『Designing for Self-Determined Performance』のカバーアート

Designing for Self-Determined Performance

Designing for Self-Determined Performance

著者: Dr Timothy Stafford
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概要

Designing for Self-Determined Performance explores instructional design, Human Performance Technology, and executive learning leadership.


Hosted by Dr. Timothy Stafford, the podcast examines how organizations move beyond traditional training to build capability-driven systems that foster autonomy, measurable performance, and strategic alignment.


For CLOs, instructional designers, performance consultants, and learning leaders who believe learning should produce real-world impact.

© 2026 Designing for Self-Determined Performance
マネジメント マネジメント・リーダーシップ 個人的成功 経済学 自己啓発
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  • Autonomy Isn’t Optional: Designing Learning That Performs
    2026/03/11

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    In November, 2025, I had the privilege of joining PineApple Academy for a conversation about the future of learning — and why traditional instructional models are no longer sufficient for enterprise performance.

    We explored heutagogy, or self-determined learning, not as a theory of engagement, but as a design discipline for building real autonomy — the kind of decision agency required in complex environments.

    We discussed:

    • Why learning only “sticks” when it produces adaptive capability
    • How autonomy emerges through discovery, resonance, and structured reflection
    • Why AI must be treated as a performance partner — not a shortcut or a threat
    • And how ethical AI integration becomes a leadership responsibility, not a technical one

    At the core of this conversation was a simple but urgent premise:

    Learning has value only when it converges with performance.

    As complexity increases — whether through digital transformation, AI integration, or shifting enterprise demands — organizations must move beyond content delivery and toward designing environments where capability, autonomy, and alignment intersect.

    If you are a leader navigating AI adoption, capability development, or the future of learning strategy, this conversation offers a structured lens for thinking about autonomy not as freedom — but as mature, aligned decision-making within enterprise systems.

    Designing for Impact Intro

    Designing for Impact Outro

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    32 分
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