Cyberlearning 2017 Gallery Walk.
The purpose of this research project is to explore how a web-based crowdsourcing peer assessment solution within a Massive Open Online Course (MOOC) environment could be implemented to support contemplative reading practice. Research Question: Does implementing a crowdsourcing peer assessment solution within a Massive Open Online Course (MOOC) environment support contemplative reading practice?
As part of the Georgetown Dante’s Journey to Freedom: Inferno MOOC, students were asked to submit writing assignments in relation to specific prompts (one per week). Individual submissions were then assessed by peers using a set rubric that evaluated knowledge. Students’ level of contemplative reading was not assessed due to the difficulty of evaluating contemplative reading for a large number of students. In this research study, we aimed to determine ways that we could implement peer to peer assessment specifically for contemplative reading in order to determine whether we could scale the use of peer assessment within the MyDante platform (http://dante.georgetown.edu). The MyDante platform was designed and developed by developers at Georgetown University.
In late November, we launched a study asking participants to do the following:
- Complete a web-based tutorial to be able to recognize the different levels of contemplative reading (literal, interpretive/metaphoric/reflective).
- Upon successful completion of the tutorial (80% passing score), participants used the contemplative reading rubric to rate responses (text) from two assessment prompts that were completed as part of the Dante’s journey to freedom MOOC.
- Upon submission of the rating activity, participants completed a brief online survey about the experience.
Data collected from the platform include: tutorial ratings and actual ratings of peer entries. In addition, we link these data points with a user’s past activity on the platform as well as their grades in the different assessments as part of the MOOC. We are in the midst of analyzing the data and would share results as part of Cyberlearning 2017.