Helping students discover relevant study materials inside Studocu AI
MY ROLE
Product designer
The TL;DR
THE TEAM
Product manager
Machine learning engineer
Full stack developer
QA specialist
Tech lead
THE TIMELINE
2 months
THE PRODUCT
Real-time student guidance. This is an AI-driven feedback coach that ensures personalised, effective feedback to improve students’ peer reviews.
THE PROBLEM
Feedback giving is one of the most important skills for the workforce but teachers don’t have time to provide guided, timely feedback to students. The previous efforts from the company to have a feedback coach are outdated, both from a design and technical perspective.
THE OUTCOMES
77%
CSAT from students
15%
Increase on feedback length
130+
Teachers choosing the feature
2500+
Students using the feature
Transforming Student Feedback in Real-Time
This conversational coach gives real-time, AI-powered feedback to students on their peer reviews. It provides suggestions for improvement tailored to student language use and content of the review. Although having AI as a co-pilot can be daunting, students love it! This is demonstrated by the remarkable 77% customer satisfaction score.
This feature has the highest CSAT recorded in the product!
Where it lives
Feedbackfruits is a dynamic feedback tools provider nestled within university Learning Management Systems. With different configurable activities, it empowers teachers to craft impactful learning experiences, helping them save time in and outside the classroom.
Cracking the code of constructive feedback
Feedback giving is one of the most important skills for the workforce but teachers don’t have time to provide guided, timely feedback to students.
this results in students giving too short, overly positive or negative feedback that is not actionable.*
*insight from interviews with instructors from top level universities teaching a class of 50+ students.
Modernizing feedback coaching
Within our company, there was a previous effort to have an “Automated feedback coach” but unfortunately, it was outdated both from a design and technical perspective.
Essentially, the homegrown model provided eight possible suggestions to students' reviews, which didn’t scale and had an erratic performance.
The team approach
I was part of the Analytics and Insights team and together with the PM we analyzed the existing feature and came up with requirements for the redesign. For a two month period I closely collaborated with the developers and machine learning engineer to decide on the best solution to the problem. While they investigated on how we could leverage generative AI for the coach and iterated on the prompt, I focused on the experience that the students would have with it.
To know more about the technical side, click here
Old design
Interaction with the coach
Upholding transparency, empowering choice
Given that we were working with generative AI and Large Language Models, we needed to be compliant with the regulations in EU, US and APAC regions so that the feature could be used in all the partner institutions.
This involved several back and forth with our legal team to ensure that the design:
Reflect that AI is being used
Give the chance to turn the feature off
Include a link to an article about transparency with AI
Crafting a seamless user experience
My main job was making sure that the redesign would seamlessly integrate with the existing product while complying with the legal AI-regulations for all regions and keeping the focus on the prime action for the user: giving feedback to their peers.
Decision #1
I decided to use an existing pattern in the product that would convey the idea of a discussion between peers. I gave our coach a profile picture next to their suggestions, achieving a conversational effect.
Decision #2
With minor adjustments to the alignment and sizing of the fonts, I decided to keep the ‘Automated Feedback Coach’ title and add a discreet help icon to disclose information about what the feature does and how to disable it. It was important to ensure that the suggestions are coming from AI and that the student is in control at all times.
Decision #3
Since the transparency note prepared with the legal team didn't need to be displayed constantly, I chose to present it as a link only at the initial stage
Designing for every state
Part of the requirements was to design for all the possible states of the coach, this included and initial state with a presentation, a "thinking" state while suggestions were being processed, the actual feedback from the coach and an error state.
Flow states
Designing for scalability
I ensured the design would fit various placements, such as sidebars, making it a flexible element in the product. Additionally, I considered language options, allowing students to receive feedback in their preferred language.
Accessibility annotations
Making designs inclusive for all students
Last but not least, I needed to make sure the designs were accessible to our students. With the iterative efforts to be compliant with the WACG level 2.1, I annotated the designs with the relevant labels to make the elements tabbable and available to screen readers.
Driving success, one feedback at a time
We aimed to make a real difference with this project, and the results speak for themselves.
These achievements highlight the true impact of our efforts!
We set out to hit a customer satisfaction score of 60%, but the students’ happiness pushed us to an impressive 77%. *the highest recorded in the entire product
We hoped for 10 CSAT survey responses and were blown away when over 400 came in, showing fantastic engagement.
On top of that, we saw amazing adoption of the feature from the instructors’ side, with 346 activities performed instead of the 15 we planned for.
