=Paper=
{{Paper
|id=Vol-2650/paper31
|storemode=property
|title=Students’ Knowledge in File Management After Elementary School
|pdfUrl=https://ceur-ws.org/Vol-2650/paper31.pdf
|volume=Vol-2650
|authors=Katalin Sebestyén
|dblpUrl=https://dblp.org/rec/conf/icai3/Sebestyen20
}}
==Students’ Knowledge in File Management After Elementary School==
Proceedings of the 11th International Conference on Applied Informatics Eger, Hungary, January 29–31, 2020, published at http://ceur-ws.org Students’ Knowledge in File Management After Elementary School Katalin Sebestyén University of Debrecen, Doctoral School of Informatics 26 Kassai út, Debrecen 4028, Hungary sebestyen.katalin@inf.unideb.hu Abstract According to the Hungarian Frame Curriculum, teaching informatics starts in grade 6 as a compulsory subject, with only one class a week. By this time students are regular smartphone and/or computer users, primarily applying trial-and-error based computer problem-solving methods. In this way they gain knowledge through their own experiences and observations, without any guidance. In the Frame Curriculum the first topic is file man- agement, which is the basis of operating system use and further data-handling procedures. Due to the late introduction of informatics in schools and the different levels of knowledge that students bring into the classes this topic is difficult to teach. In addition, this topic is not sufficiently emphasized and practiced, since both students and teachers consider it to consist of elemen- tary, born-with knowledge. Consequently, students evaluate their knowledge as high, but practice does not justify this assessment. Our research team invented and applied a knowledge-transfer based webtable-datatable conversion process to cover file-, elementary data- and webpage-management. In order to quantify and prove the efficiency of the method, we tested grade 9 students in experimental and control groups, cov- ering the topic with our novel and with traditional methods, respectively. During the research period, the students were tested in two rounds: in a pre-test, before they studied the topic to record what knowledge is brought into classes, and in a post-test, after the intervention. The test included tasks involving error message interpretation, recognizing file types based on default associations and conventions, explaining algorithms, and handling data files. This article presents the results of students in the pre-test administered in grade 9, starting their secondary education. It was found that when studying this topic with the trial-end-error methods, students do not build up knowl- edge in long-term memory, cannot see the algorithms behind fundamental Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). 296 file management processes, and consequently cannot solve real-world prob- lems effectively. These results clearly show that there is a need for changes in the approaches adopted to file management. Keywords: IT education, file management, elementary school 1. Introduction The Hungarian Frame Curricula [1][2] is developed on the basis of the National Base Curricula [3]. These documents tend to follow Prensky’s [4] ideas, i.e. that the members of the Z-generation are digital natives, so they do not need ICT (In- formation and Communications Technology) education. This resulted in a drastic reduction in the number of ICT classes in the Frame Curricula. The number of classes decreased from 9.5 [1] to 5 [2], while the amount of knowledge items present in the curricula remained unchanged. This drastic decrease may be the reason that teachers neglect the proper teaching of file management. The results of PISA 2009 Students On Line [5] clearly shows that the Frame Curricula and the traditional methods do not develop the students’ digital literacy, or their algorithmic and computational thinking skills efficiently in Hungary. The country is ranked 15th of the 19 participating countries. Furthermore, analyzing the connection between the students’ PISA scores and computer use at schools reveals that in this respect Hungarian students are the weakest. According to researchers [6][7][8][9], computational thinking is the fourth basic skill along-side writing, reading and mathematics. Consequently, like the other three skills, it should be improved and be a part of the core fundamentals of education [10][11][12]. Furthermore, ICT education should not focus on tool-, interface-, and environment-usage, but rather on problem-solving with an algo- rithmic focus [10][13]. Settle’s [14] work at the Lab Schools demonstrates that computational thinking can be integrated into high-school courses. She considers the application and integration of computational thinking especially important in non-computational environments as well [14]. 2. Students’ knowledge of file management The aim of this testing is to measure the students’ algorithmic and computational thinking skills through knowledge-transfer elements connected to file management at the beginning of their secondary education. 