From Tabula Rasa to RPL/PLAR: Valuing What’s Already There

There’s a theory, "tabula rasa", which says that we are born as blank slates. That knowledge is only gained through experience and that we start from nothing and build up from there. But is that really true?

As newborns, we instinctively root, grasp, and respond to voices. We are born with reflexes, rhythms and preferences. There is knowledge already encoded in our bodies that is passed through our DNA. New research also suggests that the knowledge of our culture, survival, pain and trauma is perhaps also stored in our cells.

And yet… in most of our learning and talent development systems, we still treat people as if they are starting from scratch. Before we acknowledge their expertise, we create plans to train, reskill, upskill, and make people 'fit' for the job.

- What if we stopped assuming blank slates and asking people to start from zero and, instead, recognized the wealth of learning and skills they bring to the table, from day one? What if Bootcamp Day 1 is all about recognition of learning and validation of skills?

- What kind of conversations can we have in our teams, organizations and industry sectors, that can allow us to acknowledge, recognize and validate this prior learning and skills and meet people where they are?

- How can we use a strength-based lens and recognition-first mindset? What can help us reframe our thinking and our work?

The answers? You will have to wait just a bit :) I had a great conversation on all things recognition of prior learning where I got a chance to chat with a wonderful colleague for their upcoming podcast. Coming soon to your feed!

In the meantime, I am heading to the Canadian Association for Prior Learning Assessment Conference in Antigonish, Nova Scotia and looking forward to both presenting and participating in all things RPL/PLAR!


May 26, 2025 - Preconference
1:15 – 4:45 p.m.
Andy Brown, CAPLA Chair; Dan McFaull and Taruna Goel, North Pacific Metrics Inc.
"Recognizing RPL Practitioners: Findings from the CAPLA/ONCAT research project"


Day 2 - May 28, 2025
10:05 - 11:05 a.m.
Dan McFaull and Taruna Goel, North Pacific Metrics Inc.
"RPL Tools for Upskilling in High Tech"

https://capla.ca/

https://caplacon2025.mailchimpsites.com/schedule

L&D in the Age of AI: Value Creators, Not Just Validators

Inspired by and in response to Dr Philippa Hardman's insightful vision of ADDIE 4.0, I explore how AI is reshaping Instructional Design and why L&D professionals must go beyond validation to create cultural, ethical, and emotionally resonant learning experiences.

I propose an expanded version, ADDIE 4.1 :), where L&D acts as social architects designing not just learning, but connection, equity, and community. The way I see it, the future of L&D lies in intentionally shaping behaviour, meaning, and workplace performance alongside AI!

Image by Iris,Helen,silvy from Pixabay

Last week, I read an insightful post on how AI is impacting the role of instructional designers and the future of Instructional Design. In her latest post, Dr Philippa Hardman argues that Instructional Design isn't dying, it is infact evolving into more "specialised roles that reflect both the capabilities of generative AI and the strategic imperatives facing modern organisations." You can read her post here: https://drphilippahardman.substack.com/p/instructional-design-isnt-dying-its

I really like her take on the complimentary roles of AI & ID especially the breakdown of which tasks in the Instructional Design process are best handled by AI versus those that require human insight. It offers a good roadmap for what lies ahead. In her post, she also proposes an ADDIE 4.0 version of the classic ADDIE model focusing on "Where Humans & Machines Collide".

I appreciate the proposed ADDIE 4.0 model but I also recognize how it assumes a highly mature AI system and organization-wide, bias-free, accurate data to generate valuable learning content on an individual basis.

But this kind of data organization and personalization is very resource-intensive and perhaps somewhat unrealistic for many small and medium-sized organizations.

I am also thinking about the accuracy and fairness of data that is guiding these automated pathways. Isn't there a critical role of L&D to prevent AI from using data sets that might inadvertently reinforce existing biases or limit exposure to diverse perspectives?

Perhaps what is missing in this ADDIE 4.0 model is how L&D work goes beyond the validation function into the more value creation function by bringing the cultural, ethical, and emotional context into the work we do.

To build on Dr Philippa Hardman's vision, I would advocate for ADDIE 4.1, which expands the human L&D tasks column to bring the the lens of learning contexts around ethics, accessibility and building a community.

In my version of ADDIE 4.1, successful L&D roles and functions will need to:

1) actively identify and reduce the bias in datasets collected by AI,

2) consciously add contextual, cultural, and emotional relevance to learning in order to build a community, and

3) intentionally move beyond being the providers and validators of learning experiences to become the architects of equitable and meaningful connection and workplace performance.

In my version of ADDIE 4.1, I see L&D as social architects. Just like architects design spaces not buildings, L&D social architects will design human connection and shared meaning through learning and performance.

Because the real impact of our work lies not only in what people learn but in how they behave and how they connect, with themselves, with each other and with the work they do.

How do you see the role of L&D evolving alongside AI? I am curious to hear your thoughts and perspectives!

#InstructionalDesign #ArtificialIntelligence #AI #LearningandDevelopment #HumanCenteredDesign #FutureOfWork #LDCulture #ADDIEModel #LeveragingAI #ADDIE