Experiment 1 examined sex differences in the DSP. We predicted that males would take more shortcuts and take less time to navigate to goal locations while females would take more learned routes and take more time to navigate to goal locations. Another goal was to explore the relationship between strategy and efficiency to evaluate the degree to which sex differences in efficiency could be accounted for by differences in strategy. The final goal was to evaluate the relation of these measures to standard measures, both objective and subjective, of large-scale spatial ability and strategy. We predicted that subjective and objective measures would be related and that taking shortcuts in the DSP would be related to measures of large-scale spatial ability.

Method

Participants

Participants were 72 University of California, Santa Barbara, undergraduates who participated in return for course credit. Four participants were excluded from analysis due to motion sickness (N = 2), colorblindness (N = 1), and experimenter error (N = 1). Sixty-eight participants (40 female, 28 male) were included in the final analyses.

Materials

The experiment was administered using a Dell Optiplex 9020 with an AMD Radeon 8570 graphics card computer running Windows 7 64-bit and presented through Vizard 4.0 (Santa Barbara, CA). The environment was displayed on a 24-inch LCD monitor (289.9 × 531.4 mm display area) with a refresh rate of 60 Hz at a resolution of 1920 × 1080. The viewing distance was approximately 1,000 mm. The field of view in the virtual environment was set to 60 degrees.

Maze environment

We created a VR training maze (see Fig. 1a) and a DSP learning maze, which were the same size and shape (55 × 55 meters) and had no dead ends. There were 12 nodes within the DSP learning maze, and landmark objects were placed in 11 of these nodes (see Fig. 1b). These objects were: chair, duck, telescope, large plant, soccer ball, stove/range, piano, car, wheelbarrow, harp, and wooden well. Each object was easily detectable against the concrete wall and could be seen in a single view. As Fig. 2 illustrates, basic concrete texture was used for the walls of the maze, and the sky was displayed as a flat light blue without clouds or a central light source to eliminate possible use of directional cues.

Fig. 1 VR training maze (a) and dual solution paradigm maze (b) structure modeled after Marchette et al. (2011). The starting location is marked with text, while the arrows indicates the direction of travel. Black diamonds represent local landmark locations. Participants never saw the overhead representation Full size image

Fig. 2 Examples of views of the environment that a participant saw in the (a) timer condition of Experiment 1 and (b) in the distal landmark condition of Experiment 2 Full size image

Psychometric measures of spatial ability

The Money Road Map test (MRM; Money, Alexander, & Walker, 1965) presented participants with a bird’s-eye view of a street network map with a single dotted line marking a navigator’s path. Participants were told to imagine travelling this path and mark “R” or “L” to indicate a left or right turn at each corner. Participants were given 30 s to mark as many turns as possible (out of 32), in order of the path, without turning the sheet. The Spatial Orientation Test (SOT; Hegarty & Waller, 2004) presented participants with an array of objects above an arrow circle. Text above the arrow circle instructed participants to imagine standing at one object while facing a second and then pointing to a third object in the array (e.g., “Imagine you are standing at the cat, facing the tree, point to the flower”). Participants were required to draw a line from the center of the arrow circle to the edge of the circle to indicate the designated relationship. The SOT consisted of 12 trials with a maximum time limit of 5 minutes. The measure of performance was the angular error averaged across trials. Incomplete trials were assigned an angular error of 90 degrees (chance performance).

Self-report measures

The Santa Barbara Sense of Direction Scale is a self-report measure of environmental spatial abilities (Hegarty, Richardson, Montello, Lovelace, & Subbiah, 2002). Participants are provided 15 statements such as “I very easily get lost in a new city” and rate their agreement with each on a scale of 1 to 7. in which 1 is strongly agree and 7 is strongly disagree. The Lawton Wayfinding Strategy Scale (WSS; Lawton, 1994) asks participants to consider a recent trip they have taken to answer questions about how they approached navigation. The first two subscales separately assess orientation and route strategies, while the third scale assesses spatial anxiety. A 1 to 5 scale is provided, where 1 is extremely not typical of me and 5 is extremely typical of me. Finally, participants were asked to report on their video-game experience (none, little or some, moderate, a lot).

