagogy · Second language · Second language writing · Usability · Computer Science · EFL/ESL Teaching and Learning · Psychology · Student Assessment and Feedback · Writing and Handwriting Education · Artificial Intelligence
A systematic review of AI-based automated written feedback research
Can algorithm-based feedback help students to write better? A meta-analysis exploring surface- and deep-level outcomes
Compositional Analysis of Writing Instructional Practices Performed with Digital Tools
Timed second language writing performance
The impact of online feedback on student learning outcomes
The effectiveness of automated writing evaluation in EFL/ESL writing
Using automated corrective feedback tools in language learning
What Are We Missing in AI‐Supported L2 Writing Research? A Systematic Review From 2014 to 2024
The impact of automated writing evaluation on English as a foreign language learners' writing self‐efficacy, self‐regulation, anxiety, and performance
Still a fallible tool? Revisiting effects of automated writing evaluation from activity theory perspective
Automated writing evaluation use in second language classrooms
Impact of automated writing evaluation on teacher feedback, student revision, and writing improvement
Problems in Output and the Cognitive Processes They Generate
The Contribution of Written Corrective Feedback to Language Development
Computer‐mediated feedback for L2 learners
Validity arguments for diagnostic assessment using automated writing evaluation
Enhancing the grammatical accuracy of EFL writing by using an AWE-assisted process approach
Effects of Written Feedback and Revision on Learners' Accuracy in Using Two English Grammatical Structures
| Citations per year | 3.67 |
|---|---|
| Citation span | 2023 - 2026 (4) |
| Highly cited | No |