Capturing the interconnected and interpersonal nature of emotion concepts: implications for social-emotional learning
Keywords: semantic networks
personality
task development
emotion concept
child development
thematic analysis
cross-sectional
trait attribution
interpersonal accuracy
meta-analysis
social-emotional learning
data visualization
multi-method study
emotion understanding
linguistic analysis
interpersonal accuracy task
emotion representation
social connectedness
systematic review
young adult
middle childhood
mixed-methods
SEL
undergraduate

The current multimethod study adopts a developmental perspective to address how emotional learning relates to social learning and its import to education settings. The aim is to add to the social-emotional learning (SEL) literature by setting precedent for future research on how we identify emotions in others that simultaneously addresses the roles of language, temperament/personality, and interpersonal accuracy (IA). Three studies were undertaken to approach the main research question via different lenses. The first, a systematic review and meta-analysis of intervention studies with SEL programmes universally implemented in Primary Years 4 to 6, addressed the question of how emotions have been ‘taught’ in primary schools in the past decade, and whether SEL programme participation directly promotes child emotion understanding (EU). The second study, a linguistic analysis of child-produced emotion definitions, explored the relationship between emotion representation and emotion language across middle childhood. The third study focused on the impact of emotion representation on IA in a sample of first- and final-year undergraduates, and potential links with personality, the ability to identify and describe one’s own emotional states, and sense of social connectedness.
Results: A total of 54 studies were included in the review (Study 1) based on the presence of an SEL programme targeting a specific aspect of EU and transparent reporting of programme components. EU areas most frequently targeted were: ‘Recognition’ (38 programmes), ‘Regulation’ (33 programmes), ‘Decision/Action’ (33 programmes), ‘External Cause’ (30 programmes), and ‘Belief’ (26 programmes). A sub-set of 20 studies from the systematic review were included in the meta-analysis that indicated SEL programme participation had a small positive impact on child EU (Hedge’s g = 0.22) as compared to a control group.
Study 2 was a small-scale corpus analysis of 1,239 definitions of 27 emotions produced by 49 children (Mage = 9.24; SD = .75; 46.9% Female). All emotion words appearing in definitions co-occurred with at least one additional emotion term. Emotion term co-occurrence patterns were also operationalized as a ‘blend score.’ A significant regression equation was found between emotion term co-occurrence and non-emotional mental state term (MST) production (F(1, 47)= 20.879, p less than .001) with an R2 of .308; average MST production increased by 1.233 for each average blend score. Independent samples t-tests indicated a statistically significant difference based on gender for average MST production (t(47) = -2.811, p = .007), with female children producing more MSTs across emotion definitions as compared to male children, but there was no statistically significant relationship between gender and emotion blend score. Thematic analysis indicated that common topics across child emotion definitions included: interpersonal dynamics (e.g., rejection, conflict), experiencing a non-social situation (e.g., a disappointing/negative event), non-emotional human behaviour (e.g., sleeping), and performing an activity (primarily leisure, such as playing or reading a book).
Study 3, an online cross-sectional study with a sample of 150 undergraduates (67.3% Female; Mage = 19.93, SD = 2.05), found a small positive relationship between an emotion language manipulation (i.e., condition) on the researcher-developed IA task and below-average trait-based behaviour prediction accuracy (rs(148) = .18, p = .025). General difficulty appraising one’s feelings predicted self-reported levels of social connectedness (R2 = 0.147, F(1, 148) = 25.431, p less than .001), and was inversely correlated with personality dimensions—specifically participant ‘Extraversion’ (r(148) = -.19, p = .020) and ‘Agreeableness’ (rs(148) = -.20, p = .016). Social connectedness was also positively correlated with certain participant personality dimensions including ‘Agreeableness’ (rs(148) = .26, p = .001) and ‘Extraversion’ (r(148) = .29, p less than .001).
Conclusions: The three studies provide preliminary evidence in support of: a) the positive impact of SEL programme participation across middle childhood on EU development (Study 1); b) the interrelated nature of emotion concepts across middle childhood, the importance of context for anchoring EU, and a relationship between gender and MST production rates in emotion definitions across middle childhood (Study 2); and c) positive relationships between levels of social connectedness, the ability to describe and identify one’s own emotional states, and personality in young adults (Study 3).
To the researcher’s knowledge, this study is the first to: a) identify trends in how emotions have been taught across middle childhood by synthesizing SEL intervention literature to reflect broader emotion socialization practices in schools; b) provide statistically significant evidence of the direct impact of SEL programme participation on the development of child emotion understanding; c) provide evidence of spontaneous emotion term co-occurrence across definitions in order to stress the inter-relational dimension of emotion concepts from the child’s perspective, a consideration often lacking in SEL literature and programme content; and d) to directly explore the impact of emotion representation on IA. By ‘inter-relational’ is meant the interconnected nature of emotion concepts within a representational system as well as the primacy of social experience in forming the conceptual understanding of emotions.
In addition to findings, contributions to the field include the creation of a corpus of child emotion definitions, a data visualization protocol for translating emotion term co-occurrence patterns found in emotion definitions into network maps that highlight interrelationships amongst emotion concepts, and a new IA task that captures personality trait attribution, trait-based behaviour predictions, and trait covariance ratings. Implications for the promotion of social-emotional development in classroom settings (in particular the need to consider the classroom’s social-emotional reality pre-intervention) and the potential for student well-being are discussed, in addition to how SEL as a field can embrace individual and cross-cultural differences in understanding SEL programme implementation.