Apparent Causers for the Academic Declination of Students in University Level Compared with Secondary Level An Application on Computer Science {&} Information Technology-Al Neelain University

Copyright © 2014 IJECCE, All right reserved

Apparent Causers for the Academic Declination of

Students in University Level Compared with Secondary

Level

An Application on Computer Science & Information

Technology-Al Neelain University

Dr. Mozamel M. Saeed

Faculty of Science, Dept. of Computer Science, Al-Aflaj E-mail: mozamel8888@gmail.com

Abstract – The aims of this paper is to study the causes of academic declination of students in universitylevel compared with secondary level, taking the students of Computer Science & Information Technology-Al Neelain University (batch 2012) as sample using SPSS and its outputs to help decision makers to determine best resolution for the phenomena.

Keywords – Neelain University, Academic Declination, Batch 2012, Secondary Level.

I.

I

The academic study is considered as the final conclusion of the practical instructional process. The student receives good education and becomes fully prepared to participate in administrative matters of life. His success will have positive impact on the community to which he belongs. It is very important to make best use of all the capabilities that have been earned by the student during the previous studying years. Especially the secondary level. Where he is fit and prepared to join the university level.

In spite of the importance of the academic study in the university level and the acceptance of the students in the scientific and applied colleges after obtaining high degrees in Sudanese testimony. Unfortunately we find that there is an academic declination of studentsin the university level. It is an indicator for presence of a problem which requires searching for a solution. In order To ensure the continuation of success and academic rise of the students. It is an apparent study of diminishing standard of students in the university level compared with their standard in secondary level. Through the statistical bundle for the social sciences (SPSS). Which is considered as the most important and powerful programs for studying the social phenomena and suggesting ideal solutions using schedules and forms to describe outputs. The researcher will practically apply the programs of (SPSS) in studying the diminishing standard of students in the university level compared with their standard in secondary level. Using all the technicalities, the available possibilities in the bundle, and the chosen sample which will be deliberately studied and analyzed. In order to produce outputs that can help and support the decision - makers.

II.

D

A

D

:

Data analysis and discussion is to start studying the targeted sample of the students of (Computer Science & Information Technology-Al Neelain University (batch 2012) – (Department of science, Technology, and Information system). Introducing both the degrees that have been obtained by the students in the Sudanese testimony and the accumulative average of the academic year (batch 2012) as appointing for the level of the university students in (SPSS).Putting all the substances in the Sudanese testimony (with the different specializations of the students) in form of fields. Each field will have a code number that symbolizes the substance.Then anew field will be chosen to mark both the general average in the Sudanese testimony and the accumulative average of the academic year (batch 2012). Thus, all the fields thereby are completed. Statements are entered in the (SPSS). Each student register includes all details of substances in the Sudanese testimony, the general ratio and the accumulative average of the academic year (batch2012). Afterwards data operation analysis is carried out. Using the factorial method analysis as it is clarified below.

Table 1: Matrix treatments of the connection:

The above schedule (1) is about a matrix that clarifies the simple treatments of the connection between the changeable variable of the study. And assist in examining the skeleton of the general connection through which we can easily reach the main components .And extract the factors which will give an explanation for the greater part of the contrast phenomenon .

1.000 .073 .357 -.516 -.618 -.074 .107 -.881 .073 1.000 -.732 -.306 .409 -.258 .000 -.223 .357 -.732 1.000 .171 -.452 -.349 -.334 -.407 -.516 -.306 .171 1.000 -.200 -.084 -.587 .260 -.618 .409 -.452 -.200 1.000 -.309 .112 .504 -.074 -.258 -.349 -.084 -.309 1.000 .693 .479 .107 .000 -.334 -.587 .112 .693 1.000 .326 -.881 -.223 -.407 .260 .504 .479 .326 1.000 Arabic Languge

English Languge Religious Studies Mathimatics Biology Physics Chemistry Add Mathimatics Correlation

Arabic Languge

English Languge

Religious

Copyright © 2014 IJECCE, All right reserved Table 2: Values of common

Table (2) contains the values of the common (shared). The prevalence of the common variable is determined by its contributions in all factors which are measured by the sum of the coefficient variable squares on the different factors.

So the Communist values cannot be obtained before obtaining all the factors. And it is simple to say that it represents the variables interpreted by the contrast ratio factors. Therefore it can be defined as the sum of the squares of the variables saturations factors.

Table 3: Factors derived

Table 3 Represents the matrix of the factors derived from the total variables of the study detailed as follows:

Initial value:

There are a number of methods that are used in the program for calculating the common values (shared): As follows:

The initial value for the common values should be equal = 1 (one correct). For all the variables.

Extraction:

These are the common variables values of the study that have been practically extracted.

