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THE RELATIONSHIPS AMONG INTEGRATED SCIENCE PROCESS SKILLS,

LOGICAL THINKING ABILITIES, AND SCIENCE ACHIEVEMENT AMONG

RURAL STUDENTS OF SABAH, MALAYSIA

Lay Yoon Fah

Universiti Malaysia Sabah

Khoo Chwee Hoon Malaysia Teacher Education Institute-Kent Campus

Tuaran, Sabah

Jenny Cheng Oi Lee

Lok Yuk Secondary School

Kota Kinabalu, Sabah, Malaysia

Abstract

Science curriculum in Malaysia gives conscious emphasis on the acquisition of scientific

skills and thinking skills, the inculcation of scientific attitudes and nobles values besides the

acquisition of scientific and technological knowledge and its application to the natural

phenomena and students daily experiences. The purpose of this study is to gauge the acquisition of integrated science process skills, logical thinking abilities and science

achievement among Form 4 students in the Interior Division of Sabah, Malaysia. This study is

also aimed to determine whether there is a significant difference in the acquisition of

integrated science process skills, logical thinking abilities, and science achievement between

male and female secondary students in the Interior Division of Sabah, Malaysia. The ultimate

goal of this study is to investigate whether integrated science process skills and logical

thinking abilities can predict rural secondary students science achievement. This is a non-experimental quantitative research and sample survey method was used to collect data.

Research samples were selected by using a two-stage cluster random sampling technique.

Instruments namely Integrated Science Process Skills Test (ISPST), Group Assessment of

Logical Thinking Abilities (GALT), and Science Achievement Test (SAT) were adopted to

investigate the possible linear relationships among rural secondary students integrated science process skills, logical thinking abilities and science achievement. Five subscales of

integrated science process skills measured in this study were Identifying variables, Identifying and stating hypothesis, Defining operationally, Designing investigations, and Graphing and interpreting data whereas six modes of logical thinking abilities measured were Conservational reasoning, Proportional reasoning, Controlling variables, Combinatorial reasoning, Probabilistic reasoning, and Correlational reasoning. Students science achievement in Elementary Biology, Elementary Chemistry and Elementary Physics

were also measured in this study. Parametric tests namely Independent samples t-test,

Pearsons product moment correlation, simple and multiple regression analysis were used to test the stated null hypotheses at a specified significance level of .05. Quantitative data was

analyzed by using the Statistical Packages for Social Sciences (SPSS) and QUEST. The

research findings will bring some meaningful implications to those who are directly or

indirectly involved in the development and implementation of science curriculum especially

in the Interior Division of Sabah, Malaysia.

Background of the Study

The progressiveness of a nation is very much dependent on the generation of new ideas which will act

as a catalyst to the development of the nation. In an effort to achieve the status of a developed nation, the

Malaysian government had initiated and documented a vision to be achieved by the year 2020. Among the nine

strategic challenges identified, the sixth strategic challenge is to establish a scientific and progressive society, a

society that is innovative and forward-looking, one that is not only a consumer of technology but also a

contributor to the scientific and technological civilization of the future (Wan Mohd. Zahid, 1993). The core of

this vision requires Malaysians to possess high scientific and technological skills to enable the people to be

involved directly and indirectly in the up-stream and down-stream of science and technology activities.

The most fundamental and powerful human resource is intelligence where it is important not only to

have a good brain but also to have the ability to use it and to ensure it is functioning effectively. In relation to

this, science has prepared ways which enable us to think logically about our daily events and practical problem

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solving. Science also represents ways of organizing knowledge which will then contribute to the development

of cultures and intellect. To achieve this aim, the concept of education through science becomes imperative.

Two important fields of study in science education are science process skills and logical thinking

abilities. Science process skills represent problem solving mechanisms that involved in any cognitive processes

whereas logical thinking abilities are crucial in the acquisition and understanding of science concepts. Scientific

knowledge is believed to develop via the use of science process skills and logical thinking abilities.

