**3. Results**

The responses to correct trials and error trials differed in both groups. Moreover, as expected, differences of error-monitoring ERPs between growth and fixed mindset students emerged, suggesting different attention allocation to mistakes, which is believed to play an important role in bouncing back after failure (**Figure 2**). It can be seen from the data that the difference curve calculated between the correct and error trials was larger in children with fixed mindset when compared to children with growth mindset. In the frontal areas (observed at Fz channel) in the early latencies 100–200 ms after response (the button press), the ERN amplitude (calculated as the difference between positivity on error trials and relative to that on correct trials, see **Figure 3**) is larger in the children with fixed mindset. There is no difference in the shape or timing of the ERN response in the two groups.

The data also show clear differences between the groups in the Pe component, the difference signal calculated between the correct and the error trials in the parietal electrodes (observed at Pz channel) in later latencies (200–500 ms after response). Fixed mindset was associated with larger Pe difference than growth mindset.

#### **Figure 2.**

*Response-locked waveforms for correct and error trials in fixed (upper panel) and growth mindset groups (lower panel) at frontal Fz (left) and parietal Pz (right) electrodes.*

**Figure 3.** *Response-locked subtraction signals in fixed and growth mindset groups at frontal Fz (left) and parietal Pz (right) electrodes. Here, response to correct trials is subtracted from the response to the error trials.*

At the behavioral level, growth mindset participants showed decreased posterror accuracy, meaning that they got less correct responses on trials following error hits than on trials following correct hits; this was opposite for the fixed mindset group. There was no considerable difference in post-error reaction times, but overall reaction times were shorter for the fixed mindset group, especially in error trials. Fixed mindset participants also made less error hits and more correct hits, i.e., their overall performance was slightly better. This is in line with results by Torpey et al. [31], who found that a more positive Pe is associated with greater accuracy and shorter reaction time in error trials. Overall, these results suggest that participants with a fixed mindset responded faster and, while allocating attention to errors, did not show improvement/adjustment in behavioral terms, such as post-error slowing.

## **4. Discussion**

This pilot study contributes to the international mindset research by testing the mindset theory and experimental design, previously used in North America, in the Finnish context. It also provides evidence for differences in the neural mechanisms of attention allocation and in automatic reactions to errors between individuals with growth and fixed mindsets. Namely, in this study, the ERN amplitude was larger in the children with fixed mindset. Large ERN can be interpreted as more neural resources allocated to the detection of the error and also the further processing after detecting the error [32]. In addition to this, fixed mindset was also associated with larger Pe difference than growth mindset. These responses may reflect further processing of the errors, recovery after the errors, and reallocation of attentional resources to avoid future errors [33]. This suggests that fixed mindset children in this pilot study seem to invest a lot of effort in processing their errors and reorienting after the error has occurred. Growth mindset students also showed decreased post-error accuracy, while this was opposite for the fixed mindset group.

Interestingly, even though clear differences between the two groups emerged, these findings are somewhat inconsistent with the results from previously conducted research in North America [14, 17]. Namely, researchers [14, 17] have found growth mindset to be related to an enhanced amplitude of the Pe and better accuracy after mistakes, but not to ERN. Thus, the findings on the amplitude of Pe and

*Mindsets and Failures: Neural Differences in Reactions to Mistakes among Second-Grade Finnish… DOI: http://dx.doi.org/10.5772/intechopen.85421*

also post-error accuracy were strikingly different from the findings from the North American studies. In addition to this, in this pilot study, differences in ERN were found, while this did not differentiate between growth and fixed mindset participants in the North American studies.

One possible explanation for this difference in the results of this pilot study, when compared to previous studies, is the young age of the participants. Namely, ERN seems to fluctuate during development [34]. Consistent with this, researchers [35] showed in their study that in younger children (8-to-10-year-old), a smaller ERN related to parent-reported anxiety, whereas in older children (11–13-yearolds), a larger ERN was significantly related to anxiety [35]. Consequently, the authors of the mentioned study discussed that it is possible that the relationship between increased error-related brain activity and anxiety may not emerge before early adolescence. Thus, one could speculate that it might be the same regarding the relationship between ERN and mindsets.

