In Experiment 1, we presented native Chinese readers with Chinese sentences in four different spacing conditions (see ). In the control condition the text was presented in normal unspaced format with each Chinese character immediately adjacent to its neighbors. In the single character spaced condition, we inserted a space between every character. In the word spaced condition, we inserted a space between groups of characters that formed a word. To confirm that the Chinese readers would agree on the word boundaries, we required 12 Chinese readers who did not participate in the main experiment to indicate the word boundaries within the sentences. This reliability prescreen produced 95% agreement among participants, and word spacing was manipulated accordingly. Finally, in the nonword spaced condition, spaces were inserted between characters such that the resulting groups of characters formed nonwords.1
If the introduction of spaces between words facilitates reading, then reading times for sentences under word spaced conditions should be shorter than under the normal unspaced, single spaced, and nonword spaced conditions. Of particular interest was whether the global measure of sentence reading times under word spacing conditions would be shorter than reading times under normal, unspaced conditions. We anticipated that this comparison would be informative with respect to the first of the theoretical questions that we set out to address: whether the introduction of spaces into Chinese text might facilitate reading (as with the Kohsom and Gobet, 1997
, study with Thai).
Figure 1 Example Chinese stimuli from the four spacing conditions used in Experiment 1. Under normal conditions the characters were presented in an unspaced format. Under single character spacing, a space was inserted between every character of the sentence; in (more ...)
We also anticipated that differences in sentence reading times might allow us to address our second important theoretical question: whether words or characters are the primary unit of information in Chinese reading. We predicted that if characters are the primary unit of information in Chinese reading, then sentence reading times would be shorter under the single character spacing condition than under the word spacing condition. Conversely, if words are the primary unit of information, then the opposite pattern should be obtained. Additionally, sentence reading times for these conditions in relation to normal unspaced text would be informative of the degree to which reading was facilitated or hindered relative to reading under normal conditions.
In addition to the sentence reading times under each condition, we anticipated that there might be differences in the precise mechanics of oculomotor control under the different spacing conditions. Given that the text is more or less spatially extended, as well as differentially spatially grouped under each of the spacing conditions, we assumed that we might observe differences in a number of other global measures such as average fixation durations, numbers of fixations and saccade sizes, as well as local measures computed for individual target words or characters that we identified in the sentences under different spacing conditions in the experiment.
Sixteen undergraduate students at Tianjin Normal University participated in the experiment.2
They were all native speakers of Chinese who were skilled readers with normal or corrected-to-normal vision. They were all naive regarding the purpose of the experiment.
Materials and design
Sixty Chinese sentences were constructed. The sentences were all between 19 and 23 characters in length (M = 20.83 characters). The experimental sentences were rated on a 9-point scale for their naturalness by 30 participants who did not take part in the eye-tracking study. The mean naturalness score was 2.04 (where a score of 1 was very natural). We included four spacing conditions in the experiment: normal spacing, single spacing, word spacing, and nonword spacing (see ).
Four files were constructed, with each file containing 60 sentences. There were 15 sentences in each condition, and conditions were rotated across files according to a Latin square. Sentences in each condition were presented in a blocked format, and the order of the sentences in each block was random. Sixteen practice sentences, four for each spacing condition, were included at the beginning of each experimental file. In addition, there were 20 filler sentences (five in each condition) that appeared randomly throughout the block. After each of these filler sentences, a yes/no comprehension question was presented.3
In total each participant read 96 sentences.
Participants’ eye movements were recorded with an SR Research (Osgoode, Ontario, Canada) EyeLink II eye tracker (location; sampling rate = 500 Hz) that monitored the position of the right eye every 2 ms. This system is accurate to 0.5° visual angle. The stimuli were presented on a 19-in. (48.3-cm) DELL monitor with a 1,024 × 768 pixel resolution. The distance between the participant and the screen was 75 cm. Stimuli were presented in Song font, and the size of each Chinese character was 21 × 21 pixels (with a space of 1 pixel between characters in the unspaced condition). One Chinese character subtended 0.63° visual angle.
