Indices of Favourable and Unfavourable Emotions in the Inter-Actional Context of the Classroom: Constructions from the Chilean Case
2. Theoretical Framework
2.1. Emotions and Learning
Theoretical Model: Favourable and Unfavourable Emotions for Learning
2.2. System for Measuring the Quality of Education
The Chilean Case
3. Materials and Methods
3.1. Literature Review
Data Sources, Search Strategy and Exclusion Criteria
3.2. Content Analysis and Validation through Expert Judgement
4.1. Literature on Emotions, Learning and Classroom Interactional Context
4.2. Content Analysis and Consistency with the Theoretical Model
4.3. Favorable and Unfavourable Emotion Indices for Learning
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
|Description||Methodological Tools to Assess Relationships among Emotions, Interactional Context and Learning|
|To evaluate a mindfulness intervention effects on classroom climate and academic outcomes, particularly regarding rading fluency.||14 school classrooms of 4th and 6th grade||Primary||QUAN||Quasi-experimental design (treatment and control group). Pre- and post-tests (controlling for confounding variables) to test the relationship between the intervention aimed at promoting emotional climate and classroom interactions and reading fluency achievement level.||Academic performance—reading fluency achievement level measured with Reading and Analysis Prescription System 360 (RAPS 360; MindPlay 2012).|
The potential impact of participation in the mindfulness intervention on reading fluency was measured using ANDEVA.
|The results associated with time were significant (Wilk’s lambda = 0.98, F (1, 286) = 6.44, p = 0.012, partial eta squared = 0.0).||Meyer and Eklund, 2020|
|596 students||Increased reading fluency was observed in control and treatment groups with no significant differences between them.|
|In subsequent measurements, the treatment group showed greater increases in fluency, but this difference was not statistically significant and could not be directly attributed to intervention participation.|
|To examine associations between RULER (SEL program) and changes in student engagement, conduct and academic achievements.||64 schools in one school district |
(n = 318 students)
|Diverse student population, preferably in early adolescence, in the northeast of the EEUU||QUAN||Analysis of multiple theoretical trajectories, with control and treatment group.||Student engagement was assessed by student report on the Engagement vs. Disengagement Scale (10 items; alpha, 0.89; Furrer and Skinner, 2003) and student reports of classroom climate and school motivation (Skinner et al., 2008).|
Academic performance was measured by calculating students’ academic subject grade point averages (GPA).
Student behaviour was obtained using teacher reports.
|Significant relationships between participation and behaviour in 5th grade for the control group and the RULER group were found; only the students who participated in RULER showed improvements in participation in sixth grade and in behaviour in seventh grade. No significant relationships were found between participation and academic achievement.||Cipriano et al., 2019|
|To test whether students’ participation in INSIGHTS tasks improved low socio-economic pre-school and first grade students’ achievement in mathematics and reading, through the prior improvement of emotional support and classroom organisation.||120 teachers and 435 students/parents duple in 22 public schools||Pre-school and primary education||QUAN||Randomised testing of school programmes. |
Multilevel regression analysis, instrumental variables estimation and inverse probability of treatment weight (IPTW) were conducted.
Pre- and post-tests were conducted to test the potential impact of intervention participation on improving classroom emotional and organisational climate and student outcomes.
|The emotional climate considered 4 dimensions of pedagogical practices: positive and negative climate, teacher sensitivity and consideration of students’ perspectives.|
Independent measurements were made of the relevant variables grouped as follows:
(a) Variables of outcome—achievement in reading and mathematics measured through total scores on the LetterWord Identification and Applied Problems subtests of the Woodcock–Johnson III Tests of Achievement, Form B (Woodcock, McGrew, and Mather, 2001).
(b) Variables of mediation
emotional support and classroom organisation—measured using the Classroom Assessment Scoring System (CLASS; Pianta, La Paro, et al., 2008).
|For pre-school there was no evidence of correlation.|
For first grade, emotional support was associated with higher achievement levels in mathematics (B = 0.89, SE = 0.38, p = 0.02), as was classroom organisational climate (B = 0.97, SE = 0.40, p = 0.0) There were no statistically significant relationships for reading.
|MacCornick et al., 2015|
|The results show that the INSIGHTS programme improved the climate of emotional support in the classroom and that, subsequently, this positively impacted first grade students’ academic achievement in mathematics.|
|To examine the role of teacher–student interactions in the classroom highlighting when they are predictive of academic achievement and also when they reflect pre-existing student characteristics.||643 students in 37 classrooms in (11 schools in 6 districts)||Secondary school||QUAN||Hierarchical linear modelling (Raudenbush and Bryk, 2002) was used as the conceptual and analytical framework for specifying two-level models examining the association between measures of classroom quality and students’ outcomes.||Observation of standardised classroom interactions using a modified version of the CLASS system, including domains of emotional support (positive climate, negative climate, teacher sensitivity and adolescent perspectives subscales), classroom organisation (behaviour management, productivity and instructional formats subscales) and instructional support (content comprehension, analysis and problem solving and quality of feedback subscales).|
Student achievement was measured using the Standards of Learning (SOL; Commonwealth of Virginia, 2005).
