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The Development of a Questionnaire for Assessing Students' Learning Motivation toward Mathematics (QSLMM)

Yıl 2025, Cilt: 12 Sayı: 4, 108 - 121, 06.01.2026
https://doi.org/10.17278/ijesim.1687705

Öz

Learners with motivation are more likely to construct knowledge actively and strive towards their goals continuously. Therefore, this study aims to develop a Mathematics Learning Motivation Questionnaire to provide a reference for mathematics teachers. After the literature review, this study categorises the factors influencing students' learning motivation into five main categories: learning environment, test anxiety, intrinsic value, self-efficacy, and self-regulation. After the pre-test data were analysed and tested for reliability and validity, the contents of QSLMM were 30 items whilst 7 items for “learning environment stimulation”, 6 items for “test anxiety”, 4 items for “intrinsic value”, 7 items for “self-efficacy”, and 4 items for “self-regulation”, and 2 reverse coded items as test items. The Cronbach’s α coefficient of the total scale was .977, and Cronbach’s coefficients of the five subscales were .938, .913, .850, .899, and .810, respectively. At the same time, the values of the RMR, RMSEA, GFI, AGFI, CFI, NFI, NNFI and IFI were .035, .055, .917, .901, .936, .928, .929 and .936, respectively. All data meets the test standards. In the cross-validation analysis part, the result of measurement invariance was not significant in Δχ2 of residual analysis. Both △CFI and △TLI are less than the standard of .05. The results of the study showed that the questionnaire possesses good reliability and validity. Hence the QSLMM could effectively assess students’ learning motivation toward mathematics for teachers’ reference for teaching mathematics.

