To ensure the team was a united front for the journey ahead, we created a Team Manifesto. The Manifesto held each member to a few rules:

· Communicate clearly
· Communicate often
· Come to standup with discussion points ready
· Express concerns with evidence and the "why"
· Propose solutions backed by evidence
· Listen to others and ask their opinion
· Be respectful

These rules set the foundation for a solid team framework between Luany, Sophia, and myself. This was an excellent team to work on, and creating these agreed upon set of rules helped establish our rapport.

In order to familiarize ourselves with the platform, each team member enrolled in the free course, and worked through portions of the class. Since I was in charge of the research side of the project, I worked through the lions share of the course, in order to better understand what questions we should ask in interviews. A few findings I discovered from my analysis of the free course were:

· Exemplars seemed helpful, although the course did not offer templates

· It was jarring to be asked if I'm enrolled in the free course, within the free course
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· The Search function was effective for scanning for particular sections, but not for material within sections
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· There were many long videos within sections that don't have to do with the topic and seem to be distracting
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· Many of the assignments are buried deep within the Information Architecture of the site, highlighting the IA as an area we should investigate during user interviews
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· There are many steps required to complete the program, which highlighted this as an area of interest to ask users about during the interview process

To gain valuable qualitative information about the platform, it was necessary to undergo a thorough investigation of user experiences through interviews. However, since we already had mountains of data from users who had completed the course, we needed to hone our interviews to hear from users who had not completed the course. We emailed 3000+ users to secure interviews, heard back from 15, and were able to schedule 6 for our initial round. Drawing from the initial background research I and the team conducted, I drafted up interview questions to maintain consistency across interviews and hone in on the areas we wanted to investigate.

The main areas I and my team wanted to derive insight from users were:

· Who are our target users?
· What motivates educators to take this course?
· What motivates educators to complete this course?
· What prevents educators from completing the course?
· Identify any pain points associated with the free course experience.
· Validate or invalidate our assumptions about whether the layout of the content is not user friendly

In order to make sure the questions I planned to ask during interviews we also were addressing the concerns of our stakeholders, I made sure to ask them what questions they would like to explore.

‍The main areas of interest our stakeholders were curious to know about were:

· Is the course too overwhelming or intimidating?
· Is the course easy to navigate and understand?
· Does the course give users a clear sense of what they can do next, without being too promotional?

Setting our sights on these areas of interest greatly helped in refining the questions I drafted for the interviews ahead. Each interview lasted from 40 minutes to an hour, which provided us with great levels of detail on user's experience with the Modern Classrooms Project Free Course. In order to derive takeaways and find patterns between users, it was necessary to synthesize our information using affinity mapping.

Synthesizing the data we received in interviews shed light on who are users were, what they needed from the course, and helped to reframe our goals for the project. Through synthesizing the data, we discovered the following key insights from users:

· I want more resources
· I don't know how to implement the model
· I want a community to meet other teachers
· I want more mastery checks and engagement
· I skim the text
· I feel overwhelmed
· I don't have a lot of time
· I wish resources in the course were more easily accessible
· I think the course is too long
· I have constraints when implementing the model
· I like how easy this course makes it to get my Professional Development hours

As we analyzed these findings as a group, we started to see patterns emerge between how certain users were approaching the course, which helped us in creating our Personas.

Out of our research, we created three personas to identify user needs.

Deep Dive Diana represents the users who already know the model will work for them and their students, and are looking for ways to implement the MCP model in their class. In order to do this, Diana needs quick access to resources, and an easy way to identify what information is contained in the available links.

Skeptical Sarah represents the users who were on the fence about whether they could implement the model in their classrooms, and are taking the course to determine if this is possible. Since Sarah is unsure if the course is worth her time, we needed to create an easy way for her to skim the material to aid her in her determination.

PD Peter's also arose in our research, who were teachers who were only taking the course to fulfill their required professional development hours. As a group, we wanted to identify that they do exist as a part of our user base, although since they are not our primary user group, we did not aim our diagnostic efforts towards their needs.

To identify the journey our users experienced, I created a journey map to track their experience. The typical journey for user's experiences with the course started before the course, when defining a need to improve their teaching style, and be able to better serve their students. This drew teachers into the course, where they would enroll. At this point in the journey, teachers articulated they were at the peak of their emotional experience, as they were hopeful this course would help them in implementing the mastery based approach in their classrooms, and have more time for individual student needs. However, many teachers experienced challenges when beginning the course. They articulated that the many steps required to complete the course felt daunting. The Skeptical Sarah's typically dropped off in their enrollment and progress at this point, feeling unsure if the course was worth their time.

