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The Interrelationship Among High School Students’ Conceptions of Learning Science, Self-Regulated Learning Science, and Science Learning Self-Efficacy

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Abstract

This research explored the interrelationship among Taiwanese high school students’ conceptions of learning science (COLS), self-regulated learning science (SRLS), and science learning self-efficacy (SLSE). A total of 309 students participated in the study, and the self-report survey data were collected to measure these three constructs. Four COLS factors (Testing, Calculating and practicing, Application, and Understanding and seeing in a new way), two SRLS dimensions (Preparatory SRLS [task definition, goal setting, planning] and Enactment SRLS [controlling, monitoring, reflecting]), and two SLSE factors (Conceptual understanding and Higher-order cognitive skills), which adhere to the cognitive learning dimensions, were included for analysis. The results revealed a direct relationship between Testing and SLSE without going through any of the SRLS constructs. However, no direct relationship was built among other COLS components and the two SLSE dimensions. There are direct relationships among Calculating and practicing, Application, and the two SRLS constructs, but Understanding and seeing in a new way solely links to Enactment SRLS and not to Preparatory SRLS. In the end, the two SRLS constructs are directly associated with the students’ SLSE dimensions. These results have the important implication that learners’ COLS have a significant impact on their SRL engagement, which eventually leads to their beliefs about their cognitive abilities in learning the abstract concepts and critical thinking tasks in science.

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References

  • Ardura, D., & Galán, A. (2019). The interplay of learning approaches and self-efficacy in secondary school students’ academic achievement in science. International Journal of Science Education, 41, 1723–1743.

    Article  Google Scholar 

  • Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.

    Google Scholar 

  • Berkhout, J. J., Helmich, E., Teunissen, P. W., van den Berg, J. W., van der Vleuten, C. P. M., & Jaarsma, A. D. C. (2015). Exploring the factors influencing clinical students’ self-regulated learning. Medical Education, 49, 589–600.

    Article  Google Scholar 

  • Berkhout, J. J., Helmich, E., Teunissen, P. W., van der Vleuten, C. P. M., & Jaarsma, A. D. C. (2018). Context matters when striving to promote active and lifelong learning in medical education. Medical Education, 52, 34–44.

    Article  Google Scholar 

  • Biggs, J. (1987). Student approaches to learning and studying. Australian Council for Educational Research.

    Google Scholar 

  • Britner, S. L., & Pajares, F. (2006). Sources of science self-efficacy beliefs of middle school students. Journal of Research in Science Teaching, 43(5), 485–499.

    Article  Google Scholar 

  • Butler, D. L., Cartier, S. C., Schnellert, L., Gagnon, F., & Giammarino, M. (2011). Secondary students’ self-regulated engagement in reading: Researching self-regulation as situated in context. Psychological Test and Assessment Modeling, 53, 73–105.

    Google Scholar 

  • Campos, F., Sola, M., Santisteban-Espejo, A., Ruyffelaert, A., Campos-Sánchez, A., Garzón, I., Carriel, V., de Dios Luna-Del-Castillo, J., Martin-Piedra, M. A., & Alaminos, M. (2018). Conceptions of learning factors in postgraduate health sciences master students: A comparative study with nonhealth science students and between genders. BMC Medical Education, 18(128), 1–8.

    Google Scholar 

  • Cao, L., & Nietfeld, J. L. (2007). College students’ metacognitive awareness of difficulties in learning the class content does not automatically lead to adjustment of study strategies. Australian Journal of Educational and Developmental Psychology, 7, 31–46.

    Google Scholar 

  • Cera, R., Mancini, M., & Antonietti, A. (2013). Relationships between metacognition, self-efficacy, and self-regulation in learning. ECPS Journal, 7, 115–141.

    Article  Google Scholar 

  • Chiu, Y. L., Liang, J. C., & Tsai, C. C. (2013). Internet-specific epistemic beliefs and self-regulated learning in online academic information searching. Metacognition Learning, 8, 235–260.

