Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Tathmini ya Programu Dijitali× | Uchanganuzi wa Maudhui Dijitali× | |
|---|---|---|
| Nyanja≠ | Mbinu za Uwandani | Mbinu za Kimaelezo |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2000s–2010s (formalized alongside proliferation of digital programs and online data) | 1950s (classical); digital adaptation 2000s–2010s |
| Mwanzilishi≠ | Evolving practice; rooted in Rossi, Lipsey & Freeman's evaluation tradition; extended by digital methods scholars in the 2000s–2010s | Building on Berelson (1952) and Krippendorff (1980); adapted for digital contexts by Herring (2010) and Neuendorf (2002+) |
| Aina≠ | Applied evaluation methodology | Qualitative/quantitative hybrid research approach |
| Chanzo asilia≠ | George, S., & Leidner, D. (2020). Digital Evaluation: Leveraging Digital Data and Methods for Program Assessment. Routledge. link ↗ | Neuendorf, K. A. (2017). The Content Analysis Guidebook (2nd ed.). Sage. ISBN: 978-1412979474 |
| Majina mbadala | technology-enhanced evaluation, digital evaluation, e-evaluation, online program evaluation | DCA, online content analysis, web content analysis, digital media content analysis |
| Zinazohusiana≠ | 5 | 4 |
| Muhtasari≠ | Digital program evaluation applies the systematic logic of program evaluation to programs that operate fully or partly in digital environments, using digital tools and data — web analytics, online surveys, platform logs, social media metrics, and digital trace data — to assess program reach, implementation fidelity, and outcomes. It retains the core evaluative commitment to rendering a defensible judgment about program merit and worth while exploiting the speed, scale, and granularity that digital data sources offer. Applications span online education, digital public health campaigns, e-government services, and technology-mediated social programs. | Digital Content Analysis is a systematic research method for describing, categorising, and interpreting the content of digital materials — social media posts, websites, online forums, blogs, emails, and video transcripts. It applies the rigorous coding logic of classical content analysis to digitally native or digitally collected text, enabling researchers to move from raw online data to structured, interpretable findings about communication, meaning, and social phenomena. |
| ScholarGateSeti ya data ↗ |
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