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Article

Effect of Emotional Valence on Text Comprehension by French Fourth and Fifth Graders

by
Ugo Ballenghein
1,*,
Léa Lachaud
1,
Xavier Aparicio
1 and
Denis Alamargot
2
1
Laboratory Cognitions Humaine et Artificielle, University of Paris-Est Créteil, 94380 Bonneuil, France
2
Laboratory CeRCA-CNRS, Graduate School for Teachers, University of Poitiers, 86000 Poitiers, France
*
Author to whom correspondence should be addressed.
Psychol. Int. 2025, 7(1), 4; https://doi.org/10.3390/psycholint7010004
Submission received: 6 December 2024 / Revised: 9 January 2025 / Accepted: 15 January 2025 / Published: 20 January 2025
(This article belongs to the Section Cognitive Psychology)
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Abstract

:
Background: Emotional valence can be used to describe the pleasant or unpleasant nature of information such as images, words, sentences, or texts. The possible existence of a bias favoring the comprehension of positive versus negative information remains a controversial subject. The aim of the present study was to explore whether the emotional valence of a text influences its comprehension by students in the fourth or fifth grade. Methods: To this end, 55 French students with a mean age of 10.11 years answered surface, semantic, and inferential questions after reading texts with a positive, negative, or neutral valence. Results: The results showed that surface comprehension scores were higher for texts with a positive or negative valence, rather than a neutral one. They also showed that semantic comprehension scores were lower for negatively valenced texts. Conclusion: These observations suggest that emotional valence influences text comprehension in young readers. The existence of a positivity bias in children’s reading comprehension and the educational implications in the classroom are discussed.

1. Introduction

Reading comprehension is the key to knowledge acquisition, but it is a complex skill and its development a gradual process. Students’ decoding and vocabulary levels both influence comprehension, as does text readability (see Best et al., 2008). There is also a large body of scientific literature on the role of emotions in cognition. In addition to influencing our judgments and decision-making (Frijda, 2009), emotions have been shown to impact both learning (Pekrun, 2014) and text comprehension (Blanc & Syssau, 2018).

1.1. Two-Dimensional Structure of Emotions

Studies on the influence of emotions on cognitive processes are mainly based on a two-dimensional (valence and arousal) structure of emotions (Citron et al., 2014). Valence refers to the pleasant or unpleasant nature of the emotion, and ranges from positive to negative (Lang et al., 1997). Arousal describes the intensity of the emotion, and ranges from low to high (Lang et al., 1997). These two dimensions are usually rated on 9-point nonverbal self-assessment manikin scales (Bradley & Lang, 1994), although for young children, researchers often use a simplified 5-point valence scale featuring stylized faces (see Largy et al., 2018). Experimental data for emotional words (Bradley & Lang, 1994), pictures (Lang et al., 1997), and news (Kaakinen & Simola, 2020) have shown that valence and arousal are linked by a U-shaped function (Bayer et al., 2010). In other words, emotions judged to be strongly positive or negative are also judged to have a high level of arousal, whereas neutral stimuli are judged to have a low level of arousal.
Recent studies on reading have highlighted an emotional bias in adults when text is processed in silent reading. More specifically, word fixation times are shorter during the reading of texts with a positive valence rather than a neutral or negative one (Ballenghein et al., 2019; Usée et al., 2020). Adults’ cognitive engagement (as measured by a change in posture) during the reading of short narrative texts has been shown to be greater when the texts have emotionally charged content rather than neutral content (Ballenghein et al., 2019). However, these authors failed to demonstrate a difference between positively versus negatively valenced texts.
There are contradictory results on the influence of negatively valenced texts or sentences on comprehension, depending on the age of the reader. A study of negativity bias, which refers to the tendency to be more affected by negative than positive information (Rozin & Royzman, 2001), reported that stories with negative endings were read more slowly than stories with positive endings (Egidi & Gerrig, 2009). Another study found that negative information attracted more attention than either neutral or positive information (Baumeister et al., 2001). These asymmetrical effects of emotional valence on cognitive processes have been observed in other studies. For example, emotional words have been shown to be read faster than neutral words, regardless of valence polarity (Knickerbocker et al., 2015; Kousta et al., 2009; Scott et al., 2012). Studies point to a positivity bias in children. In particular, Sylvester et al. (2016) found that positive words were processed faster in an emotion categorization task in 9- and 12-year-olds. Similarly, children have been shown to categorize faster and make fewer categorization errors for faces expressing positive emotions than for faces expressing negative emotions or neutral faces (Feyereisen et al., 1986; Leppänen & Hietanen, 2004). Finally, Kauschke et al. (2019) recently showed that children have a clear positivity advantage for word and face processing, indicating similar processing biases in both modalities. Over the course of development, this initial positivity advantage gradually disappears, and in some studies of face processing, even reverses into a negativity bias (Vesker et al., 2018). In the context of text comprehension, it seems appropriate to study the influence of emotional valence on text comprehension in young students who already have a good reading level.

