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AI learning doesn’t remove effort — it makes learning accessible
AI is often described as something that makes learning faster or easier.But in reality, learning has never been effortless — and it still isn’t.
In this episode of Simply Briefed, we explore what actually changes when learning can be personalised. Not by lowering expectations or removing struggle, but by improving structure so effort is placed where it matters most.
Using math as a clear and honest example, founder of House of Math Vibeke Fængsrud explains why learning breaks down when structure doesn’t match the learner — and how AI now makes it possible to adapt learning paths to the individual. The result isn’t less work, but more accessible learning that builds confidence instead of frustration.
Together, host Kristine Lium and Vibeke discuss:
why struggle is still a necessary part of learning
how personalised structure changes motivation and outcomes
what math can teach us about learning in general
and why lifelong learning is becoming a personal responsibility, not an optional extra
This conversation is for anyone curious about learning, work, and how AI can support human capability — without replacing it.
Name: Vibeke G. Fængsrud
Title: Founder & CEO, House of Math
Background:
Vibeke G. Fængsrud is the founder of House of Math and a former lecturer in math and physics. After failing math in high school and repeating a year, she went on to earn a master’s degree in Mathematical Finance. Since 2004, she has worked closely with learners, developing teaching methods that challenge one-size-fits-all education by focusing on structure, effort, and personalised learning.
Quote:
“Learning doesn’t get easier — it gets clearer when structure fits the learner.”
Contact: Linkedin
#learning&development #artificial intelligence #education
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By PimmAI is often described as something that makes learning faster or easier.But in reality, learning has never been effortless — and it still isn’t.
In this episode of Simply Briefed, we explore what actually changes when learning can be personalised. Not by lowering expectations or removing struggle, but by improving structure so effort is placed where it matters most.
Using math as a clear and honest example, founder of House of Math Vibeke Fængsrud explains why learning breaks down when structure doesn’t match the learner — and how AI now makes it possible to adapt learning paths to the individual. The result isn’t less work, but more accessible learning that builds confidence instead of frustration.
Together, host Kristine Lium and Vibeke discuss:
why struggle is still a necessary part of learning
how personalised structure changes motivation and outcomes
what math can teach us about learning in general
and why lifelong learning is becoming a personal responsibility, not an optional extra
This conversation is for anyone curious about learning, work, and how AI can support human capability — without replacing it.
Name: Vibeke G. Fængsrud
Title: Founder & CEO, House of Math
Background:
Vibeke G. Fængsrud is the founder of House of Math and a former lecturer in math and physics. After failing math in high school and repeating a year, she went on to earn a master’s degree in Mathematical Finance. Since 2004, she has worked closely with learners, developing teaching methods that challenge one-size-fits-all education by focusing on structure, effort, and personalised learning.
Quote:
“Learning doesn’t get easier — it gets clearer when structure fits the learner.”
Contact: Linkedin
#learning&development #artificial intelligence #education