Does Academic and Social Self-Concept and Motivation Explain the Negative Grading Effect on Students´ Subsequent Achievement?
Author(s):
Alli Klapp (presenting / submitting)
Conference:
ECER 2017
Format:
Paper

Session Information

09 SES 08 B, Investigating the Validity of Assessment and Grading Practices and Their Effect on Student Achievement

Paper Session

Time:
2017-08-24
09:00-10:30
Room:
W5.18
Chair:
Stefan Johansson

Contribution

Researchers, policymakers and society at large seem to agree that summative assessments such as grading and testing affect students´ learning and achievement in school. In several reviews on the impact of summative assessments on students´ learning, motivation and achievement, it has been shown that low-achieving students are negatively affected by high-stakes testing and grading (Harlen & Deakin Crick 2002; Natriello 1987), that some students experience test-anxiety (Harlen & Deakin Crick 2002), and in many cases, students would learn more if not being assessed in high-stakes summative environments (Black & Wiliam 1998; Crooks 1988; Kluger & DeNisi 1996). In two previous studies, summative assessment (grading) was found to have a differentiating effect on students´ subsequent achievement in school where grading in 6th Grade affected low-achieving students´ subsequent achievement negatively, compared to ungraded low-achieving students (Klapp, Cliffordson & Gustafsson, 2014; Klapp, 2015). The differences between low-achieving graded and ungraded students were significant with Cohen´s d .31. The difference between graded and ungraded high-achieving students was negliable with Cohen´s d .14. Students´ level of achievement was measured by cognitive tests.

One possible explanation for the negative grading effect may be that students´ non-cognitive or affective skills such as self-concept and motivation are affected by summative assessment regimes (Wentzel et al. 2010) and thus affect their learning and achievement in school (Harlen & Deakin Crick 2002). New information (grades) may thus have affected the low-achieving students negatively.

The Conservation of Resource Stress theory (COR) (Covington 2000; Frydenberg 2008; Hobfoll 1989, 2001) is an overall multi-disciplinary theory which builds upon the beliefs that humans are trying to keep, develop and gain personal resources in order to manage in difficult situations and throughout life. For students in school, resources are personal cognitive and non-cognitive skills such as academic and social self-concept, interest and motivation. When students´ resources are threatened, for example by failure in learning situations, in summative assessment situations and receiving bad school results, the loss of personal resources may cause emotional stress. The stress may in turn lead to negative and maladaptive learning strategies in order to avoid further losses and disparagement of school-work (Frydenberg & Lewis 2009).

In sum, literature suggests that constructs such as academic and social self-concept and motivation may be of importance for understanding why low ability students are negatively affected in their achievement when graded compared to low ability students who are not graded. It also seems as if there are differences regarding gender and socio-economic status and achievement.

Design of the study

Due to a unique natural circumstance, municipalities in Sweden could decide whether or not to grade their students in 6th Grade which made it possible to apply a quasi-experimental design. In the sample, 50 percent of the students were graded in 6th Grade while all students were graded in 7th Grade. By adding questionnaire data to the previous models (Klapp et al., 2014; Klapp, 2015), it was possible to investigate the importance of students´ academic and social self-concept and motivation to improve in order to explain the negative grading effect on low-achieving students.

 

Purpose

The purpose of the study was to investigate if academic and social self-concept and motivation to improve in academic school subjects mediated the negative effect of summative assessment (grades) for low-ability students´ achievement in compulsory school. Differences between subgroups of students (cognitive ability, gender and socioeconomic status) were controlled for in the analyses.

Method

Data was retrieved from The Evaluation Through Follow-up (ETF) longitudinal project containing register and questionnaire data on a large national representative sample of Swedish compulsory school students born in 1967 (N = 8 558). The sampling was conducted by Statistics Sweden and was a two-step stratified sampling procedure where municipalities were selected in a first step, and classes were selected in a second step. In all, 430 classes in 29 municipalities participated in the third cohort of the ETF project. The data used are school subject grades (GPA) in the 7th Grade, when the subjects were 13 to 14 years old. Information on results on cognitive tests, gender, socio-economic status (SES) and questionnaire data from the 6th Grade was used. GPA was used as dependent variable while Graded (in 6th Grade: 0=ungraded; 1=graded), Gender: 0=male; 1=female, Socio-Economic Status (SES: I-III) were used as independent variables. Confirmatory factor analysis (CFA), multiple multivariate regression analyses and structural equation models (SEM) have been estimated. The intra-class correlations (ICC) for the variables range from .003 to .045 for all the variables except for cognitive ability (ICC = .078) and SES (ICC = .109). To take account of effects of possible clustering of students in schools (school level), the “Complex” option offered by the Mplus program was used. As measures of model fit, the χ2 goodness-of-fit test and the Root Mean Square Error of Approximation (RMSEA) were used. The Comparative Fit Indices (CFI) measure was also used. This index should be as close to 1.0 as possible, and values below .95 are hesitant to accept (Bentler, 1990). The Tucker-Lewis Test (TLI) was used which is a measure similar to the CFI but has a penalty for models with many parameters. The TLI should be as close to 1 as possible but values above .90 is considered acceptable (see for example Hu & Bentler, 1995).

