Student Use of Automated Essay Evaluation Technology During Revision

Moore, Noreen S.; MacArthur, Charles A.

doi:10.17239/jowr-2016.08.01.05

Cited by 30 publications

(16 citation statements)

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“…Immediate feedback positively predicts engagement in web-based courses. The revision may motivate the students to revise by receiving the technology scores (Moore and MacArthur, 2016). For research writing, the findings indicated no statistically significant difference in the engagement scores for non-equipped L2 students under the same instructional procedure.…”

Section: Discussionmentioning

confidence: 91%

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

Nazari

Shabbir

Setiawan

2021

Heliyon

135

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A major challenge in educational technology integration is to engage students with different affective characteristics. Also, how technology shapes attitude and learning behavior is still lacking. Findings from educational psychology and learning sciences have gained less traction in research. The present study was conducted to examine the efficacy of a group format of an Artificial Intelligence (AI) powered writing tool for English second postgraduate students in the English academic writing context. In the present study, (N ¼ 120) students were randomly allocated to either the equipped AI (n ¼ 60) or non-equipped AI (NEAI). The results of the parametric test of analyzing of covariance revealed that at post-intervention, students who participated in the AI intervention group demonstrated statistically significant improvement in the scores, of the behavioral engagement (Cohen's d ¼ .75, 95% CI [0.38, 1.12]), of the emotional engagement Cohen's d ¼ .82, 95% CI [0.45, 1.25], of the cognitive engagement, Cohen's d ¼ .39,95% CI [0.04, .76], of the self-efficacy for writing, Cohen's d ¼ .54, 95% CI [0.18, 0.91], of the positive emotions Cohen's d ¼ . 44, 95% CI [0.08, 0.80], and of the negative emotions, Cohen's d ¼ À.98, 95% CI [À1.36, À0.60], compared with NEAI. The results suggest that AI-powered writing tools could be an efficient tool to promote learning behavior and attitudinal technology acceptance through formative feedback and assessment for non-native postgraduate students in English academic writing.

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Section: Discussionmentioning

confidence: 91%

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

Nazari

Shabbir

Setiawan

2021

Heliyon

135

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“…Students who used PEG Writing expressed stronger willingness to invest time in solving problems in their writing. Other studies have used behavioral measures of writing motivation, showing that students who use AWE increase time on task and revise more (Foltz, 2014; Moore & MacArthur, 2016).…”

Section: Introductionmentioning

confidence: 99%

Automated Writing Evaluation and Feedback: Multiple Metrics of Efficacy

Wilson

Roscoe

2019

Journal of Educational Computing Research

100

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The present study extended research on the effectiveness of automated writing evaluation (AWE) systems. Sixth graders were randomly assigned by classroom to an AWE condition that used Project Essay Grade Writing ( n = 56) or a word-processing condition that used Google Docs ( n = 58). Effectiveness was evaluated using multiple metrics: writing self-efficacy, holistic writing quality, performance on a state English language arts test, and teachers' perceptions of AWE's social validity. Path analyses showed that after controlling for pretest measures, composing condition had no effect on holistic writing quality, but students in the AWE condition had more positive writing self-efficacy and better performance on the state English language arts test. Posttest writing self-efficacy partially mediated the effect of composing condition on state test performance. Teachers reported positive perceptions of AWE's social validity. Results emphasize the importance of using multiple metrics and considering both contextual factors and AWE implementation methods when evaluating AWE effectiveness.

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“…A related limitation to address in future research is about the uptake of feedback, which is not always interpreted or used as intended (Brown et al, 2016;Moore and MacArthur, 2016). Winstone et al (2017) proposed that, in addition to characteristics of the feedback itself, four recipience processes-self-appraisal, assessment literacy, goal setting and self-regulation, and engagement and motivation-affect students' proactive engagement with the feedback process.…”

Section: Limitations Of and Directions For Researchmentioning

confidence: 99%

Classroom Assessment as Co-Regulated Learning: A Systematic Review

Andrade

Brookhart

2021

Front. Educ.

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Current conceptions of assessment describe interactive, reciprocal processes of co-regulation of learning from multiple sources, including students, their teachers and peers, and technological tools. In this systematic review, we examine the research literature for support for the view of classroom assessment as a mechanism of the co-regulation of learning and motivation. Using an expanded framework of self-regulated learning to categorize 94 studies, we observe that there is support for most but not all elements of the framework but little research that represents the reciprocal nature of co-regulation. We highlight studies that enable students and teachers to use assessment to scaffold co-regulation. Concluding that the contemporary perspective on assessment as the co-regulation of learning is a useful development, we consider future directions for research that can address the limitations of the collection reviewed.

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Student Use of Automated Essay Evaluation Technology During Revision

Cited by 30 publications

References 0 publications

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

Application of Artificial Intelligence powered digital writing assistant in higher education: randomized controlled trial

Automated Writing Evaluation and Feedback: Multiple Metrics of Efficacy

Classroom Assessment as Co-Regulated Learning: A Systematic Review

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