Instructor
@ one of the world's top learning institutions
The coach was really straightforward to set up. And none of the students had any trouble using it, which is pretty big. […] it was helping them give more detailed feedback and gave them good tips on what to improve on and assisting giving detailed responses about specific things. I would rate the quality with: 8/10 (missing 2 points due to low sample size), uniqueness: 10/10 and would recommend to colleague: Oh, 10. For sure. 10
Final reflection
This project, completed in just two months, was a significant learning experience for me. I discovered an essential truth: real-world projects rarely follow the playbooks. Instead, you often have to leverage existing resources and knowledge to drive success.
For instance, we did not conduct new user interviews, as we built on an existing product and already understood the user needs. This allowed us to quickly and effectively enhance the solution, addressing users' immediate needs with confidence.
This project was a major milestone in developing my communication skills. Working with multiple stakeholders—from legal team, to the development team—required clear, consistent, and persuasive communication. Aligning everyone's vision and ensuring that the project stayed on track was challenging but ultimately rewarding.
______________________________________________________________________________________________________________________________
Credits
Product Manager
Machine Learning Engineer
Full-stack Developer
Tech Lead
Quality Assurance
Product Designer
Improving 360° feedback skills with an AI feedback coach that students love!
MY ROLE
Product designer
The TL;DR
THE TEAM
Product manager
Machine learning engineer
Full stack developer
QA specialist
Tech lead
THE TIMELINE
2 months
THE PRODUCT
Real-time student guidance. This is an AI-driven feedback coach that ensures personalised, effective feedback to improve students’ peer reviews.
THE PROBLEM
Feedback giving is one of the most important skills for the workforce but teachers don’t have time to provide guided, timely feedback to students. The previous efforts from the company to have a feedback coach are outdated, both from a design and technical perspective.
THE OUTCOMES
77%
CSAT from students
15%
Increase on
feedback length
130+
Teachers choosing
the feature
2500+
Students using
the feature
Transforming Student Feedback in Real-Time
This conversational coach gives real-time, AI-powered feedback to students on their peer reviews. It provides suggestions for improvement tailored to student language use and content of the review. Although having AI as a co-pilot can be daunting, students love it! This is demonstrated by the remarkable 77% customer satisfaction score.
This feature has the highest CSAT recorded in the product!
Where it lives
Feedbackfruits is a dynamic feedback tools provider nestled within university Learning Management Systems. With different configurable activities, it empowers teachers to craft impactful learning experiences, helping them save time in and outside the classroom.
Cracking the code of constructive feedback
Feedback giving is one of the most important skills for the workforce but teachers don’t have time to provide guided, timely feedback to students.
this results in students giving too short, overly positive or negative feedback that is not actionable.*
*insight from interviews with instructors from top level universities teaching a class of 50+ students.
Modernizing feedback coaching
Within our company, there was a previous effort to have an “Automated feedback coach” but unfortunately, it was outdated both from a design and technical perspective.
Essentially, the homegrown model provided eight possible suggestions to students' reviews, which didn’t scale and had an erratic performance.
The team approach
I was part of the Analytics and Insights team and together with the PM we analyzed the existing feature and came up with requirements for the redesign. For a two month period I closely collaborated with the developers and machine learning engineer to decide on the best solution to the problem. While they investigated on how we could leverage generative AI for the coach and iterated on the prompt, I focused on the experience that the students would have with it.
To know more about the technical side, click here
Old design
Interaction with the coach
Upholding transparency, empowering choice
Given that we were working with generative AI and Large Language Models, we needed to be compliant with the regulations in EU, US and APAC regions so that the feature could be used in all the partner institutions.
This involved several back and forth with our legal team to ensure that the design:
Reflect that AI is being used
Give the chance to turn the feature off
Include a link to an article about transparency with AI
Crafting a seamless user experience
My main job was making sure that the redesign would seamlessly integrate with the existing product while complying with the legal AI-regulations for all regions and keeping the focus on the prime action for the user: giving feedback to their peers.
Decision #1
I decided to use an existing pattern in the product that would convey the idea of a discussion between peers. I gave our coach a profile picture next to their suggestions, achieving a conversational effect.
Decision #2
With minor adjustments to the alignment and sizing of the fonts, I decided to keep the ‘Automated Feedback Coach’ title and add a discreet help icon to disclose information about what the feature does and how to disable it. It was important to ensure that the suggestions are coming from AI and that the student is in control at all times.
