@CONFERENCE{MTMT:34095521,
	title = {viSkillz - a project dealing with Mental Cutting Test exercises},
	url = {https://m2.mtmt.hu/api/publication/34095521},
	author = {Tóth, Róbert and Hoffmann, Miklós and Zichar, Marianna},
	booktitle = {12th International Conference on Applied Informatics (ICAI 2023)},
	unique-id = {34095521},
	year = {2023},
	pages = {1-2},
	orcid-numbers = {Hoffmann, Miklós/0000-0001-8846-232X; Zichar, Marianna/0000-0002-1943-6053}
}

@article{MTMT:33639889,
	title = {viskillz-blender—A Python package to generate assets of Mental Cutting Test exercises using Blender},
	url = {https://m2.mtmt.hu/api/publication/33639889},
	author = {Tóth, Róbert and Tóth, Bálint and Hoffmann, Miklós and Zichar, Marianna},
	doi = {10.1016/j.softx.2023.101328},
	journal-iso = {SOFTWAREX},
	journal = {SOFTWAREX},
	volume = {22},
	unique-id = {33639889},
	issn = {2352-7110},
	abstract = {Several different methods are used to test the spatial abilities or visual skills of people. One of them is the Mental Cutting Test (MCT), the exercises of which offer a 2D projection of a 3D shape and a 2D plane, and testees should determine the shape of their intersection. MCT exercises need various 2D and 3D assets that should be developed before publishing a test. In recent decades, very few exercises have been available to instructors and researchers. In 2019, we published our first solution that could be used to calculate the intersections of MCT scenarios, then render or export their assets using Blender. This paper proposes an extended, open-source package for Blender that generates assets of MCT exercises by permuting predefined shapes, cutting planes, rotation, and scale operators. The additional wrapper script helps users use the package for various purposes, such as developing exercise offering methods, designing exercises, practicing, or organizing exams and measurements.},
	year = {2023},
	eissn = {2352-7110},
	orcid-numbers = {Tóth, Róbert/0000-0002-7583-7433; Hoffmann, Miklós/0000-0001-8846-232X; Zichar, Marianna/0000-0002-1943-6053}
}

@article{MTMT:33573320,
	title = {Lossless Encoding of Mental Cutting Test Scenarios for Efficient Development of Spatial Skills},
	url = {https://m2.mtmt.hu/api/publication/33573320},
	author = {Tóth, Róbert and Hoffmann, Miklós and Zichar, Marianna},
	doi = {10.3390/educsci13020101},
	journal-iso = {EDUC SCI},
	journal = {EDUCATION SCIENCES},
	volume = {13},
	unique-id = {33573320},
	issn = {2227-7102},
	abstract = {In the last decade, various mobile applications have been developed to improve and measure spatial abilities using different spatial tests and tasks through augmented reality (AR), Virtual Reality (VR), or embedded 3D viewers. The Mental Cutting Test (MCT) is one of the most well-known and popular tests for this purpose, but it needs a vast number of tasks (scenarios) for effective practice and measurement. We have recently developed a script-aided method that automatically generates and permutes Mental Cutting Test scenarios and exports them to an appropriate file format (to GLB (glTF 2.0) assets) representing the scenarios. However, the significant number of permutations results in more than 1,000,000 assets, requiring more than 6 GB of storage space. This paper introduces an encoding scheme consisting of four stages to handle this issue through significantly reducing the storage space, making the app suitable for everyday individual use, even on a mobile phone. The proposed method encodes a subset of assets from which it can decode the whole dataset with 3% time complexity compared to classical Blender’s computations, exceeding the compression ratio of 10,000 and storage space saving 99.99%. This paper explains the features of the original assets, introduces the encoding and decoding functions with the format of documents, and then measures the solution’s efficiency based on our dataset of MCT scenarios.},
	year = {2023},
	orcid-numbers = {Tóth, Róbert/0000-0002-7583-7433; Hoffmann, Miklós/0000-0001-8846-232X; Zichar, Marianna/0000-0002-1943-6053}
}

@inproceedings{MTMT:33066496,
	title = {Educational Applications to Support the Teaching and Learning of Mental Cutting Test Exercises},
	url = {https://m2.mtmt.hu/api/publication/33066496},
	author = {Tóth, Róbert and Tóth, Bálint and Zichar, Marianna and Fazekas, Attila and Hoffmann, Miklós},
	booktitle = {Proceedings of the 20th International Conference on Geometry and Graphics, ICGG 2022},
	doi = {10.1007/978-3-031-13588-0_81},
	unique-id = {33066496},
	abstract = {Developing or measuring the spatial skills of people is still an interesting research topic nowadays. Well-known assignments such as the exercises of Mental Cutting Test are still popular tools of performing measurements or validating the knowledge of our students. However, we found that researchers, instructors and students are not entirely supported with tools that can be used to enhance their processes. In this paper, we present a resource browser and a quiz application, that might be useful for people who have to deal with Mental Cutting Test exercises.},
	keywords = {assets; Mental Cutting Test; Quiz},
	year = {2023},
	pages = {928-938},
	orcid-numbers = {Zichar, Marianna/0000-0002-1943-6053; Fazekas, Attila/0000-0001-6893-3067; Hoffmann, Miklós/0000-0001-8846-232X}
}

