Administrators and approved researchers can access all data (e.g., research surveys, comments on papers, scores in a single Excel file that is sortable by variable. This information is provided for institutional data and IRB opt-in data.)
This feature is intended for a manual analysis. An Excel file is made for each rubric an institution uses. Every row contains a single review including a clickable link to a text file, school code, writer code, grader code, grader type (instructor or student), class code, class name, draft name (initial, intermediate, final, etc.), project name (CV, response letter, etc.), comments left by a reviewer by rubric criterion, rubric criterion scores, weights assigned to rubric criteria, final draft score and corresponding letter grade. If surveys are used, survey responses are included from the pre-, post- and upload surveys (these contain demographics questions, etc.)
This is intended for automated analysis using a programming language (e.g. R, Perl, Python, etc.) Data are the same as above, with a difference that instead of Excel review and related data are exported to a large delimited text file with linked draft files. Connections are preserved by document IDs.
Intended for automated analysis. This is also intended for automated analysis using a programming language and/or a convenient import into a database-driven storage (e.g. Microsoft Access, Microsoft SQL Server, MySQL, MongoDB, etc.)
MyReviewers allows each student to prohibit usage of her/his data in research studies, e.g. opt out. The three mentioned above datasets are exported for (1) all and (2) opt-ins only. All data can be used by the Institutional Research department while the opt-out data may be shared with academic researchers after de-identification
Each dataset is also de-identified by removing student and instructor names from draft texts. An institution may choose to receive identified data, de-identified data or both.
Several data summaries with descriptive statistics are produced in Excel format, showing counts of drafts per class, per instructor, and per draft.
An Excel pivot table is produced showing counts of drafts, which can be arranged by an end user using multiple variables from the original dataset.
A report containing the most frequent n-grams, n-gram frequency histograms and word clouds.