Combining automated and peer feedback for effective learning design in writing practices

Shibani, A

Combining automated and peer feedback for effective learning design in writing practices

Shibani, A

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Publication Type:: Conference Proceeding
Citation:: ICCE 2017 - 25th International Conference on Computers in Education: Technology and Innovation: Computer-Based Educational Systems for the 21st Century, Doctoral Student Consortia Proceedings, 2017, pp. 21 - 24
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Shibani, A https://orcid.org/0000-0003-4619-8684	en_US
dc.date.available	2020-05-25T19:06:43Z
dc.date.issued	2017-01-01	en_US
dc.identifier.citation	ICCE 2017 - 25th International Conference on Computers in Education: Technology and Innovation: Computer-Based Educational Systems for the 21st Century, Doctoral Student Consortia Proceedings, 2017, pp. 21 - 24	en_US
dc.identifier.isbn	9789869401258	en_US
dc.identifier.uri	http://hdl.handle.net/10453/115965
dc.description.abstract	© 2017 Institute of Electrical and Electronics Engineers Inc.. All rights reserved. The provision of formative feedback has been shown to support self-regulated learning for improving students' writing. Formative peer feedback is a promising approach, but requires scaffolding to be effective for all students. Automated tools making use of writing analytics techniques are another useful means to provide formative feedback on students' writing. However, they should be applied through effective learning designs in pedagogic contexts for better uptake and sense-making by students. Such learning analytics applications open up the possibilities to combine different types of feedback for effective design of interventions in authentic contexts. A framework combining peer feedback and automated feedback is proposed to design effective interventions for improving student writing. Automated feedback is augmented by peer feedback for better contextual feedback and sense making, and peer feedback is enhanced by automated feedback as scaffolding, thus complementing each other.	en_US
dc.relation.ispartof	ICCE 2017 - 25th International Conference on Computers in Education: Technology and Innovation: Computer-Based Educational Systems for the 21st Century, Doctoral Student Consortia Proceedings	en_US
dc.title	Combining automated and peer feedback for effective learning design in writing practices	en_US
dc.type	Conference Proceeding
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Transdisciplinary Innovation
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2017 Institute of Electrical and Electronics Engineers Inc.. All rights reserved. The provision of formative feedback has been shown to support self-regulated learning for improving students' writing. Formative peer feedback is a promising approach, but requires scaffolding to be effective for all students. Automated tools making use of writing analytics techniques are another useful means to provide formative feedback on students' writing. However, they should be applied through effective learning designs in pedagogic contexts for better uptake and sense-making by students. Such learning analytics applications open up the possibilities to combine different types of feedback for effective design of interventions in authentic contexts. A framework combining peer feedback and automated feedback is proposed to design effective interventions for improving student writing. Automated feedback is augmented by peer feedback for better contextual feedback and sense making, and peer feedback is enhanced by automated feedback as scaffolding, thus complementing each other.

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http://hdl.handle.net/10453/115965