# Cognitive engagement and reading comprehension of French pupils aged between 9- and 11-Years old are influenced by task relevance: evidence from concurrent recordings of postural and eye movements

Ugo Ballenghein, Léa Lachaud

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Ugo Ballenghein, Léa Lachaud. Cognitive engagement and reading comprehension of French pupils aged between 9- and 11-Years old are influenced by task relevance: evidence from concurrent recordings of postural and eye movements. Reading and Writing: an interdisciplinary journal, 2024, 10.1007/s11145-024-10614-8. hal-04873213

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# Cognitive engagement and reading comprehension of French pupils aged between 9- and 11-Years old are influenced by task relevance: evidence from concurrent recordings of postural and eye movements

Ugo Ballenghein<fnref n="1" /> ID · Léa Lachaud<fnref n="1" /> ID

Accepted: 4 November 2024

© The Author(s) 2024

## Abstract

The *relevance effect* refers to the influence that instructions have on readers' attention and learning. The present study examined whether relevance influences elementary school students' reading comprehension and cognitive engagement. To measure the latter, eye movements and postural sway were recorded in 42 French speaking students aged 9.3–11.6 years. Eye movements were recorded with infrared-based eye-tracking glasses, and postural sway with an infrared-based motion capture system. Children read two texts, one task-relevant and one task-irrelevant, and answered surface and inference questions right after reading it. Results showed that children scored better on surface and inference questions about the relevant text than about the irrelevant one. As for eye movements, readers made more fixations on the relevant text and spent more time reading it. There was also less postural sway during the reading of the relevant text. These results indicate that cognitive engagement during reading is embodied in fourth- and fifth-grade students, with postural stability probably reflecting cognitive engagement and promoting the construction of meaning during reading tasks.

**Keywords** Cognitive engagement · Eye movements · Postural sway · Reading · Children

<figure><img src="image_3.png" /></figure>

<footnote>Ugo Ballenghein
ugo.ballenghein@u-pec.fr</footnote>

<footnote>Léa Lachaud
lea.lachaud@u-pec.fr</footnote>

<footnote n="1">¹ Human and Artificial Cognition (CHArt) Laboratory, University Paris Est Créteil, Bonneuil, France94380</footnote>
In the present study, we utilized a methodological combination of eye tracking and head movement recordings to inspect task-induced changes in cognitive engagement during reading comprehension in fourth- and fifth-grade students. Recently, Ballenghein et al. (2020, 2023) and Kaakinen et al. (2018) have shown that cognitive engagement in adult readers can be measured using eye and postural movements. More specifically, it was suggested that when readers were cognitively engaged in a reading task, this engagement was embodied by a reduction in postural sway while reading task-related passages. As such observations have not yet been examined in young readers, we were particularly interested in how elementary school students embody the cognitive demands of the reading task.

Reading comprehension is one of the most common skills used by students to acquire knowledge. It involves numerous and complex cognitive processes and can be defined as the ability to form a coherent mental representation of a text (Kintsch & Van Dijk, 1978; Linderholm et al., 2004). The most common way to assess reading comprehension is to ask several types of questions. Surface questions call for an answer that is explicitly given in the text, and inference questions ask readers to make connections with their own prior knowledge to fill in missing elements in the text (Cain & Oakhill, 1999). For elementary school students, inference making can be challenging. Oakhill et al. (2003) showed that younger students have difficulty drawing inferences, whereas older students do so more spontaneously. Current theories assume that during reading, readers try to create a coherent mental representation of the text, and the task they have in mind sets the standards of coherence to be maintained while reading (Linderholm et al., 2004). When reading to study rather than for pleasure, readers set themselves higher coherence standards and are more likely to invest cognitive effort in making connections with their prior knowledge in order to form coherent and meaningful mental representations (Van den Broek et al., 2001).

