AI-Enabled Plant Recognition for Business Plan Writing in Vocational Agribusiness - Ayyid Sur’ataini; Arina Restian; Husamah (Women, Education, and Social Welfare, 2026)
This study evaluated a Google Lens-supported learning sequence for improving ornamental-plant business plan writing in a public vocational high school in Indonesia. A quasi-experimental nonequivalent pretest-posttest control-group design compared 31 students who received smartphone-mediated plant recognition and teacher-guided data verification with 32 students who received conventional instruction. Performance tests and structured classroom observations were analyzed using descriptive statistics, assumption tests, an independent-samples t-test, and derived effect-size indicators. Baseline performance did not differ significantly (M = 52.66, SD = 10.68 versus M = 54.29, SD = 7.41; p = .482). The intervention group achieved a higher posttest score (M = 73.46, SD = 9.35) than the control group (M = 63.98, SD = 8.84), t(61) = 4.138, p < .001, mean difference = 9.48, 95% CI [4.90, 14.07], Hedges’ g = 1.03. Observations showed that the learning sequence supported product identification, market-oriented analysis, collaboration, and more independent evidence gathering. The contribution is a pedagogical model that moves image recognition beyond taxonomy by linking AI output to verification, business judgment, and written entrepreneurial planning.