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Skip to main content. Log In Sign Up. Another variable included in the mtah is the role of the semester in which students take the first cal- culus maath. The data consists of grade records of more than two thousands students tracked over seven semesters, and comes from bilingual Arab students studying at an English medium university.

The implications of this finding for academic policy are discussed. Background of the study English language is gradually becoming the main language of instruction in higher ed- ucation institutions within the Middle East.

The trend is much more in area of sciences, medical, and engineering courses. However, the Arabic language remains the main lan- guage of instruction at the primary and secondary levels. At the university entry level, different Middle Eastern universities use different programmes to bridge the gap that this language switch may cause.

The most common approach is a one-year prepara- tory programme.

In addition to bridging the language matn, the programme also aims at creating a conducive atmosphere for a smooth transition from secondary school to university.

Consequently, all students admitted to KFUPM are required to complete a one-year preparatory programme before starting their undergraduate studies.

In addition, students take courses related to graphics, a mechanical engineering workshop, and physical education during the preparatory year. According to the Undergraduate Bulletin of KFUPMthe main aim of the preparatory-year programme is to prepare students for undergraduate study, especially with regard to the new language of instruction.

How- ever, students are given a maximum of three semesters to complete the programme.

For a student to go for any academic programme of his choice, he has to meet some minimum entry requirement based on the preparatory-year mathematics and En- glish courses. After passing the preparatory-year courses, students follow two different mathe- matics mxth. Those students posted to the college of sciences, engineering, and com- puter sciences are required to take a more rigorous mathematics strand which begins with Calculus I, while others go for a different set of mathematics courses.

Our focus in this study is on students taking the Calculus I strand. The reason for choosing Calculus I is because it is largely considered as the backbone of the calcu- lus series. On the other hand, the typical calculus sequence of courses is considered the nucleus of modern mathematics and vital for any science and engineering related courses, in which KFUPM specialises. As in many other college algebra and pre-calculus courses, the aim of preparatory mathematics Kfu;m and at KFUPM is to prepare students for these calculus courses.

In addition, we intend to investigate the effect of the semester in which students take Calculus I. Method The ,ath whose grades formed the data of this study were male students with an average age of 19 years, mostly in the first year of university life after the completion of their preparatory-year programme.

Almost all these students have Arabic as their first language as well as it being the language of instruction during their previous schooling. Most of them have had little English background at the time of admission. The number of students that took Calculus I in all the seven terms are presented in Table 1. Number of students from each Term. Letter grades for all English and mathematics courses in the preparatory-year pro- gramme were recorded for each student, as well as that of Calculus I.


The number of students with these letter grades and corresponding numer- ical grades in the regression analyses are given in Table maath. Calculus I response profile. Other independent variables include the academic Term,, and in which the students took Calculus I.

Results and discussion In the course of this investigation several models ,fupm developed using regression anal- ysis. However, only the pertinent models are reported here.

Math002 Old Exams

Table 3 gives three of these models and variables therein. The results of the three models are summarised in Table 4 in descending order.

The table also reports the models, the multiple correlation R- values, R2 kfupj, Adjusted R2 -values with associated degrees of freedom, F -values and p-values. Summary of the variables in the best three models. As can be noticed from Table 4, all three models are statistically significant at alpha 0. However, Model mzth is the best model and explains about 36 per cent of the total variance in the Calculus I grade. Multiple regression model summary.

The first column of Table 5 is the name of the variable, followed by degree of freedom, the estimate of the parameter, standard error, and the associated t-value, and p-value.

The best model seems to suggest that the academic subjects of the preparatory year are important predictors matg Calculus I performance. Among the academic terms, semester appears to be the only significant term when compared to the reference term This simply means that from mah perspective of the model, students taking Calculus I in different semesters, were not very different in ability except for those taking the course in term Only the significant variables are reported here.

The non-significant variables were reported in Table 3. Summary of the value of each coefficient with standard error, t-statistics, and p-value. There are also several significant interaction effects in the best model.

Although MATHwhich was crucial in Model 1 and 2, is surprisingly not significant in mathh best model, its joint effects with MATH appear significant as a predictor of Calculus I per- formance in the best model.

