Alma Lub Platform Cob Qhia Hloov Kho Tau Raws Li los ntawm Mina Maazi

Qhov qauv tsim Alma Lub Platform Cob Qhia Hloov Kho Tau Raws Li los ntawm Mina Maazi yog tus yeej muaj nqis heev ntawm qhov khoom plig 2025 A' Design Award Tooj hauv Pawg Sib Tw Tsim Kev Kawm, Khoom Pab Qhia thiab Kev Cob Qhia.

ToojKev Kawm· 2025

Alma Lub Platform Cob Qhia Hloov Kho Tau Raws Li

los ntawm Mina Maazi

Tus Neeg Siv: Birmingham City University

Tus Yeej A' Design Award Tooj hauv Pawg Kev Kawm

24,831

Tus Yeej Khoom Plig Tau Txheeb Xyuas

Txheeb Xyuas Qhov Xwm Txheej Khoom Plig rau #169409

Mus Saib Lub Vev Xaib Saib ntawm A' Design Award Tsab Xov Xwm Daim Phiaj Khoom Plig

Xim

Qhov Tsim

Txog Alma Lub Platform Cob Qhia Hloov Kho Tau Raws Li

Alma yog ib tug pab tswj kev kawm uas siv AI los txhim kho kev cob qhia hauv tuam txhab thiab kev siv digital. Nws ua kom kev kawm haum rau txhua tus neeg los ntawm kev txheeb xyuas txhua tus neeg cov qauv kawm thiab ua kom lub sijhawm cob qhia zoo tshaj plaws. Tsis zoo li cov txheej txheem qub, Alma sib txuas kev qhia tib tiam, kev paub los ntawm AI, thiab kev teem sijhawm hloov tau, uas ua kom muaj kev pib ua haujlwm uas du thiab muaj txiaj ntsig. Los ntawm kev txo nqi cob qhia thiab txhawb kev koom tes, Alma pab cov koom haum ua kom kev tsim kev txawj nrawm dua thaum txhim kho kev npaj ua haujlwm.

Qhov Lees Paub

Txog A' Design Award Tooj

Alma Lub Platform Cob Qhia Hloov Kho Tau Raws Li yog tus yeej ntawm A' Design Award Tooj, ib qho kev lees paub muaj meej mom heev uas muab rau cov qauv tsim tshwj xeeb uas txawv los ntawm kev tsim tshiab, kev txawj tsim thiab kev ntse. Cov neeg yeej Tooj yog cov khoom muaj txuj ci heev thiab tsim tshiab heev uas ua pov thawj txog kev paub ntau, kev xav thiab kev txawj ua ntawm cov kws tsim qauv. Alma Lub Platform Cob Qhia Hloov Kho Tau Raws Li xav tias yuav yog ib qho khoom uas neeg hwm, qhuas thiab hlub, uas tshaj lij heev thiab tsim tshiab. Cov qauv tsim yeej A' Design Award Tooj no siv cov kev coj ua zoo tshaj plaws ntawm kev kos duab, kev tshawb fawb, kev tsim qauv thiab thev naus laus zis thiab zoo heev vim nws saib xyuas cov ntsiab lus. Alma Lub Platform Cob Qhia Hloov Kho Tau Raws Li ua tau raws li cov kev xav tau zoo kawg, kov cov kev xav, ntxias cov kev xav thiab txhawb kev xav paub.

Tom Qab Qhov Tsim

Pob Xov Xwm

Cov credit, cov neeg pab thiab cov ntsiab lus kev txawj ntse muab los ntawm tus tsim.

Yam Tshwj Xeeb: Alma is an AI-powered learning assistant that personalizes corporate training by identifying learning styles and optimizing scheduling. Unlike traditional platforms, it integrates peer-to-peer learning, mentorship, and smart scheduling to reduce onboarding costs. AI-driven insights help users access relevant content, connect with peers, and enhance digital adoption while ensuring a seamless, human-centered learning experience.
Qhov Loj & Ntim: Alma is a cloud-based AI-driven learning platform designed for adaptive training. It integrates with Google Calendar and Outlook APIs for smart scheduling. The platform was prototyped in Figma and refined through iterative user testing. It supports responsive design, ensuring accessibility across desktop and mobile devices. End-to-end encryption safeguards user data, while scalable architecture allows seamless company-wide deployment.
Cov Ntsiab Lus: Adaptive Learning, AI Assistant, Digital Literacy, Peer-to-Peer Learning, Mentorship Platform, E-Learning, Smart Scheduling, User-Centered Design, Personalized Education, Cloud-Based Platform
Thev Naus Laus Zis Tsim Khoom: Alma was developed using AI-driven learning models and machine learning algorithms to personalize training experiences. It integrates with digital calendars for adaptive scheduling and suggests peer interactions based on shared learning topics. The Design Thinking and User-Centered Design methodologies guided the UX process. Figma was used for prototyping, while continuous user testing and feedback loops refined the system for optimal usability.
Kev Sib Tw Tsim Qauv: The biggest challenge was integrating AI-driven adaptive learning while maintaining a human-centered approach. Developing accurate learning style detection algorithms required extensive research. We conducted both qualitative and quantitative research, including user interviews, surveys, and usability testing, to ensure an effective and engaging user experience. Additionally, overcoming resistance to digital adoption was critical. Inspired by Google and Amazon, we leveraged Peer-to-Peer Learning and Adaptive Scheduling to create a validated, user-centric platform that fosters digital readiness.
Kev Tshawb Fawb: This research employed User-Centered Design and Design Thinking methodologies to enhance digital literacy and onboarding. Surveys and user interviews were conducted with employees struggling with traditional training. Insights from Google and Amazon case studies highlighted Peer-to-Peer Learning and Adaptive Scheduling as key solutions. Findings shaped Alma, making onboarding more efficient, cost-effective, and engaging in corporate environments.
Kev Txhawb Siab: Alma was inspired by the need to improve digital adoption and corporate learning. Research showed that traditional training lacks engagement and human interaction, slowing digital readiness. By integrating peer-to-peer learning, mentorship, and adaptive AI-driven scheduling, Alma creates a seamless and practical learning experience, making onboarding more effective and reducing resistance to change.
Lub Sij Hawm Ua Hauj Lwm: The project began in October 2023 in Birmingham, UK, as part of the MA Design Management program at Birmingham City University. It was completed in November 2023 and received the Best Idea Award at the People-Led Digitalisation event, organized in collaboration with the University of Bath. The project was developed through extensive research and user-centered design methodologies to enhance corporate learning experiences.
Txheej Txheem Ua Hauj Lwm: Alma streamlines learning by analyzing individual learning styles and suggesting tailored courses, mentors, and training paths. It seamlessly syncs with calendars, offering AI-powered scheduling for optimal learning sessions. Users can book mentors, track progress, and receive automated reminders. Alma fosters peer-to-peer learning, recommending colleagues with similar interests, ensuring an engaging, efficient, and interactive learning experience.
Cov Patent: Copyrights belong to Mina Maazi, 2025.
Cov Tswv Cuab Pab: Mina Maazi
Kev Qhuas Duab: Image #1: Designer Mina Maazi, ALMA UI Design, 2024.
Image #2: Designer Mina Maazi, Learning Style Detection Flow, 2024.
Image #3: Designer Mina Maazi, Adaptive Scheduling Interaction, 2024.
Video Credits: Designer Mina Maazi, ALMA User Flow Prototype, 2024.
Image #4: Illustrator John Doe, Icons from Freepik, 2024.