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Artykuły w czasopismach na temat "Educational statistics – data processing"
Szreder, Mirosław. "Some new challenges and expectation of statistics". Wiadomości Statystyczne. The Polish Statistician 61, nr 6 (28.06.2016): 1–9. http://dx.doi.org/10.5604/01.3001.0014.1000.
Pełny tekst źródłaNur Ghifari, Shafira Zahra, Zahid Mubarok i Sutisna Sutisna. "DIFFERENCES IN STUDENTS' ABILITY TO RECEIVE AND PROCESS INFORMATION ON EDUCATIONAL STATISTICS COURSES". JURNAL EDUSCIENCE 10, nr 1 (28.05.2023): 357–70. http://dx.doi.org/10.36987/jes.v10i1.4115.
Pełny tekst źródłaPečiuliauskienė, Palmira. "Application of Statistical Methods in Education Sciences: the Didactical Principles in the Educational Means Prepared by Bronislovas Bitinas". Pedagogika 124, nr 4 (2.12.2016): 47–57. http://dx.doi.org/10.15823/p.2016.50.
Pełny tekst źródłaKRASNOZHON, O. B., i V. V. MATSIUK. "КОМП’ЮТЕРНО-ОРІЄНТОВАНІ ЕЛЕМЕНТИ НАВЧАННЯ МАТЕМАТИЧНИХ ДИСЦИПЛІН МАЙБУТНІХ УЧИТЕЛІВ МАТЕМАТИКИ". Scientific papers of Berdiansk State Pedagogical University Series Pedagogical sciences 1, nr 2 (4.10.2021): 255–62. http://dx.doi.org/10.31494/2412-9208-2021-1-2-255-262.
Pełny tekst źródłaSoroko, N. V., i M. A. Shynenko. "Monitoring electronic educational and scientific resources using Google Analytics". CTE Workshop Proceedings 1 (21.03.2013): 95–96. http://dx.doi.org/10.55056/cte.144.
Pełny tekst źródłaHaryati, Haryati, Muhammad Nur Akbar Rasyid, Sitti Mania i Supardi Widodo. "Evaluasi Pembelajaran Statistik Pendidikan di STAI Al Khairaat Labuha dengan Model Evaluasi Discrepancy dan Kirkpatrick". PALAPA 11, nr 1 (1.05.2023): 426–45. http://dx.doi.org/10.36088/palapa.v11i1.3251.
Pełny tekst źródłaAshofteh, Afshin, i Jorge M. Bravo. "Data science training for official statistics: A new scientific paradigm of information and knowledge development in national statistical systems". Statistical Journal of the IAOS 37, nr 3 (1.09.2021): 771–89. http://dx.doi.org/10.3233/sji-210841.
Pełny tekst źródłaSalsabila, Nilza Humaira, Ulfa Lu’luilmaknun, Dwi Novitasari, Ratna Yulis Tyaningsih i Riska Ayu Ardani. "GAME EDUKASI PADA PEMBELAJARAN MATEMATIKA: TANGGAPAN SISWA SMP BERDASARKAN GENDER". Mathematic Education And Aplication Journal (META) 2, nr 1 (15.10.2020): 25–32. http://dx.doi.org/10.35334/meta.v2i1.1632.
Pełny tekst źródłaSusilawati, Sumarni. "Analysis of Motivation and Interests of Arabic Language Education Students at Unismuh Makassar in Educational Statistics Subject". Journal of Mathematics and Applied Statistics 1, nr 1 (30.05.2023): 38–41. http://dx.doi.org/10.35914/mathstat.v1i1.41.
Pełny tekst źródłaNursyabani, Akbar, Tajuddin Tajuddin i Nur Astuti Darmiyanti. "PENINGKATAN EDUCATIONAL QUALITY ASSURANCE (EQA) MELALUI SARANA DAN PRASARANA DI LEMBAGA PENDIDIKAN ISLAM MADRASAH TSANAWIYAH NEGERI 4 KARAWANG". Jurnal Pendidikan dan Pengajaran Guru Sekolah Dasar (JPPGuseda) 4, nr 2 (14.07.2021): 154–58. http://dx.doi.org/10.55215/jppguseda.v4i2.3618.
Pełny tekst źródłaRozprawy doktorskie na temat "Educational statistics – data processing"
Hill, Rachelle Phelps. "A Case Study of the Impact of the Middle School Data Coach on Teacher Use of Educational Test Data to Change Instruction". Thesis, University of North Texas, 2010. https://digital.library.unt.edu/ark:/67531/metadc33164/.