Decision #3
Since the transparency note prepared with the legal team didn't need to be displayed constantly, I chose to present it as a link only at the initial stage
Designing for every state
Part of the requirements was to design for all the possible states of the coach, this included and initial state with a presentation, a "thinking" state while suggestions were being processed, the actual feedback from the coach and an error state.
Connect to Content
Add layers or components to swipe between.
Flow states
Flow states
Designing for scalability
I ensured the design would fit various placements, such as sidebars, making it a flexible element in the product. Additionally, I considered language options, allowing students to receive feedback in their preferred language.
Making designs inclusive for all students
Last but not least, I needed to make sure the designs were accessible to our students. With the iterative efforts to be compliant with the WACG level 2.1, I annotated the designs with the relevant labels to make the elements tabbable and available to screen readers.
Accessibility annotations
Driving success, one feedback at a time
We aimed to make a real difference with this project, and the results speak for themselves.
These achievements highlight the true impact of our efforts!
We set out to hit a customer satisfaction score of 60%, but the students’ happiness pushed us to an impressive 77%. *the highest recorded in the entire product
We hoped for 10 CSAT survey responses and were blown away when over 400 came in, showing fantastic engagement.
On top of that, we saw amazing adoption of the feature from the instructors’ side, with 346 activities performed instead of the 15 we planned for.
Instructor
@ one of the world's top learning institutions
The coach was really straightforward to set up. And none of the students had any trouble using it, which is pretty big. […] it was helping them give more detailed feedback and gave them good tips on what to improve on and assisting giving detailed responses about specific things. I would rate the quality with: 8/10 (missing 2 points due to low sample size), uniqueness: 10/10 and would recommend to colleague: Oh, 10. For sure. 10
______________________________________________________________________________________________
Credits
Product Manager
Machine Learning Engineer
Full-stack Developer
Tech Lead
Quality Assurance
Product Designer
Final reflection
This project, completed in just two months, was a significant learning experience for me. I discovered an essential truth: real-world projects rarely follow the playbooks. Instead, you often have to leverage existing resources and knowledge to drive success.
For instance, we did not conduct new user interviews, as we built on an existing product and already understood the user needs. This allowed us to quickly and effectively enhance the solution, addressing users' immediate needs with confidence.
This project was a major milestone in developing my communication skills. Working with multiple stakeholders—from legal team, to the development team—required clear, consistent, and persuasive communication. Aligning everyone's vision and ensuring that the project stayed on track was challenging but ultimately rewarding.
This project, completed in just two months, was a significant learning experience for me. I discovered an essential truth: real-world projects rarely follow the playbooks. Instead, you often have to leverage existing resources and knowledge to drive success.
For instance, we did not conduct new user interviews, as we built on an existing product and already understood the user needs. This allowed us to quickly and effectively enhance the solution, addressing users' immediate needs with confidence.
This project was a major milestone in developing my communication skills. Working with multiple stakeholders—from legal team, to the development team—required clear, consistent, and persuasive communication. Aligning everyone's vision and ensuring that the project stayed on track was challenging but ultimately rewarding.
Improving 360° feedback skills with an AI feedback coach that students love!
MY ROLE
Product designer
THE TEAM
Product manager
Machine learning engineer
Full stack developer
QA specialist
Tech lead
THE TIMELINE
2 months
THE PRODUCT
Real-time student guidance. This is an AI-driven feedback coach that ensures personalised, effective feedback to improve students’ peer reviews.
THE PROBLEM
Feedback giving is one of the most important skills for the workforce but teachers don’t have time to provide guided, timely feedback to students. The previous efforts from the company to have a feedback coach are outdated, both from a design and technical perspective.
THE OUTCOMES
2500+
Students using the feature
77%
CSAT from students
15%
Increase on
feedback length
130+
Teachers choosing
the feature
2500+
Students using
the feature
Transforming Student Feedback in Real-Time
This conversational coach gives real-time, AI-powered feedback to students on their peer reviews. It provides suggestions for improvement tailored to student language use and content of the review. Although having AI as a co-pilot can be daunting, students love it! This is demonstrated by the remarkable 77% customer satisfaction score.
This feature has the highest CSAT recorded in the product!
Where it lives
Feedbackfruits is a dynamic feedback tools provider nestled within university Learning Management Systems. With different configurable activities, it empowers teachers to craft impactful learning experiences, helping them save time in and outside the classroom.
Cracking the code of constructive feedback
Feedback giving is one of the most important skills for the workforce but teachers don’t have time to provide guided, timely feedback to students.
this results in students giving too short, overly positive or negative feedback that is not actionable.*
*insight from interviews with instructors from top level universities teaching a class of 50+ students.