## Relevance effect in sreading

The term *relevance effect* refers to the influence the instructions have on readers’ attention and learning (McCrudden & Schraw, 2007). For example, having a reading perspective has been shown to have a significant impact on the ability to recall textual information (Baillet & Keenan, 1986). In this study, adult participants read three stories, adopting a different perspective for each one, and then had to recall each story from that same perspective. Results indicated that they recalled more information when it was relevant to the encoding perspective. It has been suggested that as the reader progresses through the text, text-related concepts and background knowledge are activated, reducing the cognitive demands of the reading task. Thus, Hyönä and Niemi (1990) proposed that it is possible for relevance effects to change during reading, and that greater cognitive effort may be required to recognize and encode relevant information in memory at the beginning of the text, and less effort may be required at the end of the text. This hypothesis has been supported by studies that have compared the reading of relevant and irrelevant information by aggregating observations over the whole text (Kaakinen & Hyönä, 2007, 2014; Kaakinen et al., 2002; McCrudden et al., 2010; McCrudden & Schraw, 2007). The results showed
that the pattern of eye movements can change over the course of a text, as the reader enters the reading flow, and that during the reading of a text, the average duration of individual fixations decreased as the reader progressed through the story.

Other studies have shown that when readers are asked to read texts that describe different countries while imagining that they must live in one of them, they recall more information about the country in which they have imagined living (Kaakinen & Hyönä, 2007; Kaakinen et al., 2002). In other words, the task instructions direct readers' attentional focus to task-relevant information that can be incorporated into their mental representation of the text, thereby allowing them to draw the necessary inferences (Van den Broek et al., 2001).

More recently, the RESOLV theoretical model conceptualized by Rouet et al. (2017) proposes a theoretical model considering both the construction and management of the reader's goals at the time of the text comprehension task. According to the authors, two types of mental models are constructed prior to the reading task: the context model, which depicts the representation of the physical and social context of reading, and the task model, which represents the set of goals that guide readers' decisions and actions during reading. According to this theoretical model, reading decisions and processes are guided by readers' perceptions and mental representations regarding the task statement (goals), but also by more implicit cues from the reading context. The reading task that the reader has in mind at the time of the task is decisive in allocating the cognitive resources needed to understand the text.

## Cognitive engagement

In educational psychology, learning in which students cognitively engage with the educational materials is referred to as *active learning* (Bonwell & Eison, 1991). Cognitive engagement has been studied using qualitative methods such as self-report scales in order to explore students' motivation (Greene, 2015) and determine whether variations in motivation reflect deep versus shallow processing (Graham & Golan, 1991). For their part, Rotgans and Schmidt (2011) found that the level of cognitive engagement during a problem-based learning task fluctuated according to the students' degree of autonomy. The more autonomous students were, the higher their subjective cognitive engagement.

In cognitive psychology, and more specifically in reading studies, the notion of cognitive engagement has yet to be clearly defined. For some authors, this multi-component concept corresponds to a process in which readers' cognitive resources are focused on the reading task and reflected in response times and physiological indicators (Blumenfeld et al., 2006; Sinatra et al., 2015) that can be measured on line, such as eye movements (Miller, 2015) and postural sway (Ballenghein & Baccino, 2018; Ballenghein et al., 2019, 2020; Kaakinen et al., 2018). More specifically, the empirical data yielded by these measures reflect attention, one of the main aspects of cognitive engagement (Ikehara & Crosby, 2005). Several studies among adults have shown that fixation duration and total reading time can be used as indicators of cognitive engagement during reading, as fixation duration and total reading time are longer during the reading of task-relevant versus task-irrelevant information and with
higher recall scores for relevant information (Ballenghein et al., 2020; Kaakinen et al., 2002, 2018). Kaakinen and Hyönä (2005) postulated that the extra time spent on relevant information reflects attempts to encode it in memory and construct a mental representation of the text.

