AI-Enabled Plant Recognition for Business Plan Writing in Vocational Agribusiness
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Abstract
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.
References
1
[1] O. Zawacki-Richter, V. I. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education—Where are the educators?,” International Journal of Educational Technology in Higher Education, vol. 16, Art. no. 39, 2019. https://doi.org/10.1186/s41239-019-0171-0
2
[2] G.-J. Hwang, H. Xie, B. W. Wah, and D. Gašević, “Vision, challenges, roles and research issues of artificial intelligence in education,” Computers and Education: Artificial Intelligence, vol. 1, Art. no. 100001, 2020. https://doi.org/10.1016/j.caeai.2020.100001
3
[3] F. Ouyang and P. Jiao, “Artificial intelligence in education: The three paradigms,” Computers and Education: Artificial Intelligence, vol. 2, Art. no. 100020, 2021. https://doi.org/10.1016/j.caeai.2021.100020
4
[4] F. Kamalov, J. Santandreu Calonge, and L. Gurrib, “New era of artificial intelligence in education: Towards a sustainable multifaceted revolution,” Sustainability, vol. 15, no. 16, Art. no. 12451, 2023. https://doi.org/10.3390/su151612451
5
[5] D. T. K. Ng, J. K. L. Leung, S. K. W. Chu, and M. S. Qiao, “Conceptualizing AI literacy: An exploratory review,” Computers and Education: Artificial Intelligence, vol. 2, Art. no. 100041, 2021. https://doi.org/10.1016/j.caeai.2021.100041
6
[6] D. Long and B. Magerko, “What is AI literacy? Competencies and design considerations,” in Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 2020, pp. 1–16. https://doi.org/10.1145/3313831.3376727
7
[7] S. Akgün and C. Greenhow, “Artificial intelligence in education: Addressing ethical challenges in K–12 settings,” AI and Ethics, vol. 2, pp. 431–440, 2022. https://doi.org/10.1007/s43681-021-00096-7
8
[8] Y.-T. Sung, K.-E. Chang, and T.-C. Liu, “The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis,” Computers & Education, vol. 94, pp. 252–275, 2016. https://doi.org/10.1016/j.compedu.2015.11.008
9
[9] W.-H. Wu, Y.-C. J. Wu, C.-Y. Chen, H.-Y. Kao, C.-H. Lin, and S.-H. Huang, “Review of trends from mobile learning studies: A meta-analysis,” Computers & Education, vol. 59, no. 2, pp. 817–827, 2012. https://doi.org/10.1016/j.compedu.2012.03.016
10
[10] G.-J. Hwang and C.-C. Tsai, “Research trends in mobile and ubiquitous learning: A review of publications in selected journals from 2001 to 2010,” British Journal of Educational Technology, vol. 42, no. 4, pp. E65–E70, 2011. https://doi.org/10.1111/j.1467-8535.2011.01183.x
11
[11] A. Ancheta-Arrabal et al., “Gender digital divide and education in Latin America,” Education Sciences, vol. 11, no. 12, Art. no. 804, 2021. https://doi.org/10.3390/educsci11120804
12
[12] OECD, OECD Digital Education Outlook 2023: Towards an Effective Digital Education Ecosystem. Paris, France: OECD Publishing, 2023. https://doi.org/10.1787/c74f03de-en
13
[13] H. G. Jones, “What plant is that? Testing automated image recognition apps for identification of plants,” AoB Plants, vol. 12, no. 5, Art. no. plaa052, 2020. https://doi.org/10.1093/aobpla/plaa052
14
[14] P. Mäder et al., “The iNaturalist species classification and detection dataset,” Scientific Data, vol. 8, Art. no. 126, 2021. https://doi.org/10.1038/s41597-021-00937-2
15
[15] J. Wäldchen and P. Mäder, “Plant species identification using computer vision techniques: A systematic literature review,” Archives of Computational Methods in Engineering, vol. 25, pp. 507–543, 2018. https://doi.org/10.1007/s11831-016-9206-z
16
[16] Nuraini et al., “Identification of ornamental plants via Google Lens based on intersemiotic,” Jurnal Penelitian Pendidikan IPA, vol. 8, no. 3, pp. 1260–1266, 2022. https://doi.org/10.29303/jppipa.v8i3.1627
17
[17] Rahman et al., “Plant species identification using Google Lens and its effect on science learning outcomes among students of SMP Negeri 11 Maros Baru,” Genius: Jurnal Ilmiah Pendidikan, vol. 2, no. 2, 2024. https://doi.org/10.58227/gjipp.v2i2.178
18
[18] S. R. A. Sofian, W. Subchan, and S. Sudarti, “Penerapan model discovery learning berbantuan Google Lens untuk meningkatkan aktivitas dan hasil belajar siswa pada materi klasifikasi makhluk hidup,” Jurnal Teknologi Pendidikan, vol. 11, no. 2, pp. 176–189, 2022. https://doi.org/10.32832/tek.pend.v11i2.5972
19
[19] E. S. Mwasalwiba, “Entrepreneurship education: A review of its objectives, teaching methods, and impact indicators,” Education + Training, vol. 52, no. 1, pp. 20–47, 2010. https://doi.org/10.1108/00400911011017663
20
[20] H. M. Neck and P. G. Greene, “Entrepreneurship education: Known worlds and new frontiers,” Journal of Small Business Management, vol. 49, no. 1, pp. 55–70, 2011. https://doi.org/10.1111/j.1540-627X.2010.00314.x
21
