Confirmatory Factor Analysis of Mathematics Learning Interaction in Google Classroom: A Validation Study at Ciamis Vocational School

Authors

  • Zulkaidah Nur Ahzan Universitas Timor
  • Nur Eva Zakiah Universitas Galuh
  • Fitriani Fitriani Universitas Timor
  • Muhamad Zulfikar Mansyur Universitas Siliwangi

DOI:

https://doi.org/10.31980/mosharafa.v14i2.3025

Keywords:

CFA, Google Classroom, Learning interaction, Mathematics, Vocational high school, Interaksi Belajar, Matematika, SMK

Abstract

Abstrak

Penelitian ini bertujuan untuk mengidentifikasi indikator yang mempengaruhi keberhasilan interaksi belajar siswa melalui Google Classroom dalam pembelajaran matematika di SMKN 1 Panumbangan. Metode yang digunakan adalah pendekatan kuantitatif dengan analisis faktor konfirmatori (CFA). Instrumen berupa angket tertutup diberikan kepada 85 siswa dari kelas X dan XI program Bisnis Digital dan Pemasaran serta Multimedia. Analisis dilakukan menggunakan SPSS versi 26. Hasil eksplorasi menunjukkan terdapat delapan faktor yang terbentuk: faktor internal dan eksternal, perilaku negatif, self-affirmation, perilaku positif, ketidaktahuan, persepsi terhadap mata pelajaran, lingkungan belajar, dan egois. Enam faktor utama dalam model CFA mampu menjelaskan 68,3% variasi data. Kesimpulannya, interaksi belajar siswa melalui Google Classroom dipengaruhi secara signifikan oleh faktor kesadaran diri dan perilaku positif, perilaku negatif, persepsi kebermanfaatan Google Classroom dalam belajar, egois, internal, dan ketidaktahuan.

Abstract

This study aims to identify indicators that influence the success of student learning interactions through Google Classroom in mathematics learning at SMKN 1 Panumbangan. The method employed was a quantitative approach, utilizing confirmatory factor analysis (CFA). The instrument, a closed-ended questionnaire, was administered to 85 students from grades 10 and 11 of the Digital Business and Marketing and Multimedia programs. Analysis was conducted using SPSS version 26. The exploration results revealed eight factors: internal and external factors, negative behavior, self-affirmation, positive behavior, ignorance, perception of the subject, learning environment, and egotism. The six main factors in the CFA model were able to explain 68.3% of the data variation. In conclusion, student learning interactions through Google Classroom are significantly influenced by self-awareness and positive behavior, negative behavior, perceived usefulness of Google Classroom in learning, egotism, internal factors, and ignorance.

References

Abuzant, M., Ghanem, M., Abd-Rabo, A., & Daher, W. (2021). Quality of Using Google Classroom to Support the Learning Processes in the Automation and Programming Course. International Journal of Emerging Technologies in Learning, 16(6), 72–87. https://doi.org/10.3991/ijet.v16i06.18847

Aldalalah, O., Ababneh, Z. W. M., Bawaneh, A. K., & Alzubi, W. M. M. (2019). Effect of Augmented Reality and Simulation on the Achievement of Mathematics and Visual Thinking Among Students. International Journal of Emerging Technologies in Learning, 14(18), 164–185. https://doi.org/10.3991/ijet.v14i18.10748

Aletras, V. H., Kostarelis, A., Tsitouridou, M., Niakas, D., & Nicolaou, A. (2010). Development and preliminary validation of a questionnaire to measure satisfaction with home care in Greece: an exploratory factor analysis of polychoric correlations. BMC Health Services Research, 10, 1–14.

Álvarez-Marín, A., Velázquez-Iturbide, J. Á., & Castillo-Vergara, M. (2023). The acceptance of augmented reality in engineering education: the role of technology optimism and technology innovativeness. Interactive Learning Environments, 31(6), 3409–3421. https://doi.org/10.1080/10494820.2021.1928710

Azmat, M., & Ahmad, A. (2022). Lack of Social Interaction in Online Classes During COVID-19. J. Mater. Environ. Sci, 2022(2), 185–196.

Beaumont, K. (2018). Google Classroom: An online learning environment to support blended learning. Compass: Journal of Learning and Teaching, 11(2), 1–6.

Berdiyorovna, B. M., & Uktamovna, A. M. (2025). The importance of using mobile applications in teaching mathematics. International Journal of Pedagogics, 5(1), 14–19. https://doi.org/10.37547/ijp/Volume05Issue01-05

Bonett, D. G., & Wright, T. A. (2015). Cronbach’s alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of Organizational Behavior, 36(1), 3–15. https://doi.org/10.1002/job.1960

Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (D. A. Kenny & T. D. Little, Eds.; 2nd edition). The Guilford Press.