When discussing the differences between the results concerning Pe in this pilot study and previous studies, it is worth to mention that also Schroder and colleagues [17] showed that more attention allocation to errors (Pe) is not necessary for growth mindset children to recover from mistakes. Indeed, they did not find Pe to have the mediating role in recovering from mistakes as it had for grown-ups in the study conducted by Moser and colleagues [14]. Also the correlation found between growth mindset and Pe in study [17] on children was rather modest, and there were actually many growth mindset children who had average or below average Pe amplitudes. In addition to this, even though there is a difference in the time windows when compared to the current pilot study, in study [16] Schroder and colleagues found no differences in the early Pe (150–350 ms post-response time window) but found a smaller late Pe (350–750 ms post-response time window) amplitude in adult participants with an induced growth mindset when compared to the participants with an induced fixed mindset. Even though Pe has been shown not to have a similar age-related fluctuation as ERN [34], the inconsistencies of these findings might refer to other mechanisms involved in the processes of dealing with mistakes related to mindsets. Indeed, Meyer and colleagues also showed that smaller Pe amplitude related to greater parent-reported anxiety only among older children, with younger children's anxiety level having no significant effect on Pe [35]. Thus, taking into account the mentioned research concerning ERPs, it is possible to speculate that as the ERN fluctuates during development, a clearer relationship between increased error-related activity and mindset also may possibly not emerge before early adolescence, at least concerning ERN. The findings on Pe in this study, though, are somewhat controversial when compared to other studies and require further research on the developmental processes involved in error-related brain activity and mindsets, as the results suggest that there might be other mechanisms involved in the processes of dealing with mistakes when it comes to mindsets. Thus, in the future it would be important to conduct more research on the neural mechanisms related to mindsets among different age groups, including more participants and including both boys and girls as the current pilot study had a small sample size and only included girls as participants. Moreover, it would also be important to include participants from different schools and possibly more diverse socioeconomic backgrounds.

In addition to this, the results of this pilot study might differ from the previous ones due to a different cultural context. As mentioned in the first part of this chapter, there are studies that refer to possible culture- and context-dependency of mindsets [7, 19–21]. Thus, it would be important to study mindsets in different cultural contexts and also conduct comparative studies investigating mindsets, their functioning, and relations to neural mechanisms.

None of the neuroscientific research concerning mindsets has taken academicdomain-specificity into account. Previous studies using EEG recordings have measured mindsets about and used a task/test addressing general intelligence [13]; measured or induced mindsets about general intelligence [14, 16, 17] and the EEG measurements have been done during a completion of a go/no-go task or a Flanker's test. Even though the mindset measurement reflects the general underlying dimension of the mindset tendency in addition to the directly reflecting the mindset about intelligence [36], it is possible to speculate that the go/no-go task or Flanker's test used might not be reflecting the domain of intelligence for the participants. As these ERPs are measured and should theoretically reflect automatic reactions to errors of a person with a growth vs. fixed mindset, the ERPs may reflect the person's implicit beliefs in another domain than intelligence, which was measured or induced in these studies. Rather one could speculate that these tests might resemble more of a computer game than a test concerning intelligence, and thus, it might be more relevant comparing these ERPs regarding a growth vs. fixed mindset about the ability to play computer games, which might be remarkably different from the mindset that the individual holds about their intelligence or other domains like mathematics. Indeed, among these studies, as mentioned above, only Mangels and colleagues [13] have used a design, where the mindset measured and task used for EEG measurements match in their domains. Namely, they used measures of theories of intelligence (TOI) and a task, which included general knowledge questions. As mindsets, though, have been shown to have such considerable relations to academic outcomes [7], one important future direction would be measuring academic-domain-specific mindsets and using tasks/tests from the matching academic domain during the EEG measurements. This would enable to study the automatic reactions to errors in the specific academic domain of the held mindset and would thus yield to theoretically more sound results. One possibility to do this would be to modify the go/no-go task or Flanker's test to be more domain-specific, for example, resembling a math test and then comparing the ERPs from this test to the participants' academic-domainspecific (math-specific in the case of this example) mindsets.

All in all, understanding the neural mechanisms related to mindsets will enable, when combined with findings from other fields of research, the planning and construction of more successful interventions to encourage growth mindset. Taking into account the underlying neural mechanisms and structures of mindsets will enable to tap into how these implicit beliefs interact with cognitive and also other higher psychological processes, in order to improve students' learning experience and results. Moreover, it will help to understand how these interactions affect behavioral outcomes not only in the academic but also a variety of other contexts.

## **Notes**

The earlier version of this chapter was presented in April 2019 as a talk at the International State-of-the-Art Symposium: Recent connections between Brain, Neuroscience and Education, which was part of the American Educational Research Association (AERA) Annual Meeting 2019 in Toronto, Canada.
