Serious elearning Manifesto
Recently I signed the new E-learning Manifesto that will hopefully help to transform our industry and courses into truly effective, performance driven solutions. Since these are principles that I subscribe to and practice everyday in my own business, I whole-heartedly endorse this manifesto.
This manifesto was initiated by Michael Allen, Julie Dirkson, Clark Quinn, Will Thalheimer and many others.
Supporting Principles for the elearning Manifesto
Do Not Assume that Learning is the Solution
We do not assume that a learning intervention is always the best means to helping people perform better.
Do Not Assume that eLearning is the Answer
When learning is required, we do not assume elearning is the only (or the best) solution.
Tie Learning to Performance Goals
We couple the skills we are developing to the goals of organizations, individuals, or both.
Target Improved Performance
We help our learners achieve performance excellence; enabling them to have improved abilities, skills, confidence, and readiness to perform.
Provide Realistic Practice
We provide levels of realistic practice. For example: simulations, scenario-based decision making, case-based evaluations, and authentic exercises.
Enlist Authentic Contexts
We provide learners with sufficient experience in making decisions in authentic context.
Provide Guidance and Feedback
We provide learners with guidance and feedback to correct their misconceptions, reinforce their comprehension, and build effective performance.
Provide Realistic Consequences
We will provide learners with a sense of the real-world consequences.
Adapt to Learner Needs
We utilize elearning’s capability to create flexible learning environments for the learner.
Motivate Meaningful Involvement
We provide learners with experiences relevant to their goals. And/or experiences that motivate them to engage deeply in the process of learning.
Aim for Long-term Impact
We create learning experiences with long-term impact.
Use Interactivity to Prompt Deep Engagement
We use unique interactive capabilities to support: reflection, application, rehearsal, elaboration, contextualization, debate, evaluation, synthesization, page turning, rollovers, and information search.
Provide Support for Post-Training Follow-Through
We support instruction with the appropriate mix of follow-through. We provide learning events to: reinforce key learning points, marshal supervisory for learning application, and create mechanisms.
Diagnose Root Causes
We determine whether training is likely to produce benefits and whether other factors should be targeted for improvement. We also endeavor to be proactive in assessing organizational performance factors–not waiting for requests from organizational stakeholders.
Use Performance Support
We consider providing: job aids, checklists, wizards, sidekicks, planners, and other performance support tools for standard elearning interactions.
Good learning cannot be assured without measurement, which includes the following:
- Measure Outcomes
We measure if the learning has led to benefits for the individual and/or the
- Measure Actual Performance Results
We measure if the learner’s level of success, success factors, obstacles encountered, and level of supervisor support where warranted.
- Measure Learning Comprehension and Decision Making During Learning
At a minimum, during the learning, we measure both learner comprehension and decision-making ability. Ideally, we would also measure these at least a week after the learning.
- Measure Meaningful Learner Perceptions
We measure learners’ perceptions of the following: ability to apply what they’ve learned, level of motivation, and support they receive in implementing the learning.
- Measure Outcomes
Iterate in Design, Development, and Deployment
We won’t assume our first pass is right, but we evaluate and refine until we achieve our design goals.
Support Performance Preparation
We prepare learners to be motivated to apply what they’ve learned, inoculated against obstacles, and prepared to deal with specific situations.
Support Learner Understanding with Conceptual Models
We believe performance should be based upon conceptual models to guide decisions. And that such models should be presented, linked to steps in examples, practiced with, and used in feedback.
Use Rich Examples and Counterexamples
We present examples and counterexamples, together with the underlying thinking.
Enable Learners to Learn from Mistakes
Failure is an option. We let learners make mistakes so they can learn from them. In addition, where appropriate, we model mistake-making and mistake-fixing.
We leverage the knowledge and skills learners bring to the learning environment through their past experience and individual contexts.
(list taken from manifesto website)
What do you think about these principles? Leave your thoughts below.