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This article uses the hierarchical linear modelling (HLM) technique toexplain causally the Mathematics Performance achievement of students in SaudiArabia. Particularly, the HLM technique was applied to the TIMSS 2011 data setwhere five variables (Home educational resources (BSBGHER), Like learningmathematics (BSBGSLM), Self-confidence in mathematics (BSBGSCM), Engaged inmathematics learning (BSBGEML), Value learning math (BSBGSVM)) at the studentlevel and three variables (Emphasis on academic success (BCBGEAS), Schooldiscipline and safety (BCBGDAS), and Instruction affected by mathematicsresources shortages (BCBGMRS) at the school level, were used to build thehierarchical linear model so as to predict the status of mathematically 8thgrader. The final model suggested that all the student level factors are foundto be significant but their impact on achievement do not vary significantlyacross the population of schools, i.e. BSBGHER, BSBGSLM, BSBGSCM, BSBGEML, andBSBGSVM significantly predicted the status of Mathematics Performanceachievement of students in Saudi Arabia. At the school level, it is found thatBCBGDAS and BCBGMRS have a significant impact on performance. However, a scalepoint increase in the availability of school resources for mathematicsdecreased achievement by 4 points.

A multilevel Analysis of Saudi Arabian Student 8th Grade Mathematics Achievement TIMSS 2011