Reading and postural control

Studies of postural control and its development in healthy children have shown that the process of postural regulation is not automatic and requires the implementation of several processes (Belenkii et al., 1967). Moreover, postural stability has been shown to improve with age until adolescence (i.e., about 13–14 years), suggesting that the brain structures responsible for postural control continue to develop through-out childhood (Assaiante, 2012; Barozzi et al., 2014). The body of literature on the effect of visual tasks on postural control indicates that postural movements can reflect cognitive engagement in adults (Balaban et al., 2004; Bonnet et al., 2017; Qiu & Helbig, 2012). When Bonnet and Baudry (2016) investigated the synergy between eye movements and posture, they found that a reduction in postural sway made eye movements more efficient during tasks that required high visual precision, such as target pursuits. Other studies have specifically examined the link between posture and reading processes, showing that when a reading task demands high cognitive engagement, in terms of the difficulty of the text or even the emotional nature of the stories to be read, readers move less (Ballenghein & Baccino, 2018; Ballenghein et al., 2019, 2020, 2023; Kaakinen et al., 2018). In line with these findings, Bucci et al. (2015) observed greater postural stability during a reading task compared with a target pursuit task in children aged 7–15 years. The authors attributed this result to the fact that reading is a complex task in which not only oculomotor, but also perceptual and semantic processes are activated. In addition, Chang et al. (2010) investigated the influences of two different suprapostural visual tasks (i.e., visual searching and visual inspection on paper) on the postural sway of children with and without autism spectrum disorder (ASD). The authors showed that although the children with ASD exhibited greater sway than their typically developing (TD) peers, both groups of children exhibited less postural sway during the search task than during the inspec-tion task. These results on paper indicate that TD children and children with ASD are able to functionally modulate postural sway to facilitate the performance of a highly demanding perceptual task.

In summary, reading comprehension requires readers to cognitively engage in the reading task, in order to memorize the information and successfully construct a mental representation of the text. Although recent studies have shown that physiological indicators such as eye movements or postural sway can be used to gauge cognitive engagement in adult readers (see Ballenghein et al., 2020, 2023; Kaakinen et al., 2018), very few studies have investigated the value of these metrics in child readers (e.g. Bucci et al., 2015; Chang et al., 2010).

The purpose of the present study was to examine the relevance effect on reading comprehension and cognitive engagement among fourth- and fifth-grade students. More specifically, we examined whether reading a task-relevant text promoted stu-
dents' memorization and comprehension of that text, and whether cognitive engagement was embodied and reflected in readers' postural sway. We predicted that task-relevant texts would induce higher surface and inference scores and would be more cognitively engaging than task-irrelevant texts. We expected these differences to be reflected in a longer fixation duration and reading time and reduced postural sway for the task-relevant texts.

# Material and method

## Participants

A power analysis using G\*Power 3 software (Faul et al., 2007) indicated that a total sample of 34 people would be needed to detect medium effects ($d=0.25$) with power (1 - $\beta$) set at 0.80 and $\alpha=0.05$ using an F test (repeated-measures within-factors ANOVA) for a main effect of relevance. Participants were 42 elementary school students (from 4th and 5th grade classes, which constitutes cycle 3 in France). Seven participants had to be excluded from the eye tracking and motion capture analyses, owing to technical problems during data collection. The final dataset therefore consisted of 42 participants for the comprehension test, and 35 participants for the eye-tracking and motion capture analyses.

Participants were French elementary school pupils ($M_{age} = 10.36$ years, $SD=0.64$; 15 male). They were all native French speakers with normal or corrected-to-normal eyesight (the students concerned wore their own glasses). We tested participants' reading skills using the Alouette-R Test (Lefavrais, 2005), which yielded reading time, number of words read, number of errors, number of correctly read words, an accuracy index, and a speed index. Time and accuracy results are typically used to analyze reading disorders, while speed and accuracy indices provide a percentage of success in terms of the number of words correctly read within the space of 3 min. Inclusion test analyses showed that all participants had normal reading skills (see Table 1).

The present study was carried out in compliance with French legislation, and all the participants' parents gave their written informed consent, in accordance with the Declaration of Helsinki.

<table><caption>**Table 1** Participants reading skills and reference data for fourth- and fifth-Grade Students according to Alouette-R Test (Lefavrais, 2005). Mean (SD)</caption><thead><tr><th></th><th>Fourth graders</th><th>Ref.<br>Fourth graders</th><th>Fifth graders</th><th>Ref.<br>Fifth graders</th></tr></thead><tbody><tr><td>Reading time</td><td>158.17 (26.58)</td><td>171</td><td>169.19 (22.07)</td><td>159</td></tr><tr><td>Words read</td><td>208.06 (55.68)</td><td>211</td><td>214.69 (56.09)</td><td>238</td></tr><tr><td>Number of errors</td><td>12.56 (7.68)</td><td>12</td><td>13.56 (7.62)</td><td>11</td></tr><tr><td>Number of correct words</td><td>195.50 (60.60)</td><td>200</td><td>201.12 (55.85)</td><td>228</td></tr><tr><td>Accuracy index</td><td>92.52 (7.49)</td><td>94</td><td>93.26 (4.16)</td><td>95</td></tr><tr><td>Speed index</td><td>237.59 (104.90)</td><td>217</td><td>223.50 (90.72)</td><td>268</td></tr></tbody></table>
## Apparatus

