Cerdas Menyusun Skripsi Kuantitatif Pendidikan Keteknikan di Era AI dan Teknologi Masa Depan
Keywords:
Kuantitatif, Pendidikan KeteknikanSynopsis
Buku ini membahas langkah-langkah penting dalam menyusun skripsi kuantitatif pada bidang pendidikan keteknikan. Pembahasan diawali dari pemahaman tentang desain penelitian, seperti penelitian korelasional, eksperimen, quasi eksperimen, ex post facto, dan survei. Setiap desain dijelaskan dengan contoh yang dekat dengan pendidikan teknik, seperti pembelajaran praktik, penggunaan media digital, simulasi, LMS, AI tutor, literasi digital, dan kesiapan kerja peserta didik.
Selanjutnya, buku ini menguraikan cara menentukan populasi, sampel, dan teknik sampling yang sesuai dengan karakteristik penelitian. Pembahasan juga dilanjutkan dengan penyusunan instrumen penelitian berbasis digital, mulai dari angket, tes, lembar observasi, rubrik praktik, dokumentasi nilai, hingga skala sikap. Buku ini menekankan pentingnya validitas, reliabilitas, kualitas data, dan etika penggunaan AI agar data yang dikumpulkan tetap akurat, jujur, dan layak dianalisis.
Pada bagian akhir, buku ini membahas teknik pengumpulan data, pengolahan data awal, statistik deskriptif, analisis inferensial, penyajian hasil, visualisasi digital, pembahasan, kesimpulan, implikasi, dan saran penelitian. Buku ini juga mengingatkan bahwa AI dapat membantu mahasiswa memahami konsep, merapikan bahasa, membaca output statistik, dan menyusun draf awal, tetapi keputusan ilmiah tetap berada di tangan peneliti. Dengan demikian, buku ini menjadi panduan praktis untuk menghasilkan skripsi kuantitatif pendidikan keteknikan yang sistematis, relevan, dan sesuai dengan kebutuhan era teknologi masa depan.
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Adeoye, M. A. (2023). Review of sampling techniques for education. ASEAN Journal for Science Education, 2(2), 87–94. https://www.ejournal.bumipublikasinusantara.id/index.php/ajsed/article/viewFile/230/214
Ahmad, N. A., Elias, N. F., Sahari, N., & Mohamed, H. (2023). Learning management system acceptance factors for technical and vocational education training (TVET) institutions. TEM Journal, 12(2), 1156–1165. https://doi.org/10.18421/TEM122-61
Ahmad, N., Alias, F. A., & Abdul Razak, N. A. (2023). Understanding population and sample in research: Key concepts for valid conclusions. SIG e-Learning@CS, Universiti Teknologi MARA. https://appspenang.uitm.edu.my/sigcs/2023-2/Articles/20234_UnderstandingPopulationAndSampleInResearch.pdf
Ahmed, S. K. (2024). How to choose a sampling technique and determine sample size for research: A simplified guide for researchers. Oral Oncology Reports, 12, 100662. https://doi.org/10.1016/j.oor.2024.100662
Ahmid, S. S., Baskaran, S., & Singh, P. (2023). The influence of innovative characteristics, work readiness, and vocational self concept on employability of vocational college students. International Journal for Research in Vocational Education and Training, 10(3), 288–317. https://doi.org/10.13152/IJRVET.10.3.2
Amelia, R. N., Listiaji, P., Dewi, N. R., Heriyanti, A. P., Atmaja, B. D., Shoba, T. M., & Sajidi, I. (2024). Developing and validating a rubric for measuring skills in designing science experiments for prospective science teachers. Jurnal Inovasi Pendidikan IPA, 10(1). https://doi.org/10.21831/jipi.v10i1.65853
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for educational and psychological testing. American Educational Research Association. https://www.testingstandards.net/uploads/7/6/6/4/76643089/standards_2014edition.pdf
American Psychological Association. (2024). Figure setup. APA Style. https://apastyle.apa.org/style-grammar-guidelines/tables-figures/figures
American Psychological Association. (2024). Table setup. APA Style. https://apastyle.apa.org/style-grammar-guidelines/tables-figures/tables
American Psychological Association. (n.d.). Journal article reporting standards. APA Style. https://apastyle.apa.org/jars
Antonietti, C., Cattaneo, A., & Amenduni, F. (2022). Can teachers’ digital competence influence technology acceptance in vocational education? Computers in Human Behavior, 132, 107266. https://doi.org/10.1016/j.chb.2022.107266
Bach, B., Keck, M., Rajabiyazdi, F., Losev, T., Meirelles, I., Dykes, J., Laramee, R. S., AlKadi, M., Stoiber, C., Huron, S., Perin, C., Morais, L., Aigner, W., Kosminsky, D., Boucher, M., Knudsen, S., Manataki, A., Aerts, J., Hinrichs, U., Roberts, J. C., & Carpendale, S. (2024). Challenges and opportunities in data visualization education: A call to action. IEEE Transactions on Visualization and Computer Graphics, 30(1), 649–660. https://doi.org/10.1109/TVCG.2023.3327378
Barella, Y., Fergina, A., Mustami, M. K., Rahman, U., & Alajaili, H. M. A. (2024). Quantitative methods in scientific research. Jurnal Pendidikan Sosiologi dan Humaniora, 15(1), 281–287. https://doi.org/10.26418/j-psh.v15i1.71528
Barroga, E., & Matanguihan, G. J. (2022). A practical guide to writing quantitative and qualitative research questions and hypotheses in scholarly articles. Journal of Korean Medical Science, 37(16), Article e121. https://doi.org/10.3346/jkms.2022.37.e121
