Skip to main content
SpringerLink
Log in

Consistency of report card grades and external assessments in a Canadian province

  • Published:
Educational Assessment, Evaluation and Accountability Aims and scope Submit manuscript

Abstract

The study investigated how well report card grades communicate to students and parents that state educational standards are being met, standards that are objectively measured by infrequently administered mandated assessments. Data sources were report card grades and external assessment scores for 2006–09 for Ontario Canada. The information that parents and students received about student performance from report cards and external assessments were similar (r s  = .47) to the r = .40–.60 range previously reported. Teachers assigned higher grades than external assessments warranted, even after a major source of construct irrelevant variance in report card grades (teacher ratings on multiple scales measuring student effort and school commitment) was controlled. The relationship of grades to assessment scores was robust across genders, school district types (Public versus Catholic) and language (English and French). Agreement of assessments was higher for grade 6 than for grade 3 and for Writing than for Reading or Mathematics. Report cards provided information about students’ future achievement that was accurate and delivered up to 2 years prior to the administration of external assessments. Seventy to 80% of students who reached the provincial achievement standard on one or both prior report cards were successful on the subsequent external assessment, compared to 30–50% of students who failed to meet the report card standard at least once.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Airasian, P. W., Engemann, J. F., & Gallagher, T. L. (2007). Classroom assessment: Concepts and applications (Canadianth ed.). Toronto: McGraw-Hill Ryerson.

    Google Scholar 

  • Assor, A., & Connell, J. P. (1992). The validity of students’ self-reports as measures of performance affecting self-appraisals. In D. H. Schunk & J. L. Meece (Eds.), Student perceptions in the classroom. Hillsdale: Erlbaum.

    Google Scholar 

  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman.

    Google Scholar 

  • Bassiri, D., & Schulz, E. M. (2003). Constructing a universal scale of high school course difficulty. Journal of Educational Measurement, 40(2), 147–161.

    Article  Google Scholar 

  • Bird, R. B., & Smith, E. A. (2005). Signaling theory, strategic interaction, and symbolic capital. Current Anthropology, 46(2), 221–248.

    Article  Google Scholar 

  • Blatchford, P. (1997). Students’ self assessment of academic attainment: accuracy and stability from 7 to 16 years and influence of domain and social comparison group. Educational Psychology, 17(3), 345–360.

    Article  Google Scholar 

  • Bowers, A. J. (2008). Reconsidering grades as data for decision making: more than just academic knowledge. Journal of Educational Administration, 47(5), 609–625.

    Article  Google Scholar 

  • Brennan, R., Kim, J., Wenz-Gross, M., & Siperstein, G. (2001). The relative equitability of high stakes testing versus teacher-assigned grades: an analysis of the Massachusetts Comprehensive Assessment System (MCAS). Harvard Educational Review, 71(2), 173–216.

    Google Scholar 

  • Brown, R. S., & Conley, D. T. (2007). Comparing state high school assessments to Standards for Success in entry-level university courses. Educational Assessment, 12(2), 137–160.

    Article  Google Scholar 

  • Bryk, A. S., & Raudenbush, S. W. (2002). Hierarchical linear models: Applications and data analysis methods. 2/E. Newbury Park: Sage.

    Google Scholar 

  • Burton, N. W., & Ramist, L. (2001). Predicting success in college: SAT studies of classes graduating since 1980. College Board Research Report No. 2001–2. New York: College Entrance Examination Board.

    Google Scholar 

  • Cizek, G. J. (2000). Pockets of resistance in the assessment revolution. Educational Measurement: Issues and Practice, 19(2), 16–33.

    Article  Google Scholar 

  • Cliffordson, C. (2008). Differential prediction of study success across academic programs in the Swedish context: the validity of grades and tests as selection instruments for higher education. Educational Assessment, 13(1), 56–75.