2.1. Participants, sample We tested first-year secondary school students’ file management skills in grade 9. The measurement involved two schools in Hungary. Considering all groups, 109 students completed the pre-test. 297 2.2. Previous studies In 2018 a Mini-Competence Test [15][16] with similar tasks was conducted in 93 schools with 8,880 participants. Students from grades 7 to 10 took part in the measurement. In this paper we only focus on the data of grade 7 and 8 elemen- tary school students of the previous test, 1,562 and 1,643 students, respectively. The measurement included a self-evaluation part where the students were asked to mark how familiar they are with the given ICT topics, including file management (Figure 1). Figure 1: An extract of the Mini-Competence Test self-evaluation part, inquiring about familiarity with the file management topic Figure 2 reflects the results of the file management topic in the self-evaluation task. No significant differences were revealed between grade 7 and 8 students. Most of them (79.06%) choose options 3, 4 or 5, (good, very good and excellent, respectively). Note, that 32.64% of the students selected the highest (5) option. Figure 3 shows the proportion of respondents who studied file management in school, with 14.72% of grade 7 and 8 students admitting that they did not study file management in school. In the diagram on Figure 6, the correlations between the students’ answers for both their knowledge level and for the source of their knowledge are presented. Most of the students marking 3, 4, or 5 also indicated that a high proportion of them studied the topic in schools: 80%, 30.33%, 37.59%, respectively. Interestingly, those students who do not study file management in school are confident they have knowledge of this topic (mark 4-5: 40.04%). This leads to the conclusion that despite having studied the topic, the students do not necessarily feel that they have mastered the topic. 298 Figure 2: The self-assessment results of grade 7 and 8 students regarding the topic of file management Figure 3: The results of students’ answers for the self-assessment task considering whether they studied file management in school or not 2.3. Measuring prior file management knowledge in grade 9 2.3.1. Tasks and results Task F1 (section 4) was about the interpretation of the Windows file rename warn- ing message, where students had to choose from a number of given answers. Note that we allowed students to mark multiple answers, while only one of them was correct. 4.59% of the students marked only the correct answer; considering mul- 299 tiple selections, the correct answer was chosen in the lowest proportion (15.60%) (Figure 4). The high proportion of incorrect answers shows that students have no knowledge about data file types and the role of extensions. Figure 4: The distribution of the selected answers in Task F1 This statement is further supported by the results of Task F2: “What happens when we double-click on a document file?”. Based on the answers, the students are only familiar with the last step (opening) of the 4-step process. This is in accordance with the results of Task F1, as students are not only unfamiliar with the roles of extensions, but with their connection with the operating system, as well. In Task F3 the students had to provide an answer as to how a spreadsheet can be converted into a text file. Despite the task stating that only one answer was to be selected, 8.26% of the students ignored this instruction (Table 1). 38.53% of the students marked the correct answer together with others, while only 35.78% marked only the correct option (Table 1). Task F4 inquired about the cut file operation: “What happens when you cut a file?”. Similarly to the previous tasks, the students had to choose their answers from the listed options. We allowed multiple selections even though that there was only one correct answer. 35.78% of the students completed this task successfully, while 35.90% marked the correct answer besides other options (Table 2). In Task F5, the students had to decide the types of the listed files, considering their names and extensions. Based on Tasks F1 and F2, we have found that the students are not familiar with the definition of various extensions. The results of the current task support and extend this finding. This can be explained by the widespread use of the File Explorer present in Windows systems, where the extensions of the files are hidden by default. We accepted the options listed in the second row of Table 3 as correct solutions (if the students only marked one answer). 37.31% of the students completed the 300 Table 1: The distribution of answers in Task F3, highlighting the correct answers. Table 2: The distribution of student wrong answers along with the correct answer in Task F4 Figure 5: The number of correctly recognized the file types in Task F5 task (Table 6). Based on the diagram shown in Figure 5, there were no students who provided correct answers for each file. Most of them recognized two or three 301 Table 3: The correct solutions and the proportions of student an- swers in Task F5 file types correctly. Table 4: The solutions for Task F6 and the proportion of correct answers. To analyze the connection between the answers, we conducted a correlation analysis using Guilford’s approach [17]. Based on our matrix, no solid correla- tion could be found except “low correlation, relationship definite but small” [17] occurrences (±0.2–0.4). We designed Task F6 to have multiple questions inquiring about the same knowledge items using differing approaches and phrasing. In this way we could gather data about the conscious choices and reliable knowledge of students. Each question could be answered with the following options: true, false or I don’t know (Table 4). In summary, 42.05% of the students completed the task correctly. Table 5 shows the knowledge items required for solving Task F6. The stu- dents had to be familiar with the concept of extensions, assignment, file types and opening, editing and saving files. Table 5 shows which statements rely on what knowledge items. We expected correlations between answers for statements relying on the same items. We completed a correlation analysis of the answers, considering the knowledge items required for the solution. The results show a weak correlation between the answers (below 0.4). Interestingly, we could not find any connection between the 302 Table 5: The knowledge items required (marked with +) for cor- rectly answering the statements Table 6: The rate of correct answers for each task in the file man- agement