Through the MyReviewers assessment ecology, researchers can investigate student learning.
Using corpus methods, researchers have access to six categories of data:
1. Linguistic Data: Researchers use natural language processing technologies to examine the makeup of the corpus (e.g. peer reviews, drafts, etc.) and provide data-driven insights into how they are commonly structured. The goal is to examine how these lexical properties relate to performance and can be used to classify types of assignments.
2. Performance Data: Researchers examine the grades and scores.
3. Meta-Reflection Data: Researchers gather how students reviewed their peers, as well as how helpful they found their peers’ feedback.
4. Audio Data: As of fall 2017, MyReviewers may data mine audio files of reviewers’ comments
5. Program Data: The data collected here focuses on how teachers rate their student’s peer reviews and analyzes teacher feedback to both the reviewee and reviewer.
6. Demographic/Survey Data: This feature asks students to provide their age, grade, gender, ethnicity, and college major via a short survey.
Moving forward, we anticipate adding additional measures:
Clickstream Data: This data collects timestamps, mouse movements, time on task, and actions completed.