OER·harvester

Competency catalogue

The 104 active T2.3 competencies: the vocabulary the harvester searches with, the descriptor the alignment reads, and what the alignment found. Compose a harvest →

What the alignment foundHow often each was searched

How many resources the alignment reads as contributing to each competency or developing it: decided at level 2 or 3, or not decided yet and more likely than not to reach 2. 54 competencies have none, 24 one or two. Every figure is a lower bound: on a sample graded on every competency, the map counts 33% of what was graded 2 or 3, and almost nothing of the 5 competencies underlined with dots.

How many times a harvest has searched for each competency, once for each source it asked. 101 competencies have never been searched. A search is not material found: the aligned view says what came of it.

none 1–2 3–9 10–29 30+
never 1–2 3–5 6–11 12+
DDigital 94212203420012149086012303134 GGreen 0000000102000010000100010 RResilience & Entrepreneurial 004000000000000010000120000 TDeep Tech 72643202372825212335201140010

T23 Deep Tech · Skill · Advanced

AI Research Methodology

Conduct systematic research on AI topics

Alignment

0 resources likely to contribute to it or develop it

None found yet in what the alignment has read.

What the map misses here is not measured: the graded sample holds no pair graded 2 or 3 for it.

Retrieval

0 resources harvested by searching its terms

Never searched yet.

Search vocabulary

Domain group
AI research methodologysystematic literature reviewmachine learning experimentresearch designreproducible AI researchempirical AI studyexperimental methodology

Zenodo and arXiv take the whole group in one query. GitHub takes one phrase at a time and works left to right, stopping once the competency is satisfied — so on that lane this order decides which terms actually run.

The compiled queries
zenodo ("artificial intelligence" OR "machine learning" OR "generative AI" OR "deep learning" OR "reinforcement learning" OR "large language model" OR "AI") AND ("AI research methodology" OR "systematic literature review" OR "machine learning experiment" OR "research design" OR "reproducible AI research" OR "empirical AI study" OR "experimental methodology")
arxiv (all:"artificial intelligence" OR all:"machine learning" OR all:"generative AI" OR all:"deep learning" OR all:"reinforcement learning" OR all:"large language model") AND (all:"AI research methodology" OR all:"systematic literature review" OR all:"machine learning experiment" OR all:"research design" OR all:"reproducible AI research" OR all:"empirical AI study" OR all:"experimental methodology")
github · term 1 AI "AI research methodology" in:name,description,readme fork:false archived:false
github · term 2 AI "systematic literature review" in:name,description,readme fork:false archived:false
github · term 3 AI "machine learning experiment" in:name,description,readme fork:false archived:false
github · term 4 AI "research design" in:name,description,readme fork:false archived:false
github · term 5 AI "reproducible AI research" in:name,description,readme fork:false archived:false
github · term 6 AI "empirical AI study" in:name,description,readme fork:false archived:false
github · term 7 AI "experimental methodology" in:name,description,readme fork:false archived:false

Profile b06382cf818b36ee

Alignment descriptor draft

Outcomes
  • Can design and conduct a systematic study of an AI topic.
  • Can run reproducible experiments and report them.
  • Can review the literature systematically.
Develops it

Material on AI research methodology — research questions, experimental design, reproducibility, literature reviews — with practice.

Only mentions it

A research paper, which applies a methodology without teaching it.

Alignment terms
research methodologysystematic reviewexperimental designreproducible researchablation studyresearch question

Read in a resource's text beside the domain group. They are never compiled into a search.

Neighbours

Descriptor 8d6b130e00ff

How a vocabulary becomes a search

Every candidate must match both concept groups in its title, description or keywords before any content is downloaded. Precision warnings are recorded for audit; they never silently cancel positive evidence.

  1. Official name and description
  2. AI/ML terms and domain terms
  3. Zenodo, arXiv and GitHub syntax
  4. Metadata relevance gate
Mandatory AI/ML group
artificial intelligencemachine learninggenerative AIdeep learningreinforcement learninglarge language modelAI

GitHub's repository search takes one phrase at a time. Measured against the live endpoint, a parenthesised OR group returns nothing at all where each term alone returns thousands, and the 256-character limit rejects a long group outright — so that lane issues one query per term and stops as soon as the competency is satisfied.

coverage-vocabulary-1.3.0+sha256:08ad2cd19868 · catalogue sha256:04970bfc77255b1f

What a descriptor is

A descriptor is how the alignment reads a competency: what a learner who has it can do, what a resource has to do to develop it, what only mentions it, the phrases its subject is written in, its false friends, and how to tell it from the competencies that share its words. The definition above it stays the authority.

Every descriptor is a draft until a partner approves it; 0 of 104 are approved. Read the alignment rubric →

competency-descriptors-1.0.0+sha256:3cc741a61ced