Teacher, Forgive Me, I Forgot To Do It! The Impact Of Children's Prospective Memory On Teachers' Evaluation Of Academic Performance

Abstract 

Background: According to Munsat (1965, The concept of memory. University of Michigan), a person who makes frequent prospective memory (PM) errors is considered to have a flawed character rather than a bad memory. Given that PM completes its development only in young adulthood, this bias might occur not only within social relationships but also in school. However, little is known about the impact of this bias on academic performance. 

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Aims: This study aimed to evaluate the impact of children's PM on teacher's evaluations of their academic performance (i.e., grades) and social skills. 

Sample: A total of 158 eight- and twelve-year-old children (48% females) participated in this study.

Methods: A working memory (WM) updating task was used as an ongoing task (OT), in which the PM task was embedded and required participants to respond whenever certain pictures appeared. Children's social skills were measured through teacher ratings, whereas grades were collected as indicators of teachers' assessment of academic performance. Children's WM span and inhibitory control were also assessed. 

Results: Results showed that 8- and 12-year-old children's academic performance was predicted by both PM performance and teachers' evaluations of social skills. However, social skills evaluations were not predicted by PM performance. WM span was related to grades in 8-year-olds, while inhibitory control was related to PM performance in 12-year-olds.

Conclusions: These outcomes highlight that children's grades are not explained only by academic performance itself but also by other personal skills. Awareness of the biases that can occur when evaluating children's academic performance can help teachers to be more objective in their assessment. 

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KEYWORDS academic performance, prospective memory, school-aged children, social skills, teachers' evaluations

INTRODUCTION 

Children are often told to turn in their homework on time, to return a book to the library, or to deliver a message to their parents. However, they frequently forget to follow teachers' directions and fail to implement instructed intentions at the right moment (see Mahy et al., 2014). The reason could be that the ability to remember to perform an intended action, also known as prospective memory (PM; Einstein & McDaniel, 1990), reaches its developmental peak only around late adolescence or young adulthood (Zimmermann & Meier, 2006). Developmental changes in PM performance during the school years seem to contribute not only to children's increasing autonomy and independence from others in everyday life but also to their success in various contexts. For instance, a child who frequently forgets to turn in homework on time may be disadvantaged in school, despite being as academically skilled as their schoolmates (see Mahy et al., 2014). In addition, PM failures may negatively influence children's social relationships, for example, when a child frequently forgets to return a book to a friend or to bring a birthday present to a party. As Munsat (1965) first suggested, PM failures tend to be interpreted as character flaws rather than as pure memory difficulties in the way that retrospective memory errors are interpreted. Thus, children who do not develop the ability to successfully perform a PM task are likely to have difficulties, not only in the execution of formal tasks (such as in school) but also in their interactions with parents, teachers, and peers (see Mahy et al., 2014). However, there is still no evidence on whether and to what extent PM abilities impact children's success in school and social interactions. This study aimed to investigate the role of children's PM development on teachers' evaluations of both academic performance and social skills. 