1.2. Text Comprehension Model

Reading comprehension refers to the activity by which individuals acquire and use knowledge (Vellutino, 2003). This process of meaning construction mobilizes numerous cognitive functions and skills, including decoding, access to mental lexicon, working memory, and emotion regulation, and leads to the elaboration of a mental representation (Gernsbacher et al., 1990; Kintsch & Van Dijk, 1978). Thus, to understand a text, readers must be able to memorize the surface (i.e., explicit) information, and generate inferences enabling them to fill in any missing elements and thus understand the implicit information. This inferential process corresponds to the construction of the situation model proposed by Kintsch and Van Dijk (1978).
Derived from cognitive psychology, Kintsch and Van Dijk (1978)’s model of comprehension formalizes three levels of representation: surface, semantic (or text base), and inferential (or situation model). At the surface level, information present in the text passes directly into the reader’s memory without its meaning being taken into consideration. It is, therefore, possible for the reader to memorize information present in the text without necessarily accessing the latter’s meaning. At the semantic level, sentence meaning can be integrated independently of the reader’s knowledge. Finally, at the inferential level, the mental representation of the text is created, the product of an interaction between the information explicitly present in the text and the reader’s prior knowledge (Kintsch & Van Dijk, 1978). The fine-grained comprehension of a text, therefore, comes down to producing inferences in order to construct a precise and coherent mental representation. Text comprehension is both a complex and dynamic process, as the mental representation of the text must be continually updated according to new information from the text and the reader’s prior knowledge. More specifically, understanding a text requires the ability to establish links between information from the text that is held in working memory and the reader’s own prior knowledge stored in long-term memory. Children with the greatest working memory capacity have been shown to be those who resolve the most inferences in reading (Cain et al., 2004).

1.3. Reading Comprehension and Emotions

In their 1983 model, Van Dijk and Kintsch suggest that emotions stimulate readers’ attention and constitute an active control structure for text comprehension. According to Miall (1989), emotions may tell readers what is important in the text and guide the construction of the mental representation of the text. Authors have already studied the effect of emotions on text comprehension. In children, short narrative texts with emotional valence have been shown to be recalled better than neutral stories, regardless of polarity (Cahill & McGaugh, 1995). A recent study revealed the differences between texts with a positive or negative emotional valence and neutral texts. More specifically, Megalakaki et al. (2019) found that, compared with neutral texts, texts with a negative valence favored inferential comprehension in adult readers, while texts with a positive valence favored surface memorization.
Generally speaking, experimental results converge to show that, compared with neutral information, emotional information is likely to be better memorized (Ochsner, 2000), activate semantic information more strongly, and favor the elaboration of inferences (Brainerd et al., 2010). However, studies among children sometimes yield contradictory results. For example, one study found that although 11-year-olds achieved higher comprehension scores than 6-year-olds for nonemotional stories, there was no significant difference in memorization between the two groups when emotional information was inserted into the texts. Thus, the emotional valence of stories has a greater impact on the comprehension of younger children (see Bishop et al., 2004).
In view of these divergent results, it is important to further explore the influence of emotional valence on students’ text comprehension. A methodological bias is regularly responsible for the contradictory results obtained with children. Pupils’ perception of the emotional valence of texts is not controlled by the pupils themselves. Therefore, in the present study, we set out to control for this methodological bias, by asking students to make their own emotional valence judgements on nonverbal self-assessment scales that are easy for children to use (see Burkitt & Barnett, 2006).

