Trend analysis for digital inclusion

Evidence concerning digital inclusion should inform action without implying a level of precision, coverage or causal certainty that the underlying data cannot support. The relevant concern is the effect of consequential decisions on learners, institutions and resources entrusted for education.

Implementation of the available evidence should be organised around a decision that can be tested. For trend analysis for digital inclusion, a sound interpretation should identify the unit of analysis, reference period, denominator, exclusions, missing values and any change in definition or collection practice.

Application to trend analysis for digital inclusion

Its relevance to digital inclusion should be assessed against the affected jurisdiction, learner population and form of provision.

Review of the analysis should follow a stated and reproducible method. The analysis proceeds on the basis that trend analysis depends on stable definitions and repeated observation of comparable populations. For digital inclusion, a change in policy, coverage or recording practice can create an apparent movement that is not a change in the underlying educational condition.

The principal risks in relation to the comparison are assessment methods that do not support valid judgements, reduced opportunities for timely support, technology access determining educational access, and supplier dependency without continuity controls. In the context of digital inclusion, the risks are connected, and failure of one safeguard may disable or conceal another.

Relevant evidence for the measure will normally include service availability and incident records, assessment validity and integrity reviews, supplier performance and exit arrangements, accessibility and usability testing, and learner access and participation information.

Controls for trend analysis for digital inclusion

The review method for digital inclusion should be reproducible. The method for the measure is to establish a baseline, annotate every material change in definition or collection, compare like periods and retain revised series. Where comparability is interrupted, begin a new series or present the break clearly rather than joining unlike observations. Across the defined scope, a competent reviewer should be able to follow the record from source selection to conclusion and exception handling.

• Is the baseline still comparable?
• Have coverage or definitions changed?
• Were earlier values revised?
• Is the period long enough to show sustained movement?
• What external condition may explain the change?

Review of trend analysis for digital inclusion

Decision-makers using evidence on the analysis should be told what the data cannot establish as clearly as what it can. For digital inclusion, the finding should identify its analytical character and the system, institution, programme or learner population to which it applies.

• Support staff and learners before it informs a consequential decision.
• Define the educational purpose of the technology.
• Assure assessment validity.
• Provide alternative routes for material barriers before it is relied on for a decision with material effect.
• Test access before requiring use.

Implications for trend analysis for digital inclusion

For decisions concerning trend analysis for digital inclusion, the relevant outcome should be capable of direct and consistent explanation. A change in delivery mode should not weaken the defined learning outcomes, learner protection, accessibility or reliability of assessment.

Across the defined scope, analysis should remain within the limits of the evidence. For trend analysis for digital inclusion, missing or delayed information may be patterned rather than random.

When examining trend analysis for digital inclusion, progress should not be assessed by the amount of policy or documentation produced.