Prospective memory and its development 

Prospective memory performance is usually assessed using dual-task-like laboratory-based experiments in which participants are involved in an ongoing activity, also known as an ongoing task (OT), and simultaneously have to remember to execute an intention whenever a predetermined event, that is, a PM cue, occurs (Einstein & McDaniel, 1990). This paradigm has been designed to mimic everyday life situations in which we commonly have to interrupt ongoing activities to execute a previously planned task (e.g., stopping a conversation to enter the bakery and buy bread). Based on this paradigm, studies have created various tasks to evaluate PM in children. For instance, many studies used laboratory-based PM tasks, such as computerized or game-like tasks in which children are required to play a game or to categorize pictures or words as OT and simultaneously to remember to press a different key or perform a different action whenever a specific target appears (the PM cue). Importantly, the PM cue appears only a few times during the OT (e.g., 3 PM cues among 100 OT trials), to resemble what happens in daily life when there are only a few occasions to execute our intention (Brandimonte & Passolunghi, 1994). However, another line of research adopted more ecological PM tasks, in which children were asked to remember to ask for candies or stickers when they see the experimenter or to take cupcakes out of the oven after a specific delay time (Ceci & Bronfenbrenner, 1985; Kliegel et al., 2010; Ślusarczyk & Niedźwieńska, 2013; Somerville et al., 1983). Both laboratory-based and ecological experiments showed advantages and the choice is dependent on several factors such as the size of the available sample, the desired level of control over the variables, and the goal of the study, among others. Nonetheless, both approaches were able to provide useful insights into the PM process in developmental age. Developmental research has shown that the first signs of PM abilities arise early around the age of 2 or 3 years and increase during the preschool period (e.g., Matthias Kliegel et al., 2010; Mahy & Moses, 2011; Ślusarczyk et al., 2018; Ślusarczyk & Niedźwieńska, 2013). For instance, particular improvements in PM performance have been revealed between 3 and 6 years of age by using both ecological and laboratory-based PM tasks (Mahy & Moses, 2011; Ślusarczyk & Niedźwieńska, 2013). During the school-age period children's PM performance continues to improve, with important developmental shifts around the ages of 7–8 and 10–11 years (e.g., Shum et al., 2008; Smith et al., 2010; Spiess et al., 2016; Yang et al., 2011; Zuber et al., 2019). This is supported by a study by Yang et al. (2011), who assessed PM performance in 120 seven- to twelve-year-old children through various laboratory-based computerized PM tasks. Finally, PM becomes relatively stable only around late adolescence or young adulthood, as has been shown in numerous lifespan studies including children, adolescents, and adults (e.g., Kretschmer-Trendowicz & Altgassen, 2016; Zimmermann & Meier, 2006). According to the executive framework of PM development (Mahy et al., 2014), which is based on both the multiprocess view (McDaniel et al., 2015; McDaniel & Einstein, 2000) and the preparatory and attentional memory theory (Smith, 2003; Smith & Bayen, 2004), executive functions play an important role in the development of PM during childhood and adolescence, especially when a PM task is resource demanding. For instance, PM tasks that are non-focal to the OT (e.g., a PM task that requires semantic processing and an OT that requires perceptual processing) seem to rely more on executive processes compared to PM tasks that are focal to the OT (Einstein et al., 2005; Maylor, 1996; Maylor et al., 2002; Meier & Graf, 2000; Meiser & Schult, 2008). Furthermore, this framework suggests that PM development during early childhood is particularly supported by working memory (WM) abilities, whereas inhibitory control, monitoring, and switching play an important role during school-age years. Relations between PM development and executive functions have been shown in several studies using different PM tasks. For instance, Shum et al. (2008) tested 63 eight- to thirteen-year-old children on a focal PM task, in which children were required to read a text aloud and remember to substitute a target word with another word, and found that inhibition, switching and WM were all related to PM performance. Similarly, Zuber et al. (2019) tested the role of executive functions on both focal and non-focal PM tasks in 212 six- to eleven-year-old children. In a focal PM task, children were required to play a computerized card-sorting game as OT (i.e., sort objects according to dimension) and to remember to press a specific key whenever an animal appeared as a PM task. Performance on both PM tasks was related to inhibition and WM updating (see Cherie et al., 2021, for similar results). However, switching was found to be mainly related to PM performance in the non-focal task in which the OT consisted of sorting cards according to a small symbol below or above the central picture and the PM task consisted of remembering to press a specific key for animals (see Spiess et al., 2016, for similar results). 

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Prospective memory, academic performance, and social interactions 