Kaynakça

  • Adesola, S. A., & Li, Y. (2018). The relationship between self-regulation, self-efficacy, test anxiety and motivation. International Journal of Information and Education Technology, 8(10), 759-763.
  • Alzubaidi, E., Aldridge, J. M., & Khine, M. S. (2016). Learning English as a second language at the university level in Jordan: Motivation, self-regulation and learning environment perceptions. Learning Environments Research, 19(1), 133-152.
  • Bandura, A. (1990). Perceived self-efficacy in the exercise of personal agency. Journal of Applied Sport Psychology, 2(2), 128-163.
  • Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71-81). Academic Press.
  • Blumenfeld, P. C., Kempler, T. M., & Krajcik, J. S. (2006). Motivation and cognitive engagement in learning environments. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 475–488). Cambridge University Press.
  • Borasi, R. (1994). Capitalizing on errors as "springboards for inquiry": A teaching experiment. Journal for Research in Mathematics Education, 25(2), 166-208.
  • Brophy, J. E. (2013). Motivating students to learn. Taylor & Francis.
  • Brown, T., & Morrissey, L. (2004). The effectiveness of verbal self-guidance as a transfer of training intervention: Its impact on presentation performance, self-efficacy and anxiety. Innovations in Education and Teaching International, 41(3), 255–271.
  • Cook, D. A., & Artino Jr, A. R. (2016). Motivation to learn: an overview of contemporary theories. Medical education, 50(10), 997-1014.
  • Covington, M. V. (2000). Goal theory, motivation, and school achievement: An integrative review. Annual Review of Psychology, 51, 171-200.
  • Covington, M. V., & Müeller, K. J. (2001). Intrinsic versus extrinsic motivation: An approach/avoidance reformulation. Educational Psychology Review, 13(2), 157-176.
  • DeVellis, R. F. (1991). Scale development. Sage.
  • Dörnyei, Z., & Ushioda, E. (2013). Teaching and researching: Motivation. Routledge.
  • El-Adl, A. & Alkharusi, H. (2020). Relationships between self-regulated learning strategies, learning motivation and mathematics achievement. Cypriot Journal of Educational Sciences, 15(1), 104-111.
  • Fan, W., & Williams, C. M. (2010). The effects of parental involvement on students’ academic self‐efficacy, engagement and intrinsic motivation. Educational Psychology, 30(1), 53-74.
  • Fekumo, B. & Omeka, F. O. (2022). Influence of students’ perception of mathematics on junior secondary school students’ academic performance in Yala local government area of Cross River State, Nigeria. VillageMath Educational Review (VER), 3(1), 53-71.
  • Fraser, B. J. (2002). Learning environments research: Yesterday, today and tomorrow. In S. W. Goh and M. S. Khine (Eds.), Studies in educational learning environments: An international perspective (pp. 1-25). World Scientific.
  • Garcia, T., & Pintrich, P.R. (1996). Assessing students’ motivation and learning strategies in the classroom context: The motivated strategies for learning questionnaire. In M. Birenbaum & F.J.R.C. Dochy (Eds.), Alternatives in assessment of achievements, learning processes and prior knowledge (pp. 319-339). Springer.
  • Gottfried, A. E., Marcoulides, G. A., Gottfried, A. W., Oliver, P. H., & Guerin, D. W. (2007). Multivariate latent change modeling of developmental decline in academic intrinsic math motivation and achievement: Childhood through adolescence. International Journal of Behavioral Development, 31(4), 317-327.
  • Hanrahan, M. (1998). The effect of learning environment factors on students’ motivation and learning. International Journal of Science Education, 20(6), 737-753.
  • Hirst, G., van Knippenberg, D., Chen, C. H., & Sacramento, C. A. (2011). How does bureaucracy impact individual creativity? A cross-level investigation of team contextual influences on goal orientation–creativity relationships. Academy of Management Journal, 54(3), 624-641.
  • Hoorfar, H., & Taleb, Z. (2015). Correlation between mathematics anxiety with metacognitive knowledge. Procedia-Social and Behavioral Sciences, 182, 737-741.
  • Irvine, J. (2018). A framework for comparing theories related to motivation in education. Research in Higher Education Journal, 35, 1-30.
  • Jarrett, D. (1997). Inquiry strategies for science and mathematics learning: It’s just good teaching. Northwest Regional Educational Laboratory.
  • Kubravi, S. U., Shah, S. O., & Jan, K. (2018). Digital story telling the impact on student academic achievement, critical thinking and learning motivation. International Journal of Research in Engineering, Science and Management, 1(12), 787-791.
  • Lavasani, M. G., Mirhosseini, F. S., Hejazi, E., & Davoodi, M. (2011). The effect of self-regulation learning strategies training on the academic motivation and self-efficacy. Procedia-Social and Behavioral Sciences, 29, 627-632.
  • Li, J. Y., & Shieh, C. J. (2016). A study on the effects of multiple goal orientation on learning motivation and learning behaviors. Eurasia Journal of Mathematics, Science & Technology Education, 12(1), 161-172.
  • Lim, D. H., & Kim, H. (2003). Motivation and learner characteristics affecting online learning and learning application. Journal of Educational Technology Systems, 31(4), 423-439.
  • Lopez-Morteo, G., & López, G. (2007). Computer support for learning mathematics: A learning environment based on recreational learning objects. Computers & Education, 48(4), 618-641.
  • Maddux, J. E. (2016). Self-efficacy. In S. Trusz & P. Bąbel (Eds.), Interpersonal and intrapersonal expectancies (pp. 41-46). Routledge.
  • Maehr, M. L., & Meyer, H. A. (1997). Understanding motivation and schooling: Where we’ve been, where we are, and where we need to go. Educational Psychology Review, 9(4), 371-409.
  • Mamaril, N. A., Usher, E. L., Li, C. R., Economy, D. R., & Kennedy, M. S. (2016). Measuring undergraduate students' engineering self‐efficacy: A validation study. Journal of Engineering Education, 105(2), 366-395.
