Transparency
Last updated: September 2026 · Pre-release (n < 500)
This manual documents the psychometric properties of the TalentPath DigComp 3.0 assessment. Several sections require live data from enough completions to be statistically meaningful. Until at least 500 complete sessions are recorded, those sections show the planned analyses rather than results. Each section states whether it reports live data or a prospectus.
See also: Methodology
The TalentPath DigComp 3.0 assessment issues verifiable credentials that attest to digital competence levels. Any credential that carries consequences — for hiring, compliance, or self-development — owes its audience evidence that the underlying test measures what it claims, does so consistently, and treats candidates fairly.
This manual is that evidence. It follows the reporting framework of the Standards for Educational and Psychological Testing(AERA, APA, & NCME, 2014) and the European Guidelines on Computer-Based and Online Assessment(ATP/E-ATP, 2023). Where the assessment is still below the sample size needed for a given analysis, the section describes the planned method instead.
The construct is digital competence as defined by DigComp 3.0 (Vuorikari et al., 2022; updated November 2025) — the five competence areas recognised by the EU Joint Research Centre and used by Europass and national education systems across all 27 member states.
Each of the five areas is assessed independently. A candidate may sit any subset. 12 items are drawn per area from the item bank, with stratified sampling so that every competence within the area is represented. Total test length for all five areas is 60 items.
| Area | Items drawn | Item types |
|---|---|---|
| Information and Data Literacy | 12 | Know, Judge |
| Communication and Collaboration | 12 | Know, Judge |
| Digital Content Creation | 12 | Know, Judge |
| Safety and Wellbeing | 12 | Know, Judge |
| Problem Solving | 12 | Know, Judge |
Items are authored in a structured YAML format and validated by a build-time linter that enforces the DigComp 3.0 taxonomy, correct answer coding, and test-wiseness rules (no absolute language in distractors, no “all of the above”, stem length and readability checks). Items that fail the linter cannot ship.
Each item is tagged with its DigComp area, competence, proficiency level band (Foundation / Intermediate / Advanced), and question type (Know or Judge). Option order is randomised per candidate using a session-derived shuffle key, and the answer key is never sent to the browser.
Scoring uses conjunctive banding: a level is awarded only when the candidate meets both a global threshold and a per-area minimum. This prevents strength in one area from compensating for absence in another.
| Level | Overall minimum | Per-area minimum |
|---|---|---|
| Basic | 50% | 40% |
| Intermediate | 70% | 60% |
| Advanced | 85% | 75% |
Levels 7–8 of DigComp (“Highly advanced”) are never awarded: they describe creating practice that a professional field adopts, which an unsupervised multiple-choice test cannot observe. A 24-hour cooldown between attempts discourages guessing.
Awaiting data (n < 500)
Once at least 500 complete sessions are recorded, this section will report classical item statistics for each item in the bank:
Items with p < 0.20 or p > 0.95 will be reviewed for floor/ceiling effects. Items with rpbis < 0.15 will be reviewed for weak discrimination or possible miskeying.
Awaiting data (n < 500)
Reliability evidence will be reported as:
Until n ≥ 500, the thresholds are set from published comparators and expert judgement. The methodology page states this openly.
Awaiting data (n < 500)
The current cut scores (50/40, 70/60, 85/75) are provisional, set by anchoring to DigComp proficiency level descriptors and published digital literacy assessment benchmarks. A formal standard-setting study is planned once item statistics stabilise:
Awaiting data (n < 500)
Differential Item Functioning (DIF) analysis will flag items that perform differently across demographic groups (where candidates have consented to provide that information):
The assessment is delivered in English only. Items avoid culture-specific references (UK tax forms, US healthcare terminology) and use EU-neutral scenarios. Option order is randomised per candidate to eliminate position bias.
The following limitations are inherent to the current assessment design and are stated openly: