Big Data with small cases: A method for discovering students centered contexts for Physics courses

M. S. Bülbül


This article proposes a methodology that could assist teachers in understanding their students’ primary needs or interests to decide on the kind of examples or contexts to be used in the classroom. The methodology was tested on 100 volunteers from university (N=50) and high school (N=50) in Ankara, Turkey. The participants were asked to write down the first word they thought of when they were presented with a single letter from the Turkish alphabet, which contains 29 letters. Then all the collected words (29x100=2900) were analyzed with the online word cloud creator, Wordle. According to results, the most cited words from the high-school classes were similar to each other, while the data from university participants showed more diversity. The most chosen word by the participants may give some clues in relation to the context that the teacher can utilize in planning a course. This study shows how to use a big-data-visualization-tool-based methodology to analyze the data gleaned from the participants’ life-long experiences.


Big Data, Physics courses, word cloud

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