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Biology Interest Among Asasipintar Students

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biology interest among ASASIPINTAR STUDENTS | A MINI PROJECT REPORT| Submitted by 1. AHMAD SYAZWAN BIN SUHAIMI AP00161 2. IZZATY SHAIMA BINTI SHAMSUDIN AP00164 3.

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MUHAMMAD FAIZUAN BIN AMINUDDIN AP00159 4. SITI NABILA AMIRA BINTI SAMSUDIN AP00158| Submitted toMiss Noraniza Binti IbrahimSTATISTICS (PNAP0154)ASASIpintarPUSAT PERMATApintarTM NEGARAUNIVERSITI KEBANGSAAN MALAYSIA (UKM)APRIL 2013| Table of Contents Content| Page| Abstract| | Introduction to project topic| |

Methods of Data Analysis| | Analysis and Results| | Conclusion| | References| | Appendix| | | ABSTRACT Most students have to take biology as one of the subjects graded in their CGPA. But not all students want to be a doctor or have much interest in biology. Quizzes and test are frequently used to measure the level of understanding of students towards specific topic of a subject Biology quizzes are common, and their marks or scores in these quizzes can be used to measure either their effort in the quizzes or their interest in biology or maybe both.

This research paper discussed the relationship between the interest in biology and their total score, gender and their study style and lastly the relationship between scores 1. INTRODUCTION 2. 1. Overview Biology is one of the compulsory courses that have to be taken by ASASIpintar students. This course aims to enhance the students’ understanding and knowledge in biological sciences. Teaching methods include small group lecture, tutorial, laboratory experiments, independent learning and problem based learning. Students will be assessed by weekly quizzes, lab reports, and mid-semester and final semester examination.

However, the interest level of students in Biology differs from one another. Other than that, their style of studying Biology or doing their revision on this particular subject is also different between students. This project aims to study the relationship between these two factors, which are the level of interest in Biology and their style of learning and studying the subject with the scores that these students gained in their topical quizzes. 2. 2. Objectives 2. 3. 1. To investigate the relationship between interest and total score 2. 3. 2.

To investigate the distribution of interest in biology among student 2. 3. 3. To investigate the relationship between gender and study style 2. 3. Research Question 2. 4. 4. Does interest has any relationship with the total scores gain by student in their quizzes? 2. 4. 5. What are the distribution of interest in biology among student? 2. 4. 6. Is there any relationship between gender and their style of study biology? 2. 4. Research Hypothesis A statistical hypothesis is a conjecture about the population parameter. This conjecture may or may not be true.

Null hypothesis (Ho) is a statistical hypothesis states that there is no difference between a parameter and a specific value, or that there is no difference between the two parameters while alternative hypothesis (H1) is a statistical hypothesis that states the existence of a difference between a parameter and a specific value, or states that there is a difference between two parameters. 2. 5. 7. Hypothesis 1 Ho: There is no relationship between interest and total score H1: There is relationship between interest and total score 2. 5. 8. Hypothesis 3 Ho: The students’ interest in biology are distributed as follows; 17. % are not interested, 20% are moderate and 62. 5% are interested in biology. H1: The distribution are not the same as stated in Ho. 2. 5. 9. Hypothesis 2 Ho: There is no relationship between gender and study style H1: There is relationship between gender and study style 2. 5. 10. Hypothesis 4 Ho: There is no relationship between interest and study style H1: There is relationship between interest and study style 2. METHODOLOGY Herein, the chosen respondents were randomly selected from ASASIpintar students. The survey methods are the research instruments used for the data collection. 0 students of ASASIpintar were chosen in this study accomplished a questionnaire to assess their biology quizzes’ marks. The computed values are compared to the Likert scale for data interpretation. The collected data were analyzed using SPSS software. These will be presented below: 3. 5. Descriptive statistics The descriptive method is used to collect the necessary data. In the descriptive statistic, the measures of tendency (mean, mode, median and variance) will be calculated. Measures of tendency are numerical values that locate, in some sense, the center of a data set.

