Research

FITPED-AI (2021-2024)

The project team published the following scientific papers where the team presents the findings and experience with the realisation of the project FITPED-AI. The following papers have been already accepted and published in the journals and proceedings, which are indexed in the Scopus and Web of Science Databases:

Scientific Papers Published in 2023

• Pecuchova, J. & Drlik, M. (2023). The Importance of Selected LMS Logs Pre-processing Tasks on the Performance Metrics of Classification Models. In: Singh, Y., Verma, C., Zoltán, I., Chhabra, J.K., Singh, P.K. (eds) Proceedings of International Conference on Recent Innovations in Computing. ICRIC 2022. Lecture Notes in Electrical Engineering, vol 1011. Springer, Singapore. https://doi.org/10.1007/978-981-99-0601-7_11
• Pecuchova, J. & Drlik, M. (2023). Predicting Students at Risk of Early Dropping Out from Course Using Ensemble Classification Methods. Procedia Computer Science. KES2023 – 27th Annual KES Conference, Athens, Greece, 6-8 September 2023 (accepted)
• Drlik, M. – Skalka, J. – Pecuchova, J. (2023). Identification of Students with Similar Progress in Automated Programming Assignments in the Micro-Learning Environment. Procedia Computer Science. KES2023 – 27th Annual KES Conference, Athens, Greece, 6-8 September 2023 (accepted)

Scientific Papers Published in 2022

• Skalka, J. & Drlik, M. (2022). Proposal of Artificial Intelligence Educational Model Using Active Learning in a Virtual Learning Environment. DOI 10.34916/el.2022.14.02. In: E-learning : E-learning, vol. 14 / Eugenia Smyrnova-Trybulska. – Katowice : University of Silesia in Katowice, 2022. – ISBN 978-83-66055-31-5. – ISSN 2451-3644, p. 15-28.
• Pecuchova, J. & Drlik, M. (2022). Identification of Students With Similar Behavioural Patterns Using Clustering Techniques. DOI 10.34916/el.2022.14.09. In: E-learning : E-learning, vol. 14 / Eugenia Smyrnova-Trybulska. – Katowice : University of Silesia in Katowice, 2022. – ISBN 978-83-66055-31-5. – ISSN 2451-3644, p. 257-267.
• Kuzminska, O. – Morze, N. – Smyrnova-Trybulska, E. (2022). Artificial Intelligence in Education: A Study on Using Bibliometric Systems. DIVAI 2022 – The 14th international scientific conference on Distance Learning in Applied Informatics. ISBN 978-80-7676-410-1 ISSN 2464-7470 (Print) ISSN 2464-7489 (On-line), p. 393-403.
• Pecuchova, J. (2022). The Issues Related to Preprocessing Educational Datasets for Improving Student’s Performance. DIVAI 2022 – The 14th international scientific conference on Distance Learning in Applied Informatics. ISBN 978-80-7676-410-1 ISSN 2464-7470 (Print) ISSN 2464-7489 (On-line), p. 424-431.
• Popovych, V. & Drlik, M. (2022) Towards Development of Data Architecture for Learning Analytics Projects Using Data Engineering Approach. 4th International Conference on Computing Communication and Cyber Security (IC4S-2022), Springer. 2022. (In press)

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FITPED (2018-2022)

Scientific Monograph Published in 2022

Intellectual Output O17 – Contemporary Didactics, Methods and Technologies of Teaching Programming Using Microlearning and Automated Source Code Evaluation eds. E. Smyrnova-Trybulska, P. Kommers, M. Drlik, J. Skalka, . Preprints of the articles submitted to the Springer Verlag Publisher.  

