@inproceedings{MTMT:36149271,
	title = {ANALYTICS FOR THE ASSESSMENT OF COMPUTATIONAL THINKING},
	url = {https://m2.mtmt.hu/api/publication/36149271},
	author = {Bilbao, Javier and Bravo, Eugenio and García, Olatz and Rebollar, Carolina and Dagiené, Valentina and Masiulionytė-Dagienė, Vaida and Jankauskienė, Asta and Laakso, Mikko and Kaarto, Heidi and Lehtonen, Daranee and Parviainen, Marika and Güven, Ismail and Gulbahar, Yasemin and Öztürk, Tugba and Tan Yenigün, Nilüfer and Pluhár, Zsuzsa and Sarmasági, Pál György and Rumbus, Anikó and Pears, Arnold},
	booktitle = {INTED2025 Proceedings},
	doi = {10.21125/inted.2025.1764},
	unique-id = {36149271},
	abstract = {Computational thinking is a fundamental competence in contemporary education, which enables individuals to approach problems in a logical and structured manner. This new competence is not only crucial for computer science professionals, but is also applicable in various disciplines and contexts of daily life. Computational thinking is essential in education because it fosters problem-solving skills, critical thinking, and creativity. In the digital age, computational thinking is not just a technical skill, but a way of thinking that can transform the way we approach the challenges and opportunities of the modern world. Assessing this skill requires precise analytical tools and methods. Assessing computational thinking is a complex process that requires a combination of qualitative and quantitative methods. Analytical rubrics, portfolio analysis, and standardized tests are essential tools that help provide a comprehensive and accurate assessment of students’ skills in this field. In our project, we also work to assess computational thinking using Bebras-type tasks and applying data analysis. Data analysis also facilitates the continuous improvement of teaching and assessment methods. By monitoring and analysing data over time, educators can identify which strategies are most effective and make adjustments to improve learning outcomes. Furthermore, data can help develop new tools and resources for teaching computational thinking. In this article, we present the assessment instrument, Comath, a research-based instrument with two rounds of piloting in six counties with subject-matter experts and over 4500 students and 100 teachers. We use tasks related to computational thinking, and we present some of the results obtained so far.},
	keywords = {learning; STEAM; Mathematics; computational thinking; digital competence; analytics; Algebraic thinking; cross-curricular competence},
	year = {2025},
	pages = {6861-6868},
	orcid-numbers = {Pluhár, Zsuzsa/0000-0003-2688-4652; Sarmasági, Pál György/0009-0002-7683-8515}
}

@CONFERENCE{MTMT:36477130,
	title = {ENHANCING LEARNING THROUGH MEANINGFUL ASSESSMENT OF COMPUTATIONAL THINKING IN MULTIDISCIPLINARY EDUCATION},
	url = {https://m2.mtmt.hu/api/publication/36477130},
	author = {Bilbao, Javier and Bravo, Eugenio and García, Olatz and Rebollar, Carolina and Laakso, Mikko-Jussi and Kaarto, Heidi and Lehtonen, Daranee and Parviainen, Marika and Jankauskienė, Asta and Pears, Arnold and Güven, Ismail and Gulbahar, Yasemin and Öztürk, Tugba and Tan Yenigün, Nilüfer and Pluhár, Zsuzsa and Sarmasági, Pál György and Rumbus, Anikó and Dagienė, Valentina and Masiulionytė-Dagienė, Vaida},
	booktitle = {ICERI2025 Proceedings},
	doi = {10.21125/iceri.2025.1677},
	unique-id = {36477130},
	year = {2025},
	pages = {6086-6094},
	orcid-numbers = {Pluhár, Zsuzsa/0000-0003-2688-4652; Sarmasági, Pál György/0009-0002-7683-8515}
}

@article{MTMT:35498816,
	title = {Teachers’ Motivation to Engage with Students in a Computer Science and Computational Thinking Challenge: Does Motivation Conform to a ‘One-Size-Fits-All’ Model?},
	url = {https://m2.mtmt.hu/api/publication/35498816},
	author = {Gaál, Bence and Pluhár, Zsuzsa and Lidia, Feklistova and Tatjana, Jevsikova},
	doi = {10.1007/978-3-031-73474-8_12},
	journal-iso = {LNCS},
	journal = {LECTURE NOTES IN COMPUTER SCIENCE},
	volume = {15228},
	unique-id = {35498816},
	issn = {0302-9743},
	year = {2025},
	eissn = {1611-3349},
	pages = {152-166},
	orcid-numbers = {Gaál, Bence/0000-0001-8771-7140; Pluhár, Zsuzsa/0000-0003-2688-4652}
}