Prospective memory has been suggested to influence success not only in school but also in social relationships (see Mahy et al., 2014). However, little is known about the impact of PM development on children's academic performance and social interactions. Regarding academic attainment, to date, various studies have investigated the relationship between executive functions and school performance. For instance, St Clair-Thompson and Gathercole (2006) showed that visuospatial WM and inhibition of 11- and 12-year-old children predicted their school performance in English, mathematics, and science. Similarly, Visu-Petra et al. (2011) showed that WM was highly predictive of 11- and 15-year-olds' school performance in mathematics. Although executive functions are important predictors of academic success, there are also other factors influencing school performance. For instance, a study with 7- and 8-year-old children showed that in addition to executive functions, personality traits, such as extraversion and openness, predicted academic success. Importantly, this outcome was found when considering school grades (which are given by teachers) but not when considering standardized tests as a measure of academic performance (Neuenschwander et al., 2013). This suggests that teachers' evaluations of academic performance may be to some extent biased towards aspects that go beyond actual academic competence. As we have argued before, children who frequently forget to accomplish school assignments may be erroneously seen as academically less competent than their schoolmates. Thus, children's PM abilities could be a further factor influencing academic assessments. Similarly, about the social aspects of PM, it has been often argued that a child who does not appropriately develop the ability to successfully perform PM tasks is likely to have many difficulties, not only in the execution of formal tasks (such as in school) but also in suitable interactions with parents, teachers and peers (McCauley & Levin, 2004). PM performance seems particularly sensitive to the social value (i.e., social importance) of the action to be performed (Cicogna & Nigro, 1998): intentions are more likely to be accomplished for actions with a high level of interest. This factor may be critical for school children, given that homework is one of the most important activities and, many times, is accompanied by negative feelings. Researchers in this field have frequently argued that successful prospective remembering would not only be influenced by social interactions but also influence social interactions themselves (Brandimonte & Ferrante, 2008). Accordingly, retrospective memory failures would be attributed mainly to a person's bad memory, whereas PM failures would be attributed more frequently to a person's bad character and unreliability (Munsat, 1965). Consequently, it would be more likely that PM failures negatively affect the perceptions of a person's social competence. In this vein, Moeller et al. (2021) recently explored how forgetful children are perceived by adults. In two experiments, the authors showed different vignettes to adult participants, depicting children of different ages (4-year-old and 10-year-old children) who forget to complete intentions in different situations (academic or social). Participants were asked to give judgments of children's traits (i.e., kindness, friendliness, trustworthiness, capability, competence, intelligence, and conscientiousness). The results of this study showed that adults judged children who make PM errors negatively, especially when children were older than when they were younger. Moreover, both 4- and 10-year-old children were similarly negatively judged when PM errors occurred in the social rather than in the academic domain. Considering these outcomes, the authors call out the need to extend this research by exploring whether children are also treated differently by adults in school or at home based on their PM performance. There have been no studies to date that have empirically tested the impact of children's PM performance on adults' evaluations of their academic success and social competencies.

The present study 

The present study aimed to explore whether and to what extent children's PM abilities would affect teachers' evaluations of their academic performance (i.e., grades) and social skills. Moreover, we aimed to investigate whether executive functions may modulate these relations and their development. We compared the performance of 8- and 12-year-old participants on a PM task that was adapted from previous studies with adults (Basso et al., 2010; Palladino & Jarrold, 2008) and on tasks measuring some components of executive functions (i.e., WM and inhibitory control). These two age groups were selected based on previous studies which have shown that PM improves during the school years with a considerable shift between the ages of 10 and 11 years (Shum et al., 2008; Yang et al., 2011). Testing children before and after this shift may provide us with lower variability so that age differences could be more reliable. Due to their documented relevance in both PM and academic performance (Cherie et al., 2021; St Clair-Thompson & Gathercole, 2006; Zuber et al., 2019), WM and inhibitory control were evaluated to disentangle their effects from PM while estimating the dependent variables. Participants' school grades were considered as teacher's evaluations of their academic performance, whereas teachers' assessment of participants' social competencies was collected using a questionnaire. First, we hypothesized that children's school grades would be influenced by teachers' evaluations of social skills and that both these variables could be predicted by children's PM performance (cf. Munsat, 1965). Second, as suggested by the literature, we expected school grades to be related to participants' inhibitory control and WM performance (St Clair-Thompson & Gathercole, 2006; Visu-Petra et al., 2011). Finally, we expected to replicate developmental advances in PM performance from childhood to (pre)adolescence (Kretschmer-Trendowicz & Altgassen, 2016; Zimmermann & Meier, 2006) as well as their relation to inhibitory control and WM (Cherie et al., 2021; Shum et al., 2008; Yang et al., 2011; Zuber et al., 2019). 