test correlations and the knowledge items, as the results of the analysis yielded a ran- domized pattern. To summarize the results for each task, Table 6 shows the correct completion rates of the file management test. The students completed the test with varying results. Considering the whole test, 32.34% of them completed it successfully, which is a lower proportion than the results expected on the basis of the self-assessment test in section 2.2 (p=0.000). The results of the file management test have been converted to a scale of 0-5 (Figure 7) to make them comparable to the results of the Mini-Competence Test (Figure 6). Most of the students have confidence in their knowledge, despite the fact that in the file management test none of them reached knowledge level four. 303 Figure 6: The summarized results in the file management self- assessment task and the proportion of those studying the topic at school Figure 7: The results of the file management test displayed on a scale of 0-5 3. Conclusion ICT education start as a mandatory subject in grade 6 in Hungary with 1 class per week. By that time, students are regular users of smartphones, laptops, and/or desktop computers. It follows that they met and started learning the topic of file management by themselves. This leads to students showing unsupported confi- dence when the topic first emerges in grade 6, causing the class to move forward to 304 different topics after a brief introduction. The results of the self-assessment part of the Mini-Competence Test show that students are overconfident about their knowl- edge. This shows a connection with the results of the PISA 2009 measurement. The results of our file management test and measurement shows that the stu- dents lack basic knowledge in the topic, such as extensions, cut, file type, etc. As these items are frequently revisited and required in ICT education and in everyday computer use as well, this deficiency cannot be ignored. Furthermore, the knowl- edge students do have is fragmented, which resulted in randomized answers in the test. Moreover, their answers were inconsistent and showed no correlation in tasks requiring the same knowledge items. The students (as digital natives) after completing primary education – with a minimum of 3 years of ICT education – do not possess the required level of knowledge of file management that would enable the conscious use of file operations and data handling. Therefore, the optimal and effective use of the available ICT lessons is recommended, but this can only be possible with novel approaches. The file management topic demands a greater emphasis within the wider subject area, accompanied by the correct and accurate use of the terminology. Acknowledgements. This work was supported by the construction EFOP-3.6.3- VEKOP-16-2017-00002. The project was supported by the European Union, co- financed by the European Social Fund. References [1] OFI (2008). Frame Curricula In Hungarian: Kerettanterv. 2/2008.(II.8.) számú OKM rendelet – a kerettantervek kiadásának és jóváhagyásának rendjéről. Retrieved 12/12/2019 from http://www.nefmi.gov.hu/kozoktatas/tantervek/ oktatasi-kulturalis [2] OFI (2012). In Hungarian: Kerettanterv. 51/2012. (XII. 21.) számú EMMI rendelet – a kerettantervek kiadásának és jóváhagyásának rendjéről. Retrieved 12/10/2018 from http://kerettanterv.ofi.hu/ [3] NAT 2012 (2012). 110/2012. (VI. 4.) Korm. rendelete a Nemzeti alaptan- terv kiadásáról, bevezetéséről és alkalmazásáról. Retrieved 12/06/2018 from http://ofi.hu/sites/default/files/attachments/mk_nat_20121.pdf [4] Prensky, Marc (2001). Digital Natives, Digital Immigrants. On the Horizon. MCB University Press, Vol. 9 No. 5, October 2001. [5] OECD (2011). PISA 2009 Results: Students on Line: Digital Technologies and Performance (Volume VI) [6] Ben-Ari, M. (1999).Bricolage Forever! PPIG 1999. 11th Annual Workshop. 5–7 January 1999. Computer-Based Learning Unit, University of Leeds, UK. Retrieved: 12. 03. 2015. from http://www.ppig.org/papers/11th-benari.pdf [7] Sysło, M. M. & Kwiatkowsa, A. B. (2015). Informatics for All High School Stu- dents: A Computational Thinking Approach. In Informatics in Schools. Sustainable 305 Informatics Education for Pupils of all Ages. ISSEP 2013. Lecture Notes in Computer Science, vol 7780. pp 43-56. [8] Wing, J. M. (2006).Computational thinking. Communications of the ACM, 49(3), pp 33-35 [9] Wing, J.M. (2008). Computational thinking and thinking about computing. Phil. Trans. R. Soc. A 366, 3717–372 [10] Csernoch, M. (2019). From webtables to datatable. EuSpRiG 2019 Conference, London, accepted [11] Csernoch, M., Biró, P., Máth, J. & Abari, K. (2015). Testing Algorithmic Skills in Traditional and Non-Traditional Programming Environments. Informatics in Education, 2015, 14(2), pp. 175–197. DOI: http://doi.org/10.15388/infedu. 2015.11. [12] Kirschner, P. A & De Bruyckere, P. (2017). The myths of the digital native and the multitasker, Teaching and Teacher Education. 67 (2017), pp 135-142 [13] Wilson, C & Sudol, L. A. & Stephenson, C. & Stehlik, M. (2010). Running on Empty: The Failure to Teach K-12 Computer Science in the Digital Age. ACM, CSTA (2010) [14] Settle et al. (2012). Infusing Computational Thinking into the Middle- and High- School Curriculum. In: ITiCSE 2012, Haifa, Israel, pp. 22–27 [15] Nagy T. K. (2018). 7-10. évfolyamos tanulók tudástranszfer alapú számítógépes gondolkodásának elemzése reprezentatív felmérés alapján. Debreceni Egyetem Infor- matikai Kar Tudományos Diákköri Konferencia 2018.11.15. [16] Nagy, T. K. (2019). Tantárgyközi kapcsolatok és tudástranszfer elemek az adatkezelésben. Debreceni Egyetem Informatikai Kar Tudományos Diákköri Kon- ferencia 2019.11.14. [17] Guilford, J. P. (1950). Fundamental Statistics in Psychology and Education. 2nd ed. New York: McGraw 306 4. Appendix 307 308