  • Cleary, T. J., & Kitsantas, A. (2017). Motivation and self-regulated learning influences on middle school mathematics achievement. School Psychology Review, 46(1), 88–107.

    Article  Google Scholar 

  • Cleary, T. J., Verladi, B., & Schnaidman, B. (2017). Effects of the self-regulation empowerment program (SREP) on middle school students’ strategic skills, self-efficacy, and mathematics achievement. Journal of School Psychology, 64, 28–42.

    Article  Google Scholar 

  • DiBenedetto, M. K., & Bembenutty, H. (2013). Within the pipeline: Self-regulated learning, self-efficacy, and socialization among college students in science courses. Learning and Individual Differences, 23, 218–224.

  • Entwistle, N. J., & Peterson, E. R. (2004). Conceptions of learning and knowledge in higher education: Relationships with study behavior and influences of learning environments. International Journal of Educational Research, 41(6), 407–428.

    Article  Google Scholar 

  • Fadlelmula, F. K., Cakiroglu, E., & Sungur, S. (2015). Developing a structural model on the relationship among motivational beliefs, self-regulated learning strategies, and achievement in mathematics. International Journal of Science and Mathematics Education, 13, 1355–1375.

    Article  Google Scholar 

  • Ferla, J., Valcke, M., & Schuyten, G. (2008). Relationships between student cognitions and their effects on study strategies. Learning and Individual Differences, 18, 271–278.

    Article  Google Scholar 

  • Geitz, G., Brinke, D. J.-T., & Kirschner, P. A. (2016). Changing learning behavior: Self-efficacy and goal orientation in PBL groups in higher education. International Journal of Educational Research, 75, 146–158.

    Article  Google Scholar 

  • Gutiérrez-Braojos, C. (2015). Future time orientation and learning conceptions: Effects on metacognitive strategies, self-efficacy beliefs, study effort and academic achievement. Educational Psychology, 35(2), 192–212.

    Article  Google Scholar 

  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. Prentice Hall.

    Google Scholar 

  • Honicke, T., & Broadbent, J. (2016). The influence of academic self-efficacy on academic performance: A systematic review. Educational Research Review, 17, 63–84.

    Article  Google Scholar 

  • Huang, Y. S., & Asghar, A. (2018). Science education reform in Confucian learning cultures: Teachers’ perspectives on policy and practice in Taiwan. Cultural Studies of Science Education, 13, 101–131.

    Article  Google Scholar 

  • Kirbulut, Z. D., & Uzuntiryaki-Kondakci, E. (2019). Examining the mediating effect of science self-efficacy on the relationship between metavariables and science achievement. International Journal of Science Education, 41(8), 995–1014.

    Article  Google Scholar 

  • Kirschner, P. A., & Hendrick, C. (2020). How learning happens: Seminal works in educational psychology and what they mean in practice. Routledge.

    Book  Google Scholar 

  • Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 46(2), 75–86.

    Article  Google Scholar 

  • Komarraju, M., & Nadler, D. (2013). Self-efficacy and academic achievement: Why do implicit beliefs, goals, and effort regulation matter? Learning and Individual Differences, 25, 67–72.

    Article  Google Scholar 

  • Lai, C. L., Hwang, G. J., & Tu, Y. H. (2018). The effects of computer-supported self-regulation in science inquiry on learning outcomes, learning processes, and self-efficacy. Educational Technology Research & Development, 66, 863–892.

    Article  Google Scholar 

  • Lee, M.-H., Johanson, R. E., & Tsai, C. C. (2008). Exploring Taiwanese high school students’ conceptions of and approaches to learning science through a structural equation modeling analysis. Science Education, 92, 191–220.

  • Li, J. (2003). U.S. and Chinese cultural beliefs about learning. Journal of Educational Psychology, 95, 258–267.

    Article  Google Scholar 

  • Li, S., Du, H., Xing, W., Zhang, J., Chen, G., & Xie, C. (2020). Examining temporal dynamics of self-regulated learning behaviors in STEM learning: A network approach. Computers & Education, 158, 103987.

