Your eLearning Looks Great but Nobody Is Applying It — Here Is Exactly Why

The course launched on schedule. The visual design is sharp. The interactions work flawlessly. Completion rates are sitting at 87 percent. Your satisfaction scores are the highest they have been in two years.

And then your operations manager sends you a message. The error rates have not moved. The customer complaint patterns are identical to before the training. The sales behaviours your programme was designed to change are unchanged three months after every eligible team member completed the module.

This is the eLearning application gap. And it is, without question, the most expensive and most demoralising problem in corporate learning because it happens after everything appears to have worked. The course was built. The learners completed it. The data looks fine. And yet nothing in the real world has changed.

The eLearning application gap is not a failure of aesthetics or technical execution. It is a failure of instructional architecture, organisational support design, and the fundamental understanding of what it actually takes to move knowledge from a screen into a human behaviour that persists under real workplace conditions. This guide names every cause precisely and gives you the practical strategies to close the gap for good.

Why the eLearning Application Gap Is So Widespread

Before diagnosing the specific causes, it is worth understanding why the eLearning application gap is so consistently prevalent across organisations that invest seriously in learning quality.

The root issue is a fundamental mismatch between what eLearning development processes are optimised to produce and what behaviour change actually requires.

Most eLearning development processes are optimised to produce a completed, technically functional, visually polished course that passes stakeholder review and launches on schedule. These are legitimate and measurable production goals. However, none of them is the same as producing a change in learner behaviour in the real workplace, which is a fundamentally different and significantly more complex outcome that requires a different set of design and organisational conditions to achieve.

Furthermore, the metrics most commonly used to evaluate eLearning success — completion rates, satisfaction scores, and assessment pass rates, all measure the experience of consuming the course, not the experience of applying its content in the real world. These metrics can look excellent while the application gap remains entirely unaddressed, because they are measuring the wrong thing entirely.

Consequently, organisations receive consistently positive production metrics that signal success while the actual learning outcome, changed behaviour and improved performance, fails to materialise. The eLearning application gap persists not because organisations are not paying attention, but because they are paying attention to the wrong signals.

The 10 Exact Reasons Your eLearning Is Not Being Applied

Each of the following reasons is a distinct, diagnosable cause of the eLearning application gap. Most underperforming training programmes have several of these present simultaneously, which is why the gap persists even when individual improvements are made. Closing the application gap requires addressing all relevant causes, not just the most obvious one.

Reason 1: The Learning Objectives Were Never Connected to Real Performance Behaviours

This is the foundational cause of the eLearning application gap and the one that, when present, makes every other improvement insufficient.

A learning objective that is not connected to a specific, observable performance behaviour cannot produce behaviour change. Full stop. If the instructional design of your eLearning programme was built around objectives like “understand the importance of customer communication” or “be aware of the company’s data privacy obligations”, both of which are legitimate awareness goals, the course was structurally incapable of producing application, because neither objective specifies what the learner should actually do differently after completing the training.

Application requires that the learner know not just what is true or important, but specifically what they should do, when they should do it, how they should do it differently from what they currently do, and what doing it correctly looks and feels like in a realistic professional context. Learning objectives that do not specify these dimensions cannot be designed toward and content that is not designed toward specific performance behaviours does not produce them.

Therefore, the first diagnostic question for any eLearning programme experiencing an application gap is whether the learning objectives can be restated as specific, observable performance behaviours. If they cannot, if they describe states of awareness, understanding, or knowledge rather than observable actions, the root cause of the application gap is in the objective design, and the fix begins there.

Reason 2: The Content Taught Principles Without Building Decision-Making Practice

The second most common cause of the eLearning application gap is the principle-delivery problem, the design pattern in which eLearning content explains what the correct approach is without ever requiring learners to practise applying it in conditions that resemble real workplace decision-making.

This design pattern is deeply embedded in most eLearning development conventions. Content slide, followed by example, followed by knowledge check. The knowledge check confirms that the learner can identify the principle when it is presented clearly and explicitly. What it does not confirm and what the design pattern does not develop, is whether the learner can recognise when to apply the principle in the noise and complexity of a real work situation, choose the right application approach among competing options, and execute it under the social, emotional, and time pressure that real workplace situations create.