  • Mega, C., Ronconi, L., & De Beni, R. (2014). What makes a good student? How emotions, self-regulated learning, and motivation contribute to academic achievement. Journal of educational psychology, 106(1), 121.
  • Midgley, C., Maehr, M. L., Hruda, L. Z., Anderman, E., Anderman, L., Freeman, K. E., Gheen, M., Kaplan, A., Kumar, R., Middleton, M. J., Nelson, J., Roeser, R., & Urdan, T. (2000). Manual for the patterns of adaptive learning scales (PALS). University of Michigan.
  • Murayama, K., Matsumoto, M., Izuma, K., & Matsumoto, K. (2010). Neural basis of the undermining effect of monetary reward on intrinsic motivation. Proceedings of the National Academy of Sciences, 107(49), 20911-20916.
  • Nissim, Y., Weissblueth, E., Scott-Webber, L., & Amar, S. (2016). The effect of a stimulating learning environment on pre-service teachers’ motivation and 21st century skills. Journal of Education and Learning, 5(3), 29-39.
  • Olatoye, R. A. (2009). Students’ test anxiety, motivation for examinations and science achievement in junior secondary schools in Ogun State, Nigeria. International Journal of Psychology and Counselling, 1(10), 194-198.
  • Pasco, J. C. (2021). Self-concept, peer pressure, and teaching strategies, and their influence on students’ performance in mathematics: A cross-sectional study. Journal of Education in Black Sea Region, 7(1), 85-104.
  • Peng, S. L., Cherng, B. L., Chen, H. C. & Lin, Y. Y. (2013). A model of contextual and personal motivations in creativity: How do the classroom goal structures influence creativity via self-determination motivations? Thinking Skill and Creativity, 10, 50-67.
  • Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667-686.
  • Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-40.
  • Pintrich, P. R., Marx, R. W. & Boyle, R. A. (1993) Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63, 167-199.
  • Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications (2nd ed.). Prentice Hall.
  • Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). National Center for Research to Improve Postsecondary Teaching and Learning.
  • Prahmana, R. C. I., Sutanti, T., & Diponegoro, A. M. (2021). Mathematics anxiety and the influencing factors among junior high school students in Yogyakarta, Indonesia. Croatian Journal of Education, 23(2), 343-369.
  • Rakes, G. C., & Dunn, K. E. (2010). The impact of online graduate students' motivation and self-regulation on academic procrastination. Journal of Interactive Online Learning, 9(1), 78-93.
  • Schmitz, B., & Perels, F. (2011). Self-monitoring of self-regulation during math homework behaviour using standardized diaries. Metacognition and Learning, 6(3), 255-273.
  • Schunk, D. H. (2012). Learning theories: An educational perspective (6th Ed.). Merrill/Prentice Hall.
  • Schunk, D. H., & DiBenedetto, M. K. (2016). Self-efficacy theory in education. In K. R. Wentzel & D. B. Miele (Eds.), Handbook of motivation at school (2nd Ed., pp. 34-54). Routledge.
  • Schunk, D. H., & DiBenedetto, M. K. (2021). Self-efficacy and human motivation. In Advances in Motivation Science (Vol. 8, pp. 153-179). Elsevier Academic Press.
  • Schunk, D. H., & Greene, J. A. (2017). Handbook of self-regulation of learning and performance. Routledge.
  • Shin, M., & Bolkan, S. (2021). Intellectually stimulating students’ intrinsic motivation: the mediating influence of student engagement, self-efficacy, and student academic support. Communication Education, 70(2), 146-164.
  • Singh, K., Granville, M., & Dika, S. (2002). Mathematics and science achievement: Effects of motivation, interest, and academic engagement. The Journal of Educational Research, 95(6), 323-332.
  • Skaalvik, E. M., Federici, R. A., & Klassen, R. M. (2015). Mathematics achievement and self-efficacy: Relations with motivation for mathematics. International Journal of Educational Research, 72, 129-136.
  • Tambunan, H. (2018). The dominant factor of teacher's role as a motivator of students' interest and motivation in mathematics adchievement. International Education Studies, 11(4), 144-151.
  • Thrash, T. M., & Elliot, A. J. (2001). Delimiting and integrating the goal and motive constructs in achievement motivation. In A. Efklides, J. Huhl, & R. Sorrentino (Eds.), Trends and prospects in motivation research (pp. 3–21). Kluwer Academic.
  • Timmerman, H. L., Toll, S. W. M., & Van Luit, J. E. H. (2017). The relation between math self-concept, test and math anxiety, achievement motivation and math achievement in 12 to 14-year-old typically developing adolescents. Psychology, Society, & Education, 9(1), 89-103.
  • Torres, J., & Alieto, E. (2019). English learning motivation and self-efficacy of Filipino senior high school students. Asian EFL Journal, 22(1), 51-72.
  • Tuan, H.L., Chin, C.C. & Shieh, S.H. (2005). The development of a questionnaire for assessing students’ motivation toward science learning. International Journal of Science Education, 27(6), 639-654.
  • van Ginkel, S., Gulikers, J., Biemans, H., & Mulder, M. (2015). Towards a set of design principles for developing oral presentation competence: A synthesis of research in higher education. Educational Research Review, 14, 62-80.
  • Wæge (2009, January). Motivation for learning mathematics in terms of needs and goals. In F. Arzarello (Chair), Proceedings of the 6th Congress of the European Society for Research in Mathematics Education. Symposium conducted at the meeting of the University of Lyon, Lyon, France.
  • Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68-81.
  • Wolters, C. A., Pintrich, P. R., & Karabenick, S. A. (2005). Assessing academic self-regulated learning. In K. A. Moore & L. H. Lippman (Eds.), What do children need to flourish? (pp. 251-270). Springer.
  • Yang, Y. T. C., & Wu, W. C. I. (2012). Digital storytelling for enhancing student academic achievement, critical thinking, and learning motivation: A year-long experimental study. Computers & Education, 59(2), 339-352.

