Tracking Students’ Mental Engagement Using EEG Signals during an Interaction with a Virtual Learning Environment

Abstract

Monitoring students' level of engagement during learning activities is an important challenge in the development of tutoring interventions. In this paper, we explore the feasibility of using electroencephalographic signals (EEG) as a tool to monitor the mental engagement index of novice medicine students during a reasoning process. More precisely, the objectives were first, to track students' mental engagement evolution in order to investigate whether there were particular sections within the learning environment that aroused the highest engagement level among the students, and, if so, did these sections have an impact on learners' performance. Experimental analyses showed the same trends in the different resolution phases as well as across the different regions of the environments. However, we noticed a higher engagement index during the treatment identification phase since it aroused more mental effort. Moreover statistically significant effects were found between mental engagement and students' performance.

Art Teachers' Attitudes Toward Online Learning: An Empirical Study Using Self Determination Theory

“…Mental engagement can be seen as a kind of mental state and mechanisms in information processing (Ben Khedher et al, 2019). Well-being is part of these psychological mechanisms and is considered a combination of feelings that can support work performance.…”

Workplace Mental State Monitoring during VR-Based Training for Offshore Environment

“…Rapid advancement in sensor technologies has allowed simpler and cheaper setup that integrates EEG with the VR technology. It has been used in various settings such as healthcare [ 9 , 10 , 11 , 12 ], oil production [ 13 , 14 ], workplace [ 15 ] and education [ 16 ]. With the integration of EEG, researchers have studied various brain functions such as attention [ 17 , 18 ], cognitive load [ 19 , 20 ], motor intention and planning [ 11 ], emotional processing [ 21 , 22 ], sense of immersion [ 23 , 24 ], engagement [ 25 ] and relaxation [ 26 , 27 , 28 ].…”

EEG-based Measurement System for Student Engagement Detection in Learning 4.0

“…As concerns the engagement measurability, evaluation grids and self-assessment questionnaires (to be filled out by the observer or by the learner autonomously) are traditionally the most used methods for the behavioral, cognitive, and emotional engagement detection [15]. In recent years, measures based on biosignals are spreading very rapidly.…”

“…In 1995, authors in [17] proposed an engagement index to decide when to use the autopilot and when to switch to the manual one during a fly simulator session. The engagement index was E = β θ+α where α, β, and θ are the EEG frequency bands in (8-13) Hz, (13)(14)(15)(16)(17)(18)(19)(20)(21)(22) Hz, and (4-8) Hz respectively. Several studies used this index as engagement estimator also in learning contexts [15,18,19].…”

“…The engagement index was E = β θ+α where α, β, and θ are the EEG frequency bands in (8-13) Hz, (13)(14)(15)(16)(17)(18)(19)(20)(21)(22) Hz, and (4-8) Hz respectively. Several studies used this index as engagement estimator also in learning contexts [15,18,19]. However, the proposed index does not take into account the different engagement types (i.e., cognitive, emotional and behavioural) proposed by the theories previously reported.…”