Barroga, E., Matanguihan, G. J., Furuta, A., Arima, M., Tsuchiya, S., Kawahara, C., Takamiya, Y., & Izumi, M. (2023). Conducting and writing quantitative and qualitative research. Journal of Korean Medical Science, 38(37), Article e291. https://doi.org/10.3346/jkms.2023.38.e291
Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023). Use of ChatGPT in academia: Academic integrity hangs in the balance. Technology in Society, 75, Article 102370. https://doi.org/10.1016/j.techsoc.2023.102370
Boyd, R. J., Powney, G. D., & Pescott, O. L. (2023). We need to talk about nonprobability samples. Trends in Ecology & Evolution, 38(6), 521–531. https://doi.org/10.1016/j.tree.2023.01.001
Branson, Z., Jenny, D., Lee, K. B., Rubien, N., Stoudt, S., & VanderPlas, S. (2025). The landscape of college level data visualization education. Journal of Statistics and Data Science Education. https://doi.org/10.1080/26939169.2025.2537049
Carolus, A., Koch, M. J., Straka, S., Latoschik, M. E., & Wienrich, C. (2023). MAILS: Meta AI literacy scale: Development and testing of an AI literacy questionnaire based on well-founded competency models and psychological change and meta-competencies. Computers in Human Behavior: Artificial Humans, 1(2), Article 100014. https://doi.org/10.1016/j.chbah.2023.100014
Cattaneo, A. A. P., Antonietti, C., & Rauseo, M. (2022). How digitalised are vocational teachers? Assessing digital competence in vocational education and looking at its underlying factors. Computers & Education, 176, Article 104358. https://doi.org/10.1016/j.compedu.2021.104358
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, 43. https://doi.org/10.1186/s41239-023-00411-8
Chaudhuri, A., & Pal, S. (2022). A comprehensive textbook on sample surveys. Springer. https://doi.org/10.1007/978-981-19-1418-8
Chiang, F. K., Shang, X., & Qiao, L. (2022). Augmented reality in vocational training: A systematic review of research and applications. Computers in Human Behavior, 129, Article 107125. https://doi.org/10.1016/j.chb.2021.107125
Chiang, T. H. C., Shang, X., & Qiao, L. (2022). Augmented reality in vocational training: A systematic review of research and applications. Computers in Human Behavior, 129, 107125. https://doi.org/10.1016/j.chb.2021.107125
Chigbu, U. E., Atiku, S. O., & Du Plessis, C. C. (2023). The science of literature reviews: Searching, identifying, selecting, and synthesising. Publications, 11(1), Article 2. https://doi.org/10.3390/publications11010002
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, Article 100118. https://doi.org/10.1016/j.caeai.2022.100118
Chuenyindee, T., Montenegro, L. D., Ong, A. K. S., Prasetyo, Y. T., Nadlifatin, R., Ayuwati, I. D., Sittiwatethanasiri, T., & Robas, K. P. E. (2022). The perceived usability of the learning management system during the COVID-19 pandemic: Integrating system usability scale, technology acceptance model, and task-technology fit. Work, 73(1), 41–58. https://doi.org/10.3233/WOR-220015
Committee on Publication Ethics, Directory of Open Access Journals, Open Access Scholarly Publishing Association, & World Association of Medical Editors. (2022). Principles of transparency and best practice in scholarly publishing. https://publicationethics.org/guidance/guideline/principles-transparency-and-best-practice-scholarly-publishing
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148
Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications. https://uk.sagepub.com/en-gb/eur/research-design/book270550
Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications. https://us.sagepub.com/en-us/nam/research-design/book270550
Creswell, J. W., & Guetterman, T. C. (2024). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (7th ed.). Pearson. https://www.pearson.com/en-us/subject-catalog/p/educational-research-planning-conducting-and-evaluating-quantitative-and-qualitative-research/P200000010566/9780138173784
Cunningham, S. A., & Muir, J. A. (2023). Data cleaning. In A. L. Nichols & J. Edlund (Eds.), The Cambridge handbook of research methods and statistics for the social and behavioral sciences (Chapter 21). Cambridge University Press. https://doi.org/10.1017/9781009010054.022
Dehghan, H., Esmaeili, S. V., Paridokht, F., Javadzade, N., & Jalali, M. (2022). Assessing the students’ readiness for E-learning during the COVID-19 pandemic: A case study. Heliyon, 8(8), Article e10219. https://doi.org/10.1016/j.heliyon.2022.e10219
Deschênes, M., Dionne, L., & Parent, S. (2024). Supporting digital competency development for vocational education student teachers in distance education. Frontiers in Education, 9, 1452445. https://doi.org/10.3389/feduc.2024.1452445
Deschênes, M., Dionne, L., & Parent, S. (2024). Supporting digital competency development for vocational education student teachers in distance education. Frontiers in Education, 9, Article 1452445. https://doi.org/10.3389/feduc.2024.1452445
Directory of Open Access Journals. (2022, September 15). Revised principles of transparency and best practice released. https://blog.doaj.org/2022/09/15/revised-principles-of-transparency-and-best-practice-released/
DOAJ. (2026). Directory of Open Access Journals. https://doaj.org/