1.4. The Present Study

The present study investigated the influence of emotional valence on the surface, semantic, and inferential text comprehension in fourth and fifth graders. Studies of the influence of emotions on text comprehension have generally focused on the impact of emotion induction on the different levels of comprehension of a neutrally valenced text (see Blanc & Syssau, 2018). Therefore, the aim of the present study was to analyze the effect of the emotional valence of each text (positive, negative, or neutral) on surface memorization (information contained in the text), semantic memorization (meaning of the text), and inferential memorization (implicit information inferred from the text). Doing so, we would be able to inform the debate about a potential positivity bias in the memorization of textual elements and text comprehension. It was the students themselves who judged the emotional valence of the texts in order to objectify their emotion perception. Finally, the experiments took place in the classroom, and the experimenters were the students’ regular teachers in order to create the most ecological experimental conditions possible and not confuse the students with the protocol. We predicted that students would achieve higher comprehension scores for emotionally charged texts, whatever their valence (positive or negative), than for neutrally valenced texts.

2. Materials and Methods

2.1. Participants

A total of 55 students (33 boys and 22 girls) took part in the experiment. They were in their fourth (Mage = 10.10 years, SD = 0.59) or fifth (Mage = 10.20 years, SD = 0.53) year of primary education, and attended a school in France. The students were normal readers (no student had a proven reading or language disorder). None of them were repeating a year, and none had been identified as having specific or general learning difficulties. All had normal or corrected-to-normal eyesight.

2.2. Measures

Valence judgments: The students were asked to rate the emotional valence of each text on a 5-point nonverbal Likert-like scale ranging from 1 (very positive valence) to 5 (very negative valence), with stylized faces as anchors (Burkitt & Barnett, 2006).
Comprehension test: The comprehension test was developed following the model of Aparicio et al. (2022) to assess the different levels of comprehension (surface, semantic and inferential). The students were asked to answer a multiple-choice questionnaire comprising a set of six surface questions (0.5 points per correct answer; maximum score = 3), three semantic questions (1 point per correct answer; maximum score = 3), and three inferential questions (1 point per correct answer; maximum score = 3).

2.3. Material

The texts read by the pupils consisted of six extracts from children’s literature, two of which were positively valenced, two negatively valenced, and two neutrally valenced (see Appendix available in the section Supplementary Materials). The texts each contained approximately the same number of words and had equivalent Flesch Reading Ease (FRE; Flesch, 1948) scores. The descriptive statistics are provided in Table 1. An additional neutral text was used to familiarize students with the valence judgment scale and comprehension test.

2.4. Procedure

The tests took place in two different classes. All students read all six texts in a within-participants experimental design. They were divided into groups of five or six, under the supervision of an experimenter who was also their regular teacher. Prior to the experiment, participants underwent a training session featuring a neutral text. Students read each text and rated its emotional valence on the 5-point nonverbal Likert scale with stylized faces (Burkitt & Barnett, 2006). They then answered comprehension questions. The order in which the texts were presented was randomized for each group of students.

2.5. Data Analysis

Emotional valence ratings and scores on the comprehension questionnaire were submitted to an analysis of variance (ANOVA) with valence (positive, neutral, negative) and question type (surface, semantic and inferential) as within-participants factors. The experimental design incorporated two independent variables, each with three levels: valence (positive, neutral, negative) and question type (surface, semantic, inferential). The dependent variables included participants’ emotional valence judgments of the texts, assessed using the SAM scale (ranging from 1 to 5), as well as their comprehension scores across the three question types (surface, semantic, and inferential).
Post hoc analyses were performed with Bonferroni correction due to a limited number of comparisons. All statistical analyses were conducted using JASP software (JASP 0.17 (Intel), Amsterdam, The Netherlands) (Love et al., 2019).

