Intelligent diagnostic feedback for online multiple-choice questions

Guo, Ruisheng, Palmer-Brown, Dominic, Lee, S. W. and Cai, Fang Fang (2014) Intelligent diagnostic feedback for online multiple-choice questions. Artificial Intelligence Review, 42 (3). pp. 369-383. ISSN 1573-7462

[img]
Preview
Text
3-dominic.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (686kB) | Preview
Official URL: https://link.springer.com/article/10.1007%2Fs10462...

Abstract / Description

When students attempt multiple-choice questions (MCQs) they generate invaluable information which can form the basis for understanding their learning behaviours. In this research, the information is collected and automatically analysed to provide customized, diagnostic feedback to support students’ learning. This is achieved within a web-based system, incorporating the snap-drift neural network based analysis of students’ responses to MCQs. This paper presents the results of a large trial of the method and the system which demonstrates the effectiveness of the feedback in guiding students towards a better understanding of particular concepts.

Item Type: Article
Uncontrolled Keywords: Learning behaviour; Diagnostic feedback; Neural networks; On-line multiple-choice questions
Subjects: 000 Computer science, information & general works
Department: School of Computing and Digital Media
Depositing User: Bal Virdee
Date Deposited: 01 May 2018 07:25
Last Modified: 08 Apr 2020 10:10
URI: https://repository.londonmet.ac.uk/id/eprint/1445

Downloads

Downloads per month over past year



Downloads each year

Actions (login required)

View Item View Item