{"id":169,"date":"2024-10-11T14:59:47","date_gmt":"2024-10-11T09:29:47","guid":{"rendered":"https:\/\/edu.cmb.ac.lk\/journal\/ijsse\/?page_id=169"},"modified":"2024-10-18T10:41:28","modified_gmt":"2024-10-18T05:11:28","slug":"article-1","status":"publish","type":"page","link":"https:\/\/edu.cmb.ac.lk\/journal\/ijsse\/article-1\/","title":{"rendered":"The Relationship between the Factors Affecting Learning- Teaching Process of Mathematics and Students\u2019 Performance in Mathematics in Type II Schools in the Jaffna District"},"content":{"rendered":"

[vc_row][vc_column width=”5\/6″][vc_column_text]<\/p>\n

The Relationship between the Factors Affecting Learning- Teaching Process of Mathematics and Students\u2019 Performance in Mathematics in Type II Schools in the Jaffna District<\/strong><\/h3>\n

[\/vc_column_text][vc_separator color=”black” style=”shadow” border_width=”2″][vc_column_text]Vartharajan Balamurali1<\/sup>, Sabarathnam Atrhirathan1<\/sup><\/strong><\/p>\n

Faculty of Education, University of Colombo<\/em><\/p>\n

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Abstract<\/strong><\/p>\n

The learning-teaching process significantly impacts student achievement, but the challenges schools and teachers face contribute to ineffective learning and teaching activities. In Sri Lanka, mathematics is an essential subject for secondary schools. However, type II schools in the Jaffna District need more levels of student achievement in mathematics. So far, there have yet to be studies on the learning- teaching process of Mathematics in type II schools in the Jaffna district. This study aims to examine the relationship between the domain factors affecting the learning-teaching process of mathematics and students’ performance in mathematics in type II schools in the Jaffna district. The survey research method- based quantitative approach was adopted. Thirty schools were selected as the sample using the systematic sampling technique from 83 type II schools with G.C.E. (O\/L.) in Jaffna District for the survey. Data were collected by questionnaire from 341 senior secondary students selected by stratified random sampling technique. The quantitative data were analyzed using factor analysis. The results revealed that the domain factors that affect the learning-teaching process of Mathematics are the Teacher’s Knowledge, Teacher’s Effective Communication, Teaching Process, Teacher’s Attitude, Managing the lesson and classroom, Classroom psychological environment, Teacher’s Motivation, Teacher-Student Relationship, Students’ Attitude, Students’ Preparation for Learning, and Students’ Self-Motivation. Linear<\/p>\n

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Multiple Regression examined the relationship between the domain factors and the Mathematics marks of students. The multiple correlation coefficient value was<\/p>\n

0.540. In the ANOVA test, the F value was 11.232, and the p-value was 0.000. The Regression results revealed that a 1-unit increase in teacher performance value, teacher motivation, teacher-student relationship, students’ self-learning, and readiness to learn led to 1058.9%, 320.8%, 474.4%, and 602.1% increases in students’ mathematics marks, respectively.<\/p>\n

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Keywords: <\/em>Factors, Affecting, learning-teaching, Mathematics<\/p>\n

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Introduction<\/strong><\/p>\n

Quality education is challenging to provide to all children in South Asia. In many places, learning methods are teacher-centric (UNICEF, 2014). Issues with education in Sri Lanka include teacher-centered to student-centered pedagogies, exam- oriented competition and pressure, mastering skills, and neglect of secondary education (Brinkmann, 2017).<\/p>\n

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Teachers worldwide are moving towards more inquiry-based, experiential, and constructivist methods. In Sri Lanka, however, education’s transmission and transaction functions are diminishing in favor of a textbook culture (National Education Commission, 2017). Even though exam-focused instruction is still prominent in classrooms, the results could be better. Many students fail the G.C.E. (O.L.) exam after 11 years of schooling. Even those with adequate basic skills cannot fulfill the demands of the workplace, and there are also issues with discipline (National Education Commission, 2016).<\/p>\n

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The Jaffna district has a lower proportion of the number of students and the number of teachers in type II schools than Sri Lanka as a whole.<\/p>\n

Table 1<\/strong><\/p>\n

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Consequently, the schools in the Jaffna district should achieve better results than schools in other parts of Sri Lanka. However, the opposite is true.<\/p>\n