The data will be presented in bar chart or pie chart for qualitative data and histogram for quantitative data. 3. 6. Inferential statistics The inferential statistics using sample data to draw coclusions about the ASASIpintar students. The sample random is selected and the information gained from it is used to make generalizations about the ASASIpintar students. 3. 7. 11. Correlation 3. 7. 12. 1. Pearson’s correlation coefficient test was used to determine the relationship of non-parametric data. One of the tests is to check the relationship between gender and the study style.

The linear correlation coefficient (r) is used to measure the strength and direction of a linear relationship between two variables 3. 7. 12. 2. Spearman’s correlation coefficient test was used to determine the relationship between parametric and non-parametric data. One of the tests is to check the relationship between interest of the students towards biology and their total score. The linear correlation coefficient (r) is used to measure the strength and direction of a linear relationship between two variables 3. 7. 12. Comparison Test 3. 7. 13. 3. Chi-square

The Chi-square goodness-of-fit test is used to how well a particular statistical distribution, such as a binomial or a normal. The null hypothesis Ho is that the particular distribution does provide a model for the data; the alternative hypothesis H1 is that it does not. 3. ANALYSIS AND RESULTS 4. 7. Descriptive statistics 4. 8. Inferential statistics 4. 9. 13. Relationship between interest and total score VARIABLES| R| R SQUARE| Interest and Total score| . 399| . 159| Since r = 0. 399, there is weak positive correlation between total score and interest. Since r= 0. 159, this indicates that 15. % of the variation in total score can be attributed to the linear relationship with the interest. 15. 9% of total variation in total score is explained by regression line using the interest. Another 84. 1% is explained by other variable. Since the P-value is 0. 011 and it is less than ? -value, the null hypothesis is rejected. There is sufficient evidence to show that there is relationship between the interest and the total score. It is proven that the interest does affect the total score. 4. 9. 14. Distribution of interest in biology VARIABLES| P-VALUE| Interest in biology| 0. 190|

Since the P-value is 0. 19 and it is more than ? -value, the null hypothesis is failed to be rejected. There is sufficient evidence to show that the students’ interest in Biology are distributed as follows; 17. 5% are not interested, 20% are moderate and 62. 5% are interested in biology. 4. 9. 15. Relationship between style and gender VARIABLES| P-VALUE| Style and Gender| 0. 558| Since the P-value is 0. 558 and it is more than ? -value, the null hypothesis is failed to be rejected. There is sufficient evidence to show that there is no relationship between the study style and gender.

It is proven that the gender is independent to the study style. The study style may affected by environment and the students’ self. 4. CONCLUSION 5. REFERENCES 6. APPENDIX 7. 9. Questionnaire Personal information| | Age | | Gender | | Interest in biology| 1| 2| 3| 4| 5| | | | | | | Which of the following is the way you study? | | Study alone| | Group study| | Continuous study| | Stay up| | What is your marks in following quizzes? | | The cell| | Cellular respiration| | Biochemistry | | Photosynthesis | | Plant physiology | | 7. 10. Analysis of interest & total score Correlations| | TotalScore| Interest|

Spearman’s rho| TotalScore| Correlation Coefficient| 1. 000| . 399*| | | Sig. (2-tailed)| . | . 011| | | N| 40| 40| | Interest| Correlation Coefficient| . 399*| 1. 000| | | Sig. (2-tailed)| . 011| . | | | N| 40| 40| *. Correlation is significant at the 0. 05 level (2-tailed). | 7. 11. Analysis of gender ; style Correlations| | Style| Gender| Style| Pearson Correlation| 1| -. 095| | Sig. (2-tailed)| | . 558| | N| 40| 40| Gender| Pearson Correlation| -. 095| 1| | Sig. (2-tailed)| . 558| | | N| 40| 40| Case Processing Summary| | Cases| | Valid| Missing| Total| | N| Percent| N| Percent| N| Percent|

