The Impact of Motivation and Learning Strategies as Predictors of Biology Performance among Non- Science Majors
Main Article Content
Keywords
predictors, performance, motivation, learning strategies, Biology
Abstract
Science Education has improved the quality of life, developed competitiveness, and helped understand global issues. Thus, the present study identified the impact of motivation and learning strategies in Biology among non- science majors. The respondents chosen through simple random sampling for this study were the 83 Information Technology students taking Biology. The study used the descriptive method of research using Biology Motivation Questionnaire (Glynn and Koballa, 2005) and Motivated Strategies for Learning Questionnaire (Pintrich et al., 1991). These instruments were administered thrice: at the start of classes, and a week before the midterm and the final examinations. The data gathered were tabulated and analyzed. The student's midterm exam scores in biology were used as measures of achievement. The statistical tools employed were mean, standard deviation, ANOVA and regression analysis. Results showed that non- Science majors have high motivation level. Among the sub- components: intrinsic, and extrinsic motivation, personal relevance and self- determination have very high contribution to the level of motivation especially to the high performers. The results further revealed that all the respondents have the low assessment anxiety in Biology. For the learning strategies used, high performers often used organization, metacognitive selfregulation skills, rehearsal and elaboration while low performers seldom used the given strategies. Average performers often used these strategies including critical thinking. The level of motivation is significantly different among the different course performers. Among the learning strategies, there is a significant difference in the use of organization, metacognitive self- regulation skills and rehearsal. Furthermore, the extrinsic and intrinsic motivation, personal relevance and self-determination are significant predictors of better performance in Biology. In conclusion, the level of motivation and learning strategies used can predict the level of Biology performance of non-science majors.
References
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Yu, S. L. (1999). Women's motivation and strategy use in college science classes. Journal of Staff, Program, & Organization Development, 16, 93-101.
Zusho et al., (2003). Skill and will: The role of motivation and cognition in the learning of college chemistry. International Journal of Science Education, 25, 1081-1094.
Bleicher, R. E., Romance, N., & Haky, J. (2002). Curriculum by design: Improving student learning in college chemistry and biology. Proceedings of the Annual International Conference of the Association for the Education of Teachers in Science: Charlotte, NC.
Britner, S. L., & Pajares, P. (2006). Sources of science self-efficacy beliefs of middle school students. Journal of Research in Science Teaching, 43, 485-499.
Corno, L. & Randi, J. (1999). A design theory for classroom instruction in self-regulated learning? In C. M. Reigeluth (Ed.), Instructional theories in action: Lessons illustrating selected theories and models. (pp. 293-318). Mahwah, New Jersey: Lawrence Erlbaum Associates.
Covington, M. V. (2000). Intrinsic versus extrinsic motivation in schools: reconciliation. American Psychological Society, 9(1), 22-25. Eccles, J. S. & Wigfield, A. (2002). Motivational beliefs, values, and goals. Ann Arbor, Michigan: Institute for Social Research, University of Michigan.
Fraenkel J. R., Wallen, E. N., Hyun, H. E. (2012). How to design and evaluate research in education, eighth ed. New York: McGraw- Hill Companies.
Glynn, S. M. & Koballa, T. R., Jr. (2005). Science Motivation Questionnaire. Handbook of college science teaching. Arlington, VA: National Science Teachers Association Press.
Ibe, M. D. & Ogena, E. B. (1998). Science education in the Philippines: An overview. Manila: Department of Science and Technology.
Lublin, J. (2003) Deep surface and strategic approaches to learning Contributor: Centre for Teaching and Learning. Good Practice in Teaching and Learning retrieved from http://www2.warwick.ac.uk/services/ldc/development/pga/introtandl/resources/2a_deep_
surfacestrategic_approaches_to_learning.pdf.
Miyake, A., Kost-Smith, L. E., Finkelstein, N. D., Pollock, S. J., Cohen, G. L., & Ito, T. A. (2010). Reducing the gender achievement gap in college science: A classroom study of values affirmation. Science, 330, 1234-1237.
Movahedzadeh, F. (2011). Improving students' attitude toward science through blended learning science education and civic engagement. Chicago, Illinois: Harold Washington College.
Murphy, P. K., & Alexander, P. A. (2000). A motivated explorations of motivation terminology.Contemporary Educational Psychology 25(3), 3-53.
Obrentz, S. B., (2012). Predictors of Science Success: The Impact of Motivation and Learning Strategies on College Chemistry Performance. Dissertation, Georgia State University.
Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). The Motivated Strategies for Learning Questionnaire. Ann Arbor, Michigan: National Center for Research to Improve Post Secondary Teaching and Learning.
Rogers, W.D., and R. Ford. 1997. “Factors that Affect Student Attitude Toward Biology.” Bioscene: Journal of College Biology Teaching 23(2), 3–6.
Schunk, D. (2012). Learning theories: An educational perspective VI edition. Boston, MA:Pearson Education Inc. Singh, K., Granville, M., & Dika, S. (2002). Mathematics and science achievement: Effects of motivation, interest, and academic engagement. The Journal of Educational Research, 95, 323-332.
Taasoobshirazi, G., & Glynn, S. M. (2009). College students solving chemistry problems: A theoretical model of expertise. Journal of Research in Science Teaching, 46, 1070-1089.
Walker et al., (2006). Identification with academics, intrinsic/extrinsic motivation, and self-efficacy as predictors of cognitive engagement. Learning and Individual Differences, 16, 1-12.
Yu, S. L. (1999). Women's motivation and strategy use in college science classes. Journal of Staff, Program, & Organization Development, 16, 93-101.
Zusho et al., (2003). Skill and will: The role of motivation and cognition in the learning of college chemistry. International Journal of Science Education, 25, 1081-1094.
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Published
Dec 20, 2016
Article Details
How to Cite
Nacionales, E. N., Muyong, Jr., P. M., & Gavasan, J. C. (2016). The Impact of Motivation and Learning Strategies as Predictors of Biology Performance among Non- Science Majors. Asia Pacific Higher Education Research Journal (APHERJ), 3(2). https://doi.org/10.56278/apherj.v3i2.282
Section
Research Article