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AI & Organizational Learning - a different approach

Consider this post an invitation to engage for every AI expert seeking to transform the way teams and organizations learn. We consider ourselves AI enthusiasts, but not experts - and we are in need of advice and support from those higher up the ladder.

These days, organizational learning is a pretty dynamic space. Everyone's abuzz with AI - and for good reason. Every day, it's linking content and context in fantastic new ways. The content has always been there.  It's the context piece that makes AI so exciting - and also its biggest challenge. How can we get AI to become ever more intelligent about "our" context? How can AI help generate solutions and feedback that are contextualized to what "we" need?  

To transform learning with AI, most people are seeking to answer the following question: How can we leverage AI to capture all the relevant data in our learning ecosystem?  

We're asking a different question.

How can we reimagine the learning ecosystem to better leverage AI?

AI feeds off contextual data. If we want better, more relevant, more nuanced solutions from AI, then AI needs our help understanding our unique context.  But how do we feed AI our context when so many of our learning systems are focused on yesterday's goals of 'completing courses' or 'identifying correct answers'? Systems set up around finite goals (right / wrong answers) will struggle to fully leverage the power of AI. 

What we need are learning ecosystems set up to gather new types of data - data that is both qualitative and quantitative. The goal cannot simply be focused on helping learners find 'right' answers, but on helping measure the quality of ideas, solutions, and feedback that is shared. The ecosystem becomes a data-rich environment, continually populated with more examples from "our" context.

In short, how can AI be used to help us better learn from all that is "out there" AND those within my own organization?

This December, we're excited to introduce two new few features that will open doors for those wanting to be at the forefront of AI and organizational learning. (Hint: the first feature is that ability for this new model to integrate with almost any LMS - yes, likely the one you're already using.)  

But first, let explore this transformative three-step process that outlines the future evolution of learning.

Step 1: Igniting Creativity through Active Learning

Problem: In traditional learning models, engagement often falls flat as participants passively consume information and demonstrate “success” by answering quiz questions correctly.

Solution: Imagine an online course where each learner actively applies knowledge to solve real-world problems. This dynamic approach not only sparks creativity but transforms the learning environment into an active and collaborative space with others your team trying to do the same. The aim aim is to infuse innovation into learning. 

Unlike traditional approaches that emphasize passive absorption of information, this feature prompts learners to actively engage with content. The essence of learning is captured when individuals actively apply their knowledge and skills to solve specific problems.

By encouraging participants to share their unique solutions within any LMS system, we foster a culture of creative thinking. This active participation not only elevates the learning experience but also lays the groundwork for a collaborative and dynamic learning environment. 

Research on the power of active learning


"Experiential Learning and Its Critics: Preserving the Role of Experience in Management Learning and Education" by Reynolds, M., & Vince, R. (2004)

"Using Action Learning for Change and Development in a Global Organization" by Pedler, M., & Abbott, C. (2013)


 "A Meta-Analysis of the Effects of Active Learning on Student Achievement, Attitude, and Retention" by Freeman et al. (2014)

"The Case for Learner-Centered Teaching: Five Changes to Practice" by Maryellen Weimer (2013)

Step 2: Fostering Diverse Ideas for Targeted Problem Solving

Problem: Organizations struggle to address specific challenges with one-size-fits-all solutions where training/learning simply shares information and fails to bridge the gap of effective implementation (changed behavior). 

Solution: By encouraging learners to take action and share unique solutions within the LMS, a diverse array of ideas is generated. This step ensures that each problem is met with targeted and innovative approaches tailored to the organization's needs.

It also ensures that each learner is given a voice into actively sharing how they would best solve the problem. It removes the gap between 'learning' and 'implementation'. 

As each learner contributes their creative solutions, the LMS transforms into a hub of diverse ideas, each tailored to address the organization's specific challenge(s). This diversity of perspectives enriches the learning journey, providing learners with exposure to different problem-solving approaches.

The LMS becomes more than a repository; it becomes a platform for collaborative learning. Participants engage with and learn from each other, fostering a sense of community and shared knowledge. This step ensures that the learning experience extends beyond theory, empowering learners to share practical insights with their peers applicable to real-world scenarios.

Research on the power of team-based learning

3 reasons why you should switch to team-based learning by Mark Eggers, 2023

Importance of Social Networks for Knowledge Sharing and the Impact of Collaboration on Network Innovation in Online Communities by 

Stefan Behfar, 2020

Step 3: Unlocking the Power of Peer Feedback

Problem: Traditional assessments measure comprehension. This provides learners with limited insight. The data fails to measure the quality of their solutions within a particular context. (And, it makes the learning process boring and lacking relevance!)

Solution: Leveraging peer feedback based on rubric scores introduces a data-driven approach. Learners receive both qualitative and quantitative insights on key skills and goals, fostering a comprehensive understanding of their strengths and areas for improvement.

This is the real game-changer towards building a learning community where users are naturally learning from each other. This data-driven approach not only enriches the learning experience but also provides a robust mechanism for tracking learners’ progress in sharing solutions and feedback.

By analyzing peer feedback and rubric scores throughout a project, organizations can now create a comprehensive, data-rich narrative around key organizational goals over time. This narrative unveils how well each learner (and the organization as a whole) is meeting key goals - offering insights into strengths, areas for improvement, and overall contribution to the learning initiative.

Users learn and collaborative by 1) sharing solutions, 2) receiving aggregated peer feedback (qualitative and quantitative) based on best practices, and 3) viewing individual feedback from their peers

 A data-rich story: (left) comparing user's scores on a single rubric... (right) comparing user's scores on key skills tracked by multiple rubric scores

Read more research on Peer Feedback

Peer Feedback in Online Learning Communities, by C. -H. Liao, H. -J. Chung and J. -Y. Wu, 2023

Effects of different online peer-feedback approaches on students' performance skills, motivation and self-efficacy in a dance course by L.H Hsia, I. Huang, G.J. Hwang, 2015

A Different Way for Organizations to Learn

This is a paradigm shift. The best learning isn’t a precursor to (hopeful) implementation; the best learning happens as we strive to take action. 

Instead of relying solely on traditional , comprehension-based assessments, organizations can now gauge the effectiveness of their long-term learning initiatives with data aligned to impact - thus, offering a much clearer ROI metric.  

By tracking the degree to which each organizational goal is met, the entire learning ecosystem becomes more transparent, with shared accountability for everyone.  Learning is more active, collaborative, and solution-focused.  

Two big steps forward

We are passionate about making this a reality for everyone, and we are excited to share two recent updates in December to the Huddle Up Learning platform that help make this happen.

  1. Organizations can customize their own goals (eg. “Creativity”, “Critical Thinking”, “Sustainability” etc.) and track these goals for each learner. Here’s a look at the unique types of data that organizations can now customize to link the implementation of learning and organizational goals. 
  2. We can now link this solution-focused, collaborative learning model to almost any LMS system out there (thanks to LTI integration). That means that your users won’t have to leave your current LMS (eg. “Canvas”) to experience this sort of interactive,model. Here’s a short video to show you how that works.

We’re reshaping how  organizations  learn, collaborate and improve:

  • From passive comprehension... to a focus on creating and sharing solutions.
  • From numerous meetings where we try to collaborate about learning... to a shared space where we can share our ideas and feedback asynchronously, archived for everyone.
  • From isolating experiences... to collaborative communities.

We’re on the lookout to connect with individuals and organizations who share our passion. Specifically, we'd love to hear from and build relationships from those on the forefront of linking AI and organizational learning. We learn better when we learn together.  

Reach out and learn more below.


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