Dorsah, P. (2026). The use of Cronbach’s alpha reliability in educational research: A systematic review. European Journal of Contemporary Education and E-Learning, 4(2), 39–50. https://doi.org/10.59324/ejceel.2026.4(2).04
Eke, D. O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13, Article 100060. https://doi.org/10.1016/j.jrt.2023.100060
Elsevier. (2026). Scopus: Abstract and citation database. https://www.elsevier.com/products/scopus
Enders, C. K. (2022). Applied missing data analysis (2nd ed.). The Guilford Press. https://www.guilford.com/books/Applied-Missing-Data-Analysis/Craig-Enders/9781462549863
ERIC. (2026). Education Resources Information Center. https://eric.ed.gov/
European Commission, Directorate-General for Education, Youth, Sport and Culture. (2022). Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. Publications Office of the European Union. https://doi.org/10.2766/153756
European Commission, Directorate-General for Education, Youth, Sport and Culture. (2022). Ethical guidelines on the use of artificial intelligence and data in teaching and learning for educators. Publications Office of the European Union. https://op.europa.eu/en/publication-detail/-/publication/d81a0d54-5348-11ed-92ed-01aa75ed71a1/language-en
European Commission, Joint Research Centre. (2025). Digital competence framework: DigComp. https://joint-research-centre.ec.europa.eu/projects-and-activities/education-and-training/digital-transformation-education/digital-competence-framework-digcomp_en
European Commission. (2026). Guidelines on the ethical use of artificial intelligence and data in teaching and learning. European Education Area.
European Commission: Directorate-General for Education, Youth, Sport and Culture. (2022). Ethical guidelines on the use of artificial intelligence (AI) and data in teaching and learning for educators. Publications Office of the European Union. https://doi.org/10.2766/153756
Fadhly, F. Z. (2022). Extensive reading as a gateway to create research gap: Valuable lessons from Indonesian expert authors. Indonesian Journal of EFL and Linguistics, 7(2), 397–413. https://doi.org/10.21462/ijefl.v7i2.537
Fahira, S. I., Dewi, I. P., Al-Adwan, A. S., & Castro, R. C. (2025). Augmented reality to enhance informatics learning outcomes: A quasi-experimental study in vocational education. Journal of Hypermedia & Technology-Enhanced Learning, 3(2), 185–201. https://doi.org/10.58536/j-hytel.167
Field, A. (2024). Discovering statistics using IBM SPSS statistics (6th ed.). SAGE Publications. https://uk.sagepub.com/en-gb/eur/discovering-statistics-using-ibm-spss-statistics/book285130
Firmansyah, D., & Dede. (2022). Teknik pengambilan sampel umum dalam metodologi penelitian: Literature review. Jurnal Ilmiah Pendidikan Holistik, 1(2), 85–114. https://doi.org/10.55927/jiph.v1i2.937
Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2023). How to design and evaluate research in education (11th ed.). McGraw Hill. https://www.mheducation.com/highered/product/how-to-design-and-evaluate-research-in-education-fraenkel.html
Francis, M., Avoseh, M., Card, K., Newland, L., & Streff, K. (2023). Student privacy and learning analytics: Investigating the application of privacy within a student success information system in higher education. Journal of Learning Analytics, 10(3), 102–114. https://doi.org/10.18608/jla.2023.7975
Garuda. (2026). Garba Rujukan Digital. Kementerian Pendidikan Tinggi, Sains, dan Teknologi Republik Indonesia. https://garuda.kemdiktisaintek.go.id/
Garzón, J. (2025). Systematic review of artificial intelligence in education: Trends, benefits, and challenges. Multimodal Technologies and Interaction, 9(8), 84. https://doi.org/10.3390/mti9080084
Gottfried, J. (2024). Practices in data-quality evaluation: A large-scale review of online survey studies published in 2022. Advances in Methods and Practices in Psychological Science, 7(2). https://doi.org/10.1177/25152459241236414
Goyal, M., Gupta, C., & Gupta, V. (2022). A meta-analysis approach to measure the impact of project-based learning outcome with program attainment on student learning using fuzzy inference systems. Heliyon, 8(8), Article e10248. https://doi.org/10.1016/j.heliyon.2022.e10248
Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004
Hariyanto, D., Yatmono, S., Khairudin, M., & Köhler, T. (2022). Students e-learning readiness towards education 4.0: Instrument development and validation. Jurnal Pendidikan Vokasi, 12(3), 236–244. https://doi.org/10.21831/jpv.v12i3.51798
Hirsch, R. (2022). Sampling. In Statistical hypothesis testing with Microsoft Office Excel (pp. 11–22). Springer. https://doi.org/10.1007/978-3-031-04202-7_2
IBM. (2026). IBM SPSS Statistics. IBM. https://www.ibm.com/products/spss-statistics
IEEE. (2026). About IEEE Xplore. https://innovate.ieee.org/about-the-ieee-xplore-digital-library/
Illowsky, B., & Dean, S. (2023). Introductory statistics 2e. OpenStax. https://openstax.org/details/books/introductory-statistics-2e
International Center for Academic Integrity. (2021). The fundamental values of academic integrity (3rd ed.). International Center for Academic Integrity.