Principles that are understood in the clean, explicit context of a training module frequently fail to activate in the ambiguous, pressured context of real professional situations, not because the learner forgot the principle, but because the cognitive pathway between the principle and its real-world application was never built during training.

Building that pathway requires practice — specifically, practice in conditions that are sufficiently similar to the real performance context to activate the same cognitive and decision-making processes. Scenario-based practice, realistic case application, and decision simulations are the design tools that build this pathway. Content-delivery modules, however well written and visually engaging, do not.

Reason 3: The Assessment Measured Recall, Not Application Readiness

The assessment design of most eLearning programmes actively reinforces the application gap rather than closing it, because most assessments are designed to measure whether learners can recall or recognise the content they have just consumed, not whether they are ready to apply it in the real world.

A learner who can correctly answer “Which of the following best describes the GDPR definition of personal data?” has demonstrated recall. A learner who can navigate a realistic scenario in which they must decide whether a specific data handling situation requires consent, notification, or no additional action, under conditions of contextual ambiguity that reflect actual workplace data privacy decisions, has demonstrated something closer to application readiness.

The difference between these two assessment designs is not primarily about difficulty. It is about what cognitive process the assessment activates. Recall-based assessments activate recognition, a relatively shallow cognitive process that does not reliably predict real-world application. Application-based assessments activate judgment, situational reading, and decision-making, the cognitive processes that are actually required in the performance context.

Consequently, programmes with high assessment pass rates and low application rates are almost always programmes whose assessments are measuring recall rather than readiness. The assessment scores look good because recall of recently presented content is relatively easy for most adult learners. But those scores predict nothing about whether the learner will apply the content when it matters, because they were never required to demonstrate that capability during the training.

Reason 4: There Was No Workplace Application Plan

Even well-designed eLearning that builds genuine capability through scenario-based practice and application-focused assessment will produce limited real-world behaviour change if learners complete it and then return to their work environment without any structured plan for translating what they learned into changed practice.

Application planning is the bridge between learning and behaviour change and it is almost universally absent from corporate eLearning programmes. Learners who complete a module close the browser, navigate back to their inbox, and immediately re-enter the cognitive and behavioural patterns of their normal work routine. The new learning is present in memory briefly, but there is no trigger, no structure, and no social expectation that directs them to actually apply it before those memory traces begin to fade.

A structured workplace application plan changes this dynamic. It gives the learner a specific, concrete action to take within a defined short timeframe after completing the module, an application commitment that is personalised, realistic, and small enough to be genuinely achievable within the demands of their current work schedule.

Effective application planning prompts include asking learners to identify one specific situation in their upcoming week where they will apply the target skill, to specify what they will do differently from their current approach, and to share that commitment with their manager or a peer, creating a social accountability structure that significantly increases follow-through. These prompts take 60 to 90 seconds to complete and produce measurably better application rates than completing the module without them.

Reason 5: The Manager Was Not Involved — Before, During, or After

This is the cause of the eLearning application gap that L&D teams most frequently acknowledge and most consistently fail to address because addressing it requires changing the behaviour of people who are not in the L&D function’s direct control.

The research on learning transfer consistently identifies manager behaviour as the single most powerful predictor of whether training produces real workplace application. Specifically, learners whose managers discuss the training with them before they complete it, ask them about it after completion, create opportunities for them to practise the target skills, and provide feedback on their application are significantly more likely to apply training content than learners whose managers treat training as a scheduling inconvenience to be accommodated and forgotten.

The mechanism is straightforward. When a manager expresses genuine interest in a training programme, by discussing its relevance to the team’s current challenges before the training, asking the learner what they took from it immediately after completion, and explicitly creating or acknowledging opportunities for the learner to apply new skills, the social signal sent to the learner is that applying this training is a real expectation, not a box-ticking exercise. That social signal is far more powerful than any internal motivation the training content itself can generate.

Conversely, when managers treat training as an administrative requirement, signing off on completion records without engaging with the content or its application, learners receive the equally clear social signal that completing the training is the goal, not applying it. And learners reliably act on the social signals of their immediate work environment rather than on the intrinsic motivation generated by a well-designed module.

Closing this cause of the eLearning application gap requires designing manager engagement into the training programme as explicitly as any other component including manager briefing materials that explain what the training covers and what specific application behaviours to look for and reinforce, post-training conversation guides that give managers a structured framework for the application conversation, and reporting that shows managers their team’s training activity and flags learners who may need additional support.

