Week #1 #

Presentation #

Team Formation and Project Proposal #

Team Members #

Value Proposition #

• Identify the Problem:

The A-level Economics exam preparation process currently lacks a structured and systematic approach, creating significant challenges for students. In contrast to the Russian Unified State Exam (ЕГЭ), which has a well-defined structure that helps students clearly understand their performance in various topics, the A-levels do not offer similar clarity. This ambiguity in the A-level examination system makes it difficult for students, especially newcomers, to ascertain which topics they have mastered and which they need to focus on. Additionally, the primary resources available for A-level exam preparation are typically static PDF documents provided by educators, which do not facilitate interactive learning or performance tracking. Unlike the ЕГЭ, where there are numerous online platforms that provide structured practice and feedback, A-level students must often resort to manually organizing their study materials and independently tracking their progress, leading to a disjointed and inefficient study process. This lack of structured preparation resources and feedback mechanisms places A-level students at a disadvantage, making the exam preparation experience unnecessarily challenging and stressful.

• Solution Description:

To effectively address the structured preparation deficiencies in A-level Economics exam preparation, we propose a web application that uses state-of-the-art machine learning technology to transform static PDF documents into dynamic, interactive study materials. Upon uploading their practice question PDFs, students will benefit from the app’s text parsing algorithms that systematically extract and analyze questions. Each question is then categorized by the ML model according to its topic and difficulty level, and transformed into interactive cards displaying essential metadata like difficulty and topic category. This approach not only makes navigation and review more straightforward but also enhances the overall study experience by providing a more organized and engaging learning environment.

• Benefits to Users:

The web application designed for A-level Economics exam preparation offers several key benefits to its users. Firstly, it transforms the traditionally static and disjointed study materials into a cohesive and interactive format, significantly improving engagement and retention of information. The ability to upload and parse PDFs into categorized questions allows students to clearly understand which areas they have covered and which they need to focus on, addressing the confusion often associated with the A-level’s unstructured format. Each question is presented with detailed metadata, such as difficulty and topic, making it easier for students to target their studies effectively and efficiently. Additionally, by consolidating all study materials into a single platform, the app reduces the need for multiple external tools, streamlining the preparation process and making study sessions more productive. This structured and user-friendly approach ultimately aids in reducing the stress and uncertainty typically associated with exam preparation, making the learning process more pleasant and less overwhelming.

• Differentiation:

The proposed web application stands out in the A-level Economics exam preparation market through several distinct features. Unlike existing resources, which predominantly consist of static PDFs and lack interactivity, our application utilizes advanced machine learning algorithms to parse and categorize questions from uploaded documents. This not only provides a more interactive learning environment but also ensures that each question is accurately identified by topic and difficulty level, a capability not commonly found in other study aids. Furthermore, the ability to transform these questions into interactive cards with essential metadata allows for a level of engagement and personalized study that traditional methods do not offer. This approach directly addresses the specific needs of A-level students, who currently lack dedicated platforms that cater to the nuanced demands of their curriculum, setting our solution apart in an environment where generic educational tools are the norm. Our application’s focus on user-friendly design and tailored content specifically for A-level Economics positions it as a unique and valuable tool in enhancing students’ preparation and confidence in facing their examinations.

• User Impact:

The impact of our web application on A-level Economics students is substantial and multifaceted. By providing a structured and interactive platform for exam preparation, the app directly enhances students’ ability to efficiently manage their study time and focus on areas needing improvement. The transformation of static PDFs into dynamic, interactive cards with detailed metadata allows students to engage more deeply with the material, promoting better understanding and retention of economic concepts. This targeted approach helps diminish the overwhelming aspects of exam preparation, thereby reducing stress and increasing confidence. As students use the application to consistently review and assess their progress, they are likely to see measurable improvements in their understanding and performance in exams.

• User Testimonials or Use Cases:

Testimonial 1 #

“Before using this app, I felt lost with piles of unorganized PDFs and notes. Now, I can quickly upload my resources and instantly get a clear breakdown of questions by topic and difficulty. It’s like having a personal tutor that organizes everything for me. My preparation is now much more focused and effective.”

• Emily, A-level Economics Student

Use Case 1 #

John, an A-level Economics teacher, incorporates the application into his teaching regimen. He recommends that his students upload their practice PDFs to the app, allowing them to independently manage their revision while he tracks their progress through the platform. This not only makes his students more self-sufficient but also enables John to provide targeted assistance based on the analytics provided by the app.

Testimonial 2 #

“The interactive question cards have changed the way I study. I can now see exactly where my weak points are and get suggestions on what to study next. This app has definitely relieved a lot of the stress of A-level exam prep.”

• Liam, A-level Economics Student

Use Case 2 #

Sarah, a student struggling with time management and exam anxiety, uses the application to systematically approach her revision. By focusing on high-difficulty questions identified by the app, she efficiently allocates her study time to areas that most impact her exam performance, leading to a more confident and prepared state on exam day.