The above schedule gives us the self values obtained by using the major formations system. Which has been extracted from the matrix treatments of the connection. It is divided into three parts:

 The first part is concerned with the initial self value, the contributed ratio in the total discrepancy and the accumulative ratio for the explained discrepancy.

 Thesecond part of schedule assimilates the total squares of the valuable saturations after the summarizing process and before the rotation of the axes. We can notice that the first three factors give a clear interpretation for the biggest part of the total discrepancy.

 The third part of the schedule explains the total squares of the saturations after the rotation of the axes.

Through the mentioned results we can find that the first factor gives about 35.768% of the total discrepancy. The second factor gives about 27.236% of the total discrepancy. The third factor gives about 24.319% of the total discrepancy. The accumulative ratio that explained by these factors is about 87.323% of the total discrepancy.

Initial self values

The values assimilates the discrepancies of factors that have been extracted through using the matrix treatments of the connection .Where all variables are changed into the form of normative image. Itmeans that each variable will have a discrepancy that is equal to one correct(1). (The total discrepancy for 8 variables is equal 8).

The total :

The column contains the self values (discrepancies of the factors) . The first factor explains the biggest ratio of the discrepancy. And the factor that follows explains as big amount as possible of the remnant discrepancy. Also we notice that the extraction process has stopped at the fifth factor, due to the fact that the value of the discrepancy of the factor is smaller than the one correct (1).

Ratio of the discrepancy (%of Variance):

The column clarifies the ratio of the discrepancy been explained by each factor. The ratio is calculated as follows:

%of Variance = 100

y discrepanc Total

factor the of y discrepanc

The _

For example:

Ratio of the discrepancy for the first factor explains:

%

323

.

35

100

*

8

861

.

2

_

The accumulative ratio (Cumulative %):

The column assimilates the accumulative ratio for the explained discrepancy by means of factors. We can notice that the first five factors gives us explanation for the biggest part of the total discrepancy (is about 87.323%) of the total discrepancy (The total saturation squares of the extracted factors)

In this part of the schedule the program depends on the extracted factors only. Sometimes there is difference in the explained ratio of discrepancy. Due to the fact that in this part of the schedule we are not depending on the value of the total discrepancy,but depending on the common discrepancies.

The rotation:

The values that are included in this column assimilate the ratio of discrepancy explained by each factor after the practical rotation process. The rotation is an attempt to glorify the discrepancy being explained by each factor through the way of re -distribution. (We notice that there is no difference between the ratio of the total explained discrepancy after the rotation and the ratio of the total explained discrepancy before the rotation).

1.000 .997 1.000 .866 1.000 .794 1.000 .772 1.000 .782 1.000 .899 1.000 .893 1.000 .983 Arabic Languge

Englis h Languge Religious Studies Mathimatic s Biology Phys ics Chemistry Add Mathimatics

Initial Ex traction

Ex traction Method: Principal Component Analys is .

2.861 35.768 35.768 2.861 35.768 35.768 2.548 2.179 27.236 63.004 2.179 27.236 63.004 2.322 1.946 24.319 87.323 1.946 24.319 87.323 2.250

.883 11.039 98.362 .131 1.638 100.000 5.0E-016 6.23E-015 100.000 2.0E-016 2.46E-015 100.000 -2E-016 -2.16E-015 100.000 Component

1 2 3 4 5 6 7 8

Total % of Variance Cumulative % Total % of Variance Cumulative % Total Initial Eigenvalues Extraction Sums of Squared Loadings Rotation

Sums of Squared Loadingsa

Extraction Method: Principal Component Analysis.

Copyright © 2014 IJECCE, All right reserved Table 4: The extracted factors

The above schedule (4) shows the matrix of factors after rotation:

It explains the variables of high saturations in each factor as follows:

 First factor (mathematics): The substance of mathematics with its both parts (the elementary and specialized part) forms the first factor that explains about 35% of the total discrepancy. There is a noticeable rise in the valuable saturations relative to the substance of mathematics. As clarified in the equation below:

F1= 0.981 Arabic + 0.579 Math + 0.916Add Math

 Second factor (Biology): The substance of biology forms the second factor that explains about 27% of the total discrepancy. The valuable saturations relative to the substance of biology rises as clarified in the equation below:

F2 = 0.874 𝐸𝑛𝑔𝑙𝑖𝑠ℎ + 0.802 𝑅𝑒𝑙𝑖𝑔 + 0.732 𝐵𝑖𝑜

 Third factor (physic & chemistry): Forms the third factor that explains about. 24% of the total discrepancy. There is a noticeable rise in the valuable saturationsrelative to the substance of physic and chemistry. As clarified in the equation below:

𝐹3 = 0.886 𝑃ℎ𝑦 + 0.934 𝐶ℎ𝑒𝑚

As for the other substances that have not appeared in the previous equations such as the substances of the drifted literatures in the Sudanese testimony. Have already been deleted, due to the drop values of its connection treatments with the other variables of the study as clarified in table 1.

