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Abstract

Motivation plays a crucial role in enhancing students' achievement in mathematics, as motivated students are more likely to engage actively with the subject. However, in China, there is a concerning trend of declining motivation among students toward mathematics, with many exhibiting avoidance behaviors. Despite Ningbo's significance as a major city in China, there is a lack of studies and surveys addressing students' motivation in mathematics learning. This study addresses this gap by employing a questionnaire based on Keller’s ARCS (Attention, Relevance, Confidence, Satisfaction) model, which has been proven effective in measuring students’ motivation. The survey, conducted among 384 high school students in Ningbo, China, aimed to assess their motivation levels in mathematics learning. Descriptive statistical analysis was performed using SPSS Statistics 29 to calculate the mean and percentage for each item. The results revealed that the motivation level among high school students in Ningbo is notably low. Two significant factors contributing to this low motivation were identified: students’ lack of confidence due to the perceived difficulty of mathematics and the belief that mathematics is not closely related to real life.

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ARCS Model China High School Mathematics Motivation

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How to Cite
Mengyao, H., Ismail, Z., Ismail, N., & Xueting, H. (2024). Motivation in learning mathematics among high school students in Ningbo, China. Journal on Mathematics Education, 15(3), 961–978. https://doi.org/10.22342/jme.v15i3.pp961-978
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References

  1. Abramovich, S., Grinshpan, A. Z., & Milligan, D. L. (2019). Teaching mathematics through concept motivation and action learning. Education Research International, 2019, 1–13. https://doi.org/10.1155/2019/3745406
  2. Arroyo, I., Woolf, B. P., Burelson, W., Muldner, K., Rai, D., & Tai, M. (2014). A multimedia adaptive tutoring system for mathematics that addresses cognition, metacognition and affect. International Journal of Artificial Intelligence in Education, 24(4), 387–426. https://doi.org/10.1007/s40593-014-0023-y
  3. Bakar, K. A., Ayub, A. F. M., Luan, W. S., & Tarmizi, R. A. (2010). Exploring secondary school students’ motivation using technologies in teaching and learning mathematics. Procedia - Social and Behavioral Sciences, 2(2), 4650–4654. https://doi.org/10.1016/j.sbspro.2010.03.744
  4. Bardach, L., Oczlon, S., Pietschnig, J., & Lüftenegger, M. (2020). Has achievement goal theory been right? A meta-analysis of the relation between goal structures and personal achievement goals. Journal of Educational Psychology, 112(6), 1197–1220. https://doi.org/10.1037/edu0000419
  5. Cai, J., Chen, T., Li, X., Xu, R., Zhang, S., Hu, Y., Zhang, L., & Song, N. (2020). Exploring the impact of a problem-posing workshop on elementary school mathematics teachers’ conceptions on problem posing and lesson design. International Journal of Educational Research, 102, 101404. https://doi.org/10.1016/J.IJER.2019.02.004
  6. Chang, N.-C., & Chen, H.-H. (2015). A motivational analysis of the ARCS model for information literacy courses in a blended learning environment. Libri, 65(2), 129-142. https://doi.org/10.1515/libri-2015-0010
  7. Dincer, S. (2020). The effects of materials based on ARCS Model on motivation: A meta-analysis. İlköğretim Online, 1016–1042. https://doi.org/10.17051/ilkonline.2020.695847
  8. Fuqoha, A. A. N., Budiyono, B., & Indriati, D. (2018). Motivation in mathematics learning. Pancaran Pendidikan, 7(1), 15-30. https://doi.org/10.25037/pancaran.v7i1.151
  9. Gjicali, K., & Lipnevich, A. A. (2021). Got math attitude? (In)direct effects of student mathematics attitudes on intentions, behavioral engagement, and mathematics performance in the U.S. PISA. Contemporary Educational Psychology, 67, 102019. https://doi.org/10.1016/j.cedpsych.2021.102019
  10. Gokhale, S. S. (2019). Do PISA scores relate to happiness? 2019 IEEE Integrated STEM Education Conference (ISEC), 111–116. https://doi.org/10.1109/ISECon.2019.8882045
  11. Guo, M., & Leung, F. K. S. (2021). Achievement goal orientations, learning strategies, and mathematics achievement: A comparison of Chinese Miao and Han students. Psychology in the Schools, 58(1), 107–123. https://doi.org/10.1002/pits.22424
