JumboCode/lcs-tutoring
Oct 2024 – Apr 2025
6 Months active
Languages Used
CSSHTMLJavaScriptTypeScriptSQL
Technical Skills
Component-Based ArchitectureFront-end DevelopmentFrontend DevelopmentNext.jsReactTypeScript
annewu109
PROFILE
Annewu109
Anne Wu contributed to the JumboCode/lcs-tutoring repository by building and refining core features that streamline tutor-tutee matching, improve user experience, and enhance site performance. She developed reusable React components for dynamic content, implemented end-to-end matching workflows with TypeScript and Node.js, and optimized frontend assets for faster load times. Anne addressed usability issues such as pop-up dismissal and standardized branding, while also improving tutor search reliability through precise filtering logic and robust API integration. Her work demonstrated depth in both frontend and backend development, resulting in a maintainable, responsive application that supports efficient onboarding and data-driven decision making.
Overall Statistics
Feature vs Bugs
82%Features
Repository Contributions
16Total
Bugs
2
Commits
16
Features
9
Lines of code
783
Activity Months6
Your Network
9 peopleShared Repositories
9
Work History
April 2025
4 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for JumboCode/lcs-tutoring focused on delivering three prioritized items: a UX reliability fix, branding and labeling improvements, and frontend asset optimization to improve performance. The work contributed to improved user experience, consistent branding and faster page loads, aligning with business goals to boost engagement and reduce support friction.
4 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for JumboCode/lcs-tutoring focused on delivering three prioritized items: a UX reliability fix, branding and labeling improvements, and frontend asset optimization to improve performance. The work contributed to improved user experience, consistent branding and faster page loads, aligning with business goals to boost engagement and reduce support friction.
April 2025
March 2025
3 Commits • 1 Features
Mar 1, 20252025-03 monthly summary: Delivered end-to-end TutorMatcher-based tutor-tutee matching system for JumboCode/lcs-tutoring. Implemented integration with matchSuggestionsController, wired fetch and match calculation, and produced frontend-ready structured data. Completed backend-to-frontend connection and established data pipelines for UI and analytics. No major bugs reported; feature delivery enhances matching accuracy, reduces manual effort, and enables data-driven decision making.
March 2025
3 Commits • 1 Features
Mar 1, 20252025-03 monthly summary: Delivered end-to-end TutorMatcher-based tutor-tutee matching system for JumboCode/lcs-tutoring. Implemented integration with matchSuggestionsController, wired fetch and match calculation, and produced frontend-ready structured data. Completed backend-to-frontend connection and established data pipelines for UI and analytics. No major bugs reported; feature delivery enhances matching accuracy, reduces manual effort, and enables data-driven decision making.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for JumboCode/lcs-tutoring focusing on the Tutor-Tutee Match delivery and its impact. Delivered an end-to-end Tutor-Tutee Match Approval workflow, combining a new UI with a backend API to process approvals and updating the match suggestion UI to support the new selection mechanism. This work streamlines the tutoring matchmaking process and reduces manual steps, accelerating decision making and improving alignment between tutors and tutees.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for JumboCode/lcs-tutoring focusing on the Tutor-Tutee Match delivery and its impact. Delivered an end-to-end Tutor-Tutee Match Approval workflow, combining a new UI with a backend API to process approvals and updating the match suggestion UI to support the new selection mechanism. This work streamlines the tutoring matchmaking process and reduces manual steps, accelerating decision making and improving alignment between tutors and tutees.
January 2025
December 2024
1 Commits
Dec 1, 2024December 2024 monthly summary for JumboCode/lcs-tutoring focusing on improving tutor search reliability and data integrity. Key work included stabilizing the tutor filtering experience by ensuring filters apply to both matched and unmatched tutors and by introducing a new inArray helper. The frontend data fetch was corrected to retrieve tutor data rather than tutee data, aligning UI results with business expectations. The improvements were validated end-to-end, reducing confusion and increasing trust in search results.