Reason 6: The Work Environment Did Not Support the New Behaviour

A learner can leave a training programme fully capable of performing the target behaviour, genuinely understanding it, practising it in a realistic scenario, and committing to apply it and then return to a work environment that makes applying it structurally difficult or socially unrewarding.

This cause of the eLearning application gap reflects a fundamental truth about behaviour change that learning design cannot overcome alone: behaviour is shaped by the environment in which it occurs, not only by the capability of the individual performing it. When the work environment rewards the old behaviour through incentive structures, social norms, workload pressures, tool limitations, or management practices, new behaviour learned in training faces genuine structural competition that capability alone cannot win.

Consider a customer service training programme designed to build more empathetic, needs-focused customer conversations. If the operational metrics that customer service representatives are measured and managed on are purely about call handling time and first-call resolution rate, with no measurement of conversation quality or customer experience, the environment is actively rewarding the efficient, transactional approach that the training was designed to replace.

No amount of eLearning quality can overcome this structural barrier. The capability to have a different kind of conversation may be present. But the environmental signals, what gets measured, what gets rewarded, what managers comment on, all point in the opposite direction.

Diagnosing whether the work environment is a cause of the application gap requires honest stakeholder conversations about the metrics, incentives, social norms, and operational pressures that shape behaviour in the target performance context. When environmental barriers are identified, the solution is not a better eLearning course, it is organisational change work that addresses the structural factors preventing application, alongside the learning design work that builds the capability.

Reason 7: The Training Was a One-Time Event with No Reinforcement

Memory decay is not a theory. It is a well-documented biological reality of human cognition. Hermann Ebbinghaus’s forgetting curve, one of the most robustly replicated findings in psychological research, demonstrates that without active reinforcement, people forget approximately 50 percent of new information within a day of learning it, and up to 70 percent within a week.

Most corporate eLearning programmes are delivered as single events. A learner completes a module, the completion is recorded, and the programme is considered delivered. The learner returns to their work environment carrying a memory trace of the content that begins decaying immediately and is typically reduced to a fraction of its original accessibility within the week.

This is not a failure of the learner. It is a failure of the programme design to account for one of the most fundamental and well-established principles of human memory. Content encountered once, without reinforcement, does not persist at the level of accessibility required for reliable application under real workplace conditions.

Closing this cause of the eLearning application gap requires designing reinforcement into the programme architecture from the outset, not adding it as an afterthought if application rates are disappointing. Spaced reinforcement microlearning modules, deployed at three days, seven days, fourteen days, and thirty days after primary module completion, dramatically improve long-term retention and application readiness compared to a single-event delivery.

Additionally, performance support resources, job aids, quick reference guides, decision trees, or mobile-accessible micro-tools, that give learners access to the key learning content at the moment they need to apply it bridge the gap between what memory retains and what real performance situations require.

Reason 8: The Learner Did Not See the Personal Relevance

Learners apply training when they believe, concretely and specifically, that applying it will produce a better outcome for them in their specific professional situation. They do not apply training when the personal relevance of the content has not been made concrete, when the connection between the module content and the specific professional challenges they face daily has been left implicit rather than made explicit.

Most eLearning content is written from an organisational perspective, explaining why the content matters to the organisation, what business outcomes the training supports, and what the organisational consequences of non-application are. This framing addresses the wrong motivational target.

Learners are motivated by personal relevance, by the answer to the question they are asking implicitly throughout every training module: “What does this mean for me, specifically, in the situations I actually face?” When that question is not answered explicitly and convincingly, learners experience the training as organisationally important but personally peripheral and personally peripheral content does not produce personally sustained behaviour change.

Writing for personal relevance requires deep understanding of the learner’s specific professional challenges, frustrations, and goals and framing every learning objective, every scenario, and every application prompt in terms of what the target behaviour change will make easier, better, or more effective for this specific learner in their specific professional reality.

Reason 9: There Was No Performance Support at the Moment of Application

Even highly motivated learners with strong recall of training content frequently fail to apply new behaviours correctly in their first real-world attempts because real performance situations are more complex, more ambiguous, and more emotionally pressured than the training environment in which the capability was first built.

