In today’s rapidly evolving educational landscape, the demand for personalized learning experiences is growing exponentially. Organizations are seeking ways to enhance student engagement, adapt to individual learning needs, and offer tailored content that enriches the overall educational journey. This is where AI-powered solutions like those developed by EDT&Partners, the global education and technology consulting firm, come into play. Their approach simplifies the implementation of AI, allowing organizations to easily integrate these cutting-edge solutions with their existing platforms while offering impactful, scalable results.

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Personalization in education is not just a buzzword; it’s a critical need. Students learn at different paces, have varying interests, and require content that meets them where they are. For educators and educational platforms, addressing these individual needs can be a daunting challenge—without the right technology in place. That’s where AI steps in.

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EDT&Partners, in collaboration with AWS, has developed an AI-powered recommendation engine designed to offer customized content, adjust learning paces, and provide deep insights into student progress. By integrating this AI solution, companies can quickly enhance their platforms, offering personalized experiences that truly resonate with their users.

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Little Thinking Minds, a leading EdTech company in the Arabic language learning space, sought to elevate user engagement by delivering tailored content based on students’ reading capabilities and interests. Their goal was to create a personalized learning experience that dynamically adjusts to each student’s progress.

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Using the AI-powered recommendation engine developed by EDT&Partners they were able to achieve this by implementing two key features:

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1. Personalized Learning Pace Adjustment: The system recommends content based on students’ academic performance, ensuring each learner progresses at their own pace.
2. Personalized Content Suggestion: The platform adapts to student preferences, suggesting materials that align with their interests and learning objectives.
3. Data Monetization and Analytics: By uncovering valuable trends and patterns through its analytics, the system generates insights essential for strategic decision-making, enabling organizations to leverage these insights for targeted marketing and product development, thereby creating new revenue opportunities.

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Additionally, a Progress Tracking Dashboard allows educators and administrators to monitor individual learning journeys, providing data-driven insights that can be used to further customize the educational experience. These features not only enhance student engagement but also give educators the tools to offer more impactful learning experiences—ensuring that no student is left behind.

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One of the key differentiators of this AI solution is its ease of implementation. Built using AWS technologies like Amazon Aurora MySQL and Amazon Bedrock, the system is highly customizable, scalable, and easy to integrate with existing platforms. Its low-code/no-code model means that even organizations without extensive technical resources can quickly deploy and begin leveraging its powerful personalization features.

‍

For companies in EdTech and beyond, this opens the door to enhanced customer experiences without the need for a full-scale technical overhaul. In addition, the built-in analytics and dashboards provide insights into data that many organizations may not have previously had access to, unlocking new opportunities for optimization and growth.

‍

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At EDT&Partners, we believe in the transformative power of technology to drive meaningful change in education—and beyond. The success of our AI recommendation engine showcases how our solutions can help organizations scale while meeting the unique needs of their customers. But we’re not stopping there. Our vision extends beyond education to other sectors like telecommunications, where the need for personalization and data-driven insights is just as critical.

‍

By continuing to innovate and inspire, EDT&Partners remains at the forefront of AI-driven solutions, empowering organizations to make a real impact through technology advancement.

‍

AI has the potential to transform the way organizations approach personalized learning and user engagement. By leveraging AI-powered recommendation engines, other educational platforms and companies can similarly enhance their offerings, delivering tailored experiences that meet the unique needs of each user. Our goal at EDT&Partners is to support organizations in using AI to create meaningful, lasting change—whether in education or beyond.

Our commitment to EdTech, innovation, and customer impact will continue to shape the future—not only in education but across industries where AI has the potential to revolutionize how organizations meet their customers’ needs.

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Little Thinking Minds is aiming to elevate the user engagement with the platform through delivering tailored and customized content to users based on areas of interest and reading capabilities. In addition, a fine grained dashboard is required to visual different metrics. The above results in three defined product goals.

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Product Goals

Goal 1: Personalized Learning Pace Adjustment

Customize the recommended content for students based on their achieved academic goals, learning Arabic language. The overall platform content must be all labelled and dissected per level. The system must be able to generate the next piece of content for the user based on their reading capacities (i.e., the scores achieved on their past exams).

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Goal 2: Personalized Content Suggestion

Customize the recommended content for students based on their reading preferences. The overall platform content must be all labelled and dissected per category. The system must be able to generate the next piece of content for the user based on their reading preferences (i.e., the themes and categories that interest the user the most).