Modernizing feedback coaching
Within our company, there was a previous effort to have an “Automated feedback coach” but unfortunately, it was outdated both from a design and technical perspective.
Essentially, the homegrown model provided eight possible suggestions to students' reviews, which didn’t scale and had an erratic performance.
The team approach
I was part of the Analytics and Insights team and together with the PM we analyzed the existing feature and came up with requirements for the redesign. For a two month period I closely collaborated with the developers and machine learning engineer to decide on the best solution to the problem. While they investigated on how we could leverage generative AI for the coach and iterated on the prompt, I focused on the experience that the students would have with it.
To know more about the technical side, click here
Old design
Interaction with the coach
Upholding transparency, empowering choice
Given that we were working with generative AI and Large Language Models, we needed to be compliant with the regulations in EU, US and APAC regions so that the feature could be used in all the partner institutions.
This involved several back and forth with our legal team to ensure that the design:
Reflect that AI is being used
Give the chance to turn the feature off
Include a link to an article about transparency with AI
Crafting a seamless user experience
My main job was making sure that the redesign would seamlessly integrate with the existing product while complying with the legal AI-regulations for all regions and keeping the focus on the prime action for the user: giving feedback to their peers.
Decision #1
I decided to use an existing pattern in the product that would convey the idea of a discussion between peers. I gave our coach a profile picture next to their suggestions, achieving a conversational effect.
Decision #2
With minor adjustments to the alignment and sizing of the fonts, I decided to keep the ‘Automated Feedback Coach’ title and add a discreet help icon to disclose information about what the feature does and how to disable it. It was important to ensure that the suggestions are coming from AI and that the student is in control at all times.
Decision #3
Since the transparency note prepared with the legal team didn't need to be displayed constantly, I chose to present it as a link only at the initial stage
Designing for every state
Part of the requirements was to design for all the possible states of the coach, this included and initial state with a presentation, a "thinking" state while suggestions were being processed, the actual feedback from the coach and an error state.
Flow states
Designing for scalability
I ensured the design would fit various placements, such as sidebars, making it a flexible element in the product. Additionally, I considered language options, allowing students to receive feedback in their preferred language.
Making designs inclusive for all students
Last but not least, I needed to make sure the designs were accessible to our students. With the iterative efforts to be compliant with the WACG level 2.1, I annotated the designs with the relevant labels to make the elements tabbable and available to screen readers.
Accessibility annotations
Driving success, one feedback at a time
We aimed to make a real difference with this project, and the results speak for themselves.
These achievements highlight the true impact of our efforts!
We set out to hit a customer satisfaction score of 60%, but the students’ happiness pushed us to an impressive 77%. *the highest recorded in the entire product
We hoped for 10 CSAT survey responses and were blown away when over 400 came in, showing fantastic engagement.
On top of that, we saw amazing adoption of the feature from the instructors’ side, with 346 activities performed instead of the 15 we planned for.
Instructor
@ one of the world's top learning institutions
The coach was really straightforward to set up. And none of the students had any trouble using it, which is pretty big. […] it was helping them give more detailed feedback and gave them good tips on what to improve on and assisting giving detailed responses about specific things. I would rate the quality with: 8/10 (missing 2 points due to low sample size), uniqueness: 10/10 and would recommend to colleague: Oh, 10. For sure. 10
______________________________
Final reflection
This project, completed in just two months, was a significant learning experience for me. I discovered an essential truth: real-world projects rarely follow the playbooks. Instead, you often have to leverage existing resources and knowledge to drive success.
For instance, we did not conduct new user interviews, as we built on an existing product and already understood the user needs. This allowed us to quickly and effectively enhance the solution, addressing users' immediate needs with confidence.
This project was a major milestone in developing my communication skills. Working with multiple stakeholders—from legal team, to the development team—required clear, consistent, and persuasive communication. Aligning everyone's vision and ensuring that the project stayed on track was challenging but ultimately rewarding.
This project, completed in just two months, was a significant learning experience for me. I discovered an essential truth: real-world projects rarely follow the playbooks. Instead, you often have to leverage existing resources and knowledge to drive success.
For instance, we did not conduct new user interviews, as we built on an existing product and already understood the user needs. This allowed us to quickly and effectively enhance the solution, addressing users' immediate needs with confidence.
This project was a major milestone in developing my communication skills. Working with multiple stakeholders—from legal team, to the development team—required clear, consistent, and persuasive communication. Aligning everyone's vision and ensuring that the project stayed on track was challenging but ultimately rewarding.