GAZE TRACKING METHOD IN MARINE EDUCATION FOR SATISFACTION ANALYSIS Papachristos Dimitrios Nikitakos Nikitas Michail Kalogiannakis Alafodimos Constantinos
CONTENTS INTRODUCTION RESEARCH METHODOLOGY THE PROPOSED INTERPETATION FRAMEWORK RESULTS DISCUSSION CONCLUSIONS
INTRODUCTION (1) marine education and training Eye-tracking research in education visual attention Satisfaction analysis interpretation framework (INFW)
RESEARCH METHODOLOGY (1) The main elements of the proposed approach include: Registration and interpretation of user emotional states (satisfaction scale), Gaze tracking and interpretation, Questionnaires (medical & learn profile, appraisal) and Wrap-up interviews.
RESEARCH METHODOLOGY (2) The measurement methodology must fulfill all three requirements of the cognitive neuroscience (experiential verification, operational definition, repetition) and include data-tools: Recording device: might include special glasses with the recording camera or a web camera, Registration data process - analysis software and data process software
RESEARCH METHODOLOGY (3) Gaze trucking software Interpretation (software: Excel, SPSS) Measurement equipment Data Processing Web camera or special glasses Recording software Educational software (Matlab) Outcomes Optical data registration and analysis procedure
RESEARCH METHODOLOGY (4) Eyes Eye gaze vector (horizontal, vertical) Quality parameter (eye gaze trucking) values (horizontal)~0: mean out of screen values (horizontal) 10 view of the center of the screen Schedule of eyes & head pose ~0 attention in screen ~1 & >1 no attention Distance from monitor >1 close to the screen <1 away from the screen X o Eye Level, EL Head roll (angle), HR Horizontal Level, HL Values >10 o degrees, (high mobility) Values <10 o degrees (attention depending on the scenario EL HR= --------- HL Βiometric tool parameters interpretation ( Face Analysis )
RESEARCH METHODOLOGY (5) In the beginning of the procedure each user-student is given a series of questionnaires which include: experiment participation acceptance statement, medical-learning profile questionnaire, and software educational evaluation questionnaire
RESEARCH METHODOLOGY (6) Next, the scenario is based on the educational material (according to the STCW 95 corresponding standard) tutored in the Ε Semester of the Marine Academy of Aspropyrgos (Merchant Faculty) aiming at the following Educational Goals - ΕG : ΕG1- Automatic control mathematical tools application / use, ΕG2-Automatic control model development, ΕG3-Model analysis & simulation.
THE PROPOSED INTERPETATION FRAMEWORK
THE PROPOSED INTERPETATION FRAMEWORK (1) The INterpretation FrameWork (INFW) consists of several possible factors that pose an effect on the satisfaction case The INFW aims at interpreting, determining and evaluating the figures of the biometric tool in combination with the conventional methods (qualitative, quantitative) results based on the factors that are possible to influence the user s satisfaction
THE PROPOSED INTERPETATION FRAMEWORK (2) Parameters: -Structure -Levels of difficulties -Educational targets Scenario Meta-cognitive data Prior knowledge -skills -knowledge -techniques Parameters: -theoretical infrastructure -skills Educational software (Simulator) Para - e-learning elements INFW Parameters: -multimedia -interaction -learning theories -instructional design Parameters: -course -equipment -teacher expertise -IMO standards (marine education standards) -Faculty organization relation Factors Parameters Qualitative forms: Factor= f(parameters) SR= R i,j P: Parameters F: Factor SR: Set of Relationships R var i,j : Relationship factor-to factor i,j: factor, factor var: variable The proposed INterpretation FrameWork (INFW)
RESULTS (1) random sampling January 2011 Marine Academy of Aspropyrgos Computer Systems Lab sample consists of 20 students (17 Male, 3 Female)
RESULTS (2) Number of Question Medical Learning profile /educational characteristics Male (n=17) Female (n=3) 1 Strabismus 1 0 2 Monochromatic 0 0 3 Eye disease 5 (3-myopia, 1-hypermetropia, 1-astigmatism) 3 (2-myopia, 1-astigmatism) 4 Eye operation 0 0 5 Dyslexia 4 0 6 ADHD 0 0 7 Simulator experience 9 1 8 Usability 13 2 9 Math knowledge (grades) 5-6 7-8 9-10 12 5 0 1 2 0 10 Learning to Matlab (easy not easy) 16 (easy) 3 (easy)