Expected Outcomes

Several steps in the modelling process were conducted. Here only the main steps are presented. A measurement model was estimated with four factors Self-concept in mathematics (ScMa), Self-concept in Swedish (ScSw), Self-concept in social situations (ScSocial) and Motivation to improve in academic subjects (MotImp) related to all their respective indicators. The goodness-of-fit indices for this model were acceptable (χ2 (34, 7 927) = 780.55; CFI = .936; TLI = .962; RMSEA = .053). Three regression models were estimated stepwise where the first model was a main model with GPA in 7th Grade regressed on the variables Graded, Cognitive ability, SES and Gender. No significant effect for Graded on GPA7 occurred. The second model included interactions between the variables and a significant effect for Graded on GPA7 became evident (β = -.043). The final saturated model included the significant interaction effects and the four factors (ScMa, ScSw, ScSoc and MotImp) and the result showed that when including the four factors the significant grading effect became non-significant. Therefore, the next step in the modelling process was to estimate models with direct and indirect relations. The result show that the negative effect of summative assessment (grading) for low ability students on their subsequent achievement is fully mediated by academic self-concept in mathematics and Swedish, and motivation to improve in academic school subjects. However, self-concept in social situations did not explain the negative grading effect on low-achieving students. This result suggests that the negative grading effect for low ability students seem to be explained by their lower academic self-confidence and beliefs that they need to improve their academic skills. However, reciprocal relations between assessment and non-cognitive competencies may explain the grading gap between graded low ability students and ungraded low ability students and why they are affected differently by grading (Marsh & O´Mara 2007; Martin et al. 2010).

References

Bentler, P.M. (1990). Comparative indexes in structural models. Psychology Bulletin, 107, 238-246. Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education, 5(1), 7-74. Covington, M. V. (2000). Goal theory, motivation, and school achievement: An integrative review. Annual Review of Psychology, 51, 171–200. Crooks, T. (1988). The impact of classroom evaluation practices on students. Review of Educational Research, 58, 438-481. Frydenberg, E. (2008). Adolescent coping: Advances in theory, research and prac¬tice. London & New York: Routledge, Taylor & Francis Group. Frydenberg, E., & Lewis, C. (2009). The relationship between problem-solving efficacy and coping among Australian adolescents. British Journal of Guidance and Counselling, 37(1), 51-64. Harlen, W., & Deakin Crick, R. (2002). A systematic review of the impact of summative assessment and tests on students´ motivation for learning (EPPI-Centre Review, version 1.1*). In: Research Evidence in Educational Library. Issue 1. London: EPPI-Centre, Social Science Research Unit, Institute of Education. Hobfoll, S. E. (1989). Conversation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513-524. Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254-284. Marsh, W. H., & O´Mara, A. (2007). Reciprocal effects between academic self-concept, self-esteem, achievement and attainment over seven adolescent years: Unidimensional and multidimensional prospects of self-concept. Personality and Social Psychology Bulletin, 542-552. Martin, J. A., Colmar, H. S., Davey, A. L., & Marsh, W. H. (2010). Longitudinal modelling of academic buoyance and motivation: Do the `5Cs` hold up over time? British Journal of Educational Psychology, 80, 473-496. Natriello, G. (1987). The impact of evaluation processes on students. Educational Psychologist, 22, 155-175. Wentzel, K. R., Battle, A., Russell, S. L., & Looney, L. B. (2010). Social supports from teachers and peers as predictors of academic and social motivation. Contemporary Educational Psychology, 35(3), 193–202.

Author Information

Alli Klapp (presenting / submitting)
Gothenburg university
Lund

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