@inproceedings{MTMT:33066494,
	title = {Detecting and Correcting Errors in Mental Cutting Test Intersections Computed with Blender},
	url = {https://m2.mtmt.hu/api/publication/33066494},
	author = {Tóth, Róbert and Tóth, Bálint and Zichar, Marianna and Fazekas, Attila and Hoffmann, Miklós},
	booktitle = {Proceedings of the 20th International Conference on Geometry and Graphics, ICGG 2022},
	doi = {10.1007/978-3-031-13588-0_79},
	unique-id = {33066494},
	abstract = {Mental Cutting Test is a widely used format to develop or measure the spatial skills of people in various situations, having different purposes. An exercise consists of a 2D projection of a 3D shape and an intersection plane, denoted by a frame. The task is to choose the shape of their intersection from the set of five shapes. In this paper, we investigate a great number of different shapes that are rendered with Blender, containing various errors that change the basic morphological features of the shapes. After a human-based validation process, we developed a post-processing Python script which detects and corrects the issues of the automatically generated intersections.},
	keywords = {Blender; post-processing; Mental Cutting Test},
	year = {2023},
	pages = {904-916},
	orcid-numbers = {Zichar, Marianna/0000-0002-1943-6053; Fazekas, Attila/0000-0001-6893-3067; Hoffmann, Miklós/0000-0001-8846-232X}
}

@inproceedings{MTMT:32371973,
	title = {Vízminőségi indexek vizualizációs lehetőségei KML leíró nyelv alkalmazásával. Visualization of Water Quality Index using Keyhole Markup Language},
	url = {https://m2.mtmt.hu/api/publication/32371973},
	author = {Balla, Dániel and Zichar, Marianna and Tóth, Róbert and Kiss, Emőke and Karancsi, Gergő and Lázár, Vilmos and Baranyi, Imre and Mester, Tamás},
	booktitle = {LXII. Georgikon Napok konferenciakötet},
	unique-id = {32371973},
	year = {2021},
	pages = {1-6},
	orcid-numbers = {Balla, Dániel/0000-0002-8051-1518; Zichar, Marianna/0000-0002-1943-6053}
}

@article{MTMT:31938849,
	title = {Script-aided generation of Mental Cutting Test exercises using Blender},
	url = {https://m2.mtmt.hu/api/publication/31938849},
	author = {Tóth, Róbert},
	doi = {10.33039/ami.2021.03.011},
	journal-iso = {ANN MATH INFORM},
	journal = {ANNALES MATHEMATICAE ET INFORMATICAE},
	volume = {54},
	unique-id = {31938849},
	issn = {1787-5021},
	year = {2021},
	eissn = {1787-6117},
	pages = {147-161}
}

@inproceedings{MTMT:31687556,
	title = {Improving and Measuring Spatial Skills with Augmented Reality and Gamification},
	url = {https://m2.mtmt.hu/api/publication/31687556},
	author = {Tóth, Róbert and Zichar, Marianna and Hoffmann, Miklós},
	booktitle = {ICGG 2020 - Proceedings of the 19th International Conference on Geometry and Graphics},
	doi = {10.1007/978-3-030-63403-2_68},
	unique-id = {31687556},
	year = {2021},
	pages = {755-764},
	orcid-numbers = {Zichar, Marianna/0000-0002-1943-6053; Hoffmann, Miklós/0000-0001-8846-232X}
}

@{MTMT:31757768,
	title = {Visualization of Water Quality Index using Keyhole Markup Language},
	url = {https://m2.mtmt.hu/api/publication/31757768},
	author = {Balla, Dániel and Zichar, Marianna and Tóth, Róbert and Kiss, Emőke and Gergő, Karancsi and Vilmos, Lázár and Imre, Baranyi and Mester, Tamás},
	booktitle = {LXII. Georgikon Napok Nemzetközi Tudományos Konferencia},
	unique-id = {31757768},
	year = {2020},
	pages = {12},
	orcid-numbers = {Balla, Dániel/0000-0002-8051-1518; Zichar, Marianna/0000-0002-1943-6053}
}

@CONFERENCE{MTMT:31634271,
	title = {Motivating students’ study with ICT},
	url = {https://m2.mtmt.hu/api/publication/31634271},
	author = {Tóth, Róbert and Hoffmann, Miklós and Kósa, Márk Szabolcs and Zichar, Marianna},
	booktitle = {Proceedings of the 11th International Conference on Applied Informatics (ICAI 2020)},
	unique-id = {31634271},
	year = {2020},
	orcid-numbers = {Hoffmann, Miklós/0000-0001-8846-232X; Zichar, Marianna/0000-0002-1943-6053}
}