Procedure

After giving informed consent, participants were given the opportunity to practice with the active navigation controls (keyboard and mouse) within the VR training maze (see Fig. 1a) until they indicated they were comfortable with the controls. In the learning phase of the DSP (Fig. 1b), participants were asked to follow red arrows on the ground to navigate the maze, while taking note of the objects that they passed. An invisible wall blocked each corridor that was not on the learned path, but the view of the corridor was not obscured. Participants followed the route five times. Following a 30-second break, participants were given instructions for the testing phase. Participants were placed in different locations along the learned route and were asked to navigate to another location within the maze. For example, in one trial, the person was placed near the wooden well and had to navigate to the stove (see Fig. 3). There were 24 total trials. Twelve trials were “shortcut available” trials, in which there was a shortcut (i.e., a path to the goal that was shorter than the learned route), six were “shortcut equivalent” trials, in which the shortest novel path and the learned route were equivalent in length. The final six trials served as catch trials, in which the learned route was actually the shortest path to the goal location.

Fig. 3 Representative trial of each major category code. Note. a shortcut, b shortcut liberal, c learned, d learned liberal, e reversed learned, f wandering. Dotted line indicates the initially learned path. Black diamonds indicate the locations of landmarks in the environment Full size image

For half of the participants, a countdown timer of 60 seconds was presented in the top right of the screen (see Fig. 2a). A trial ended when the participant reached the goal location or when 60 s elapsed, whichever was sooner. The other half of the participants did not see a timer, nor did the trial end at 60 seconds, but we only analyzed their performance within the first 60 s.Footnote 2

Next, participants were administered the Money Road Map Test (MRM), the Spatial Orientation Task (SOT; Hegarty & Waller, 2004), the Santa Barbara Sense of Direction Scale (SBSOD; Hegarty et al., 2002), the Lawton Wayfinding Strategy Scale (WSS), including the spatial anxiety component (Lawton, 1994), and asked to rate their video-game experience. After completion of all tasks, participants were debriefed and dismissed.

Coding

A preliminary coding of the DSP navigation retrieval trials by two raters (blind to gender of the participants) revealed four strategies: taking a shortcut, taking the learned route, reversing the learned route, and wandering (repeating sections of the route until the goal was eventually found). Small deviations from the shortest path, learned routes, and reverse learned routes were allowed in a liberal coding scheme. For example, if a participant primarily followed the learned path but near the target landmark had a minor deviation from this path, that trial was coded as a liberal learned route. Figure 3b and d present examples of these categories. Interrater reliability was high (k = .96, p < .001).

This initial coding scheme was then used to formalize the liberal coding scheme mathematically, with the general criteria that a shortcut was shorter than the learned route and had little overlap with the learned route. A shortcut was defined as a path that is no more than 84% the length of the learned route and in which less than 70% of the path taken was on the learned route. The mean length of trials coded as shortcuts was 64% of the learned route, and the average overlap of the shortcuts with learned route was 39%. Trials were coded as following the learned route if participants traversed 70% or more of the learned route; on average, trials classified as learned route overlapped this route by 80%. Similarly, trials coded as reversing the learned route overlapped this route by at least 70% and by 87% on average. Trials were classified as “wandering” when a major section of the participant’s route was repeated, so that the route taken was longer than the learned route. Finally, trials that did not meet any of these criteria were classified as uncodable.

As in previous research, we computed a single, solution index measure (SI; Furman et al., 2014; Marchette et al., 2011), which takes account of the number of shortcut trials divided by the sum of shortcuts and learned routes (including liberally coded trials) and produces a number on a scale of 0 (indicating all learned routes) to 1 (indicating all shortcuts). Reversals of the learned route and wandering were not considered in computing this index.

To assess navigation efficiency, time and distance travelled to the goal location on trial were computed for each trial, then Z-score transformed and averaged across all shortcut available trials for each participant. This measure weights all trials equally and expresses navigation efficiency relative to other participants. There was a strong correlation between the distance and time efficiency measures, r(66) = .98, p < .001; therefore, we adopted time to find the goal as our measure of efficiency. Results do not differ if we use distance taken to the goal location.

Results

Sex differences in ability and self-report measures

Table 1 presents descriptive statistics for the psychometric and self-report measures. As expected based on previous research with these measures (Tarampi, Heydari, & Hegarty, 2016), males produced lower error scores than females on the SOT, t(66) = 2.02, p = .05, and outperformed females on the MRM, t(66) = 3.09, p = .003. There was a nonsignificant trend such that males reported better sense of direction than females, t(66) = 1.80, p = .08 (cf. Hegarty et al., 2006). Consistent with previous research (Lawton, 1994, 1996), females were more likely than males to indicate use of route-based strategy on the WSS, t(66) = 3.75, p < .001, and females reported more spatial anxiety than males, t(66) = 2.33, p = .02. However, no differences were found between males and females for self-reported use of the orientation strategy, t(66) = 1.40, p = .17. Finally, males (M = 3.14, SD = 1.79) reported playing video games more frequently than females (M = 1.83, SD = 1.01), t(66) = 5.15, p < .001.