Without access to performance support at the moment of application, a resource the learner can quickly consult to confirm the correct approach, check a procedural step, or remind themselves of the key decision criteria, that first application attempt often defaults to the familiar old behaviour rather than risking the new one in a high-stakes real situation.

Performance support design is therefore not a supplement to eLearning programmes, it is an integral component of a complete learning solution that is serious about producing application. Mobile-accessible quick reference guides, decision-support checklists embedded in workflow tools, short video demonstrations of key procedures accessible at the point of task, and conversational AI tools that answer application questions in real time are all forms of performance support that bridge the gap between training completion and confident real-world application.

The design principle is simple: make the correct behaviour easier to access and perform than the old behaviour, at the moment when the application decision is being made. Performance support is the most practical implementation of this principle available to L&D teams.

Reason 10: The Organisation Treated Training Completion as the Goal

The final and perhaps most systemic cause of the eLearning application gap is organisational, the widespread institutional treatment of training completion as the definition of training success.

When completion is the goal, every organisational system around the training programme orients toward completion. Learning management systems track and report completion. Managers chase completion rates among their team members. HR and compliance functions report completion percentages to leadership. L&D teams are evaluated on whether learners completed the training on schedule.

None of these systems track, report, or evaluate whether learners applied the training. Consequently, the social and organisational pressure that drives behaviour, what gets measured, what gets reported, what gets celebrated, points entirely toward completing the module and entirely away from applying its content.

This systemic misalignment is self-reinforcing. The more completion is treated as success, the more every stakeholder in the training ecosystem, from the L&D team that designs the programme, to the managers who schedule their teams to complete it, to the learners who engage with it, internalises completion as the actual goal. Application becomes an aspiration that everyone agrees is important in principle and nobody is actually measuring, reinforcing, or accountable for in practice.

Closing this cause of the application gap requires a fundamental shift in how the organisation defines and measures training success, moving the primary success metric from completion to measurable behaviour change and business outcome improvement. This shift is organisationally significant and often politically challenging. But it is the only systemic solution to a systemic problem.

The Application Gap Diagnostic: Finding Your Specific Causes

Not every training programme experiencing an application gap has all ten causes present simultaneously. The most efficient path to closing the gap is diagnosing which specific causes are active in your situation and addressing those with targeted interventions rather than attempting to overhaul everything at once.

The following diagnostic questions help identify the active causes in a specific programme. Work through them in sequence, using honest answers rather than optimistic assumptions.

Can each learning objective be restated as a specific, observable performance behaviour? If not, Reason 1 is active.

Does the programme include scenario-based practice that requires learners to make decisions in conditions resembling their real work context? If not, Reason 2 is active.

Do your assessments include application-based items, situational judgment questions, realistic case scenarios, or decision simulations, rather than exclusively recall or recognition items? If not, Reason 3 is active.

Does the programme include a structured workplace application prompt, asking learners to identify a specific upcoming situation where they will apply the target behaviour? If not, Reason 4 is active.

Have managers received a briefing on the programme, a guide for the post-training conversation, and access to reporting on their team’s training activity? If not, Reason 5 is active.

Have you evaluated whether the work environment including metrics, incentives, social norms, and operational pressures, supports or competes with the target behaviour? If not, Reason 6 may be active and undiagnosed.

Does the programme include spaced reinforcement content deployed at intervals after initial completion, or performance support resources accessible at the moment of application? If not, Reasons 7 and 9 are active.

Is the personal relevance of the target behaviour change, specifically what it will make easier or better for this learner in their specific professional situation, made explicit and concrete in the programme content? If not, Reason 8 is active.

Does your organisation track any metric of training success beyond completion rates, assessment pass rates, and satisfaction scores? If not, Reason 10 is active, and is likely amplifying every other cause.

Closing the eLearning Application Gap: A Prioritised Action Framework

Diagnosing the active causes is only valuable if it leads to action. The following framework prioritises the actions that produce the greatest improvement in application rates for the lowest implementation cost, so that L&D teams with limited capacity can focus their effort where it will have the most impact.

Start with the objectives and assessment design. These are the two design elements with the greatest leverage on application outcomes and the most cost-effective to revise in existing programmes. Rewriting objectives to specify observable performance behaviours and redesigning at least two or three assessment items to require situational judgment rather than recall can be accomplished within a relatively modest revision cycle and produces measurable improvement in application readiness without requiring a complete programme rebuild.