International Labour Organization, & UNESCO. (2020). The digitization of TVET and skills systems. International Labour Organization. https://www.ilo.org/publications/digitization-tvet-and-skills-systems
Jaeger, S. R., & Cardello, A. V. (2022). Factors affecting data quality of online questionnaires: Issues and metrics for sensory and consumer research. Food Quality and Preference, 102, Article 104676. https://doi.org/10.1016/j.foodqual.2022.104676
Jiang, X., Xu, J., & Xu, X. (2024). An overview of domestic and international applications of digital technology in teaching in vocational education: Systematic literature mapping. Education and Information Technologies, 29, 16867–16899.
Johnson, R. B., & Christensen, L. B. (2024). Educational research: Quantitative, qualitative, and mixed approaches (8th ed.). SAGE Publications. https://uk.sagepub.com/en-gb/eur/educational-research/book277701
Karanam, S. A. K., Choi, S., & Lyons, K. W. (2025). A systematic review of digital twin and virtual learning environment in manufacturing education. Manufacturing Letters. https://doi.org/10.1016/j.mfglet.2025.04.024
Karimian, Z., & Chahartangi, F. (2024). Development and validation of a questionnaire to measure educational agility: A psychometric assessment using exploratory factor analysis. BMC Medical Education, 24, Article 1284. https://doi.org/10.1186/s12909-024-06307-z
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., Stadler, M., Weller, J., Kuhn, J., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kestin, G., Miller, K., Klales, A., Milbourne, T., & Ponti, G. (2025). AI tutoring outperforms in-class active learning: An RCT introducing a novel research-based design in an authentic educational setting. Scientific Reports, 15, 17458. https://doi.org/10.1038/s41598-025-97652-6
Khalifa, M., & Albadawy, M. (2024). Using artificial intelligence in academic writing and research: An essential productivity tool. Computer Methods and Programs in Biomedicine Update, 5, Article 100145. https://doi.org/10.1016/j.cmpbup.2024.100145
Kholifah, N., Nurtanto, M., Sutrisno, V. L. P., Majid, N. W. A., Subakti, H., Daryono, R. W., & Achmadi, A. (2025). Unlocking workforce readiness through digital employability skills in vocational education graduates: A PLS-SEM analysis based on human capital theory. Social Sciences & Humanities Open, 11, 101625. https://doi.org/10.1016/j.ssaho.2025.101625
Koo, M., & Yang, S.-W. (2025). Likert-type scale. Encyclopedia, 5(1), 18. https://doi.org/10.3390/encyclopedia5010018
Kraus, S., Breier, M., Lim, W. M., Dabić, M., Kumar, S., Kanbach, D., Mukherjee, D., Corvello, V., Piñeiro-Chousa, J., Liguori, E., Palacios-Marqués, D., Schiavone, F., Ferraris, A., Fernandes, C., & Ferreira, J. J. (2022). Literature reviews as independent studies: Guidelines for academic practice. Review of Managerial Science, 16(8), 2577–2595. https://doi.org/10.1007/s11846-022-00588-8
Kumalasari, R., Sugiharto, D. Y. P., Sugiyo, S., & Sutoyo, A. (2024). Assessing self-efficacy in vocational students: Development and psychometric evaluation of a new scale using exploratory factor analysis. Edukasi Islami: Jurnal Pendidikan Islam, 13(3), 663–674. https://doi.org/10.30868/ei.v13i03.8917
Kumar, V. (2024). Sampling. In International marketing research (pp. 321–354). Palgrave Macmillan. https://doi.org/10.1007/978-3-031-54650-1_12
Kurniawati, K., & Suartini, T. (2025). Learning management system utilization and perceived training benefits among vocational teachers. Jurnal Pendidikan Vokasi, 15(1). https://doi.org/10.21831/jpv.v15i1.81270
Lakens, D. (2022). Improving your statistical inferences. Eindhoven University of Technology. https://lakens.github.io/statistical_inferences/
Lakens, D. (2022). Sample size justification. Collabra: Psychology, 8(1), Article 33267. https://doi.org/10.1525/collabra.33267
Lathifah, D. N. N., & Hidayati, N. (2025). The influence of kinesthetic learning style on student learning outcomes in experience based vocational learning at SMKN 7 Surakarta. Sunan Kalijaga International Journal on Islamic Educational Research, 9(2). https://doi.org/10.14421/skijier.2025.92.07
Leedy, P. D., & Ormrod, J. E. (2023). Practical research: Design and process (13th ed.). Pearson.