[21] B. C. Martin, J. J. McNally, and M. J. Kay, “Examining the formation of human capital in entrepreneurship: A meta-analysis of entrepreneurship education outcomes,” Journal of Business Venturing, vol. 28, no. 2, pp. 211–224, 2013. https://doi.org/10.1016/j.jbusvent.2012.03.002
22
[22] T. J. Bae, S. Qian, C. Miao, and J. O. Fiet, “The relationship between entrepreneurship education and entrepreneurial intentions: A meta-analytic review,” Entrepreneurship Theory and Practice, vol. 38, no. 2, pp. 217–254, 2014. https://doi.org/10.1111/etap.12095
23
[23] A. Fayolle and B. Gailly, “The impact of entrepreneurship education on entrepreneurial attitudes and intention: Hysteresis and persistence,” Journal of Small Business Management, vol. 53, no. 1, pp. 75–93, 2015. https://doi.org/10.1111/jsbm.12065
24
[24] A. Rauch and W. Hulsink, “Putting entrepreneurship education where the intention to act lies: An investigation into the impact of entrepreneurship education on entrepreneurial behavior,” Academy of Management Learning & Education, vol. 14, no. 2, pp. 187–204, 2015. https://doi.org/10.5465/amle.2012.0293
25
[25] G. Nabi, F. Liñán, A. Fayolle, N. Krueger, and A. Walmsley, “The impact of entrepreneurship education in higher education: A systematic review and research agenda,” Academy of Management Learning & Education, vol. 16, no. 2, pp. 277–299, 2017. https://doi.org/10.5465/amle.2015.0026
26
[26] D. B. Rideout and D. O. Gray, “Does entrepreneurship education really work? A review and methodological critique of the empirical literature on the effects of university-based entrepreneurship education,” Journal of Small Business Management, vol. 51, no. 3, pp. 329–351, 2013. https://doi.org/10.1111/jsbm.12021
27
[27] K. Fellnhofer, “The effects of entrepreneurship education: Evidence from a systematic literature review,” Educational Research Review, vol. 25, pp. 1–17, 2019. https://doi.org/10.1016/j.edurev.2018.10.002
28
[28] S. Göksen-Olgun, W. Groot, and I. Wakkee, “Entrepreneurship programs and their underlying pedagogy in secondary education in the Netherlands,” Entrepreneurship Education, vol. 5, pp. 261–287, 2022. https://doi.org/10.1007/s41959-022-00078-8
29
[29] A. Mack et al., “Entrepreneurial knowledge and skill exposure in vocational education: Development of a new assessment scale,” Discover Education, vol. 4, Art. no. 45, 2025. https://doi.org/10.1007/s44217-024-00331-3
30
[30] P. Guo, N. Saab, L. S. Post, and W. Admiraal, “A review of project-based learning in higher education: Student outcomes and measures,” International Journal of Educational Research, vol. 102, Art. no. 101586, 2020. https://doi.org/10.1016/j.ijer.2020.101586
31
[31] B. J. Zimmerman, “Becoming a self-regulated learner: An overview,” Theory Into Practice, vol. 41, no. 2, pp. 64–70, 2002. https://doi.org/10.1207/S15430421TIP4102_2
32
[32] E. Panadero, “A review of self-regulated learning: Six models and four directions for research,” Frontiers in Psychology, vol. 8, Art. no. 422, 2017. https://doi.org/10.3389/fpsyg.2017.00422
33
[33] M. A. Camilleri and A. C. Camilleri, “The students’ perceived use, usefulness and satisfaction with the use of learning management systems: The case of business education,” International Journal of Information and Learning Technology, vol. 36, no. 5, pp. 441–459, 2019. https://doi.org/10.1108/IJILT-08-2019-0090
34
[34] L. Li et al., “Does team cooperation matter? The impact of team cooperation on student learning outcomes in project-based learning,” Educational Studies, vol. 50, no. 4, pp. 507–524, 2024. https://doi.org/10.1080/03055698.2022.2041489
35
[35] S. Haq, N. Jalinus, and M. Giatman, “Entrepreneurship project-based practical learning model: Development and implementation,” TEM Journal, vol. 13, no. 3, pp. 2418–2428, 2024. https://doi.org/10.18421/TEM133-69
36
[36] D. Lakens, “Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs,” Frontiers in Psychology, vol. 4, Art. no. 863, 2013. https://doi.org/10.3389/fpsyg.2013.00863
37
[37] K. S. Taber, “The use of Cronbach’s alpha when developing and reporting research instruments in science education,” Research in Science Education, vol. 48, pp. 1273–1296, 2018. https://doi.org/10.1007/s11165-016-9602-2
38
[38] A. Ghasemi and S. Zahediasl, “Normality tests for statistical analysis: A guide for non-statisticians,” International Journal of Endocrinology and Metabolism, vol. 10, no. 2, pp. 486–489, 2012. https://doi.org/10.5812/ijem.3505
Author Biographies
Ayyid Sur’ataini
Department of Master of Pedagogy
Arina Restian
Department of Master of Pedagogy
Husamah
Department of Master of Pedagogy
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Copyright (c) 2026 Ayyid Sur’ataini, Arina Restian, Husamah
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2026-06-26
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