Error detection through mouse movement in an online adaptive learning environment. (24th August 2020)

• Record Type: Journal Article
• Authors: de Mooij, Susanne M. M.; Raijmakers, Maartje E. J.; Dumontheil, Iroise; Kirkham, Natasha Z.; van der Maas, Han L. J.
• Is Part Of: Journal of computer assisted learning. Volume 37:Number 1(2021)
• Page Start: 242
• Page End: 252
• Publication Date: 2020-08-24
• Subjects: adaptive learning -- arithmetic -- educational games -- error detection -- mouse tracking; Computer-assisted instruction -- Periodicals; 371.334
• DOI: 10.1111/jcal.12483
• Languages: English
• ISSNs: 0266-4909

Abstract

Abstract: While response time and accuracy indicate overall performance, their value in uncovering cognitive processes, underlying learning, is limited. A promising online measure, designed to track decision‐making, is computer mouse tracking, where mouse attraction towards different locations may reflect the consideration of alternative response options. Using a speedy arithmetic multiple‐choice game in an online adaptive learning environment, we examined whether mouse movements could reflect arithmetic difficulties when error rates are low. Results showed that mouse movements towards alternative responses in correctly answered questions mapped onto the frequency of errors made in this online learning system. This mapping was stronger for the younger children, as well as for easy arithmetic problems. On an individual level, users showed more mouse movement towards their previously made response errors than towards other alternative options. This opens the possibility of adapting feedback and instruction on an individual basis through mouse tracking. Lay Description: What is currently known about this topic: In online learning environments, detecting systematic difficulties for students during learning is challenging due to the required high success rate. Previous studies have found that computer mouse tracking offers a window into the cognitive process of considering multiple alternatives before deciding. What is lacking is a validation outside the lab, whether mouse tracking can be a source for detecting systematic difficulties students might have. What the paper adds to this: Mouse tracking was implemented outside the lab in a large‐scale online learning environment for primary school children practicing maths. Novel mouse metrics were developed to measure attraction towards multiple distractors instead of one. Findings show that mouse movements reveal cues to arithmetic difficulties without the need for errors. Implications of the study findings: Mouse tracking is a useful tool to investigate difficulties in the learning process in a motivating practice system. Diagnosing these arithmetic misconceptions for individuals can help to adapt feedback and instruction. The developed mouse method can be used for more daily‐life complex designs with multiple attractors.