The Main Problem:

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Students are lacking the basic skills necessary to succeed in their current and future math classes. Teachers have limited time and resources to help these students catch up. Furthermore, these students often lack engagement and experience math anxiety. This increases difficulty learning more advanced math concepts later in students' academic studies, causing them to fall even further behind grade level.

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The Process:

 

1. Created before and after stories to envision the product's impact

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2. Created user profiles

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3. Researched engagement, personalization, math education, and more to guide product features

    (See the infographic to learn more)

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4. Came up with the idea to create a math platform that incorporates emotional tools and data tracking

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Our team came up with almost 50 ideas of different products that could solve our problem. After two brainstorm sessions, I created wireframes in Balsamiq for one solution but determined that there was a better option. One of my partners was set on creating an individualized learning platform (similar to those being created by AltSchool and Summit/Facebook). I came up with the idea of providing emotional support tools at targeted times (i.e. when working on math homework or in math class). I realized that we could combine these two ideas and address individual academic and emotional needs within one product.

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The platform would collect data on...

     (1) when and what kind of emotional support is needed by students 

     (2) the change in students' emotional states as a result of a variety of math activities

 

The data analytics would provide teachers with insight into what academic activities are liked by each student, what activities or skills create stress for each student, and what stress-reduction techniques are most helpful. This would help the teacher improve students' experiences learning math via the Pi Makers platform. For example, teachers could use individual activity ratings to assign more activities like those the student rated highly. Additionally, the analytics would help the teacher support students outside of the platform. For example, a teacher could see in Pi Makers that a student finds deep breathing very helpful to reduce their anxiety; so in class, a teacher could verbally remind that student to breathe deeply before starting a worksheet on a skill that Pi Maker's determined was stressful to that student. Access to this type of student information could transform teacher-student relations which could help improve students' mindsets and emotional responses when working on math.

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5. Began wireframing the overall platform