본문으로 바로가기

세부 정보를 입력하여 웨비나에 참여하세요.

계속 진행하시면 당사의 이용약관, 개인정보처리방침 및 귀하의 데이터가 미국에 저장되는 것에 동의하시는 것입니다.

스피커

비즈니스용

2명 이상을 교육하시나요?

팀원들이 중앙 집중식 보고, 과제, 프로젝트 등을 포함한 DataCamp 라이브러리 전체에 액세스할 수 있도록 하세요.
DataCamp for Business를 사용해 보세요.맞춤형 솔루션을 원하시면 데모를 예약하세요.

Using Science to Optimize Your Learning Programs

October 2025
Webinar Preview

Session Resources + Slides

Summary

Using science to optimize learning programs is essential for enhancing training effectiveness and ensuring skill application in the workplace. Stella Collins, a learning impact advocate, shared insights on evidence-based learning strategies, emphasizing the importance of moving beyond simple content delivery to achieve real skill transfer. The session highlighted the Gear model, a framework for structuring training to maximize impact, and explored the role of motivation, experimentation, and application in learning. Collins also addressed common pitfalls in training and the potential of AI to enhance learning experiences.

Key Takeaways:

  • Effective training requires a focus on skill transfer, not just content delivery.
  • The Gear model provides a structured approach to optimize learning programs.
  • Motivation and real-world application are vital for successful learning.
  • AI can personalize and enhance learning experiences, but careful evaluation is essential.
  • Understanding and addressing learning myths can improve training outcomes.

Insights

The Gear Model for Learning

The Gear model is a comprehensive framework designed to enhance the effectiveness of learning programs. It emphasizes the importance of setting clear goals, maintaining motivation, and providing guidance and experimentation opportunities. The model outlines a process where learners are guided through structured c ...
더 읽어보기

ontent, allowed to experiment in a safe environment, and then encouraged to apply their skills in real-world scenarios. Retention is achieved through repetition and practice, ensuring that skills become second nature. As Stella noted, "We rarely think about how we're going to help people apply this in the workplace and retain it as a long-term skill."

Motivation and Real-World Application

Motivation is a vital component of successful learning. Stella highlighted the importance of making training relevant and engaging for learners. She suggested that training should not only focus on content delivery but also on how learners can apply new skills in their work environment. This involves setting clear transfer objectives and ensuring that learners understand the practical benefits of their training. "If the training solves a problem for them, they are more likely to actually do it," Stella explained. Engaging managers and peers in the learning process can also reinforce motivation and support skill application.

The Role of AI in Learning

AI offers significant opportunities to enhance learning experiences by providing personalized content and immediate access to information. However, Stella cautioned about the potential downsides, such as over-reliance on AI for information retrieval, which might hinder the development of critical thinking skills. "If you don't have that knowledge, how will you acquire it for yourself?" she questioned. AI can be a powerful tool for amplifying learning impact, but it must be used thoughtfully to ensure that learners develop a deep understanding of the material.

Addressing Learning Myths

Stella addressed several common myths in the learning field, such as the idea of fixed learning styles and the misconception that we only use 10% of our brains. She emphasized the importance of evidence-based practices and debunking myths to improve training outcomes. "There is no such thing as a boring topic, only boring training," she asserted, highlighting the need for engaging and relevant training methods. By focusing on scientifically validated approaches, trainers can create more effective and impactful learning experiences.


관련된

webinar

How You & Your Team Can Learn Data Skills More Effectively

In this session Jo Boaler, the Nomellini & Olivier Professor of Mathematics Education at Stanford University, explains what we know about how to learn quantitative subjects well.

webinar

The Executive Guide to Data & AI Literacy

Experts share how to design and implement a literacy strategy that works. Hear practical lessons on training at scale, increasing data and AI maturity, and identifying the highest-impact use cases.

webinar

Train Your Workforce to Thrive in a Data-Driven Age

Develop a scalable data training program and measure its effectiveness.

webinar

How Data Can Supercharge L&D

Lori Niles-Hofmann, Senior EdTech Transformation Strategist at 8Levers, shares how L&D leaders can leverage data to maximize the impact of their programs.

webinar

Scaling Data Science At Your Organization - Part 3

Learn how to organize your data science team to scale effectively.

webinar

Creating a Learning Community for Better Training Results

Helen Marshall, Chief Learning Officer at Thrive, shares practical strategies for creating and nurturing a learning community that enhances training outcomes.