|All three domains (emotional support, classroom organisation and instructional support) were predictors of improvement of academic performance.||Allen et al., 2013|
|The strongest predictor was the emotional support domain. Class size interacted with emotional support (B = −4.81, SE = 2.00, p = 0.02) and instructional support (B = −3.54, SE = 1.78, p = 0.046), such that both emotional support and instructional support increased in predictive value for students in smaller classrooms compared to those in larger classrooms.|
|To assess the effect of students’ perception of the learning environment on their performance on a standardised licensing test controlling for prior academic ability.||N = 267||Higher education||QUAN||The results of students’ assessment of their learning environments were contrasted with their performance on Step 1 of the United States Medical Licensing Examination (USMLE).||Students’ perceptions of their learning environments were assessed using the previously validated Learning Environment Questionnaire (LEQ) (Moore-West et al., 1989), which contains 5 subscales: meaningful environment, emotional climate, student–student interaction, nurturance and flexibility.|
A linear regression was performed for each sub-scale of the applied test, including MCAT scores, GPA and gender in each model.
|Three of the five learning environment subscales were statistically associated with Step 1 performance (p < 0.05): meaningful learning environment, emotional climate and student–student interaction. A one-point increase in subscale scores (1–4 scale) was associated with increases of 6.8, 6.6 and 4.8 points on the Step 1 test.|
The findings provided evidence for the generalised assumption that a positively perceived learning environment contributes to better academic performance.
|Wayne et al., 2013|
|To examine whether (i) heterogeneity in students’ perceptions of classroom climate is related with their achievements in mathematics and (ii) heterogeneity in perceptions of classroom climate among students in the same grade is associated with academic achievement.||N = 1604|
82 math classrooms in 10 public schools
|Primary||QUAN||A latent profile analysis was conducted to characterise students’ perceptions of the classroom. Based on it, a model of five profiles was generated. Next, a measure of the heterogeneity of the profiles within each classroom was generated. Finally, multilevel modelling was conducted.||(1) Perceptions of classroom climate were collected through questionnaires and|
(2) performance was measured using mathematics class grades.
Controls for prior mathematics performance, ethnicity, number of students per grade and gender.
|Five student profiles were identified: 1. high Achievement focus (8%), 2. medium emotional support and high achievement (6%), 3. low emotional support (22%), 4. high emotional support (57%), 5. high emotional support and autonomy support (7%). The first and third profiles were negatively correlated with achievements in mathematics (r = −0.12, p=0.001 and r = −0.11, p = 0.001, respectively) and the fourth profile was positively correlated with achievements in mathematics (r = 0.14, p = 0.001).|
The level of heterogeneity of students’ perceptions of classroom climate within the same course was negatively related to the mathematics achievements of the course as a whole.
|Schenke et al., 2017|
|To assess the seven scales of medical interest: personal interest, emotional climate, flexibility, meaningful learning experience, organisation, support and student–student interaction.||311 medical students (40%):|
1st year, 120;
2nd year, 102;
3rd year, 89.
Age variation: from 20 to 42 years of age (M = 27.7, SD = 3.7).
|Higher education||QUAN||A confirmatory factor analysis was conducted to test a 5-factor model for learning environments, assessing the correlation between its dimensions and students’ satisfaction and performance.||(a) Medical School Learning Environment Survey (MSLES).|
(b) Student satisfaction, measured on a seven-point scale.
(c) Academic performance: the overall grade of students at the end of their respective year.
Confirmatory factor analysis was used to support the validity of the MSLES when used with this sample.
Correlations between the dimensions of learning environment, student satisfaction and achievement were calculated using Pearson correlations.
|Positive correlations were detected between learning environment and academic performance and between learning environment and student satisfaction. The correlation was significant but weak (0.10–0.29).||Rusticus et al., 2014|
|Examining the influence of classroom climate and teacher behaviour on the Italian students’ results in the PISA 2012 test.||16,709 15 years old students (8276 male and 8433 female)||Secondary||QUAN||Classroom climate and teacher behaviour were assessed as predictors of student outcomes, accounting for differences in the sample sizes.|
Multilevel regressions with two levels and random intercepts were performed with the Mplus software (V6) and the plausible value estimation method (5 levels) was incorporated.
|Aggregate mathematics achievement percentages from the PISA test were used.|
Classroom climate and teacher behaviour were obtained at two levels.
The student level—items were selected from various background questionnaires included in the application of the PISA test. These items were included in the following indices:
(i) disciplinary climate index;
(ii) the teacher–student relations index;
(iii) teacher direct instruction index;
(iii) student orientation index;
(iv) formative assessment use index;
(v) cognitive activation strategies use index.
