Sekundarna analiza podatkov in masovni podatki v pedagoškem raziskovanju
DOI:
https://doi.org/10.55707/ds-po.v38i2.103Ključne besede:
sekundarna analiza podatkov, masovni podatki, rudarjenje podatkov, učna analitikaPovzetek
Prispevek se usmerja v dva koncepta, ki se tudi na področju raziskovanja vzgoje in izobraževanja vse pogosteje pojavljata v strokovnih razpravah, nista pa bila znotraj tega področja pri nas še deležna dovoljšne pozornosti, zato sta manj poznana in razširjena ter skromno implementirana. V prvem delu prispevka se usmerjamo v sekundarno analizo podatkov, pri čemer najprej opredelimo sam koncept sekundarne analize podatkov, nato pa analiziramo potencial in zadržke pri rabi tovrstnih podatkov. V nadaljevanju predstavimo pojem masovni podatki, ki z vse večjo digitalizacijo, tudi v šolskem prostoru, postajajo vse pomembnejši vir podatkov, ki predstavlja pomembno osnovo za načrtovanje sprememb za višjo kakovost izobraževanja. Hkrati predstavimo tudi pomembne slabosti rabe masovnih podatkov, med katerimi se zlasti usmerimo v problem varnosti podatkov na spletu ter pomanjkanja kompetentnih strokovnjakov za analizo tovrstnih podatkov. Oba koncepta skušamo tudi smiselno umestiti v polje pedagoškega raziskovanja.
Literatura
Amershi, S. in Conati, C. (2009). Combining Unsupervised and Supervised Classification to Build User Models for Exploratory Learning Environments. Journal of Educational Data Mining, 1(1), 18–71.
Anirban, S. (2014). Big Data Analytics in the Education Sector: Needs, Opportunities, and Challenges. International Journal of Research in Computer and Communication Technology (IJRCCT), 3(11), 2278–5841.
Baig, I. M., Shuib, L. in Yadegaridehkordi, E. (2020). Big Data in Education: a State of the Art, Limitations, and Future Research Directions. International Journal of Educational Technology in Higher Education, 17(44), 1–23. https://doi.org/10.1186/s41239-020-00223-0
Bamiah, M. A., Brohi, S. N. in Bashari, B. R. (2018). Big Data Technology in Education: Advantages, Implementations, and Challenges. Journal of Engineering Science and Technology, Special Issue on ICCSIT, 229–241.
Beneito-Montagut, R. (2017). Big Data and Educational Reserach. V: Wyse, D., Selwyn, N., Smith, E. idr. (ur.). The BERA. Sage Handbook of Educationa Research (str. 913–914). London: Sage.
Bichsel, J. (2012). Analytics in Higher Education: Benefits, Barriers, Progress, and Recommendations. Louisville: EDUCAUSE Center for Applied Research.
Black, P. in Wiliam, D. (2018). Classroom Assessment and Pedagogy. Assessment in Education: Principles, Policy & Practice, 25(6), 551–575.
Blažič, M. (2021). Prispevek visokošolskega učnega okolja h kariernemu razvoju študentov. Didactica Slovenica – Pedagoška obzorja, 36(1), 93–113.
Brands, K. (2014). TECH Practices. Big Data and Business Intelligence for Management Accountants. Strategic Finance. Dostopno na: http://sfmagazine.com/wpcontent/uploads/sfarchive/2014/06/TECH-PRACTICES-Big-Data-and-Business-Intelligence-for-Management-Accountants.pdf (pridobljeno 3. 4. 2022).
Bulmer, M. (1980). Why Don’t Sociologists Make More Use of Official Statistics? Sociology, 14(4), 505–524.
Campbell, J. P., Daft, R. L. in Hulin, C. L. (1982). What to Study: Generating and Developing Research Questions. Beverley Hills: Sage.
Cencič, M. (2009). Kako poteka pedagoško raziskovanje: primer kvantitativne empirične neeksperimentalne raziskave. Ljubljana: Zavod Republike Slovenije za šolstvo.
Cook, T. D. (1974). The Potential and Limitations of Secondary Evaluations. V: Apple, M. W., Subkoviak, M. J. in Lufler, H. S. (ur.). Educational Evaluation: Analysis and Responsibility (str. 15–48). California: McCutchan.
Cope, B. in Kalantzis, M. (2015). Sources of Evidence-of-Learning: Learning and Assessment in the Era of Big Data. Open Review of Educational Research, 2(1), 194–217.
Čepar, Ž., Likar, B. in Kunc, P. (2022). Povezovanje srednjega šolstva in gospodarstva ter kadrovske štipendije. Didactica Slovenica – Pedagoška obzorja, 37(1), 125–140.
Daniel, B. (2014). Big Data and Analytics in Higher Education: Opportunities and Challenges. British Journal of Educational Technology, 46(5), 904–920.
Glaser, B. G. (1963). Retrading Research Materials: the Use of Secondary Analysis by the Independent Researcher. American Behavioral Scientist, 6(10), 11–14.
