Chapter 2 Why a book on data science in educational research
There are at least three reasons why data analysis in educational research is hard:
Educational researchers have unique methods: an emphasis on multi-level models, networks, and measurement are just some examples.
Educational researchers face unique challenges: coming from myriad backgrounds, and working in fields with greater or lesser emphases on different aspects of data analysis.
Finally, there are training challenges. Educational research features some great methodologists: Many advances in the fields mentioned earlier in this session have been made by those working primarily in educational research. Nevertheless, few quantitative classes teach data analysis.