Assessing Engineering Education with the Eye Tracking Technology-Videonystagmography

Sandhya Dass; Sultan Ahmad; A. V. Prabu; Hikmat A. M. Abdeljaber; H. S. Ramananda

doi:10.2478/ijssis-2026-0010

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Assessing Engineering Education with the Eye Tracking Technology-Videonystagmography

International Journal on Smart Sensing and Intelligent Systems

Volume 19 (2026): Issue 1 (January 2026)

By: Sandhya Dass , Sultan Ahmad , A. V. Prabu , Hikmat A. M. Abdeljaber and H. S. Ramananda

Open Access

|Jul 2026

Figures & Tables

Screenshot of the VNG test interface showing the complete set of available ocular and vestibular assessment modules, including saccades, smooth pursuit, caloric test, optokinetic test, spontaneous nystagmus, gaze test, positional test, Subjective Mid-Point, Subjective Visual Vertical, Pupillometry, Head Impulse Test, and Video Frenzal. VNG, videonystagmography.

Hardware configuration of the Balance Eye VNG system (Cyclops MedTech Pvt. Ltd.), comprising the infrared video goggles for binocular eye tracking and the processing unit for real-time recording and analysis of horizontal and vertical eye movements. VNG, videonystagmography.

Experimental setup for VNG-based eye-movement recording using the Balance Eye system, illustrating the participant seated in front of the visual stimulus display while wearing infrared video goggles for real-time acquisition of horizontal and vertical saccadic eye movements under controlled laboratory conditions. VNG, videonystagmography.

Table 1:

Reliability analysis of saccadic eye-movement parameters using Cronbach’s alpha.

		N	%
Cases	Valid	36	100.0
	Excluded	0	0.0
	Total	36	100.0
*Reliability statistics*
Cronbach’s alpha	Cronbach’s alpha based on standardized items	N of Items
0.738	0.846	12

Table 2:

Normality assessment of saccadic latency and academic performance scores.

*Tests of normality on saccades latency*				Shapiro–Wilk
	Kolmogorov–Smirnova
	Statistic	df	Sig.	Statistic	df	Sig.
Saccades latency	0.090	36	0.200^*	0.974	36	0.537

*Tests of normality on average marks*				Shapiro–Wilk
	Kolmogorov–Smirnova
	Statistic	df	Sig.	Statistic	df	Sig.
Average marks	0.094	36	0.200^*	0.980	36	0.742

a Lilliefors significance correction.

* This is a lower bound of true significance.

Table 3:

Pearson correlation matrix of horizontal and vertical saccadic parameters.