Eye movements were recorded with an infrared-based Tobii Pro Glasses 2 eye-tracking system (for technical details, see www.tobii.com). The sampling rate was set at 100 Hz. Stimuli were displayed on an Apple iPad Air 2, 9.7" retina monitor, with 2048×1536 pixel resolution and a 60 Hz screen refresh rate.

We used a Qualysis motion capture system (for technical details, see www.qualisys.com) to record participants' head movements while reading. More specifically, head motion measures were recorded with six infrared-based MIQUS M3 motion capture cameras. The sampling rate was set at 100 Hz for each camera, with 2-megapixel resolution. A target with six degrees of freedom and six 12-mm diameter markers was affixed to glasses worn by participants to calculate head motion. Eye-tracking data were analyzed with Tobii Pro Lab software, and motion capture data were analyzed with Qualisys Track Manager software.

## Material

Material consisted of two expository texts taken from Aparicio et al. (2021). One text dealt with the *day/night cycle*, the other with the *water cycle*. The number of words, number of characters, readability index (Björnsson, 1968), and reading ease scores (Flesch, 1948) are set out in Table 2.

Each text was presented on a digital tablet and followed by five comprehension questions: three surface questions, and two inference questions probing mental representations. Surface questions assessed memory for words that were present in the text (Yes/No answers). Inference questions assessed readers' ability to combine their own prior knowledge with text information to establish inferences (True/False answers). The children answered directly using the tablet.

## Procedure

Students took the tasks individually in an experiment room installed at the school. After arriving in the experimental room, the participants were given eye-tracking glasses, and the tracker was calibrated with Tobii target calibration (i.e., single-point

<table><caption>**Table 2** Text characteristics</caption><thead><tr><th></th><th>Day/night<br>cycle text</th><th>Water<br>cycle<br>text</th></tr></thead><tbody><tr><td>Number of characters</td><td>1284</td><td>1452</td></tr><tr><td>Number of words</td><td>236</td><td>239</td></tr><tr><td>Number of paragraphs</td><td>5</td><td>5</td></tr><tr><td>Number of commas (punctuation)</td><td>1</td><td>8</td></tr><tr><td>Number of points (punctuation)</td><td>18</td><td>18</td></tr><tr><td>Number of colons</td><td>0</td><td>1</td></tr><tr><td>Readability index<fnref n="1" /></td><td>34.4</td><td>37.4</td></tr><tr><td>Reading ease score</td><td>17.5</td><td>23</td></tr></tbody></table>

<footnote n="1">¹ Scores usually range from 20 ("very easy") to 60 ("very difficult")</footnote>
calibration). During the calibration process, participants were asked to watch the target in front of them and to fixate its center point while keeping their head still. The calibration was then validated by asking participants to read the home page of the experiment on the tablet in front of them. Calibration was considered successful if the gaze point hit the sentences displayed on the tablet. The software did not measure the accuracy of the calibration. The following instructions were then provided orally: “You will read two texts: one describing the water cycle and the other the day/night cycle. Read the following texts to learn as much as you can about the water cycle / day/night cycle.”

