Write some more LA and EDM

bibliography.bib

@@ -734,6 +734,25 @@
   pages = {312--316}
 }
 
+@article{chattiReferenceModelLearning2012,
+  title = {A Reference Model for Learning Analytics},
+  author = {Chatti, Mohamed Amine and Dyckhoff, Anna Lea and Schroeder, Ulrik and Th{\"u}s, Hendrik},
+  year = {2012},
+  month = jan,
+  journal = {International Journal of Technology Enhanced Learning},
+  volume = {4},
+  number = {5-6},
+  pages = {318--331},
+  publisher = {{Inderscience Publishers}},
+  issn = {1753-5255},
+  doi = {10.1504/IJTEL.2012.051815},
+  url = {https://www.inderscienceonline.com/doi/10.1504/IJTEL.2012.051815},
+  urldate = {2024-02-13},
+  abstract = {Recently, there is an increasing interest in learning analytics in Technology-Enhanced Learning (TEL). Generally, learning analytics deals with the development of methods that harness educational datasets to support the learning process. Learning analytics (LA) is a multi-disciplinary field involving machine learning, artificial intelligence, information retrieval, statistics and visualisation. LA is also a field in which several related areas of research in TEL converge. These include academic analytics, action analytics and educational data mining. In this paper, we investigate the connections between LA and these related fields. We describe a reference model for LA based on four dimensions, namely data and environments (what?), stakeholders (who?), objectives (why?) and methods (how?). We then review recent publications on LA and its related fields and map them to the four dimensions of the reference model. Furthermore, we identify various challenges and research opportunities in the area of LA in relation to each dimension.},
+  keywords = {academic analytics,action research,educational data mining,learning analytics,literature review,reference model},
+  file = {/home/charlotte/sync/Zotero/storage/3GV8IWBM/chatti2012.pdf.pdf}
+}
+
 @article{cheangAutomatedGradingProgramming2003,
   title = {On Automated Grading of Programming Assignments in an Academic Institution},
   author = {Cheang, Brenda and Kurnia, Andy and Lim, Andrew and Oon, Wee-Chong},
@@ -3462,6 +3481,25 @@
   file = {/home/charlotte/sync/Zotero/storage/ZRN5QMRC/Rogers et al. - 2014 - ACCE automatic coding composition evaluator.pdf}
 }
 
+@article{romeroDataMiningCourse2008,
+  title = {Data Mining in Course Management Systems: {{Moodle}} Case Study and Tutorial},
+  shorttitle = {Data Mining in Course Management Systems},
+  author = {Romero, Crist{\'o}bal and Ventura, Sebasti{\'a}n and Garc{\'i}a, Enrique},
+  year = {2008},
+  month = aug,
+  journal = {Computers \& Education},
+  volume = {51},
+  number = {1},
+  pages = {368--384},
+  issn = {0360-1315},
+  doi = {10.1016/j.compedu.2007.05.016},
+  url = {https://www.sciencedirect.com/science/article/pii/S0360131507000590},
+  urldate = {2024-02-13},
+  abstract = {Educational data mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from the educational context. This work is a survey of the specific application of data mining in learning management systems and a case study tutorial with the Moodle system. Our objective is to introduce it both theoretically and practically to all users interested in this new research area, and in particular to online instructors and e-learning administrators. We describe the full process for mining e-learning data step by step as well as how to apply the main data mining techniques used, such as statistics, visualization, classification, clustering and association rule mining of Moodle data. We have used free data mining tools so that any user can immediately begin to apply data mining without having to purchase a commercial tool or program a specific personalized tool.},
+  keywords = {Data mining,Distance education and telelearning,E-learning,Evaluation of CAL systems,Web mining},
+  file = {/home/charlotte/sync/Zotero/storage/6RIZ3VUP/romero2008.pdf.pdf;/home/charlotte/sync/Zotero/storage/BVU6QZKD/S0360131507000590.html}
+}
+
 @article{romeroEducationalDataMining2010,
   title = {Educational {{Data Mining}}: {{A Review}} of the {{State}} of the {{Art}}},
   shorttitle = {Educational {{Data Mining}}},