Educational data mining: A survey from 1995 to 2005

By Cristóbal Romero, Sebastián Ventura. Expert systems with applications, 2007

1,609 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Science Applications, Information Systems

View Paper: https://www.semanticscholar.org/paper/057cd48efcf1712066a416a88f612030207833a5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Computer Science Applications

In Information Systems

Citations in the corpus

Attention please!: learning analytics for visualization and recommendation (2011, background): “The new field of learning analytics is quite related to similar evolutions in other domains, such as Big Data [1], escience [14, 9, 26], web analytics [7], educational data mining [25].”
Learning analytics and educational data mining: towards communication and collaboration (2012, neutral): “H.2.8 [Database Applications]: Data Mining”
Data Mining Algorithms to Classify Students (2008, background): “A very promising arena to attain this objective is the use of Data Mining (DM) [26].”
Perceiving Learning at a Glance: A Systematic Literature Review of Learning Dashboard Research (2017, background): “As Romero & Ventura concluded in their state-of-the-art review [8], there have been several research approaches since 1995 dealing with the interpretation of educational data.”
Automatic Recommendations for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval (2008, neutral): “In Section 4, we make our conclusions.”
Educational data mining and learning analytics: An updated survey (2020, background): “Analyzing this important type of papers, the first and most popular review of EDM research was published by Romero and Ventura (2007), and it was followed by a more complete (Romero and Ventura, 2010a) and a more comprehensible (Romero and Ventura, 2013) reviews by the same authors.”
A Systematic Review on Educational Data Mining (2017, methodology): “A survey conducted in 2007, provided a comprehensive resource of papers published between 1995 and 2005 on EDM by Romero & Ventura [12].”
Educational Data Mining: A Review of the State of the Art (2010, background): “The first one [221] is a former review of Romero and Ventura with 81”
An overview on subgroup discovery: foundations and applications (2011, background): “However, due to the huge quantities of data, these systems can generate data mining tools which can assist in this task are demanded [ 95 ].”
Learning Analytics and Educational Data Mining in Practice: A Systematic Literature Review of Empirical Evidence (2014, background): “Furthermore, indicative reviews on former work can be found in Romero and Ventura (2007) and Romero and Ventura (2010).”
A reference model for learning analytics (2012, methodology): “LMS accumulate large logs of data of the students’ activities and interaction data, such as reading, writing, accessing and uploading learning material, taking tests, and sometimes have simple, built-in reporting tools (Romero and Ventura, 2007).”
Asynchronous Discussion Forums: Success Factors, Outcomes, Assessments, and Limitations (2009, background): “The difficulty with employing data mining methods in asynchronous discussion forum evaluation (or any evaluation for that matter) is that currently data mining tools are too complex for those not trained in computer science (Romero and Ventura, 2007).”
Preface to the special issue on data mining for personalised educational systems (2011, background): “On the other hand, there are different types of educational systems, such as traditional classrooms, test/quiz systems, e-learning systems, learning management systems (LMS), adaptive educational hypermedia systems (AEHS), intelligent tutoring systems (ITS), etc. (Romero and Ventura 2007).”