Pełny tekst źródłaZhang, Zhidong 1957. "Cognitive assessment in a computer-based coaching environment in higher education : diagnostic assessment of development of knowledge and problem-solving skill in statistics". Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102853.
Pełny tekst źródłaThe objective of this study was to develop a Bayesian assessment model that implements DCA in a specific domain of statistics, and evaluate it in relation to its potential to achieve the objectives of DCA. This study applied a method for model development to the ANOVA score model domain to attain the objectives of the study. The results documented: (a) the process of model development in a specific domain; (b) the properties of the Bayesian assessment model; (c) the performance of the network in tracing students' progress towards mastery by using the model to successfully update the posterior probabilities; (d) the use of estimates of log odds ratios of likelihood of mastery as a measure of "progress toward mastery;" (e) the robustness of diagnostic inferences based on the network; and (f) the use of the Bayesian assessment model for diagnostic assessment with a sample of 20 students who completed the assessment tasks. The results indicated that the Bayesian assessment network provided valid diagnostic information about specific cognitive components, and was able to track development towards achieving mastery of learning goals.
Mercier, Julien 1974. "Help seeking and use of tutor scaffolding by dyads learning with a computer tutor in statistics". Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85191.
Pełny tekst źródłaParticipants were 18 graduate students from a faculty of Education of a Canadian university. The seven-hour experiment involved working in pairs to solve a very challenging statistics problem for which students did not have sufficient background. A computer coach based on human tutoring, the McGill Statistics Tutor, was available to provide help with every aspect of the task.
Data consisted of two complementary sources. The main source was the dialogue between the participants as they worked on the statistics problem using the computer coach. The students' use of the computer coach and solutions to the tasks were also integrated into the database.
Data analysis consisted of statistical analyses using log-linear models. Conditional probability graphs were also constructed from the data.
The results were consistent with the help seeking model. Individual differences were found in terms of emphasis on certain help seeking activities. Effects of the progression in the sequence of tasks were also found. The quality of the solutions students elaborated corresponded to specific profiles of help seeking. The structure of help seeking episodes was established and corresponded to the model. These results have implications for the design of computer coaches and instructional situations.
Thayne, Jeffrey L. "Making statistics matter| Self-data as a possible means to improve statistics learning". Thesis, Utah State University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10250713.
Pełny tekst źródłaResearch has demonstrated that well into their undergraduate and even graduate education, learners often struggle to understand basic statistical concepts, fail to see their relevance in their personal and professional lives, and often treat them as little more than mere mathematics exercises. Undergraduate learners often see statistical concepts as means to passing exams, completing required courses, and moving on with their degree, and not as instruments of inquiry that can illuminate their world in new and useful ways.
This study explored ways help learners in an undergraduate learning context to treat statistical inquiry as mattering in a practical research context, by inviting them to ask questions about and analyze large, real, messy datasets that they have collected about their own personal lives (i.e., self -data). This study examined the conditions under which such an intervention might (and might not) successfully lead to a greater sense of the relevance of statistics to undergraduate learners. The goal is to place learners in a context where their relationship with data analysis can more closely mimic that of disciplinary professionals than that of students with homework; that is, where they are illuminating something about their world that concerns them for reasons beyond the limited concerns of the classroom.
The study revealed five themes in the experiences of learners working with self-data that highlight contexts in which data-analysis can be made to matter to learners (and how self-data can make that more likely): learners must be able to form expectations of the data, whether based on their own experiences or external benchmarks; the data should have variation to account for; the learners should treat the ups and downs of the data as more or less preferable in some way; the data should address or related to ongoing projects or concerns of the learner; and finally, learners should be able to investigate quantitative or qualitative covariates of their data. In addition, narrative analysis revealed that learners using self-data treated data analysis as more than a mere classroom exercise, but as exercises in inquiry and with an invested engagement that mimicked (in some ways) that of a disciplinary professional.
Tao, Yufei. "Indexing and query processing of spatio-temporal data /". View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?COMP%202002%20TAO.
Pełny tekst źródłaIncludes bibliographical references (leaves 208-215). Also available in electronic version. Access restricted to campus users.
Andersson-Sunna, Josefin. "Large Scale Privacy-Centric Data Collection, Processing, and Presentation". Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-84930.
