THE READINESS ANALYSIS OF BLENDED LEARNING IN FLORES UNIVERSITY
This research aims to know the readiness of blended learning in Flores University area especially in the study program of Information System. This research used a survey research approach with 113 people for the sample. The instrument that was used for this research is the questionnaire of the Likert scale. To analyze the data, this research uses factor analysis in the readiness of adopted learning by Aydin and Tasci. The result of this research were: (1) normally test result showed that all the data are normally distributed because each variable was more than 0,05. (2) The point of KMO MSA was 0,533>0,50 and the point of Barlett's Test of Sphericity (sig.) was 0,000<0,05, it means that the factor analysis can continue. (3) The value of MSA for all variables was >0,50, it means the factor analysis is fulfilled. (4) The extraction value for all the variables was >0,50. So it can be concluded that all the variables are used to explain the factor. (5) The value of Eigenvalues component 1 was 1,858> 1, so it becomes a factor of 1 and can explain 46.453% of the variation. Meanwhile, the value of Eigenvalues component 2 is 1,225>1 so it becomes a factor of 2 and can explain 30,633% of the variation. (6) from the two factors formed, it was feasible to summarize the four variables analyzed. This means that the four variables have the readiness to carry out blended learning at Flores University.
S. Bibi and H. Jati, “Efektivitas model blended learning terhadap motivasi dan tingkat pemahaman mahasiswa mata kuliah algoritma dan pemrograman,” J. Pendidik. Vokasi, vol. 5, no. 1, p. 74, 2015, doi: 10.21831/jpv.v5i1.6074.
S. Riyanto and H. A. Mumtahana, “Analisis Kesiapan Blended Learning Di Lingkungan Program Studi Teknik Informatika Universitas PGRI Madiun,” J-SAKTI (Jurnal Sains Komput. dan Inform., vol. 2, no. 2, p. 191, 2018, doi: 10.30645/j-sakti.v2i2.82.
A. Kristanto, M. Mustaji, and A. Mariono, “The Development of Instructional Materials E-Learning Based On Blended Learning,” Int. Educ. Stud., vol. 10, no. 7, p. 10, 2017, doi: 10.5539/ies.v10n7p10.
E. Fitri, “Efektivitas Layanan Informasi,” J. Psikol. Pendidik. Konseling, vol. 2, pp. 84–92, 2016.
C. H. Aydin and D. Tasci, “Measuring readiness for e-learning: Reflections from an emerging country,” Educ. Technol. Soc., vol. 8, no. 4, pp. 244–257, 2005.
X. Meng, “Scalable simple random sampling and stratified sampling,” 30th Int. Conf. Mach. Learn. ICML 2013, vol. 28, no. PART 2, pp. 1568–1576, 2013.
J. Tejada and J. Punzalan, “On the misuse of Slovin’s formula,” Philipp. Stat., vol. 61, no. 1, pp. 129–136, 2012.
I. Purwandani, “Analisa Tingkat Kesiapan E-Learning (E-Learning Readiness) Studi Kasus: AMIK Bina Sarana Informatika Jakarta,” Bianglala Inform., vol. 5, no. 2, pp. 102–107, 2017, [Online]. Available: http://ejournal.bsi.ac.id/ejurnal/index.php/Bianglala/article/view/2976/1895.
R. Yilmaz, “Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom,” Comput. Human Behav., vol. 70, pp. 251–260, 2017, doi: 10.1016/j.chb.2016.12.085.
G. Pramesti, Kupas Tuntas Data Penelitian dengan SPSS 22. Jakarta: PT Elex Media Komputindo, 2014.
L. L. Chan and N. Idris, “Validity and Reliability of The Instrument Using Exploratory Factor Analysis and Cronbachâ™s alpha,” Int. J. Acad. Res. Bus. Soc. Sci., vol. 7, no. 10, pp. 400–410, 2017, doi: 10.6007/ijarbss/v7-i10/3387.
Abstract viewed = 36 times
PDF downloaded = 20 times