RESULTS (3) Numerical Scale Scenario Matlab 1 2 M ** (1) * M(1) - 3 4 5 6 7 8 9 10 M(1) M(1) M(2) M(4) M(4) M(2) - F(1) - M(1) M(4) M(3) M(4) M(2), F *** (1) - - *(n):frequency in sample **M:Male, ***F:Female
RESULTS (4) Time ap pro x. (min) Eye gaze vecto r horizontal Head pose Vecto r pitch Head pose Vector Yaw Dist_ Monitor Head roll Average F * (11), M ** (8.5), T *** (8.9) F( 1.86), M(5.17), T(3.5) F( 0.18), M(0.15), T(0.165) F( 0.11), M(-0.006 ), T(0.058) F( 1.27), M(1.32), T(1.29) F(0.78), M(0.97), T(0.87) Standard Dev F(4.6), M(4.6) F(21.4), M(31.6) F(0.43), M(0.37) F( 0.48), M(0.32) F( 0.31), M(1.078) F(9.34), M(12.97) CV F(0.41), M(0.54) F(11.5), M(6.11) - - F( 0.24), M(0.81) F( 11.9), M(13.37) F*: Female, M**: Male, T***: Total
RESULTS (5) The Eye gaze vector parameter (horizontal) approximately shows that regardless of the gender, the students see inside the monitor and not outside of it, with the men focusing more in the centre of the monitor, indicating a bigger average
RESULTS (6) In Head pose Vector parameters (pitch, yaw) is discovered that the users are focused in the scenario execution (their attention is not distracted). In a distance from the monitor (dist_mon parameter) it is observed that both men and women approach the screen (>1) and keep a relatively close distance (figures homogeneity)
RESULTS (7) In the following variable a balance in the head declination is indicated (~0o) in both genders with women having a better figure (homogeneity)
RESULTS (8) The CV agent of the group samples (Male, Female) in female sample indicates a larger homogeneity in the parameters Time, Dist_Monitor, Head roll, while in the male sample a larger homogeneity is indicated in the Gaze vector horizontal parameter
RESULTS (9) In data about Satisfaction (Matlab, Scenario) an improvement (with some discontinuity) of the eye Gaze vector (horizontal) parameter is observed as the satisfaction scale grows whereas in the other parameters (Head pose, Dis_monitor, Head roll) there s a relative stabilityhomogeneity in rates
RESULTS (10) In addition it is concluded that there is an increase in the Time parameter as the satisfaction scale (Scenario & Matlab) grows
DISCUSSION (1) With the application of INFW to the data so far (optical data registration, interview) for the qualitative research of the users satisfaction it is established that:
DISCUSSION (2) Visual attention (VA) is probably connected indirectly (positively) with the Satisfaction scale (Sc): (VA Sc )
DISCUSSION (3) there is a connection between interest (Inter) and the Satisfaction scale (Sc): (Inter Sc )
DISCUSSION (4) Possible connection between a simulating experience (SimExp) and the satisfaction scale VA is probably influenced by the mathematics knowledge there is a possible relation between VA mathematics knowledge level satisfaction scale from the qualitative relations that led to the connection between VA & satisfaction level and the interview responses as well
DISCUSSION (5) Confirmation between a possible connection between head roll - interface and the interview responses (negative answers on interface) Possible connection between eye diseases & dyslexia with VA and therefore with the satisfaction scale (tends to a negative relation) according to the qualitative relations
DISCUSSION (6) The Time (T) parameter is directly and proportionally connected to the Satisfaction scale (Sc): (VA, satisfaction scale, Inter Time )
CONCLUSSIONS (1) Firstly, regarding the analytical framework unfolded over Matlab and the experimental measurements and the interview responses, it is established that:
CONCLUSSIONS (2) Visual Attention (VA) is connected indirectly (positively) with the Satisfaction scale, there is a connection (positively) between interest (Inter) and the Satisfaction scale (Sc), mathematics knowledge is an important factor of influence (positive) on the user s behavior (Matlab is a mathematics tool), the Time (T) parameter is directly and proportionally connected to the Satisfaction scale (Sc) and the knowledge of the cognitive subject matter is also an important factor.
CONCLUSSIONS (3) From the processing of the experimental optical data so far it is established that visual attention (VA) seems to relates with the users satisfaction and INFW factors (prior knowledge, para e-learning elements, simulator, scenario) each in different rate seem to participate in the interpretation of the influence in the users satisfaction.
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