The Study

Problem Statement This proposed piece of study is a follow-up of a research undertaken by the principal researcher which

entitled The Influence of Science Process Skills, Logical Thinking Abilities, Attitudes towards Science and, Locus of Control on Science Achievement among Form 4 Students in the Interior Division of Sabah, Malaysia. One of the important findings of the study revealed that higher logical thinking abilities will ensure better

science process skills and hence better science achievement among Form 4 students in the Interior Division of

Sabah. The same study had also proposed a structural model to show the direct and indirect effects of all the

endogenous and exogenous variables studied by using the Structural Equation Modeling (SEM) approach.

However, there have not been many well-documented research which aimed to gauge the acquisition

of integrated science process skills, logical thinking abilities, and science achievement among rural secondary

students especially in the Interior Division of Sabah, Malaysia. The possible linear relationships among the

acquisition of integrated science process skills, logical thinking abilities, and science achievement have not been

well-investigated. Hence, due to the scarcity of well-documented research in this field of study, this proposed

study is aimed to gauge the acquisition of integrated science process skills, logical thinking abilities, and

science achievement among rural secondary students in the Interior Division of Sabah; to determine if there is

any significant relationship among integrated science process skills, logical thinking abilities, and rural

secondary students science achievement. The ultimate goal of this study is to investigate whether integrated science process skills and logical thinking abilities can be used to predict rural secondary students science achievement.

Objectives of the Study

This study attempts to achieve the following objectives:-

i) to gauge the acquisition of integrated science process skills, logical thinking abilities and science achievement among rural secondary students in the Interior Division of Sabah, Malaysia;

ii) to determine whether there is a significant difference in the acquisition of integrated science process skills, logical thinking abilities, and science achievement between male and female rural

secondary students;

iii) to identify any possible linear relationships among integrated science process skills, logical thinking abilities, and rural secondary students science achievement; iv) to ascertain whether integrated science process skills and logical thinking abilities can predict rural secondary students science achievement;

Research Questions

This study attempts to answer the following questions:-

i) What is the acquisition level of integrated science process skills, logical thinking abilities, and science achievement among rural secondary students in the Interior Division of Sabah, Malaysia?

ii) Is there a significant difference in the acquisition of integrated science process skills, logical thinking abilities, and science achievement between male and female rural secondary students?

iii) Is there a significant linear relationship among integrated science process skills, logical thinking abilities, and rural secondary students science achievement? iv) To what extent do integrated science process skills and logical thinking abilities predict rural secondary students science achievement?

Research Hypotheses

Four null hypotheses identified to be tested in this study were listed below:

i) There is no significant difference in the acquisition of integrated science process skills, logical

thinking abilities, and science achievement between male and female rural secondary students in the

Interior Division of Sabah, Malaysia.

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ii) There is no significant linear relationship among integrated science process skills, logical

thinking abilities, and rural secondary students science achievement. iii) The regression coefficient for logical thinking abilities is equal to zero when rural secondary

students integrated science process skill is the dependent variable. iv) The regression coefficients for integrated science process skills and logical thinking abilities

are equal to zero when rural secondary students science achievement is the dependent variable.

Methodology

Research Design

This is a non-experimental quantitative research. Non-experimental research is a systematic empirical

inquiry in which the researcher does not have direct control of independent variables because their

manifestations have already occurred or because they are inherently not manipulable. Hence, inferences about

relations among variables are made, without direct intervention, from concomitant variation of independent and

dependent variables (Johnson & Christensen, 2000). Sample survey method was used to collect data. In this

study, intruments namely Integrated Science Process Skills Test (ISPST), Group Assessment of Logical

Thinking Abilities (GALT), and Science Achievement Test (SAT) were used to gauge students acquisition of integrated science process skills, logical thinking abilities and science achievement respectively.

Location of the Study

This study was conducted in 18 Form 4 classes of nine randomly-selected rural secondary schools in

the Interior Division of Sabah, Malaysia. The distribution of schools and Form 4 classes according to four

districts in the Interior Division of Sabah is shown in Table 1.