Half the participants were given the water cycle text ($n=23$), and half the day/night cycle text ($n=18$). In other words, for participants who received the *water cycle* instruction, the *water cycle* text was relevant and the *day/night cycle* text was irrelevant. By contrast, for participants who received the *day/night cycle* instruction, the *water cycle* text was irrelevant and the *day/night cycle* text was relevant. The presentation of the texts was randomized according to four orders: (1) day/night cycle-Relevant then water cycle, (2) water cycle then day/night cycle-Relevant, (3) water cycle-Relevant then day/night cycle (4) day/night cycle then water cycle-Relevant. Participants were asked to rephrase the instructions before starting the task, to make sure they understood and remembered them, and these instructions were repeated if necessary. We explained to participants that they could read the text at their own pace and move on to the second text by pressing the “Next” button in the bottom righthand corner of the screen. Participants were not allowed to go back to previous screens. After reading both texts, participants answered comprehension questions on the tablet. For each condition, the text was always presented alone on the first screen. Participants were given unlimited time to read it. Comprehension questions were then asked on the following pages of the questionnaire. Once on the question screen, participants could not return to the text. Surface questions were displayed on one page, and inference questions on another. Within each category (surface and inference), questions could be answered in the preferred order and in unlimited time. Participants had to press the “Next” button in the bottom righthand corner of the screen to move from one page to the next. The total duration of the experimental session was about 15 min.

# Results

## Data preparation

Comprehension scores for surface and inference questions were converted into percentages of correct answers. For each text, motion capture data collected during the first and last 3 s were discarded, as we assumed that page change would generate artefacts. The final motion capture dataset consisted of data recorded from 35 participants and totaled 895 528 observations. Before the analyses, observations that deviated more than 2.5 standard deviations (SDs) from each participant's mean were excluded as outliers. This resulted in data loss of 2.11% for the distance traveled by head markers per second. This indicator was calculated by dividing total distance
travelled (mm) by total time (s) for each sample. The distribution of the head motion variable was examined with the checkdistr function in the fitdistrplus package for R and was not skewed (skewness=0.41). When we ran statistical models with and without outliers, to check the impact of removing the outliers, results were almost identical. For eye movement data, we analyzed mean fixation duration, total reading time, and total number of fixations. The distribution of eye movement variables was also examined with the checkdistr function in the fitdistrplus package for R (Delignette-Muller & Dutang, 2015). For mean fixation duration, the distribution was skewed (skewness=3.54), and examination of the Cullen and Frey graph indicated that logarithmic transformation was necessary. As distributions were not skewed for total fixation time (0.59) and total number of fixations (0.27), no logarithmic transformation was needed. Observations that deviated more than 2.5 SDs from each participant's mean were excluded as outliers, and this resulted in data losses of 2.80% for mean fixation duration and 1.45% for total reading time. When we ran the model with the outliers, to check the impact of removing them, results were almost identical.

## Data analysis

The data were analyzed with linear mixed effects models using the lme4 package (version 1.1-32; Bates et al., 2015) for R (version 4.2.3; R Core Team, 2023). For text comprehension, relevance (relevant=1; irrelevant=0), question type (surface=1; inference=2), and their interaction term were included as fixed factors in the models. Eye movement and motion capture data were categorized as either task-relevant (i.e., occurring while reading the task-relevant text) or task-irrelevant. In the models for mean fixation duration, total reading time, total number of fixations, and distance traveled, relevance was entered as a fixed factor. Random intercepts for participants and texts were included in the random part of all models. For example: dependent variable~Relevance + (1|Participant) + (1|Text) for eye movement and motion capture measures, and Score~Type * Relevance + (1|Participant) + (1|Text) for text comprehension analyses. When models failed to converge because of singular fit, we applied the lmerControl function for mixed model fitting (lme4 package). Confidence intervals (CIs) for fixed effect estimates were computed using the Wald method (confint function in lme4 package). All models are provided in the online Supplementary Material.

## Text comprehension

Text characteristics are reported in Table 2, and descriptive statistics for dependent variables according to text relevance in Table 3.