Gender * Style| 40| 100. 0%| 0| 0. 0%| 40| 100. 0%| Gender * Style Crosstabulation| | Style| Total| | Discussion| Study Alone| Stay up| continuous study| | Gender| Male| Count| 4| 6| 5| 5| 20| | | Expected Count| 4. 0| 7. 5| 4. 0| 4. 5| 20. 0| | female| Count| 4| 9| 3| 4| 20| | | Expected Count| 4. 0| 7. 5| 4. 0| 4. 5| 20. 0| Total| Count| 8| 15| 8| 9| 40| | Expected Count| 8. 0| 15. 0| 8. 0| 9. 0| 40. 0| Chi-Square Tests| | Value| df| Asymp. Sig. (2-sided)| Pearson Chi-Square| 1. 211a| 3| . 750| Likelihood Ratio| 1. 221| 3| . 748| Linear-by-Linear Association| . 355| 1| . 551| N of Valid Cases| 40| | | . 6 cells (75. 0%) have expected count less than 5. The minimum expected count is 4. 00. | 7. 12. Analysis of gender ; interest Case Processing Summary| | Cases| | Valid| Missing| Total| | N| Percent| N| Percent| N| Percent| Gender * int| 40| 100. 0%| 0| 0. 0%| 40| 100. 0%| Gender * int Crosstabulation| | int| Total| | not interested| moderate| interested| | Gender| Male| Count| 2| 6| 12| 20| | | Expected Count| 3. 5| 4. 0| 12. 5| 20. 0| | | % within Gender| 10. 0%| 30. 0%| 60. 0%| 100. 0%| | | % within int| 28. 6%| 75. 0%| 48. 0%| 50. 0%| | | % of Total| 5. 0%| 15. 0%| 30. 0%| 50. 0%| female| Count| 5| 2| 13| 20| | | Expected Count| 3. 5| 4. 0| 12. 5| 20. 0| | | % within Gender| 25. 0%| 10. 0%| 65. 0%| 100. 0%| | | % within int| 71. 4%| 25. 0%| 52. 0%| 50. 0%| | | % of Total| 12. 5%| 5. 0%| 32. 5%| 50. 0%| Total| Count| 7| 8| 25| 40| | Expected Count| 7. 0| 8. 0| 25. 0| 40. 0| | % within Gender| 17. 5%| 20. 0%| 62. 5%| 100. 0%| | % within int| 100. 0%| 100. 0%| 100. 0%| 100. 0%| | % of Total| 17. 5%| 20. 0%| 62. 5%| 100. 0%| Chi-Square Tests| | Value| df| Asymp. Sig. (2-sided)| Pearson Chi-Square| 3. 326a| 2| . 190| Likelihood Ratio| 3. 461| 2| . 177| Linear-by-Linear Association| . 63| 1| . 686| N of Valid Cases| 40| | | a. 4 cells (66. 7%) have expected count less than 5. The minimum expected count is 3. 50. | ANOVA| | Sum of Squares| df| Mean Square| F| Sig. | Score1| Between Groups| 87. 811| 4| 21. 953| 2. 331| . 075| | Within Groups| 329. 689| 35| 9. 420| | | | Total| 417. 500| 39| | | | Score2| Between Groups| 31. 709| 4| 7. 927| 1. 950| . 124| | Within Groups| 142. 266| 35| 4. 065| | | | Total| 173. 975| 39| | | | Score3| Between Groups| 9. 376| 4| 2. 344| . 710| . 591| | Within Groups| 115. 599| 35| 3. 303| | | | Total| 124. 975| 39| | | | Score4| Between Groups| 21. 78| 4| 5. 494| 1. 217| . 321| | Within Groups| 158. 022| 35| 4. 515| | | | Total| 180. 000| 39| | | | Score5| Between Groups| 24. 961| 4| 6. 240| 1. 195| . 330| | Within Groups| 182. 814| 35| 5. 223| | | | Total| 207. 775| 39| | | | We used the Other than that, Check relationship between interest and total score – weak relationship Style and total score – no correlation Between score – correlation pearson Correlation coefficient – spearman Style and interest – no correlation – pearson Gender and score – -weak relationship – spearman Style and gender – chi square test = no relationship

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