  12. Hanus, M. D., & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers & Education, 80, 152–161. https://doi.org/10.1016/j.compedu.2014.08.019
  13. Herbert, B., Fischer, J., & Klieme, E. (2022). How valid are student perceptions of teaching quality across education systems? Learning and Instruction, 82, 101652. https://doi.org/10.1016/j.learninstruc.2022.101652
  14. Hodges, C. B., & Kim, C. (2013). Improving college students’ attitudes toward mathematics. TechTrends, 57(4), 59–66. https://doi.org/10.1007/s11528-013-0679-4
  15. Hsu, Y.-C. (2020). Exploring the learning motivation and effectiveness of applying virtual reality to high school mathematics. Universal Journal of Educational Research, 8(2), 438–444. https://doi.org/10.13189/ujer.2020.080214
  16. Huang, B., Hew, K. F., & Lo, C. K. (2019). Investigating the effects of gamification-enhanced flipped learning on undergraduate students’ behavioral and cognitive engagement. Interactive Learning Environments, 27(8), 1106–1126. https://doi.org/10.1080/10494820.2018.1495653
  17. Imran, H. (2023). An empirical investigation of the different levels of gamification in an introductory programming course. Journal of Educational Computing Research, 61(4), 847–874. https://doi.org/10.1177/07356331221144074
  18. Izmirli, S., & Izmirli, O. S. (2015). Factors motivating preservice teachers for online learning within the context of ARCS motivation model. Turkish Online Journal of Distance Education, 16(2), 56-68. https://doi.org/10.17718/tojde.26620
  19. Jossberger, H., Brand-Gruwel, S., van de Wiel, M. W. J., & Boshuizen, H. P. A. (2020). Exploring students’ self-regulated learning in vocational education and training. Vocations and Learning, 13(1), 131–158. https://doi.org/10.1007/s12186-019-09232-1
  20. Karakis, H., Karamete, A., & Okcu, A. (2016). The effects of a computer-assisted teaching material, designed according to the ASSURE instructional design and the ARCS model of motivation, on students’ achievement levels in a mathematics lesson and their resulting attitudes. European Journal of Contemporary Education, 15(1), 105-113. https://doi.org/10.13187/ejced.2016.15.105
  21. Keller, J. M. (1984). The use of the ARCS model of motivation in teacher training. Aspects of Educational Technology, 17, 140–145.
  22. Keller, J. M. (1987). Development and use of the ARCS model of instructional design. Journal of Instructional Development, 10(3), 2–10. https://doi.org/10.1007/BF02905780
  23. Keller, J. M. (2009). Motivational design for learning and performance: The ARCS model approach. Springer Science & Business Media.
  24. Khakpour, A., Franke, S., Gortschakow, S., Uhrlandt, D., Methling, R., & Weltmann, K.-D. (2016). An improved Arc model based on the Arc diameter. IEEE Transactions on Power Delivery, 31(3), 1335–1341. https://doi.org/10.1109/TPWRD.2015.2473677
  25. Kriegbaum, K., Jansen, M., & Spinath, B. (2015). Motivation: A predictor of PISA’s mathematical competence beyond intelligence and prior test achievement. Learning and Individual Differences, 43, 140–148. https://doi.org/10.1016/j.lindif.2015.08.026
  26. Li, J. (2019). Research on the cognitive dimension of overseas students in China and from countries along “the belt and road” on the image of Chinese cities a case study of Ningbo. Proceedings of the 2nd International Conference on Contemporary Education, Social Sciences and Ecological Studies (CESSES 2019). https://doi.org/10.2991/cesses-19.2019.235
  27. Li, K., & Keller, J. M. (2018). Use of the ARCS model in education: A literature review. Computers & Education, 122, 54–62. https://doi.org/10.1016/j.compedu.2018.03.019
  28. Liu, Binrou. (2021). A study on mathematics test questions in the high school entrance examination based on the PISA (2012) mathematics literacy framework [Master Thesis]. Ningbo University.
  29. Lopes, A. P., & Soares, F. (2024). Assessment of students’ satisfaction and expectations with an online mathematics project. 5589–5598. https://doi.org/10.21125/inted.2024.1441
  30. Mazana, M. Y., Montero, C. S., & Casmir, R. O. (2018). Investigating students’ attitude towards learning mathematics. International Electronic Journal of Mathematics Education, 14(1), 207-231. https://doi.org/10.29333/iejme/3997
  31. Milman, N. B., & Wessmiller, J. (2016). Motivating the online learner using Keller’s ARCS model. Distance Learning, 13(2), 67–71.
