Provide definitions for learning analytics and educational data mining

bibliography.bib

@@ -186,6 +186,25 @@
   file = {/home/charlotte/sync/Zotero/storage/3SWAEQHJ/Avery - 2015 - A Similarity Ranking of Python Programs.pdf;/home/charlotte/sync/Zotero/storage/83HXZXCM/14446.html}
 }
 
+@incollection{bakerEducationalDataMining2016,
+  title = {Educational {{Data Mining}} and {{Learning Analytics}}},
+  booktitle = {The {{Wiley Handbook}} of {{Cognition}} and {{Assessment}}},
+  author = {Baker, Ryan S. and Martin, Taylor and Rossi, Lisa M.},
+  year = {2016},
+  pages = {379--396},
+  publisher = {John Wiley \& Sons, Ltd},
+  doi = {10.1002/9781118956588.ch16},
+  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9781118956588.ch16},
+  urldate = {2024-05-08},
+  abstract = {In recent years, there has been increasing interest in using the methods of educational data mining (EDM) and learning analytics (LA) to study and measure learner cognition. In this chapter, we discuss how these types of methods can be used to measure complex cognition and meta-cognition in types of environments where inference can be challenging: exploratory and inquiry learning environments, complex games, and project-based learning. We give examples from a range of projects for the types of constructs that can be inferred using EDM/LA methods and how these measures compare to what can be obtained from more traditional methods. We conclude with a discussion of future discussion and potentials for these kinds of methods.},
+  chapter = {16},
+  copyright = {{\copyright} 2017 John Wiley \& Sons, Inc.},
+  isbn = {978-1-118-95658-8},
+  langid = {english},
+  keywords = {complex games,educational data mining,educational measurement,exploratory learning environments,inquiry learning environments,learning analytics},
+  file = {/home/charlotte/sync/Zotero/storage/L5U4ZHN5/Baker et al. - 2016 - Educational Data Mining and Learning Analytics.pdf;/home/charlotte/sync/Zotero/storage/ES2FJTYW/9781118956588.html}
+}
+
 @article{bakerStateEducationalData2009,
   title = {The {{State}} of {{Educational Data Mining}} in 2009: {{A Review}} and {{Future Visions}}},
   shorttitle = {The {{State}} of {{Educational Data Mining}} in 2009},
@@ -3698,6 +3717,26 @@ New York, NY},
   file = {/home/charlotte/sync/Zotero/storage/J5JNI6J8/Romero and Ventura - 2010 - Educational Data Mining A Review of the State of .pdf;/home/charlotte/sync/Zotero/storage/H7MJHSEM/5524021.html}
 }
 
+@article{romeroEducationalDataMining2020,
+  title = {Educational Data Mining and Learning Analytics: {{An}} Updated Survey},
+  shorttitle = {Educational Data Mining and Learning Analytics},
+  author = {Romero, Cristobal and Ventura, Sebastian},
+  year = {2020},
+  journal = {{WIREs Data Mining and Knowledge Discovery}},
+  volume = {10},
+  number = {3},
+  pages = {e1355},
+  issn = {1942-4795},
+  doi = {10.1002/widm.1355},
+  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/widm.1355},
+  urldate = {2024-05-08},
+  abstract = {This survey is an updated and improved version of the previous one published in 2013 in this journal with the title ``data mining in education''. It reviews in a comprehensible and very general way how Educational Data Mining and Learning Analytics have been applied over educational data. In the last decade, this research area has evolved enormously and a wide range of related terms are now used in the bibliography such as Academic Analytics, Institutional Analytics, Teaching Analytics, Data-Driven Education, Data-Driven Decision-Making in Education, Big Data in Education, and Educational Data Science. This paper provides the current state of the art by reviewing the main publications, the key milestones, the knowledge discovery cycle, the main educational environments, the specific tools, the free available datasets, the most used methods, the main objectives, and the future trends in this research area. This article is categorized under: Application Areas {$>$} Education and Learning},
+  copyright = {{\copyright} 2020 Wiley Periodicals, Inc.},
+  langid = {english},
+  keywords = {Big Data in Education,Data Mining on Education,Data-Driven Decision-Making in Education,Educational Data Mining,Educational Data Science},
+  file = {/home/charlotte/sync/Zotero/storage/TWKMMNLS/Romero and Ventura - 2020 - Educational data mining and learning analytics An.pdf;/home/charlotte/sync/Zotero/storage/ZJJ7I9HL/10.1002@widm.1355.pdf.pdf;/home/charlotte/sync/Zotero/storage/TQQL6NQ5/widm.html}
+}
+
 @article{rosslingEnhancingLearningManagement2008,
   title = {Enhancing Learning Management Systems to Better Support Computer Science Education},
   author = {R{\"o}{\ss}ling, Guido and Joy, Mike and Moreno, Andr{\'e}s and Radenski, Atanas and Malmi, Lauri and Kerren, Andreas and Naps, Thomas and Ross, Rockford J. and Clancy, Michael and Korhonen, Ari and Oechsle, Rainer and Iturbide, J. {\'A}ngel Vel{\'a}zquez},