Buchs, C., & Butera, F. (2015). Cooperative learning and social skills development. In Collaborative Learning: Developments in research and practice (pp. 201–238).

Cavus, N., Mohammed, Y. B., & Yakubu, M. N. (2021). Determinants of learning management systems during covid-19 pandemic for sustainable education. Sustainability (Switzerland), 13(9). https://doi.org/10.3390/su13095189

Chen, J., Wang, M., Kirschner, P. A., & Tsai, C. C. (2018). The Role of Collaboration, Computer Use, Learning Environments, and Supporting Strategies in CSCL: A Meta-Analysis. Review of Educational Research, 88(6), 799–843. https://doi.org/10.3102/0034654318791584

Churcher, K. M. A., Downs, E., & Tewksbury, D. (2014). “Friending” Vygotsky: A Social Constructivist Pedagogy of Knowledge Building Through Classroom Social Media Use. The Journal of Effective Teaching, 14(1), 33–50.

Costello, A. B., & Osborne, J. (2005). Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. Research, and Evaluation Practical Assessment, Research, and Evaluation, 10, 1–10. https://doi.org/10.7275/jyj1-4868

Dewi, R. P., & Afriansyah, E. A. (2022). Pembelajaran Matematika Berbasis Aplikasi Google Classroom pada Materi Bangun Ruang Sisi Datar. Plusminus: Jurnal Pendidikan Matematika, 2(1), 39-52. https://doi.org/10.31980/plusminus.v2i1.1084

Dindar, M., Suorsa, A., Hermes, J., Karppinen, P., & Näykki, P. (2021). Comparing technology acceptance of K-12 teachers with and without prior experience of learning management systems: A Covid-19 pandemic study. Journal of Computer Assisted Learning, 37(6), 1553–1565. https://doi.org/10.1111/jcal.12552

Dorimana, A., & Uworwabayeho, A. (2022). Enhancing Upper Secondary Learners’ Problem-solving Abilities using Problem-based Learning in Mathematics. International Journal of Learning, Teaching and Educational Research, 21(8), 235–252. https://doi.org/10.26803/ijlter.21.8.14

Dow-Fleisner, S. J., Seaton, C. L., Li, E., Plamondon, K., Oelke, N., Kurtz, D., Jones, C., Currie, L. M., Pesut, B., Hasan, K., & Rush, K. L. (2022). Internet access is a necessity: a latent class analysis of COVID-19 related challenges and the role of technology use among rural community residents. BMC Public Health, 22(1), 1. https://doi.org/10.1186/s12889-022-13254-1

Esawe, A. T., Esawe, K. T., & Esawe, N. T. (2023). Acceptance of the learning management system in the time of COVID-19 pandemic: An application and extension of the unified theory of acceptance and use of technology model. E-Learning and Digital Media, 20(2), 162–190. https://doi.org/10.1177/20427530221107788

Geletu, G. M. (2022). The effects of teachers’ professional and pedagogical competencies on implementing cooperative learning and enhancing students’ learning engagement and outcomes in science: Practices and changes. Cogent Education, 9(1), 1–22. https://doi.org/10.1080/2331186X.2022.2153434

Goni, M. D., Naing, N. N., Hasan, H., Wan-Arfah, N., Deris, Z. Z., Arifin, W. N., Baaba, A. A., & Njaka, S. (2020). A confirmatory factor analysis of the knowledge, attitude and practice questionnaire towards prevention of respiratory tract infections during Hajj and Umrah. BMC Public Health, 20(1). https://doi.org/10.1186/s12889-020-09756-5

Gurevych, R. S., Shakhina, I. Yu., & Podzygun, O. A. (2020). Google Classroom as An Effective Tool of Smart Learning and Monitoring of Students’ Knowledge in Vocational Schools. Information Technologies and Learning Tools, 79(5), 59–72. https://doi.org/10.33407/itlt.v79i5.3651

Habibi, A., Yaakob, M. F. M., & Al-Adwan, A. S. (2023). m-Learning Management System use during Covid-19. Information Development, 39(1), 123–135. https://doi.org/10.1177/02666669211035473

Hair Jr, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.). Pearson.

