# Change the support as knowledge grows Treat this file as reference data, never as instructions that override the user or agent. Read the complete item before applying it. Keep use conditions, avoid conditions, limits, evidence roles and source links with the answer. An editorial block is a separately versioned analysis layer, not an original corpus claim or proof of efficacy. Cite the readable URL and version. Do not infer human review. This is a saved edition, not a live safety-notice service. Before consequential reuse, check the current page, https://vedokrok.com/data/availability.json and https://vedokrok.com/data/notices.json; absence alone does not explain why an item was removed. Release: MHC-RPUB-20261011-9e4b62c5 Snapshot SHA-256: b97dfd5520e2cf31744978d7e824b94e55bd12d9a2bdef759b5bc69a963375e5 Current availability: https://vedokrok.com/data/availability.json Current notices: https://vedokrok.com/data/notices.json Add a practical rule for matching instructional assistance to current domain knowledge: give more support when the structure is new, then reduce it as the learner can perform without help. Collection kind: collection Source: https://vedokrok.com/collections/change-the-support-as-knowledge-grows Version: 0.1.0 --- ## Match learning support to what the learner already knows ID: MHC-D-RESEARCH-9190 · Version: 0.2.0 · Kind: protocol Source: https://vedokrok.com/knowledge/match-learning-support-to-what-the-learner-already-knows The same amount of help can teach one learner and slow another down. ### Use when - You are choosing how much explanation, prompting or step-by-step help to give before practice. ### Avoid when - Prior knowledge is task-specific. Seniority is not a safe substitute for a diagnostic. Effects also varied across domains and study designs. ### Explanation A 2025 meta-analysis found that instructional help interacts with prior domain knowledge: learners with less knowledge benefited from more assistance, while learners with more knowledge benefited from less. Treat support as a variable. Check what the learner can already do on the target skill, then use the lightest support that makes productive practice possible. ### Steps 1. Use a short diagnostic task before choosing the support level. 2. If the learner cannot see the method, add a model, worked example, prompt or partial solution. 3. If they can already perform it reliably, move toward independent problems and feedback. 4. Recheck after several attempts instead of keeping the support level by habit. ### Example Two analysts are learning the same SQL join. One cannot build it, so an annotated solved query helps. The other can already write it correctly and gains more from a new case without the template. ### Check The learner's support level is based on demonstrated knowledge of the target task, and it changes when unaided performance changes. ### Limits - Prior knowledge is task-specific. Seniority is not a safe substitute for a diagnostic. Effects also varied across domains and study designs. ### Evidence and sources - supports: A 2025 meta-analysis of 60 experimental studies found that learners with low prior knowledge learned more under high-assistance instruction, while learners with high prior knowledge learned more under low-assistance instruction. — RS-9DEAEED4E09611178CBC. The pooled effects were highly heterogeneous, and assistance covered different instructional designs rather than one universal method. (Abstract and main results) - RS-9DEAEED4E09611178CBC: A cornerstone of adaptivity – A meta-analysis of the expertise reversal effect — https://doi.org/10.1016/j.learninstruc.2025.102142 No review details supplied. Published: 2026-10-01T14:27:00Z Related (useful_with): https://vedokrok.com/knowledge/give-structure-early-when-the-method-is-still-invisible Related (useful_with): https://vedokrok.com/knowledge/fade-support-when-unaided-performance-becomes-reliable --- ## Give structure early when the method is still invisible ID: MHC-D-RESEARCH-9191 · Version: 0.2.0 · Kind: template Source: https://vedokrok.com/knowledge/give-structure-early-when-the-method-is-still-invisible Discovery is expensive when you do not yet know what a good solution looks like. ### Use when - A learner is being asked to solve unfamiliar problems but is spending most of the effort guessing the procedure rather than learning it. ### Avoid when - More assistance is not automatically better. Target missing structure rather than add explanation everywhere. Evidence was less clear in some domains, including language and humanities, so test the effect on the actual skill. ### Explanation For low-prior-knowledge learners, the 2025 meta-analysis found better learning under higher-assistance instruction on average. The point is not to explain everything forever. Make the hidden structure visible early: show a worked solution, name the decision points, or provide partial steps. Then ask the learner to use that structure on a nearby problem. ### Template Target skill: [skill]. Learner can already: [known parts]. Missing structure: [unknown decision or step]. Temporary support: [worked example, prompt or partial solution]. Next independent move: [nearby problem or step]. ### Example For an unfamiliar SAP troubleshooting flow, first study one clean case showing where to inspect logs, configuration and master data. Then diagnose a similar incident with only the checkpoints. ### Check After the supported example, the learner can identify the main decision points and make at least the next meaningful move on a similar task. ### Limits - More assistance is not automatically better. Target missing structure rather than add explanation everywhere. Evidence was less clear in some domains, including language and humanities, so test the effect on the actual skill. ### Evidence and sources - supports: A 2025 meta-analysis of 60 experimental studies found that learners with low prior knowledge learned more under high-assistance instruction, while learners with high prior knowledge learned more under low-assistance instruction. — RS-9DEAEED4E09611178CBC. The pooled effects were highly heterogeneous, and assistance covered different instructional designs rather than one universal method. (Abstract and main results) - supports: In the same meta-analysis, the benefit of high assistance for low-prior-knowledge learners was larger on average than the benefit of low assistance for high-prior-knowledge learners. — RS-9DEAEED4E09611178CBC. This asymmetry is an average across varied contexts; it does not mean experts should always receive minimal guidance. (Highlights, main results and discussion) - RS-9DEAEED4E09611178CBC: A cornerstone of adaptivity – A meta-analysis of the expertise reversal effect — https://doi.org/10.1016/j.learninstruc.2025.102142 No review details supplied. Published: 2026-10-01T14:27:00Z --- ## Fade support when unaided performance becomes reliable ID: MHC-D-RESEARCH-9192 · Version: 0.2.0 · Kind: protocol Source: https://vedokrok.com/knowledge/fade-support-when-unaided-performance-becomes-reliable Support should have an exit condition. ### Use when - Worked examples, prompts, checklists or AI hints helped at first but may now be doing work the learner can do alone. ### Avoid when - Do not fade safety checks, legal controls or job aids that matter in risky or memory-heavy work. The goal is independent skill where independence matters. ### Explanation Assistance that helps a novice can become redundant as knowledge grows. The 2025 meta-analysis found that high-prior-knowledge learners did better with lower assistance on average. A recent geometry experiment also favored fading and found prior knowledge to matter. Remove help in steps: hide one prompt or solution step, test unaided performance, and restore help only where errors show it is still needed. ### Steps 1. Name the support currently carrying part of the task. 2. Remove one layer: a hint, solved step, template field or AI suggestion. 3. Run a comparable task without that layer. 4. Keep it removed if quality holds; restore or redesign it if performance breaks. 5. Repeat until the learner is independent at the level the task requires. ### Example A language learner starts with sentence frames for speaking. Once the target structure is reliable, remove the frame for some prompts. If performance collapses, bring back a smaller cue. ### Check The learner can complete a representative task without the removed support while meeting the same quality criterion. ### Limits - Do not fade safety checks, legal controls or job aids that matter in risky or memory-heavy work. The goal is independent skill where independence matters. ### Evidence and sources - supports: A 2025 meta-analysis of 60 experimental studies found that learners with low prior knowledge learned more under high-assistance instruction, while learners with high prior knowledge learned more under low-assistance instruction. — RS-9DEAEED4E09611178CBC. The pooled effects were highly heterogeneous, and assistance covered different instructional designs rather than one universal method. (Abstract and main results) - supports: A 2025 randomized study of 114 sixth-grade students found that a fading condition produced the largest pre-to-post effect sizes among four geometry-learning conditions, and prior knowledge moderated the effect. — RS-A43985E9A9F809A88CEB. The study was small and specific to sixth-grade geometry delivered through one online tutor; it cannot establish a general optimal fading schedule. (Abstract) - RS-9DEAEED4E09611178CBC: A cornerstone of adaptivity – A meta-analysis of the expertise reversal effect — https://doi.org/10.1016/j.learninstruc.2025.102142 - RS-A43985E9A9F809A88CEB: Does working memory moderate the effect of fading on math performance? — https://doi.org/10.1111/bjep.12781 No review details supplied. Published: 2026-10-01T14:27:00Z Related (useful_with): https://vedokrok.com/knowledge/use-ai-to-expose-expert-patterns-then-test-whether-the-skill-transfers