3. Results

The students’ emotional ratings of the texts are reported in Table 1, together with their scores on the surface, semantic, and inferential questions. To check the equivalence of the texts, we also calculated the FRE score for each one, as follows: FRE = 206.835 − (1.015 × ASL) − (84.60 × ASW), where ASL is the number of words/number of sentences, and ASW is the number of syllables/number of words. The mean length of the texts (in characters and words) and the mean FRE score for each valence are shown in Table 1.
The results showed that students’ emotional ratings differed significantly according to the texts’ emotional valence, F(2, 108) = 139.64, p < 0.01, η2p = 0.72. More specifically, post hoc analyses revealed that positive texts were rated as more positive than neutral texts, t(108) = −8.20, SE = 0.14, p < 0.001, d = −1.54, 95% CI [−1.49, −0.80], negative texts were rated as more negative than neutral texts, t(108) = −7.83, SE = 0.15, p < 0.001, d = −1.57, 95% CI [−1.53, −0.80], and positive texts were rated as more positive than negative texts, t(108) = −18.42, SE = 0.12, p < 0.001, d = −3.12, 95% CI [−2.61, −2.00] (Figure 1).
The ANOVA comparing students’ comprehension scores according to the text valence and question type revealed a significant main effect of text valence, F(2, 108) = 11.45, p < 0.001, η2p = 0.18. Post hoc analyses showed that for all the question types taken together, comprehension scores were significantly higher for positive texts than for either negative texts, t(108) = 4.26, SE = 0.038, p < 0.001, d = 0.39, 95% CI [0.069, 0.26] or neutral texts, t(108) = 5.10, SE = 0.036, p < 0.001, d = 0.43, [CI: 0.095, 0.27]. No significant difference was observed between negative and neutral texts, t(108) = 0.39, SE = 0.050, p = 1.00, d = −0.047, 95% CI [−0.14, 0.10].
The ANOVA also revealed the main effect of the question type on comprehension scores, F(2, 108) = 31.03, p < 0.001, η2p = 0.37. Post hoc analyses showed that for all emotional valences taken together, the scores were significantly higher for inferential questions than for either semantic questions, t(108) = 4.79, SE = 0.037, p < 0.001, d = 0.42, 95% CI [−0.27, −0.086], or surface questions, t(108) = 7.05, SE = 0.041, p < 0.001, d = 0.68, 95% CI [−0.39, −0.19]. The post hoc analysis revealed that the scores were significantly higher for semantic questions than for surface questions, t(108) = 3.43, SE = 0.032, p < 0.01, d = 0.26, 95% CI [−0.19, −0.031].
The ANOVA comparing students’ comprehension scores according to the text valence and question type revealed an interaction effect between the two, F(4, 216) = 8.57, p < 0.001, η2p = 0.14 (Figure 2).
The post hoc analyses revealed a significant difference in surface comprehension scores between the three valences. The mean surface comprehension score for neutrally valenced texts (M = 2.17, SD = 0.44) was significantly lower than the mean scores for texts with either a negative (M = 2.49, SD = 0.41), t(108) = −4.52, SE = 0.070, p < 0.001, d = −0.75, 95% CI [−0.54, −0.091] or a positive (M = 2.60, SD = 0.39), t(108) = −6.14, SE = 0.070, p < 0.001, d = 1.02, 95% CI [0.20, 0.66] valence. The surface comprehension scores for positive texts (M = 2.60, SD = 0.39) did not differ significantly from those for negative texts (M = 2.49, SD = 0.41), t(108) = 1.61, SE = 0.070, p = 1.00, d = 0.27, 95% CI [−0.11, 0.34].
Regarding the scores on semantic questions, these same post hoc analyses revealed that scores were significantly higher for positively valenced texts (M = 2.65, SD = 0.43) than for negatively valenced texts (M = 2.39, SD = 0.50), t(108) = 3.68, SE = 0.070, p = 0.01, d = 0.61, 95% CI [0.032, 0.49]. The scores on the inferential questions did not differ significantly across the three valences.