The Development of a Questionnaire for Assessing Students' Learning Motivation toward Mathematics (QSLMM)

Yıl 2025, Cilt: 12 Sayı: 4, 108 - 121, 06.01.2026
https://doi.org/10.17278/ijesim.1687705

Öz

Learners with motivation are more likely to construct knowledge actively and strive towards their goals continuously. Therefore, this study aims to develop a Mathematics Learning Motivation Questionnaire to provide a reference for mathematics teachers. After the literature review, this study categorises the factors influencing students' learning motivation into five main categories: learning environment, test anxiety, intrinsic value, self-efficacy, and self-regulation. After the pre-test data were analysed and tested for reliability and validity, the contents of QSLMM were 30 items whilst 7 items for “learning environment stimulation”, 6 items for “test anxiety”, 4 items for “intrinsic value”, 7 items for “self-efficacy”, and 4 items for “self-regulation”, and 2 reverse coded items as test items. The Cronbach’s α coefficient of the total scale was .977, and Cronbach’s coefficients of the five subscales were .938, .913, .850, .899, and .810, respectively. At the same time, the values of the RMR, RMSEA, GFI, AGFI, CFI, NFI, NNFI and IFI were .035, .055, .917, .901, .936, .928, .929 and .936, respectively. All data meets the test standards. In the cross-validation analysis part, the result of measurement invariance was not significant in Δχ2 of residual analysis. Both △CFI and △TLI are less than the standard of .05. The results of the study showed that the questionnaire possesses good reliability and validity. Hence the QSLMM could effectively assess students’ learning motivation toward mathematics for teachers’ reference for teaching mathematics.