Pełny tekst źródłaDet har blivit en viktig del av affärsutvecklingen hos företag att samla in statistiska data från deras online-källor. Information om användare och hur de interagerar med en online-källa kan hjälpa till att förbättra användarupplevelsen och öka försäljningen av produkter. Att samla in data om användare har många fördelar för företagsägaren, men det väcker också integritetsfrågor eftersom mer och mer information om användare sprids över internet. Det finns redan verktyg som kan samla in statistiska data från online-källor, men när sådana verktyg används förloras kontrollen över den insamlade informationen. Om ett företag implementerar sitt eget analyssystem är det lättare att göra det mer integritetscentrerat och kontrollen över den insamlade informationen behålls. Detta arbete undersöker vilka tekniker som är mest lämpliga för ett system vars syfte är att samla in, lagra, bearbeta och presentera storskalig integritetscentrerad information. Teorier har undersökts om vilken teknik som ska användas för att samla in data och hur man kan hålla koll på unika användare på ett integritetscentrerat sätt, samt om vilken databas som ska användas som kan hantera många skrivförfrågningar och lagra storskaligdata. En prototyp implementerades baserat på teorierna, där JavaScript-taggning används som metod för att samla in data från flera online källor och cookies används för att hålla reda på unika användare. Cassandra valdes som databas för prototypen på grund av dess höga skalbarhet och snabbhet vid skrivförfrågningar. Två versioner av bearbetning av rådata till statistiska rapporter implementerades för att kunna utvärdera om data skulle bearbetas i förhand eller om rapporterna kunde skapas när användaren ber om den. För att utvärdera teknikerna som användes i prototypen gjordes belastningstester av prototypen där resultaten visade att en flaskhals nåddes efter 45 sekunder på en arbetsbelastning på 600 skrivförfrågningar per sekund. Testerna visade också att prototypen lyckades hålla prestandan med en arbetsbelastning på 500 skrivförfrågningar per sekund i en timme, där den slutförde 1 799 953 förfrågningar. Latenstest vid bearbetning av rådata till statistiska rapporter gjordes också för att utvärdera om data ska förbehandlas eller bearbetas när användaren ber om rapporten. Resultatet visade att det tog cirka 30 sekunder att bearbeta 1 200 000 rader med data från databasen vilket är för lång tid för en användare att vänta på rapporten. Vid undersökningar om vilken del av bearbetningen som ökade latensen mest visade det att det var hämtningen av data från databasen som ökade latensen. Det tog cirka 25 sekunder att hämta data och endast cirka 5 sekunder att bearbeta dem till statistiska rapporter. Testerna visade att Cassandra är långsam när man hämtar ut många rader med data, men är snabb på att skriva data vilket är viktigare i denna prototyp.
Wong, Ka-yan, i 王嘉欣. "Positioning patterns from multidimensional data and its applications in meteorology". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B39558630.
Pełny tekst źródłaFathi, Salmi Meisam. "Processing Big Data in Main Memory and on GPU". The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1451992820.
Pełny tekst źródłaGwaze, Arnold Rumosa. "A cox proportional hazard model for mid-point imputed interval censored data". Thesis, University of Fort Hare, 2011. http://hdl.handle.net/10353/385.
Pełny tekst źródłaTsoi, Kit-hon, i 徐傑漢. "Aspects of the statistics of condensation polymer networks". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38985433.
Pełny tekst źródłaKsiążki na temat "Educational statistics – data processing"
Stemmer, Paul M. Microcomputer programs for educational statistics: A review of popular programs. Princeton, N.J: ERIC Clearinghouse on Tests, Measurements, and Evaluation, Educational Testing Service, 1986.
Znajdź pełny tekst źródłaNational Forum on Education Statistics (U.S.). National Education Statistics Agenda Committee. Improving the capacity of the national education data system to address equity issues: An addendum to A guide to improving the national education data system. Washington, DC: The Center, 1995.
Znajdź pełny tekst źródłaFundação Centro Brasileiro de TV Educativa., red. Um Relato do estado atual de informática no ensino no Brasil. [Rio de Janeiro]: Ministério da Educação e Cultura, Fundação Centro Brasileiro de TV Educativa, 1985.
Znajdź pełny tekst źródłaHolcomb, Edie L. Data-based decision making. Wyd. 3. Bloomington, IN: Solution Tree PRess, 2012.
Znajdź pełny tekst źródłaAbbott, Martin L. Understanding educational statistics using Microsoft Excel® and SPSS®. Hoboken, N.J: Wiley, 2011.
Znajdź pełny tekst źródłaSheila, Heaviside, Educational Resources Information Center (U.S.) i National Center for Education Statistics., red. Advanced telecommunications in U.S. public elementary and secondary schools, 1995: Fast Response Survey System. [Washington, DC]: U.S. Dept. of Education, Office of Educational Research and Improvement, Educational Resources Information Center, 1996.