Li, J., Qiao, X., Liu, J., Liu, Y., & Wang, L. (2024). Effectiveness of virtual laboratory in engineering education: A meta-analysis. PLOS ONE, 19(12), Article e0316269. https://doi.org/10.1371/journal.pone.0316269
Liu, Y., Zhan, Q., & Zhao, W. (2024). A systematic review of VR/AR applications in vocational education: Models, affects, and performances. Interactive Learning Environments, 32(10), 6375–6392. https://doi.org/10.1080/10494820.2023.2263043
López, F., Contreras, M., Nussbaum, M., Paredes, R., Gelerstein, D., Alvares, D., & Chiuminatto, P. (2023). Developing critical thinking in technical and vocational education and training. Education Sciences, 13(6), 590. https://doi.org/10.3390/educsci13060590
Luft, J. A., Jeong, S., Idsardi, R., & Gardner, G. E. (2022). Literature reviews, theoretical frameworks, and conceptual frameworks: An introduction for new biology education researchers. CBE—Life Sciences Education, 21(3), Article rm33. https://doi.org/10.1187/cbe.21-05-0134
MacFarlane, A., Russell-Rose, T., & Shokraneh, F. (2022). Search strategy formulation for systematic reviews: Issues, challenges and opportunities. Intelligent Systems with Applications, 15, Article 200091. https://doi.org/10.1016/j.iswa.2022.200091
Magana, A. J. (2022). The role of frameworks in engineering education research. Journal of Engineering Education, 111(1), 9–13. https://doi.org/10.1002/jee.20443
Masuwai, A., Zulkifli, H., & Hamzah, M. I. (2024). Evaluation of content validity and face validity of secondary school Islamic education teacher self-assessment instrument. Cogent Education, 11(1), Article 2308410. https://doi.org/10.1080/2331186X.2024.2308410
Matolić, T., Jurakić, D., Greblo Jurakić, Z., Maršić, T., & Pedišić, Ž. (2023). Development and validation of the EDUcational Course Assessment TOOLkit (EDUCATOOL): A 12 item questionnaire for evaluation of training and learning programmes. Frontiers in Education, 8, Article 1314584. https://doi.org/10.3389/feduc.2023.1314584
Mayer, R. E. (2024). The past, present, and future of the cognitive theory of multimedia learning. Educational Psychology Review, 36, Article 8. https://doi.org/10.1007/s10648-023-09842-1
Miao, F., & Cukurova, M. (2024). AI competency framework for teachers. UNESCO. https://doi.org/10.54675/ZJTE2084
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://doi.org/10.54675/EWZM9535
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://doi.org/10.54675/EWZM9535
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://doi.org/10.54675/EWZM9535
Miao, F., Shiohira, K., & Lao, N. (2024). AI competency framework for students. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000391105
Miao, F., Shiohira, K., & Lao, N. (2024). AI competency framework for students. UNESCO. https://doi.org/10.54675/JKJB9835
Muijs, D. (2022). Doing quantitative research in education with IBM SPSS statistics (3rd ed.). SAGE Publications. https://uk.sagepub.com/en-gb/eur/doing-quantitative-research-in-education-with-ibm-spss-statistics/book259738
Mukti, B. H. (2025). Methods in health research: Probability and non-probability sampling. Health Sciences International Journal. https://hsij.anandafound.com/journal/article/view/64
National Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0). U.S. Department of Commerce. https://doi.org/10.6028/NIST.AI.100-1
Naveed, Q. N., Qureshi, M. R. N., Tairan, N., Mohammad, A. H., Shaikh, A., Alsayed, A. O., Shah, A., & Alotaibi, F. M. (2023). Mobile learning in higher education: A systematic literature review. Sustainability, 15(18), Article 13566. https://doi.org/10.3390/su151813566
Negahban, A. (2024). Simulation in engineering education: The transition from physical experimentation to digital immersive simulated environments. Simulation, 100(7), 695–708. https://doi.org/10.1177/00375497241229757
Nyström, S. (2024). Teaching with simulators in vocational education and training: From a storing place to a new colleague. Teaching and Teacher Education, 136, 104383. https://doi.org/10.1016/j.tate.2023.104383
OECD. (2023). Building future-ready vocational education and training systems. OECD Publishing. https://doi.org/10.1787/28551a79-en
OECD. (2023). Education at a glance 2023: OECD indicators. OECD Publishing. https://doi.org/10.1787/e13bef63-en
OECD. (2023). OECD digital education outlook 2023: Towards an effective digital education ecosystem. OECD Publishing. https://doi.org/10.1787/c74f03de-en
OECD. (2023). OECD employment outlook 2023: Artificial intelligence and the labour market. OECD Publishing. https://doi.org/10.1787/08785bba-en
OECD. (2023). OECD skills outlook 2023: Skills for a resilient green and digital transition. OECD Publishing. https://doi.org/10.1787/27452f29-en
OECD. (2023a). Building future-ready vocational education and training systems. OECD Publishing. https://doi.org/10.1787/28551a79-en
OECD. (2023a). OECD digital education outlook 2023: Towards an effective digital education ecosystem. OECD Publishing. https://doi.org/10.1787/c74f03de-en