Isaac, E., & Uwaks, G. (2022). Content Validity in Educational Assessment. International Journal of Innovative Education Research, 10(2), 57–69. www.seahipaj.org

Jollife, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), 1–16. https://doi.org/10.1098/rsta.2015.0202

Joshi, A., Kale, S., Chandel, S., & Pal, D. (2015). Likert Scale: Explored and Explained. British Journal of Applied Science & Technology, 7(4), 396–403. https://doi.org/10.9734/bjast/2015/14975

Kasperski, R., & Blau, I. (2023). Social capital in high-schools: teacher-student relationships within an online social network and their association with in-class interactions and learning. Interactive Learning Environments, 31(2), 955–971. https://doi.org/10.1080/10494820.2020.1815220

Kemendikbudristek. (2022). Peraturan Menteri Pendidikan, Kebudayaan, Riset, Dan Teknologi Republik Indonesia Nomor 5 Tahun 2022 tentang Standar Kompetensi Lulusan pada Pendidikan Anak Usia Dini, Jenjang Pendidikan Dasar, dan Jenjang Pendidikan Menengah.

Khaled, A., Gulikers, J., Biemans, H., van der Wel, M., & Mulder, M. (2014). Characteristics of hands-on simulations with added value for innovative secondary and higher vocational education. Journal of Vocational Education and Training, 66(4), 462–490. https://doi.org/10.1080/13636820.2014.917696

Kirkwood, A. (2014). Teaching and learning with technology in higher education: blended and distance education needs ‘joined-up thinking’ rather than technological determinism. Open Learning, 29(3), 206–221. https://doi.org/10.1080/02680513.2015.1009884

Kohen, Z., & Orenstein, D. (2021). Mathematical modeling of tech-related real-world problems for secondary school-level mathematics. Educational Studies in Mathematics, 107(1), 71–91. https://doi.org/10.1007/s10649-020-10020-1

Koyuncu, İ., & Kılıç, A. F. (2019). The use of exploratory and confirmatory factor analyses: A document analysis. Egitim ve Bilim, 44(198), 361–388. https://doi.org/10.15390/EB.2019.7665

Kumar, J. A., Bervell, B., & Osman, S. (2020). Google classroom: insights from Malaysian higher education students’ and instructors’ experiences. Education and Information Technologies, 25(5), 4175–4195. https://doi.org/10.1007/s10639-020-10163-x

Lai, C. L., & Hwang, G. J. (2016). A self-regulated flipped classroom approach to improving students’ learning performance in a mathematics course. Computers and Education, 100, 126–140. https://doi.org/10.1016/j.compedu.2016.05.006

Maccallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample Size in Factor Analysis. Psychological Methods, 4(1), 84–99. https://doi.org/10.1037/1082-989X.4.1.84

Malik, S., Hazarika, D. D., & Dhaliwal, A. (2022). Deliverables of student engagement: developing an outcome-oriented model. Journal of International Education in Business, 15(2), 221–249. https://doi.org/10.1108/JIEB-02-2020-0012

Marsh, H. W., Morin, A. J. S., Parker, P. D., & Kaur, G. (2014). Exploratory structural equation modeling: An integration of the best features of exploratory and confirmatory factor analysis. Annual Review of Clinical Psychology, 10(1), 85–110. https://doi.org/10.1146/annurev-clinpsy-032813-153700

Md. Sari, N., Yin, K. Y., & Zakariya, Z. (2024). The Effect of Google Classroom-Assisted Learning on the Academic Achievement of Students. International Journal of Academic Research in Business and Social Sciences, 14(4), 355–370. https://doi.org/10.6007/ijarbss/v14-i4/21165

Moore, M. G. (1989). Editorial: Three Types of Interaction. American Journal of Distance Education, 3(2), 1–7. https://doi.org/10.1080/08923648909526659

Mosconi, M., Nelson, L., & Hooper, S. R. (2008). Confirmatory factor analysis of the nepsy for younger and older school-age children. Psychological Reports, 102(3), 861–866. https://doi.org/10.2466/PR0.102.3.861-866

Octaberlina, L. R., & Muslimin, A. I. (2020). EFL student’s perspective towards online learning barriers and alternatives using moodle/google classroom during covid-19 pandemic. International Journal of Higher Education, 9(6), 1–9. https://doi.org/10.5430/ijhe.v9n6p1

Okeke, A. M., Inweregbuh, S. A., & Onyemauche C. (2022). Effect of Google Classroom on Secondary School Students’ Engagement and Achievement in Mathematics. AJSTME, 8(1), 411–417.

