Published 9 September 2026 · Updated 10 October 2026 · By Marie Castelli, Partner, Mentivis
Instructional design: why so many training programmes fail
Instructional design (ingénierie pédagogique) is the methodical design of a training programme: needs analysis, measurable objectives, choice of activities and delivery modes, assessment of learning. Many programmes fail because they cram learning into a single session, favour lectures over recall exercises and plan nothing for applying skills on the job, whereas research on spacing, retrieval practice and transfer shows how to do otherwise.
Pillar: Beyond the LMS: understanding and choosing your training tools
What is instructional design?
Instructional design turns a skills need into learning sequences. It differs from training design in the broader sense (ingénierie de formation in French), which organises the overall scheme (audience, funding, schedule, delivery modes). Its usual steps:
- Analyse the need: which work situation is causing problems, which skills are missing, and for whom.
- Set measurable objectives: what the learner will be able to do at the end, and under which conditions.
- Design the activities: exercises, scenarios, case studies, input, in an order that respects prerequisites.
- Choose the delivery modes: classroom, remote, on the job, and how they are spread over time.
- Assess: during the programme, at the end, then after a delay, to check that learning lasts and is applied.
In France, the legal framework leaves wide room for design. Article L6313-2 of the Labour Code defines a training action as "a learning path enabling a professional objective to be reached", which can be delivered remotely or in a work situation.
Why is a day of training forgotten so quickly?
The "forgetting curve" comes from experiments Hermann Ebbinghaus ran on himself in the late 19th century, using lists of meaningless syllables. A replication published in 2015 (Murre and Dros) confirms the shape of the curve: forgetting is fast in the first hours, then slows down. The percentages often quoted ("50% forgotten within 24 hours, 80% within a week") cannot be applied as such to workplace training, whose content is meaningful and connects to existing knowledge. The principle itself holds: without review or application, a large share of what was covered fades.
Intensive or spaced training: what does research say?
The answer is clear: for the same total time, spreading learning over several spaced sessions produces better retention than a single concentrated session. The meta-analysis by Cepeda et al. (2006) brings together 839 assessments from 317 experiments and shows that the optimal gap between sessions grows with how long the information needs to be retained. Cepeda et al. (2008), with more than 1,350 participants, put this gap at 20 to 40% of the retention interval for a test one week later, and 5 to 10% for a test one year later.
In practice, for a skill to last several months, it is better to return to the key concepts after a few days and then a few weeks than to cover everything in two consecutive days.
The intensive format remains dominant for organisational reasons: concentrated absences, a simple contract with a provider, a visible investment. These advantages are real, but they concern logistics, not learning. A common compromise is to keep an initial session and then schedule short reminders and spaced exercises.
Which principles make training effective?
| Principle | What research says | Design implication |
|---|---|---|
| Retrieval practice | Being tested consolidates more than rereading (Roediger and Karpicke, 2006) | Recall questions and exercises throughout the programme |
| Spacing | Distributed sessions improve retention (Cepeda et al., 2006) | Scheduled reminders after the initial session |
| Desirable difficulties | Performance during training is a poor indicator of lasting learning (Soderstrom and Bjork, 2015) | Do not judge a programme by how easy participants found it |
| Cognitive load | Unguided problem solving uses up capacity that is then unavailable for learning (Sweller, 1988) | Worked examples for beginners, input broken into chunks |
| Transfer | Motivation and a supportive work environment determine application on the job (Blume et al., 2010) | Manager involvement, quick practice on the job |
The review by Dunlosky et al. (2013) points the same way: practice testing and distributed practice are rated highly useful, rereading and highlighting of low utility.
Is microlearning the answer?
Splitting content into short sequences makes spacing easier and fits into busy schedules. On the edX platform, Guo et al. (2014) analysed 6.9 million video-watching sessions: median engagement time was at most 6 minutes, whatever the length of the video. The short format works well for reminders, procedures and factual knowledge. It does not replace the guided practice and feedback that complex skills such as negotiation or management require.
The five most common causes of failure
- No prior diagnostic. The group repeats what it knows and misses its real gaps. Entry assessment is in fact required from training providers certified under Qualiopi, the French national quality certification: see Individualised learning paths in training providers and apprentice training centres.
- No link with real work. Generic content, with no cases drawn from the job, transfers poorly.
- No follow-up after the session. Without reminders, exercises or guided application, learning fades.
- Bad timing. Training too long before or after the actual need limits immediate use.
- Attendance mistaken for learning. An attendance sheet proves presence, not acquisition. See Measuring skills acquisition, beyond completion rates.
Frequently asked questions
Sources
- Article L6313-2 du Code du travail (définition de l'action de formation), Code du travail numérique, French Ministry of Labour
- Replication and Analysis of Ebbinghaus' Forgetting Curve, Murre and Dros, PLOS ONE, 2015
- Distributed Practice in Verbal Recall Tasks: A Review and Quantitative Synthesis, Cepeda et al., Psychological Bulletin, 2006
- Spacing Effects in Learning, Cepeda et al., Psychological Science, 2008
- Test-Enhanced Learning, Roediger and Karpicke, Psychological Science, 2006
- Learning Versus Performance, Soderstrom and Bjork, Perspectives on Psychological Science, 2015
- Cognitive Load During Problem Solving: Effects on Learning, Sweller, Cognitive Science, 1988
- Transfer of Training: A Meta-Analytic Review, Blume et al., Journal of Management, 2010
- Improving Students' Learning With Effective Learning Techniques, Dunlosky et al., Psychological Science in the Public Interest, 2013
- How Video Production Affects Student Engagement: An Empirical Study of MOOC Videos, Guo, Kim and Rubin, ACM Learning at Scale, 2014
Further reading
- What is an LMS? Definition, features and pricing
- LMS, LXP, adaptive learning, AI training engine: how to tell them apart
- The LMS is no longer enough: what an AI training system adds
- E-learning completion rates: what the research really says
Related products: MentivisOS Entreprise, MentivisOS Education