4. Discussion

The present study examined the influence of the emotional valence of short texts on three levels of comprehension. We used texts from children’s literature with different emotional valences, and designed three types of comprehension questions for each of these texts: surface, semantic, and inferential (see Gernsbacher et al., 1990; Kintsch & Van Dijk, 1978). After reading a text, students were also asked to rate its emotional valence on a nonverbal self-assessment scale featuring five stylized faces as anchors (Burkitt & Barnett, 2006) in order to check that they had correctly perceived its emotional character.
An analysis of the results showed that students in their fourth or fifth year of primary school correctly perceived the emotional valence of the texts, with significantly different ratings for each valence. These results confirmed the validity of our material, and also confirmed that students aged 9–11 years can perceive the emotional valence of positive, negative, and neutral texts without any difficulty.
The analysis also showed that text valence influenced students’ comprehension at different levels. Irrespective of the question type, texts with a positive emotional valence elicited significantly higher comprehension scores than negative and neutral texts. More specifically, the results indicated that texts with a positive valence favored good comprehension at all three levels: surface, semantic, and inferential. By contrast, surface comprehension was affected by neutrally valenced texts, and semantic comprehension by negatively valenced texts. These results only partially confirm Megalakaki et al. (2019)’s findings for young adults. In their study, the authors found greater surface comprehension for positively and neutrally valenced texts, and greater inferential comprehension for negatively valenced texts. In our sample of 9-to-11-year-old children in their fourth or fifth year of primary school, text valence, whatever its polarity, favored surface comprehension, with better memorization of the elements present in the text, compared with neutrally valenced texts. This confirms the results of previous studies showing better memorization scores among children for emotionally valenced information than for neutral information (Bishop et al., 2004; Davidson et al., 2001; Ochsner, 2000).
The results of the present study indicated significantly lower scores on semantic questions for texts with a negative emotional valence than for texts with a positive or neutral valence. Semantic questions require access to the strict meanings of sentences. Our results suggest that this access to meaning was disrupted by negative emotion. Some studies have found a negativity bias among adults, with negative information attracting more attention than neutral or positive information (Baumeister et al., 2001), and inducing longer reading times compared with neutral texts (Egidi & Gerrig, 2009). In children, studies seem to point more to a positivity bias, favoring the processing of information with a positive valence (Feyereisen et al., 1986; Kauschke et al., 2019; Leppänen & Hietanen, 2004). In addition, some studies indicate that negative emotions are more difficult to identify without confusion (Leppänen & Hietanen, 2004; Nummenmaa & Calvo, 2015), and positive verbal information is better elaborated and interconnected in memory than negative information (Sylvester et al., 2016; Unkelbach et al., 2008). The results of the present study revealed that information with a positive emotional valence was easier to process, while a negative emotional valence hindered access to sentence meanings. Interestingly, inferential comprehension was not affected by text valence. This suggests that students were able to produce inferences by creating links between working memory and long-term memory, whatever the emotional valence of the texts. Studies on children’s ability to make inferences show that younger children have difficulty generating inferences, whereas older children do so more spontaneously (Oakhill et al., 2003). This ability already seemed to have been consolidated in the fourth and fifth graders in the present study.

5. Conclusions

The results suggest that texts with a positive emotional valence make reading–comprehension exercises easier for students in their fourth or fifth year of primary school, and, more generally, promote learning. The present study highlights the importance of considering the emotional valence of texts given to students. Experimental data tend to show a consistent influence of positive emotional valence on text comprehension. At a time when reading comprehension is at the heart of learning in primary school, and more specifically in the fourth and fifth grades, it seems essential for emotional valence to be taken into consideration in teaching content and practices. Compared with neutral texts, ones with an emotional valence are likely to enhance students’ cognitive engagement, and lead them to memorize and understand the content better. Future studies will enable us to learn more about the influence of emotions in learning contexts, in particular through the careful analysis of the impact of emotional content on various school activities such as reading comprehension, memorization, and the reading of problem statements in mathematics.

