设计师 Mina Maazi 的作品 Alma 自适应培训平台荣获了极具声望的 2025 A' Design Award 铜奖，竞赛类别为教育、教学辅助与培训内容设计。

铜教育· 2025

Alma 自适应培训平台

设计师： Mina Maazi

客户: Birmingham City University

教育类别A' Design Award 铜奖获奖者

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关于 Alma 自适应培训平台

Alma是一款AI驱动的学习管理助手，提升企业培训与数字化应用效果。它通过识别个体学习风格并优化培训安排实现个性化学习。不同于传统方法，Alma融合了同伴辅导、AI智能洞察与自适应排程，确保流畅高效的入职培训体验。通过降低培训成本并增强参与度，Alma帮助企业加速技能发展，提升员工就绪度。

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关于A' Design Award 铜奖

Alma 自适应培训平台是 A' Design Award 铜奖得主，这是授予以创造力、独创性和敏锐见长的杰出设计的极具声望的认可。铜奖得主是技艺娴熟、创意惊人的作品，印证了其设计师丰富的经验、想象力与机智。预计Alma 自适应培训平台将成为一件备受推崇、令人钦佩且被珍爱的物品，兼具显著的专业性与创新性。这件赢得 A' Design Award 铜奖的设计融入艺术、科学、设计和技术领域的最佳实践，并因注重细节而出类拔萃。Alma 自适应培训平台出色地满足需求，触动渴望，迷住情感，并吸引好奇心。

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由设计师提供的致谢、团队成员及技术详情。

独特属性: 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.
尺寸与包装: 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.
标签: Adaptive Learning, AI Assistant, Digital Literacy, Peer-to-Peer Learning, Mentorship Platform, E-Learning, Smart Scheduling, User-Centered Design, Personalized Education, Cloud-Based Platform
生产技术: 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.
设计挑战: 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.
研究: 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.
灵感: 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.
项目周期: 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.
操作流程: 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.
专利: Copyrights belong to Mina Maazi, 2025.
团队成员: Mina Maazi
图片版权: 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.