Table 1

Distribution of Schools and Form 4 Classes according to Four Districts in the Interior Division of Sabah,

Malaysia

District Nos. of Schools Nos. of Form 4 Classes

Tambunan 2 4

Keningau 4 8

Tenom 2 4

Nabawan 1 2

Total 9 18

Research Samples and Sampling Method

The population of this study were Form 4 students from 22 rural secondary schools in the Interior

Division of Sabah who took the Integrated Curriculum for Secondary School (ICSS) Science (Sains KBSM) as one of their compulsory learning subjects in school. The population size is approximately 3500 students. The

average age of the population is 16 years old. Sample size of this study was determined based on the formula

suggested by Krejcie and Morgan (1970) and power analysis (Miles & Shevlin, 2001). Hence, sample size used

in this study is considered adequate as compared to Krejcie and Morgans recommendation which is a sample size of 346 for the population size of 3500.

To be specific, a two-stage cluster random sampling technique was used to identify nine rural

secondary schools and 18 Form 4 classes to be involved in this study. At stage one, systematic sampling

technique was used to identify nine secondary schools from all the 22 secondary schools in the Interior

Division of Sabah. After the schools have been identified, simple random sampling techinique was used to

identify any two Form 4 classes from each of the chosen schools by using a random number table. All students

in the chosen classes were automatically taken as the samples of the study. This combination of sampling

techniques is to ensure the representativeness of the samples.

Instrumentation

Instruments namely Integrated Science Process Skills Test (ISPST) (Appendix I), Group Assessment

of Logical Thinking Abilities (GALT) (Appendix II), and Science Achievement Test (SAT) (Appendix III)

were adopted to gauge the acquisition of integrated science process skills, logical thinking abilities and science

achievement among rural secondary students in the Interior Division of Sabah. The same instruments were used

to investigate the possible linear relationships among students acquisition of integrated science process skills, logical thinking abilities and science achievement.

In this study, students acquisition of integrated science process skills was measured by using a modified and translated version of Integrated Science Process Skills Test II (TIPS II) (Burns et al., 1985) and

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Middle Grades Integrated Process Skill Test (MIPT) (Padilla & Cronin, 1986). The item distribution of ISPST according to the five subscales of integrated science process skills measured in this study is shown in Table 2.

Table 2

Item Distribution of ISPST according to Subscales

Subscales Item No. Nos. Item

Identifying Variables 1,3,13,14,15,18,19,20,30,

31,32,36

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Identifying and Stating Hypothesis 4,6,8,12,16,17,27,29,35, 40 10

Defining Operationally 2,7,22,23,26,33 6

Designing Investigation 10,21,24, 37,38,39 6

Graphing and Interpreting Data 5,9,11,25,28,34 6

Total 40

In this study, rural secondary students acquisition of logical thinking abilities was measured by using a modified and translated version of Group Assessment of Logical Thinking Abilities (GALT) (Roadrangka et al., 1983) and Test of Logical Thinking (TOLT) (Tobin & Capie, 1981). The item distribution of GALT according to the six modes of logical thinking measured is shown in Table 3.

Table 3

Item Distribution of GALT according to Subscales

Subscales Item No. Nos. Item

Conservational Reasoning 1,2,3,4 4

Proportional Reasoning 5,6,7,8,9 5

Controlling Variables 10,11,12 3

Probabilistic Reasoning 13,14,15 3

Correlational Reasoning 16,17,18 3

Combinatorial Reasoning 19,20,21 3

Total 21

On the other hand, rural secondary students science achievement was measured by Science Achievement Test (SAT) which is developed based on the ICSS Form 4 Science Curriculum Specification

(Curriculum Development Centre, 2001). The item distribution of SAT according to five subscales (topics) is

shown in Table 4.

Table 4

Item Distribution of SAT according to Subscales

Subscales (Topics) Item No. Nos. Item

Elementary Biology

Body Coordination 1,2,3,4,5,6,7,8,9, 9

Heredity and Variation 10,11,12,13,14,15 6

Elementary Chemistry

Matter and Material 16,17,18,19,20,21,22,23 8

Energy and Chemical Changes 24,25,26,27,28,29,30 7

Elementary Physics

Light, Colour and Vision 31,32,33,34,35,36,37,38,39,

40,41,42,43,44,45

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Total 45

The Difficulty Index and reliability analysis of the instruments used in this study are reported in Table

5 below. The Cronbachs alpha reliability of .72 and .66 for ISPST and SAT respectively are relatively high as compared to GALT (.52). On the other hands, the Difficulty index of .43 and .39 for ISPST and SAT

respectively showed that the items are not too difficult for the respondents to answer.