OECD. (2023b). Building future-ready vocational education and training systems. OECD Publishing. https://doi.org/10.1787/28551a79-en
OECD. (2023b). OECD digital education outlook 2023: Towards an effective digital education ecosystem. OECD Publishing. https://doi.org/10.1787/c74f03de-en
OECD. (2024). OECD digital economy outlook 2024, Volume 2: Strengthening connectivity, innovation and trust. OECD Publishing. https://doi.org/10.1787/3adf705b-en
Ofem, B. I., & Mchi, A. A. (2023). Variable conceptualisation and measurement in environmental research. International Journal of Methodology, 2(1), 2–11. https://doi.org/10.21467/ijm.2.1.5991
OpenStax. (2023). Introductory statistics 2e: Hypothesis testing with one sample. OpenStax. https://openstax.org/books/introductory-statistics-2e/pages/9-introduction
Patnawar, S. T. (2023). A comprehensive review on PBL and digital PBL in engineering education: Status, challenges and future prospects. Journal of Engineering Education Transformations, 37(2), 142–157. https://doi.org/10.16920/jeet/2023/v37i2/23157
Peters, M. D. J., Marnie, C., Tricco, A. C., Pollock, D., Munn, Z., Alexander, L., McInerney, P., Godfrey, C. M., & Khalil, H. (2022). Best practice guidance and reporting items for the development of scoping review protocols. JBI Evidence Synthesis, 20(4), 953–968. https://doi.org/10.11124/JBIES-21-00242
Pilowsky, J. K., Elliott, R., & Roche, M. A. (2024). Data cleaning for clinician researchers: Application and explanation of a data quality framework. Australian Critical Care, 37(5), 827–833. https://doi.org/10.1016/j.aucc.2024.03.004
Pitaloka, D. A. E., Kusuma, I. Y., Pratiwi, H. P., & Pradipta, I. S. S. (2023). Development and validation of assessment instrument for the perception and attitude toward tuberculosis among the general population in Indonesia: A Rasch analysis of psychometric properties. Frontiers in Public Health, 11, Article 1143120. https://doi.org/10.3389/fpubh.2023.1143120
Raifman, S., DeVost, M. A., Digitale, J. C., Chen, Y. H., & Morris, M. D. (2022). Respondent-driven sampling: A sampling method for hard-to-reach populations and beyond. Current Epidemiology Reports, 9, 38–47. https://doi.org/10.1007/s40471-022-00287-8
Rho, J., Kim, S., & Zhu, X. (2025). Comparing the deceptive impact of misleading data visualization types. Computers & Education. https://doi.org/10.1016/j.compedu.2025.105465
Rodriguez-Segura, D. (2022). EdTech in developing countries: A review of the evidence. The World Bank Research Observer, 37(2), 171–203. https://openknowledge.worldbank.org/entities/publication/2e40df91-909f-4cd2-888d-b9d3bf401f42
Sala, R., Maffei, A., Pirola, F., Enoksson, F., Ljubić, S., Skoki, A., Zammit, J. P., Bonello, A., Podržaj, P., Žužek, T., Priarone, P. C., Antonelli, D., & Pezzotta, G. (2024). Blended learning in the engineering field: A systematic literature review. Computer Applications in Engineering Education, 32(3), Article e22712. https://doi.org/10.1002/cae.22712
Saltos-Rivas, R., Novoa-Hernández, P., & Serrano Rodríguez, R. (2022). How reliable and valid are the evaluations of digital competence in higher education: A systematic mapping study. SAGE Open, 12(1). https://doi.org/10.1177/21582440211068492
Schmid, M., Brianza, E., Mok, S. Y., & Petko, D. (2024). Running in circles: A systematic review of reviews on technological pedagogical content knowledge (TPACK). Computers & Education, 214, 105024. https://doi.org/10.1016/j.compedu.2024.105024
Setiawan, A., Cendana, W., Ayres, M., Yuldashev, A. A., & Setyawati, S. P. (2023). Development and validation of a self-assessment-based instrument to measure elementary school students’ attitudes in online learning. REID: Research and Evaluation in Education, 9(2), 184–197. https://doi.org/10.21831/reid.v9i2.52083
Setiawan, R., Wagiran, W., & Alsamiri, Y. (2024). Construction of an instrument for evaluating the teaching process in higher education: Content and construct validity. REID (Research and Evaluation in Education), 10(1), 50–63. https://doi.org/10.21831/reid.v10i1.63483
Setiyawan, H., Dardiri, A., Suyetno, A., Muladi, M., Purnomo, P., & Sudjimat, D. A. (2023). The influence of digital and vocational information literacy on students’ learning outcomes. Jurnal Pendidikan Vokasi, 13(2), 223–236. https://doi.org/10.21831/jpv.v13i2.55921
Setiyawan, H., Suharno, S., & Pambudi, N. A. (2023). The influence of digital and vocational information literacy on student learning outcomes. Jurnal Pendidikan Vokasi, 13(2), 192–204. https://doi.org/10.21831/jpv.v13i2.53999
Sharifnia, A. M., Kpormegbey, D. E., Thapa, D. K., & Cleary, M. (2026). A primer of data cleaning in quantitative research: Handling missing values and outliers. Journal of Advanced Nursing, 82(1), 970–975. https://doi.org/10.1111/jan.16908
SINTA. (2026). Science and Technology Index. Kementerian Pendidikan Tinggi, Sains, dan Teknologi Republik Indonesia. https://sinta.kemdiktisaintek.go.id/
Snyder, H. (2024). Designing the literature review for a strong contribution. Designs, Codes and Cryptography?
