Mining of Keystroke and Mouse Dynamics to Increase the Engagement of Students with Programming Assignments

2019 ◽  
pp. 41-61
Author(s):  
Mario Garcia Valdez ◽  
Juan-J. Merelo ◽  
Amaury Hernandez Aguila ◽  
Alejandra Mancilla Soto
Keyword(s):  
Mouse Dynamics

Spotting faked 5 stars ratings in E-Commerce using mouse dynamics

2020 ◽  
Vol 109 ◽  
pp. 106348
Author(s):  
Merylin Monaro ◽  
Emanuela Cannonito ◽  
Luciano Gamberini ◽  
Giuseppe Sartori
Keyword(s):  
Mouse Dynamics

A Survey of User Authentication Based on Mouse Dynamics

2008 ◽  
pp. 210-219 ◽  
Author(s):  
Kenneth Revett ◽  
Hamid Jahankhani ◽  
Sérgio Tenreiro de Magalhães ◽  
Henrique M. D. Santos
Keyword(s):  
User Authentication ◽  
Mouse Dynamics

scholarly journals Spotting Faked Identities via Mouse Dynamics Using Complex Questions

2018 ◽  
Author(s):  
Merylin Monaro ◽  
Luciano Gamberini ◽  
Giuseppe Sartori
Keyword(s):  
Mouse Dynamics

scholarly journals Mouse dynamics correlates to student behaviour in computer-based exams

2017 ◽  
Vol 25 (6) ◽  
pp. 967-978
Author(s):  
Davide Carneiro ◽  
Paulo Novais ◽  
Nuno Sousa ◽  
José Miguel Pêgo ◽  
José Neves
Keyword(s):  
Higher Education ◽  
Higher Education Institutions ◽  
Interaction Patterns ◽  
Student Behaviour ◽  
Computer Based ◽  
Mouse Dynamics

Abstract Nowadays, it is common for higher education institutions to use computer-based exams, partly or integrally, in their evaluation processes. These exams, much like their paper-based counterparts, are one of the most significant sources of stress in the life of students. However, the fact that exams are undertaken in a computer allows for new features to be acquired that may provide more reliable insights into the behaviour and state of the student during the exam. In this article we analyse these novel behavioural features and explore, to which extent, they can point out previously unknown phenomena. Specifically, we show that the time a student takes to complete an exam is correlated with mouse dynamics features. In practical terms, we are able to predict the duration of each individual exam with a satisfying error based on the interaction patterns of the student.

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