METHOD Participants 

A total of 158 participants took part in the present study: 76 eight-year-old (Mage = 8.12; SD = .45; 36 females) and 82 twelve-year-old children (Mage = 12.21; SD = .53; 40 females). Children were recruited from public schools in Northern Italy and had mixed socio-economic status, as children attending public schools in that region belong to a variety of socio-economic backgrounds going from a medium-low to a medium-high socio-economic status. Most children were either native Italian speakers or sufficiently proficient in Italian. None of the participants had any neurological or developmental disorders, and all of them had normal or corrected-to-normal visual acuity. The study procedure respected the ethical standards of the American Psychological Association and was approved by the local university and the participating schools. All children as well as their legal caretakers gave oral or written informed consent for participation in the present study. 

Materials and procedures 

Prospective memory paradigm 

The OT consisted of a computerized WM updating task adapted from previous studies including adults (Basso et al., 2010; Palladino & Jarrold, 2008). The task included a total of 266 standardized black-and-white line drawings depicting easy-to-name living and non-living objects (Lotto & Dell'Acqua, 2001). Of these pictures, three were used as PM cues (i.e., pig, belt, and pumpkin), while the remaining 263 pictures were used for the training phase and the two blocks (see Figure 1). The task was designed and run on Presentation software (Neurobehavioral Systems, San Francisco, CA). The pictures were presented one by one (every 3 s) on the computer screen and were organized into 32 lists, eight lists for each of four different list lengths that included 3, 4, 5, or 6 pictures. For the OT, the participants were required to remember the last three pictures of every list without knowing the list length in advance. At the end of each list, they were presented with a fixation cross (200ms), followed by the probe picture. Participants had to decide whether the probe picture was among the last three to-be-remembered items by pressing the yes- or no key on the keyboard. Half of the probe pictures were present within the last three to-be-remembered items, while half were not. Of these, 12 were presented within the list but did not belong to the last three to-be-remembered items, while four were new items. The PM cues were embedded in the OT and were never presented among the last three to-be-remembered pictures. The PM cues appeared eight times within the OT, with a presentation rate of roughly one every 2 min as is usual in PM paradigms (Brandimonte & Passolunghi, 1994). Whenever a PM cue appeared on the screen, participants had to press the space bar. Consequently, the PM task was focal or highly overlapping with the OT (Einstein et al., 2005). All participants performed the OT twice, once without (single OT) and once with embedded PM cues (dual OT). The presentation order was randomized across participants. After being explained about the task procedure, participants were also instructed to be as fast and accurate as possible. After completing a practice phase and being asked to repeat the instructions in their own words, the participants performed the experimental phase. Correct responses to the 8 PM cues as well as RTs of correct responses were considered for PM task performance. For OT performance correct responses to the probe pictures at the end of each list as well as RTs of correct responses were considered for each the single (n = 32) and the dual OT (n = 32).

FIGURE 1 Schematic representation of the computerized updating working memory task used for the ongoing task with an embedded prospective memory (PM) cue. Participants were told that they would see a series of pictures presented one by one on the computer screen and that each list could be composed of three to six pictures. They had to always remember the last three pictures of each list without knowing in advance how many pictures would be presented. Each list ended with a fixation cross (fifth picture in the example list) followed by a probe picture (last picture in the example list) and participants were asked to decide whether it was part of the last three pictures of the previously presented list by pressing the yes-key or no-key. In the example list the correct response would be "yes". In the PM block, participants had to additionally press the space bar whenever one of 3 PM cues appeared (first picture in the example list).

Go/no-go task 

Inhibitory control was measured by using a go/no-go paradigm (e.g., Brocki & Bohlin, 2004). The computer-based task was designed and run on Presentation software and consisted of two parts, one including only go stimuli (yellow dot on black background; n = 30) and the other consisting of both go (n = 15) and no-go stimuli (blue dot on black background; n = 15). Go and no-go stimuli were randomly presented and with a random interstimulus interval (ranging from 800 to 1200ms). The participants had to press the spacebar whenever a go stimulus was presented, whereas they had to inhibit their response whenever a no-go stimulus appeared. The presentation of the task including only go stimuli and the one including go and no-go stimuli was randomized across participants. Accuracies (i.e., responding correctly to go-stimuli) and RTs for correct responses were considered. 

