  This article uses the hierarchical linear modelling (HLM) technique to
explain causally the Mathematics Performance achievement of students in Saudi
Arabia. Particularly, the HLM technique was applied to the TIMSS 2011 data set
where five variables (Home educational resources (BSBGHER), Like learning
mathematics (BSBGSLM), Self-confidence in mathematics (BSBGSCM), Engaged in
mathematics learning (BSBGEML), Value learning math (BSBGSVM)) at the student
level and three variables (Emphasis on academic success (BCBGEAS), School
discipline and safety (BCBGDAS), and Instruction affected by mathematics
resources shortages (BCBGMRS) at the school level, were used to build the
hierarchical linear model so as to predict the status of mathematically 8th
grader. The final model suggested that all the student level factors are found
to be significant but their impact on achievement do not vary significantly
across the population of schools, i.e. BSBGHER, BSBGSLM, BSBGSCM, BSBGEML, and
BSBGSVM significantly predicted the status of Mathematics Performance
achievement of students in Saudi Arabia. At the school level, it is found that
BCBGDAS and BCBGMRS have a significant impact on performance. However, a scale
point increase in the availability of school resources for mathematics
decreased achievement by 4 points.