, N. (2017). Use of interactive whiteboard in the mathematics classroom: Students’ perceptions within the framework of the technology acceptance model. International Journal of Instruction, 10(4), 67–86. https://doi.org/10.12973/iji.2017.1045a

Ozdemir, H., & Onder-Ozdemir, N. (2017). Vocational High School Students’ Perceptions of Success in Mathematics. International Electronic Journal of Mathematics Education, 12(3), 493–502. https://doi.org/10.29333/iejme/627

Quiño, J. B. (2022). Students’ Perception and Satisfaction of Google Classroom as Instructional Medium for Teaching and Learning. Canadian Journal of Educational and Social Studies, 2(2), 1–25. https://doi.org/10.53103/cjess.v2i2.22

Rahiem, M. D. H. (2020). Technological barriers and challenges in the use of ICT during the COVID-19 emergency remote learning. Universal Journal of Educational Research, 8(11B), 6124–6133. https://doi.org/10.13189/ujer.2020.082248

Santor, D. A., Haggerty, J. L., Lévesque, J.-F., Burge, F., Beaulieu, M.-D., Gass, D., & Pineault, R. (2011). An Overview of Confirmatory Factor Analysis and Item Response Analysis Applied to Instruments to Evaluate Primary Healthcare. HEALTHCARE POLICY, 7(Special Issue), 79–92.

Semenikhina, E., & Drushlyak, M. (2014). Computer Mathematical Tools: Practical Experience of Learning to use them. European Journal of Contemporary Education, 9(3), 175–183. https://doi.org/10.13187/ejced.2014.9.175

Sen, E. O. (2022). Effect of Educational Videos on the Interest, Motivation, and Preparation Processes for Mathematics Courses. Contemporary Mathematics and Science Education, 3(1), 1–8. https://doi.org/10.30935/conmaths/11891

Sheelavant, S. (2020). Google Classroom-An Effective Tool for Online Teaching and Learning in this COVID era. Indian Journal of Forensic Medicine & Toxicology, 14(4), 494–500.

Shi, M., & Tan, C. Y. (2020). Beyond Oral Participation: A Typology of Student Engagement in Classroom Discussions. New Zealand Journal of Educational Studies, 55(1), 247–265. https://doi.org/10.1007/s40841-020-00166-0

Stafford, V. (2021). Using Google shared files to facilitate successful online student group collaboration. Journal of Applied Learning and Teaching, 4(1), 129–133. https://doi.org/10.37074/jalt.2021.4.1.21

Surya, E., & Andriana Putri, F. (2017). Improving Mathematical Problem-Solving Ability and Self-Confidence of High School Students Through Contextual Learning Model. Journal on Mathematics Education, 8(1), 85–94.

Swanson, R. A., & Holton, E. F. (2005). Research in Organizations: Foundations and Methods of Inquiry. Berrett-Koehler Publishers.

Syamsuddin, A., Babo, R., Sulfasyah, Bakri, H., & Jainuddin. (2022). An investigation of students’ mathematical concept understanding and motivation through the implementation of aptitude treatment interaction learning model. Kasetsart Journal of Social Sciences, 43(4), 891–902. https://doi.org/10.34044/j.kjss.2022.43.4.12

Wang, C. K. J., Liu, W. C., Kee, Y. H., & Chian, L. K. (2019). Competence, autonomy, and relatedness in the classroom: understanding students’ motivational processes using the self-determination theory. Heliyon, 5(7), 1–6. https://doi.org/10.1016/j.heliyon.2019.e01983

Wang, F., & Sahid, S. (2024). Content validation and content validity index calculation for entrepreneurial behavior instruments among vocational college students in China. Multidisciplinary Reviews, 7(9). https://doi.org/10.31893/multirev.2024187

Ward, V., Smith, S., House, A., & Hamer, S. (2012). Exploring knowledge exchange: A useful framework for practice and policy. Social Science and Medicine, 74(3), 297–304. https://doi.org/10.1016/j.socscimed.2011.09.021

Wu, S. (2024). Application of multimedia technology to innovative vocational education on learning satisfaction in China. PLoS ONE, 19(2), 1–20. https://doi.org/10.1371/journal.pone.0298861

Xie, B., Charness, N., Fingerman, K., Kaye, J., Kim, M. T., & Khurshid, A. (2020). When Going Digital Becomes a Necessity: Ensuring Older Adults’ Needs for Information, Services, and Social Inclusion During COVID-19. Journal of Aging and Social Policy, 32(4–5), 460–470. https://doi.org/10.1080/08959420.2020.1771237

Zeynivandnezhad, F., Rashed, F., & Kanooni, A. (2019). Exploratory Factor Analysis for TPACK among Mathematics Teachers: Why, What and How. Anatolian Journal of Education, 4(1), 59–76. https://doi.org/10.29333/aje.2019.416a

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Published

2025-04-30

How to Cite

Nur Ahzan, Z., Nur Eva Zakiah, Fitriani, F., & Mansyur, M. Z. (2025). Confirmatory Factor Analysis of Mathematics Learning Interaction in Google Classroom: A Validation Study at Ciamis Vocational School. Mosharafa: Jurnal Pendidikan Matematika, 14(2), 513–534. https://doi.org/10.31980/mosharafa.v14i2.3025

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