Design and Evaluation of a Guided Discovery-Based Calculus Module on Derivatives with Islamic Values Integration
Abstract
Purpose of the study: This study aims to develop and evaluate a guided discovery-based calculus module on derivatives integrated with Islamic values to support students’ conceptual understanding, independent learning, and spiritual awareness in higher education mathematics learning.
Methodology: This study employed a Research and Development (R&D) method using the 4D model (define, design, develop, disseminate). Data were collected through questionnaires, validation sheets, and documentation. Instruments included expert validation sheets and student response questionnaires. Data were analyzed using descriptive quantitative and qualitative techniques with a Likert scale (1–4).
Main Findings: Results show that the module achieved valid criteria across material, media, and Islamic values aspects after revision. Material validation increased to 3.75, media design to 3.8, and Islamic values to 4.0. Limited trial results indicated an average score of 3.56, categorized as very attractive. These findings confirm that the module is feasible and well-received by students.
Novelty/Originality of this study: This study presents an integrative calculus module combining guided discovery learning with Islamic values on derivative topics. It simultaneously addresses cognitive and spiritual aspects within a single instructional design. This approach provides a holistic learning resource and contributes to advancing mathematics education by integrating pedagogical strategy and value-based learning.
References
A. Fawaid and P. Handayani, “Visualizing inequality: Uncovering gender bias in Islamic textbooks of Indonesia,” Cogent Educ., vol. 12, no. 1, pp. 1–25, 2025, doi: 10.1080/2331186X.2025.2593342.
D. Li, W. Yang, N. Chen, Y. Xu, and D. Li, “Updates in the treatment of rosacea with γ-aminobutyric acid derivatives,” Clin. Cosmet. Investig. Dermatol., vol. 7015, pp. 1–9, 2025, doi: 10.2147/CCID.S550614.
J. Zhu, S. Yin, S. Luo, F. Yu, and K. Sun, “Traditional chinese medicine monomers and their derivatives as a promising therapeutic tool for hepatocellular carcinoma by activation of mitophagy,” Drug Des. Devel. Ther., vol. 8881, pp. 1–20, 2025, doi: 10.2147/DDDT.S535244.
R. Shahin, S. Jaafreh, and Y. Azzam, “Tracking protein kinase targeting advances: integrating QSAR into machine learning for kinase-targeted drug discovery,” Futur. Sci. OA, vol. 11, no. 1, pp. 1–28, 2025, doi: 10.1080/20565623.2025.2483631.
Z. Malik et al., “Thiazolidine derivatives attenuate carrageenan-induced inflammatory pain in mice,” Drug Des. Devel. Ther., vol. 8881, pp. 1–17, 2021, doi: 10.2147/DDDT.S281559.
O. Spjuth, J. Frid, A. Hellander, and O. Spjuth, “The machine learning life cycle and the cloud: Implications for drug discovery,” Expert Opin. Drug Discov., vol. 16, no. 9, pp. 1071–1080, 2021, doi: 10.1080/17460441.2021.1932812.
L. Yu et al., “The anticancer potential of maslinic acid and its derivatives: A review,” Drug Des. Devel. Ther., vol. 8881, pp. 1–18, 2021, doi: 10.2147/DDDT.S326328.
Y. Wang et al., “Synthesis and biological activity of piperine derivatives as potential PPARγ agonists,” Drug Des. Devel. Ther., vol. 8881, pp. 1–11, 2020, doi: 10.2147/DDDT.S238245.
H. Xiao, X. Yang, Y. Zhang, Z. Zhang, and G. Zhang, “RNA-targeted small-molecule drug discoveries: A machine-learning perspective,” RNA Biol., vol. 20, no. 1, pp. 384–397, 2023, doi: 10.1080/15476286.2023.2223498.
G. Antoniolli et al., “Recent advances in the investigation of the quinazoline nucleus and derivatives with potential anticancer activities,” Future Med. Chem., vol. 17, no. 10, pp. 1193–1212, 2025, doi: 10.1080/17568919.2025.2507558.
D. Design, “Quaternary lidocaine derivatives: Past, Present, and Future,” Drug Des. Devel. Ther., vol. 8881, pp. 1–14, 2021, doi: 10.2147/DDDT.S291229.
X. Ma and H. Lin, “Predicting stock market crises using stock index derivatives: Evidence from China,” Emerg. Mark. Financ. Trade, vol. 60, no. 3, pp. 576–597, 2024, doi: 10.1080/1540496X.2023.2236284.
M. Mohammed, J. Alabdulhadi, and K. M. Alkandari, “Practices of islamic education teachers in promoting moderation (wasatiyyah) values among high school students in Kuwait: Challenges and obstacles,” Cogent Educ., vol. 11, no. 1, pp. 1–17, 2024, doi: 10.1080/2331186X.2024.2365577.
E. Balıkçı, A. M. C. Marques, J. S. Hansen, and V. M. Kilian, “Open resources for chemical probes and their implications for future drug discovery,” Expert Opin. Drug Discov., vol. 18, no. 5, pp. 505–514, 2023, doi: 10.1080/17460441.2023.2199979.
F. E. Toerien et al., “On the determinants of derivatives disclosure–an emerging markets perspective perspective,” South African J. Account. Res., vol. 39, no. 3, pp. 249–265, 2025, doi: 10.1080/10291954.2024.2362475.
M. A. Hussein et al., “Novel biologically active polyurea derivatives and its TiO2-doped nanocomposites,” Des. Monomers Polym., vol. 23, no. 1, pp. 59–74, 2020, doi: 10.1080/15685551.2020.1767490.