Znajdź pełny tekst źródłaYi, Chong-sŏng. Kyoyuk yŏnʾgu ŭi sŏlgye wa charyo punsŏk. Wyd. 8. Sŏul Tʻŭkpyŏlsi: Kyohak Yŏnʾgusa, 1996.
Znajdź pełny tekst źródłaLogunova, Oksana, Petr Romanov i Elena Il'ina. Processing of experimental data on a computer. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1064882.
Pełny tekst źródłaNational Center for Education Statistics. i Educational Resources Information Center (U.S.), red. Evaluation of the 1996-97 nonfiscal common core of data surveys data collection, processing, and editing cycle. [Washington, DC]: U.S. Dept. of Education, Office of Educational Research and Improvement, National Center for Education Statistics, 1999.
Znajdź pełny tekst źródłaNational Center for Education Statistics, red. Integrated postsecondary education data system: Guide to surveys. [Washington, D.C.?]: U.S. Dept. of Education, Office of Educational Research and Improvement, National Center for Education Statistics, 1992.
Znajdź pełny tekst źródłaCzęści książek na temat "Educational statistics – data processing"
Fischer, Svenja, i Andreas H. Schumann. "Data Processing". W Type-Based Flood Statistics, 73–95. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32711-7_6.
Pełny tekst źródłaRomero, Cristóbal, José Raúl Romero i Sebastián Ventura. "A Survey on Pre-Processing Educational Data". W Educational Data Mining, 29–64. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02738-8_2.
Pełny tekst źródłaXue, Dingyü, i Feng Pan. "Data Processing and Statistics". W MATLAB and Simulink in Action, 353–84. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-1176-9_12.
Pełny tekst źródłaFroeschl, K. A. "Semantic Metadata: Query Processing and Data Aggregation". W Computational Statistics, 357–62. Heidelberg: Physica-Verlag HD, 1992. http://dx.doi.org/10.1007/978-3-642-48678-4_45.
Pełny tekst źródłaWang, Jiachun, Jing Zhao, Shiliang Sun i Dongyu Shi. "Intelligent Educational Data Analysis with Gaussian Processes". W Neural Information Processing, 353–62. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04224-0_30.
Pełny tekst źródłaKauffman, James M., i John Wills Lloyd. "Statistics, Data, and Special Educational Decisions". W Handbook of Special Education, 29–39. Second Edition. | New York : Routledge, 2017. | “First edition published by Routledge 2011”—T.p. verso.: Routledge, 2017. http://dx.doi.org/10.4324/9781315517698-4.
Pełny tekst źródłaZhang, Qing, Germaine Uwimpuhwe, Dimitris Vallis, Akansha Singh, Tahani Coolen-Maturi i Jochen Einbeck. "Elicitation of Priors for Intervention Effects in Educational Trial Data". W Contributions to Statistics, 28–33. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65723-8_5.
Pełny tekst źródłaFroeschl, Karl A. "Application Case I: Labour Force Statistics — Harmonizing Official Statistics Data". W Metadata Management in Statistical Information Processing, 279–390. Vienna: Springer Vienna, 1997. http://dx.doi.org/10.1007/978-3-7091-6856-1_4.
Pełny tekst źródłaBuscemi, Francesco. "Reverse Data-Processing Theorems and Computational Second Laws". W Springer Proceedings in Mathematics & Statistics, 135–59. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2487-1_6.
Pełny tekst źródłaReboiro-Jato, Miguel, Daniel Glez-Peña i Hugo López-Fernández. "CHAPTER 5. Statistics, Data Mining and Modeling". W Processing Metabolomics and Proteomics Data with Open Software, 120–200. Cambridge: Royal Society of Chemistry, 2020. http://dx.doi.org/10.1039/9781788019880-00120.
Pełny tekst źródłaStreszczenia konferencji na temat "Educational statistics – data processing"
Ponomarenko, Alexey. "Reformatting statistical education in Russia: changes in classifications, standards, and programs". W Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2017. http://dx.doi.org/10.52041/srap.17314.
Pełny tekst źródłaLee, Taerim. "A deep learning analytics to facilitate sustainability of statistics education". W Decision Making Based on Data. International Association for Statistical Education, 2019. http://dx.doi.org/10.52041/srap.19306.
Pełny tekst źródłaMarhoum, Adil. "Plenary lecture: the teaching of statistics in morocco l’enseignement de la statistique au maroc". W Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2017. http://dx.doi.org/10.52041/srap.17103.
Pełny tekst źródłaMotoryn, Ruslan, Tetiana Motoryna i Kateryna Prykhodko. "Impact of big data on development of the curriculums of training statisticians in Ukrainian university". W Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2017. http://dx.doi.org/10.52041/srap.17702.