Lean Questionnaire #

Please answer the following questions related to the lean methodology:

1. What problem or need does your software project address?

   Our software project addresses the significant challenge of unstructured and non-interactive preparation for A-level Economics exams. Students are currently dependent on static PDF files for practice, which lack feedback and tracking mechanisms. This leads to inefficient study sessions where students struggle to identify key areas for improvement or topic mastery. Our application resolves this by employing a machine learning model to analyze the uploaded PDFs, identifying and categorizing each question by topic. This transformation enables a dynamic, interactive study environment, allowing students to engage more effectively with the material and better prepare for their exams.

2. Who are your target users or customers?

   Our target users are primarily A-level Economics students who require structured and efficient study tools to prepare for their exams. Additionally, our application is also valuable for A-level Economics teachers and tutors who seek to enhance their teaching resources and provide their students with a more interactive and effective way to learn and review exam materials. This dual focus allows us to serve both self-studying students and educational professionals, enhancing the learning experience and improving educational outcomes across this academic community.

3. How will you validate and test your assumptions about the project?

   To validate and test our project assumptions, we will gather feedback directly from A-level Economics tutors and students that we personally know. This approach allows for quick and direct insights into how well our application meets the needs of its intended users. By engaging with a familiar and accessible group, we can efficiently collect qualitative feedback on the usability, functionality, and overall effectiveness of our web service.

4. What metrics will you use to measure the success of your project?

   To measure the success of our project, we will track user retention rates to understand the long-term engagement with our application, and gather user feedback scores to assess satisfaction with the app’s features and usability. Additionally, we’ll monitor the accuracy of our machine learning model in categorizing questions, which is vital for ensuring the app’s effectiveness.

5. How do you plan to iterate and pivot if necessary based on user feedback?

   We plan to implement a responsive iteration cycle, where user feedback directly informs continuous improvements to the application. By analyzing feedback from A-level tutors and students, we will quickly address any issues and make adjustments to enhance functionality and usability. Our development approach is flexible, allowing us to pivot features or strategies to better meet user needs, ensuring the application remains effective and relevant. Regular updates will be guided by this feedback to ensure ongoing alignment with user expectations.

Leveraging AI, Open-Source, and Experts #

We will use machine learning to analyze and categorize A-level Economics questions from uploaded PDFs and OpenAI/YaGPT API to work with some pre-finetuned large language models. While we are still deciding on the specific open-source tools to use, we aim to leverage their robustness and community support for better development. Feedback from A-level Economics tutors will guide the accuracy and relevance of our content, ensuring it aligns with educational standards and effectively supports student learning.

Defining the Vision for Your Project #

• Overview:

Our project, the A-Level Economics web application, is designed to transform the way students prepare for their A-level exams by integrating advanced technological solutions to address current educational challenges. The primary purpose of this initiative is to provide a streamlined, user-friendly platform that assists students in systematically organizing and reviewing exam material. Unlike existing preparation methods, which often involve disjointed resources such as PDFs and physical flashcards, our application allows students to upload exam question PDFs directly into the system. The app intelligently parses these documents to extract individual questions, categorizes them, and stores them in a structured database. Each question is converted into a digital card that includes key metadata such as difficulty and topic category, which can be further enriched by the user.

This digital transformation not only simplifies the revision process but also enhances it through the application of a state-of-the-art machine learning model. This model analyzes questions to determine their type and the economic concepts they test, guiding students towards a more focused and effective study approach. By doing so, the application addresses a significant gap in the availability of structured, accessible, and comprehensive exam preparation tools specifically tailored for A-Level Economics students.

The intended benefit of our project is two-fold: enhancing educational outcomes by providing a more organized and efficient revision experience, and reducing the stress and uncertainty often associated with exam preparation. As students gain better insights into their performance and areas of need, they can adjust their study strategies accordingly, leading to improved understanding and retention of subject matter. Ultimately, our project aims to empower students to approach their exams with confidence, supported by a robust tool that adapates to their individual learning needs. This not only impacts students but also educators, who can utilize the platform to track progress and identify common areas of difficulty among their students, enabling more targeted teaching interventions.

• Schematic Drawings:

.

• Tech Stack:

For the machine learning component, we will utilize Python and C++ for optimized model performance, IPython Notebooks for experimentation, PyTorch as the deep learning framework, and Word2Vec, FastText, or other embedders for text representation. We may also incorporate OpenAI or YaGPT API for advanced natural language processing capabilities, along with custom implementations of SVMs and other classical ML algorithms, and LSTMs for sequence modeling.

For the backend, we plan to adopt Docker for containerization and microservices architecture for modularity and ease of maintenance. The frontend technology stack is yet to be determined but will be chosen based on factors such as user experience, development speed, and compatibility with the backend infrastructure.