Table 5

Difficulty Index and Reliability Analysis of Instruments

Instrument

Nos. Item Sample

size

Difficulty Index Cronbachs Alpha

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ISPST 40 575 .43 .72

GALT 21 549 - .52

SAT 45 598 .39 .66

Further QUEST analysis found that all the items in the ISPST were fit with an Infit MNSQ of .88 -

1.13 (Appendix IV). Item fit map showed that the Infit MNSQ of these items were in the range of .77 - 1.30

(Appendix V). Based on the values of Pt-Biserial and Mean Ability, all the items were functioning well and

showed a high internal consistency (Alpha= .72) (Appendix VI). Table 6 showed the summary of item estimates

and fit statistics for ISPST used to measure the acquisition of integrated science process skills among Form 4

students in the Interior Division of Sabah.

Table 6

Summary of Item Estimates and Fit Statistics for ISPST

Item Estimates

Mean .00

Standard Deviation .64

Standard Deviation (Adjusted) .63

Item Estimates Reliability .98

Fit Statistics

Infit MNSQ:

Mean 1.00

Standard Deviation .06

(N = 575, L = 40, Probability level = .50)

QUEST analysis found that all the items in the SAT were fit with an Infit MNSQ of .92-1.09

(Appendix VII). Item fit map showed that the Infit MNSQ of these items were in the range of .77-1.30

(Appendix VIII). Based on the values of Pt-Biserial and Mean Ability, all items were functioning well and

showed a high internal consistency (Alpha = .66) (Appendix IX). The summary of item estimates and fit

statistics for SAT used to measure science achievement among Form 4 students in the Interior Division of

Sabah is shown in Table 7:

Table 7

Summary of Item Estimates and Fit Statistics for SAT

Item Estimates

Mean .00

Standard Deviation .71

Standard Deviation (Adjusted) .70

Item Estimates Reliability .98

Fit Statistics

Infit MNSQ:

Mean 1.00

Standard Deviation .04

(N = 598, L = 45, Probability level = .50)

Data Collection Procedures

Before administering the instruments, formal permission from the principals of the schools involved

was sought and obtained. The instruments of this study were administered by researcher. Students were

gathered in the school hall and the instruments were administered to the students concurrently. The students

were told about the nature of the instruments and how the instruments should be answered.

Data Analysis Procedures

Descriptive statistics were used to describe the acquisition of integrated science process skills, logical

thinking abilities, and science achievement among rural secondary students in the Interior Division of Sabah.

Among the descriptive statistics used were mean, standard deviation, mean in percentages, standard deviation in

percentages, and range.

As an effort to ensure all the quantitative data were drawn from a normally distributed population,

graphical measures such as histogram, stem-and-leaf plot, normal Q-Q plot and detrended normal Q-Q plot

were plotted for each of the variables studied. Furthermore, numerical measures such as skewness and kurtosis

were used to identify any deviations from normal distributions (Hair, Anderson, Tatham, & Black, 1998; Miles

& Shevlin, 2001). After the assumptions of using parametric techniques in analyzing quantitative data were met,

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statistical analyses which include independent-sample t-test, Pearsons product-moment correlation, simple and multiple regression analysis were used to test the stated null hypotheses at a specified significance level, alpha

= .05.

Independent-Sample t-Test

Independent-sample t-test was used to determine whether there is a significant difference in the

acquisition of integrated science process skills, logical thinking abilities, and science achievement between male

and female rural secondary students in the Interior Division of Sabah.

Pearsons Product-Moment Correlation Correlation analysis was used to identify possible linear relationships among integrated science process

skills, logical thinking abilities, and rural secondary students science achievement. Pearsons product-moment correlation coefficients (r) were calculated to show the strength of the linear relationships among the variables

studied.

Simple and Multiple Linear Regression Analysis

Simple linear regression analysis was used to examine the possible contribution of logical thinking

abilities (LOGIC) on rural secondary students integrated science process skills (PROCESS). On the other hand, stepwise multiple regression analysis was used to ascertain whether logical thinking abilities (LOGIC) and

integrated science process skills (PROCESS) can make significant contribution on rural secondary students science achievement (SCIENCE).

