Facilitating learners' self-assessment during formative writing tasks using writing analytics toolkit

IF 5.1 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH
Luzhen Tang, Kejie Shen, Huixiao Le, Yuan Shen, Shufang Tan, Yueying Zhao, Torsten Juelich, Xinyu Li, Dragan Gašević, Yizhou Fan
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Abstract

Background

Learners' writing skills are critical to their academic and professional development. Previous studies have shown that learners' self-assessment during writing is essential for assessing their writing products and monitoring their writing processes. However, conducting practical self-assessments of writing remains challenging for learners without help, such as formative feedback.

Objectives

To facilitate learners' self-assessment in writing, we developed a writing analytics toolkit and used data visualisation and cutting-edge machine learning technology that provides real-time and formative feedback to learners.

Methods

To investigate whether our newly-developed tool affects the accuracy and process of learners' self-assessment, we conducted a lab study. We assigned 59 learners to complete writing (2 h) and revising (1 h) tasks. During the revision stage, we randomly assigned the learners to two groups: one group used the writing analytics toolkit while the second group was not granted access to the toolkit. Learners' self-assessment accuracy and process of self-assessment were compared between the two groups.

Results

In our study, we found the toolkit helped learners in the experimental group improve the self-assessment accuracy of their writing products compared to the learners in the control group. In addition, we also found that the affordances of the toolkit affected the learners' self-assessment process, and poor design affordances may have prevented the learners from reflecting by themselves.

Conclusions

Together, our empirical study shed light on the design of future writing analytics tools which aim at improving learners' self-assessment during formative writing processes.

Abstract Image

利用写作分析工具包促进学习者在形成性写作任务中进行自我评估
背景学习者的写作技能对其学术和专业发展至关重要。以往的研究表明,学习者在写作过程中的自我评估对于评估他们的写作成果和监控他们的写作过程至关重要。为了促进学习者在写作中进行自我评估,我们开发了一个写作分析工具包,并使用了数据可视化和尖端的机器学习技术,为学习者提供实时的形成性反馈。我们指派 59 名学习者分别完成写作(2 小时)和修改(1 小时)任务。在修改阶段,我们将学习者随机分为两组:一组使用写作分析工具包,另一组不使用该工具包。结果在研究中,我们发现与对照组的学习者相比,工具包帮助实验组的学习者提高了写作产品自我评估的准确性。此外,我们还发现,工具包的可负担性影响了学习者的自我评估过程,设计不当的可负担性可能会阻碍学习者进行自我反思。结论我们的实证研究为未来写作分析工具的设计提供了启示,这些工具旨在提高学习者在形成性写作过程中的自我评估能力。
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来源期刊
Journal of Computer Assisted Learning
Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
9.70
自引率
6.00%
发文量
116
期刊介绍: The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope
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