IBM SkillsBuild Learning Pathway Advisor

IBM 3 - PORTAL. SkillsBuild. Learning Pathway. Advisor.

Agenda. 01. Team. Meet the team & responsibilities.

[Audio] Team. 01. 01. Team.

[Audio] Meet The Team Each member's key responsibility and professional takeaway from this project. Sharmila Nagaraju Yiwen Ma Project Lead & Business Problem Recommendation Logic & Technical Docs Translating domain logic into a deterministic, auditable scoring system Leading cross functional delivery under enterprise constraints Ingyin Hmwe Dileep Madhugiri Lakshmaiah UI/UX design, logo creation, layout structuring App Development & Flow, Firebase Deployment & Course Dataset Architecting a responsive 4-tab React interface for student first UX End to end cloud deployment with persistent, real time data storage Fardeen Ahmed Shaik Aayush Bairagi System Testing & Validation QA & Performance Validation Ensuring rule engine correctness across edge cases and profile types Validating end to end user flows for reliability and performance IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · 01 · team.

[Audio] Pitch. 02. 02. Pitch.

A screenshot of a computer and a phone AI-generated content may be incorrect..

[Audio] What We Built A live web application that maps student profiles to personalised I-B-M SkillsBuild learning pathways using a six rule scoring engine. How it works Student profile Six rule score Ranked pathway Feedback captured Rule Based Engine Live Firebase Deployment Scores each course using six rules: role, degree, skill gap, level, prerequisites and interests. No A-P-I dependency. Auditable by design. Built as a React web app with Firebase authentication and persistent data storage. Student profiles, saved courses and feedback are retained across sessions. role 35 degree 25 gap 20 level 15 4-Tab Interface Feedback Loop My Profile · Recommendations · Dashboard · Feedback. Ranked cards include “Why this?” explanations, live learning stats and star rating feedback. Thumbs up/down per card and session level star ratings are captured in Firebase, enabling data driven weight adjustment in future iterations. IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · 02 · pitch.

IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · 02 · PITCH.

A screenshot of a computer AI-generated content may be incorrect..

[Audio] The Business Problem 1 in 3 73% learners abandon online courses without personalised guidance of students say generic course lists don't reflect their goals Img_0515.mov This is not a UI problem. It is an analytics problem — reflecting a structural absence of recommendation logic in an otherwise high quality platform. IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · 02 · pitch.

[Audio] Application Flow & 4-Tab Interface Each tab is a distinct student journey step — users never need to guess what to do next. My Profile Recommendations Dashboard Feedback Degree programme Ranked pathway cards Live learning stats Star rating (1–5) Year of study 'Why this?' panel Saved courses list Free text comments Academic interests Match % display Progress tracking History panel Save & Start Course C-T-A-s Target industry & role Persistent via Firebase Existing skills tags Thumbs up / down Design decision: linear flow guides students from input → output → tracking → improvement, reducing drop off at each stage. IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · UI / UX.

[Audio] Design Process & Logo Creation Designed a clear logo, colour palette, and layout. Logo Creation Colour & Typography SkillsPath — logo conveys guidance and learning. Combines I-B-M blue with a clean wordmark for instant brand recognition across the 4-tab interface. Primary: #0F62FE · Text: #111111 · Background: #F8F9FB · Accent: #E8F1FF Font: Calibri for readability. I-B-M Blue as the primary accent. Neutral greys keep attention on content..

[Audio] Evidence. 03. 03. Evidence.

[Audio] Why The Metrics Are Appropriate Metric How Measured Why Appropriate Recommendation Relevance Directly reflects whether the engine’s output is useful, which is the primary objective of the system. Star rating (1–5) per session Star rating (1–5) per session Per Card Relevance Granular signal enabling future per rule weight recalibration based on real usage data. Thumbs up / down per recommendation Thumbs up / down per recommendation Engagement Depth A saved course indicates genuine intent, making it a stronger signal than a passive view or click through. Courses saved to dashboard Courses saved to dashboard Qualitative Feedback Captures nuance star ratings cannot, such as which rule explanations students found most helpful. Free text comments written to Firebase Free text comments written to Firebase IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · 03 · EVIDENCE.

[Audio] Why The Engine Is Designed This Way Rule weights reflect the relative influence on recommendation relevance. A Scoring rule weight distribution Career intent drives relevance Role category match 35 pts Role category match (35 pts) and degree affinity (25 pts) carry the highest weights because the system is primarily designed to guide students toward relevant career pathways. Degree affinity 25 pts Skill gap reward 20 pts B Readiness matters Level appropriateness 15 pts Skill gap reward (20 pts) and level appropriateness (15 pts) help balance stretch and feasibility, ensuring recommendations are useful but still achievable. Interest keywords 10 pts C Prerequisite check 5 pts Fine tuning factors refine the result Interest keywords (10 pts) and prerequisite check (5 pts) act as secondary signals to improve personalisation without overpowering the core logic. Maximum score contribution (pts) Higher weights indicate greater influence on recommendation relevance..

[Audio] Future. 04. 04. Future.

[Audio] How I-B-M Can Take This Forward Phase 1 Phase 2 Phase 3 0 – 3 months 3 – 6 months 6 – 12 months Full Catalogue Integration Data Driven Weight Optimisation Adaptive Recommendation Model Add collaborative filtering as a second layer signal alongside rule based scoring Connect to I-B-M SkillsBuild A-P-I or maintain a full course database Use collected feedback to recalibrate rule weights empirically Extensible schema — only new data entries required, no logic changes needed A/B test weighting schemes to maximise relevance across student cohorts Track learning progress and update recommendations as student skills develop IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · 04 · future.

[Audio] Business Case. 05. 05. Business Case.

[Audio] The Case For Continuing A low cost, high impact investment: the core system is built and deployed — what remains is scaling the data and refining the logic. Benefits Costs Developer time for full catalogue integration · Firebase hosting (minimal at prototype scale) · Ongoing maintenance for weight recalibration Increased course completion rates Stronger student engagement with I-B-M SkillsBuild Demonstrable employability outcomes for institutional partnerships Return On Investment Competitive positioning in the digital learning market If completion rates rise by X%, Y more learners earn I-B-M certifications — generating direct brand and partnership value with universities and enterprise clients. Feedback loop enables continual engine improvement IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · 05 · business C-A-S-E.

[Audio] Testing Implementation & User Testing Setup Live deployment using React & Firebase, tested with university students. Prototype Deployment User Testing Setup 15 participants from University of Bristol representing diverse academic backgrounds Tasks: profile creation, recommendation generation, pathway exploration, and feedback submission Data collection: star ratings (quantitative) and open ended responses (qualitative) Live web application built with React and deployed via Firebase Hosting Real time interaction with persistent user profiles, saved courses, and feedback Four tab interface: Profile, Recommendations, Dashboard, and Feedback Testing Rationale University students represent the primary target users of I-B-M SkillsBuild, ensuring evaluation reflects realistic user behaviour and provides meaningful insights into recommendation effectiveness and system usability IBM SkillsBuild Learning Pathway Advisor · IBM 3 – Portal · EFIMM0144 · 05 · testing.

[Audio] I-B-M SkillsBuild Learning Pathway Advisor Thank You Questions welcome Live Prototype project ibm a7a63.web.app.