There is a rich body of literature that details the effects of automated writing evaluation (AWE) on second language (L2) students. However, these studies mostly focus on the impact that automated feedback has on writing performance, i.e. that is, there is a dearth of research on its influence on affective factors. Hence, this study was conducted…

This study investigated the effectiveness of applying pedagogical translanguaging by utilizing Google Translate to facilitate college juniors in writing presentation scripts. Participants included 109 non-English major juniors divided into high- and low-proficiency groups, with 56 and 53 students, respectively. Each participant first drafted their…

This study investigates the impact of ChatGPT on EFL students' argumentative writing development of 30 third-year English majors. The research examines writing quality improvements, student perceptions, and patterns of AI tool usage across a 16-week period. This study employed a mixed-methods design to investigate both students' writing…

To test the predictive power of the SSARC (stabilize, simplify, automatize, reconstruct, and complexify) model of pedagogic task sequencing in second language (L2) writing development, the present study explores the performance of written decision-making tasks with varied levels of cognitive complexity in a simple-to-complex sequence in comparison…

A perfect writing skill has been deemed instrumental to achieving competence in EFL, yet it is considered one of the most impressive learning domains. This study investigates the impact of human-AI collaborative feedback on the writing proficiency of EFL students. It examines key teaching domains, including the teaching environment, teacher…

In an era of widespread automation--from grocery store self-checkout machines to selfdriving cars--it is not outrageous to wonder: can teachers be automated? And more specifically, can automated computer teachers instruct students how to write? Automated computer programs have long been used in summative writing evaluation efforts, such as scoring…

Written corrective feedback for improving L2 writing skills has been a debatable issue for more than two decades. The aims of this meta-analysis are to (1) provide a quantitative measure of the effect of computer-generated written feedback for improving L2 writing skills and (2) verify how moderators (i.e., adopted technology, task types, and…

Purpose: This study presents results from a pilot intervention that integrated self-regulation through reflection and goal setting with automated writing evaluation (AWE) technology to improve students' writing outcomes. Methods: We employed a single-group pretest-posttest design. All students in Grades 5-8 (N = 56) from one urban, all female,…

Automated writing evaluation (AWE) has been frequently used to provide feedback on student writing. Many empirical studies have examined the effectiveness of AWE on writing quality, but the results were inconclusive. Thus, the magnitude of AWE's overall effect and factors influencing its effectiveness across studies remained unclear. This study…

This study reports the integrated findings of a mixed-methods sequential explanatory study that investigated the feasibility and effectiveness of mobile-based writing tools (MBWTs) as well as gender differences that emerged from these learning effects in the narrative writing skills of a group of sixth to seventh grade Latinx English Learners…

Feedback is powerful but variable. This study investigates which forms of feedback are more predictive of improvement to students' essays, using "Turnitin Feedback Studio"--a computer augmented system to capture teacher and computer-generated feedback comments. The study used a sample of 3,204 high school and university students who…

Writing is a necessary skill in our technological world. Many people have a mobile device that they use for e-mailing, social media, as an alarm clock to start the day, reading the news, searching for information, ordering food, managing transportation (e.g., monitoring traffic, accessing public transit), or for relaxing pursuits, such as watching…

While the use of automated writing evaluation software has received much attention in CALL literature, as Frankenberg-Garcia (2019) notes, empirical research on predictive text and intelligent writing assistants is lacking. Thus, this study addressed this gap in the literature by examining the impact of Grammarly, an intelligent writing assistant…

This study has devoted itself to examining the effect of using cloud-based collaborative writing on EFL students' writing quantity and quality. Twenty-one EFL students studying at Jubail College of Education, IAU University participated in the study. They were pretested in writing quantity and quality before the treatment then they practiced…

This study explored the role of written languaging (WL) in response to automated written corrective feedback (AWCF) in L2 accuracy improvement in English classrooms at a university in China. A total of 254 freshmen enrolled in intermediate composition classes participated, and they wrote 4 essays and received AWCF. A half of them engaged in WL…