Pełny tekst źródłaLee, Jung Jin, i Gunseog Kang. "An Educational Software for the Design of Experiments". W Statistical Literacy- Material From Some of the Talks. International Association for Statistical Education, 2001. http://dx.doi.org/10.52041/srap.01105.
Pełny tekst źródłaHöper, Lukas, Susanne Podworny, Carsten Schulte i Daniel Frischemeier. "Exploration of Location Data: Real Data in the Context of Interaction with a Cellular Network". W IASE 2021 Satellite Conference: Statistics Education in the Era of Data Science. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.nkppy.
Pełny tekst źródłaPuchianu, Crenguta, Anata flavia Ionescu, Daniela Caprioara i Dorin mircea Popovici. "STATISTICAL SOFTWARE FOR EDUCATIONAL RESEARCHES". W eLSE 2016. Carol I National Defence University Publishing House, 2016. http://dx.doi.org/10.12753/2066-026x-16-116.
Pełny tekst źródłaWei, Yuan. "The training of researchers in the use of statistics in China". W Training Researchers in the Use if Statistics. International Association for Statistical Education, 2000. http://dx.doi.org/10.52041/srap.00404.
Pełny tekst źródłaR. P, Arya, i Anuja S. B. "Effectively Analysis and Predict Students Performance and Other Evaluation". W The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/gdhl6261/ngcesi23p2.
Pełny tekst źródłaToledo, J. M., Thiago J. M. Moura i R. D. A. Timoteo. "BrStats: a socioeconomic statistics dataset of the Brazilian cities". W Dataset Showcase Workshop. Sociedade Brasileira de Computação, 2023. http://dx.doi.org/10.5753/dsw.2023.233621.
Pełny tekst źródłaRaporty organizacyjne na temat "Educational statistics – data processing"
Volkova, Nataliia P., Nina O. Rizun i Maryna V. Nehrey. Data science: opportunities to transform education. [б. в.], wrzesień 2019. http://dx.doi.org/10.31812/123456789/3241.
Pełny tekst źródłaMazorchuk, Mariia S., Tetyana S. Vakulenko, Anna O. Bychko, Olena H. Kuzminska i Oleksandr V. Prokhorov. Cloud technologies and learning analytics: web application for PISA results analysis and visualization. [б. в.], czerwiec 2021. http://dx.doi.org/10.31812/123456789/4451.
Pełny tekst źródłaVos, Rob. Educational Indicators: What's to Be Measured? Inter-American Development Bank, styczeń 1996. http://dx.doi.org/10.18235/0011588.
Pełny tekst źródłaStonaha, P. Development of a Data Acquisition Program for the Purpose of Monitoring Processing Statistics Throughout the BaBar Online Computing Infrastructure's Farm Machines. Office of Scientific and Technical Information (OSTI), wrzesień 2004. http://dx.doi.org/10.2172/833112.
Pełny tekst źródłaCueto, Santiago. Empirical Information and the Development of Educational Policies in Latin America. Inter-American Development Bank, październik 2005. http://dx.doi.org/10.18235/0008713.
Pełny tekst źródłaMurphy, Keire, i Anne Sheridan. Annual report on migration and asylum 2022: Ireland. ESRI, listopad 2023. http://dx.doi.org/10.26504/sustat124.
Pełny tekst źródłaShabelnyk, Tetiana V., Serhii V. Krivenko, Nataliia Yu Rotanova, Oksana F. Diachenko, Iryna B. Tymofieieva i Arnold E. Kiv. Integration of chatbots into the system of professional training of Masters. [б. в.], czerwiec 2021. http://dx.doi.org/10.31812/123456789/4439.
Pełny tekst źródłaKelly, Elish, i Bertrand Maître. Identification Of Skills Gaps Among Persons With Disabilities And Their Employment Prospects. ESRI, wrzesień 2021. http://dx.doi.org/10.26504/sustat107.
Pełny tekst źródłaKelly, Elish, i Bertrand Maître. Identification Of Skills Gaps Among Persons With Disabilities And Their Employment Prospects. ESRI, wrzesień 2021. http://dx.doi.org/10.26504/sustat107.
Pełny tekst źródłaAtuhurra, Julius, Rastee Chaudhry i Michelle Kaffenberger. Conducting Surveys of Enacted Curriculum Studies in Low- and Middle-Income Countries: A Toolkit for Policymakers, Researchers, and Education Practitioners. Research on Improving Systems of Education (RISE), marzec 2023. http://dx.doi.org/10.35489/bsg-rise-misc_2023/13.
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