    Article  Google Scholar 

  • Coe, R. (2008). Comparability of GCSE examinations in different subjects: an application of the Rasch model. Oxford Review of Education, 34(5), 609–636.

    Article  Google Scholar 

  • Cousins, J. B., Ross, J. A., & Prentice, M. (1993). Teachers’ evaluation of correlational reasoning skills. Alberta Journal of Educational Research, 39(3), 297–317.

    Google Scholar 

  • D’Agostino, J. V., & Bonner, S. M. (2009). High school exit exam scores and university performance. Educational Assessment, 14(1), 25–37.

    Article  Google Scholar 

  • Dunn, J., Childs, R., Cleland, P., Pang, X., & Saunders, K. (2004). Isolating item and rater variance in the Grade 3 Assessment of Reading. Paper presented at the annual meeting of the American Educational Research Association, San Diego.

  • Education Quality and Accountability Office. (2006a). Grade 3 assessment of reading, writing, and mathematics: Framework. Retrieved February 22, 2006, from http://www.eqao.com/pdf_e/06/06P008e.pdf

  • Education Quality and Accountability Office. (2006b). Grade 6 assessment of reading, writing, and mathematics: Framework. Retrieved February 22, 2006, from http://www.eqao.com/pdf_e/06/06P008e.pdf

  • Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis and the interpretation of research results. Cambridge: Cambridge University.

  • Entwisle, D. R., & Alexander, K. L. (1988). Factors affecting achievement test scores and marks of black and white first graders. Elementary School Journal, 88(5), 449–471.

    Article  Google Scholar 

  • Firestone, W. A., & González, R. A. (2007). Culture and processes affecting data use in school districts. Paper presented at the annual meeting of the American Educational Research Association, Chicago. April.

  • Frederickson, J. R., & White, B. Y. (2004). Designing, assessments for instruction and accountability: An application of validity theory to assessing scientific inquiry. In M. Wilson (Ed.), Towards coherence between classroom assessment and accountability. 103rd Yearkbook of the National Society for the Study of Education, Part II (pp. 74–104). Chicago: University of Chicago Press.

    Google Scholar 

  • Friedman, S. J., & Frisbie, D. A. (1995). The influence of report cards on the validity of grades reported to parents. Educational and Psychological Measurement, 5–26.

  • Guskey, T. R. (2007). Multiple sources of evidence: an analysis of stakeholders’ perceptions of various indicators of student learning. Educational Measurement: Issues and Practice, 26(1), 19–27.

    Article  Google Scholar 

  • Kerr, K. A., Marsh, J. A., Ikemoto, G. S., Darilek, H., & Barney, H. (2006). Strategies to promote data use for instructional improvement: actions, outcomes, and lessons from three urban districts. American Journal of Education, 112, 496–520.

    Article  Google Scholar 

  • Kirst, M. W., & Reeves Bracco, K. (2004). Bridging the great divide. How the K-12 and postsecondary split hurts students, and what can be done about it. In M. W. Kirst & A. Venezia (Eds.), From high school to college: Improving opportunities for success in postsecondary education (pp. 1–30). San Francisco: Jossey-Bass.

    Google Scholar 

  • Koretz, D., Stecher, B., Klein, S., & McCaffrey, D. (1994). The Vermont portfolio assessment program: findings and implications. Educational Measurement: Issues and Practice, 13(3), 5–16.

    Article  Google Scholar 

  • Lamprianou, I., & Christie, T. (2009). Why school based assessment is not a universal feature of high stakes assessment systems? Educational Assessment, Evaluation and Accountability, 21, 329–345.

    Article  Google Scholar 

  • Leiter, J., & Brown, J. S. (1985). Determinants of elementary school grading. Sociology of Education, 58(3), 166–180.

    Article  Google Scholar 

  • Lekholm, A. K., & Cliffordson, C. (2008). Discrepancies between school grades and test scores at individual and school level: effects of gender and family background. Educational Research and Evaluation, 14(2), 181–199.

