International Journal of
Information and Education Technology

Abstract—Mathematical literacy is one of the most important skills in the 21st century. However, according to PISA data, mathematical literacy in Indonesia is still low. Low mathematical literacy makes it difficult for students to solve mathematical problems. This issue arises from various factors, both internal and external. One internal factor is how students react to and overcome difficulties, this capability is called Adversity Quotient (AQ). External factors include the quality of learning and the supporting media utilized. So models and media are needed that can support these capabilities. This study evaluates the quality of a MathCityMap assisted CBL model with an RME approach in enhancing mathematical literacy and examines AQ’s role in it. Two sample classes, an experimental group and a control group, were selected through cluster random sampling from the population of grade VII students at SMPN 20 Semarang. Two subjects from each AQ category were selected through purposive sampling to describe mathematical literacy based on AQ. The developed model effectively enhances students’ mathematical literacy, as shown by the results of the right one-part two mean difference test of n-gain values, t_count = 7.071 ≥ t_1-α,dk = 1.997 was obtained, H₀ rejected, it can be concluded that there is a difference in the enhance students’ mathematical literacy average, with the experimental class showing higher literacy levels than the control class, experimental class n-gain = 0.528 > 0.320= control class n-gain. Both fall within the category of moderate improvement. In addition, based on the results of the test examining the influence of AQ on mathematical literacy and the description of mathematical literacy in relation to AQ, it can be concluded that AQ positively influences mathematical literacy—the higher a student’s AQ, the greater their mathematical literacy. The relationship between AQ and the MathCityMap-assisted CBL model with the RME approach is to support learning with relevant and realistic cases.

Keywords—mathematical literacy, case-based learning, MathCityMap, adversity quotient

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Cite: Scolastika Mariani, Fityan Asani, Wardono, Nuriana Rachmani Dewi (Nino Adhi), and Kristina Wijayanti, "MathCityMap-Assisted Case-Based Learning with a Realistic Mathematics Education Approach to Improve Mathematical Literacy Reviewed from Adversity Quotient," International Journal of Information and Education Technology, vol. 15, no. 10, pp. 2218-2235, 2025.

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