Table 1 Descriptive statistics for the paper-and-pencil measures in each experiment Full size table

Navigation performance

Successful navigation to the goal location occurred on 98.6% of the 12 shortcut-available trials. A strict coding of the main strategies as shortcut or learned route accounted for over half of the trials (mean of 6.99 out of 12). Including liberal coding, an average of 4.81 of the 12 paths were coded as shortcuts, 2.96 were coded as learned routes, and 2.25 were coded as reversed learned routes. In addition, 1.44 of the 12 trials were coded as wandering and an average of 0.54 of the 12 trials, that is, 4.5% of trials were uncodable.

As seen in Fig. 4, based on the SI measure, participants showed a wide range of strategy preference, ranging from always taking learned routes to always taking shortcuts (M = .61, SD = .30; range = .08–1.00) as in previous research on this task (Marchette et al., 2011).

Fig. 4 Histogram of solution index of Experiments 1 and 2. Note. Values closer to zero indicate use of learned routes, whereas values closer to one indicate use of shortcut routes Full size image

Sex differences in solution index and navigation efficiency

As predicted, males (M = .72, SD = .29) showed a significantly greater preference for shortcuts than females (M = .54, SD = .25), t(66) = 2.70, p = .009, d = .66.Footnote 3 As predicted, sex differences were also found in efficiency such that males (Z-score M = −0.27, SD = .43) took less time to reach the goal than females (Z-score M = .19, SD = .51), t(66) = 3.93, p < .001, d = .98. Efficiency correlated with SI such that those who took more shortcuts reached the goal faster, r(66) = −.56, p < .001. To assess whether the difference in efficiency was due to differences in strategy as measured by the SI, a univariate ANCOVA was carried out comparing the efficiency of males and females while controlling for navigation preference using SI. There was a significant effect of sex on efficiency such that males were more efficient than females, even after controlling for navigation preference (SI), F(1, 65) = 7.92, p = .006, η p 2 = .11. This indicates that sex difference in efficiency was not only due to solution strategy as measured by the solution index.

Sex differences in route selection

Figure 5 plots the average number of shortcuts, learned routes, reversed learned routes, and wandering trials taken by males and females. To test for differences between males and females for each strategy, Mann–Whitney U tests were conducted, with alpha adjusted for multiple comparisons using Bonferonni correction (p = .0125). As predicted, males traversed significantly more shortcuts than females, U = 355.50, p = .01, d = .67, and females traversed significantly more learned routes than males, U = 361.00, p = .01, d = .54. No sex differences were found for reversing the learned route, U = 495.50, p = .41. Interestingly, there was a trend for females to wander more than males, U = 355.50, p = .06, d = .57. Specifically, 28 females wandered on at least one trial (average of 2.5 trials), while 17 males wandered on at least one trial (average of 1.65 trials).

Fig. 5 Route selection coding by sex in each experiment. Error bars show the standard error of the mean Full size image

Correlations of strategy and efficiency with psychometric measures

Correlations of strategy and efficiency with the psychometric measures are shown in Table 2. Of the two measures of perspective taking, only the MRM test correlated with SI, such that participants with better perspective-taking ability took more shortcuts. Participants who reported route-based strategies on the WSS also took more learned routes in the DSP, providing limited evidence that self-report measures are consistent with objective measures of navigation strategy. However, SI does not reliably correlate with other self-report measures of strategy or with SBSOD. In contrast, ability measures correlated significantly with measures of efficiency. Specifically, participants with a better self-reported sense of direction and better perspective-taking ability (as measured by both the MRM and SOT tests) took less time to reach the goal locations, and participants who reported using route strategies in everyday life were less efficient.

Table 2 Correlation of dependent measures with individual difference measures in each experiment Full size table

Discussion

Experiment 1 provides objective evidence for a reliable sex difference in strategy in the DSP whereby males took significantly more shortcuts, and females were more likely to take learned routes. Further, Experiment 1 indicated large sex differences in navigation efficiency (measured by time to travel to goal locations and directness of travel). The sex difference in efficiency was somewhat related to differences in strategy as measured by the solution index (SI); however, SI did not account for all of the variance in efficiency. Moreover, although efficiency in finding the goal location had reliable correlations with psychometric measures of strategy and ability, the solution index measure, which takes account of shortcuts and learned routes, provided only limited evidence that self-reports of navigation strategy are related to objective measures of strategy.