Continuous and Placement Assessment Results as a Predictor of Student Achievement in Primary Schools
Abstract
The purpose of this study was to explore the performance of out-of-school children in speed school and accelerated learning programs as a basis for success in primary schools. This research field has received very little attention. The continuous assessment and placement test results of students at risk were not used much in the literature, which this study aims to fill. The total number of students involved in the study was 624. The study used the continuous assessment average scores and placement test scores as predictor variables. The results show that the relationship between placement test and 1st-semester score in grade four was significant, r (196) = .501, p < .001. For the Accelerated Learning Program, the placement test and 1st-semester score in grade three were significant, r (111) = .413, p<.001. As a tool to forecast primary school students' future achievement, the teacher-made continuous assessment appears to be less useful than placement tests for children who come through speed school. Students from speed school backgrounds performed better than students from formal schools; students from accelerated learning program backgrounds performed almost similarly to students from formal schools except in environmental science. The study indicated that in grade four of formal primary school, continuous assessment was found to be poorly linked with student knowledge and skills. However, the results show that both comparisons found placement examinations to be a reliable indicator of children's achievement in primary schools. It can be concluded that students who joined grades three and four of formal school through speed school and an accelerated learning program are capable of achieving minimum learning competence in the subsequent educational outcomes in elementary grades.
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References
Anyor, J. W., & Abah, J. A. (2014). Mathematics curriculum change and assessment models: The quest for an integrated approach. Benue Journal of Mathematics and Mathematics Education, 1(3), 11–19. https://doi.org/10.31219/osf.io/egph4
ATEM Consultancy Service. (2012). All children in school by 2015 global out of school children initiative: study on situation of out of school children (OOSC) in Ethiopia Addis Ababa. July 2012, 1–147.
Atondo, G. T., Abah, J. A., & Naakaa, T. (2019). Continuous assessment as a predictor of students’ achievement in mathematics at the junior secondary school level in Makurdi local government area of Benue state, Nigeria. World Wide Journal of Multidisciplinary Research and Development, 5(2), 18–29.
Bae, C. L., & Lai, M. H. C. (2020). Opportunities to participate in science learning and student engagement: A mixed methods approach to examining person and context factors. Journal of Educational Psychology, 112(6), 1128–1153. https://doi.org/10.1037/edu0000410
Cornwell, C., & Parys, J. Van. (2010). The Gender Gap in Academic Achievement among Primary-School Children : Test Scores , Teacher Grades and the Importance of Non-Cognitive Skills. October 2010, 1–41.
Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35(1), 13–21. https://doi.org/10.1016/j.intell.2006.02.001
Elmore, R. F. (2019). The future of learning and the future of assessment. ECNU Review of Education, 2(3), 328–341. https://doi.org/10.1177/2096531119878962
Frye, W., & Hemmer, P. (2012). Program evaluation models and related theories: AMEE Guide, Med Teach, 34(5), e288-99. https://doi.org/10.3109/0142159X.2012.668637
Geiser, S., & Santelices, M. V. (2007). Validity of high-school grades in predicting student success beyond the freshman year: High school record vs. standardized tests as indicators of four-year college outcomes. CSHE Research & Occasional Paper Series.
Ghaicha, A. (2005). Theoretical framework for educational assessment: A synoptic review. Journal of Education and Practice, 7(24), 212–231. www.iiste.org
Global, A. E. D. (n.d.). (2010). Success in Primary School.
Greive, C. (2012). Visible learning for teachers: Maximising impact on learning. TEACH Journal of Christian Education, 6(1). https://doi.org/10.55254/1835-1492.1033
Gutu, T. S., Tefera, B. F., & Ejeta, T. T. (2014). Educational Research and Reviews An assessment of grade four students learning : The case of Jimma town. August 2016. https://doi.org/10.5897/ERR2014.1718
Hall, M. T. (2015). An examination into the validity of secondary school entrance scores in predicting the academic success of secondary aged students. Current Issues in Education, 18(1), 1–10.
