This WIP discusses the preliminary results of a paid-for-pilot, at the University of Birmingham, of a new assessment and feedback platform --- Graide. Graide uses machine learning and AI to assist educators in the grading process. It has been shown to increase both the detail of feedback for individual students and consistency of feedback across the cohort. Graide enables increased oversight of the assessment process whilst providing opportunities for continuous training of markers, whilst also reducing the time taken to grade work by up to 89%.
|Title of host publication||L@S 2022 - Proceedings of the 9th ACM Conference on Learning @ Scale|
|Subtitle of host publication||Proceedings of the Ninth ACM Conference on Learning @ Scale|
|Place of Publication||New York|
|Publisher||Association for Computing Machinery (ACM)|
|Number of pages||5|
|Publication status||Published - 1 Jun 2022|
|Event||L@S '22: Ninth (2022) ACM Conference on Learning @ Scale - Cornell Tech, New York, United States|
Duration: 1 Jun 2022 → 3 Jun 2022
|Name||L@S 2022 - Proceedings of the 9th ACM Conference on Learning @ Scale|
|Period||1/06/22 → 3/06/22|
Bibliographical noteFunding Information:
This research was funded in whole or in part by the Funder [Grant number EP/N509590/1]. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript (AAM) version arising from this submission.
© 2022 ACM.
ASJC Scopus subject areas
- Computer Networks and Communications