Kaynakça

  • Adesola, S. A., & Li, Y. (2018). The relationship between self-regulation, self-efficacy, test anxiety and motivation. International Journal of Information and Education Technology, 8(10), 759-763.
  • Alzubaidi, E., Aldridge, J. M., & Khine, M. S. (2016). Learning English as a second language at the university level in Jordan: Motivation, self-regulation and learning environment perceptions. Learning Environments Research, 19(1), 133-152.
  • Bandura, A. (1990). Perceived self-efficacy in the exercise of personal agency. Journal of Applied Sport Psychology, 2(2), 128-163.
  • Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71-81). Academic Press.
  • Blumenfeld, P. C., Kempler, T. M., & Krajcik, J. S. (2006). Motivation and cognitive engagement in learning environments. In R. K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 475–488). Cambridge University Press.
  • Borasi, R. (1994). Capitalizing on errors as "springboards for inquiry": A teaching experiment. Journal for Research in Mathematics Education, 25(2), 166-208.
  • Brophy, J. E. (2013). Motivating students to learn. Taylor & Francis.
  • Brown, T., & Morrissey, L. (2004). The effectiveness of verbal self-guidance as a transfer of training intervention: Its impact on presentation performance, self-efficacy and anxiety. Innovations in Education and Teaching International, 41(3), 255–271.
  • Cook, D. A., & Artino Jr, A. R. (2016). Motivation to learn: an overview of contemporary theories. Medical education, 50(10), 997-1014.
  • Covington, M. V. (2000). Goal theory, motivation, and school achievement: An integrative review. Annual Review of Psychology, 51, 171-200.
  • Covington, M. V., & Müeller, K. J. (2001). Intrinsic versus extrinsic motivation: An approach/avoidance reformulation. Educational Psychology Review, 13(2), 157-176.
  • DeVellis, R. F. (1991). Scale development. Sage.
  • Dörnyei, Z., & Ushioda, E. (2013). Teaching and researching: Motivation. Routledge.
  • El-Adl, A. & Alkharusi, H. (2020). Relationships between self-regulated learning strategies, learning motivation and mathematics achievement. Cypriot Journal of Educational Sciences, 15(1), 104-111.
  • Fan, W., & Williams, C. M. (2010). The effects of parental involvement on students’ academic self‐efficacy, engagement and intrinsic motivation. Educational Psychology, 30(1), 53-74.
  • Fekumo, B. & Omeka, F. O. (2022). Influence of students’ perception of mathematics on junior secondary school students’ academic performance in Yala local government area of Cross River State, Nigeria. VillageMath Educational Review (VER), 3(1), 53-71.
  • Fraser, B. J. (2002). Learning environments research: Yesterday, today and tomorrow. In S. W. Goh and M. S. Khine (Eds.), Studies in educational learning environments: An international perspective (pp. 1-25). World Scientific.
  • Garcia, T., & Pintrich, P.R. (1996). Assessing students’ motivation and learning strategies in the classroom context: The motivated strategies for learning questionnaire. In M. Birenbaum & F.J.R.C. Dochy (Eds.), Alternatives in assessment of achievements, learning processes and prior knowledge (pp. 319-339). Springer.
  • Gottfried, A. E., Marcoulides, G. A., Gottfried, A. W., Oliver, P. H., & Guerin, D. W. (2007). Multivariate latent change modeling of developmental decline in academic intrinsic math motivation and achievement: Childhood through adolescence. International Journal of Behavioral Development, 31(4), 317-327.
  • Hanrahan, M. (1998). The effect of learning environment factors on students’ motivation and learning. International Journal of Science Education, 20(6), 737-753.
  • Hirst, G., van Knippenberg, D., Chen, C. H., & Sacramento, C. A. (2011). How does bureaucracy impact individual creativity? A cross-level investigation of team contextual influences on goal orientation–creativity relationships. Academy of Management Journal, 54(3), 624-641.
  • Hoorfar, H., & Taleb, Z. (2015). Correlation between mathematics anxiety with metacognitive knowledge. Procedia-Social and Behavioral Sciences, 182, 737-741.
  • Irvine, J. (2018). A framework for comparing theories related to motivation in education. Research in Higher Education Journal, 35, 1-30.