Each participant was tested individually. Participants were informed that they would read sentences in which the characters would be presented under different spacing conditions. They were told that they were required to read the sentences and understand them to the best of their ability. When they completed reading a sentence, they pushed a button box to terminate the display. They were instructed that occasionally a comprehension question would appear after a sentence and that they should try hard to answer the question correctly. Participants gave answers to the comprehension questions orally, and their answers were noted by the experimenter. Although the EyeLink tracker compensates for head movements, a chin rest was used to ensure that the head was maintained in a still position. Prior to the start of the experiment, a calibration procedure was completed, and the computer software calculated the position of the point of fixation on the basis of the calibration. After a successful calibration, the sentences were presented in turn. Calibration was checked after each trial, and participants were recalibrated whenever necessary. In total the experiment took approximately 20 min.
The overall comprehension rate was 92% indicating that participants read and fully understood the sentences. Three of the participants accidentally triggered the button box prematurely terminating the display for four of the sentences and therefore no data were obtained for these trials. We also excluded trials on which tracker loss occurred, as well as any first fixation durations that were less than 80 ms or greater than 1,200 ms. All the eye movement measures above or below three standard deviations from the mean were also excluded. In total 5.1% of the data was removed prior to conducting the analyses.
Below we provide two sets of analyses. In the global analyses we conducted analyses of different measures of eye movement behavior based on all the fixations made as each of the sentences was read under each of the experimental conditions. We computed the mean fixation duration, mean saccade length, number of forward saccades (i.e., saccades made in a left-to-right direction), number of regressive saccades (i.e., saccades made from right to left), total number of fixations, total sentence reading time (i.e., the sum of all the fixations and saccades made during sentence reading), and reading speed (see ).
Global Eye Movement Measures for Unspaced, Single Spaced, Word Spaced, and Nonword Spaced Conditions in Experiment 1
In addition to the global analyses, we conducted four sets of local analyses based on only a proportion of the fixations that were made as the sentences were read. For these analyses we computed first fixation duration (the duration of the first fixation on a word), single fixation duration (the duration of fixations when only one fixation is made on a word), gaze duration (the sum of all fixations on a word before moving to another word), total fixation time (the sum of all fixations on a word, including regressions), number of first pass fixations, and total number of fixations. In order to carry out these analyses we selected smaller regions of the sentences that were of particular interest under particular spacing conditions. Below, we first report the global analyses followed by the local analyses.
A repeated measures analysis of variance was carried out for the variable presentation condition with four levels (normal unspaced, single character spacing, word spacing, nonword spacing) using participants (F1) and sentences (F2) as random effects. The mean fixation duration, the mean saccade length, the number of forward saccades, the number of regressive saccades, the total number of fixations, the total sentence reading time, and the reading speed are given in .
For mean fixation duration there was a significant effect of presentation condition, F1
(3, 45) = 35.9, p
< .001; F2
(3, 177) = 38.3, p
< .001. To establish which conditions differed from each other we conducted paired t
tests. Mean fixation durations were longer under normal spacing conditions than under single character, word spacing, and nonword spacing conditions (all p
s < .001). Also, mean fixation durations were longer under word and non-word spacing conditions than under single spacing conditions (all p
s < .001). Finally, mean fixation durations did not differ between word and nonword spacing conditions (p
s > .05). The results show very clearly that readers made longer fixations under normal unspaced conditions relative to all the other conditions. This result may initially appear surprising in that increased fixation times are usually taken to indicate increased processing difficulty (Liversedge & Findlay, 2000
; Rayner, 1998
). However, as seen in , there was a trade-off between fixation duration and number of fixations so that while fixations were longer in the normal unspaced condition readers also made fewer fixations. Thus, it is perhaps most helpful to consider the fixation duration data in relation to the total reading time data presented below.
For mean saccade lengths there was a highly reliable effect of presentation condition, F1(3, 45) = 148.6, p < .001; F2(3, 177) =140.7, p < .001. Unsurprisingly, mean saccades were shortest under the normal spacing conditions, somewhat longer under non-word spacing conditions, longer again under word spacing conditions, and longest under the single character spacing condition (all differences reliable, ps < .001). The main point to note from these results is that saccade length varied in relation to how horizontally distributed the text was. The Chinese characters are most densely packed under unspaced conditions; are horizontally, spatially distributed to a greater degree under word and nonword spacing conditions; and are most distributed under the single character spacing condition. Notably, the reliably shorter saccades under nonword spaced conditions compared with word spaced conditions might reflect increased processing difficulty under the nonword compared with the word spaced conditions.