Text comprehension analyses indicated that scores were higher for surface questions than for inference questions (β = -27.78, *SE* = 3.88, 95% CI [-38.24, -17.31], *t* = -5.20), and scores were better overall for the relevant text than for the irrelevant one (β = 13.49, *SE* = 5.34, 95% CI [3.03, 23.95], *t* = 2.53) (Fig. 1). There was no evidence of an interaction between question type and relevance (β = -4.76, *SE* = 7.55, 95% CI [-19.56, 10.03], *t* = -0.63).
<table><caption>**Table 3** Descriptive statistics (means and Standard Deviations) for dependent variables according to text relevance</caption><thead><tr><th rowspan="2">Dependent variable</th><th colspan="2">Relevant</th><th colspan="2">Irrelevant</th></tr><tr><th>M</th><th>SD</th><th>M</th><th>SD</th></tr></thead><tbody><tr><td>Surface comprehension score (%)</td><td>69.05</td><td>26.94</td><td>55.56</td><td>25.15</td></tr><tr><td>Inference comprehension score (%)</td><td>36.51</td><td>25.30</td><td>27.78</td><td>25.41</td></tr><tr><td>Fixation duration (ms)</td><td>274.64</td><td>192.46</td><td>276.08</td><td>192.82</td></tr><tr><td>Total reading time (s)</td><td>147.67</td><td>68.34</td><td>124.73</td><td>64.88</td></tr><tr><td>Number of fixations</td><td>346.97</td><td>143.74</td><td>293.62</td><td>138.50</td></tr><tr><td>Distance travelled per second (mm/s)</td><td>21.26</td><td>9.77</td><td>22.87</td><td>9.65</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Fig. 1** Mean comprehension score according to text relevance. Vertical bars denote SEs</figcaption></figure>

## Eye movements

There was no difference between relevant and irrelevant texts on mean fixation duration ($\beta$=0.010, *SE*=0.0089, 95% CI [-0.0071, 0.028], $t$=1.16). There was, however, a difference on total reading time. Results showed that total reading time was longer for the relevant text than for the irrelevant one ($\beta$=20.45, *SE*=9.59, 95% CI [1.66, 39.24], $t$=2.13) (Fig. 2). As for number of fixations, results revealed that there were more fixations on the relevant text than on the irrelevant one ($\beta$=53.34, *SE*=23.33, 95% CI [7.62, 99.06], $t$=2.29).

## Head motion

Statistical analyses indicated that there was less head motion, calculated as the distance traveled per second (mm/s), for the relevant text than for the irrelevant one ($\beta$ = -1.60, *SE*=0.011, 95% CI [-1.62, -1.58], $t$ = -148.15) (Fig. 3).
<figure><img src="image_5.png" /><figcaption>Fig. 2 Mean total reading time according to text relevance. Vertical bars denote SEs</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Fig. 3 Mean distance traveled per second according to text relevance. Vertical bars denote SEs</figcaption></figure>

Discussion

The present study examined the relevance effect on cognitive engagement and reading comprehension in fourth- and fifth-grade students. Previous studies had indicated that relevance helps to focus attention and enhances learning (McCrudden & Schraw, 2007). The relevance effect in reading has been supported by numerous studies showing that a reading perspective helps individuals to recall textual information (Baillet & Keenan, 1986), and to incorporate that information into their mental representation of the text to support inference generation (Van den Broek et al., 2001). Recent
research suggests that just like an increase in fixation duration, a reduction in postural sway reflects cognitive engagement in a reading task (Ballenghein et al., 2019, 2020, 2023; Kaakinen et al., 2018). Based on previous findings, we expected our readers to engage more in the relevant text than in the irrelevant one, resulting in better text comprehension scores. We predicted that this would be reflected in eye movement data, with more fixations, longer fixation duration and longer total reading time for the relevant text, as well as greater stability in postural sway.

Results were in line with previous findings showing that a relevance effect arising from the adoption of a reading perspective enhances memory performance and reading comprehension (Kaakinen et al., 2018; Kaakinen & Hyönä, 2007; McCrudden & Schraw, 2007). More specifically, data revealed that readers performed better on both the surface and inference questions for the relevant text and suggested that perspective instructions affect goal focus during reading and promote the construction of a mental representation of the text at both surface and situational levels (Kintsch & Van Dijk, 1978).

We also observed greater cognitive engagement during the reading of the relevant text. First, total reading time was longer for the relevant text than for the irrelevant one, indicating that readers took more time to integrate information from the relevant text and to build a more robust mental representation. However, statistical analyses revealed that mean fixation duration did not differ significantly between relevant and irrelevant texts. We can assume that some of the fixations on the relevant text were made during rereading, and were shorter in duration, as previous studies have shown that readers are more likely to reread relevant information in texts (Kaakinen et al., 2002; Kaakinen & Hyönä, 2007). Unfortunately, the eye tracking methodology used in the present study did not allow us to examine rereading fixations, as it was not accurate enough for word- or sentence-level analysis. As for the number of fixations, results showed that there were more fixations during the reading of the relevant versus irrelevant text. Thus, taken together, these results indicate that readers spent more time on relevant text than on irrelevant one, in order to construct their mental representation.