Indices were also used at the school level, incorporating responses from principals and students.
|The perception of classroom climate and teacher behaviour significantly affected students’ academic performance in the PISA test.|
The classroom climate index positively affected mathematics performance (regression coefficients of 2.77 and 13.82). Individual results overlapped with those obtained at the school level (the performance of a student who perceived a good classroom climate increased if he or she belonged to a school with better results on classroom climate).
The teacher–student relations index had a negative impact on mathematics achievements at both levels.
The aggregate of the four indices referring to teaching behaviour was statistically significant.
The index referring to the use of cognitive activation strategies was significantly positively correlated with mathematics achievements. In this case, the results at school level also overlapped with an additive effect. This index showed the strongest positive correlation with students’ academic results (increase of 28 points on average); it was followed by the classroom climate index (increase of 16 points).
Significant negative effects were observed in relation to the student orientation index (−22 points), use of formative assessments (−14 points) and direct teacher instruction (−14 points). This means that teacher behaviours and classroom climate that students perceived as characterised by frequent use of student guidance, use of formative assessments and direct instruction were significantly associated with lower achievement levels in mathematics.
|Bove et al., 2016|
|To examine patterns of school climate as perceived by students and their relationship with educational outcomes.||N = 5313 students (50.2% of female students is represented)||Most students attended the tenth grade. Less than 1% were ninth graders.||QUAN||Using a sample of Norwegian students who took the PISA test in 2015, the study integrated different stages of analysis aimed at identifying latent profiles of students’ perceptions of school climate (using the person-centred latent profile analysis approach), establishing the extent to which some of the students’ background variables determined their belonging to each profile and, finally, exploring differences between the profiles in educational outcomes, including science achievement and achievement motivation.||Students rated their opinions on a four-point Likert scale. The responses were used as overt indicators of a latent variable representing the underlying trait in PISA 2015.||Three profiles were evident: (1) students with consistently positive perceptions, (2) students with moderately negative perceptions and (3) students with extremely negative perceptions, especially with regard to teacher fairness and bullying.|
A strong correlation was detected between the identified profiles, and academic achievement and motivation in science.
In relation to science achievement, the difference between profile 1 (M = −0.526, SD = 0.988) and profile 2 (M = 0.059, SD = 0.988) was significant (d = −0.592, 95% CI between −0.702 and −0.482), as well as between profile 1 and 3 (M = 0.040, SD = 0.988; d = −0.573, 95% CI between −0.676 and −0.470). The difference between profile 2 and 3 was not significant (d = 0.019, 95% CI between −0.041 and 0.079).
|Rohatgi and Scherer, 2020|
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|Dimension 1. |
Emotions favourable to learning
Methodology and participation.
Relationship with teachers and student’s perception of them.
Relationship with peers.
Relationship with actors in the educational community (not specified).
Emotions unfavourable to learning
Methodology and participation.
Relationship with teachers and student’s perception of them.
Relationship with peers.
Relationship with actors in the educational community (not specified).
|Total number of items||57|
|Indices Identified||Components||Code||Type of Emotion|
Motivation arising from interaction
|3.8. My teachers motivate me to study and to make an effort.||p03_08||Favourable emotion|
|3.9. My teachers motivate me to improve every day.||p03_09|
|6.3. My teachers care about treating students well.||p06_03|
|16.1. The teachers encourage students to express our opinions.||p16_01|
|40.3. (The teacher) explains again if asked to do so by a student.||p40_03|
|40.4 The teacher explains the incorrect answers in the corrected tests.||p40_04|
|40.5. (The teacher) develops and explains in class the corrections of the guides and exercises.||p40_05|
|43.1. I feel fear that the maths tests will be difficult for me.||p43_01||Unfavourable emotion|
|43.3. I get nervous before maths tests.||p43_03|
|43.4. I get nervous if I don’t understand a maths assignment.||p43_04|
|16.2. My opinion is taken into account by my classmates.||p16_02||Favourable emotion|
|16.5. My opinion is heard in the classroom.||p16_05|
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Contreras-Quiroz, N.; Román-Soto, D.; Druker-Ibáñez, S.; Caldera-Mercado, J.; Rodríguez-Becerra, J. Indices of Favourable and Unfavourable Emotions in the Inter-Actional Context of the Classroom: Constructions from the Chilean Case. Educ. Sci. 2022, 12, 11. https://doi.org/10.3390/educsci12010011
Contreras-Quiroz N, Román-Soto D, Druker-Ibáñez S, Caldera-Mercado J, Rodríguez-Becerra J. Indices of Favourable and Unfavourable Emotions in the Inter-Actional Context of the Classroom: Constructions from the Chilean Case. Education Sciences. 2022; 12(1):11. https://doi.org/10.3390/educsci12010011Chicago/Turabian Style
Contreras-Quiroz, Natalia, David Román-Soto, Sofía Druker-Ibáñez, Jorge Caldera-Mercado, and Jorge Rodríguez-Becerra. 2022. "Indices of Favourable and Unfavourable Emotions in the Inter-Actional Context of the Classroom: Constructions from the Chilean Case" Education Sciences 12, no. 1: 11. https://doi.org/10.3390/educsci12010011