Novice Programmers Talking about Projects: What Automated Text Analysis Reveals about Online Scratch Users' Comments

In this paper we examine the possibilities of applying predictive analysis to users' written communication via comments in an open-ended online social networking forum: Scratch.mit.edu. Scratch is primarily used by youth ages 8-16 years to program software like games, animations, and stories; their social interactions take place around commenting, remixing, and sharing computer programs (called projects). This exploratory work contributes to work in educational data mining by broadly describing and comparing comments about projects versus other topics in Scratch. Referencing communication accommodation theory, we found that user comments about projects exhibited different linguistic cues than other comments, and these cues were successfully used to classify comment topic. Further, results also suggest that project comments embody richer language than other comments. This suggests several future avenues for research on youth's online comments about programming and other technical projects that may reveal educational opportunities in creating and sharing projects.

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