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An Innovative Approach to Automatically Generating Derivative Questions for Calculus with Rule-based Algorithmic Model

Jurnal Penelitian Pendidikan · Vol. 42 No. 2 (2025) · pp. 540–549

DOI
10.15294/jpp.v42i2.62082
ISSN
2580-4154, 2503-1260
Published
2025-10-31
Publisher
Universitas Negeri Semarang
Language
eng

Abstract

This study aims to develop an automated system for generating derivative function questions to enhance learning and assessment in calculus education. The system uses a rule-based algorithmic approach to generate questions covering various derivative rules, including constant, power, sum, difference, product, quotient, and chain rules, with randomly generated coefficients and exponents. The system's performance was evaluated by measuring the accuracy of the generated questions, achieving a validity rate of 95.63%, and execution time, with an average of 0.00115 milliseconds per question, indicating high efficiency and effectiveness. The results show that the system successfully generates valid questions across various derivative rules, offering significant contributions to both students and educators in the context of calculus education. The system can be further developed by adding additional derivative rules and integrated into larger educational platforms to support a more comprehensive learning experience.

Keywords

Collaboration network of the authors

40 authors · 138 co-authorship links · showing the 40 most connected

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  • State University of Semarang
  • University of Brawijaya
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Maria KrisnawatiAffiliation unknown8
Mia Hafizah TumanggerAffiliation unknown7
Nur QudusAffiliation unknown5
Sri Endah WahyuningsihAffiliation unknown5
Indah Indi AfifahAffiliation unknown5
Yeri SutopoAffiliation unknown4
Alfa Faridh SuniState University of Semarang4
Okta PurnawirawanUniversity of Brawijaya4
Erna SetyowatiAffiliation unknown4
Musdalifah MusdalifahAffiliation unknown3
Milda RuliyantiAffiliation unknown3
Eny Widhia AgustinAffiliation unknown2
Adhi KusumastutiAffiliation unknown2
Eko SupraptonoAffiliation unknown2
Basyirun BasyirunAffiliation unknown2
Nelly Setyowati AnggraeniAffiliation unknown2
Marwiyah MarwiyahAffiliation unknown2
Hanan Iqbal AlrahmaState University of Semarang1
Ahmad Fashiha HastawanState University of Semarang1
Ulfah Mediaty AriefState University of Semarang1
Budi SunarkoState University of Semarang1
Hari WibawantoState University of Semarang1
Anggraini MulwindaState University of Semarang1
Anas FauziState University of Semarang1
Dwi OktaviyantiState University of Semarang1
Dina Wulung SavitriState University of Semarang1
Ariska Fitriyana NingrumAffiliation unknown1
Hizkia Natanael RichardoAffiliation unknown1
Paramesti AstaginaAffiliation unknown1
Anantha Revoislami AriolinAffiliation unknown1
Kholiq BudimanAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/journals/JPP/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en">An Innovative Approach to Automatically Generating Derivative Questions for Calculus with Rule-based Algorithmic Model</dc:title>
	<dc:creator xml:lang="en">Widowati, Trisnani</dc:creator>
	<dc:creator xml:lang="en">Septian Eko Prasetyo</dc:creator>
	<dc:creator xml:lang="en">Anan Nugroho</dc:creator>
	<dc:creator xml:lang="en">Ade Novi Nurul Ihsani</dc:creator>
	<dc:creator xml:lang="en">Alfian Ardhiansyah</dc:creator>
	<dc:creator xml:lang="en">Ajeng Rahma Sudarni</dc:creator>
	<dc:creator xml:lang="en">Mulil Khaira</dc:creator>
	<dc:creator xml:lang="en">Clarita Apriliani</dc:creator>
	<dc:creator xml:lang="en">Anik Maghfiroh</dc:creator>
	<dc:subject xml:lang="en">automated item generation, algorithmic question generation, calculus, derivative function, rule-based system</dc:subject>
	<dc:description xml:lang="en">This study aims to develop an automated system for generating derivative function questions to enhance learning and assessment in calculus education. The system uses a rule-based algorithmic approach to generate questions covering various derivative rules, including constant, power, sum, difference, product, quotient, and chain rules, with randomly generated coefficients and exponents. The system's performance was evaluated by measuring the accuracy of the generated questions, achieving a validity rate of 95.63%, and execution time, with an average of 0.00115 milliseconds per question, indicating high efficiency and effectiveness. The results show that the system successfully generates valid questions across various derivative rules, offering significant contributions to both students and educators in the context of calculus education. The system can be further developed by adding additional derivative rules and integrated into larger educational platforms to support a more comprehensive learning experience.</dc:description>
	<dc:publisher xml:lang="en">Universitas Negeri Semarang</dc:publisher>
	<dc:date>2025-10-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en">Peer-reviewed Article</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unnes.ac.id/journals/JPP/article/view/62082</dc:identifier>
	<dc:identifier>10.15294/jpp.v42i2.62082</dc:identifier>
	<dc:source xml:lang="en">Jurnal Penelitian Pendidikan; Vol. 42 No. 2 (2025): October 2025; 540-549</dc:source>
	<dc:source>2580-4154</dc:source>
	<dc:source>2503-1260</dc:source>
	<dc:source>10.15294/jpp.v42i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/journals/JPP/article/view/62082/10936</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2025 Jurnal Penelitian Pendidikan</dc:rights>
</oai_dc:dc>