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Showing posts from May, 2019

Text mining, unruly text, XML, TEI, and R: Go with conventional architecture, or make your own?

Many educational researchers will inevitably work with text as data. It is unavoidable, as reflective practice (almost universally required by teacher preparation programs) requires conveying meaning through words, and retaining a corpus of reflections throughout a semester, or even a year. Finding patterns in teaching strategies will inevitably require text parsing. Student writing assessment naturally lends itself to text analytics, so educational researchers can gain data on student learning through reading student responses to writing prompts. Further still, professional educational researchers stand to gain much by taking in large amounts of text, searching for patterns, and reporting on their findings. The more skill at working with text, the greater the opportunities abound for educational researchers. Working with text requires effort and copious patience, mostly because text is, relative to numbers, messy. The Curse of Messiness Messiness is essentially the observatio