Hemphill, J. F. (2003). Interpreting the magnitudes of correlation coefficients. American Psychologist, 58(1), 78–79. https://doi.org/10.1037/0003-066X.58.1.78
Ing, L. M., Musah, M. B., Al-Hudawi, S. H. V., Tahir, L. M., & Kamil, N. M. (2015). Validity of teacher-made assessment: A table of specification approach. Asian Social Science, 11(5), 193–200. https://doi.org/10.5539/ass.v11n5p193
Khan, A., Okwun, & Kalu, C. (2011). Psychology and counseling responsibilities for continuous assessment in Malaysian school system. Scientific Research and Essays, 6(11), 2259–2263. https://doi.org/10.5897/SRE10.321
MoE. (2022). The Federal Democratic Republic of Ethiopia, Ministry of Education Statistics Annual Abstract (ESAA). 2014 E.C/2021/22. 1–121. file:///C:/Users/HP/Downloads/ESAA 2014 EC (2021-22 G.C) Final.pdf%0Awebsite: www.moe.gov.et
Mullis, I. V., Martin, M. O., & Foy, P. (2004). Students’ backgrounds and attitudes toward mathematics. In TIMSS 2007 International Mathematics Report. http://isc.bc.edu/timss2003i/mathD.html
Martin, M. O., & Mullis, I. V. (2013). TIMSS and PIRLS 2011 : Relationships Among Reading, Mathematics, and Science Achievement at the Fourth Grade —Implications for Early Learning. https://pirls.bc.edu/timsspirls2011/downloads/TP11_Relationship_Report.pdf
Muskin, J. Samuel, W. Ecwou, R. (2021). Speed School Program (2021). Annual Report, Ethiopia.
Niyi, O. J., Chinwubu, M. A., & Victor, O. A. (2022). Out of school children in Nigeria: Causes, social implication and way forward. International Journal on Integrated Education, 5(12), 82–91.
Nosek, B. A., Banaji, M. R., & Greenwald, A. G. (2002). Math = male, me = female, therefore math ≠ me. Journal of Personality and Social Psychology, 83(1), 44–59. https://doi.org/10.1037/0022-3514.83.1.44
O’Dea, R. E., Lagisz, M., Jennions, M. D., & Nakagawa, S. (2018). Gender differences in individual variation in academic grades fail to fit expected patterns for STEM. Nature Communications, 9(1). https://doi.org/10.1038/s41467-018-06292-0
Omirin, Martin, S., & Ale, V. M. (2008). Pred Validity of Mock.
Omonigho, A. J. (2019). Continuous assessment: scope and relevance. Journal of Teacher Perspective, 32(2), 554–563.
Perform, G. (2009). Prepared for life ? And girls perform.
Pryor, J., Humphreys, S., & Akyeampong. (2018). Speed school program Ethiopia: Tracking the progress of speed school students : 2011-17. International Education, March, 1–58.
Randall, J., O’Donnell, F., & Botha, S. (2020). Accelerated learning programs for out-of-school girls: The impact on student achievement and traditional school enrollment. FIRE: Forum for International Research in Education, 6(2), 1–23. https://doi.org/10.32865/fire20206225
Stoet, G., & Geary, D. C. (2018). The gender-equality paradox in science, technology, engineering, and mathematics education. Psychological Science, 29(4), 581–593. https://doi.org/10.1177/0956797617741719
Strand, S., Deary, I. J., & Smith, P. (2006). Sex differences in cognitive abilities test scores: A UK national picture. British Journal of Educational Psychology, 76(3), 463–480. https://doi.org/10.1348/000709905X50906
Tosuncuoglu, I. (2018). Importance of assessment in ELT. Journal of Education and Training Studies, 6(9), 163. https://doi.org/10.11114/jets.v6i9.3443
Tsaousis, I., & Alghamdi, M. H. (2022). Examining academic performance across gender differently: Measurement invariance and latent mean differences using bias-corrected bootstrap confidence intervals. Frontiers in Psychology, 13(August), 1–12. https://doi.org/10.3389/fpsyg.2022.896638
Ullah, R. (2019). Boys versus girls’ educational performance: Empirical evidences from global north and global south. African Educational Research Journal, 7(4), 163–167. https://doi.org/10.30918/aerj.74.19.036
Yusuf, M. A. (2010). The influence of school sex, location and type on students’ academic performance. International Journal of Educational Sciences, 02(02), 81–85. https://doi.org/10.31901/24566322.2010/02.02.03
Zimmermann, S., Klusmann, D., & Hampe, W. (2017). Correcting the predictive validity of a selection test for the effect of indirect range restriction. BMC Medical Education, 17(1). https://doi.org/10.1186/s12909-017-1070-5
DOI: 10.15408/tazkiya.v11i2.34736
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