Red Rover automatically makes recommendations on student groups, providing the student with a shortlist of options tailored to their interests.
How It Works
1. Based on the tags the student added to Red Rover, the system delivers appropriate groups with matching tags.
2. The student can join the groups with one click (based on the title alone) or they can click on the group to see the description, the group links, the advisors, the student leaders, and the other students who have joined.
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Key Concepts
1. The best organized schools present their groups in one long list**, with, if you are lucky, an e-mail link to a student that may or may not be current. Big lists are daunting, especially for Freshman who are not particularly outgoing or self-motivated. The recommendation process provides a highly relevant shortlist, increasing the likely hood that everyone will at least opt into a few groups.
2. Joining a group with one click is painless. While seeking out groups on the web or in the student union and introducing themselves to the leaders might work for self-motivated and outgoing students, this is a small percentage of incoming students. For the majority of the students, anything we can do to reduce their “work” and social “risk” in the beginning is a step in the right direction. (Once the student is “in” we can then work to build them up.) With Red Rover, the impetus and responsibility lie with the student leaders, who can be trained and are far more likely to possess the maturity and traits necessary for a successful connection. Red Rover delivers new students to the leaders, instead of the students having to find the leaders.
3. Everything is tracked. With the paid version (coming soon after the free version) advisors will be able to see conversion ratios, benchmark against similar institutions, as well as quickly see which students did not join anything. With this information, the institution can focus precious staff resources where it is most needed.
Future Additions to This Function
1. With use and data, we should be able to play and tweak the recommended methodology to increase joining. As increasing involvement is the goal of the system, the conversion to “joining” will be a key metric.
2. Administration control of recommendation sensitivity. Small schools will want to have a lower “match” threshold to provide enough recommendations from a smaller list of schools, while larger schools will want a higher threshold to avoid providing too large a recommended list. This flexibility will be added shortly.
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