The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Why Triangulate?
Abstract
This article discusses triangulation as a strategy for increasing the validity of evaluation and research findings. Typically, through triangulating we expect various data sources and methods to lead to a singular proposition about the phenomenon being studied. That this is not the case is obvious to most researchers and evaluators. Given that this expectation is unrealistic, an alternative perspective of triangulation is presented. This alternative perspective takes into account that triangulation results in convergent, inconsistent, and contradictory evidence that must be rendered sensible by the researcher or evaluator.
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Using multiple forms of data across the three campuses to deepen understanding of the ways the PLCs facilitated culture change increased the credibility and confirmability of the findings.
“Furthermore, using multiple forms of data across the three campuses to deepen our understanding of the ways the PLCs facilitated culture change which increased the credibility and confirmability of our findings (Lincoln & Guba, 1986;Mathison, 1988).”
From Moving Toward Institutional Culture Change in Higher Education: An Exploration into Cross-functional Professional Learning Communities (2025) · cites this paper as Mathison, 1988
Citations
Cites
Convergent and discriminant validation by the multitrait-multimethod matrix.
Campbell, D. T., & Fiske, D. W. (1959) · Psychological Bulletin · doi:10.1037/h0046016 · Cited by 17,116
Flagged first, then by citations
Research works printed but not linked: 11
- DenzinNKThe research actA theoretical introduction to sociological methods1978New YorkMcGraw-Hill
- EisnerEWThe educational imagination1979New YorkMacmillan
- GubaEGLincolnYSEffective evaluation1981San FranciscoJossey-Bass
- HouseEREvaluating with validity1980Beverly HillsSage
- JickTDVan MaanenJMixing qualitative and quantitative methods: Triangulation in actionQualitative methods1983Beverly HillsSage
- 10.1177/000276482026001009 · DOI
- MilesMBHubermanAMQualitative data analysis1984Beverly HillsSage
- PattonMQQualitative evaluation methods1980Beverly HillsSage
- 10.1177/016146817207300505 · DOI
- 10.1002/ev.1426 · DOI
- WebbEJCampbellDTSchwartzRDSechrestLUnobtrusive measures1966ChicagoRand McNally
Cited by
Sorted by citations
Toward a Conceptual Framework for Mixed-Method Evaluation Designs
Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989) · Educational Evaluation and Policy Analysis · doi:10.3102/01623737011003255 · Cited by 5,687
How to Construct a Mixed Methods Research Design
Schoonenboom, J., & Johnson, R. B. (2017) · KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie · doi:10.1007/s11577-017-0454-1 · Cited by 1,757
Triangulation in aetiological epidemiology
Lawlor, D. A., Tilling, K., & Davey Smith, G. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyw314 · Cited by 1,129
Validity in qualitative research revisited
Cho, J., & Trent, A. (2006) · Qualitative Research · doi:10.1177/1468794106065006 · Cited by 1,037
Food waste management innovations in the foodservice industry
Martin-Rios, C., Demen-Meier, C., Gössling, S., & Cornuz, C. (2018) · Waste Management · doi:10.1016/j.wasman.2018.07.033 · Cited by 386
Kezar, A., Hallett, R. E., Corwin, Z. B., & Hypolite, L. (2025) · Innovative Higher Education · doi:10.1007/s10755-024-09753-1 · Cited by 50
Menstrual problems and health seeking in Sri Lanka
Hemachandra, D. K. N. N., & Manderson, L. (2009) · Women & Health · doi:10.1080/03630240903238636 · Cited by 11
Metadata
- Authors
- Mathison, S.
- Venue
- Educational Researcher
- Published
- 1988-03
- Volume
- 17
- Issue
- 2
- Pages
- 13-17
- ISSN
- 0013-189X
- 1935-102X
- Cited by
- 762
- References
- 1
- Language
- en
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