Corsi block-tapping task 

The Corsi block-tapping task (Milner, 1971) was used to evaluate participants' visuo-spatial WM span. The participants were shown nine identical blocks, which were randomly arranged on a board, in different and asymmetrical spatial locations. The experimenter pointed to a sequence of blocks one at a time at 1-s intervals. The participants had to then point to the same blocks in identical order. The length of the block sequences gradually increased from two blocks to nine blocks. The task was stopped when the participant could not correctly reproduce two block sequences of the same length. The longest correctly reproduced block sequence was considered the visuo-spatial span.

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Teacher assessments of children's academic achievements 

The participants' school grades in all school subjects (e.g., mathematics, languages, science, etc.) were collected from the first semester of the year (i.e., September – February), during which time the experiment took place. Grades were given by teachers and could range between 4 (=unsatisfactory) to 10 (=excellent). These were averaged in order to obtain one single final mean score of school grades for each participant. 

Social skills questionnaire 

To measure children's social skills, the "Indicators of Social Development" questionnaire (Pastorelli et al., 1997) was administered to the children (self-rated evaluations) as well as to their teachers (teacher evaluations). Both versions of the questionnaire were divided into three scales evaluating emotional instability (EI; 13 items), physical and verbally aggressive behavior (PVA; 13 items), and prosocial behavior (PSB; 15 items). Example items for the EI scale were "He/she is impatient" or "It is hard for him/her to stay still"; for the PVA "He/she gets into fights" or "He/she insults other kids or calls them names"; and for the PSB scale "He/she tries to make sad people happier" or "He/she tries to help others". The responses were given on a 3-point Likert scale ranging from 1 (=never) to 3 (=often). The reliability of the social skills questionnaire is α = .93 for the EI, α = .85, for the PSB, and α = .93, for the PVA scale. Since the focus of the present study was on teacher's evaluations of children's social competencies, children's self-ratings were not considered in the analyses.

Procedure 

Participants were tested by four trained experimenters. They were first evaluated individually in a quiet room near their classroom for approximately 45 minutes. Participants were assessed on the OT without embedded PM task, and the OT with the embedded PM task, while both the Corsi block-tapping task and the go/no-go task were administered between the two main tasks. The order of presentation of the single and dual tasks was randomly assigned between participants. At the end of the individual session, each child could choose a coloring page as a reward for participation. Social skill questionnaires were administered in the classroom and were left to teachers for their completion (teachers had to answer the three EI, PVA, and PSB for each child in the classroom). 

Data analysis 

For performance on the OT, the PM and the go/no-go tasks, accuracy (percentage of correct responses) and mean RTs in milliseconds (ms) of correct responses were calculated for each participant separately. To control for abnormal RTs within each participant for the OT and the go/no-go task, RTs were adjusted for outliers for each task and for each participant separately by using boxplot analyses. These permitted exclusion RTs which were below the 25th and above the 75th percentile from the median RTs. In addition to considering correct responses and RTs, rate residual scores (i.e., the rate of correct responses per second) were calculated for the OT and PM tasks to obtain a score that comprehends information relative to both accuracy and RTs (Cottini & Meier, 2020; Hughes et al., 2014). Efficient performance is represented by higher rate residual scores. Statistical analyses were run on the free statistical software R (R Core Team, 2016). Descriptive statistics considering children's mean raw scores on the different tests were calculated separately for each age group. An independent sample t-test was performed to evaluate age-related differences between 8-year-old (Group 1) and 12-year-old children (Group 2). The relations between the various cognitive measures, grades, and social skills evaluations were preliminarily analyzed with a series of Pearson correlations, conducted separately for each age group: the p-values were adjusted with the Benjamini and Yekutieli method (2001), in order to take into account the dependency between the correlation tests. Subsequently, a multigroup structural equation model (SEM) was conducted using the la vaan package (Rosseel, 2012) to compare the two age groups on the hypothesized influence of cognitive abilities (i.e., WM and inhibitory control), teachers' evaluations of social skills and PM abilities on grades, and children's PM and cognitive abilities on social skills evaluations. The model's goodness of fit was evaluated following criteria recommended by Kline (2012). Consequently, a good model fit was represented by a non-significant chi-square value, a Root Mean Square Error of Approximation (RMSEA) a Standardized Root Mean Square Residual (SRMR) smaller than .08, a Tucker–Lewis index (TLI) and a Comparative Fit Index (CFI) equal to or greater than .90 to .95. For the multigroup SEM, the observed variables related to the EI, PVA and PSB scales of teachers' social skills evaluations were grouped into one latent variable. This was included both as a predictor of children's grades, together with PM performance and visuospatial WM span, and as a predicted variable of PM performance and inhibitory control. Moreover, a covariance relationship was assumed between visuospatial WM span and inhibitory control, and these two variables were also treated as predictors of PM performance. The estimation method used to fit the SEM was the maximum likelihood estimation, and because of the presence of 17 Missing values in EI, PVA, and PSB, an expectation–maximization algorithm was used to find the estimates of the model's parameters. Furthermore, robust estimates of the parameters' standard errors (sandwich estimator) were used to be safer from the deviation of some variables from the normality assumption, which was needed to estimate the model. The global fit of the model was satisfying: χ2 (20) = 17.288, p = .634, TLI = 1.000, CFI = 1.030, RMSEA = .000, SRMR = .056, and the residual correlation between all the observed variables was almost zero for both age groups. Power analyses were conducted with G*Power 3 (Faul et al., 2007) to determine the appropriateness of our sample size to detect a medium effect size (power = .80 and α = .05). For independent-sample t-test the minimum number of participants to reach the desired power was 64 per group, whereas for correlations the minimum number was 67. According to Nunnally and Bernstein (1967), the minimum sample size required for SEM should be at least 10 times the number of the observed variables. Since the model in the present study includes seven variables, a minimum sample size of 70 would be required in each group. Consequently, the size of our sample was appropriate. 