Next we considered the number of forward saccades and again found reliable effects of presentation condition, F1(3, 45) = 42.2, p < .001; F2(3, 177) = 45.4, p < .001. Readers made the least number of progressive saccades in the normal unspaced condition, slightly more under the word spaced condition, more again under the nonword spaced condition, and the most under the single spaced condition. The data for each condition were reliably different from the data in all the other conditions (all ps < .01). Presumably, readers made the most forward saccades for text with single character spacing because the text is most horizontally distributed in this condition. As with the saccade length data, the difference we observed between the data for the word and non-word spacing conditions may reflect increased processing difficulty associated with processing Chinese text when it is segmented as nonwords relative to when it is segmented as words. Finally, readers made fewest forward saccades for normally presented text both because it is easiest to read and the least horizontally distributed.
The effect of presentation condition was also reliable for the total number of fixations, F1(3, 45) = 26.4, p < .001; F2(3, 177) = 28.5, p < .001. Readers made fewest fixations when reading text presented normally, numerically more when reading word spaced text (ps < .05), and substantially more when either reading text presented as nonwords or text presented under single character spacing conditions (ps < .01). There was no difference in the total number of fixations readers made when reading text under non-word and single character spacing conditions (ps > .05). These results suggest that for the total number of fixations the data from the word spacing condition pattern were similar to the data from the normal spacing condition. In contrast, the data from the non-word spacing condition pattern were similar to those from the single character spacing condition. Assuming that the total number of fixations provides an index of the overall difficulty that the participants experienced as they read the sentences, then these data are at least suggestive that readers found the text presented under word spacing conditions almost as easy to read as the text presented under normal unspaced conditions. The data also suggest that single character spacing and nonword spacing conditions were much more disruptive to processing than were word spaced and normal unspaced text.
We also considered the number of regressive saccades that participants made as they read the sentences. As before, we observed a highly reliable effect of presentation condition, F1(3, 45) = 8.1, p < .001; F2(3, 177) = 11.4, p < .001. Readers made fewest regressions for text presented normally and slightly more when text was presented under word spacing conditions (ps<.05). There was no reliable difference in the number of regressions made under word and single character spacing conditions (ps > .05), however, readers made reliably more regressions under non-word conditions than under word conditions (ps < .05). There was no reliable difference in the number of regressions readers made under nonword conditions compared to single character spacing conditions. The pattern of results for the regression data is similar to that obtained for the total number of fixations. Readers made fewest regressions when text was presented normally and made the most regressions when text was presented under nonword spacing conditions.
Finally, we considered the total reading times for the sentences under each of the spacing conditions. Total sentence reading times are an extremely important measure with respect to the first (and perhaps also the second) theoretical question that we set out to address. This measure provides us with an indication of how long, overall, it took readers to read the sentences under the different spacing conditions. Additionally, on the basis of the total reading times and the mean number of characters in a sentence together, we present reading rates (in terms of characters per minute) for each of the conditions. As with the measures reported earlier, total sentence reading times showed a reliable effect of presentation condition, F1(3, 45) = 5.7, p < .01; F2(3, 177) = 5.7, p < .01. The pattern of effects is extremely informative regarding the ease with which processing occurred. Total reading times were shortest and approximately the same for the text presented in the normal unspaced and word spaced conditions (ps > .05). By contrast, total reading times for text under the nonword spacing condition were reliably longer than for text under both the normal unspaced condition and the word spaced condition (ps < .01). However, total times for text presented under nonword and single character spacing conditions were not reliably different (ps > .05).
These data show that the presentation of text using nonword spacing caused disruption to processing such that the time to read the sentences was substantially increased relative to all the other conditions. A second important aspect to note from these data is that text presented with word spacing was as easy to read as normal unspaced text. These data are directly relevant to the first theoretical question that we set out to address in this experiment, namely, whether the introduction of word space information into Chinese text would facilitate reading. While the introduction of spaces to demark word boundaries did not facilitate reading relative to that for text presented in the usual unspaced format, it also appears that word spacing information did not disrupt processing to any great degree. In contrast, single character and nonword spacing did induce disruption relative to normal unspaced text.
