Mina MaaziによるAlma 適応型研修プラットフォームは、教育・教材・研修コンテンツデザインコンペティションカテゴリーにおける非常に権威ある2025 A' Design Award 銅賞の優れた受賞作品です。

銅教育· 2025

Alma 適応型研修プラットフォーム

デザイナー： Mina Maazi

クライアント: Birmingham City University

教育カテゴリーのA' Design Award 銅賞受賞者

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デザイン

Alma 適応型研修プラットフォームについて

アルマは、企業研修とデジタル導入を強化するAI搭載の学習管理アシスタントです。個々の学習スタイルを特定し、研修スケジュールを最適化することで、学習をパーソナライズします。従来の手法とは異なり、アルマはピアツーピアメンタリング、AI主導のインサイト、適応型スケジューリングを統合し、シームレスで効率的なオンボーディング体験を実現します。研修コストを削減し、エンゲージメントを促進することで、組織のスキル開発を加速させ、従業員の即戦力化を向上させます。

受賞

A' Design Award 銅賞について

Alma 適応型研修プラットフォームは、創造性、独創性、鋭い洞察力で際立つ傑出したデザインに授与される、高い権威をもつ評価である A' Design Award 銅賞の受賞作品です。銅賞の受賞作品は、十分に巧みで印象的なほど創造的な工芸品であり、デザイナーの豊富な経験、想像力、機知を裏づけています。Alma 適応型研修プラットフォームは、高く評価され、称賛され、愛される品であり、顕著にプロフェッショナルで革新的であることが期待されます。この A' Design Award 銅賞を受賞したデザインは、芸術・科学・デザイン・技術のベストプラクティスを取り入れており、細部への配慮に優れています。Alma 適応型研修プラットフォームは、ニーズを見事に満たし、欲求に触れ、感情を魅了し、好奇心を引きつけます。

デザインの裏側

プレスキット

デザイナーが提供するクレジット、チームメンバー、技術的な詳細。

独自の特性: 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.
寸法とパッケージ: 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.
タグ: Adaptive Learning, AI Assistant, Digital Literacy, Peer-to-Peer Learning, Mentorship Platform, E-Learning, Smart Scheduling, User-Centered Design, Personalized Education, Cloud-Based Platform
製造技術: 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.
デザインの課題: 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.
リサーチ: 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.
インスピレーション: 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.
プロジェクト期間: 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.
オペレーションフロー: 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.
特許: Copyrights belong to Mina Maazi, 2025.
チームメンバー: Mina Maazi
画像クレジット: 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.