The Relationship among Academic Self-Efficacy, Academic Resilience, and Academic Flow: The Mediating Effect of Intensity Using Learning Management System

Yarmis Syukur - Universitas Negeri Padang, 25132, Padang, Indonesia
Ade Putra - Universitas Negeri Padang, 25132, Padang, Indonesia
Zadrian Ardi - Universitas Negeri Padang, 25132, Padang, Indonesia
Vivi Mardian - Universitas Pendidikan Indonesia, 40154, Bandung, Indonesia


Citation Format:



DOI: http://dx.doi.org/10.62527/joiv.8.2.2216

Abstract


University students can have low academic flow when using a Learning Management System (LMS). Three variables are predicted to correlate with the academic flow (FA) of students who use LMS: academic self-efficacy (ASE), academic resilience (AR), and LMS use intensity (LMSI). This study looks at the link between academic self-efficacy, academic resilience, LMS use intensity, and academic flow among university students who use LMS. This study employs a quantitative approach, using correlational approaches and path analysis. Furthermore, 740 Indonesian university students who used LMS participated in this study. This study used the partial least squares-structural equation model (PLS-SEM) to analyze data. This study found that academic resilience and LMS use intensity are both positively and significantly associated with academic flow in university students who use LMS. Furthermore, the current research results show that academic self-efficacy is not directly related to academic flow among university students. Aside from that, the study's findings imply that LMS usage intensity is a deciding variable for academic flow among university students who use LMS and that it can control the link between academic self-efficacy, academic resilience, and academic flow. Academic resilience and LMS use intensity must be considered when improving university students' academic flow using LMS.

Keywords


Flow academic; academic self-efficacy; academic resilience; Learning Management System (LMS)

Full Text:

PDF

References


Y. Siron, A. Wibowo, and B. S. Narmaditya, “Factors affecting the adoption of e-learning in Indonesia: Lesson from Covid-19,” J. Technol. Sci. Educ., vol. 10, no. 2, p. 282, Sep. 2020, doi: 10.3926/jotse.1025.

E. Purwanto and H. Tannady, “The factors affecting intention to use Google Meet amid online meeting platforms competition in Indonesia,” Technol. Reports Kansai Univ., vol. 62, no. 06, pp. 2829–2838, 2020, [Online]. Available: https://s.id/1TIq2

J. F. Kalolo, “Digital revolution and its impact on education systems in developing countries,” Educ. Inf. Technol., vol. 24, pp. 345–358, 2019, doi: https://doi.org/10.1007/s10639-018-9778-3.

G. J. Hwang, C. L. Lai, and S. Y. Wang, “Seamless flipped learning: a mobile technology-enhanced flipped classroom with effective learning strategies,” J. Comput. Educ., vol. 2, pp. 449–473, 2015, doi: https://doi.org/10.1007/s40692-015-0043-0.

A. Aldiab, H. Chowdhury, A. Kootsookos, F. Alam, and H. Allhibi, “Utilization of Learning Management Systems (LMSs) in higher education system: A case review for Saudi Arabia,” Energy Procedia, vol. 160, pp. 731–737, Feb. 2019, doi: 10.1016/j.egypro.2019.02.186.

I. B. K. Widiartha, J. Hwang, H. Yoon, and O. N. Pratiwi, “Analysis of Resilience of Education System in Higher Education Due to Covid-19 Pandemic in Indonesia: A Systematic Literature Review,” JOIV Int. J. Informatics Vis., vol. 7, no. 2, p. 439, May 2023, doi: 10.30630/joiv.7.2.1814.

N. Adzharuddin, “Learning Management System (LMS) among University Students: Does It Work?,” Int. J. e-Education, e-Business, e-Management e-Learning, 2013, doi: 10.7763/IJEEEE.2013.V3.233.

L. Tobarra, A. Robles-Gómez, S. Ros, R. Hernández, and A. C. Caminero, “Analyzing the students’ behavior and relevant topics in virtual learning communities,” Comput. Human Behav., vol. 31, pp. 659–669, Feb. 2014, doi: 10.1016/j.chb.2013.10.001.

V. Bradley, “Learning Management System (LMS) use with online instruction,” Int. J. Technol. Educ., vol. 4, no. 1, pp. 68–92, 2021, [Online]. Available: https://eric.ed.gov/?id=EJ1286531

D. Taylor, J. Grant, H. Hamdy, L. Grant, H. Marei, and M. Venkatramana, “Transformation to learning from a distance,” MedEdPublish, vol. 9, p. 76, Apr. 2020, doi: 10.15694/mep.2020.000076.1.

W. L. Wong and K. A. Yuen, “Online Learning Stress and Chinese College Students’ Academic Coping during COVID-19: The Role of Academic Hope and Academic Self-Efficacy,” J. Psychol., vol. 157, no. 2, pp. 95–120, Feb. 2023, doi: 10.1080/00223980.2022.2148087.