RESULTS 

Age-group differences in prospective memory, executive functions, social skills, and academic achievement 

Means and standard deviations of the participant's cognitive measures, grades, and social skills evaluations as well as age-group differences calculated by means of t-tests are shown in Table 1. Although the two age groups did not differ in accuracy, 12-year-old children were significantly faster than 8-year-olds in performing the ongoing and PM tasks. Similarly, rate residual scores were significantly different between the two age groups, with older children being more efficient in performing the tasks than younger children. Older children also outperformed younger children on the Corsi block-tapping task and were significantly faster than younger children in performing the go/no-go task. However, the two groups did not differ in go/no-go accuracy. Although children's cognitive abilities generally improved from 8 to 12 years of age, their academic performance decreased. In fact, 12-year-old children obtained significantly lower grades than 8-year-olds. Since the two age groups are in different school levels it is likely that both demands and grading methods would differ between younger and older children. Furthermore, significant developmental changes also emerged in social skills evaluations, with teachers evaluating older children as being less emotionally unstable and aggressive than younger children.

TABLE 1 Means (and standard deviations) of scores for each age group and t-tests for the differences between age groups in the various measures

The relation between prospective memory, executive functions, social skills, and academic achievement 

Preliminary analysis 

The results of correlational analyses are presented in Table 2. The results showed that in 8-year-old children, the cognitive variables related to OT were significantly correlated with each other. Children's grades were significantly related to both cognitive measures (single OT, visuospatial WM span) and almost all scales of the social skills questionnaire, with medium effect sizes (range: r =.44 to .53). Finally, the two scales of the social skills questionnaire EI and PVA were significantly related with each other while PSB was related only with PVA. The results related to 12-year-old children showed that of the cognitive measures, PM correlated with dual OT, which was significantly related to visuospatial WM span. Moreover, the single OT was significantly correlated with go/no-go RTs and WM span. Grades were significantly negatively correlated with teachers' evaluations on the EI and PVA scales. Finally, the two social skills scales EI and PVA were significantly related to each other while they did not relate to the PSB scale.

TABLE 2 Pearson correlations between the various measures for each age group

Structural equation model 

Figure 2 shows regression weights (and their significance levels) of relations between the variables separately for each age group. In 8-year-old children (Figure 2a), grades were significantly predicted by PM, WM span, and teachers' evaluations of social skills; that is, children who obtained high scores on the PM task, the Corsi-block-tapping task, and who were evaluated by their teachers as less emotionally unstable and aggressive and with a greater pro-social attitude were also those children with better grades. Social skills evaluations were also significantly predicted by go/no-go performance. Consequently, those children who obtained a high performance on the go/no-go task were also those who were evaluated by their teachers as being less emotionally unstable and aggressive and with a greater pro-social attitude. Finally, social skills were not predicted by PM performance in this age group. In 12-year-old children (Figure 2b), grades were significantly predicted by PM performance and teachers' evaluations of social skills (but not by WM span), and so in this age group, children who obtained high scores on the PM task and who were evaluated by their teachers as less emotionally unstable and aggressive and with a greater pro-social attitude were also those children with better grades. Even in this case, social skills were not predicted by PM performance, and only for this age group was the go/no-go task not significantly related to social skills evaluations. Finally, PM performance was positively predicted by performance in the go/no-go task.

