Alma Nemachtilhuaztli Mopatlanqui ītēchcopa Mina Maazi

Tlanāhuatīlli Alma Nemachtilhuaztli Mopatlanqui ītēchcopa Mina Maazi cē cencā mahuizzō tēmacēhualōni īpan huēyi 2025 Mahuizolli A' Design Award Bronse īpan Temachtiloliztli, Temachtilizpalehuilli ihuan Nemachtiloliztlahtolpamitl Tlachihchihualiztli Nēhuilīztli Tlamantli.

BronseTemachtiloliztli· 2025

Alma Nemachtilhuaztli Mopatlanqui

īpal Mina Maazi

Tlanāhuatīlli: Birmingham City University

Mahuizolli A' Design Award Bronse Tēmacēhualōni īpan Temachtiloliztli Tlamantli

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Tlaneltīlīlli Tēmacēhualōni

Xictlaneltilia Tēmacēhualli ītēchcopa #169409

Xiquitta Tlahcuilōlcalli Xiquitta A' Design Award ītechcopa Āmatl Tēmachiyōtīliztli Tlamachiōtl

Tlapalli

Tlanēxtilistli

Ītechcopa Alma Nemachtilhuaztli Mopatlanqui

Alma ce nemachtilpalehuiani pampa tlamatini tlapohualhuilli, techpalehuia ipan caltequitl nemachtilli huan tlapohualneliliztli. Quimotemaca moyoliconelilia nemachtilli inic quinextia ce ce tlacatl itlamachilis huan quiyectlalia nemachtiltonalpohualli. Amo zan quemeh in huehueh tlachihualiztli, Alma quintlalia icniuhnemachtilli, tlamatini tlapohualhuilli tetlachializtli huan mopatlanqui tonalpohualli, inic cualli huan chicahuac mocaqui yancuic tequihuah. Ipampa quipitzahua nemachtilli tlaxtlahuilli huan quichihua yolpaquiliztli, Alma palehuia altepecalmecameh inic yecyotl hueyiah intlamatiliztli auh yectlaliah tequihua chicahualiztli.

Tēixīmachōtiliztli

Ītechcopa Mahuizolli A' Design Award Bronse

Alma Nemachtilhuaztli Mopatlanqui ca in quicuic in Mahuizolli A' Design Award Bronse, hueyi tlamahuizoliztli tlen momaca in cualli tlachihualli in motenehua ipampa yancuic tlamantli, tlamatiliztli ihuan ixtlamatiliztli. In quicuicah Bronse ca tlachihualli in quipia toltecayotl ihuan quinextia in cenca miac nemiliztli ihuan tlamatiliztli intlachihuanime. Ca quinequi in Alma Nemachtilhuaztli Mopatlanqui ca tlazohtli tlamantli, mahuiztic ihuan cualli. Ni dizayno in quicuic Bronse quipia cualli toltecayotl ihuan quitta in tlen tepiton. Alma Nemachtilhuaztli Mopatlanqui quipaquiltia in tlacah ihuan quitlamahuiztiltia in intlanequiliz.

Tlanēxtilistli Ītēixpan

Āmatl Tlanextīliztli

Tlapōhualli, tēquitqueh īwan tēchmachilīztli ōquinmaca in tlanēxtīlīlli.

Cē Zan Ītēchcopa: 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.
Huēyiliztli īhuān Tlacualtepēhualli: 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.
Tōcāitl: Adaptive Learning, AI Assistant, Digital Literacy, Peer-to-Peer Learning, Mentorship Platform, E-Learning, Smart Scheduling, User-Centered Design, Personalized Education, Cloud-Based Platform
Tlachīhualiztli Māchiyōtl: 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.
Tlanāhuatīlli Nētēcahuilīztli: 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.
Tlatēmōliztli: 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.
Tēyōllālīliztli: 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.
Tēquitl Cāhuitl: 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.
Tēquitl Ōhuitl: 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.
Patentēmeh: Copyrights belong to Mina Maazi, 2025.
Calpolli Tlācah: Mina Maazi
Īxiptla Tlanēxtīlli: 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.