Toward optimizing the design of virtual environments for route learning: empirically assessing the effects of changing levels of realism on memory

Figures & data

Figure 1. Screenshots illustrating the three VEs (not to scale).

Figure 2. Experimental setup (left-top), the two routes (left-bottom) and the procedure (right).

Figure 3. Overall recall accuracy for each VE. Error bars show ±SEM. ***p < .001, *p < 05.

Table 1. Mean recall accuracies, ANOVA (F, p, η_p², and pairwise comparisons (for statistically significant results).

Task	Abstract (A) Mean ± SD (%)	Mixed (M) Mean ± SD (%)	Realistic (R) Mean ± SD (%)	Repeated measures ANOVA	Pairwise comparisons
Overall	61.6 ± 12.0	73.8 ± 11.5	66.1 ± 11.9	F(2,84) = 21.1, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .154	M–A (p < .001)*** M–R (p < .001)*** R–A (p < .05)*
Visual	56.3 ± 15.8	68.9 ± 15.6	64.3 ± 18.0	F(2,84) = 9.3, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .092	M–A (p < .001)*** R–A (p < .05)*
Visuospatial	63.1 ± 17.4	76.9 ± 17.8	63.8 ± 14.3	F(2,84) = 16.3, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .129	M–A (p < .001)*** M–R (p < .001)***
Map task A (passive)	70.8 ± 23.3	85.1 ± 25.3	72.6 ± 22.0	F(2,84) = 6.7, p < .01**, ${\eta }_{\mathrm{p}}^2$ = .069	M–A (p < .01)** M–R (p < .05)*
Spatial	72.6 ± 25.2	76.4 ± 21.8	76.4 ± 17.5	p > .05	–

Note: We always list the ‘winning’ VE first (e.g. M–A means the MixedVE led to a higher recall than the AbstractVE). SD: Standard Deviation.

***p < .001, **p < .01, *p < .05, p < .10.

Figure 4. Interactions between visualization types and task types for recall accuracy rates. Error bars show ±SEM. ***p < .001, **p < .01, *p < 05.

Figure 5. Overall recall accuracy for each visualization type based on MRT- and VSM-split groups. Error bars show ±SEM. ***p < .001, **p < .01, *p < 05.

Figure 6. Interactions between the visualization types and task types for the low/high-MRT and low/high-VSM groups’ recall accuracy rates. Error bars ±SEM. ***p < .001, **p < .01, *p < .05.

Table 2. ANOVAs (F, p, η_p² and pairwise comparisons of mean recall accuracies for high/low-MRT and high/low-VSM groups per visualization and task types.

	Tasks	Repeated measures ANOVA	Pairwise comparison	Repeated measures ANOVA	Pairwise comparison
		High-MRT		Low-MRT
MRT	Overall	F(2,38) = 10.2, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .101	M–A (p < .001***), M–R (p < .05*)	F(2,40) = 12.0, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .172	M–A (p < .01**) M–R (p < .01**)
	Visual	F(2,38) = 7.0, p < .01**, ${\eta }_{\mathrm{p}}^2$ = .134	M–A (p < .01**), A–R (p < .05*)	F(2,40) = 3.7, p < .05*, ${\eta }_{\mathrm{p}}^2$ = .094	M–A (p = .053·)
	Visuospatial	F(2,38) = 4.2, p < .05*, ${\eta }_{\mathrm{p}}^2$ = .096	A–M (p = .076·)	F(2,40) = 10.6, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .172	M–A (p < .01**) M–R (p < .01**)
	Map task A	p > .05	–	F(2,40) = 4.1, p < .05*, ${\eta }_{\mathrm{p}}^2$ = .064	M–A (p < .01**)
	Spatial	p > .05	–	p > .05	–
		High-VSM		Low-VSM
VSM	Overall	F(2,36) = 13.7, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .181	M–A (p < .01**), M–R (p < .001***)	F(2,38) = 11.5, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .147	M–A (p < .001***) M–R (p < .05*)
	Visual	F(2,36) = 5.5, p < .01**, ${\eta }_{\mathrm{p}}^2$ = .163	M–A (p < .05*)	F(2,38) = 3.6, p < .05*, ${\eta }_{\mathrm{p}}^2$ = .091	M–A (p < .01**)
	Visuospatial	F(2,36) = 9.2, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .174	M–A (p < .01**), M–R (p < .01**)	F(2,38) = 8.8, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .163	M–A (p < .01**) M–R (p < .05*)
	Map task A	F(2,36) = 3.4, p < .01**, ${\eta }_{\mathrm{p}}^2$ = .090	M–A (p < .05*)	p > .05	–
	Spatial	p > .05	–	p > .05	–

Note: We list the ‘winning’ VE first (e.g. M–A means the MixedVE led to a higher recall than the AbstractVE).

***p < .001, **p < .01, *p < .05, p < .10.

Table 3. Mean recall accuracies in all stages, ANOVA (F, p, η_p², and pairwise comparisons for statistically significant results.