• Table of the Content
• Preprints (19 MB)

Scientific Papers Published in 2021

The project team published the following scientific papers in indexed journals and participated in several international conferences during 2021, where the team presents the findings and experience with the realisation of the project FITPED. The following papers have been already accepted and published in the journals and proceedings, which are indexed in the Scopus and Web of Science Databases:

• Skalka, J. et al. (2021). Conceptual Framework for Programming Skills Development Based on Microlearning and Automated Source Code Evaluation in Virtual Learning Environment. Sustainability. 2021,13(6), 3293 (Q2, IF = 2,579 ), dataset
• Kabáthová, J. & Drlik, M. (2021).  Towards Predicting Student’s Dropout in University Courses Using Different Machine Learning Techniques. Appl. Sci. 2021, 11(7), 3130. (Q2, IF=2,474)

Scientific Papers Published in 2020

The project team published the following scientific papers in indexed journals and participated in several international conferences during 2020, where the team presents the progress and intellectual outputs of the project FITPED. The following papers have been already accepted and will be published in the journals and proceedings, which are indexed in the Scopus and Web of Science Databases:

• Skalka, J. et al. (2020). Architecture Proposal for Micro-Learning Application for Learning and Teaching Programming Courses. IEEE Global Engineering Education Conference, EDUCON, April-2020.
• Skalka, J. & Drlik, M. (2020). Automated Assessment and Microlearning Units as Predictors of At-Risk Students and Students’ Outcomes in the Introductory Programming Courses. Appl. Sci. 2020, 10(13), 4566; (Q2, IF = 2,474)

Scientific Papers Published in 2019

The project team participated in several international conferences during 2019. The authors also presented several important aspects of the project FITPED in the indexed journals. The following papers have been already published in indexed in the Scopus and Web of Science Databases:

• Kapusta, J. et al. (2019). User Identification in the Process of Web Usage Data Preprocessing. International Journal of Emerging Technologies in Learning (iJET), [S.l.], v. 14, n. 09, p. pp. 21-33, May. 2019. ISSN 1863-0383. 
• Skalka J., Drlik M. & Obonya, J. (2019). Automated assessment in learning and teaching programming languages using virtual learning environment. (2019) IEEE Global Engineering Education Conference, EDUCON, April-2019, art. no. 8725127, pp. 689-697. 

Conference Papers Published in 2018

The project team participated in several international conferences during 2018. The authors presented several important aspects of the project FITPED. The following papers have been published in the proceedings, which are indexed in the Scopus and Web of Science Databases:

• Skalka, J. & Drlík, M. (2018). Educational Model for Improving Programming Skills based on Conceptual Microlearning Framework. In: ICL 2018. 21th International Conference on Interactive Collaborative Learning, 25-28 September 2018, Kos Island, Greece, p. 490-501 – ISSN 2194-5357.
• Skalka, J. & Drlík, M. (2018). Priscilla – Proposal of System Architecture for Programming Learning and Teaching Environment. In: The IEEE 12th International Conference Application of Information and Communication Technologies 17-19 Oct 2018. Almaty, Kazakhstan. ISBN 978-1-5386-0501-1.
• Skalka, J. (2018). Data processing methods in the development of the microlearning-based framework for teaching programming languages. In: DIVAI 2018: Proceedings from 12th International Scientific Conference on Distance Learning in Applied Informatics, Štúrovo 2. – 4. May 2018; Eds. Milan Turčáni et al. – 1. ed. – Praha: Wolters Kluwer ČR, 2018. P. 504-511 – ISBN 978-80-7598-059-5.
• Obonya, J. & Kapusta, J. (2018). Identification of Important Activities for Teaching Programming Languages by Decision Trees. In: DIVAI 2018: Proceedings from 12th International Scientific Conference on Distance Learning in Applied Informatics, Štúrovo 2. – 4. May 2018; Eds. Milan Turčáni et al. – 1. ed. – Praha: Wolters Kluwer ČR, 2018. – P. 481-490. – ISBN 978-80-7598-059-5.
• Obonya, J. & Kapusta, J. (2018). Data visualization to discover the activity and changing the teachers’ point of view in a particular LMS system. In: 12th International Technology, Education and Development Conference in Valencia, Spain. 5-7 March 2018. P. 4608-4613. ISBN: 978-84-697-9480-7 / ISSN: 2340-1079.
• Skalka, J. & Drlík, M. (2018). Conceptual framework of microlearning-based training mobile application for improving programming skills. In: Advances in Intelligent Systems and Computing: IMCL 2017. 11th International Conference on Interactive Mobile Communication Technologies and Learning, Thessaloniki; Greece; – Berlín: Springer Verlag, 2018. – ISBN 978-331975174-0. – ISSN 2194-5357, Vol. 725, p. 213-224.DOI 10.1007/978-3-319-75175-7_22.