J. M. Walczak et al., “Novel amides of mycophenolic acid and some heterocyclic derivatives as immunosuppressive agents,” J. Enzyme Inhib. Med. Chem., vol. 37, no. 1, pp. 2725–2741, 2022, doi: 10.1080/14756366.2022.2127701.
M. Taheri, R. Mohebat, and M. H. Mosslemin, “Multi-component reaction synthesis of by reusable ZnO-PTA @Fe3O4/EN-MIL-101 (Cr) nanopowder at room temperature,” Green Chem. Lett. Rev., vol. 13, no. 3, pp. 1–14, 2020, doi: 10.1080/17518253.2020.1800830.
A. Daniel, D. Gebeyhu, S. Assefa, and T. Abate, “Modified guided-discovery methods in physics laboratories: Pre-service teachers’ conceptual and procedural knowledge, views of nature of science, and motivation,” Cogent Educ., vol. 10, no. 2, pp. 1–38, 2023, doi: 10.1080/2331186X.2023.2267937.
M. Asrori, B. Fandi, G. Y. Sofian, A. Fadhel, S. Hidayat, and A. Suja, “Islamic educational and cultural values in Indonesian puppetry art: A systematic literature review,” Cogent Educ., vol. 12, no. 1, pp. 1–20, 2025, doi: 10.1080/2331186X.2025.2490445.
W. K. Abdul-jabbar and N. Ramadan, “Integrating islamic thought as intercultural praxis into secondary schools curriculum in Canada: An islamic school in Saskatchewan,” J. Beliefs Values, vol. 00, no. 00, pp. 1–15, 2025, doi: 10.1080/13617672.2025.2532340.
E. Miller et al., “Innovations and evolution of large-enrollment calculus in response to the pandemic,” PRIMUS Probl. Resour. Issues Math. Undergrad. Stud., vol. 35, no. 4–5, pp. 380–405, 2025, doi: 10.1080/10511970.2024.2352866.
H. Huang, O. A. Kraevaya, I. I. Voronov, and P. A. Troshin, “Fullerene derivatives as lung cancer cell inhibitors: Investigation of potential descriptors using QSAR approaches,” Int. J. Nanomedicine, vol. 9114, pp. 1–16, 2020, doi: 10.2147/IJN.S243463.
W. Hou et al., “Fullerene derivatives for tumor treatment: Mechanisms and application,” Int. J. Nanomedicine, vol. 9114, pp. 1–28, 2024, doi: 10.2147/IJN.S476601.
A. R. Bradley et al., “From algorithms to systems: Integrating computation into drug discovery,” Expert Opin. Drug Discov., vol. 20, no. 12, pp. 1493–1504, 2025, doi: 10.1080/17460441.2025.2601102.
M. Asutay and I. Yilmaz, “Financialisation of islamic finance: A polanyian approach on the hegemony of market logic over islamic logic,” New Polit. Econ., vol. 30, no. 2, pp. 267–286, 2025, doi: 10.1080/13563467.2024.2424170.
A. Fakhruddin, S. Anwar, M. Rindu, and F. Islamy, “Enhancing academic self-concept and historical literacy in Islamic studies through collaborative learning: A study on prospective islamic education teachers in Indonesia,” Cogent Educ., vol. 12, no. 1, pp. 1–18, 2025, doi: 10.1080/2331186X.2025.2491871.
S. Fujii, J. Hyodo, K. Shitara, A. Kuwabara, and Y. Yamazaki, “Emerging computational and machine learning methodologies for proton-conducting oxides: Materials discovery and fundamental understanding,” Sci. Technol. Adv. Mater., vol. 25, no. 1, pp. 1–50, 2024, doi: 10.1080/14686996.2024.2416383.
R. Robeva, T. D. Comar, C. D. Eaton, and R. Robeva, “Can we bridge the gap? Mathematics and the life sciences, Part 1–calculus-based modules, programs, curricula,” PRIMUS Probl. Resour. Issues Math. Undergrad. Stud., vol. 32, no. 2, pp. 117–123, 2022, doi: 10.1080/10511970.2022.2025506.
F. Boniolo et al., “Artificial intelligence in early drug discovery enabling precision medicine,” Expert Opin. Drug Discov., vol. 16, no. 9, pp. 991–1008, 2021, doi: 10.1080/17460441.2021.1918096.
J. Jiménez-luna, F. Grisoni, N. Weskamp, G. Schneider, and F. Grisoni, “Artificial intelligence in drug discovery: Recent advances and future perspectives,” Expert Opin. Drug Discov., vol. 16, no. 9, pp. 949–960, 2021, doi: 10.1080/17460441.2021.1909567.
A. Miller, K. Pyper, A. Miller, and K. Pyper, “Anxiety around learning R in first year undergraduate students: Mathematics versus biomedical sciences students,” J. Stat. Data Sci. Educ., vol. 32, no. 1, pp. 47–53, 2024, doi: 10.1080/26939169.2023.2190010.
A. Luque et al., “Aligning calculus with life sciences disciplines: The argument for integrating statistical reasoning,” PRIMUS Probl. Resour. Issues Math. Undergrad. Stud., vol. 32, no. 2, pp. 199–217, 2022, doi: 10.1080/10511970.2021.1881847.
Ö. C. Yelgel and C. Yelgel, “A review of machine learning approaches for the discovery of thermoelectric materials,” Adv. Phys. X, vol. 10, no. 01, pp. 1–24, 2025, doi: 10.1080/23746149.2025.2536269.
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