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CORRELATES OF LEARNING ENVIRONMENT AND MATHEMATICS PERFORMANCE OF ENGINEERING STUDENTS Engr. Greg A. Mallari Engr. Jan Alexis B. Monsalud Engr. Sally G. Corpuz Engr. Mark Anthony U. Bernardo Dr. David Cababaro Bueno
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Abstract- The study was focused on the school learning environment as perceived by the engineering students and its relationship with Mathematics performance. Tit utilized the descriptive method of research. Documentary analysis was done for the Mathematics performance. A standardized instrument was used to measure the level of agreement of students on the factors of the school learning environment. The data gathered were analyzed with the use of Percentage, Mean and Pearson Product Correlation. There was strong agreement on the factors of the school learning environment relative to student support, affiliation, professional interest, mission consensus, empowerment, innovation, and work pressure. However, the agreement was only noted in terms of resource adequacy. Majority of the student performed satisfactorily and very satisfactorily in Mathematics. However, it was also noted there were some who got poor performance. There was a significant relationship between school learning environment and Mathematics performance. The present study has shown how a school learning environment model can be applied to study the effect of learning environment on the performance of students. Keywords- Engineering Mathematics performance
education,
learning
environment,
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Introduction
In the book of Ballantine (2003), she said: “when children walk into the school building, they bring with them many 1
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baggages from home: ambition, motivation, pressures, expectations, physical and mental strengths and weaknesses, and sometimes abuse, insecurities, stress, and other problems�. Children bring their attitude toward school, among other contributes from home. Furthermore, Berger (2003) pointed out that when children enter school, learning then becomes a shared responsibility, a home and school affair. They do not stop learning at home because they go to school. These are just two educational grounds ventured by them at the same time. Each one should complement the other. In a large, heterogeneous school system, the relationship between achievement and learning environment is significant (Dryden & Fraser, 2006). The heterogeneity of the student population in large systems may explain this relationship. Achievement, as measured by tests, is laced with ability and learning factors. If an accurate measure of student learning could be devised, then the predictive relationship between student perceptions of the learning environment and classroom learning could be examined. To date, no literature has been found examining the relationship between school-based learning that uses multi-level modeling and the learning environment in a very large system. The literature shows that the relationships between achievement and student perceptions of the learning environment are generally positive (Walberg, 2001). However, most studies involve achievement, not learning, as the outcome measure. Noonan and Wold (2002) attempted to measure learning efficiency using the subtest on the assumption that chemistry is learned primarily in the classroom and is more dependent on school instruction than in many other subjects. Students who achieve well in one teacher's classroom may achieve poorly in another teacher's class. Similarly, in any classroom some students achieve well, while others, equally intelligent, achieve poorly. This might imply students’ attitudes 2
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toward their classroom behaviors affect their achievement and the classroom climate. Students' observation as an approach for assessment of classroom activities has been used by many studies. Ehman (2000) and Remmers (2003) indicated that students' observation approach provides an accurate picture of the classroom environment. Similarly, Goldberg pointed out that the validity of using students' observation as an approach for determining differential student reaction to teacher and classroom activities stems from the fact that students observe more of the teacher's typical behavior than is usually available to the outside observer. The assessment of learning environments is not an easy matter due to the complexity of the phenomenon under investigation, the number possible approaches that can be taken, and the conceptual and methodological difficulties within each approach. The contention here is that the difficulties involved can be reduced, delimited, and at least partially solve by appropriate representation of the problem in terms of modes for assessing and evaluating classroom learning environment. Moreover, school environment positively affects the pupil’s achievement. Gregorio (2003) said that well managed classroom create an atmosphere that is stimulating and inviting. Such classrooms are well ventilated, neatly, orderly arranged and well managed and the school grounds are beautifully landscaped, the school environment become aesthetically appealing to the learner. This creates a magnet for pupil/children to go to school regularly. The motivation that is created by this kind of surrounding may enhance pupil’s focus in learning. Creating a positive learning environment can benefit both the teacher and the learner and result in the achievement of holistic educational goals. Creating and implementing a learning environment means careful planning for the start of the school year. The learning environment must be envisioned in both a physical space and a cognitive space. The physical space of the 3