Task		Abstract (A) Mean ± SD (%)	Mixed (M) Mean ± SD (%)	Realistic (R) Mean ± SD (%)	Repeated measures ANOVA	Pairwise comparisons
Stage 1 (short-term)	Overall	61.6 ± 12.0	73.8 ± 11.5	66.1 ± 11.9	F(2,84) = 21.1, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .154	M–A (p < .001)*** M–R (p < .01)*** R–A (p < .05)*
	Visual	56.3 ± 15.8	68.9 ± 15.6	64.3 ± 18.0	F(2,84) = 9.3, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .092	M–A (p < .001)*** R–A (p < .05)*
	Visuospatial	63.1 ± 17.4	76.9 ± 17.8	63.8 ± 14.3	F(2,84) = 16.3, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .129	M–A (p < .001)*** M–R (p < .001)***
	Map task A (passive)	70.8 ± 23.3	85.1 ± 25.3	72.6 ± 22.0	F(2,84) = 6.7, p < .01**, ${\eta }_{\mathrm{p}}^2$ = .069	M–A (p < .01)** M–R (p < .05)*
Stage 2 (long-term 1, 1 h later)	Overall	61.5 ± 21.8	68.8 ± 18.4	57.3 ± 22.6	F(2,84) = 10.3, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .050	M–A (p < .05*) M–R (p < .001***)
	Visual	49.1 ± 24.9	59.5 ± 22.2	52.7 ± 22.5	p > .05	–
	Visuospatial	NA	NA	NA	NA	NA
	Map task B (sketching)	67.6 ± 28.6	73.4 ± 27.1	59.7 ± 31.3	F(2,84) = 8.8, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .037	M–R (p < .01*) A–R (p = .0511·)
Stage 3 (long-term 2, one week later)	Overall	54.6 ± 17.0	64.6 ± 18.6	54.5 ± 18.7	F(2,84) = 21.0,  p < .001***, ${\eta }_{\mathrm{p}}^2$ = .064	M–A (p < .001***) M–R (p < .001***)
	Visual	56.0 ± 24.4	50.6 ± 18.5	49.1 ± 16.2	p > .05	–
	Visuospatial	41.2 ± 15.8	65.8 ± 19.7	47.5 ± 13.7	F(2,84) = 31.6, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .289	M–A (p < .001)*** M–R (p < .001)***
	Map task B (sketching)	64.1 ± 33.0	70.6 ± 33.7	62.4 ± 35.4	p > .05	–

Note: Pairwise comparison columns always lists the ‘winning’ VE first (e.g. M–A means the MixedVE led to a higher recall than the AbstractVE). SD: Standard Deviation. NA: Not available.

***p < .001, **p < .01, *p < .05, p < .10.

Table 4. Mean recall accuracies in all stages for comparable tasks in each VE. ANOVA (F, p, η_p², and pairwise comparisons.

Visualization type		Stage 1 Mean ± SD (%)	Stage 2 Mean ± SD (%)	Stage 3 Mean ± SD (%)	Repeated measures ANOVA	Pairwise comparison
Visual	Abstract	56.3 ± 15.8	49.1 ± 24.9	56.0 ± 24.4	p > .05	–
	Mixed	68.9 ± 15.6	59.5 ± 22.2	50.6 ± 18.5	F(2,84) = 13.3, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .138	Stage1–3 (p < .001***) Stage1–2 (p < .05*) Stage2–3 (p = .054·)
	Real	64.3 ± 18.0	52.7 ± 22.5	49.1 ± 16.2	F(2,84) = 8.9, p < .001***, ${\eta }_{\mathrm{p}}^2$ = .105	Stage1–2 (p < .05*) Stage1–3 (p < .001***)
Visuospatial	Abstract	63.2 ± 17.4	NA	41.2 ± 15.8	–	t(41) = 6.90, p < .001***, r = .73
	Mixed	76.9 ± 17.8	NA	65.7 ± 19.7	–	t(41) = 2.68, p < .05*, r = .38
	Real	63.8 ± 14.3	NA	47.5 ± 13.7	–	t(41) = 6.36, p < .001***, r = .70
Map task	Abstract	70.8 ± 23.4	67.6 ± 28.6	64.1 ± 33.0	p > .05	–
	Mixed	85.1 ± 25.3	73.4 ± 27.1	70.6 ± 33.7	F(2,84) = 4.9, p < .01**, ${\eta }_{\mathrm{p}}^2$ = .046	Stage1–3 (p < .05*)
	Real	72.6 ± 22.0	59.7 ± 31.3	62.4 ± 35.4	F(2,84) = 3.8, p < .05*, ${\eta }_{\mathrm{p}}^2$ = .034	Stage1–2 (p = .053·)

Note: Pairwise comparison column lists significant differences between the three stages. ‘Winning’ stage is listed first. SD: Standard Deviation. NA: Not available.

***p < .001, **p < .01, *p < .05,·p < .10.

Table 5. Participants’ preferences for the visualization types before and after the experiment.

	Preference before	Preference after	% switched
Abstract	0 (0%)	0 (0%)	–
Mixed	5 (12%)	29 (69%)	0 (0%)
Real	37 (88%)	13 (31%)	24 (65%)

Table 6. High/low-MRT and high/low-VSM groups’ preferences for the visualization types before and after the experiment.

	Preference before				Preference after
	High-VSM		Low-VSM		High-VSM		Low-VSM
Abstract	0	(0%)	0	(0%)	0	(0%)	0	(0%)
Mixed	1	(5%)	4	(21%)	13	(72%)	14	(74%)
Real	17	(95%)	15	(79%)	5	(28%)	5	(26%)
	High-MRT		Low-MRT		High-MRT		Low-MRT
Abstract	0	(0%)	0	(0%)	0	(0%)	0	(0%)
Mixed	2	(10%)	3	(15%)	13	(68%)	14	(70%)
Real	17	(90%)	17	(85%)	6	(32%)	6	(30%)