  32. Mumcu, Y. (2018). Examining mathematics department students’ views on the use of mathematics in daily life. International Online Journal of Education and Teaching (IOJET), 5(1), 61–80. http://iojet.org/index.php/IOJET/article/view/221/220
  33. Ng, C. C. (2018). High school students’ motivation to learn mathematics: The role of multiple goals. International Journal of Science and Mathematics Education, 16(2), 357–375. https://doi.org/10.1007/s10763-016-9780-4
  34. Ning, B. (2020). Discipline, motivation, and achievement in mathematics learning: An exploration in Shanghai. School Psychology International, 41(6), 595–611. https://doi.org/10.1177/0143034320961465
  35. Novak, E. (2014). Toward a mathematical model of motivation, volition, and performance. Computers & Education, 74, 73–80. https://doi.org/10.1016/j.compedu.2014.01.009
  36. Ozgen, K. (2019). Problem-posing skills for mathematical literacy: The sample of teachers and pre-service teachers. Eurasian Journal of Educational Research, 19(84), 1–36. https://doi.org/10.14689/ejer.2019.84.9
  37. Pechočiak, T., & Kecskés, N. (2016). Mathematics and statistics in global education. The Agri-Food Value Chain: Challenges for Natural Resources Management and Society, 668–674. https://doi.org/10.15414/isd2016.s8.13
  38. Qian, Q., & Lau, K. (2022). The effects of achievement goals and perceived reading instruction on Chinese student reading performance: Evidence from PISA 2018. Journal of Research in Reading, 45(1), 137–156. https://doi.org/10.1111/1467-9817.12388
  39. Roberts, T., Jackson, C., Mohr-Schroeder, M. J., Bush, S. B., Maiorca, C., Cavalcanti, M., Craig Schroeder, D., Delaney, A., Putnam, L., & Cremeans, C. (2018). Students’ perceptions of STEM learning after participating in a summer informal learning experience. International Journal of STEM Education, 5(1), 1-14. https://doi.org/10.1186/s40594-018-0133-4
  40. Sahanata, M., & Dewi, F. K. (2022). The effect of application of the ARCS learning model (Attention, Relevance, Confidence, Satisfaction) on motivation. Journal of Curriculum and Pedagogic Studies (JCPS), 1(1), 1-11. https://doi.org/10.30631/jcps.v1i1.1360
  41. Schukajlow, S., Rakoczy, K., & Pekrun, R. (2017). Emotions and motivation in mathematics education: Theoretical considerations and empirical contributions. ZDM, 49(3), 307–322. https://doi.org/10.1007/s11858-017-0864-6
  42. Strauss, V. (2019). China is No. 1 on PISA — But here’s why its test scores are hard to believe. The Washington Post. Retrieved from Https://Www.Washingtonpost.Com/Education/2019/12/04/China-Is-No-Pisa Heres-Why-Its-Test-Scores-Are-Hard-Believe/. Accessed 29 Nov 2022.
  43. Tao, V. Y. K. (2016). Understanding Chinese students’ achievement patterns: Perspectives from social-oriented achievement motivation. In King, R., Bernardo, A. (eds) The Psychology of Asian Learners (pp. 621–634). Springer. https://doi.org/10.1007/978-981-287-576-1_38
  44. Tran, L. T., & Nguyen, T. S. S. (2021). Motivation and mathematics achievement: A Vietnamese case study. Journal on Mathematics Education, 12(3), 449–468. https://doi.org/10.22342/jme.12.3.14274.449-468
  45. Wakhata, R., Mutarutinya, V., & Balimuttajjo, S. (2022). Secondary school students’ attitude towards mathematics word problems. Humanities and Social Sciences Communications, 9(1), 1-11. https://doi.org/10.1057/s41599-022-01449-1
  46. Wang, L., Liu, Q., Du, X., & Liu, J. (2018). Chinese mathematics curriculum reform in the twenty-first century. In Cao, Y., Leung, F. (eds) The 21st Century Mathematics Education in China. New Frontiers of Educational Research (pp. 53–72). Springer. https://doi.org/10.1007/978-3-662-55781-5_3
  47. Wang Xinjing. (2022). Analysis and countermeasures of common problems in mathematics learning for senior high school students. Mathematics Learning and Research, 17, 143–145.
  48. Wong, S. L., & Wong, S. L. (2021). Effects of motivational adaptive instruction on student motivation towards mathematics in a technology-enhanced learning classroom. Contemporary Educational Technology, 13(4), ep326. https://doi.org/10.30935/cedtech/11199
  49. Yang, W., & Fan, G. (2023). Delving into the development of Chinese students based on PISA scores. In Guo, D. (eds) The Frontier of Education Reform and Development in China. Educational Research in China (pp. 107–128). Springer. https://doi.org/10.1007/978-981-19-6355-1_7
  50. Yang, X., Kaiser, G., König, J., & Blömeke, S. (2021). Relationship between Chinese mathematics teachers’ knowledge and their professional noticing. International Journal of Science and Mathematics Education, 19(4), 815–837. https://doi.org/10.1007/s10763-020-10089-3
  51. Zabala-Vargas, S. A., García-Mora, L., Arciniegas-Hernández, E., Reina-Medrano, J., de Benito-Crosetti, B., & Darder-Mésquida, A. (2022). Didactic strategy mediated by games in the teaching of mathematics in first-year engineering students. Eurasia Journal of Mathematics, Science and Technology Education, 18(2), em2082. https://doi.org/10.29333/ejmste/11707
  52. Zhang, Y., Yang, X., Sun, X., & Kaiser, G. (2023). The reciprocal relationship among Chinese senior secondary students’ intrinsic and extrinsic motivation and cognitive engagement in learning mathematics: a three-wave longitudinal study. ZDM – Mathematics Education, 55(2), 399–412. https://doi.org/10.1007/s11858-022-01465-0