December 2024
1 Commits
Dec 1, 2024December 2024 monthly summary for JumboCode/lcs-tutoring focusing on improving tutor search reliability and data integrity. Key work included stabilizing the tutor filtering experience by ensuring filters apply to both matched and unmatched tutors and by introducing a new inArray helper. The frontend data fetch was corrected to retrieve tutor data rather than tutee data, aligning UI results with business expectations. The improvements were validated end-to-end, reducing confusion and increasing trust in search results.
November 2024
3 Commits • 2 Features
Nov 1, 2024November 2024 — Delivered two key features in JumboCode/lcs-tutoring, focusing on tutor search usability and cross-device consistency. Tutor Filtering Enhancements added disability preference and tutoring mode filters to the tutor search, updated the filterTutors logic to apply the new criteria, and included a test case demonstrating usage. Global Responsive UI Improvements implemented Tailwind CSS-based adjustments for padding, margins, and layouts across the home page, getInvolved, and intro sections to ensure a consistent experience on mobile and desktop. Impact: improved tutor match relevance, better accessibility alignment, and a smoother user experience, supporting higher engagement and conversion. Technologies/skills demonstrated include React front-end, Tailwind CSS, test-driven development, and component-based architecture.
3 Commits • 2 Features
Nov 1, 2024November 2024 — Delivered two key features in JumboCode/lcs-tutoring, focusing on tutor search usability and cross-device consistency. Tutor Filtering Enhancements added disability preference and tutoring mode filters to the tutor search, updated the filterTutors logic to apply the new criteria, and included a test case demonstrating usage. Global Responsive UI Improvements implemented Tailwind CSS-based adjustments for padding, margins, and layouts across the home page, getInvolved, and intro sections to ensure a consistent experience on mobile and desktop. Impact: improved tutor match relevance, better accessibility alignment, and a smoother user experience, supporting higher engagement and conversion. Technologies/skills demonstrated include React front-end, Tailwind CSS, test-driven development, and component-based architecture.
November 2024
October 2024
4 Commits • 3 Features
Oct 1, 2024October 2024 - JumboCode/lcs-tutoring: Delivered core frontend content updates to improve student and parent experience and content manageability. Implemented About Us page with routing and homepage integration; added Get Involved section to guide participation; introduced Past Tutors section with a reusable Testimonial component, enabling dynamic tutor display. These features streamline content updates, improve navigation, and support marketing goals. Future work includes refining content and expanding testimonials data. Technologies used include React-based components, SPA routing, and component reuse for maintainable UI. Business value: clearer onboarding, higher engagement opportunities, and faster content updates across the tutoring site.
October 2024
4 Commits • 3 Features
Oct 1, 2024October 2024 - JumboCode/lcs-tutoring: Delivered core frontend content updates to improve student and parent experience and content manageability. Implemented About Us page with routing and homepage integration; added Get Involved section to guide participation; introduced Past Tutors section with a reusable Testimonial component, enabling dynamic tutor display. These features streamline content updates, improve navigation, and support marketing goals. Future work includes refining content and expanding testimonials data. Technologies used include React-based components, SPA routing, and component reuse for maintainable UI. Business value: clearer onboarding, higher engagement opportunities, and faster content updates across the tutoring site.
Activity
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Quality Metrics
Correctness85.0%
Maintainability85.0%
Architecture80.0%
Performance82.4%
AI Usage21.2%
Skills & Technologies
Programming Languages
CSSHTMLJavaScriptSQLTypeScript
Technical Skills
API DevelopmentAPI IntegrationAsset OptimizationBackend DevelopmentComponent-Based ArchitectureDatabase InteractionDatabase ManagementFront-end DevelopmentFrontend DevelopmentJavaScriptNext.jsNode.jsReactResponsive DesignTailwind CSS
Repositories Contributed To
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