Recommender

What is the Recommender Tool?

The Recommender Tool provides lightweight tailored content/messaging to learners based on their answers to a series of survey questions. It is best for situations where the final outcome or decision depends on a multitude of nuanced factors.

Student-Facing Features

Single Answer Questionnaires - Students respond to one question at a time and can choose only one answer for each question.
Email Delivery - After students answer all the questions, not only can they immediately see their recommendation. They can also choose to have it emailed to them.
Unlimited Redo’s - If students are not satisfied with their top recommendation, they can erase all of their previous responses and start over.

Instructor-Facing Features

Questionnaire Design - Instructors have full control over the design of each question, the final recommendations, and which answers correspond to a particular recommendation.

Instructional Design Tips

The questionnaire can be broken up into as many mini surveys as you like, so you can break up the questions to match course content in a more timely way. However, students must complete every mini-survey before they can receive their results.
Alternatively, you can also just create one larger survey that learners complete in one sitting and immediately receive their results.

Past Use Cases

Sustainable Food Teach-Out

This Coursera-hosted teach-out used the tool throughout the learning experience to gather information about a learner’s food-related habits and attitudes. For example, at the conclusion of the module about meat, the tool asked a handful of questions about how often a learner ate meat and whether or not they’d be willing to reduce their consumption in the future. The tool then used the learner’s responses to determine the best way he could apply what he learned to make a change in his own life and/or community.

FAQs

I want to use this tool in my course. How do I get started?

To get started with the Recommender Tool, please reach out to Gamut Support (gamut-support@umich.edu). Someone from the team will help you think through your use case and plan out the logic of how the survey questions/answers will ultimately lead to the appropriate recommendations.

Can I use this tool for graded assignments?

No. While other tools, such as the Gamut Gallery Tool, support graded assignments, Write & Revise currently does not.

Can the tool be accessed from outside an LMS?

No, in order for anyone to authenticate into the tool they must come from an LTI item within an LMS. For that reason, there is no public-facing component to any Gamut Tool.

However, the Recommender Tool does allow learners to email their results themselves at the end.

How do I set up the tool in Canvas?

Contact 4help@umich.edu to request that you be given the role of “tool installer” for course so you can set up an external LTI tool.
Inside your Canvas course, choose or create the module that will contain the link to the tool.
Add a new “item”, and choose the “External Tool” type.
In the URL field, enter: https://recommender.ai.umich.edu/simple/launch/
In the Page Name field, enter your desired name for the recommender.
For the best tool experience, check the box “Load in a new tab”.
Add/save the item.
Click into the newly created item, and on the next page click “Load [ item name ] in a new window”.
Complete the configuration steps inside the tool, and publish the LTI item when you’re ready for students to start using it.

How do I set up the tool in Coursera?

Please submit a request for the LTI Credentials to receive your key and secret, and someone from our team will respond shortly with that information.
Inside the course shell, add a new LTI item (found under “More”)
Inside the new LTI item, provide a title and description.
In the version field, leave “Version 1.1” selected.
In the Launch URL field, enter: https://recommender.ai.umich.edu/simple/launch/
Enter the provided values provided by our team for the consumer key and secret fields.
In the Learner Privacy field, select “Share learner ID, full name, and email address”
In the Outcome Callback field, select “no”.

How do I set up the tool in FutureLearn?

Complete the steps outlined in this help article
Once the tool is reviewed and approved you may proceed with final configuration steps inside the Gamut tool.

Who do I contact if I have a problem with the tool?

We’re sorry to hear you’re encountering issues with the tool. Please submit a support request and we'll be with as soon as possible.

Report abuse