		SHRV	SHRP	SHRL	SHLV	SHLP	SHLL	SVRV	SVRP	SVRL	SVLV	SVLP	SVLL
SHRV	Pearson correlation	1	0.679^**	−0.150	0.823^**	0.448^**	−0.202	0.508^**	0.357^*	−0.366^*	0.311	0.230	−0.403^*
	Sig. (two-tailed)		0.000	0.383	0.000	0.006	0.238	0.002	0.033	0.028	0.065	0.178	0.015
	N	36	36	36	36	36	36	36	36	36	36	36	36
SHRP	Pearson correlation	0.679^**	1	0.242	0.770^**	0.866^**	0.207	0.426^**	0.474^**	−0.152	0.426^**	0.363^*	−0.161
	Sig. (two-tailed)	0.000		0.156	0.000	0.000	0.225	0.009	0.003	0.376	0.010	0.029	0.349
	N	36	36	36	36	36	36	36	36	36	36	36	36
SHRL	Pearson correlation	−0.150	0.242	1	0.013	0.380^*	0.892^**	0.044	0.284	0.453^**	0.139	0.315	0.511^**
	Sig. (two-tailed)	0.383	0.156		0.941	0.022	0.000	0.800	0.093	0.005	0.419	0.061	0.001
	N	36	36	36	36	36	36	36	36	36	36	36	36
SHLV	Pearson correlation	0.823^**	0.770^**	0.013	1	0.697^**	0.031	0.456^**	0.450^**	−0.169	0.364^*	0.380^*	−0.238
	Sig. (two-tailed)	0.000	0.000	0.941		0.000	0.856	0.005	0.006	0.325	0.029	0.022	0.163
	N	36	36	36	36	36	36	36	36	36	36	36	36
SHLP	Pearson correlation	0.448^**	0.866^**	0.380^*	0.697^**	1	0.396^*	0.291	0.560^**	0.118	0.395^*	0.577^**	0.066
	Sig. (two-tailed)	0.006	0.000	0.022	0.000		0.017	0.085	0.000	0.494	0.017	0.000	0.702
	N	36	36	36	36	36	36	36	36	36	36	36	36
SHLL	Pearson correlation	−0.202	0.207	0.892^**	0.031	0.396^*	1	0.024	0.295	0.491^**	0.118	0.339^*	0.495^**
	Sig. (two-tailed)	0.238	0.225	0.000	0.856	0.017		0.888	0.081	0.002	0.493	0.043	0.002
	N	36	36	36	36	36	36	36	36	36	36	36	36
SVRV	Pearson correlation	0.508^**	0.426^**	0.044	0.456^**	0.291	0.024	1	0.770^**	−0.141	0.797^**	0.588^**	−0.155
	Sig. (two-tailed)	0.002	0.009	0.800	0.005	0.085	0.888		0.000	0.414	0.000	0.000	0.367
	N	36	36	36	36	36	36	36	36	36	36	36	36
SVRP	Pearson correlation	0.357^*	0.474^**	0.284	0.450^**	0.560^**	0.295	0.770^**	1	0.118	0.754^**	0.858^**	0.105
	Sig. (two-tailed)	0.033	0.003	0.093	0.006	0.000	0.081	0.000		0.492	0.000	0.000	0.544
	N	36	36	36	36	36	36	36	36	36	36	36	36
SVRL	Pearson correlation	−0.366^*	−0.152	0.453^**	−0.169	0.118	0.491^**	−0.141	0.118	1	0.053	0.245	0.938^**
	Sig. (two-tailed)	0.028	0.376	0.005	0.325	0.494	0.002	0.414	0.492		0.759	0.151	0.000
	N	36	36	36	36	36	36	36	36	36	36	36	36
SVLV	Pearson correlation	0.311	0.426^**	0.139	0.364^*	0.395^*	0.118	0.797^**	0.754^**	0.053	1	0.716^**	0.027
	Sig. (two-tailed)	0.065	0.010	0.419	0.029	0.017	0.493	0.000	0.000	0.759		0.000	0.874
	N	36	36	36	36	36	36	36	36	36	36	36	36
SVLP	Pearson correlation	0.230	0.363^*	0.315	0.380^*	0.577^**	0.339^*	0.588^**	0.858^**	0.245	0.716^**	1	0.179
	Sig. (two-tailed)	0.178	0.029	0.061	0.022	0.000	0.043	0.000	0.000	0.151	0.000		0.295
	N	36	36	36	36	36	36	36	36	36	36	36	36
SVLL	Pearson correlation	−0.403^*	−0.161	0.511^**	−0.238	0.066	0.495^**	−0.155	0.105	0.938^**	0.027	0.179	1
	Sig. (two-tailed)	0.015	0.349	0.001	0.163	0.702	0.002	0.367	0.544	0.000	0.874	0.295
	N	36	36	36	36	36	36	36	36	36	36	36	36

* Correlation is significant at the 0.05 level (two-tailed).

** Correlation is significant at the 0.01 level (two-tailed).

SHLL, saccade horizontal left eye latency; SHLP, saccade horizontal left eye precision; SHLV, saccade horizontal left eye velocity; SHRL, saccade horizontal right eye latency; SHRP, saccade horizontal right eye precision; SHRV, saccade horizontal right eye velocity; SVLL, saccade vertical left eye latency; SVLP, saccade vertical left eye precision; SVLV, saccade vertical left eye velocity; SVRL, saccade vertical right eye latency; SVRP, saccade vertical right eye precision; SVRV, saccade vertical right eye velocity.

Table 4:

Independent sample t-Test results comparing saccadic eye-movement parameters by gender.