Add a structured application prompt to every existing module. This is the single highest return-on-effort intervention available for programmes already in deployment. A 90-second application commitment prompt added to the final screen of any existing module, asking learners to identify a specific upcoming situation, commit to a specific application action, and optionally share that commitment with their manager, consistently improves application rates without requiring content redesign.

Build manager engagement into the programme communication plan. Manager briefing materials, post-training conversation guides, and completion reporting with manager visibility can be developed and deployed without touching the course content itself, making this a relatively low-cost intervention with disproportionate impact on application outcomes.

Design spaced reinforcement for your highest-priority programmes. Start with the one or two programmes where application failure is most consequential, whether in compliance risk, revenue impact, or operational quality and build a three to four touchpoint spaced reinforcement sequence for each. Deploy these as microlearning modules, email-based retrieval prompts, or manager-facilitated team discussion activities, whichever format fits most naturally into your learners’ workflow.

Shift at least one programme success metric toward behaviour change. Choose one programme where you can feasibly collect behaviour-level data — manager observation, quality audit results, or operational performance metrics and report that data alongside completion rates in your next L&D review. The act of measuring and reporting behaviour change, even imperfectly, begins to shift organisational attention toward application as the real definition of training success.

Key Takeaways

The eLearning application gap is not a mystery. It has specific, diagnosable causes and every one of them is addressable with targeted design and organisational interventions.

Your eLearning looks great but nobody is applying it because the learning objectives were not connected to real performance behaviours, because the content taught principles without building decision-making practice, because the assessment measured recall instead of application readiness, because there was no workplace application plan, because the manager was not involved, because the work environment did not support the new behaviour, because there was no reinforcement after a one-time event, because the personal relevance was never made concrete, because there was no performance support at the moment of application, and because the organisation treated completion as the goal.

Each of these causes is fixable. None of them requires unlimited budget or a complete programme rebuild to begin addressing. What they require is honest diagnosis, strategic prioritisation, and the willingness to measure training success by the standard that actually matters, not how many people completed the module, but how many people changed what they do because of it.

That is the goal. And with the right design decisions and the right organisational support, it is entirely achievable.

Close the Application Gap With eLearning Built for Behaviour Change — Partner with Learning Owl

At Learning Owl, we design eLearning that is built from the first conversation around a single question: what do we need learners to do differently and what will it take to make that happen?

Every programme we develop is grounded in precise performance objective definition, scenario-based practice that builds real decision-making capability, application-focused assessment design, spaced reinforcement architecture, and performance support resources that bridge the gap between training completion and confident real-world application.

We do not measure our success by completion rates. We measure it by whether learners are doing something different and whether that difference is producing the business outcomes your organisation invested in training to achieve.

If your current eLearning is completing at scale but not applying at scale, Learning Owl can help you diagnose exactly why and build the solution that closes the gap.

Frequently Asked Questions About the eLearning Application Gap

Q1. What is the eLearning application gap and why does it happen?

The eLearning application gap is the disconnect between what learners demonstrate during training — completion, assessment scores, and satisfaction — and what they actually do differently in their real work environment after training is complete. It happens because most eLearning programmes are optimised to produce a completed, technically functional course that passes stakeholder review rather than to produce the specific conditions that behaviour change requires. Those conditions include performance-specific learning objectives, decision-making practice under realistic conditions, application-focused assessment, structured workplace application planning, manager engagement, spaced reinforcement, and organisational metrics that treat behaviour change as the definition of training success. When these conditions are absent, completion and behaviour change remain disconnected regardless of how polished the course is.

Q2. Why do high completion rates not mean training is working?

High completion rates measure whether learners reached the end of a course, not whether they learned anything transferable, retained it over time, or applied it in their real work context. A learner can complete a module by clicking through content and passing a recall-based quiz without engaging deeply enough with the content to change any aspect of their professional behaviour. Completion rates are a measure of training delivery, not training effectiveness. The metrics that predict whether training is actually working are behaviour-level data, observable changes in how learners perform their work and business outcome data connected to the performance gap the training was designed to address. Both require deliberate measurement planning before training launches, not reporting of the default metrics that LMS platforms generate automatically.

Q3. What role do managers play in closing the eLearning application gap?

