Résumés
Abstract
In undergraduate university courses, the assessment methods often lack variety, which can lead to significant stress for both students and educators. It is becoming increasingly apparent that incorporating a range of assessment types could alleviate this stress and better accommodate diverse learning styles (Leite et al., 2010). Elective Grading (EG) is an approach to assessment that empowers students to determine their own grade weighting, based on their own learning goals and progress. EG can be implemented by using simple algebraic formulas to increase or decrease the original grade by the amount elected by the student. Using computer-based spreadsheet technology, EG can be included in a dynamic system that responds to the student's work, rather than relying solely on the instructor's evaluation. This article explains the rationale behind adopting an EG system, exploring a different option for students to re-weigh tests and assignments to reduce the perceived impact of each assessment, with no grade inflation. This flexible approach can mitigate student stress and anxiety, and practical strategies for its implementation across the curriculum. EG can enhance student learning and engagement from both the instructor's and the students’ perspectives. Students can use EG to adapt their own assessment preferences that may reduce stress and improve learning outcomes.
Keywords:
- Elective Grading,
- Universities
Parties annexes
Bibliography
- Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review 84(2), 191-215.
- Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman and Company.
- Beymer, P. N., & Thomson, M. M. (2015). The effects of choice in the classroom: Is there too little or too much choice? Support for Learning, 30(2), 105-120.
- Butz, A. R. & Usher, E. L. (2015). Salient sources of early adolescents’ self-efficacy in two domains. Contemporary Educational Psychology 42, 49–61. http://dx.doi.org/10.1016/j.cedpsych.2015.04.001
- Caruth, D. L. & Caruth, G. D. (2013). Grade Inflation: An issue for higher education? Turkish Online Journal of Distance Education-TOJDE, 14(1), 102-110. https://dergipark.org.tr/en/pub/tojde/issue/16895/176017
- Challis, D. (2005). Committing to quality learning through adaptive online assessment. Assessment & Evaluation in Higher Education 30(5), 519–527. https://doi.org/10.1080/02602930500187030
- Cook, A. (2001). Assessing the use of flexible assessment. Assessment & Evaluation in Higher Education, 26(6), 539-549. https://doi.org/10.1080/02602930120093878
- Honicke, T., & Broadbent, J. (2016). The relation of academic self-efficacy to university student academic performance: A systematic review. Educational Research Review, 17, 63-84. http://dx.doi.org/10.1016/j.edurev.2015.11.002
- Jephcote, C., Medland, E., Lygo-Baker, S. (2020). Grade inflation versus grade improvement: Are our students getting more intelligent? Assessment & Evaluation in Higher Education, 46(4), 547-571. https://doi.org/10.1080/02602938.2020.1795617
- Johnson, B. & Christensen, L. (2024). Educational research: Quantitative, qualitative, and mixed methods approaches. (8th ed.). Sage Publications.
- Kessels, G., Xu, K., Dirkx, K., & Martens, R. (2024). Flexible assessments as a tool to improve student motivation: an explorative study on student motivation for flexible assessments. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1290977
- Kızıltaş, Y. (2024). An important problem we need to face in schools: Inflated grades and grade inflation. European Journal of Education, (early online version) https://doi.org/10.1111/ejed.12744
- Lei, H., Cui, Y., & Zhou, W. (2018). Relationships between student engagement and academic achievement: A meta-analysis. Social Behavior and Personality, 46(3), 517-528. https://doi.org/10.2224/sbp.7054
- Leite et al. (2010). Attempted validation of the scores of the VARK: Learning styles inventory with multitrait-multimethod confirmatory factor analysis models Educational and Psychological Measurement., 70(2), 323–339.
- Okada, R. (2023). Effects of perceived autonomy support on academic achievement and motivation among higher education students: A meta-analysis. Japanese Psychological Research 65(3), 230-242. https://doi.org/10.1111/jpr.12380
- Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315–341 https://doi.org/10.1007/s10648-006-9029-9
- Reutskaja, E., Iyengar, S., Fasolo, B., & Misuraca, R. (2020). Cognitive and affective consequences of information and choice overload. In R. Viale (Ed.) Routledge Handbook of Bounded Rationality (pp. 625-636). Routledge.
- Telles-Langdon, D. M. (2020) Transitioning university courses online in response to COVID-19. Journal of Teaching and Learning. Special Issue: Digital Learning in Higher Education, 14(1), 108-119. https://doi.org/10.22329/jtl.v14i1.6262
- Wanner, T., & Palmer, E. (2015). Personalising learning: Exploring student and teacher perceptions about flexible learning and assessment in a flipped university course. Computers & Education, 88, 354-369. https://doi.org/10.1016/j.compedu.2015.07.008
- Yusuf, M. (2011). The impact of self-efficacy, achievement motivation, and self-regulated learning strategies on students’ academic achievement. Procedia Social and Behavioral Sciences 15 2623–2626. doi:10.1016/j.sbspro.2011.04.158