Robert Pinter
Research Subjects
Robert Pinter has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Sanja Maravić Čisar
Subotica Tech-College of Applied Sciences
5 shared publications - Petar Čisar
John von Neumann University
4 shared publications - Attila Kovari
Institute of Digital Technology, Faculty of Informatics, Eszterhazy Karoly Catholic University, Eszterhazy ter 1, H-3300 Eger, Hungary
1 shared publication - Jozsef Katona
Department of Software Development and Application, Institute of Computer Engineering, University of Dunaujvaros, Dunaujvaros, Hungary
1 shared publication - Lenke Major
University of Novi Sad Hungarian Language Teacher Training Faculty, 24000 Subotica, Serbia
1 shared publication - Livia Szedmina
Subotica Tech-College of Applied Sciences
1 shared publication
Latest Publications
- 6 March 2025
- Published by Springer Nature
- p. 239-247
IoT Security for Critical Infrastructure: Challenges and Best Practices
- 6 March 2025
- Published by Springer Nature
- p. 239-247
IoT Security for Critical Infrastructure: Challenges and Best Practices
- 6 September 2022
- Published by Springer Nature
- p. 111-122
Need for Cybersecurity Solutions in IoT Systems
- 6 September 2022
- Published by Springer Nature
- p. 111-122
Need for Cybersecurity Solutions in IoT Systems
- Open Access
- 11 October 2020
- Published by MDPI AG in Applied Sciences
- Vol. 10 (20) , 7044
Case Study: Students’ Code-Tracing Skills and Calibration of Questions for Computer Adaptive Tests
Computer adaptive testing (CAT) enables an individualization of tests and better accuracy of knowledge level determination. In CAT, all test participants receive a uniquely tailored set of questions. The number and the difficulty of the next question depend on whether the respondent’s previous answer was correct or incorrect. In order for CAT to work properly, it needs questions with suitably defined levels of difficulty. In this work, the authors compare the results of questions’ difficulty determination given by experts (teachers) and students. Bachelor students of informatics in their first, second, and third year of studies at Subotica Tech—College of Applied Sciences had to answer 44 programming questions in a test and estimate the difficulty for each of those questions. Analyzing the correct answers shows that the basic programming knowledge, taught in the first year of study, evolves very slowly among senior students. The comparison of estimations on questions difficulty highlights that the senior students have a better understanding of basic programming tasks; thus, their estimation of difficulty approximates to that given by the experts.
- 11 October 2020
- Published by MDPI AG in Applied Sciences
- Vol. 10 (20) , 7044
Open AccessCase Study: Students’ Code-Tracing Skills and Calibration of Questions for Computer Adaptive Tests
Computer adaptive testing (CAT) enables an individualization of tests and better accuracy of knowledge level determination. In CAT, all test participants receive a uniquely tailored set of questions. The number and the difficulty of the next question depend on whether the respondent’s previous answer was correct or incorrect. In order for CAT to work properly, it needs questions with suitably defined levels of difficulty. In this work, the authors compare the results of questions’ difficulty determination given by experts (teachers) and students. Bachelor students of informatics in their first, second, and third year of studies at Subotica Tech—College of Applied Sciences had to answer 44 programming questions in a test and estimate the difficulty for each of those questions. Analyzing the correct answers shows that the basic programming knowledge, taught in the first year of study, evolves very slowly among senior students. The comparison of estimations on questions difficulty highlights that the senior students have a better understanding of basic programming tasks; thus, their estimation of difficulty approximates to that given by the experts.