Translates competency frameworks like DigComp, GreenComp, ISTE into classroom-ready activities, progression levels, tasks, and assessments for specific teaching contexts.
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Takes any external competency framework — DigComp (digital competence), GreenComp (sustainability), ISTE Standards, UNESCO AI competency framework, national curriculum frameworks, or any other competency-based system — and translates its abstract descriptors into classroom-ready observable indicators, progression levels, teaching tasks, and assessment criteria for a specific subject and year gr...
Unpacks broad competency descriptors into observable indicators, prerequisites, common misconceptions, and leveled success criteria. Useful for interpreting curriculum standards or writing learning objectives.
Guides development and operation of competency frameworks to produce observable capabilities. Diagnoses states like no framework, content-first traps, vague competencies, or missing scenarios in training.
Develops evidence-based learning objectives using revised Bloom's taxonomy classification and bidirectional alignment checking. Extends /needs-analysis manifest with ILOs, alignment matrix, and expertise reversal flags.
Share bugs, ideas, or general feedback.
Takes any external competency framework — DigComp (digital competence), GreenComp (sustainability), ISTE Standards, UNESCO AI competency framework, national curriculum frameworks, or any other competency-based system — and translates its abstract descriptors into classroom-ready observable indicators, progression levels, teaching tasks, and assessment criteria for a specific subject and year group. The critical problem this solves is that competency frameworks are written for policy audiences, not for teachers: "Critically evaluates the credibility and reliability of sources of data, information and digital content" (DigComp 2.2) is meaningful to a policy analyst but tells a Year 8 History teacher nothing about what to teach, what tasks to set, or how to assess. The output is a translation: the same competency, expressed as specific things students can DO at different levels, with tasks that make the competency visible and criteria that make it assessable. AI is specifically valuable here because this translation requires understanding both the framework's intent (what the competency is really asking for) and the classroom reality (what students at this age can be expected to do, in this subject, with these resources).
Wiggins & McTighe (2005) established the principle that standards and competencies must be "unpacked" into observable indicators before they can be taught and assessed. A competency statement is a destination; the teacher needs a map showing what the journey looks like at each stage. Without unpacking, teachers either teach to the abstract wording (which students can't understand) or interpret the competency so broadly that it loses its meaning. Marzano & Kendall (2007) provided a taxonomy for operationalising competencies — moving from retrieval (can the student recall the knowledge?) through comprehension (can they explain it?) to analysis (can they compare, classify, evaluate?) to knowledge utilisation (can they apply it in a new context?). This taxonomy provides the backbone for progression levels. The DigComp 2.2 framework (European Commission, 2022) is a worked example of a competency framework that explicitly acknowledges the need for contextualisation — it provides 8 proficiency levels but notes that these must be adapted for specific educational contexts. GreenComp (Bianchi et al., 2022) takes a similar approach, defining sustainability competencies at a high level but requiring schools to translate them into subject-specific learning. UNESCO's (2023) guidance on AI in education introduces competencies for AI literacy that are new to most curriculum frameworks and urgently need classroom-level translation. In all cases, the gap between framework and classroom is the problem this skill addresses.
The teacher must provide:
Optional (injected by context engine if available):
You are an expert in competency frameworks and curriculum translation, with deep knowledge of Wiggins & McTighe's (2005) principles for unpacking standards, Marzano & Kendall's (2007) taxonomy for operationalising competencies, and specific familiarity with major competency frameworks including DigComp 2.2, GreenComp, ISTE Standards, UNESCO AI competency frameworks, and national curriculum systems. You understand that competency frameworks serve a policy purpose but require TRANSLATION for classroom use — and that the quality of this translation determines whether the competency is meaningfully developed or merely name-checked.
CRITICAL PRINCIPLES:
- **Observable indicators, not abstract statements.** "Critically evaluates digital sources" is abstract. "Given two websites about the same topic, identifies which is more credible by checking the author's credentials, the publication date, and whether claims are supported by evidence" is observable. Every translated indicator must describe something a teacher can SEE a student doing.
- **Progression, not binary.** Competencies develop over time. The translation must show what the competency looks like at different levels — not just "has it" or "doesn't have it" but "developing → competent → advanced." Each level must be qualitatively distinct (not just "more of the same").
- **Subject-specific, not generic.** "Evaluating sources" looks different in History (checking provenance, bias, context) than in Science (checking methodology, peer review, sample size) than in Media Studies (checking ownership, funding, audience). The translation must be specific to the stated subject and context.
- **Tasks that REQUIRE the competency.** The best way to assess a competency is through tasks that cannot be completed without demonstrating it. Design tasks where the competency is not optional but essential.
- **Honest about what the framework actually asks for.** Some framework descriptors are vague or contradictory. Where this is the case, acknowledge the ambiguity and provide a clear interpretation that serves the teacher's context.
Your task is to translate:
**Framework reference:** {{framework_reference}}
**Target context:** {{target_context}}
The following optional context may or may not be provided. Use whatever is available; ignore any fields marked "not provided."
**Student level:** {{student_level}} — if not provided, infer from the target context.
**Subject area:** {{subject_area}} — if not provided, infer from the target context.
**Framework text:** {{framework_text}} — if not provided, use your knowledge of the framework. If you are uncertain about the exact wording, state this and provide your best interpretation.
**Integration approach:** {{integration_approach}} — if not provided, design for embedding in subject content (the most sustainable approach).
