01/08/2026
๐๐พ๐ฐ๐พ๐ผ๐ฝ ๐ท๐ช! Start na naman ng research season!
Habang sinisimulan nyong buuin ang methodology, isa sa mga unang dapat linawin ay kung ano nga ba ang tamang research design para sa inyong study? Experimental, quasi-experimental, o non-experimental? ๐ค
๐๐ซ๐ฃ๐๐ฅ๐๐ ๐๐ก๐ง๐๐, ๐ค๐จ๐๐ฆ๐-๐๐ซ๐ฃ๐๐ฅ๐๐ ๐๐ก๐ง๐๐, ๐ข๐ฅ ๐ก๐ข๐ก-๐๐ซ๐ฃ๐๐ฅ๐๐ ๐๐ก๐ง๐๐?
These research designs differ primarily in whether an intervention is introduced and whether the participants or other study units are randomly assigned to conditions (Shadish et al., 2002).
๐ฌ ๐๐ฑ๐ฉ๐๐ซ๐ข๐ฆ๐๐ง๐ญ๐๐ฅ ๐๐๐ฌ๐ข๐ ๐ง
In a true experimental design, the researcher introduces an intervention or manipulates an independent variable and randomly assigns participants to comparison groups. This reduces selection bias and strengthens the basis for determining whether the intervention caused the observed outcome (Shadish et al., 2002).
Example: Gustong i-test ng researcher kung effective ba ang isang bagong teaching method. Random niyang ia-assign ang students sa dalawang groups: one group will use the new method, while the other will use the usual method. Afterward, iko-compare niya ang test scores ng dalawang groups.
โ๏ธ ๐๐ฎ๐๐ฌ๐ข-๐๐ฑ๐ฉ๐๐ซ๐ข๐ฆ๐๐ง๐ญ๐๐ฅ ๐๐๐ฌ๐ข๐ ๐ง
A quasi-experimental design tests an intervention without randomly assigning participants to study conditions. It may use existing groups, pretests and posttests, comparison groups, or repeated measurements. Since there is no random assignment, the groups may already differ before the intervention, but these methods can help strengthen the studyโs validity (Capili & Anastasi, 2024; Shadish et al., 2002).
Example: Gustong i-test ng researcher kung effective ba ang isang wellness program sa pagpapababa ng stress ng employees. I-implement niya ang program sa isang existing department, while another department will continue with its usual routine. Since hindi random ang pag-assign ng participants sa conditions, quasi-experimental ang design.
๐ ๐๐จ๐ง-๐๐ฑ๐ฉ๐๐ซ๐ข๐ฆ๐๐ง๐ญ๐๐ฅ ๐๐๐ฌ๐ข๐ ๐ง
In a non-experimental design, the researcher observes and measures variables as they naturally occur without introducing an intervention or manipulating the study conditions. It can describe characteristics, examine relationships, make predictions, or compare naturally existing groups, but it cannot directly establish cause and effect (Creswell & Creswell, 2023; Shadish et al., 2002).
Example: Gustong alamin ng researcher kung may relationship ba ang social media use at stress level ng students. Magko-collect lang siya ng data tungkol sa screen time at stress level nila without changing their routine or introducing any program. Since observation and measurement lang ang ginawa, non-experimental ang design.
๐๐ช๐๐๐ ๐๐ช๐๐๐
โ
Intervention with random assignment to study conditions โ Experimental
โ
Intervention without random assignment to study conditions โ Quasi-experimental
โ
No intervention or manipulation; variables are only observed or measured โ Non-experimental
Note: Magkaiba ang random assignment at random sampling. Sa random assignment, ang participants ay randomly inilalagay sa treatment or comparison groups. Sa random sampling naman, random ang paraan ng pagpili kung sino ang sasali sa study.
Also, hindi porke may pretest at posttest, quasi-experimental na agad ang design. Dapat may intervention or treatment na tine-test ang researcher.
๐๐ฐ๐ต ๐ด๐ถ๐ณ๐ฆ ๐ธ๐ฉ๐ช๐ค๐ฉ ๐ณ๐ฆ๐ด๐ฆ๐ข๐ณ๐ค๐ฉ ๐ฅ๐ฆ๐ด๐ช๐จ๐ฏ ๐ช๐ด ๐ข๐ฑ๐ฑ๐ณ๐ฐ๐ฑ๐ณ๐ช๐ข๐ต๐ฆ ๐ง๐ฐ๐ณ ๐บ๐ฐ๐ถ๐ณ ๐ด๐ต๐ถ๐ฅ๐บ? ๐๐ฆ๐ฏ๐ฅ ๐ถ๐ด ๐บ๐ฐ๐ถ๐ณ ๐ณ๐ฆ๐ด๐ฆ๐ข๐ณ๐ค๐ฉ ๐ฐ๐ฃ๐ซ๐ฆ๐ค๐ต๐ช๐ท๐ฆ๐ด ๐ข๐ฏ๐ฅ ๐ฑ๐ณ๐ฐ๐ฑ๐ฐ๐ด๐ฆ๐ฅ ๐ฎ๐ฆ๐ต๐ฉ๐ฐ๐ฅ๐ฐ๐ญ๐ฐ๐จ๐บ ๐ด๐ฐ ๐ธ๐ฆ ๐ค๐ข๐ฏ ๐ข๐ด๐ด๐ฆ๐ด๐ด ๐ต๐ฉ๐ฆ ๐ข๐ฑ๐ฑ๐ณ๐ฐ๐ฑ๐ณ๐ช๐ข๐ต๐ฆ ๐ฅ๐ฆ๐ด๐ช๐จ๐ฏ ๐ข๐ฏ๐ฅ ๐ด๐ต๐ข๐ต๐ช๐ด๐ต๐ช๐ค๐ข๐ญ ๐ข๐ฏ๐ข๐ญ๐บ๐ด๐ช๐ด.
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References:
Capili, B., & Anastasi, J. K. (2024). An introduction to types of quasi-experimental designs. American Journal of Nursing, 124(11), 50โ52. https://doi.org/10.1097/01.NAJ.0001081740.74815.20
Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin.