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classroom is managed as the teacher prepares the classroom for the students. An essential part of organizing the classroom involves developing a climate in which teachers encourage students to do their best and to be excited about what they are learning. There are two factors that are critical in creating such a motivational climate: value and effort. To be motivated, students must see the worth of the work that they are doing and the work others do. A teacher's demonstration of value shows students how their work is worthwhile and is connected to things that are important for them, including other learning and interests. Effort ties the time, energy, and creativity a student uses to develop the "work," to the value that the work holds. One way that teachers encourage effort is through specific praise, telling students specifically what it is that they are doing that is worthwhile and good. Thus, the preparation of an environment for the child, which contains many interesting and challenging activities, is the role of the teacher. The teacher guides, stimulates, challenges, models, elicits relevant task and provide such experience in a manner flexible enough to allow for the child’s present stage of development while providing appropriate new challenges. The program goal is to lay the foundation for academic learning through the child’s involvement in the real world and to promote achievement in school activities. A positive learning environment will contribute to a higher students’ achievement because they can interact freely to the discussion. The study focuses on the school learning environment as perceived by the engineering students and its relationship with Mathematics performance. Specifically, it aims to: (1) describe the perceived learning environment in relation to student support, affiliation, professional interest, mission consensus, empowerment, mnnovation, resource adequacy; and work pressure; (2) analyze the Mathematics performance of the
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respondents; and (3) infer significant relationship between the school learning environment and Mathematics performance.
Methodology This study used the descriptive-correlation method of research. Sevilla (1993) specified that the descriptive method is used to gather information about present existing condition. Further, Aquino (1993), defines the descriptive method as something more and beyond than just data gathering. The true meaning of the data collected should be reported from the point of view of the objectives and the basic assumptions of the study. Facts obtained maybe accurate expressions of central tendency or deviations or correlation, but the report is not research unless discussion of data is carried out up to the level of adequate interpretation. The data must be subjected to the thinking process by means of ordered reasoning. This method is the most appropriate to use because determined the existing relationship between the perceived learning environment and students’ performance in Mathematics. All second year students currently enrolled this academic year were taken as participants of the study. The researchers decided to consider the total of students to maintain the reliability and validity of the data gathered through the questionnaire. The research instrument used in this study was the “SchoolLevel Environment Questionnaire (SLEQ)” developed by Rentoul, A. J. & Fraser, B. J. (1983) for the development of a school-level environment. The SLEQ consists of 56 items, each scored on a five-point scale, and grouped in eight scales: (1) student support; (2) affiliation; (3) professional interest; (4) staff freedom; (5) participatory decision making; (6) innovation; (7) resource adequacy; and (8) work pressure. The development and validation of the instrument, the School-Level Environment Questionnaire (SLEQ), were described by Fisher, D.L and Fraser, 5
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B.J. (1990) for the study (Validity and Use of School-Level Environment Questionnaire�. The SLEQ measures perceptions of psychosocial dimensions of the environment of the school. The SLEQ was validated with three samples from Australian schools: 83 teachers from 19 metropolitan elementary and secondary schools in Sydney; 34 secondary school beginning teachers in New South Wales; and 109 elementary and secondary teachers in Tasmania. Results indicated that each SLEQ scale displayed satisfactory internal consistency with satisfactory discriminant validity results, suggesting that distinct, but somewhat overlapping, aspects of school environment were measured. The same questionnaire was pilot tested to the first year students of Special Science Curriculum to establish its face validity. Vague items on the checklist were modified. Those without bearing were removed and items that were suggested were incorporated to improve the questionnaire. The data gathered from the instrument were tabulated, analyzed and interpreted using the following tools: (1) Mean to determine the final weight of each item in the assessment of school-learning environment. To facilitate the interpretation of the description used in the assessment of school-learning environment, a Likert was used; and (2) Pearson-Product Moment Correlation was utilized to determine the significant relationship between school-learning environment and Mathematics performance.