In this study, stepwise variables selection method was used in order to obtain a parsimonious model

which can explain most of the variance in the dependent variable (i.e. SCIENCE) by using least number of

independent variables (i.e. LOGIC and PROCESS). Assumptions namely normality, homoscedasticity,

linearity, and independence were examined prior to multiple regression analysis (Appendix X). Furthermore,

distance statistics (leverage measure and Cooks distance) and influence statistics (DfBeta and DfFit) were used to identify any outliers or influential observations in the data set (Appendix XI). To detect multicollinearity

among the independent variables studied, correlation matrices, Tolerance (T) and Variance Inflation Factor

(VIF) were also examined (Hair et al., 1998).

Research Findings and Discussion

The Acquisition of Integrated Science Process Skills among Rural Secondary Students in the Interior

Division of Sabah

Table 8 shows the mean and standard deviation of students overall acquisition of integrated science process skills and for each of the five subscales respectively.

Table 8

Mean and Standard Deviation of Students Acquisition of Integrated Science Process Skills (N = 575)

Subscales Nos.

Item

M SD M% SD% Range

Graphing and Interpreting Data 6 3.016 1.391 50.262 23.185 0 - 6

Defining Operationally 6 2.574 1.343 42.898 22.377 0 - 6

Identifying and Stating Hypothesis 10 4.127 1.831 41.270 18.310 0 - 10

Designing Investigation 6 2.449 1.430 40.812 23.838 0 - 6

Controlling Variables 12 4.884 2.318 40.696 19.320 0 - 12

Overall 40 17.049 5.513 42.622 13.782 5 - 35

Based on the mean in percentages (M%) as shown in Table 8, the acquisition of integrated science

process skills in descending order is Graphing and Interpreting Data, Defining Operationally, Identifying and Stating Hypothesis, Designing Investigation, and Controlling Variables.

The Acquisition of Logical Thinking Abilities among Rural Secondary Students in the Interior Division

of Sabah

Table 9 shows the mean and standard deviation of students overall acquisition of logical thinking abilities and for each of the six subscales respectively.

Table 9

Mean and Standard Deviation of Students Logical Thinking Abilities (N = 549)

Subscales Nos.

Item

M SD M% SD% Range

Conservational Reasoning 4 1.384 1.084 34.608 27.100 0 - 4

Combinatorial Reasoning 3 .424 .619 14.147 20.640 0 - 3

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Controlling Variables 3 .368 .582 12.263 19.403 0 - 3

Correlational Reasoning 3 .330 .582 10.990 19.383 0 - 3

Proportional Reasoning 5 .516 .749 10.310 14.972 0 - 4

Probabilistic Reasoning 3 .169 .463 5.647 15.417 0 - 3

Overall 21 3.191 2.158 15.197 10.274 0 - 12

Based on the mean in percentages as shown in Table 9, the acquisition of logical thinking abilities in

descending order is Conservational Reasoning, Combinatorial Reasoning, Controlling Variables, Correlational Reasoning, Proportional Reasoning, and Probabilistic Reasoning.

Science Achievement among Rural Secondary Students in the Interior Division of Sabah

Table 10 shows the mean and standard deviation of students overall science achievement and for each of the three subscales respectively.

Table 10

Mean and Standard Deviation of Students Science Achievement (N = 598)

Subscales Nos.

Item

M SD M% SD% Range

Elementary Biology 6.142 2.293 40.947 15.287 1 - 14

Heredity and Variation 6 2.589 1.362 43.143 22.693 0 - 6

Body Coordination 9 3.554 1.567 39.483 17.410 0 - 8

Elementary Chemistry 5.977 2.390 39.844 15.932 0 - 14

Matter and Material 8 3.560 1.630 44.503 20.370 0 - 8

Energy and Chemical Changes 7 2.416 1.427 34.520 20.383 0 - 6

Elementary Physics 5.283 2.137 35.217 14.249 1 - 11

Light, Colour and Vision 15 5.283 2.137 35.217 14.249 1 - 11

Overall 45 17.401 5.248 38.670 11.661 5 - 38

Based on the mean in percentages as shown in Table 10, rural secondary students science achievement in descending order is Elementary Biology (Heredity and Variation; Body Coordination), Elementary Chemistry (Matter and Material; Energy and Chemical Changes), and Elementary Physics (Light, Colour, and Vision).