Table 5: Matrix treatments of the connection among the extracted factors

The above table (5) shows the matrix treatments of the connection among the extracted factors that were obtained after the rotation process .We can find that there is a noticeable drop in the valuable treatments of the connection. The most superior valuable treatments of the connections among the factors is about 0.180 (between the second and the third factor). That means the interior connection for the factors is bigger than the connection of the factors with each other. Which corresponds with the general assumption for the factorial way analysis.

Table 6: The descriptive statistics

The above table (6) includes a group of descriptive statistics relative to the final averages for the students who are in the academic and secondary stage. Divided according to the drifted (mathematic, biology, and arts). We can notice that there is a difference in the medium year for the degrees between the three drifted in the stages (the academic and secondary stage ) .By interior comparison for the mediums in the secondary stage, we can notice that the medium drifted for mathematics is 81.34 , in normative deviation is 1.95 , and normative error is 81.34 . As for the modified academic ratio (Mathematics), the quantity is 66.22, in normative deviation is 4, and normative error is 0.89.

Also it is noticed that the medium drifted for biology is 82.54, in normative deviation is 2.15, and normative error is 0.96. As for the modified academic ratio (biology), the quantity is 67.68, in normative deviation is 5.6, and normative error is 0.93. Therefore, we notice the valuable rising in the normative deviation which might lessen the importance rise of the mathematical mean for the students of biology comparative to the mathematical mean for the students of mathematics.

As for the literature track. The quantity of the valuable medium is (72.66), the normative deviation is (9), and the normative error is (5).

As for the modified academic ratio for the (literature track), the quantity is 62.75, normative deviation is 9, and the normative error is 1.9. It is noticed that the quantity of both the normative deviation and the error deviation is rising very high which reflects that the valuable medium of success are impacted by drastic values.

Generally the mathematical track is the best track. Followed by the biology track depending on the valuable medium of success and its normative error.

Fig.1. The Arabic language

-.981 -.173 .034

-.211 .874 -.066

-.297 -.802 -.425

.579 -.491 -.478

.479 .732 -.029

.213 -.128 .886

-.049 .271 .934

.916 .133 .423

Arabic Languge English Languge Religious Studies Mathimatics Biology Physics Chemistry Add Mathimatics

1 2 3

Component

Extraction Method: Principal Component Analysis. Rotation Method: Promax w ith Kaiser Normalization.

1.000 .027 .052

.027 1.000 .180

.052 .180 1.000

Component 1

2 3

1 2 3

Extraction Method: Principal Component Analysis. Rotation Method: Promax w ith Kaiser Normalization.

20 81.7750 1.94743 .43546 80.8636 82.6864 75.60 84.00

34 82.3412 2.14647 .36812 81.5922 83.0901 75.00 88.80

3 72.6667 9.94300 5.7406 47.9669 97.3665 63.30 83.10

57 81.6333 3.48586 .46171 80.7084 82.5583 63.30 88.80

20 66.2195 4.01599 .89800 64.3400 68.0990 59.93 72.95

34 67.6826 5.39973 .92605 65.7986 69.5667 57.40 81.90

3 62.7567 3.18586 1.8394 54.8425 70.6708 59.77 66.11

57 66.9100 4.94704 .65525 65.5974 68.2226 57.40 81.90

1.00 2.00 3.00 Total 1.00 2.00 3.00 Total Score at High Secondary Sechool

Score at University

N Mean

Std. Deviation

Std. Error

Low er Bound

Upper Bound 95% Confidence Interval for Mean

Minimum Maximum

90.00 80.00

70.00 60.00

20

15

10

5

0

Fr

eq

ue

nc

y

Copyright © 2014 IJECCE, All right reserved The above Fig.1 Shows the repetitive distribution

degrees for the students in the substance of Arabic language. It is noticed that the curve of the statements is inclined in the right direction.

Fig.2. The English language

The above Fig.2 Shows the repetitive distribution degrees for the students in the substance of English language. It is noticed that the curve of the statements is similar around the middle.

Fig.3. The religious education

The above Fig.3 Shows the repetitive distribution degrees for the students in the substance of Islamic education. It is noticed that the curve of the statements is inclined in the right direction.

Fig.4. The fundamental mathematics

The above Fig.4 Shows the repetitive distribution degrees for the students in the substance of fundamental mathematics. It is noticed that the curve of the statements is inclined in the right direction.