Gorard, S. (2002). The Role of Secondary Data in Combining Methodological Approaches. Educational Review, 54(3), 231–237.
Gorard, S. in Smith, E. (2004). An International Comparison of Equity in Education Systems. Comparative Education, 40(1), 15–28.
Gorard, S., See, B. H., Smith, E. idr. (2006) Teacher Supply: the Key Issues Workforce. London: Continuum.
Hakim, C. (1982). Secondary Analysis in Social Research: A Guide to Data Sources and Methods with Examples. London: Allen & Unwin.
Hmelak, M., Rudaš, A. in Lepičnik Vodopivec, J. (2020). Vključevanje študentov v razvoj inovativnih izobraževalnih modelov. Didactica Slovenica – Pedagoška obzorja, 35(3–4), 147–163.
Jarke, J. in Breiter, A. (2019). Editorial: the Datafication of Education. Learning, Media and Technology, 44(1), 1–6.
Jary, D. in Jary, J. (2000). Collins Dictionary of Sociology. Glasgow: Harper Collins.
Keržič, D. (2022). Učna analitika kombiniranega učenja v visokem šolstvu. [Doktorska disertacija]. Ljubljana: Fakulteta za družbene vede.
Kozina, A., Rožman, M., Vršnik Perše, T. idr. (2012). Napovedna vrednost različnih ocen šolske klime za dosežke v raziskavah TIMSS. Didactica Slovenica – Pedagoška obzorja, 27(1–2), 127–144.
Kunčič, Š., Razdevšek-Pučko, C. in Rugelj, J. (2013). Spletni dnevnik v prvem obdobju osnovne šole. Didactica Slovenica – Pedagoška obzorja, 28(3–4), 43–56.
Liñán, C. in Pérez, J. (2015). Educational Data Mining and Learning Analytics: Differences, Similarities, and Time Evolution. RUSC. International Journal of Educational Technology in Higher Education, 12(3), 98–112.
Müller, M. in Kuprešak, I. (2018). Perceptions of High School Students of the Use of ICT in the Process of a Foreign Language. Didactica Slovenica – Pedagoška obzorja, 33(1), 95–103
Oi, M., Yamada, M., Okubo, F. idr. (2017). Reproducibility of Findings from Educational Big Data. V: Proceedings of the Seventh International Learning Analytics Knowledge Conference (str. 536–537). New York: Association for Computing Machinery.
Petlák, E. (2021). Self-Refleciona as Basis of a Teacher’s Work. Didactica Slovenica – Pedagoška obzorja, 36(3–4), 41–54.
Prakash, B., Hanumanthappa, M. in Kavitha, V. (2014). Big Data in Educational Data Mining and Learning Analytics. International Journal of Innovative Research in Computer and Communication Engineering, 2(12), 2320–9801.
Riffai, M., Edgar, D., Duncan, P. idr. (2016). The Potential for Big Data to Enhance the Higher Education Sector in Oman. 3rd MEC International Conference on Big Data and Smart City. IEEE Xplore.
Russom, P. (2011). Big Data Analytics. TDWI Best Practices Report. Dostopno na: https://vivomente.com/wp-content/uploads/2016/04/big-data-analytics-white-paper.pdf (pridobljeno 7. 6. 2022).
Siemens, G. (2011). How Data and Analytics can Improve Education. Dostopno na: https://www.oreilly.com/ideas/education-data-analytics-learning (pridobljeno 16. 4. 2022).
Smith, E. (2021). Secondary Data. V: Coe, R., Waring, C. in Hedges, L. (ur.). Research Methods & Methodologies in Education (str. 144–152). London: Sage.
Smith, E. (2008). Pitfalls And Promises: The Use of Secondary Data Analysis In Educational Research. British Journal of Educational Studies, 56(3), 323–339.
Sobal, J. (1981). Teaching With Secondary Data. Teaching Sociology, 8(2), 149–170.
Štemberger, T. (2020). Uvod v pedagoško raziskovanje. Koper: Založba Univerze na Primorskem.
Wang, Y. (2016). Big Opportunities and Big Concerns of Big Data in Education. TechTrends, 60(4), 381–384.
Yorke, M. (2011). Analysing Existing Datasets: Some Considerations Arising from Practical Experience. International Journal of Research & Method in Education, 34(3), 255–267.
Young, E. (2015). Educational Privacy in the Online Classroom: FERPA, MOOCS, and the Big Data Conundrum. Harvard Journal of Law and Technology, 28(2), 1–44.
Yu, X. in Wu, S. (2015). Typical Applications of Big Data in Education. International Conference of Educational Innovation through Technology (EITT) (str. 103–105). Wuhan: Conference Publishing Services.
Zheng, M. in Bender, D. (2019). Evaluating Outcomes of Computer-Based Classroom Testing: Student Acceptance and Impact on Learning and Exam Performance. Medical Teacher, 41(1), 75–82.
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