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001-es BibID:	BIBFORM057886
Első szerző:	Biró Piroska (informatikus, matematikus)
Cím:	Measuring the level of algorithmic skills at the end of secondary education in Hungary / Biró Piroska, Csernoch Mária, Máth János, Abari Kálmán
Dátum:	2015
ISSN:	1877-0428
Megjegyzések:	Students starting their tertiary studies in Informatics are found to have a low level of algorithmic skills and understanding of programming, which leads to the high number of drop out students and failed semesters during their studies. The students' low level of programming skills contrasts with their excellent results in the school leaving exams. To find out the reasons for this wehave launched the TAaAS project (Testing Algorithmic and Application Skills), which focuses on the students' algorithmic skillsand programming ability in traditional and non-traditional programming environments. Our analyses proved that school leavingexams are not able to measure these abilities of the students, and beyond that, are not able to distinguish between the different levels of the students. Students are accepted into the universities and start their studies based on the misleading results of the school leaving exams.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban level of digital thinking algorithmic skills school leaving exams in Informatics and Mathematics
Megjelenés:	Procedia - Social and Behavioral Sciences. - 176 (2015), p. 876-883. -
További szerzők:	Csernoch Mária (1963-) (informatika tanár) Máth János (1959-) (matematikus) Abari Kálmán (1971-) (programtervező matematikus)
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001-es BibID:	BIBFORM058039
Első szerző:	Csernoch Mária (informatika tanár)
Cím:	The power in digital literacy and algorithmic skill / Csernoch Mária, Biró Piroska
Dátum:	2015
ISSN:	1877-0428
Megjegyzések:	We argue that in educational contexts ICT (Information and Communications Technology) and CS (Computer Sciences) should not be separated. To support our ideas, we present methods related to the minimalist principle with which students with different interests would develop algorithmic skills even in an ICT environment, and this introductory phase would lead the students on to more serious CS studies. The core of these methods is that from the very beginning of CSI education algorithms should be looked for in every computer-related problem. Deep-approach metacognitive methods should be applied, instead of uncontrolled sequences of surface-approach metacognitive activities such as aimless clicking, unplanned wandering, and relying on the newest features in graphical user interfaces (GUI). Our team has developed a deep-approach metacognitive method for teaching spreadsheet to novices, which is in accordance with the concept of building algorithms to solve computer-related problems. The three cornerstones of the method are (1) introducing as simple and as few functions as possible, (2) building multilevel formulas based on these functions, and (3) focusing on the problem instead of the features of the software. As the students make progress, the number of functions would be increased, but general purpose functions would still be focused on. Testing our deep-approach method has proved that it is a lot more effective in teaching spreadsheet than the classical surface-approach, wizard-based metacognitive methods, since all the basic elements are in accordance with the minimalist theory, which advises teaching as simple a language as possible for beginners to develop basic algorithmic skills. Beyond the direct advantages of the method, spreadsheet would serve as an introductory language to high level programming languages, which is our ultimate goal.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban deep- and surface-approach metacognitive processes developing algorithmic skill teaching spreadsheet Intelligens város közösségi alkotásból
Megjelenés:	Procedia - Social and Behavioral Sciences. - 174 (2015), p. 550-559. -
További szerzők:	Biró Piroska (1983-) (informatikus, matematikus)
Pályázati támogatás:	TÁMOP-4.2.2.C-11/1/KONV-2012-0001 TÁMOP Adat menedzsment és tudásfeltárás intelligens város alkalmazásokhoz K-105262 OTKA
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