Mean Difference in the Acquisition of Integrated Science Process Skills, Logical Thinking Abilities, and

Science Achievement among Rural Secondary Students in the Interior Division of Sabah

The first null hypothesis was tested by using the Independent sample t-test at a specified significance

level, alpha = .05. As shown in Table 11 and Table 12, independent sample t-test results showed that there is a

significant difference in the acquisition of integrated science process skills (t = 3.071, p = .002) and science

achievement (t = 3.244, p = .001) between male and female rural secondary students in the Interior Division of

Sabah. Hence, these findings had successfully rejected the first null hypothesis. Female students performed

better than male students in the acquisition of integrated science process skills and science achievement.

In relation to this, female rural secondary students performed better than their counterparts in the

acquisition of Identifying Variables and Identifying and Stating Hypothesis. This finding is consistent with the previous research (e.g., Pettus & Haley, 1980; Roadrangka et al.,1996; Zaliha et al., 1996). On the other

hand, this study has revealed that female rural secondary students performed better in Elementary Biology and Elementary Chemistry as compared to their counterparts. These findings are consistent with previous findings by Erickson & Erickson (1984), Roadrangka (1995) and TIMSS-R (2000). However, the mean difference in

Elementary Physics between male and female rural secondary students is not statistically significant.

Table 11

Mean Difference in the Acquisition of Integrated Science Process Skills based on Gender (N = 575)

Subscales Gender N M SD t df p

Identifying Variables Male 268 4.519 2.254 3.561* 573 < .0005

Female 307 5.202 2.330

Overall 575 4.884 2.318

Identifying and Stating

Hypothesis

Male 268 3.937 1.858 2.339* 573 .020

Female 307 4.293 1.793

Overall 575 4.127 1.831

Defining

Operationally

Male 268 2.534 1.413 .673 573 .501

Female 307 2.609 1.280

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Overall 575 2.574 1.343

Designing

Investigations

Male 268 2.396 1.479 .833 573 .405

Female 307 2.495 1.387

Overall 575 2.449 1.430

Graphing and

Interpreting Data

Male 268 2.914 1.370 1.637 573 .102

Female 307 3.104 1.406

Overall 575 3.016 1.391

Overall Male 268 16.299 5.666 3.071* 573 .002

Female 307 17.704 5.298

Overall 575 17.049 5.513

* p < .05

Table 12

Mean Difference in Science Achievement based on Gender (N = 598)

Subscales Gender N M SD t df p

Elementary Biology

Heredity and Variation

Body Coordination

Male 282 5.858 2.258 2.878* 596 .004

Female 316 6.396 2.298

Overall 598 6.142 2.293

Elementary Chemistry

Matter and Material

Energy and Chemical

Changes

Male 282 5.649 2.315 3.191* 596 .001

Female 316 6.269 2.421

Overall 598 5.977 2.390

Elementary Physics

Light, Colour and Vision

Male 282 5.163 2.128 1.292 596 .197

Female 316 5.389 2.143

Overall 598 5.283 2.137

Overall Male 282 16.670 5.096 3.244* 596 .001

Female 316 18.054 5.302

Overall 598 17.401 5.248

* p < .05

However, independent sample t-test revealed that the difference in the acquisition of logical thinking

abilities between male and female students is not statistically significant (t = -1.721, p = .086) (Table 13).

Table 13:

Mean Difference in the Acquisition of Logical Thinking Abilities based on Gender (N = 549)

Subscales Gender N M SD t df p

Conservational

Reasoning

Male 251 1.498 1.201 -2.222* 477.331 .027

Female 298 1.289 .966

Overall 549 1.384 1.084

Proportional Reasoning Male 251 .582 .777 -1.893 515.368 .059

Female 298 .460 .720

Overall 549 .516 .749

Controlling Variables Male 251 .387 .612 -.684 547 .495

Female 298 .352 .557

Overall 549 .368 .582

Probabilistic Reasoning Male 251 .163 .440 .281 547 .779

Female 298 .175 .482

Overall 549 .169 .463

Correlational

Reasoning

Male 251 .339 .627 -.331 547 .741

Female 298 .322 .542

Overall 549 .330 .582

Combinatorial

Reasoning

Male 251 .398 .601 .903 547 .367

Female 298 .446 .635

Overall 549 .424 .619

Overall Male 251 3.367 2.373 -1.721 483.410 .086

Female 298 3.044 1.949

Overall 549 3.191 2.158

* p < .05

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This study has found an insignificant difference in the acquisition of logical thinking abilities between

male and female rural secondary students in the Interior Division of Sabah. Research conducted by Keig and