    Article  Google Scholar 

  • Lin, T.-J., & Tsai, C.-C. (2013a). A multi-dimensional instrument for evaluating Taiwan high school students’ learning self-efficacy in relation to their approaches to learning science. International Journal of Science and Mathematics Education, 11, 1275–1301.

  • Lin, T.-J., & Tsai, C.-C. (2013b). An investigation of Taiwanese high school students’ science learning self-efficacy in relation to their conceptions of learning science. Research in Science and Technological Education, 31(3), 308–323.

  • Lin, T.-J., Liang, J.-C., & Tsai, C.-C. (2015). Identifying Taiwanese university students’ physics learning profiles and their role in physics learning self-efficacy. Research in Science Education, 45, 605 –624.

  • Lonka, K., Ketonen, E., & Vermunt, J. D. (2020). University students’ epistemic profiles, conceptions of learning, and academic performance. Higher Education, 81, 775–793. https://doi.org/10.1007/s10734-020-00575-6.

    Article  Google Scholar 

  • Loyens, S. M. M., Rikers, R. M. J. P., & Schmidt, H. G. (2008). Relationships between students’ conceptions of constructivist learning and their regulation and processing strategies. Instructional Science, 36, 445–462.

    Article  Google Scholar 

  • Lynch, D. J., & Trujillo, H. (2011). Motivational beliefs and learning strategies in organic chemistry. International Journal of Science and Mathematics Education, 9, 1351–1365.

    Article  Google Scholar 

  • Marton, F., Dall’Alba, G., & Beaty, E. (1993). Conceptions of learning. International Journal of Educational Research, 19, 277–299.

    Google Scholar 

  • Marton, F., Watkins, D., & Tang, C. (1997). Discontinuities and continuities in the experience of learning: An interview study of high-school students in Hong Kong. Learning and Instruction, 7, 21–48.

    Article  Google Scholar 

  • Mascardo, M. J. C., Lasala, P. B. S., & Lazarte, R. F. A. (2020). Senior high school students’ conceptions of learning biology in relation to self-regulated learning strategies: Their impact on students’ academic performance. International Journal of Innovative Science & Research Technology, 5(8), 514–520.

    Google Scholar 

  • Ministry of Education. (1998). General Guidelines of Grades 1-9 Curriculum for Elementary and Junior High School Education. Taipei, Taiwan.

  • Moos, D. C., & Azevedo, R. (2009). Self-efficacy and prior domain knowledge: To what extent does monitoring mediate their relationship with hypermedia learning? Metacognition and Learning, 4, 197–216.

    Article  Google Scholar 

  • Müller, N. M., & Seufert, T. (2018). Effects of self-regulation prompts in hypermedia learning on learning performance and self-efficacy. Learning and Instruction, 58, 1–11.

    Article  Google Scholar 

  • Neber, H., He, J., Liu, B.-X., & Schofield, N. (2008). Chinese high-school students in physics classroom as active self-regulated learners: Cognitive, motivational, and environmental aspects. International Journal of Science and Mathematics Education, 6, 769–788.

    Article  Google Scholar 

  • Nieminen, J. H., Asikainen, H., & Rämö, J. (2019). Promoting deep approach to learning and self-efficacy by changing the purpose of self-assessment: A comparison of summative and formative models. Studies in Higher Education, 46, 1296–1311. https://doi.org/10.1080/03075079.2019.1688282.

    Article  Google Scholar 

  • Pamuk, S., Sungur, S., & Oztekin, C. (2017). A multilevel analysis of students’ science achievements in relation to their self-regulation, epistemological beliefs, learning environment perceptions, and teachers’ personal characteristics. International Journal of Science and Mathematics Education, 15, 1423–1440.

    Article  Google Scholar 

  • Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, 422. https://doi.org/10.3389/fpsyg.2017.00422.

    Article  Google Scholar 

  • Panadero, E., Jonsson, A., & Botella, J. (2017). Effects of self-assessment on self-regulated learning and self-efficacy: Four meta-analyses. Educational Research Review, 22, 74–98.