Manager behaviour is the single most powerful predictor of whether training produces real workplace application. Learners whose managers discuss the training with them before completion, ask about their takeaways after completion, create explicit opportunities for application, and provide feedback on their efforts are significantly more likely to apply training content than those whose managers treat training as an administrative requirement. The mechanism is social expectation, when managers signal through their behaviour that applying training is a genuine expectation rather than an optional follow-through activity, learners act accordingly. Closing the manager engagement gap requires designing manager briefing materials, post-training conversation guides, and team completion visibility into every programme, treating manager involvement as a programme component rather than a communication afterthought.

Q4. What is performance support and how does it help close the application gap?

Performance support refers to resources that give learners access to the correct approach, procedure, or decision criteria at the moment they need to apply them in their real work context, rather than requiring them to recall that information from memory under pressure. Examples include mobile-accessible quick reference guides, decision support checklists embedded in workflow tools, short video demonstrations of key procedures, and job aids that summarise the key steps of a complex process. Performance support is particularly valuable for skills that are applied infrequently, where memory decay between training and application means that even well-retained content may not be accessible at full reliability when it is needed. Designing performance support resources as integral components of every significant eLearning programme dramatically improves first-attempt application success compared to relying on memory alone.

Q5. How does spaced repetition help close the eLearning application gap?

Spaced repetition, the practice of revisiting learning content at strategically increasing intervals after initial acquisition, counteracts the memory decay that causes training content to become less accessible over the days and weeks following a one-time learning event. By deploying brief reinforcement touchpoints at three days, seven days, fourteen days, and thirty days after initial module completion, spaced repetition maintains the accessibility of training content in long-term memory at the level required for reliable application in real performance situations. Each reinforcement touchpoint should be a short, active retrieval activity, asking learners to recall and apply the key content rather than re-reading or re-watching it, which strengthens memory traces more effectively than passive review. Programmes that include spaced reinforcement consistently demonstrate better application rates at four to twelve weeks post-training than equivalent programmes delivered as single events without reinforcement.

Q6. How do you design learning objectives that produce application rather than just awareness?

Learning objectives that produce application are written around specific, observable performance behaviours, describing what the learner will do differently after training, not what they will know or understand. The test of an application-oriented objective is whether it can be observed and measured in the real work environment. “Understand the importance of active listening” fails this test, it describes a mental state that cannot be directly observed. “Use open questions and reflective summaries in at least three customer interactions per shift” passes this test, it describes observable, measurable behaviour that a manager or quality auditor can verify. Writing application-oriented objectives requires knowing exactly what the target performance change looks like in the learner’s specific work context, which requires the kind of detailed performance analysis and learner context research that most eLearning projects do not invest sufficient time in before development begins.

Q7. Can existing eLearning programmes be redesigned to close the application gap without being completely rebuilt?

Yes, and several of the highest-impact interventions for closing the application gap can be applied to existing programmes without requiring a complete rebuild. Adding a structured workplace application commitment prompt to the final screen of an existing module is a minimal content change with measurable impact on application rates. Redesigning two or three assessment items from recall-based to situational judgment format significantly improves application readiness signalling without requiring new content development. Building a spaced reinforcement sequence of three to four microlearning touchpoints can be developed as a complementary programme element without touching the original course. And developing manager briefing materials and post-training conversation guides requires no changes to the course itself. A full rebuild is most justified when the learning objectives themselves are fundamentally misaligned with the target performance behaviour, which is the root cause that no supplementary intervention can fully compensate for.

Q8. How should L&D teams measure whether training is producing real application?

Measuring real training application requires data beyond what LMS systems generate automatically. The most practical measurement approach uses multiple data sources at different levels of outcome. Manager observation data, collected through structured post-training observation checklists completed four to eight weeks after training, provides the most direct evidence of behaviour change in the real workplace. Operational performance metrics connected to the specific performance gap the training was designed to address — error rates, conversion rates, customer satisfaction scores, compliance incident rates, productivity measures, provide business-level evidence of application impact when compared against pre-training baseline data. Learner self-report surveys completed four to six weeks after training ask learners to report on specific application attempts, challenges, and outcomes. And assessment data from spaced reinforcement activities deployed at intervals after initial training measures retention over time, which is a strong predictor of sustained application. No single data source provides a complete picture, but any combination of these sources produces significantly more meaningful evidence of application than completion and satisfaction metrics alone.

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