In addition to the M2 effect, the interaction effect of the variables M1 and M2 implies that, kfuupm that already explained by M2, the com- mon core concepts and skills found in the preparatory-year mathematics curriculum as represented in both mathematics courses are crucial as a predictor of Calculus I per- formance. This interaction appears to subtract from the gradient of the regression line representing MATH at Term That is, for Termthe profile of Calculus I student performance is better explained by a gradient that is smaller than what is represented matth MATH effects alone.

Although neither ENGL nor term were significant by themselves, their joint effects with MATH show that the prediction should be discounted by 0. Lastly, the interaction effects E1E2T32 is also kfupj. This effect represents the common knowledge and skills that are in the preparatory-year English curriculum as represented in both English courses that students carry into the context of semester term This joint English knowledge and skills in term requires a higher predicted Calculus I score kfulm in other terms beyond those already warranted by the ENGL effect.

The added last analysis was conducted with only the academic variables in the model. Summary of the contribution of preparatory-year courses in predicting Calcu- lus I performance.

For completion of the mwth, a regression model with only the academic vari- ables in the model was fitted with each of the variables in Table 6 added in last to see the effect of the course in question when other academic variables 0001 already used as predictors of Calculus I performance. Contrast this with total variance explained by the best models 36 per cent. This has shown that adding other variables including academic Term in the model add only around three per cent to the model.


On the other hand, jointly, the two mathematics courses explain twenty- seven per cent of the total variance, while the two English courses explain barely more than three per cent. As noted earlier, surprisingly ENGL and MATH did not contribute sig- nificantly to the best model as stand-alone effects, but their joint effects with other variables can be readily seen as crucial predictors of success in the Calculus I course.

This should give some empirical support to the new policy in the preparatory year that for a student to go to either an engineering or a computer-related course, he should get at least a passing grade of D in MATH and C in MATH as a placement requirement.

Firstly, our data collection method and analysis are quantitative in nature. So, no at- tempt was made to qualitatively through interviews or classroom observations inves- tigate the same problem.

Had this approach been used, a different result may have been obtained.

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Therefore, future research may possibly look into this factor to corroborate the result. Secondly, participants were Arab male students only, with little background in English. Thirdly, the variables examined here are certainly not exhaustive and other factors such as student reading habits, level of motivation, etc. Other factors that contributed significantly in the best model included some interaction of the preparatory-year courses.

They have an effect only when they interact with other variables. On the other hand, the variable term is also not significant with the exception of term A plausible explanation for this might be the superior mathematics abilities of the student cohort in this summer semester compared to the other semesters.

This result corroborates with many studies in the literature Begle, ; Tuli, ; Jamison, ; Kelly, ; Soares, ; Yushau, It is our hope that, due to lack of research in this area, the data presented in this study will serve as a starting point, and hopefully contribute to the field of mathematics education. Furthermore, the findings in this study may help university administrations in policy making regarding student placement into academic programmes after com- pleting the preparatory mtah, and in streamlining and prioritising the kfupmm.

It can also be useful for other universities with similar preparatory-year programmes. The predictive validity of selection measures used by the University of Petroleum and Minerals in Saudi Arabia, Dissertation Abstract Interna- tional, 47 2 Critical variables in mathematics education: Findings from a survey of the empirical literature.

Bilingual instruction in college mathematics: Language influence on mathematics achievement of Capeverdean students, Dissertation Abstract International, 43 12 Chinese and English mathematics language: The relation between linguistic clarity marh mathematics performance, Dissertation Abstract International, 59 7 An exploration of extra and classroom variables for three measures of college mathematics achievement academic achievementDissertation Abstract International, 55 9 A longitudinal study measuring the ability of two South African mathematics tests to predict mathematics performance of Grade 9 high school pupils, South African Journal of Education, 19 2— Kfuom effect of learning mathematics in a second language on reasoning ability, Dissertation Abstract International, 33 6 Can student aptitude and attitude assist in placing students in appropriate advanced placement mathematics courses?

Mathematics creativity as related to aptitude for achievements and attitude towards mathematics, Dissertation Abstract International, 42 1 The predictors of success of computer aided learning of pre- calculus algebra. University of South Africa: Remember me on this computer. Enter the email address you signed up with and we’ll email you a reset link.

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