Educational Data Mining

Author(s):  
Osman Kandara ◽  
Eugene Kennedy

This chapter presents a comprehensive discussion of educational data mining and its potential for educational research. The origins of data mining and the emergence of educational data mining are discussed. The variety of data generated in education (e.g., text, speech, performance, etc.) are described and the challenges of mining these data for useful information are identified. Techniques for mining these data are discussed. Software used to mine these data are noted and issues of theory and ethics are considered. Examples from published literature are cited throughout the chapter and recommendations for educational researchers are offered.

Chapter 3 builds on the previous chapters and provides a summary of big data-style research within the Community of Inquiry scholarly literature, as well as examples from educational research broadly. This chapter also connects to the broader topics of machine learning, data analytics, learning analytics, and educational data mining. Constructs from the Community of Inquiry are integrated into this synthesis and overview. Unfortunately, only a fraction of the studies in educational research broadly today exhibit the tell-tale signs of big data: data volume and variety, new environments or instrumented sources of larger data, often with emerging tools and platforms critical to the analysis of the resulting datasets. A list of additional readings is provided.


2019 ◽  
Vol 7 (2) ◽  
pp. 83-90
Author(s):  
Balwinder Kaur ◽  
Anu Gupta ◽  
R.K.Singla .

2021 ◽  
Vol 1950 (1) ◽  
pp. 012022
Author(s):  
P. Bachhal ◽  
S. Ahuja ◽  
S. Gargrish

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