  • Jarrett, D. (1997). Inquiry strategies for science and mathematics learning: It’s just good teaching. Northwest Regional Educational Laboratory.
  • Kubravi, S. U., Shah, S. O., & Jan, K. (2018). Digital story telling the impact on student academic achievement, critical thinking and learning motivation. International Journal of Research in Engineering, Science and Management, 1(12), 787-791.
  • Lavasani, M. G., Mirhosseini, F. S., Hejazi, E., & Davoodi, M. (2011). The effect of self-regulation learning strategies training on the academic motivation and self-efficacy. Procedia-Social and Behavioral Sciences, 29, 627-632.
  • Li, J. Y., & Shieh, C. J. (2016). A study on the effects of multiple goal orientation on learning motivation and learning behaviors. Eurasia Journal of Mathematics, Science & Technology Education, 12(1), 161-172.
  • Lim, D. H., & Kim, H. (2003). Motivation and learner characteristics affecting online learning and learning application. Journal of Educational Technology Systems, 31(4), 423-439.
  • Lopez-Morteo, G., & López, G. (2007). Computer support for learning mathematics: A learning environment based on recreational learning objects. Computers & Education, 48(4), 618-641.
  • Maddux, J. E. (2016). Self-efficacy. In S. Trusz & P. Bąbel (Eds.), Interpersonal and intrapersonal expectancies (pp. 41-46). Routledge.
  • Maehr, M. L., & Meyer, H. A. (1997). Understanding motivation and schooling: Where we’ve been, where we are, and where we need to go. Educational Psychology Review, 9(4), 371-409.
  • Mamaril, N. A., Usher, E. L., Li, C. R., Economy, D. R., & Kennedy, M. S. (2016). Measuring undergraduate students' engineering self‐efficacy: A validation study. Journal of Engineering Education, 105(2), 366-395.
  • Mega, C., Ronconi, L., & De Beni, R. (2014). What makes a good student? How emotions, self-regulated learning, and motivation contribute to academic achievement. Journal of educational psychology, 106(1), 121.
  • Midgley, C., Maehr, M. L., Hruda, L. Z., Anderman, E., Anderman, L., Freeman, K. E., Gheen, M., Kaplan, A., Kumar, R., Middleton, M. J., Nelson, J., Roeser, R., & Urdan, T. (2000). Manual for the patterns of adaptive learning scales (PALS). University of Michigan.
  • Murayama, K., Matsumoto, M., Izuma, K., & Matsumoto, K. (2010). Neural basis of the undermining effect of monetary reward on intrinsic motivation. Proceedings of the National Academy of Sciences, 107(49), 20911-20916.
  • Nissim, Y., Weissblueth, E., Scott-Webber, L., & Amar, S. (2016). The effect of a stimulating learning environment on pre-service teachers’ motivation and 21st century skills. Journal of Education and Learning, 5(3), 29-39.
  • Olatoye, R. A. (2009). Students’ test anxiety, motivation for examinations and science achievement in junior secondary schools in Ogun State, Nigeria. International Journal of Psychology and Counselling, 1(10), 194-198.
  • Pasco, J. C. (2021). Self-concept, peer pressure, and teaching strategies, and their influence on students’ performance in mathematics: A cross-sectional study. Journal of Education in Black Sea Region, 7(1), 85-104.
  • Peng, S. L., Cherng, B. L., Chen, H. C. & Lin, Y. Y. (2013). A model of contextual and personal motivations in creativity: How do the classroom goal structures influence creativity via self-determination motivations? Thinking Skill and Creativity, 10, 50-67.
  • Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667-686.
  • Pintrich, P. R., & De Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33-40.
  • Pintrich, P. R., Marx, R. W. & Boyle, R. A. (1993) Beyond cold conceptual change: The role of motivational beliefs and classroom contextual factors in the process of conceptual change. Review of Educational Research, 63, 167-199.
  • Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education: Theory, research, and applications (2nd ed.). Prentice Hall.
  • Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). National Center for Research to Improve Postsecondary Teaching and Learning.
  • Prahmana, R. C. I., Sutanti, T., & Diponegoro, A. M. (2021). Mathematics anxiety and the influencing factors among junior high school students in Yogyakarta, Indonesia. Croatian Journal of Education, 23(2), 343-369.