Rubba (1993), Michael Liau (1982) and Roadrangka (1995) have also made the same conclusion. However, this

finding was contradicted with the findings of previous researchers (e.g., DeLuca, 1981; Hernandez, Marek, &

Renner, 1984; Howe & Shayer, 1981; Meehan, 1984; Shemesh, 1990) which have found that male students

performed better than their counterparts in the Piagetian formal reasoning tasks.

Linear Relationships among Integrated Science Process Skills, Logical Thinking Abilities and Science

Achievement among Rural Secondary Students in the Interior Division of Sabah

The second null hypothesis was tested by using the Pearsons product-moment correlation at a specified significance level, Alpha = .05. Correlation analysis results showed that there were moderate, positive

and significant correlations among students integrated science process skills, logical thinking abilities and science achievement. In relation to this, Pearsons product-moment correlation coefficients were found in the range of .363 to .554 (Table 14). Hence, this finding had successfully rejected the second null hypothesis.

Table 14

Pearsons Product-Moment Correlation Results

Variables LOGIC PROCESS SCIENCE

LOGIC -

PROCESS .447**

(p < .0005)

N = 505

-

SCIENCE .363**

(p < .0005)

N = 518

.554**

(p < .0005)

N = 544

-

** p < .01

Logical thinking abilities were positively and moderately correlated with integrated science process

skills among rural secondary students (r = .447, p < .0005). This finding is further supported by Allen (1973),

Linn and Their (1975), Padilla et al. (1983), Tobin and Capie (1980; 1982), Yap (1985), and Yeany et al.

(1986). On the other hand, science process skills were positively and moderately correlated with students science achievement (r = .554, p < .0005). According to Funk et al. (1979), science process skills are the

vehicle to generate scientific knowledge and the ways to formulate scientific concepts. Besides that, logical

thinking abilities were also positively and moderately correlated with students science achievement (r = .363, p < .0005). This finding is consistent with previous research findings (e.g., Bitner, 1991; Boulanger & Kremer,

1981; Hofstein & Mandler, 1985; Howe & Durr, 1982; Keig & Rubba, 1993; Krajcik & Haney, 1987;Lawson,

1982a, 1982b; Marek, 1981; Mitcell & Lawson, 1988; Piburn, 1980; Piburn & Baker, 1989; Roadrangka, 1995;

Siti Hawa Munji, 1998; Staver & Halsted, 1985).

The Influence of Logical Thinking Abilities on Integrated Science Process Skills among Rural Secondary

Students in the Interior Division of Sabah

The third null hypothesis was tested by using the simple linear regression analysis. Results in Table 15

showed that logical thinking abilities significantly contributed to students integrated science process skills

(F(1, 504) = 125.421, p < .0005). Based on the Beta value, logical thinking abilities ( = .447, t(505) = 11.199, p < .0005) contributed to the variance in students integrated science process skills. The value of the coefficient of determination, R

2 (= .200) revealed that logical thinking abilities accounted for 20.0% of the variance in rural

secondary students integrated science process skills. Hence, this finding had successfully rejected the third null hypothesis.

Table 15

Simple Linear Regression Analysis Results for Logical Thinking Abilities on Integrated Science Process Skills

(N = 505)

Predictor variable B SE R2 t p

Constant

13.453 .397 33.863 p

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PROCESS = 13.453 + 1.162 LOGIC

Multiple-R = .447

R2

= .200

Adjusted R2 = .198

SEE = 4.99499

F (1, 504) = 125.421; p

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achievement. Hence, those who are involved directly or indirectly in the planning and implementation of

science curriculum need to plan effective intervention programs to increase students logical thinking abilities and integrated science process skills in the effort to improve rural secondary students science achievement. These follow-up efforts are crucial to ensure that our nations vision to establish a science and technology- based society will become reality.

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