By connecting practitioners to learn from each other, peer learning facilitates collaborative development.

How does it compare to expert-led coaching and mentoring “fellowships” that are seen as the ‘gold standard’ for professional development in global health?

Scalability in global health matters. (See this article for a comparison of other aspects.)

Simplified mathematical modeling can compare the scalability of expert coaching (“fellowships”) and peer learning

Let N be the total number of learners and M be the number of experts available. Assuming that each expert can coach K learners effectively:

For N>>M×KN>>M×K, it is evident that expert coaching is costly and difficult to scale.

Expert coaching “fellowships” require the availability of experts, which is often optimistic in highly specialized fields.

The number of learners (N) greatly exceeds the product of the number of experts (M) and the capacity per expert (K).

Scalability of one-to-one peer learning

By comparison, peer learning turns the conventional model on its head by transforming each learner into a potential coach who can provide peer feedback.

This has significant advantages in scalability.

Let N be the total number of learners. Assuming a peer-to-peer model, where each learner can learn from any other learner:

In this context, the number of learning interactions scales quadratically with the number of learners. This means that if the number of learners doubles, the total number of learning interactions increases by a factor of four. This quadratic relationship highlights the significant increase in interactions (and potential scalability challenges) as more learners participate in the model.

However, this one-to-one model is difficult to implement: not every learner is going to interact with every other learner in meaningful ways.

A more practical ‘triangular’ peer learning model with no upper limit to scalability

In The Geneva Learning Foundation’s peer learning model, learners give feedback to three peers, and receive feedback from three peers. This is a structured, time-bound process of peer review, guided by an expert-designed rubric.

When each learner gives feedback to 3 different learners and receives feedback from 3 different learners, the model changes significantly from the one-to-one model where every learner could potentially interact with every other learner. In this specific configuration, the total number of interactions can be calculated based on the number of learners N, with each learner being involved in 6 interactions (3 given + 3 received).

The total number of interactions per learner is six. However, since each interaction involves two learners (the giver and the receiver of feedback), we do not need to double-count these interactions for the total count in the system. Hence, the total number of interactions for each learner is directly 6, without further adjustments for double-counting.

Therefore, the total number of learning interactions in the system can be represented as:

Given this setup, the complexity or scalability of the system in terms of learning interactions relative to the number of participants N is linear. This is because the total number of interactions increases directly in proportion to the number of learners. Thus, the Big O notation would be:

This indicates that the total number of learning interactions scales linearly with the number of learners. In this configuration, as the number of learners increases, the total number of interactions increases at a linear rate, which is more scalable and manageable than the quadratic rate seen in the peer-to-peer model where every learner interacts with every other learner. Learn more: There is no scale.

Illustration: The Geneva Learning Foundation © 2024

https://redasadki.me/2024/02/28/how-does-peer-learning-compare-to-expert-led-coaching-fellowships/

A formula for calculating learning efficacy, (E), considering the importance of each criterion and the specific ratings for peer learning, is:

This abstract formula provides a way to quantify learning efficacy, considering various educational criteria and their relative importance (weights) for effective learning.

Weights for each variables are derived from empirical data and expert consensus.

All values are on a scale of 0-4, with a “4” representing the highest level.

Here is a summary table including all values for each criterion, learning efficacy calculated with weights, and Efficacy-Scale Score (ESS) for peer learning, cascade training, and expert coaching.

The Efficacy-Scale Score (ESS) can be calculated by multiplying the efficacy (E) of a learning method by the number of learners (N).

This table provides a detailed comparison of the values for each criterion across the different learning methods, the calculated learning efficacy values considering the specified weights, and the Efficacy-Scale Score (ESS) for each method.

Of course, there are many nuances in individual programmes that could affect the real-world effectiveness of this simple model. The model, grounded in empirical data and simplified to highlight core determinants of learning efficacy, leverages statistical weighting to prioritize key educational factors, acknowledging its abstraction from the multifaceted nature of educational effectiveness and assumptions may not capture all nuances of individual learning scenarios.

Peer learning

The calculated learning efficacy for peer learning, , is 3.20. This value reflects the weighted assessment of peer learning’s strengths and characteristics according to the provided criteria and their importance.

By virtue of scalability, ESS for peer learning is 24 times higher than expert coaching.

Cascade training

For Cascade Training, the calculated learning efficacy, , is approximately 1.40. This reflects the weighted assessment based on the provided criteria and their importance, indicating lower efficacy compared to peer learning.

Cascade training has a higher ESS than expert coaching, due to its ability to achieve scale.

Learn more: Why does cascade training fail?

Expert coaching

For Expert Coaching, the calculated learning efficacy, , is approximately 2.20. This value indicates higher efficacy than cascade training but lower than peer learning.

However, the ESS is the lowest of the three methods, primarily due to its inability to scale. Read this article for a scalability comparison between expert coaching and peer learning.

Image: The Geneva Learning Foundation Collection © 2024

https://redasadki.me/2024/02/27/calculating-the-relative-effectiveness-of-expert-coaching-peer-learning-and-cascade-training/