‍

Goal 3: Progress Tracking Dashboard

Implement a Progress Tracking Dashboard to visually showcase the learning journey of each student, enabling a more transparent and intuitive tracking of progress. Different metrics and dashboards must be set up and configured. These dashboards will be used by the business to monitor and track the user’s progress.

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Technical Implementation

Combining “Personalized Content Suggestion” and “Learning Pace Adjustment”

Due to the similarities in the requirements and desired outcome for both the Personalized Content Suggest, as well as the Learning Pace Adjustment, it has been decided that one service is enough to achieve both goals. In light of the above, a Content Recommendation Engine designed as a RESTful microservice will be created using the Python framework, with three endpoints exposed: Readiness, Content Addition and Content Suggestion. The service uses Amazon Aurora MySQL as its persistent datastore, and Amazon Bedrock as its LLM of choice.

‍

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Progress Tracking Dashboard

‍

The Progress Tracking Dashboard is a simple system that uses an Amazon Aurora MySQL database to store the required data. Amazon Quicksight will be securely connected to fetch and display the required visualizations, either through pre-defined dashboards, or custom queries. For cost optimization purposes, the same physical database created for G1 and G2 can be utilized for this purpose as well. The database can be logically dissected between the two goals to achieve.

‍

Requirements

The data to be saved and visualized is highly dependent on the business and product requirements. In this regard, LTM must specify the metrics required, based on which the database can be populated and queries created. For the moment, G3 remains an architectural aspiration that will be developed after delivering G1 and G2.

‍

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Project Outcomes

With the intention to provide transparency of how these details can be shared with other departments and teams, we wanted to provide some notes:

‍

• The solutions will be developed and deployed in the AWS accounts owned by EDT&Partners. Secure access will be given to the LTM technical team.
• The system will use a subset of data prepared by the LTM team. The used data should simulate real use case scenarios that will be expected by LTM.
• LTM can further expand on the current dataset by injecting additional data.
• The application, infrastructure, as well as preliminary testing scenarios will be documented and shared with LTM.
• Training will be offered to LTM in order to fully understand and take ownership of the application and underlying AWS infrastructure.
• A cost estimate will be performed for hosting and maintaining the application, offering LTM maximum visibility on the cost to be expected for integrating this service.

Personalization in education is not just a buzzword; it’s a critical need. Students learn at different paces, have varying interests, and require content that meets them where they are. For educators and educational platforms, addressing these individual needs can be a daunting challenge—without the right technology in place. That’s where AI steps in.

‍

EDT&Partners, in collaboration with AWS, has developed an AI-powered recommendation engine designed to offer customized content, adjust learning paces, and provide deep insights into student progress. By integrating this AI solution, companies can quickly enhance their platforms, offering personalized experiences that truly resonate with their users.

‍

‍

Little Thinking Minds, a leading EdTech company in the Arabic language learning space, sought to elevate user engagement by delivering tailored content based on students’ reading capabilities and interests. Their goal was to create a personalized learning experience that dynamically adjusts to each student’s progress.

‍

Using the AI-powered recommendation engine developed by EDT&Partners they were able to achieve this by implementing two key features:

‍

1. Personalized Learning Pace Adjustment: The system recommends content based on students’ academic performance, ensuring each learner progresses at their own pace.
2. Personalized Content Suggestion: The platform adapts to student preferences, suggesting materials that align with their interests and learning objectives.
3. Data Monetization and Analytics: By uncovering valuable trends and patterns through its analytics, the system generates insights essential for strategic decision-making, enabling organizations to leverage these insights for targeted marketing and product development, thereby creating new revenue opportunities.

‍

Additionally, a Progress Tracking Dashboard allows educators and administrators to monitor individual learning journeys, providing data-driven insights that can be used to further customize the educational experience. These features not only enhance student engagement but also give educators the tools to offer more impactful learning experiences—ensuring that no student is left behind.

‍

One of the key differentiators of this AI solution is its ease of implementation. Built using AWS technologies like Amazon Aurora MySQL and Amazon Bedrock, the system is highly customizable, scalable, and easy to integrate with existing platforms. Its low-code/no-code model means that even organizations without extensive technical resources can quickly deploy and begin leveraging its powerful personalization features.