Results and Discussion Student Support. The students are very positive in saying that they are pleasant, cooperative, and friendly to their instructors. They also strongly agree that they accept responsibility for their schooling, get along well with other students and instructors, and well-mannered and respectful to 6
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the school staff. Thus the overall assessment is 4.51, which is interpreted as “Strongly Agree”. Affiliation. The assessment on affiliation as element of schoollevel environment is 4.33 and interpreted as strongly agree. This means that the students are receiving encouragement from colleagues and classmates. Likewise, they are accepted by their instructors, and could rely on from their classmates for assistance if they need it, and most of all, they felt that they have friends at the school. Professional Interest. Professional interest as element of learning environment assess as 4.35, which is interpreted as “Strongly Agree”. This means that instructors in school are taking positively into consideration their interest in making their teaching responsive to the learners’ needs by discussing teaching methods and strategies with each other in meetings, and attending to in-service and other professional development activities. Moreover, they showed interest in what is happening in the school, and in professional activities of their colleagues. Mission Consensus. The students are very sure that they understood the mission of the school as reflected in activities being carried out in the organization. They also observed that instructors are regularly referring to the mission of the school when addressing school issues and it is consistent with the goals operated in the school. Empowerment. The assessment of 4.39 relative to instructors’ empowerment as element of learning environment is revealed. The students are very sure that decisions about the running of their activities are made by a group of instructors. This means that the instructors are encouraged to make decisions concerning students’ activities. Innovation. Innovation as element of learning environment is reflected as 4.63. As revealed, the students are very positive in saying that their instructors are encouraged to be innovative in the school. This is shown in their capacity to accept change in the 7
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organization and in teaching by implementing whatever new curricular materials as part of experimentation with various teaching approaches. Thus new and different ideas are being tried out in school. Resource Adequacy. The students strongly agree that the school has adequate selection of books and periodical. However, agreement is viewed only on the adequacy of equipment such as laboratory materials, books, videos tapes, films, recorders to cater for a variety of activities. Thus, the overall assessment is 3.94, with a descriptive rating of “Agree”. Work Pressure. It revealed that there is no constant pressure to keep studying and working in the school. They further felt that instructors have to work hard without any pressure. Thus, there is enough time for the teachers to relax, to take easy and still get the work done and to keep up with workload. Thus, the overall assessment is 4.40, which means “Strongly Agree”. Mathematics Performance of Student. The majority of the student got an average rating of satisfactory to very satisfactory, and some got an average performance. It is saddening to note that despite the strong agreement on the elements of conducive learning environment; still there are some who got poor performance. Relationship between Learning Environment and Mathematics Performance. The correlation between learning environment and Mathematics performance is revealed. The data shows that the null hypothesis is rejected as evidenced by the computed high correlation values. Thus, there is a significant relationship between school learning environment and Mathematics performance. In conclusion, there is strong agreement on the factors of school learning environment relative to student support, affiliation, professional interest, mission consensus, empowerment, innovation, and work pressure. However, agreement is only noted in terms of resource adequacy. Majority 8
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of the student performed satisfactorily and very satisfactorily in Mathematics. However, it is also noted there are some who got poor performance. There is a significant relationship between school learning environment and Mathematics performance. The present study has shown how a school learning environment model can be applied to study the effect of learning environment on the performance of students. The school administrators should give due consideration to maintain adequate selection of books and periodical. Likewise, other instructional materials and equipment such as such as videos, tapes, films, recorders, and cassettes to cater for a variety of activities should be purchased. The instructors should consider the elements of school learning environment to enhance and improve the Mathematics performance of students. The school authorities should maintain high positive school environment conducive to teaching and learning processes. The students should learn how to conceptualize based upon the multiperspective approach of the school environment geared towards improvement of their Mathematics performance. REFERENCES Adeyemo, D. A. (2005). Parental Involvement Interest in Schooling and School Environment as predictors of Academic Self-efficacy among fresh Secondary School Student in Oyo State, Nigeria. Electronic Journal of Research in Educational Psychology, 5-3 (1) 163-180. Anderson, G. J. (1970). Effects of Classroom Social Climate on Individual Learning. American Educational Research Journal. Aremu, A.O. & Oluwole, D.A. (2001).Gender and birth order as predictors of normal pupil’s anxiety pattern in examination. Ibadan Journal of Educational Studies, 1, (1), 1-7. Aremu, O. A & Sokan, B. O. (2003). A multi-causal evaluation of academic performance of nigerian learners: issues and implications for national development. Department of Guidance and Counselling, University of Ibadan,
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