The teachers that continued beyond this point were the Deep Dive Diana's, who were already bought into the model. However, their experience became increasingly negative over time as well. While taking the course, many users felt like they didn't have time to create all the course material, even when devoting their entire summer to the course. This caused users to feel overwhelmed, as if everything they had to devote to the course was not enough. Once these teachers tried to implement the model in their individual classrooms, many felt lost and confused as far as how to put what they had learned into action. This is where Deep Dive Diana's articulated the need to have quick access to resources in order to bring the teachings from the MCP Free Course into their individual classrooms.

In order to address the issues inherent in the course, we ideated solutions based on the unfulfilled needs of our users. The ideas we came up with were:

·Perform a Course Platform Redesign
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· Create a Teacher Mentor Hub

· Redesign a More Effective Content Delivery Strategy Through Progressive Disclosure

· Create Interactive Quizzes

· Have Prospective Users Complete an Intro Checklist

· Create a Course-wide Resource folder

After presenting our findings to the stakeholders, they were surprised to hear users found the platform hard to navigate, and were surprised to hear users were overwhelmed by the coursework. Upon hearing our proposed solutions, they articulated that they did not currently have a developer to build our proposed solution. However, they did want to see what we could accomplish on their current platform, Thinkific. While many of our proposed solutions faced limitations within the platform, we were able to apply the principles of progressive disclosure, and update the content delivery strategy to a more visual and digestible format. Editing the Thinkific platform involved a bit of HTML, which we we able to accomplish.

Due to the project constraints, we created not only one, but two operational prototypes. One on the Thinkific platform, and the other on Figma, which was dubbed the "Pie in the Sky" model, as this was our ideal design. In order to evaluate whether or not our ideations were helpful in solving the issues we discovered, it was necessary to test what we had created. Since my role was the Research Lead, I was responsible for leading how we would assess this. To address the needs of both Deep Dive Diana and Skeptical Sarah, I created directives to weigh the efficacy of our models through both qualitative and quantitative tests. The full test outline can be found in our full Research Plan.

Since Skeptical Sarah needed to quickly skim the course for information, it was necessary to qualitatively test her experience on the three working versions of the platform we now had. The results we found from usability testing uncovered significant improvements in both the Thinkific model we created, as well as our "Pie in the Sky" Figma prototype. Below are a few key takeaways from User testing for each of the three models:

Current MCP model:
· Text is too small
· Navigation issues
· Feels overwhelming
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Thinkific Prototype:
· Users liked text and video on the same page
· Some users missed content below the video
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Pie in the Sky Figma Prototype:
· Users liked the simplified navigation
· Users liked having the bookmark feature to save resources for future use
· Improved visual layout made navigation and identification of links easier
· Appreciated having less sections within units
· Table helps to identify information more easily
· Users prefer the overview content to be visible
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In addition to the qualitative findings above, we also ran timed tests in each of the three platforms. The directive for this test was for users to "Locate the Screencastify teacher example video." This directive was aimed at solving Deep Dive Diana's challenge of locating specific links quickly so she can use them for reference when implementing the course in her classroom. What we found in testing is that the existing Modern Classrooms Project course had a 40% success rate for users trying to locate this link before either giving up or timing out at 5 minutes, which provided an average of 4 minutes for task completion. Users approaching this challenge in the Thinkific Prototype we created were able to complete the challenge each time, averaging 2 minutes for task completion. The Pie in the Sky Figma prototype had the most significant improvement, with a 100% success rate, and an average of 1 minute for task completion.
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To create a clear cut test between the current MCP course as well as our proposed solution, we had 5 users undergo A/B testing. These tests involved placing screenshots of the current course as well as our Figma prototype side by side to compare specific components of each. Questions during A/B testing asked:

1. Which unit navigation method do you prefer?
2. Which section navigation method do you prefer?
3. Which layout better helps you compare these video recording tools?
4. Which layout better helps you understand what each link contains?

In each A/B test, for every participant, the Figma prototype was chosen. This overwhelming support for our "Pie in the Sky" Figma prototype highlights the advantages our model has over the current version, effectively solving the issues that arose in our initial interviews.

Our testing highlighted that each of our proposed solutions work significantly. The sliding scale of our proposed prototypes also provided the Modern Classrooms Project team with options for scaling their improvements. While the Pie in the Sky model allowed users to achieve the same task in 1/4 of the time with a 100% success rate, the same success rate could be achieved by applying the same principles to the Thinkific model. While it took users twice as long to locate the information in the Thinkific prototype, this was still half the time it took in the current platform. Since incorporating the principles of progressive disclosure and adopting a more visual content delivery strategy are possible for the Thinkific platform with minimal investment from the MCP., this idea was well received as a first step solution. The Pie in the Sky model proved to be the ideal prototype, as the delivery is much more accessible, and has more features such as bookmarking resources., but may take more time for the MCP to implement. Overall, our stakeholders were impressed by this model and were grateful for our input towards improving their platform.