‍

For companies in EdTech and beyond, this opens the door to enhanced customer experiences without the need for a full-scale technical overhaul. In addition, the built-in analytics and dashboards provide insights into data that many organizations may not have previously had access to, unlocking new opportunities for optimization and growth.

‍

‍

At EDT&Partners, we believe in the transformative power of technology to drive meaningful change in education—and beyond. The success of our AI recommendation engine showcases how our solutions can help organizations scale while meeting the unique needs of their customers. But we’re not stopping there. Our vision extends beyond education to other sectors like telecommunications, where the need for personalization and data-driven insights is just as critical.

‍

By continuing to innovate and inspire, EDT&Partners remains at the forefront of AI-driven solutions, empowering organizations to make a real impact through technology advancement.

‍

AI has the potential to transform the way organizations approach personalized learning and user engagement. By leveraging AI-powered recommendation engines, other educational platforms and companies can similarly enhance their offerings, delivering tailored experiences that meet the unique needs of each user. Our goal at EDT&Partners is to support organizations in using AI to create meaningful, lasting change—whether in education or beyond.

Our commitment to EdTech, innovation, and customer impact will continue to shape the future—not only in education but across industries where AI has the potential to revolutionize how organizations meet their customers’ needs.

‍

Little Thinking Minds is aiming to elevate the user engagement with the platform through delivering tailored and customized content to users based on areas of interest and reading capabilities. In addition, a fine grained dashboard is required to visual different metrics. The above results in three defined product goals.

‍

Product Goals

Goal 1: Personalized Learning Pace Adjustment

Customize the recommended content for students based on their achieved academic goals, learning Arabic language. The overall platform content must be all labelled and dissected per level. The system must be able to generate the next piece of content for the user based on their reading capacities (i.e., the scores achieved on their past exams).

‍

Goal 2: Personalized Content Suggestion

Customize the recommended content for students based on their reading preferences. The overall platform content must be all labelled and dissected per category. The system must be able to generate the next piece of content for the user based on their reading preferences (i.e., the themes and categories that interest the user the most).

‍

Goal 3: Progress Tracking Dashboard

Implement a Progress Tracking Dashboard to visually showcase the learning journey of each student, enabling a more transparent and intuitive tracking of progress. Different metrics and dashboards must be set up and configured. These dashboards will be used by the business to monitor and track the user’s progress.

‍

Technical Implementation

Combining “Personalized Content Suggestion” and “Learning Pace Adjustment”

Due to the similarities in the requirements and desired outcome for both the Personalized Content Suggest, as well as the Learning Pace Adjustment, it has been decided that one service is enough to achieve both goals. In light of the above, a Content Recommendation Engine designed as a RESTful microservice will be created using the Python framework, with three endpoints exposed: Readiness, Content Addition and Content Suggestion. The service uses Amazon Aurora MySQL as its persistent datastore, and Amazon Bedrock as its LLM of choice.

‍

‍

Progress Tracking Dashboard

‍

The Progress Tracking Dashboard is a simple system that uses an Amazon Aurora MySQL database to store the required data. Amazon Quicksight will be securely connected to fetch and display the required visualizations, either through pre-defined dashboards, or custom queries. For cost optimization purposes, the same physical database created for G1 and G2 can be utilized for this purpose as well. The database can be logically dissected between the two goals to achieve.

‍

Requirements

The data to be saved and visualized is highly dependent on the business and product requirements. In this regard, LTM must specify the metrics required, based on which the database can be populated and queries created. For the moment, G3 remains an architectural aspiration that will be developed after delivering G1 and G2.

‍

‍

Project Outcomes

With the intention to provide transparency of how these details can be shared with other departments and teams, we wanted to provide some notes:

‍

• The solutions will be developed and deployed in the AWS accounts owned by EDT&Partners. Secure access will be given to the LTM technical team.
• The system will use a subset of data prepared by the LTM team. The used data should simulate real use case scenarios that will be expected by LTM.
• LTM can further expand on the current dataset by injecting additional data.
• The application, infrastructure, as well as preliminary testing scenarios will be documented and shared with LTM.
• Training will be offered to LTM in order to fully understand and take ownership of the application and underlying AWS infrastructure.
• A cost estimate will be performed for hosting and maintaining the application, offering LTM maximum visibility on the cost to be expected for integrating this service.