Dictionary-driven analytics in Python for evaluating syllabi 

Calton, R.

Similar to DocuScope, my analysis program “SIMA” uses dictionaries to iterate through a text and categorize language features. Two dictionaries were created: one to focus on communication types (written, oral, visual, etc.), and the other to focus on core values that emerged from meetings of the CMU Core Competency Initiative’s working groups. Whereas the first half of the poster visualizes SIMA’s analytical architecture the method of using it, the second half details results of deploying SIMA to analyze 580 syllabi across ten departments at CMU. The results show communication type percentages and frequency distributions of the most commonly occurring words in each communication type. As part of CMU’s Core Competency Initiative research, SIMA also was used to uncover how core values of communication existed in these syllabi. While this research was performed under the scope of the Core Competency Initiative, it has also been helpful in both assessing current assignment rubrics and opening discussions to how we are representing communication in our classes and disciplines.

Robert Calton, English