There was less postural sway, measured as the head movement rate, during the reading of the relevant versus irrelevant text. This result is in line with previous studies reporting less postural sway during the reading of cognitively engaging texts (Ballenghein et al., 2020; Kaakinen et al., 2018). It sheds new light on students' cognitive engagement and its embodiment during a reading task. Previous research has shown that postural stability gradually increases across childhood and into adolescence (Assaiante, 2012; Barozzi et al., 2014; Belenkii et al., 1967). Our results indicate that fourth- and fifth-grade students who cognitively engage in reading stabilize their posture in order to effectively process the textual information. Bonnet and Baudry (2016) have suggested that there is a synergy between eye movements and postural movements in adults during high-precision visual tasks. The results of the present study suggest that this synergy also facilitates the processes of memorization and text comprehension in fourth- and fifth-grade students. Moreover, numerous studies in adults have shown that postural control can reflect cognitive engagement (Balaban et al., 2004; Bonnet et al., 2017; Qiu & Helbig, 2012), especially when the reading task is cognitively demanding (see Ballenghein et al., 2019, 2020, 2023). Once again,
our results for fourth- and fifth-grade students are in line with the findings of Bucci et al. (2015), who observed greater postural stability during a reading task than during a target pursuit task in children aged 7–15 years. Reading skills improve sharply between the ages of 6 and 10 years, and continue to develop across adolescence (see Rayner, 1986). In the present study, the students had proficient reading skills and were able to fully focus on the reading task.

There are also a few limitations to the study that need to be taken into account when interpreting the results of this experiment. Firstly, the participants came from just one school. It would be necessary to replicate this study in other schools with more participants. In addition, the inference questions were few and in the form of multiple-choice questions. It would be relevant to replicate this protocol using open-ended questions to limit the intervention of chance in the answers. Furthermore, the inference questions tested in our protocol came from the material developed by Aparicio et al. (2021) and were complex inferences based on young readers’ prior knowledge. These inference questions aimed to test students’ abilities to mobilize their knowledge in relation to the theme of the text. Other types of inferences, such as causal inferences linking different parts of the text, should be tested in future studies. Finally, we did not measure the students’ level of interest in each text, and therefore cannot exclude that this influenced our results in one way or another. However, given that there is an effect of the relevance of the text on the comprehension scores, we can assume that this hypothetical confounding variable only intervenes to a small extent.

Future studies will need to examine fluctuations in postural sway among younger students who are just learning to read, or children with specific reading disabilities. For example, Gouleme et al. (2015) found poorer postural stability in children with dyslexia than in a nondyslexic group. The authors hypothesized that poor postural control in children with dyslexia may be due to a deficit in the use of sensory information, most likely caused by impaired cerebellar activity. These results encourage further research on students’ postural dynamics, insofar as postural sway may provide key indicators about students with reading difficulties or associated disorders.

## Conclusion

The present results are in line with current theories of text comprehension (Kintsch & van Dijk, 1978; Linderholm et al., 2004; van den Broek et al., 2001), and extend previous findings in adults (Ballenghein et al., 2020; Kaakinen et al., 2018) by providing detailed information about the cognitive engagement processes that occur during the course of reading of relevant information in children aged between 9 and 11. The results presented in the present article indicate that young readers were cognitively engaged in processing texts relevant to the reading task. This engagement is revealed by the reduction in postural sway, a longer reading time, and a greater number of fixations when the text was relevant. These observations suggest that reading is embodied, and engagement can be measured using postural and eye movement cues. Moreover, the cognitive engagement hypothesis seems to be reinforced by the fact that the comprehension score was higher when the text was relevant. Naturally, further studies should attempt to replicate the effects reported here with younger and
older students, other texts, and different tasks. The present study demonstrates that the combination of eye movement and postural movement recordings is a promising way to study how young readers embody cognitive demands during a reading task.

**Funding** Open access funding provided by Université Paris-Est Créteil.

**Declarations**

**Conflict of interests** The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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