In addition to the global analyses, we conducted a series of local analyses in which we considered smaller regions of the sentences that comprised directly comparable characters that formed words or nonwords under different spacing conditions. These analyses are potentially important because they provide an opportunity for us to compare the different conditions when the difference in spatial arrangement of the characters is not as great as it is in the global analyses. For each Chinese sentence we identified between one and four regions that comprised two characters (except for the fourth set of local analyses in which single characters were compared). We ensured that our regions never occurred at the beginning or the end of the sentences (thereby avoiding any contamination from fixations associated with the onset or completion of reading). Each of the different comparisons that were undertaken is illustrated in .
In the first set of local analyses we compared measures for regions that comprised two Chinese characters and a space under word and nonword spacing conditions. The characters always formed a word, but the space either occurred between the characters in the nonword spacing condition or it occurred after the two characters in the word spacing condition. The inclusion of the space in the region of analysis allowed us to compare regions of the sentence that were identical in terms of physical size and content as well as spatial layout.
First fixation durations showed a marginal effect of spacing, t1(15) = 1.83, p = .09; t2(59) = 1.73, p = .09, with shorter initial fixation durations for nonword spacing (231 ms) than for word spacing conditions (240 ms). In fact, we had anticipated that first fixation durations would actually be longer under nonword than word spacing conditions, and it is not immediately clear exactly why the effect went in the opposite direction. It is possible that participants may have curtailed their initial fixation on the character string more quickly when the string under fixation was a nonword than when it was a word. The single fixation and gaze duration measures, along with the number of first pass fixations, showed no influence of spacing (all ts < 1.5, all ps > .05). However, as anticipated, there was a reliable influence of spacing on the total fixation time, t1(15) = 3.78, p < .01, and t2(59) = 2.70, p < .01, and the total number of fixations, t1(15) = 3.61, p < .01, and t2(59) = 3.46, p < .01, with longer total fixation times and a greater total number of fixations under nonword spacing conditions (483 ms and 2.2 ms, respectively) than under word spacing conditions (427 ms and 1.9 ms, respectively). Consistent with the global measures, these data show that readers experienced greater disruption to processing under nonword spacing conditions than under word spacing conditions.
In the second set of local analyses we again compared regions comprising two characters and a space, where the two characters always formed a word. However, for these analyses the words were presented under single character and nonword spacing conditions. For first fixation and single fixation duration there were no reliable effects (all t
s < 1.76, all p
s > .05). However, gaze durations were longer, t1
(15) = 4.51, p
< .001, and t2
(59) = 4.65, p
< .001, and number of first pass fixations greater, t1
(15) = 2.66, p
< .05, and t2
(59) = 2.59, p
< .05, for nonword spacing conditions (312 ms and 1.35 ms, respectively) than for single character spacing conditions (272 ms and 1.26 ms, respectively). Similarly, total fixation times were longer, t1
(15) = 4.34, p
< .001, and t2
(59) = 5.69, p
< .001, and total number of fixations greater, t1
(15) = 3.75, p
< .01, and t2
(59) = 4.48, p
< .001, for nonword spacing conditions (483 ms and 2.15 ms, respectively) than for single character spacing conditions (394 ms and 1.83 ms, respectively).4
These results clearly indicate that the introduction of spacing into Chinese text was much more disruptive to processing when the spacing information produced groups of characters that formed nonwords than when it did not. Nonword spacing produced disruption to reading for Chinese text relative to single character spacing.
For the third set of local analyses we compared measures for words under normal unspaced and word spaced conditions. While there was no significant difference between first fixations on words in normal unspaced and word spaced conditions (ts < 1.77, ps > .05), all of the other measures showed reliable or very marginal effects. There was a difference for single fixation durations that was reliable by participants but not by items, t1(15) = 2.16, p = .05; t2(58) = 1.57, p > .05. Single fixation durations were numerically longer for normal unspaced text (258 ms) than for word spaced text (243 ms). A similar pattern occurred for gaze durations, t1(15) = 3.1, p < .05, and t2(59) = 2.92, p < .01, and number of first pass fixations, t1(15) = 1.9, p = .08, t2(59) = 2.05, p < .05, as well as for the total fixation times, t1(15) = 3.41, p < .01, t2(59) = 4.06, p < .01, and the total number of fixations, t1(15) = 2.71, p < .05; t2(59) = 3.15, p < .01. Gaze durations and total fixation times were longer under normal unspaced conditions (297 ms and 440 ms, respectively) than under word spaced conditions (272 ms and 379 ms, respectively). Similarly, there were more first pass fixations and total fixations for normal unspaced text (1.23 and 1.83, respectively) than for word spaced text (1.17 and 1.63, respectively).
