Learning Analytics Methods and Tutorials
This open access comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field started. The book covers all important quantitative topics in education at large as well as the lat...
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| Formato: | Online |
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| Idioma: | inglês |
| Publicado em: |
Springer Nature
2024
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| Acesso em linha: | ONIX_20240716_9783031544644_11 |
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| _version_ | 1863748638536105984 |
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| collection | Directory of Open Access Books |
| description | This open access comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field started. The book covers all important quantitative topics in education at large as well as the latest in learning analytics and education data mining. The book also goes deeper into advanced methods that are at the forefront of novel methodological innovations. Authors of the book include world-renowned learning analytics researchers, R package developers, and methodological experts from diverse fields offering an unprecedented interdisciplinary reference on novel topics that is hard to find elsewhere. The book starts with the basics of R as a programming language, the basics of data cleaning, data manipulation, statistics, and analytics. In doing so, the book is suitable for newcomers as they can find an easy entry to the field, as well as being comprehensive of all the major methodologies. For every method, the corresponding chapter starts with the basics, explains the main concepts, and reviews examples from the literature. Every chapter has a detailed explanation of the essential techniques and basic functions combined with code and a full tutorial of the analysis with open-access real-life data. A total of 22 chapters are included in the book covering a wide range of methods such as predictive learning analytics, network analysis, temporal networks, epistemic networks, sequence analysis, process mining, factor analysis, structural topic modeling, clustering, longitudinal analysis, and Markov models. What is really unique about the book is that researchers can perform the most advanced analysis with the included code using the step-by-step tutorial and the included data without the need for any extra resources. This is an open access book. |
| format | Online |
| id | doab-20.500.12854ir-142409 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1424092024-07-23T04:33:39Z Learning Analytics Methods and Tutorials Saqr, Mohammed López-Pernas, Sonsoles learning analytics methods educational data mining quantitative methods in education social network analysis sequence analysis Process mining machine learning in education artificial intelligence in education temporal networks epistemic networks thema EDItEUR::J Society and Social Sciences::JN Education::JNV Educational equipment and technology, computer-aided learning (CAL) thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences This open access comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field started. The book covers all important quantitative topics in education at large as well as the latest in learning analytics and education data mining. The book also goes deeper into advanced methods that are at the forefront of novel methodological innovations. Authors of the book include world-renowned learning analytics researchers, R package developers, and methodological experts from diverse fields offering an unprecedented interdisciplinary reference on novel topics that is hard to find elsewhere. The book starts with the basics of R as a programming language, the basics of data cleaning, data manipulation, statistics, and analytics. In doing so, the book is suitable for newcomers as they can find an easy entry to the field, as well as being comprehensive of all the major methodologies. For every method, the corresponding chapter starts with the basics, explains the main concepts, and reviews examples from the literature. Every chapter has a detailed explanation of the essential techniques and basic functions combined with code and a full tutorial of the analysis with open-access real-life data. A total of 22 chapters are included in the book covering a wide range of methods such as predictive learning analytics, network analysis, temporal networks, epistemic networks, sequence analysis, process mining, factor analysis, structural topic modeling, clustering, longitudinal analysis, and Markov models. What is really unique about the book is that researchers can perform the most advanced analysis with the included code using the step-by-step tutorial and the included data without the need for any extra resources. This is an open access book. 2024-07-23T04:33:37Z 2024-07-23T04:33:37Z 2024-07-16T18:50:47Z 2024 book ONIX_20240716_9783031544644_11 https://library.oapen.org/handle/20.500.12657/92311 9783031544644 9783031544637 https://directory.doabooks.org/handle/20.500.12854/142409 eng open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/92311/1/978-3-031-54464-4.pdf Springer Nature Springer Nature Switzerland 10.1007/978-3-031-54464-4 10.1007/978-3-031-54464-4 9fa3421d-f917-4153-b9ab-fc337c396b5a b3168526-61fc-4d58-8acc-c4588fd3ea34 9783031544644 9783031544637 Springer Nature Switzerland 736 Cham [...] open access |
| spellingShingle | learning analytics methods educational data mining quantitative methods in education social network analysis sequence analysis Process mining machine learning in education artificial intelligence in education temporal networks epistemic networks thema EDItEUR::J Society and Social Sciences::JN Education::JNV Educational equipment and technology, computer-aided learning (CAL) thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences Learning Analytics Methods and Tutorials |
| title | Learning Analytics Methods and Tutorials |
| title_full | Learning Analytics Methods and Tutorials |
| title_fullStr | Learning Analytics Methods and Tutorials |
| title_full_unstemmed | Learning Analytics Methods and Tutorials |
| title_short | Learning Analytics Methods and Tutorials |
| title_sort | learning analytics methods and tutorials |
| topic | learning analytics methods educational data mining quantitative methods in education social network analysis sequence analysis Process mining machine learning in education artificial intelligence in education temporal networks epistemic networks thema EDItEUR::J Society and Social Sciences::JN Education::JNV Educational equipment and technology, computer-aided learning (CAL) thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences |
| topic_facet | learning analytics methods educational data mining quantitative methods in education social network analysis sequence analysis Process mining machine learning in education artificial intelligence in education temporal networks epistemic networks thema EDItEUR::J Society and Social Sciences::JN Education::JNV Educational equipment and technology, computer-aided learning (CAL) thema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQE Expert systems / knowledge-based systems thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXJ Computer applications in the social and behavioural sciences |
| url | ONIX_20240716_9783031544644_11 |