Original post by By michael cebuliak on May 25, 2018
Within the sphere of big data one finds the possibility of text mining which is certainly applicable to mobile technologies and mobile learning. Whereas it is hoped that there can be consistency found within numerical data, text data offers little promise of consistency as this data is compiled from text that emerges from natural language. Such text–as found in email, social media sites, word documents, etc—is often fraught with ambiguity, jargon, slang, colloquialisms, and differences of considerable degree in respect to semantics and syntax. Software, that can perform text analytics, can help turn much of this unstructured and qualitative data into ordered and quantitative data so that patterns of emotion, significance, degree, and relevance can be determined.
The uses of such data would prove invaluable to keeping track of issues of importance to the school environment. For example, social media sites could be analyzed to see issues pertaining to bullying found within school. Examining school emails could help determine areas of competence and concern for teachers as a whole throughout the district. Searching for key words concerning technology, within teacher emails, could help the district plan training sessions around technological problems.
Of course, such possibilities, invite ethical considerations, while having the potential to work entirely within the realm of the greater good.
Sources
What is text mining (text analytics)? – Definition from WhatIs.com. (n.d.). Retrieved May 25, 2018, from https://searchbusinessanalytics.techtarget.com/definition/text-mining
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