Table 2<\/strong><\/p>\n

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Table 3<\/strong><\/p>\n

\"\"[\/vc_column_text][vc_column_text]Table 4<\/strong><\/p>\n

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According to the National Education Commission (2016), classrooms lack student- centered, activity-oriented learning, leading to inadequate instruction, lack of development, and social distancing due to malicious attitudes among teachers.<\/p>\n

According to the NEREC (2016) study on grade 8 students,’ the performance of type II and 1C schools in Sri Lanka is lower than that of type III and 1AB schools. According to the research unit of Northern Province (2017), 20% of type II schools in the Northern province face ineffective learning and teaching processes, affecting student achievement in the Jaffna district.<\/p>\n

According to the National Education Commission (2016), 20% of teachers in government schools lack professional qualifications in teaching. Some teachers must use more effective methods to teach more students and show a lack of interest in learning. Schools and teachers face various challenges in achieving the expected level of student performance in final examinations in the subject of Mathematics. Learning and teaching activities could be more effective in terms of the outcomes of the school process. As a result, the student achievement level could be more satisfactory (Ministry of Education Northern Province, 2014). However, the background factors that have been identified by previous studies that have an impact on the teaching and learning process are found to be satisfactory. Then, the question emerges as to why schools’ learning and teaching processes could be more effective. This context leads to the need for the study into this problem.<\/p>\n

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Objective<\/strong><\/p>\n

Examine the relationship between the factors affecting the learning-teaching process of Mathematics and students’ performance in Mathematics based on the feedback from senior secondary students.<\/p>\n

 <\/p>\n

Research Design<\/strong><\/p>\n

This study used the quantitative survey method. Thirty schools were selected as samples using the systematic sampling technique from 83 type II schools with<\/p>\n

G.C.E. (O.L.) in the Jaffna, Valikamam, and Thenmarachchi education zones. Data were collected by questionnaire from 341 senior secondary students selected by stratified random sampling technique. A performance test was conducted on those students covering the first five units of class 10 mathematics. The data were analyzed using factor analysis and linear multiple regression.<\/p>\n

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Results<\/strong><\/p>\n

Test of Normality of Mathematics marks of the students<\/strong><\/p>\n

The skewness is 0.172, with a standard error of 0.132. This gives a measure of skewness of 0.172\/0.132 = 1.3030. Kurtosis is -0.271, with a standard error of 0.263, giving a value of – 0.271\/0.263 = -1.030. Based on the Z value for the normality test, either or both the skewness and kurtosis values should be within the range of +1.96 or -1.96. Therefore, the dependent variable (the students’ mathematics marks) is usually distributed.<\/p>\n

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Regression<\/em><\/strong><\/p>\n

Linear Multiple Regression examined the relationship between the domain factors and students\u2019 scores.<\/p>\n

Table 5<\/strong><\/p>\n

Regression<\/em><\/p>\n

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a. Predictors: (Constant), Motivation of School Management, Performance of teacher, Teacher Motivation, Teacher-Student Relationship, Student’s Self- Motivation, Student\u2019s self-learning and readiness for learning, Teacher’s Attitude, Psychological Environment, Managing the lesson and classroom, Student Attitude, Effective Communication, Teacher<\/p>\n

Knowledge<\/p>\n

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b. Dependent Variable: Marks<\/p>\n

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The model reveals that the R (multiple correlation coefficient) value was 0.540. It measures the degree of relationship between the students’ marks and the predicted values. The R-squared (coefficient of determination) value was 0.291. This means that about 29% of the variation in the students’ marks is explained by the variation in the independent variables. The R-squared value was 0.265. It adjusts the statistic based on the number of independent variables in the model. That is the desired property of a goodness-of-fit statistic.<\/p>\n

ANOVA<\/em><\/strong><\/p>\n

Table 6<\/p>\n

ANOVA<\/em><\/p>\n

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a. Dependent Variable: Marks<\/p>\n

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b. Predictors: (Constant), Motivation of School Management, Performance of teacher, Teacher Motivation, Teacher-Student Relationship, Students\u2019 Self- Motivation, Student\u2019s self-learning and readiness for learning, Teacher’s Attitude, Psychological Environment, Managing the lesson and classroom, Student Attitude, Effective Communication, Teacher Knowledge<\/p>\n

