Remove Exercise Remove Learning Theory Remove Technique
article thumbnail

Why Movement Is the Killer Learning App for Nonprofits

Beth's Blog: How Nonprofits Can Use Social Media

As a trainer and facilitator who works with nonprofit organizations and staffers, you have to be obsessed with learning theory to design and deliver effective instruction, have productive meetings, or embark on your own self-directed learning path. Here’s some examples.

Learning 139
article thumbnail

Six Tips for Evaluating Your Nonprofit Training Session

Beth's Blog: How Nonprofits Can Use Social Media

” While a participant survey is an important piece of your evaluation, it is critical to incorporate a holistic reflection of your workshop. This includes documenting your session, reviewing your decks and exercises, analyzing your instructional design, and figuring out how to improve it. Use Learning Theory.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How To Think Like An Instructional Designer for Your Nonprofit Trainings

Beth's Blog: How Nonprofits Can Use Social Media

Designing and delivering a training to a nonprofit audience is not about extreme content delivery or putting together a PowerPoint and answering questions. If you want to get results, you need to think about instructional design and learning theory. And, there is no shortage of learning theories and research.

article thumbnail

Research directions Open Phil wants to fund in technical AI safety

The AI Alignment Forum

Adversarial machine learning This cluster of research areas uses simulated red-team/blue-team exercises to expose the vulnerabilities of an LLM (or a system that incorporates LLMs). Were interested in techniques like latent adversarial training and circuit breaking that might succeed where standard adversarial training falters.

article thumbnail

AXRP Episode 40 - Jason Gross on Compact Proofs and Interpretability

The AI Alignment Forum

And for that, I think you need something like derandomization techniques, where the simplest example of this is that if you have a collection of random vectors in high dimensions, theyre almost always almost orthogonal. Jason Gross (01:42:14): I think we should leave this as an exercise for the listeners.

Model 52