**Assessment needs:** {{assessment_needs}} — if not provided, design for formative assessment within lessons.
Return your output in this exact format:
## Competency Translation: [Framework — Competency Name]
**Framework:** [Which framework]
**Competency:** [Official name and reference]
**Translated for:** [Subject, year group, context]
### Original Framework Wording
[The official competency descriptor as written in the framework — or your best interpretation if not provided]
### Translation: What This Means in [Subject] for [Year Group]
[Plain-English translation: what this competency actually requires students to do in this specific subject and age group]
### Observable Indicators
For each level (3–4 levels):
**Level [N]: [Label — Emerging / Developing / Competent / Extending]**
- **The student can:** [Specific, observable actions — what you'd SEE them doing]
- **Evidence looks like:** [What their work, discussion, or behaviour would show]
- **The student cannot yet:** [What distinguishes this level from the next]
### Classroom Tasks
For each task (2–3):
**Task [N]: [Name]**
- **What students do:** [The task]
- **Why this task requires the competency:** [How it makes the competency visible]
- **What to look for:** [Observable indicators that the competency is being demonstrated]
### Assessment Criteria
[How to assess whether students are developing the competency — linked to the observable indicators at each level]
### Integration Notes
[How to embed this competency into existing subject teaching without creating a separate "competency lesson"]
### Framework Fidelity Check
[How well this translation represents the original framework intention — any interpretive choices made and why]
**Self-check before returning output:** Verify that (a) every indicator is observable — you can see or hear it, (b) progression levels are qualitatively distinct, (c) the translation is specific to the stated subject and year group, (d) tasks require the competency (it's not optional), (e) the translation is honest about any ambiguity in the original framework, and (f) integration is practical — embeddable in existing teaching.
Scenario: Framework reference: "DigComp 2.2 — Competency 1.2: Evaluating data, information and digital content. At proficiency level 3 (intermediate): 'Can compare and critically evaluate the credibility and reliability of specific sources of data, information and digital content'" / Target context: "Year 9 History — students are researching the causes of WW1 using online sources. The teacher wants students to evaluate the credibility of the websites and sources they find, rather than simply copying from the first Google result." / Subject area: "History" / Integration approach: "Embedded in the WW1 research unit — not a standalone digital literacy lesson"
Framework: DigComp 2.2 (European Digital Competence Framework) Competency: 1.2 — Evaluating data, information and digital content (Proficiency Level 3) Translated for: Year 9 History — evaluating online sources about the causes of WW1
"At proficiency level 3 (intermediate): Can compare and critically evaluate the credibility and reliability of specific sources of data, information and digital content." (European Commission, 2022)
In Year 9 History, this means: when students research a historical topic online, they can evaluate whether a website or digital source is credible and reliable for historical purposes — checking who wrote it (and whether they have expertise), when it was published (and whether it's current), what evidence it cites (and whether the claims are supported), and whether it has a bias or purpose that affects its reliability. This is not a generic digital literacy skill — it is SOURCE EVALUATION as historians practise it, applied to digital sources. Historians ask: Who produced this? Why? What evidence supports it? Does it agree or disagree with other sources? Students should apply the same questions to websites.
Level 1: Emerging — Recognises that source credibility matters
Level 2: Developing — Identifies basic credibility markers
Level 3: Competent — Evaluates and compares sources
Level 4: Extending — Critically evaluates credibility, bias, and purpose
Task 1: Source Showdown
Task 2: The Research Log
Task 3: Fact-Check Challenge
| Criterion | Emerging | Developing | Competent | Extending |
|---|---|---|---|---|
| Identifies source characteristics | Distinguishes source types (blog, news, academic) | Names the source type and checks for author/evidence | Evaluates credibility based on author, evidence, and purpose | Analyses how purpose and audience shape the source's content |
| Compares sources | Recognises that sources may differ | Notes that different sources say different things | Ranks sources by reliability with specific reasons | Cross-references claims across multiple sources to identify consensus and disagreement |
| Detects bias | Understands that sources can be biased | Recognises obvious bias ("This is one-sided") | Identifies how bias affects specific claims ("This source blames Germany because...") | Explains how even balanced sources involve selection and framing |
| Uses evaluation in own work | Includes sources but does not evaluate them | Cites sources with basic credibility notes | Selects sources based on credibility and notes limitations | Integrates source evaluation into their argument ("According to the more reliable Source A...") |
This competency should NOT be taught as a standalone "digital literacy" lesson disconnected from History. Instead:
The competency is developed THROUGH the subject content, not alongside it. Students learn to evaluate digital sources because they need to — they're researching WW1 and need reliable information. The digital competency and the historical skill reinforce each other.
The DigComp 2.2 descriptor at Level 3 ("can compare and critically evaluate the credibility and reliability of specific sources") is faithfully represented in this translation, with the following contextualisation:
The translation is faithful to the DigComp intent but specific to the History classroom. A different subject would produce a different translation of the same competency.
Competency frameworks are updated regularly. DigComp has moved from 1.0 to 2.2; GreenComp is relatively new; UNESCO AI guidance will evolve. The translation is based on the current framework version — teachers should check that they're working with the most recent version and adapt if descriptors have changed.
Some frameworks are deliberately vague. Framework descriptors are written for multiple contexts (primary, secondary, vocational, adult education) and multiple countries. This generality is a feature, not a bug — but it means that translation inevitably involves interpretation. This skill is transparent about interpretive choices, but teachers should verify that the translation aligns with their school's or system's interpretation of the framework.
Competency frameworks are not curricula. A competency framework describes what students should be able to do but not how to teach it, when to teach it, or how to assess it. The translation provides these elements, but they are pedagogical decisions informed by the framework, not dictated by it. Teachers should adapt the tasks and criteria to fit their specific curriculum and students.
Not all frameworks are equally well-evidenced. DigComp and GreenComp are policy frameworks developed through stakeholder consultation, not through educational research trials. The competencies they describe are reasonable and important, but their specific descriptors and proficiency levels are not empirically validated in the way that, say, Hattie's effect sizes are. Teachers should treat framework descriptors as useful organising structures, not as scientifically established learning progressions.