    Article  Google Scholar 

  • Lekholm, A. K., & Cliffordson, C. (2009). Effects of student characteristics on grades in compulsory school. Educational Research and Evaluation, 15(1), 1–23.

    Article  Google Scholar 

  • Martínez, J. F., Stecher, B., & Borko, H. (2009). Classroom assessment practices, teacher judgments, and student achievement in mathematics: evidence from the ECLS. Educational Assessment, 14(2), 78–102.

    Article  Google Scholar 

  • Martone, A., & Sireci, S. G. (2009). Evaluating alignment between curriculum, assessment, and instruction. Review of Educational Research, 79(4), 1332–1361.

    Article  Google Scholar 

  • Munk, D. D., & Bursuck, W. D. (2001). What report card grades should and do communicate perceptions of parents of secondary students with and without disabilities. Remedial and Special Education, 22(5), 280–287.

    Article  Google Scholar 

  • Ontario Ministry of Education and Training. (2000). Guide to the provincial report card, grades 1–8. Retrieved February 22, 2006, from http://www.edu.gov.on.ca/eng/document/forms/report/1998/repgde.pdf.

  • Pajares, F. (1996). Self-efficacy beliefs in academic settings. Review of Educational Research, 66(4), 543–578.

    Google Scholar 

  • Pezdek, K., Berry, T., & Renno, P. A. (2002). Children’s mathematics achievement: the role of parents’ perceptions and their involvement in homework. Journal of Educational Psychology, 94(4), 771–777.

    Article  Google Scholar 

  • Pomerantz, E. M., & Dong, W. (2006). Effects of mothers’ perceptions of children’s competence: the moderating role of mothers’ theories of competence. Developmental Psychology, 42(5), 950–961.

    Article  Google Scholar 

  • Popham, W. J. (1997). What’s wrong—and what’s right—about rubrics? Educational Leadership, 55(2), 72–75.

    Google Scholar 

  • Randall, J., & Engelhard, G. (2009). Examining teacher grades using Rasch measurement theory. Journal of Educational Measurement, 46(1), 1–18.

    Article  Google Scholar 

  • Ream, R. K., & Palardy, G. J. (2008). Reexamining social class differences in the availability and the educational utility of parental social capital. American Educational Research Journal, 45(2), 238–273.

    Article  Google Scholar 

  • Reeves, D. J., Boyle, W. F., & Christie, T. (2001). The relationship between teacher assessments and pupil attainments in standard test tasks at key stage 2, 1996–98. British Educational Research Journal, 27(2), 141–160.

    Article  Google Scholar 

  • Ross, J. A. (2006). The reliability, validity, and utility of self-assessment. Practical Assessment, Research & Evaluation, 11(10), 1–13.

    Google Scholar 

  • Ross, J. A., & Gray, P. (2008). Alignment of scores on large scale assessments and report card grades. Alberta Journal of Educational Research, 54(3), 327–341.

    Google Scholar 

  • Ross, J. A., Rolheiser, C., & Hogaboam-Gray, A. (2002). Influences on student cognitions about evaluation. Assessment in Education, 9(1), 81–95.

    Google Scholar 

  • Schunk, D. H. (1981). Modelling and attributional effects on children’s achievement: a self-efficacy analysis. Journal of Educational Psychology, 73(1), 93–105.

    Article  Google Scholar 

  • Schunk, D. H. (1996). Goal and self-evaluative influences during children’s cognitive skill learning. American Educational Research Journal, 33(2), 359–382.

    Google Scholar 

  • Schunk, D. H., & Ertmer, P. (1999). Self-regulatory processes during computer skill acquisition: goal and self-evaluative influences. Journal of Educational Psychology, 91(2), 251–260.

    Article  Google Scholar 

  • Spence, M. (1973). Job market signaling. Quarterly Journal of Economics, 87(3), 355–374.

