| Focuses on objective methods oriented to the collection of “formal knowledge” as data, thereby producing: |
Focuses on naturalistic methods that may capture both formal and informal (tacit, embodied, practical) knowledge, and also co-create learning through dialogue between stakeholders, thereby producing: |
| • Quantitative estimates of the relationship between predefined input and output variables, and confidence intervals around these |
• Map of the different stakeholders and insights into their expectations, values, and framings of the program; illumination of who is accountable to whom |
| • Deconstruction of “context” to produce quantitative estimates and/or qualitative explanations of the effect of mediating and moderating variables on the relationship between input and output variables |
• Problematisation of “success”; insights into the struggle between stakeholder groups to define and judge success and whose voices are dominant in this struggle |
| • Judgement of the extent to which a program has achieved its original goals and the contribution of different elements in the original chain of reasoning to this |
• Illumination of how the eHealth technology exacerbates (or, perhaps, helps overcome) power differentials between different groups (e.g., through differential exposure to surveillance or access to data) |
| • Statistical generalisation, allowing prediction of how well a particular eHealth technology is likely to work in other contexts and settings |
• A rich, contextualised narrative that conveys the multiple perspectives on the program and its complex interdependencies and ambiguities• |
| • Quantification of how evaluators' formative feedback has influenced outcome |
Theoretical generalisation, allowing potentially transferable explanations of the dynamic and reciprocal relationship between macro-, meso-, and micro-level influences |
| • “Endpoint” knowledge with evaluation methods providing the means to the “end” of producing judgements in a final evaluation report |
• Reflections on how formative feedback and the relationship between evaluators and evaluands may have influenced the program, hence advice to future evaluators on how to manage these relationships |
| • Explanatory and predictive knowledge |
• Understanding and illumination |