@article{MTMT:36174710,
	title = {Analytical Methods and Tools for Evaluating the Development of Computational Thinking Abilities},
	url = {https://m2.mtmt.hu/api/publication/36174710},
	author = {Javier, Bilbao and Eugenio, Bravo and Olatz, García and Carolina, Rebollar and Mikko-Jussi, Laakso and Heidi, Kaarto and Daranee, Lehtonen and Marika, Parviainen and Asta, Jankauskienė and Arnold, Pears and Ismail, Güven and Yasemin, Gulbahar and Tugba, Öztürk and Nilüfer, Tan Yenigün and Pluhár, Zsuzsa and Sarmasági, Pál György and Rumbus, Anikó and Valentina, Dagienė and Vaida, Masiulionytė-Dagienė},
	journal-iso = {INT J EDUC INF TECH},
	journal = {INTERNATIONAL JOURNAL OF EDUCATION AND INFORMATION TECHNOLOGIES},
	volume = {19},
	unique-id = {36174710},
	issn = {2074-1316},
	year = {2025},
	eissn = {2074-1316},
	pages = {53-61},
	orcid-numbers = {Pluhár, Zsuzsa/0000-0003-2688-4652; Sarmasági, Pál György/0009-0002-7683-8515}
}

@article{MTMT:35724432,
	title = {BeLLE: Detecting National Differences in Computational Thinking and Computer Science Through an International Challenge},
	url = {https://m2.mtmt.hu/api/publication/35724432},
	author = {Kaarto, Heidi and Bilbao, Javier and Pears, Arnold and Dagienė, Valentina and Kilpi, Janica and Parviainen, Marika and Pluhár, Zsuzsa and Gülbahar, Yasemin and Laakso, Mikko-Jussi},
	doi = {10.1007/978-3-031-73257-7_14},
	journal-iso = {LNCS},
	journal = {LECTURE NOTES IN COMPUTER SCIENCE},
	volume = {15229},
	unique-id = {35724432},
	issn = {0302-9743},
	year = {2025},
	eissn = {1611-3349},
	pages = {168-182},
	orcid-numbers = {Kaarto, Heidi/0009-0004-3623-0729; Bilbao, Javier/0000-0002-2784-8496; Pears, Arnold/0000-0002-5184-4743; Dagienė, Valentina/0000-0002-3955-4751; Parviainen, Marika/0009-0000-8055-0317; Pluhár, Zsuzsa/0000-0003-2688-4652; Laakso, Mikko-Jussi/0000-0001-9163-2676}
}

@article{MTMT:36216774,
	title = {Bridging Algebraic and Computational Thinking: Impacts on Student Development in K–12 Education},
	url = {https://m2.mtmt.hu/api/publication/36216774},
	author = {Sarmasági, Pál György and Rumbus, Anikó and Javier, BILBAO and Margitay-Becht, András and Pluhár, Zsuzsa and Carolina, REBOLLAR and Valentina, DAGIENĖ},
	doi = {10.15388/infedu.2025.13},
	journal-iso = {INFORMATICS IN EDUCATION},
	journal = {INFORMATICS IN EDUCATION: AN INTERNATIONAL JOURNAL},
	volume = {24},
	unique-id = {36216774},
	issn = {1648-5831},
	abstract = {Algebraic Thinking (AT) and Computational Thinking (CT) are pivotal competencies in modern education, fostering problem-solving skills and logical reasoning among students. This study presents the initial hypotheses, theoretical framework, and key steps undertaken to explore characterized learning paths and assign practice-relevant tasks. This article investigates the relationship between AT and CT, their parallel development, and the creation of integrated learning paths. Analyses of mathematics and computer science/informatics curricula across six countries (Finland, Hungary, Lithuania, Spain, Sweden, and Türkiye) informed the development of tasks aligned with consolidated national curricula. Curricula were analysed using statistical methods, and content analysis to identify thematic patterns. To validate the effectiveness of the developed tasks for AT and CT, an assessment involving 208 students in K-12 across various grade levels (students aged 9–14) was conducted, with results analysed both statistically and qualitatively. Subsequently, a second quantitative study was carried out among teachers participating in a workshop, providing further insights into the practical applicability of the tasks. The research process was iterative, encompassing cycles of analysis, synthesis, and testing. The study also paid special attention to unplugged activities – tasks that help students learn CT without using computers or digital tools. A local workshop in Hungary, where 26 tasks were tested with students from different grade levels, showed that developing CT and AT effectively requires more time and practice, especially in key topics. The findings underscore the importance of integrating AT and CT through thoughtfully designed learning paths and tasks, including unplugged activities, to enhance students’ proficiency in these areas. This study contributes to the development
		of innovative educational programs that address the evolving digital competencies required in contemporary education.},
	keywords = {computational thinking; learning path; Algebraic thinking; Unplugged activities},
	year = {2025},
	eissn = {2335-8971},
	pages = {343-376},
	orcid-numbers = {Sarmasági, Pál György/0009-0002-7683-8515; Pluhár, Zsuzsa/0000-0003-2688-4652}
}

@book{MTMT:35475054,
	title = {Informatics in Schools. Innovative Approaches to Computer Science Teaching and Learning. 17th International Conference on Informatics in Schools: Situation, Evolution, and Perspectives, ISSEP 2024, Budapest, Hungary, October 28–30, 2024, Proceedings},
	url = {https://m2.mtmt.hu/api/publication/35475054},
	isbn = {9783031734731},
	editor = {Pluhár, Zsuzsa and Gaál, Bence},
	publisher = {Springer Nature Switzerland AG},
	unique-id = {35475054},
	year = {2025},
	orcid-numbers = {Pluhár, Zsuzsa/0000-0003-2688-4652; Gaál, Bence/0000-0001-8771-7140}
}

@mastersthesis{MTMT:36440609,
	title = {Algoritmikus gondolkodás vizsgálata és fejlesztése [Assessment and Enhancement of Algorithmic Thinking]},
	url = {https://m2.mtmt.hu/api/publication/36440609},
	author = {Pluhár, Zsuzsa},
	doi = {10.14232/phd.12602},
	publisher = {Universití of Szeged},
	unique-id = {36440609},
	abstract = {This dissertation focuses on developing a test to assess the algorithmic thinking skills of first-year students in an English-language BSc program, analysing its effectiveness, and designing and evaluating a related development course. The study is particularly relevant as some students entering the English-language BSc Programming program at the Faculty of Informatics, Eötvös Loránd University, demonstrate lower levels of algorithmic thinking than required for successful academic performance. Implementing a diagnostic assessment tool and targeted intervention strategies can help bridge the initial knowledge gap among students, enhancing their chances of academic success. The dissertation first reviews key terminologies related to developments in information and communication technologies (ICT) and examines the evolution and theoretical framework of algorithmic thinking. It introduces a comprehensive model of algorithmic thinking, serving as the theoretical foundation for empirical research. Additionally, the study presents preliminary investigations into young students’ (grades 1–4) use of digital tools and the algorithmic thinking skills of students in grades 5–6, with findings that influenced the test design. The initial version of the algorithmic thinking test was piloted alongside a self-report questionnaire measuring potential background variables (e.g., prior knowledge, language proficiency). Based on the pilot results, the test was refined and revised. To further support students’ skill development, a problem-solving and algorithmic thinking course was also created. The study was conducted over three semesters, involving 137 BSc students. The reliability of the algorithmic thinking test improved compared to the pilot study results; however, the discrimination index of certain items suggested that some tasks were less effective in distinguishing between different skill levels. As expected, the most challenging tasks required students to develop their own algorithms, demonstrating a high level of cognitive demand. While a weak correlation was found between the English proficiency test and the algorithmic thinking test, further analysis of students' programming course results and first-semester academic performance suggests that the remedial course contributes to student progress. Finally, the research examines the impact of the COVID-19 period and presents the improved online version of the test, along with its potential adaptation for other student groups.},
	year = {2025},
	orcid-numbers = {Pluhár, Zsuzsa/0000-0003-2688-4652}
}

@CONFERENCE{MTMT:35506811,
	title = {Egy oktatási robotika projekt hatása az algoritmikus gondolkodásra és a robotikával kapcsolatos attitűdökre},
	url = {https://m2.mtmt.hu/api/publication/35506811},
	author = {Bacsa-Károlyi, Borbála and Pluhár, Zsuzsa and Fehérvári, Anikó and Bereczki, Enikő Orsolya},
	booktitle = {XXIV. Országos Neveléstudományi Konferencia : Absztraktkötet},
	unique-id = {35506811},
	year = {2024},
	pages = {37},
	orcid-numbers = {Bacsa-Károlyi, Borbála/0000-0001-7601-276X; Pluhár, Zsuzsa/0000-0003-2688-4652; Fehérvári, Anikó/0000-0003-4477-7682; Bereczki, Enikő Orsolya/0000-0002-9907-7918}
}

@inproceedings{MTMT:34754688,
	title = {COMPUTATIONAL THINKING AND PROBLEM SOLVING IN THE PISA ERA},
	url = {https://m2.mtmt.hu/api/publication/34754688},
	author = {Bilbao, Javier and Bravo, Eugenio and García, Olatz and Rebollar, Carolina and Dagienė, Valentina and Masiulionytė-Dagienė, Vaida and Jankauskienė, Asta and Laakso, Mikko-Jussi and Kaarto, Heidi and Lehtonen, Daranee and Parviainen, Marika and Güven, Ismail and Gulbahar, Yasemin and Öztürk, Tuğba and Özdemir Öncül, Fatma and Tan Yenigün, Nilüfer and Pluhár, Zsuzsa and Sarmasági, Pál György and Pears, Arnold},
	booktitle = {INTED2024 Conference Proceedings},
	doi = {10.21125/inted.2024.1922},
	unique-id = {34754688},
	year = {2024},
	pages = {7335-7342},
	orcid-numbers = {Pluhár, Zsuzsa/0000-0003-2688-4652; Sarmasági, Pál György/0009-0002-7683-8515}
}