The Construction and Application of a Differentiated Model for Middle School Mathematics Differentiated Instruction Based on the AHP Theory
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Keywords

Differentiated Instruction
AHP theory
Differentiated standards
Academic performance

How to Cite

YANG, H., & HASSAN, A. (2025). The Construction and Application of a Differentiated Model for Middle School Mathematics Differentiated Instruction Based on the AHP Theory. International Theory and Practice in Humanities and Social Sciences, 2(8), 157–168. https://doi.org/10.70693/itphss.v2i8.1239

Abstract

The impact of differentiated standards on differentiated instruction is crucial. This study adopts a differentiated model based on the theory of analytic hierarchy process, which comprehensively considers factors such as students’ learning cognition, gender, learning interest, learning experience, and learning strategies. The calculation formula for layered value L:

L=1.8or1.2+C∙43%+(100I/15)∙14%+[20(5-An)/3]∙7%+20At/3∙7%+20M/3∙7%+

(100I/160)∙33%(Note:1.8 for boys and 1.2 for girls). Through a teaching control experiment, it is found that differentiated instruction based on mathematical academic performance can significantly improve the learning performance of students at weak level C, while differentiated instruction based on AHP differentiated model can significantly improve the learning performance of students at weak level C and general level B. At the same time, the differentiated model based on AHP has a more stable and less volatile learning performance than the differentiated model based on mathematical academic performance.

https://doi.org/10.70693/itphss.v2i8.1239
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References

Berger, J.-L., & Karabenick, S. A. (2011). Motivation and students’ use of learning strategies: Evidence of unidirectional effects in mathematics classrooms. Learning and Instruction, 21(3), 416-428. https://doi.org/10.1016/j.learninstruc.2010.06.002

Chandran, B., Golden, B., & Wasil, E. (2005). Linear programming models for estimating weights in the analytic hierarchy process. Computers & Operations Research, 32(9), 2235-2254. https://doi.org/10.1016/j.cor.2004.02.010

Gui-ying, H., & Bai-hua, X. (2003). Relations of academic achievement to learning self-efficacy and learning strategy for middle school students. Journal of Zhejiang University(Science Edition)(04), 477-480. https://doi.org/CNKI:SUN:HZDX.0.2003-04-028

Hai-bo, Y., Dian-zhi, L., & Rong-kun, Y. (2015). The Relationship between Self Efficacy, Learning Strategies, and Grades: A Study of Junior High School Mathematics Learning Based on Kolb Learning Style. Educational Science Research(10), 52-57. https://doi.org/CNKI:SUN:JYKY.0.2015-10-011

Hong-Yan, W., & Xiao-lin, L. (2017). Development of Mathematics Learning Interest Questionnaire and the Investigation on Junior High School Students. JOURNAL OF MATHEMATICS EDUCATION, 26(02), 50-54. https://doi.org/CNKI:SUN:SXYB.0.2017-02-010

Jia-xia, L., Tao, X., Gao-qing, H., & Ji-liang, S. (2000). A Study on the Relationship between Middle School Students’ Learning Motivation, Learning Strategies, and Academic Achievement. Theory and Practice of Education(09), 54-58. https://doi.org/CNKI:SUN:JYLL.0.2000-09-011

Lian-ming, H., & Chun-xia, Q. (2016). Study of the Greater Male Variability Hypothesis in Regional Quality Testing Project of Mathematics Achievement in Mainland. JOURNAL OF MATHEMATICS EDUCATION, 25(06), 38-41. https://doi.org/CNKI:SUN:SXYB.0.2016-06-008

Qian-qian, Z. (2022). Research on Online Teaching Evaluation Based on Analytic Hierarchy Process. Jiangsu Science and Technology Information, 39(18), 64-66. https://doi.org/CNKI:SUN:KJXY.0.2022-18-019

Qiu-qian, S. (2000). Teaching Theory Reflection on Layered Progressive Teaching. Journal of the Chinese Society of Education(03), 47-49. https://doi.org/CNKI:SUN:ZJYX.0.2000-03-017

Run-sheng, L., Ji-liang, S., & Meng-cheng, W. (2006). Analysis about the Influence of Senior High School Students’ Mathematics Grade. JOURNAL OF MATHEMATICS EDUCATION(02), 57-60. https://doi.org/CNKI:SUN:SXYB.0.2006-02-015

Satty, T. (1970). Principle and appliance of analytic hierarchy process. Management Science, 11.

Wen-jun, G., & Jian-sheng, B. (2009). Comparison of Exercises in Mathematics Cognitive Levels in China and United States —— As an Example to Quadratic Equations and Functions. JOURNAL OF MATHEMATICS EDUCATION, 18(04), 57-60. https://doi.org/CNKI:SUN:SXYB.0.2009-04-017

Xiao-peng, W., & Qi-ping, K. (2020). The Construction and Application of the Comprehensive Difficulty Model of Mathematical Advanced Examination Questions Based on AHP Theory. JOURNAL OF MATHEMATICS EDUCATION, 29(02), 29-34. https://doi.org/CNKI:SUN:SXYB.0.2020-02-006

Xiu-feng, M., & Dian-zhi, L. (2007). Study on Junior School Students about Their Individual Differences of Mathematical Learning Strategies. JOURNAL OF MATHEMATICS EDUCATION(04), 56-58. https://doi.org/CNKI:SUN:SXYB.0.2007-04-016

Yi-zhao, H., & Ji-bing, P. (2022). Comparative Study on the Comprehensive Difficulty of Mathematics Test Questions in the 2021 College Entrance Examination: A Comprehensive Difficulty Model Based on AHP Theory. Journal of Hubei Normal University(Natural Science), 42(04), 65-71. https://doi.org/CNKI:SUN:HBSF.0.2022-04-011

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Copyright (c) 2025 HUI YANG, AMINUDDIN HASSAN (Author)

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