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The F value was 11.232, and the p-value was 0.000. The p-value is less than 0.005. Therefore, the fitted model is significant. Hence, there is a significant relationship between dependent and independent variables.<\/p>\n

Relationship between a linear combination of the variables and mathematics marks of the students<\/p>\n

Table 7<\/strong><\/p>\n

Relationship between a linear combination of the variables and marks of the students<\/em><\/p>\n

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The P values of teacher knowledge, effective communication, teacher’s attitude, lesson and classroom management, psychological environment, student attitude, and motivation of school management are respectively 0.719, 0.398, 0.410, 0.972, 0.266, 0.033, 0.461, and 0.804. These values are more significant than 0.05. Therefore, these predictors were removed and reanalyzed.<\/p>\n

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Table 8<\/strong><\/p>\n

Relationship between a linear combination of the variables and mathematics marks of the students<\/em><\/p>\n

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a. Dependent Variable: Marks<\/p>\n

b. Predictors: (Constant),<\/p>\n

X1 = Performance of teacher, X2 = Teacher Motivation, X3 = Teacher-Student Relationship X4 = Student\u2019s self-learning and readiness for learning<\/p>\n

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The p-values of these selected predictors are less than 0.05, and the fitted model is significant. The fitted model is written as Y = 42.716 + 10.589 X1 + 3.208 X2 + 4.744 X3 + 6.021 X4.<\/p>\n

 <\/p>\n

The p-values of these selected predictors are less than 0.05, and the fitted model is significant. The fitted model is written as Y = 42.716 + 10.589 X1 + 3.208 X2 + 4.744 X3 + 6.021 X4.<\/p>\n

 <\/p>\n

The coefficient of X1 shows that a 1 unit increase in the teacher’s performance value would result in a 10.589 (1058.9%) increase in the mathematics marks of students, other variables being held constant. This coefficient value is significant at a 1% level, and the t<\/em>-statistics of teacher performance indicate significant positive variation in the dependent variable, which is the mathematics marks of students.<\/p>\n

The coefficient of X2 shows that a 1 unit increase in the value of teacher motivation would result in a 3.208 (320.8%) increase in the mathematics marks of students, other variables being held constant. This coefficient value is significant at a 1% level, and the t-statistic of teacher motivation indicates significant positive variation. The dependent variable is the mathematics marks of students.<\/p>\n

The coefficient of X3 shows that a 1 unit increase in the value of the teacher- student relationship would result in a 4.744 (474.4%) increase in students’ mathematics marks, other variables being held constant. This coefficient value is significant at the 1% level, and the t-statistics of teacher-student relationships indicate significant positive variation in the dependent variable, which is students’ mathematics marks.<\/p>\n

The coefficient of X4 shows that a 1 unit increase in the value of the student\u2019s self- learning and readiness for learning would result in a 6.021 (602.1% increase) in the mathematics marks of students, other variables being held constant. This coefficient value is significant at the 1% level, and the t-statistics of the student\u2019s self-learning and readiness for learning indicate significant positive variation in the dependent variable, which is the mathematics marks of students.<\/p>\n

 <\/p>\n

Recommendations<\/strong><\/p>\n

Based on the findings of this study, it is suggested that the learning and teaching process of mathematics be improved in terms of the identified domain factors. Mathematics teachers must be co-learners so that they can update and develop their professional knowledge and skills.<\/p>\n

 <\/p>\n

Mathematics teachers need to develop a positive attitude toward improving their professional capacity to suit the needs of the students and Mathematics learning and teaching. The learning and teaching process of mathematics should be carried out efficiently to achieve the expected outcomes, and teachers and school management should motivate students appropriately to make them willingly engaged in learning. Mathematics teachers should maintain rapport with students, students’ home environment should be organized so students can willingly engage in self-learning, and the cooperation of social institutions and organizations should be obtained to carry out mathematics learning and teaching processes more effectively in schools.<\/p>\n

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This study will significantly contribute to upgrading the learning and teaching process of Mathematics. It could also be used as initial work for those who are interested in conducting further studies in this area.[\/vc_column_text][vc_column_text]<\/p>\n

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References<\/strong><\/p>\n