So sánh phương pháp

	Đánh giá chương trình số	Phân tích Nội dung Số
Lĩnh vực	Phương pháp thực địa	Định tính
Họ	Process / pipeline	Process / pipeline
Năm ra đời	2000s–2010s (formalized alongside proliferation of digital programs and online data)	1950s (classical); digital adaptation 2000s–2010s
Người khởi xướng	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+)
Loại	Applied evaluation methodology	Qualitative/quantitative hybrid research approach
Công trình gốc	George, S., & Leidner, D. (2020). Digital Evaluation: Leveraging Digital Data and Methods for Program Assessment. Routledge.	Neuendorf, K. A. (2017). The Content Analysis Guidebook (2nd ed.). Sage. ISBN: 978-1412979474
Tên gọi khác	technology-enhanced evaluation, digital evaluation, e-evaluation, online program evaluation	DCA, online content analysis, web content analysis, digital media content analysis
Liên quan	5	4
Tóm tắt	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.