    Article  Google Scholar 

  • Spillane, J. P. (2000). A fifth-grade teacher’s reconstruction of mathematics and literacy teaching: exploring interactions among identity, learning, and subject matter. Elementary School Journal, 100(4), 307–330.

    Article  Google Scholar 

  • Tuten, J. (2007). “There’s two sides to every story”: how parents negotiate report card discourse. Language Arts, 84(4), 314–324.

    Google Scholar 

  • Usher, E. L., & Pajares, F. (2008). Sources of self-efficacy in school: critical review of the literature and future directions. Review of Educational Research, 78(4), 751–796.

    Article  Google Scholar 

  • Wayman, J. C., & Stringfield, S. (2006). Technology-supported involvement of entire faculties in examination of student data for instructional improvement. American Journal of Education, 112, 549–571.

    Article  Google Scholar 

  • Wildy, H. (2004). The data club: Helping schools use accountability data. In M. Wilson (Ed.), Towards coherence between classroom assessment and accountability. 103rd Yearkbook of the National Society for the Study of Education, Part II (pp. 155–168). Chicago: University of Chicago Press.

    Google Scholar 

  • Willingham, W. W., Pollack, J. M., & Lewis, C. (2002). Grades and test scores: accounting for observed differences. Journal of Educational Measurement, 39(1), 1–37.

    Article  Google Scholar 

  • Wilson, M. (2004). Towards coherence between classroom assessment and accountability. 103rd Yearkbook of the National Society for the Study of Education, Part II. Chicago: University of Chicago Press.

    Google Scholar 

  • Zwick, R., & Green, J. G. (2007). New perspectives on the correlation of SAT scores, high school grades, and socioeconomic factors. Journal of Educational Measurement, 44(1), 23–45.

    Article  Google Scholar 

  • Zwick, R., & Sklar, J. C. (2005). Predicting college grades and degree completion using high school and SAT scores: the role of student ethnicity and first language. American Educational Research Journal, 42(3), 439–464.

    Article  Google Scholar 

Download references

Acknowledgements

The research was funded by the Ontario (Canada) Ministry of Education. The views expressed in the article are not necessarily those of the Ministry.

Author information

Authors and Affiliations

  1. OISE/UT Trent Valley Centre, University of Toronto, 1994 Fisher Drive, PO Box 7190, Peterborough, ON, K9J 7A1, Canada

    John A. Ross

  2. Kawartha Pine Ridge District School Board, 1994 Fisher Drive, PO Box 7190, Peterborough, ON, K9J 7A1, Canada

    Lynn Kostuch

Authors
  1. John A. Ross
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lynn Kostuch
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to John A. Ross.

Appendix

Appendix

For this analysis we deleted the small number of cases in which the report card grade = 0. There is an important difference between Tables 9 and 10 and Tables 11 and 12. In Tables 9 and 10 the LOWEST category of the predictor variable is the reference category; i.e., the odds ratio for passing the EQAO assessment is the ratio of the highest to the lowest category of the predictor. For example, in Table 9, the odds ratio 2.96 means that students who are successful in Reading on the grade 1 report card are 2.96 times more likely to be successful on the grade 3 EQAO assessment than students who were unsuccessful on the grade 1 report card. However, when the predictors are ordinal variables, such as levels of achievement, the PASW/SPSS software creates a set of dummy variables in which each level is compared to the HIGHEST category. In calculating the odds ratio reported in Tables 11 and 12, the effect of each report card level on EQAO success is compared to the effect of level 4.

Table 11 Odds Ratio of success on grade 3 assessment by report card level, grade, and subject
Full size table
Table 12 Odds ratio of success on grade 6 assessment by report card level, grade, and subject
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ross, J.A., Kostuch, L. Consistency of report card grades and external assessments in a Canadian province. Educ Asse Eval Acc 23, 159–180 (2011). https://doi.org/10.1007/s11092-011-9117-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11092-011-9117-3

Keywords

Search

Navigation