Teaching Additional Programming Languages on the Basis of Mapping in the System of Professional Development of Computer Science Teachers
Abstract
The quality of acquired IT knowledge and Uniform State Exam (USE) results in informatics can be higher if students learn additional languages with broader capabilities in addition to the main programming language. The research is aimed at finding didactic technologies that allow expanding the range of programming languages studied by schoolchildren, which complements the professional skills of computer science teachers. On the basis of the matching mechanism and the block-modular principle of organizing the teaching material, the paper proposes a model of technology for teaching programming languages based on the matching approach, including normative-target, content, procedural and result modules. Typical algorithmic constructions corresponding to the main didactic lines of teaching programming to schoolchildren are singled out. The schemes of comparison of similar construction for Pascal and Python programming languages have been developed, templates of training tasks corresponding to the schemes of comparison have been designed. The questionnaire survey of students of advanced training courses (tutors-teachers of computer science of Krasnodar region), which revealed their readiness to study the technology of mastering additional programming languages with the use of matching schemes, was conducted. It is concluded that the use of matching schemes in the practical activity of a teacher reduces the time of learning a second programming language, forms an integrated approach to the study of algorithmic techniques, expands the professional skills of computer science teachers, and, therefore, the corresponding technology can be included in the content of the system of professional development of teachers.
References
2. Bosova L.L. Modern approaches and innovative practices in teaching school informatics. Pedagogy of Computer Science. 2020;(1):1-28. (In Russ., abstract in Eng.) EDN: XUEYHZ
3. Minina I.V., Petukhova T.P. About personification of teaching schoolchildren programming. Modern Information Technologies and IT-Education. 2018;14(4):986-993. (In Russ., abstract in Eng.) https://doi.org/10.25559/SITITO.14.201804.986-993
4. Herrero-Álvarez R., Miranda G., León C., Segredo E. Engaging Primary and Secondary School Students in Computer Science Through Computational Thinking Training. IEEE Transactions on Emerging Topics in Computing. 2023;11(1):56-69. https://doi.org/10.1109/TETC.2022.3163650
5. Omarova G.R., Shimov I.V. Modern programming languages for teaching students programming. Aktual'nye voprosy prepodavanija matematiki, informatiki i informacionnyh tehnologij = Topical issues of teaching mathematics, informatics and information technologies. 2018;(3):270-275. (In Russ., abstract in Eng.) EDN: UORVGR
6. Tretiakov O.A., Fedorkevich E.V. Choosing the first language for teaching programming. World of Science. Pedagogy and psychology. 2020;8(5):44. (In Russ., abstract in Eng.) EDN: JMQMKX
7. Sorochinsky M.A., Belolyubsky M.M. Preparation for the Unified State Exam in Computer Science and ICT: An Overview of Tasks and Problem Solving Based on the Python Programming Language. International Research Journal. 2021;(8-3):114-117. (In Russ., abstract in Eng.) https://doi.org/10.23670/IRJ.2021.110.8.097
8. Arkhipova A.I., Grushevskiy S.P. [On the specifics of additional pedagogical training in education informatization programs]. Shkol'nye gody = School years. 2011;(39):5-7. (In Russ., abstract in Eng.) EDN: TDRQIV
9. Boronenko T.A., Fedotova V.S. Digital Mentoring: are teachers ready to participate in the formation of schoolchildren's digital literacy? Yaroslavl pedagogical bulletin. 2020;(4):33-44. (In Russ., abstract in Eng.) https://doi.org/10.20323/1813-145X-2020-4-115-33-44
10. Vezirov T.G., Babayan A.V. Formation of Digital Literacy of a Modern Teacher. Pedagogical Journal. 2021;11(1-1):336-340. (In Russ., abstract in Eng.) https://doi.org/10.34670/AR.2021.42.41.041