    Article  Google Scholar 

  • Peterson, E. R., Brown, G. T. L., & Irving, S. E. (2010). Secondary school students’ conceptions of learning and their relationship to achievement. Learning and Individual Differences, 20, 167–176.

    Article  Google Scholar 

  • Phan, H. P. (2011). Interrelations between self-efficacy and learning approaches: A developmental approach. Educational Psychology, 31(2), 225–246.

    Article  Google Scholar 

  • Pinto, G., Bigozzi, L., Vettori, G., & Vezzani, C. (2018). The relationship between conceptions of learning and academic outcomes in middle school students according to gender differences. Learning, Culture and Social Interaction, 16, 45–54.

    Article  Google Scholar 

  • Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31, 459–470.

    Article  Google Scholar 

  • Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). Academic Press.

    Chapter  Google Scholar 

  • Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 385–407.

    Article  Google Scholar 

  • Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research and application (2nd ed.). Merrill Prentice Hall.

    Google Scholar 

  • Purdie, N., Hattie, J., & Douglas, G. (1996). Student conceptions of learning and their use of self-regulated learning strategies: A cross-cultural comparison. Journal of Educational Psychology, 88, 87–100.

    Article  Google Scholar 

  • Ramnarain, U., & Ramaila, S. (2018). The relationship between chemistry self-efficacy of South African first year university students and their academic performance. Chemistry Education Research and Practice, 19(1), 60–67.

    Article  Google Scholar 

  • Roick, J., & Ringeisen, T. (2018). Students’ math performance in higher education: Examining the role of self-regulated learning and self-efficacy. Learning and Individual Differences, 65, 148–158.

    Article  Google Scholar 

  • Sadi, O. (2017). Relational analysis of high school students’ cognitive self-regulated strategies and conceptions of learning biology. EURASIA Journal of Mathematics Science & Technology Education, 13(6), 1701–1722.

    Article  Google Scholar 

  • Säljö, R. (1979). Learning about learning. Higher Education, 8, 443–451.

    Article  Google Scholar 

  • Schmitz, B., & Wiese, B. S. (2006). New perspectives for the evaluation of training sessions in self-regulated learning: Time-series analyses of diary data. Contemporary Educational Psychology, 31, 64–96.

    Article  Google Scholar 

  • Schraw, G. (2000). Assessing metacognition: Implications of the Buros Symposium. In G. Schraw & J. C. Impara (Eds.), Issues in the measurement of metacognition (pp. 297–321). Buros Institute of Mental Measurements.

  • Schunk, D. H. (2005). Self-regulated learning: The educational legacy of Paul R. Pintrich. Educational Psychologist, 40(2), 85–94.

    Article  Google Scholar 

  • Senko, C., Hulleman, C. S., & Harackiewicz, J. M. (2011). Achievement goal theory at the crossroads: Old controversies, current challenges, and new directions. Educational Psychologist, 46(1), 26–47.

    Article  Google Scholar 

  • Sezgintürk, M., & Sungur, S. (2020). A multidimensional investigation of students’ science self-efficacy: The role of gender. Elementary Education Online, 19(1), 208–218.

    Google Scholar 

  • Shin, S., Lee, J. K., & Ha, M. (2017). Influence of career motivation on science learning in Korean high school students. EURASIA Journal of Mathematics Science & Technology Education, 13(5), 1517–1538.

    Google Scholar 

  • Taub, M., Azevedo, R., Bouchet, F., & Khosravifar, B. (2014). Can the use of cognitive and metacognitive self-regulated learning strategies be predicted by learners’ levels of prior knowledge in hyper-media learning environment? Computers in Human Behavior, 39, 356–367.

    Article  Google Scholar 

  • Tavakol, M., & Dennick, R. (2010). Are Asian international medical students just rote learners? Advances in Health Sciences Education, 15(3), 369–377.

    Article  Google Scholar 

  • Trigwell, K., Ashwin, P., & Millan, E. S. (2013). Evoked prior learning experience and approach to learning as predictors of academic achievement. British Journal of Educational Psychology, 83, 363–378.