Sofyan, H., Soenarto, Mutohhari, F., & Nurtanto, M. (2022). Students’ career decision-making during online learning: The mediating roles of self-efficacy in vocational education. European Journal of Educational Research, 11(3), 1669–1682. https://doi.org/10.12973/eu-jer.11.3.1669
Strzelecki, A. (2024). Students’ acceptance of ChatGPT in higher education: An extended unified theory of acceptance and use of technology. Innovative Higher Education, 49, 223–245. https://doi.org/10.1007/s10755-023-09686-1
Sudarsono, B., Tentama, F., Mulasari, S. A., Sukesi, T. W., Sulistyawati, S., Ghozali, F. A., Yuliansyah, H., Nafiati, L., & Sofyan, H. (2022). Development of integrated project-based learning (PjBL-T) model to improve work readiness of vocational high school students. Jurnal Pendidikan Vokasi, 12(3), 222–235. https://doi.org/10.21831/jpv.v12i3.53158
Suhail, N. S., Bahroun, Z. B., & Ahmed, V. A. V. (2024). Augmented reality in engineering education: Enhancing learning and application. Frontiers in Virtual Reality, 5, Article 1461145. https://doi.org/10.3389/frvir.2024.1461145
Suhandiah, S., Suhariadi, F., Yulianti, P., & Abbas, A. (2022). Online learning satisfaction in higher education: What are the determining factors? Cakrawala Pendidikan, 41(2), 351–364. https://doi.org/10.21831/cp.v41i2.35724
Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1), 31–40. https://doi.org/10.37074/jalt.2023.6.1.17
Sumargo, B., Budyanra, & Kurniawan, R. (2024). Metode dan pengaplikasian teknik sampling. Bumi Aksara. https://books.google.com/books/about/Metode_dan_Pengaplikasian_Teknik_Samplin.html?id=1HUbEQAAQBAJ
Supriyanto, S., Joshua, Q., Abdullah, A. G., Tettehfio, E. O., & Ramdani, S. D. (2023). Application of augmented reality (AR) in vocational education: A systematic literature review. Jurnal Pendidikan Vokasi, 13(2), 205–213. https://doi.org/10.21831/jpv.v13i2.54280
Supriyanto, S., Munadi, S., Daryono, R. W., Tuah, Y. A. E., Nurtanto, M., & Arifah, S. (2023). The influence of internship experience and work motivation on work readiness in vocational students: PLS-SEM analysis. Indonesian Journal on Learning and Advanced Education, 5(1), 32–44. https://doi.org/10.23917/ijolae.v5i1.20033
Suyitno, S., Nurtanto, M., Jatmoko, D., Widiyono, Y., Purwoko, R. Y., Abdillah, F., Setuju, S., & Hermawan, Y. (2025). The effect of work-based learning on employability skills: The role of self-efficacy and vocational identity. European Journal of Educational Research, 14(1), 309–321. https://doi.org/10.12973/eu-jer.14.1.309
Swan, K., Speyer, R., Scharitzer, M., Farneti, D., Brown, T., Woisard, V., & Cordier, R. (2023). Measuring what matters in healthcare: A practical guide to psychometric principles and instrument development. Frontiers in Psychology, 14, Article 1225850. https://doi.org/10.3389/fpsyg.2023.1225850
Taufan, S., Jayanti, A. R. B., Susita, D., & Frannita, E. L. (2025). Influence of self-efficacy and motivation on work readiness in vocational education students. Jurnal Ilmiah Manajemen Kesatuan, 13(5), 3787–3798. https://doi.org/10.37641/jimkes.v13i5.3501
Tembrevilla, G., Phillion, A., & Zeadin, M. (2024). Experiential learning in engineering education: A systematic literature review. Journal of Engineering Education, 113(1), 195–218. https://doi.org/10.1002/jee.20575
The Jamovi Project. (2026). Reliability analysis. Jamovi. https://www.jamovi.org/jmv/reliability.html
Think. Check. Submit. (2024). Books & chapters: Are you submitting your research to a trusted publisher? https://thinkchecksubmit.org/wp-content/uploads/2024/02/ThinkCheckSubmit-Books-English-2024.pdf
Ubaidillah, F. A., Saifullah, Hitomi, A. R., & Bulut, S. (2023). Self-efficacy and academic performance of vocational high school students. Psikoislamika: Jurnal Psikologi dan Psikologi Islam, 20(1). https://doi.org/10.18860/psikoislamika.v20i1.18369
UNESCO. (2022). Transforming technical and vocational education and training for successful and just transitions: UNESCO strategy 2022 to 2029. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000383360