Total fixation times were longer and participants made more fixations when the text was presented in the normal unspaced format that was most familiar to Chinese readers than in the comparatively unfamiliar word spaced format. On the assumption that readers make more, shorter fixations when reading is easier, then the local analyses suggest that the introduction of word spacing information facilitated reading of Chinese text. Recall also that in the global analyses average fixation durations were longer for normal unspaced than for word spaced text. Clearly, the direction of the effects obtained for the global analyses matches that obtained for the local analyses. Note also, however, that the total sentence reading times for the normal unspaced and word spaced sentences were approximately the same, and, correspondingly, participants also made more fixations on average under word spaced than normal unspaced conditions (regardless of whether those fixations were made after a progressive or regressive saccade). Thus, both the global and local measures together, along with the total sentence reading times, provide a very clear picture of the different patterns of eye movements that occurred under the normal unspaced and word spaced conditions. Readers took about the same amount of time overall to process word spaced and normal unspaced sentences, but they made more but shorter fixations when reading word spaced text than when reading normal unspaced text. What is clear is that presenting Chinese text in a visually unfamiliar format did not cause disruption to processing. We will consider why this pattern may have arisen in more detail below in the Discussion.
In the fourth and final set of local analyses, we compared single Chinese characters under the single character spacing condition and the nonword spacing condition. This analysis allowed us to investigate whether the introduction of nonword spacing caused disruption to processing of single Chinese characters compared with the introduction of characters per se (in the single character spacing condition). That is, we wished to determine whether there was a cost associated with segregating single Chinese characters such that they appeared as nonwords, relative to simply segregating all of the characters in the sentence. In this respect, our analyses showed convincingly that the introduction of nonword spacing increased reading times more than the introduction of spaces between all of the characters. Reading times were always numerically longer in the nonword spacing condition than in the single character spacing condition, though the effects were not consistently reliable by subjects and by items: for first fixation duration, t1(15) = 2.07, p = .06, and t2(49) = 1.41, p > .05; for single fixation duration, t1(15) = 2.74, p < .05, and t2(46) = 1.53, p > .05; for gaze duration, t1(15) = 2.22, p < .05, and t2(49) = 1.54, p > .05; for total fixation time, t1(15) = 2.43, p < .05, and t2(49) = 2.74, p < .01); first fixation durations, 220 ms and 205 ms; single fixation durations, 224 ms and 203 ms; gaze durations, 227 ms and 210 ms; and total fixation times, 286 and 245.
In evaluating the results for the normal unspaced and word spaced text, it is perhaps helpful to consider factors that may have exerted opposing influences on reading. The familiarity of the format in which the text was presented, as well as the extent to which word objects were demarcated by spaces, may both have affected the ease with which the text was processed. It seems reasonable to assume that a more familiar visual text format should produce shorter reading times than an unfamiliar format. Similarly, a second reasonable assumption may be that the clear demarcation of words by spaces will facilitate word identification and thereby produce shorter reading times relative to normal unspaced text for which word identification is more difficult. If these two assumptions are correct, then the influence of these two factors will be in opposition in the word spaced and the normal unspaced conditions in our experiment. The normal unspaced text will be extremely familiar, but word identification may be hindered due to poor word demarcation. In contrast, the word spaced text will be visually unfamiliar but word identification will be facilitated due to good word demarcation. It is perhaps not surprising, therefore, that total reading times for these conditions were approximately the same and that they are both somewhat shorter than for the single character spaced and the nonword spaced text.
While the results of Experiment 1 were quite straightforward, it is quite possible to argue that our findings are not as easily interpretable as we have suggested because of the natural confounding of condition by spatial layout in the experiment. That is, when spaces are inserted between characters, the resulting text will invariably be longer (more spatially distributed) than when no spaces are present. Exactly what this confounding may mean for the present results is not entirely clear. Therefore, we replicated the first experiment (using the same materials) but with a different manipulation in which we were able to create the same four conditions but the spatial distribution of the text was the same across the conditions. To do this, we used a highlighting manipulation (see ).
Example stimuli from the four conditions used in Experiment 2.