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DISCUSSION 

The present study aimed to investigate (1) whether and to what extent children's PM abilities would affect teachers' evaluations of academic performance and social skills; and (2) which is the relation between executive functions, PM, academic performance, and social competencies. Our principal hypotheses were whether participants' academic achievements would be affected by both PM performance and social skills evaluations and that the latter would also be predicted by PM performance. This expectation was only partially confirmed by our results. First, the results showed that children's grades were predicted by both their PM performance and teachers' evaluations of their social skills. Participants with better PM performance also obtained higher grades from their teachers compared to participants with low PM performance. This shows that PM abilities have an impact on teachers' evaluations of children's academic achievements. Teachers evaluated children as being less academically competent when they had a worse PM. On the one hand, this finding could confirm Munsat's claim (1965), that people with bad PM would be negatively perceived by others, which might also occur in school. Similarly, a recent study showed that adults tend to judge children, especially older children, with bad PM as having a flawed personality (Moeller et al., 2021). On the other hand, the influence of PM over grades could have been mediated by other cognitive skills, which may contribute to both PM and academic performance. Notwithstanding, while considering both age groups, a single effect of WM was found for the 8-year-old group only. No contribution of WM for the 12-year-old group or inhibition for either group was found. Therefore, although the relevance of other processes, such as planning and monitoring, still needs to be investigated, this alternative explanation does not seem to hold. Further support of biased evaluations of academic achievements is the significant relation between social skills evaluations and grades. In fact, children who were evaluated by teachers as having low social competencies were also those who obtained worse grades. This result can be considered in line with previous research showing that grades were influenced by personality factors rather than being a representation of children's sole academic competencies (Neuenschwander et al., 2013). Contrary to the hypotheses, teachers' evaluations of children's social skills were not affected by their PM performance. Based on Munsat (1965) and the recently published study by Moeller et al. (2021), it was expected that children with low PM performance would also be evaluated as being less socially skilled than participants with higher PM ability. However, our model did not reveal a significant relation between PM performance and social skills evaluations. This might be because, in Moeller et al.'s study, adults were asked to give judgments about personality characteristics by using specific adjectives (e.g., kind, friendly, trustworthy, capable, competent, intelligent, and conscientious). In general, forgetful children were judged more negatively than children with good PM. The measure used in the present study evaluated social skills, and not personality traits, presented in the form of situations in which different social skills can be observed (e.g., gets mad, for emotional instability; shares things with friends, for prosocial behavior; gets into fights, for aggressiveness). Hence, personality traits might be easier to associate with PM abilities, since people who often do not come to appointments can be seen as unreliable or people who always deliver their work on time as capable and competent. Consequently, PM abilities might be more likely to influence the evaluation of personality traits harming social relationships. In fact, forgetfulness within social relationships might be more easily interpreted, for instance, as indifference towards another person. PM abilities might be less likely to influence evaluations of people's general social skills since a person might be seen as unreliable and untrustworthy but at the same time as gentle and helpful. Future studies might evaluate personality traits in addition to social skills and PM performance. Alternatively, fewer abstract questions could be asked to teachers in order to evaluate their perception of students' reliability in classroom-related issues, such as how much responsibility the teacher would give to a student in different tasks (e.g., leading a group of peers, bringing a message to the school principal, etc.). This could shed light on the different impacts of social skills, personality traits, and PM abilities on children's academic achievements, as well as on the interrelation between the three aspects. Future research should also include a standardized measure of academic competencies in addition to school grades to evaluate the different impacts of these factors on objective and subjective evaluations of pupils' academic skills.