UNESCO. (2023). Global education monitoring report 2023: Technology in education: A tool on whose terms? UNESCO. https://doi.org/10.54676/UZQV8501
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO. https://doi.org/10.54675/EWZM9535
Venta, A., Bailey, C. A., Walker, J., Mercado, A., Colunga Rodriguez, C., Ángel González, M., & Dávalos Picazo, G. (2022). Reverse coded items do not work in Spanish: Data from four samples using established measures. Frontiers in Psychology, 13, Article 828037. https://doi.org/10.3389/fpsyg.2022.828037
Viberg, O., Cukurova, M., Feldman-Maggor, Y., Alexandron, G., Shirai, S., Kanemune, S., Wasson, B., Tømte, C., Spikol, D., Milrad, M., Coelho, R., & Kizilcec, R. F. (2023). What explains teachers’ trust of AI in education across six countries? arXiv. https://arxiv.org/abs/2312.01627
Villarroel, V., Melipillán, R., Santana, J., & Aguirre, D. (2024). How authentic are assessments in vocational education? An analysis from Chilean teachers, students, and examinations. Frontiers in Education, 9, Article 1308688. https://doi.org/10.3389/feduc.2024.1308688
Vlachopoulos, D., & Makri, A. (2024). A systematic literature review on authentic assessment in higher education: Best practices for the development of 21st century skills, and policy considerations. Studies in Educational Evaluation, 83, Article 101425. https://doi.org/10.1016/j.stueduc.2024.101425
Vuorikari, R., Kluzer, S., & Punie, Y. (2022). DigComp 2.2: The digital competence framework for citizens: With new examples of knowledge, skills and attitudes. Publications Office of the European Union. https://doi.org/10.2760/115376
Wafudu, S. J., Kamin, Y. B., & Marcel, D. (2022). Validity and reliability of a questionnaire developed to explore quality assurance components for teaching and learning in vocational and technical education. Humanities and Social Sciences Communications, 9, Article 303. https://doi.org/10.1057/s41599-022-01306-1
Wagenmakers, E.-J., & JASP Team. (2022). JASP data library. JASP. https://jasp-stats.org/
Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Systems with Applications, 252, Article 124167. https://doi.org/10.1016/j.eswa.2024.124167
Weaver, K. D. (2024). The Artificial Intelligence Disclosure (AID) framework: An introduction. College & Research Libraries News, 85(6), 226–229. https://doi.org/10.5860/crln.85.6.226
Wickham, H., Çetinkaya Rundel, M., & Grolemund, G. (2023). R for data science: Import, tidy, transform, visualize, and model data (2nd ed.). O’Reilly Media. https://r4ds.hadley.nz/
Wiyanti, I., Tuwoso, T., & Alfianto, I. (2025). The contribution of digital literacy and field work practice to the employability skills of vocational high school students. Sosioedukasi: Jurnal Ilmiah Ilmu Pendidikan dan Sosial, 14(4), 3674–3683. https://doi.org/10.36526/sosioedukasi.v14i4.6599
World Bank, UNESCO, & International Labour Organization. (2023). Building better formal TVET systems: Principles and practice in low- and middle-income countries. World Bank, UNESCO, and ILO. https://doi.org/10.54675/RVDM3811
World Bank. (2026). Digital technologies in education. https://www.worldbank.org/ext/en/topic/education/digital-technologies-in-education
World Economic Forum. (2023). The future of jobs report 2023. World Economic Forum. https://www.weforum.org/publications/the-future-of-jobs-report-2023/
World Economic Forum. (2025). The future of jobs report 2025. World Economic Forum.
Wulandari, R. M., & Hidayat, R. (2023). Materialism as personality: Psychometric properties using the Rasch model. Jurnal Psikologi, 50(2), 157–175. https://doi.org/10.22146/jpsi.77592
Yusop, S. R. M., Rasul, M. S., Mohamad Yasin, R., Hashim, H. U., & Jalaludin, N. A. (2022). An assessment approaches and learning outcomes in technical and vocational education: A systematic review using PRISMA. Sustainability, 14(9), 5225. https://doi.org/10.3390/su14095225
Zhang, X., Qian, W., & Chen, C. (2024). The effect of digital technology usage on higher vocational student satisfaction: The mediating role of learning experience and learning engagement. Frontiers in Education, 9, Article 1508119. https://doi.org/10.3389/feduc.2024.1508119