Supplementary Materials

The following supporting information can be downloaded at: https://osf.io/enkds/?view_only=57dbc53c945547589664deaf21bcb3e7 (accessed on 17 January 2025), Figure S1: Emotional valence ratings of positive, neutral, and negative texts on the self-assessment manikin (SAM); Figure S2: Mean comprehension scores as a function of the text valence and question type; Table S1: Descriptive statistics.

Author Contributions

Conceptualization, U.B., and L.L.; methodology, U.B., and L.L.; validation, D.A., and X.A.; formal analysis, U.B.; investigation, U.B., and L.L.; resources, U.B.; data curation, U.B., and L.L.; writing—original draft preparation, U.B.; writing—review and editing, U.B., L.L., X.A., and D.A.; visualization, U.B., L.L., X.A., and D.A.; supervision, D.A.; project administration, U.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The original data presented in the study are openly available in OSF at https://osf.io/enkds/?view_only=57dbc53c945547589664deaf21bcb3e7 (accessed on 17 January 2025).

Acknowledgments

We thanks the participating classes and their teachers for their valuable contribution to this study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Emotional valence ratings of positive, neutral, and negative texts on the self-assessment manikin (SAM) scale. Vertical bars represent the 95% confidence interval. 1 = very positive; 5 = very negative.
Figure 1. Emotional valence ratings of positive, neutral, and negative texts on the self-assessment manikin (SAM) scale. Vertical bars represent the 95% confidence interval. 1 = very positive; 5 = very negative.
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Figure 2. Mean comprehension scores as a function of text valence and question type. Vertical bars represent the 95% confidence interval.
Figure 2. Mean comprehension scores as a function of text valence and question type. Vertical bars represent the 95% confidence interval.
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Table 1. Descriptive statistics.
Table 1. Descriptive statistics.
Positive TextsNegative TextsNeutral Texts
Mean number of words (SD)309 (7.07)305.50 (10.61)303 (2.83)
Mean number of characters
(including spaces) (SD)		1720.50 (16.26)1804.50 (89.80)1729.50 (7.78)
Mean Flesch Reading Ease score (SD)65.87 (8.19)59.92 (3.73)66.79 (0.25)
Mean surface score (SD)2.60 (0.39)2.49 (0.41)2.17 (0.44)
Mean semantic score (SD)2.65 (0.42)2.39 (0.50)2.55 (0.42)
Mean inference score (SD)2.75 (0.34)2.63 (0.47)2.74 (0.39)
Mean emotional valence rating from 1
(Very positive) to 5 (Very negative) (SD)		1.53 (0.54)3.85 (0.78)2.68 (0.90)
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Ballenghein, U.; Lachaud, L.; Aparicio, X.; Alamargot, D. Effect of Emotional Valence on Text Comprehension by French Fourth and Fifth Graders. Psychol. Int. 2025, 7, 4. https://doi.org/10.3390/psycholint7010004

AMA Style

Ballenghein U, Lachaud L, Aparicio X, Alamargot D. Effect of Emotional Valence on Text Comprehension by French Fourth and Fifth Graders. Psychology International. 2025; 7(1):4. https://doi.org/10.3390/psycholint7010004

Chicago/Turabian Style

Ballenghein, Ugo, Léa Lachaud, Xavier Aparicio, and Denis Alamargot. 2025. "Effect of Emotional Valence on Text Comprehension by French Fourth and Fifth Graders" Psychology International 7, no. 1: 4. https://doi.org/10.3390/psycholint7010004

APA Style

Ballenghein, U., Lachaud, L., Aparicio, X., & Alamargot, D. (2025). Effect of Emotional Valence on Text Comprehension by French Fourth and Fifth Graders. Psychology International, 7(1), 4. https://doi.org/10.3390/psycholint7010004

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