    Article  Google Scholar 

  • Tsai, C.-C. (2004). Conceptions of learning science among high school students in Taiwan: A phenomenographic analysis. International Journal of Science Education, 26, 1733–1750.

  • Umapathy, K., Ritzhaupt, A. D., & Xu, C. (2019). College students’ conceptions of learning of and approaches to learning computer science. Journal of Educational Computing Research, 58(3), 662–686.

    Article  Google Scholar 

  • Uzuntiryaki, E., & Capa Aydin, Y. (2009). Development and validation of chemistry self-efficacy scale for college student. Research in Science Education, 39, 539–551.

    Article  Google Scholar 

  • Vermunt, J. D. (1998). The regulation of constructive learning processes. British Journal of Educational Psychology, 68, 149–171.

    Article  Google Scholar 

  • Vermunt, J. D. (2005). Relations between student learning patterns and personal and contextual factors and academic performance. Higher Education, 49, 205–234.

    Article  Google Scholar 

  • Vermunt, J. D., & Donche, V. (2017). A learning patterns perspective on student learning in higher education: State of the art and moving forward. Educational Psychology Review, 29, 269–299.

    Article  Google Scholar 

  • Vettori, G., Vezzani, C., Bigozzi, L., & Pinto, G. (2018). The mediating role of conceptions of learning in the relationship between metacognitive skills/strategies and academic outcomes among middle-school students. Frontiers in Psychology, 9, 1985. https://doi.org/10.3389/fpsyg.2018.01985.

    Article  Google Scholar 

  • Vezzani, C., Vettori, G., & Pinto, G. (2018). University students’ conceptions of learning across multiple domains. European Journal of Educational Psychology, 33, 665–684.

    Article  Google Scholar 

  • Vogel, F. R., & Human-Vogel, S. (2016). Academic commitment and self-efficacy as predictors of academic achievement in additional materials science. Higher Education Research and Development, 35(6), 1298–1310.

    Article  Google Scholar 

  • Wang, Y. L., Liang, J. C., & Tsai, C. C. (2018). Cross-cultural comparisons of university students’ science learning self-efficacy: structural relationships among factors within science learning self-efficacy. International Journal of Science Education, 40(6), 579–594.

  • William, D. (2011). Embedded formative assessment. Solution Tree Press.

    Google Scholar 

  • Winnie, P. H. (2019). Paradigmatic dimensions of instrumentation and analytic methods in research on self-regulated learning. Computers in Human Behavior, 96, 285–289.

    Article  Google Scholar 

  • Yang, T. C., Chen, M. C., & Chen, S. Y. (2018). The influences of self-regulated learning support and prior knowledge on improving learning performance. Computers & Education, 126, 37–52.

    Article  Google Scholar 

  • Yerdelen, S., & Sungur, S. (2019). Multilevel investigation of students’ self-regulation processes in learning science: Classroom learning environment and teacher effectiveness. International Journal of Science and Mathematics Education, 17, 89–110.

    Article  Google Scholar 

  • Zheng, L., Dong, Y., Huang, R., Chang, C.-Y., & Bhagat, K. K. (2018). Investigating the interrelationships among conceptions of, approaches to, and self-efficacy in learning science. International Journal of Science Education, 40(2), 139–158.

    Article  Google Scholar 

  • Zimmerman, B. J. (2002). Becoming a self-regulated learner. Theory Into Practice, 41(2), 64–70.

    Article  Google Scholar 

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Acknowledgements

This study is supported in part by the Ministry of Science and Technology of Taiwan under contract numbers MOST 109-2511-H-003-014-MY3 and MOST 108-2511-H-003-004-MY3. This work was financially supported by the “Institute for Research Excellence in Learning Sciences” of National Taiwan Normal University (NTNU) from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.

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Ho, H.N.J., Liang, JC. & Tsai, CC. The Interrelationship Among High School Students’ Conceptions of Learning Science, Self-Regulated Learning Science, and Science Learning Self-Efficacy. Int J of Sci and Math Educ 20, 943–962 (2022). https://doi.org/10.1007/s10763-021-10205-x

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