  • Rakes, G. C., & Dunn, K. E. (2010). The impact of online graduate students' motivation and self-regulation on academic procrastination. Journal of Interactive Online Learning, 9(1), 78-93.
  • Schmitz, B., & Perels, F. (2011). Self-monitoring of self-regulation during math homework behaviour using standardized diaries. Metacognition and Learning, 6(3), 255-273.
  • Schunk, D. H. (2012). Learning theories: An educational perspective (6th Ed.). Merrill/Prentice Hall.
  • Schunk, D. H., & DiBenedetto, M. K. (2016). Self-efficacy theory in education. In K. R. Wentzel & D. B. Miele (Eds.), Handbook of motivation at school (2nd Ed., pp. 34-54). Routledge.
  • Schunk, D. H., & DiBenedetto, M. K. (2021). Self-efficacy and human motivation. In Advances in Motivation Science (Vol. 8, pp. 153-179). Elsevier Academic Press.
  • Schunk, D. H., & Greene, J. A. (2017). Handbook of self-regulation of learning and performance. Routledge.
  • Shin, M., & Bolkan, S. (2021). Intellectually stimulating students’ intrinsic motivation: the mediating influence of student engagement, self-efficacy, and student academic support. Communication Education, 70(2), 146-164.
  • Singh, K., Granville, M., & Dika, S. (2002). Mathematics and science achievement: Effects of motivation, interest, and academic engagement. The Journal of Educational Research, 95(6), 323-332.
  • Skaalvik, E. M., Federici, R. A., & Klassen, R. M. (2015). Mathematics achievement and self-efficacy: Relations with motivation for mathematics. International Journal of Educational Research, 72, 129-136.
  • Tambunan, H. (2018). The dominant factor of teacher's role as a motivator of students' interest and motivation in mathematics adchievement. International Education Studies, 11(4), 144-151.
  • Thrash, T. M., & Elliot, A. J. (2001). Delimiting and integrating the goal and motive constructs in achievement motivation. In A. Efklides, J. Huhl, & R. Sorrentino (Eds.), Trends and prospects in motivation research (pp. 3–21). Kluwer Academic.
  • Timmerman, H. L., Toll, S. W. M., & Van Luit, J. E. H. (2017). The relation between math self-concept, test and math anxiety, achievement motivation and math achievement in 12 to 14-year-old typically developing adolescents. Psychology, Society, & Education, 9(1), 89-103.
  • Torres, J., & Alieto, E. (2019). English learning motivation and self-efficacy of Filipino senior high school students. Asian EFL Journal, 22(1), 51-72.
  • Tuan, H.L., Chin, C.C. & Shieh, S.H. (2005). The development of a questionnaire for assessing students’ motivation toward science learning. International Journal of Science Education, 27(6), 639-654.
  • van Ginkel, S., Gulikers, J., Biemans, H., & Mulder, M. (2015). Towards a set of design principles for developing oral presentation competence: A synthesis of research in higher education. Educational Research Review, 14, 62-80.
  • Wæge (2009, January). Motivation for learning mathematics in terms of needs and goals. In F. Arzarello (Chair), Proceedings of the 6th Congress of the European Society for Research in Mathematics Education. Symposium conducted at the meeting of the University of Lyon, Lyon, France.
  • Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68-81.
  • Wolters, C. A., Pintrich, P. R., & Karabenick, S. A. (2005). Assessing academic self-regulated learning. In K. A. Moore & L. H. Lippman (Eds.), What do children need to flourish? (pp. 251-270). Springer.
  • Yang, Y. T. C., & Wu, W. C. I. (2012). Digital storytelling for enhancing student academic achievement, critical thinking, and learning motivation: A year-long experimental study. Computers & Education, 59(2), 339-352.
Toplam 64 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Matematik Eğitimi
Bölüm Araştırma Makalesi
Yazarlar

Erh-tsung Chin 0009-0005-3288-3316

Ruei Chang Lo 0009-0007-0987-5419

Gönderilme Tarihi 30 Nisan 2025
Kabul Tarihi 12 Aralık 2025
Yayımlanma Tarihi 6 Ocak 2026
Yayımlandığı Sayı Yıl 2025 Cilt: 12 Sayı: 4

Kaynak Göster

APA Chin, E.- tsung, & Lo, R. C. (2026). The Development of a Questionnaire for Assessing Students’ Learning Motivation toward Mathematics (QSLMM). International Journal of Educational Studies in Mathematics, 12(4), 108-121. https://doi.org/10.17278/ijesim.1687705