Global measures

To examine differential processing across the entire paragraph as a function of the four reading conditions, two global measures were analyzed: overall reading speed (as measured by the average number of words per minute (WPM)) and comprehension accuracy. WPM measurements that were more than two standard deviations above the participant’s mean were removed from data analyses. This resulted in the elimination of 3.7% of the data in this measure. Table 1 presents the means for these global measures as a function of spacing condition and spacing usage.

Table 1 Mean Reading Speed and Comprehension Accuracy as a Function of Spacing Condition and Spacing Usage Full size table

Global measures were analyzed using a mixed effects regression model from the lmerTest package (Kuznetsova, Brockhoff, & Christensen, 2015) within the R environment for Statistical Computing (R Development Core Team, v. 3.2.0, 2015. A full random structure was initially specified for subjects and items, but when this model did not converge, the final model used was one that included random intercepts (but not slopes) for subjects and items. Period spacing type (1 vs. 2) and comma spacing type (1 vs. 2) were effect coded (where paragraphs with 1 space following punctuation marks were coded as -.5 and paragraphs with 2 spaces following punctuation marks were coded as .5) and entered as fixed effects. In addition, the participant’s period spacing usage as measured by the typing task was also effect coded (where “one-spacers” were coded as -.5 and “two-spacers” were coded as .5) and included in the model as a fixed effect. The interactions between these fixed effects were also included in the model.

In the analysis of reading speed, although there was not an overall significant effect of period spacing (β = 3.10, SE = 2.20, t = 1.41, p = .160) or typing condition (β = 17.62, SE = 18.85, t = 0.94, p = .354), there was a significant effect of comma spacing (β = -4.99, SE = 2.19, t = -2.27, p = .023) such that readers read paragraphs faster when they were written with only one space after the commas, as is the common convention. Notably, there was also a significant three-way interaction among the fixed effects (β = -23.24, SE = 8.88, t = -2.62, p = .009). Although the type of spacing following punctuation marks did not seem to have an effect on those individuals who type with one space after a period, those who type with two spaces after a period had greater reading speed when paragraphs were presented in the same way in which they type: with two spaces following periods and one space following commasFootnote 1. See Figure 1 for a graphical representation of this interaction.

Fig. 1 Paragraph reading speed as a function of spacing condition and spacing usage. Error bars represent the standard error of the mean for each condition Full size image

Comprehension accuracy was high across all participants (M = 89%; range = 79% to 100%) and did not differ as a function of period spacing (β = -.237, SE = .237, z = -.997, p = .319), comma spacing (β = -.298, SE = .237, z = -1.26, p = .209), or the participant’s period spacing usage (β = .241, SE = .236, z = 1.02, p = .309). Furthermore, none of the interactions were statistically significant (all ps > .362).

Local measures

One benefit to recording eye-movements is that we are able to capture online processing, thereby evaluating the time course of processes as they unfold (Rayner, 1998, 2009). In order to more fully examine the effect of spacing following punctuation on reading, we analyzed local measures of processing on the two-word region surrounding each of the manipulated punctuation marks. That is, the target regions included the word immediately preceding the punctuation, the punctuation mark itself, and the word immediately following the punctuation.

For the local measures, regions where the participant blinked or the eye-tracker lost track of the participant’s eye on the two words preceding or following the period/comma were removed from data analyses. In cases where there were two fixations on adjacent letters and one of the fixations was extremely short (less than 80 ms), the two fixations were pooled. Extremely short isolated fixations (those less than 80 ms) and extremely long fixations (those greater than 1000 ms) were eliminated from the data prior to analyses. These trimming procedures resulted in the elimination of 8.68% of the data.

Dependent measures that were analyzed included early measures of processing (specifically, the probability of skipping the target region, the first fixation duration on the region, the first pass reading time on the region before leaving it, and the number of fixations made on the region during the first pass reading of it), and later measures of processing (specifically, the percentage of regressions made back into the region after leaving it and the total time spent on the target region including any regressions made back to it).

Effects near the period

Effects seen in the two-word regions near the periods were analyzed using linear mixed effects regression models from the lmerTest package (Kuznetsova et al., 2015) within the R environment for Statistical Computing (R Development Core Team, v. 3.2.0, 2015). Again, a full random structure was initially specified for subjects and items, but when this model did not converge, the final model used was one that included random intercepts (but not slopes) for subjects and items. Period spacing type (1 vs. 2) was effect coded (where paragraphs with 1 space following periods were coded as -.5 and paragraphs with 2 spaces following periods were coded as .5) and entered as a fixed effect. The participant’s period spacing usage as measured by the typing task was also effect coded (where “one-spacers” were coded as -.5 and “two-spacers” were coded as .5) and included in the models as a fixed effect, along with its interaction with period spacing. Fixation duration measures were positively skewed and were thus log transformed prior to analyses. The two binary dependent measures (e.g., skipping rate, regressions in) were analyzed using mixed-effects logistic regression, with the same random and fixed effects.

The effects of period spacing from these mixed effects analyses are presented in Table 2. Across all of the early measures, there was a significant effect of period spacing. Paragraphs written with two spaces following each period led to greater skipping rates, shorter first fixation durations, shorter first pass times, and fewer first pass fixations compared to paragraphs written with only one space following each period. There were also significant effects seen in later measures; paragraphs written with two spaces following each period led to shorter total fixation durations compared to paragraphs written with one space following each period. There was, however, no significant effect seen in the percentage of regressions made back to the target region. There was not a significant difference in eye movement measures between “one-spacers” and “two-spacers” (all ps > .091), nor did typing preference interact with the period spacing effect (all ps > .315).

Table 2 Means (and Standard Deviations) on the Period Region as a Function of Period Spacing Full size table

Effects near the comma

Effects seen in the two-word regions near the commas were also analyzed using mixed effects regression models using the same structure of fixed and random effects used when analyzing the two-word regions near the periods. Fixation duration measures were again positively skewed and were thus log transformed prior to analyses. The effects of comma spacing from these mixed effects analyses are presented in Table 3. In the early measures, there was not a significant effect of comma spacing on the fixation duration measures nor on the number of first pass fixations that readers made, although there was a trend for readers to spend less time on target regions when there were two spaces following the commas. The effect of comma spacing was also not significant across any of the later measures.

Table 3 Means (and Standard Deviations) on the Comma Region as a Function of Comma Spacing Full size table

First pass times in the comma region were significantly longer (β = -0.099, SE = .043, t = -2.32, p = .024) for those who were identified as “one-spacers” during the typing task (M = 311, SD = 188) than for “two-spacers” (M = 276, SD = 166). Similarly, more first pass fixations were made in the comma region (β = -0.124, SE = 0.061, t = -2.05, p = .045) by “one-spacers” (M = 1.07, SD = .81) than by “two-spacers” (M = .94, SD = .76). There were no other differences between these two typing groups in any other measure (all ps > .102). Finally, there was a two-way interaction in the skipping measure (β = -0.341, SE = 0.132, z = -2.59, p = .010) such that while “one-spacers” were more likely to skip the target region if it had two spaces after the comma (M = 24.6%, SD = 43.1%) than if it only had one space after it (M = 20.3%, SD = 40.3%), “two-spacers” were less likely to skip the target region if it had two spaces after the comma (M = 26.4%, SD = 44.1%) than if it only had one space after it (M = 27.6%, SD = 44.7%). None of the other two-way interactions were significant (all ps > .103).