		Levene’s test for equality of variances		t-Test for equality of means
		F	Sig.	t	df	Sig. (two-tailed)	Mean difference	Std. error difference	95% confidence interval of the difference
		F	Sig.	t	df	Sig. (two-tailed)	Mean difference	Std. error difference	Lower	Upper
SHRV	Equal variances assumed	913.363	0.000	15.209	5337	0.000	26.00878	1.71005	22.65639	29.36117
Equal variances not assumed			14.635	3,665.988	0.000	26.00878	1.77715	22.52448	29.49307
SHRP	Equal variances assumed	250.421	0.000	7.471	5,337	0.000	2.28499	0.30586	1.68538	2.88460
Equal variances not assumed			7.212	3,813.823	0.000	2.28499	0.31685	1.66379	2.90619
SHRL	Equal variances assumed	45.024	0.000	−18.683	5,337	0.000	−17.27987	0.92492	−19.09309	−15.46666
Equal variances not assumed			−18.514	4,979.906	0.000	−17.27987	0.93332	−19.10958	−15.45016
SHLV	Equal variances assumed	357.325	0.000	26.236	5,337	0.000	44.13396	1.68218	40.83620	47.43172
Equal variances not assumed			25.441	4,025.262	0.000	44.13396	1.73477	40.73285	47.53507
SHLP	Equal variances assumed	842.819	0.000	9.795	5,337	0.000	3.85816	0.39388	3.08599	4.63033
Equal variances not assumed			9.349	3,305.847	0.000	3.85816	0.41269	3.04900	4.66732
SHLL	Equal variances assumed	270.582	0.000	−6.851	5,337	0.000	−7.04183	1.02782	−9.05677	−5.02688
Equal variances not assumed			−6.744	4,718.012	0.000	−7.04183	1.04409	−9.08874	−4.99491
SVRV	Equal variances assumed	273.269	0.000	−2.671	5,337	0.008	−4.91581	1.84023	−8.52342	−1.30820
Equal variances not assumed			−2.614	4,450.120	0.009	−4.91581	1.88068	−8.60288	−1.22874
SVRP	Equal variances assumed	416.645	0.000	−0.751	5,337	0.453	−0.27302	0.36367	−0.98596	0.43991
Equal variances not assumed			−0.724	3,756.542	0.469	−0.27302	0.37719	−1.01255	0.46650
SVRL	Equal variances assumed	6.181	0.013	8.238	5,337	0.000	10.49969	1.27453	8.00109	12.99829
Equal variances not assumed			8.205	5,138.282	0.000	10.49969	1.27973	7.99088	13.00850
SVLV	Equal variances assumed	18.519	0.000	−8.608	5,337	0.000	−14.37928	1.67038	−17.65391	−11.10466
Equal variances not assumed			−8.651	5,313.766	0.000	−14.37928	1.66219	−17.63785	−11.12072
SVLP	Equal variances assumed	223.709	0.000	7.777	5,337	0.000	3.61782	0.46521	2.70581	4.52983
Equal variances not assumed			7.581	4,277.298	0.000	3.61782	0.47720	2.68225	4.55339
SVLL	Equal variances assumed	33.708	0.000	−2.404	5,337	0.016	−3.22244	1.34057	−5.85049	−0.59438
Equal variances not assumed			−2.409	5,279.145	0.016	−3.22244	1.33751	−5.84452	−0.60035

[i] SHLL, saccade horizontal left eye latency; SHLP, saccade horizontal left eye precision; SHLV, saccade horizontal left eye velocity; SHRL, saccade horizontal right eye latency; SHRP, saccade horizontal right eye precision; SHRV, saccade horizontal right eye velocity; SVLL, saccade vertical left eye latency; SVLP, saccade vertical left eye precision; SVLV, saccade vertical left eye velocity; SVRL, saccade vertical right eye latency; SVRP, saccade vertical right eye precision; SVRV, saccade vertical right eye velocity.

Time-domain representation of horizontal saccadic eye movements for both the right and left eyes, showing the relative positions of the visual target (green trace), right eye foveal position (red trace), and left eye foveal position (blue trace), highlighting saccadic latency and accuracy during target shifts.

Table 5:

Linear regression analysis of saccadic latency measures as predictors of academic performance.

Saccade parameter	α	β	R	R²	F	P	Indicator
Horizontal saccade latency (R)	−0.101	44.510	0.334	0.112	4.268	0.047	Significant
Horizontal saccade latency (L)	−0.071	40.604	0.245	0.06	2.175	0.149	Insignificant
Vertical saccade latency (R)	−0.117	46.169	0.506	0.256	11.696	0.002	Significant
Vertical saccade latency (L)	−0.106	45.358	0.496	0.246	11.089	0.002	Significant

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DOI: https://doi.org/10.2478/ijssis-2026-0010 | Journal eISSN: 1178-5608

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Language: English

Submitted on: Jul 14, 2025

Published on: Jul 16, 2026

Published by: International Journal on Smart Sensing and Intelligent Systems

In partnership with: Paradigm Publishing Services

Publication frequency: Volume open

Keywords:

eye-tracking in education,

digital technology,

educational technologies,

engagement,

engineering education,

teaching–learning in engineering,

nystagmography

Related subjects:

Engineering,

Introductions and overviews,

Engineering, other

© 2026 Sandhya Dass, Sultan Ahmad, A. V. Prabu, Hikmat A. M. Abdeljaber, H. S. Ramananda, published by International Journal on Smart Sensing and Intelligent Systems
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 19 (2026): Issue 1 (January 2026)

Assessing Engineering Education with the Eye Tracking Technology-Videonystagmography

Figures & Tables

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Figure 3:

Table 1:

Table 2:

Table 3:

Table 4:

Figure 4:

Table 5:

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