Fig.5. The biology

The above Fig.5 Shows the repetitive distribution degrees for the students in the substance of biology. It is noticed that the curve of the statements is similar around the middle .But it is impacted by drastic values.

Fig.6. The physic

The above Fig.6 Shows the repetitive distribution degrees for the students in the substance of physic. It is noticed that the curve of the statements is inclined in the right direction.

Fig.7. The chemistry

100.00 90.00

80.00 70.00

60.00 25

20

15

10

5

0

Fr

eq

ue

nc

y

Mean = 80.8421 Std. Dev. = 5.73146 N = 57

100.00 90.00 80.00 70.00 60.00 50.00 15

12

9

6

3

0

F

re

q

u

en

cy

Mean = 84.8947 Std. Dev. = 8.61826 N = 57

100.00 90.00 80.00 70.00 60.00 50.00 20

15

10

5

0

F

re

q

u

en

cy

Mean = 88.2105 Std. Dev. = 7.35269 N = 57

100.00 90.00

80.00 70.00

60.00 14

12

10

8

6

4

2

0

Fr

eq

ue

nc

y

Mean = 79.125 Std. Dev. = 5.92339 N = 40

100.00 80.00 60.00 40.00 20.00 0.00 30

25

20

15

10

5

0

F

re

q

u

en

cy

Mean = 74.5926 Std. Dev. = 15.9581 N = 54

100.00 90.00

80.00 70.00

60.00 14

12

10

8

6

4

2

0

Fr

eq

ue

nc

y

Copyright © 2014 IJECCE, All right reserved The above Fig.7 Shows the repetitive distribution

degrees for the students in the substance of chemistry. It is noticed that the curve of the statements is similar around the middle.

Fig.8. Additional mathematics

The above Fig.8 Shows the repetitive distribution degrees for the students in the substance of additional mathematics. It is noticed that the curve of the statements is inclined in the right direction.

Fig.9. Rates of the secondary stage

The above Fig.9 Shows the repetitive distribution for the general rate statements in the secondary stage. It is noticed that the curve of the statements is inclined in the right direction.

Fig.10. Rates of the academic stage

The above Figure (10): Shows the repetitive distribution for the general rate statements in the academic stage. It is noticed that the curve of the statements is inclined in the left direction.

C

The analysis operation that has been carried out and the extracted results that have been reached. It is possible for us to say that the substance of the elementary and additional mathematics assimilates the most important influential factor on the results of the students in the university level. Followed by the substance of biology, physic, and chemistry.In addition to the essential substances in Sudanese testimony.It is obvious that the extraction operation for the influential factors on the total discrepancy has excluded the substances related to the literary track from the analysis. Due to its weak connection with the subjects that are being taught in the computer colleges in Sudan.

R

[1] Al-Ashgar Ahmed , Introduction in statistics Concepts and methods, Publishing House of culture – Oman, 1999

[2] Brian C. Cronk, How to Use SPSS Statistics: A Step-By-Step Guide to Analysis and Interpretation,2012.

[3] Charles Henry Brase & Corrinne Pellillo Brase, Understandable Statistics: Concepts and Methods, 2014

[4] Ditlev Monrad , Statistics Concepts and Methods, 2010. [5] Harry Frank & Steven C. Althoen, Statistics concept and

Applications , Cambridge university press, first published,1994. [6] Julie Pallant, A Step By Step Guide to Data Analysis Using

SPSS , May 2001.

[7] Julie Pallant, SPSS Survival Manual: A step by step guide to data analysis using SPSS, 4th Edition , Nov, 2010.

[8] ShigerFaeigh and others , Introduction in statistics, Publishing House of Maiesara, Oman , 2000.

[9] Raja Mahmud Abu Allam ,Statistics analysis for data (Using SPSS),Publishing house for universities –Cairo, 2003.

[10] Registrar office for computer science & technology information – Neelain University, Mar 2012.

[11] The general administration for the accepting and consolidation of the testimonies - ministry of higher education and scientific research, Feb 2012.

A

’

P

Mozamel M. Saeed

is the head department of Computer Science at Faculty of Science, Salman Bin Abdul Aziz University. I've published some papers internationally

90.00 85.00 80.00 75.00 70.00 65.00 60.00 7

6

5

4

3

2

1

0

Fr

eq

ue

nc

y

Mean = 77.00 Std. Dev. = 6.42364 N = 20

90.00 85.00 80.00 75.00 70.00 65.00 60.00 30

25

20

15

10

5

0

Fr

eq

ue

nc

y

Mean = 81.6333 Std. Dev. = 3.48586 N = 57

85.00 80.00 75.00 70.00 65.00 60.00 55.00 14

12

10

8

6

4

2

0

Fr

eq

ue

nc

y