11. Verbitsky A.А. Digital Learning: Problems, Risks and Prospects. Homo Cyberus. 2019;1(6):135-141. (In Russ., abstract in Eng.) EDN: YJYUHG
12. Robert I.V., Mukhametzyanov I.Sh., Kastornova V.A. Informacionno-obrazovatel'noe prostranstvo [Information and educational space]. Hroniki ob#edinennogo fonda jelektronnyh resursov Nauka i obrazovanie = Chronicles of the joint electronic resources Fund Science and education. 2018;(1):41. (In Russ.) https://doi.org/10.12731/ofernio.2017.23455
13. Margaritis M., Magenheim J., Hubwieser P., Berges M., Ohrndorf L., Schubert S. Development of a competency model for computer science teachers at secondary school level. In: 2015 IEEE Global Engineering Education Conference (EDUCON). Tallinn, Estonia: IEEE Press; 2015. p. 211-220. https://doi.org/10.1109/EDUCON.2015.7095973
14. Kamalov F., Santandreu Calonge D., Gurrib I. New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability. 2023;15(16):12451. https://doi.org/10.3390/su151612451
15. Dobrovolskaya N.Yu., Garkusha O.V. Research of the Readiness of Computer Science Teachers to Study Visual Programming in the Framework of Additional Education. Nauchnoe obespechenie sistemy povyshenija kvalifikacii kadrov = Scientific support of a system of advanced training. 2022;(1):115-125. (In Russ., abstract in Eng.) EDN: FXXEET
16. Cervetti G.N., Fitzgerald M.S., Hiebert E.H., Hebert M. Meta-Analysis Examining the Impact of Vocabulary Instruction on Vocabulary Knowledge and Skill. Reading Psychology. 2023;44(6):672-709. https://doi.org/10.1080/02702711.2023.2179146
17. d’Anjou B., Bakker S., An P., Bekker T. How Peripheral Data Visualisation Systems Support Secondary School Teachers during VLE-Supported Lessons. In: Proceedings of the 2019 on Designing Interactive Systems Conference (DIS '19). New York, NY, USA: Association for Computing Machinery; 2019. p. 859-870. https://doi.org/10.1145/3322276.3322365
18. Haug B.S., Mork S.M. Taking 21st century skills from vision to classroom: What teachers highlight as supportive professional development in the light of new demands from educational reforms. Teaching and Teacher Education. 2021;100:103286. https://doi.org/10.1016/j.tate.2021.103286
19. Salas-Pilco S.Z., Xiao K., Hu X. Artificial Intelligence and Learning Analytics in Teacher Education: A Systematic Review. Education Sciences. 2022;12(8):569. https://doi.org/10.3390/educsci12080569
20. Sheridan K.M., Wen X. Evaluation of an Online Early Mathematics Professional Development Program for Early Childhood Teachers. Early Education & Development. 2020;32(1);98-112. https://doi.org/10.1080/10409289.2020.1721402
21. Tzovla E., Kedraka K., Karalis T., Kougiourouki M., Lavidas K. Effectiveness of in-service elementary school teacher professional development MOOC: An Experimental research. Contemporary Educational Technology. 2021;13(4):ep324. https://doi.org/10.30935/cedtech/11144
22. Ozcan M.S, Çetinkaya E., Goksun T., Kisbu-Sakarya Y. Does learning to code influence cognitive skills of elementary school children? Findings from a randomized experiment. British Journal of Educational Psychology. 2021;91(4):1434-1455. https://doi.org/10.1111/bjep.12429
23. Copur-Gencturk Y., Baek C., Doleck T. A Closer Look at Teachers’ Proportional Reasoning. International Journal of Science and Mathematics Education. 2023;21(1):113-129. https://doi.org/10.1007/s10763-022-10249-7
24. Wong J.T., Bui N.N., Fields D.T., Hughes B.S. A Learning Experience Design Approach to Online Professional Development for Teaching Science through the Arts: Evaluation of Teacher Content Knowledge, Self-Efficacy and STEAM Perceptions. Journal of Science Teacher Education. 2022;34(6):593-623. https://doi.org/10.1080/1046560X.2022.2112552
25. Demszky D., Liu J., Hill H.C., Jurafsky D., Piech C. Can Automated Feedback Improve Teachers’ Uptake of Student Ideas? Evidence From a Randomized Controlled Trial in a Large-Scale Online Course. Educational Evaluation and Policy Analysis. 2023;46(3):016237372311692. https://doi.org/10.3102/01623737231169270

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