FIGURE 2 Parameter estimates for the multigroup structural equation model showing relations between cognitive measures, PM, teachers' evaluations of social skills, and academic achievement (grades) in (a) 8-year-old and (b) 12-year-old children. The rectangles indicate the observed variables, while the ellipse indicates the latent variable. The black solid lines indicate a regression relationship, while the dashed lines indicate the observed variables composing the latent factor. Fit indices according to Kline (2012): χ2 (20) = 17.288, p = .634, TLI = 1.000, CFI = 1.030, RMSEA = .000, SRMR = .056. ***p≤.001, **p≤.01, *p≤.05.

Finally, PM performance was expected to improve from age 8 to 12 years with WM and inhibitory control being related to PM performance (Cheie et al., 2021; Shum et al., 2008; Yang et al., 2011; Zuber et al., 2019). Although there were no developmental improvements in PM accuracy, 12-year-old participants were significantly faster than 8-year-olds. When considering the efficiency of performance (i.e., rate residual scores), 12-year-old children were more efficient in performing the PM task than 8-year-olds. Nevertheless, the developmental improvement between the ages of 8 and 12 years was quite small. This result is likely to depend on the locality and specificity of the PM task used in this study. According to the executive framework of PM development (Mahy et al., 2014) and based on multiprocess views (Einstein et al., 2005; McDaniel et al., 2015), age-developmental changes are less pronounced when PM tasks are focal than when they are non-focal. Moreover, the PM task used in the present study was also well specified; that is, participants had to remember three specific objects, which has been shown to rely more on retrospective memory and less on executive resources (Cottini et al., 2018; Hicks et al., 2005). This can also be seen in the high accuracy rates obtained by 8- and 12-year-old participants in this study. Furthermore, this would explain why PM performance was not related to WM span, suggesting that the PM task used in this study was not that resource-demanding. Similarly, other studies have shown that performance on focal and specific PM tasks does not always relate to performance in executive functions tasks (e.g., Cottini et al., 2019; Fuke & Mahy, 2022). On the other hand, in 12-year-old participants, inhibitory control abilities resulted in the prediction of PM performance, suggesting that this ability might become relevant only later in childhood with this type of PM task. Although these findings are not fully in line with our expectations, they confirm previous studies suggesting that PM task characteristics, such as locality and PM cue specificity rely on fewer executive processes (Einstein et al., 2005; Mahy et al., 2014). Future studies should test whether not only age effects but also effects on academic achievement and social skills may depend on the task chosen in this study. It should be assessed whether different types of PM tasks, such as more resource-demanding or more ecological PM tasks, may lead to similar results. In this vein, a further limitation might be the external validity of the PM task used in this study. The commonly used laboratory-based PM tasks might not be able to fully capture children's PM abilities in everyday life. Thus, it would be highly recommended for future studies to include ecological measures of PM, such as asking children to bring something to school or to include parent- or teacher ratings of children's PM (e.g., Fuke & Mahy, 2022) in order to increase ecological validity and generalizability of results. 

CONCLUSION 

In sum, the main result of the present study revealed that children's school grades were negatively affected by both their PM performance and social skills, although independently. This study shows that teachers' evaluations of students' academic competencies can be biased due to personal skills not related to their performance. This result deserves more attention from educators. In fact, neither PM nor social skills are directly assessed in school, but they still influence teachers' evaluations of academic performance. Further evidence is needed to confirm these results in a more ecological setting and to explore in more detail the various aspects that might influence children's academic achievements. This line of research is expected to have an important impact on educational practices by raising teachers' awareness about biases that can occur in students' evaluations. Moreover, teachers are not only responsible for their student's acquisition of academic competencies but also for their behavioral education. Teachers are expected to intervene and adjust children's negative behavior, such as when they rarely do or complete assignments, or do not follow teachers' instructions and requests. The present study highlights that this negative behavior might not always be a consequence of a negative attitude but can depend on the incomplete maturation of the cognitive system. Thus, it would be detrimental to apply the same intervention to a child with a negative attitude and one whose negative behavior is caused by an immature cognitive system. Teachers should be informed about the development of the various processes which can influence children's behavioral outcomes and learn to distinguish between the reasons for student's behavior in order to be able to plan appropriate interventions.

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