E. Aprianto, O. Purwati, and S. Anam, “Multimedia-Assisted Learning in a Flipped Classroom: A Case Study of Autonomous Learning on EFL University Students,” Int. J. Emerg. Technol. Learn., vol. 15, no. 24, p. 114, Dec. 2020, doi: 10.3991/ijet.v15i24.14017.

D. Urhahne and L. Wijnia, “Theories of Motivation in Education: An Integrative Framewor,” Educ. Psychol. Rev., vol. 35, no. 2, p. 45, 2023, doi: https://doi.org/10.1007/s10648-023-09767-9.

J. Nakamura, C. Dwight, and S. Shankland, “The experience of intrinsic motivation,” Oxford Handb. Hum. Motiv., vol. 169, 2019, [Online]. Available: https://s.id/1TInD

S. Abuhamdeh, “Flow Theory and Cognitive Evaluation Theory: Two Sides of the Same Coin?,” in Advances in Flow Research, Cham: Springer International Publishing, 2021, pp. 137–153. doi: 10.1007/978-3-030-53468-4_5.

A. S. Waterman and S. J. Schwartz, “Identity Contributions to a Life Well-Lived: A Study of the Relationship of Eudaimonic Well-Being to Intrinsic Motivation for Identity-Related Activities,” Identity, pp. 1–15, Jul. 2023, doi: 10.1080/15283488.2023.2233990.

P. Patel and R. K. Lodhwal, “Dimensions of flow experience in information and communication technology-based learning,” Int. J. Indian Cult. Bus. Manag., vol. 26, no. 4, p. 505, 2022, doi: 10.1504/IJICBM.2022.125213.

Y. Wang, Y. Cao, S. Gong, Z. Wang, N. Li, and L. Ai, “Interaction and learning engagement in online learning: The mediating roles of online learning self-efficacy and academic emotions,” Learn. Individ. Differ., vol. 94, p. 102128, Feb. 2022, doi: 10.1016/j.lindif.2022.102128.

R. D. Suryaratri, G. Komalasari, and G. I. Medellu, “The Role of Academic Self-Efficacy and Social Support in Achieving Academic Flow in Online Learning,” Int. J. Technol. Educ. Sci., vol. 6, no. 1, pp. 164–177, 2022, [Online]. Available: https://eric.ed.gov/?id=EJ1334735

A. A. Alazzam, N. F. Alhamad, A. A. H. Alhassan, and M. A. Rababah, “Psychological Flow and Academic Self-Efficacy in Coping with Online Learning during COVID-19 Pandemic,” J. Hunan Univ. Nat. Sci., vol. 48, no. 11, 2021, [Online]. Available: http://jonuns.com/index.php/journal/article/view/847/841

Y. Guo et al., “Mental Health Disorders and Associated Risk Factors in Quarantined Adults During the COVID-19 Outbreak in China: Cross-Sectional Study,” J. Med. Internet Res., vol. 22, no. 8, p. e20328, Aug. 2020, doi: 10.2196/20328.

Y. Mao, R. Yang, M. Bonaiuto, J. Ma, and L. Harmat, “Can Flow Alleviate Anxiety? The Roles of Academic Self-Efficacy and Self-Esteem in Building Psychological Sustainability and Resilience,” Sustainability, vol. 12, no. 7, p. 2987, Apr. 2020, doi: 10.3390/su12072987.

N. Ainiyah et al., “Emotional Intelligence and Self-efficacy as Predictor Factors of Student Resilience in Online Learning during Pandemic Era,” Open Access Maced. J. Med. Sci., vol. 9, no. T5, pp. 40–43, Dec. 2021, doi: 10.3889/oamjms.2021.7854.

J. W. Creswell, Research Design: Qualitatives, Quantitative, and Mixed. USA: Sage, 2014.

E. Seeram, “An overview of correlational research,” Radiol. Technol., vol. 91, no. 2, pp. 176–179, 2019, [Online]. Available: http://www.radiologictechnology.org/content/91/2/176.extract

I. Ghozali and H. Latan, Partial Least Squares: Konsep, Teknik dan Aplikasi Menggunakan Program SmartPLS 3.0. Semarang: Badan Penerbit Universitas Diponegoro, 2015.

A. H. Putra and R. Ahmad, “Improving Academic Self Efficacy in Reducing First Year Student Academic Stress,” J. Neo Konseling, vol. 2, no. 2, May 2020, doi: 10.24036/00282kons2020.

L. Erlina, A. Waluyo, D. Irawaty, J. Umar, and D. Gayatri, “Instrument development and validation: Assessment of self efficacy for mobilization,” Enfermería Clínica, vol. 29, pp. 384–389, Sep. 2019, doi: 10.1016/j.enfcli.2019.04.048.

S. Cassidy, “The Academic Resilience Scale (ARS-30): A New Multidimensional Construct Measure,” Front. Psychol., vol. 7, Nov. 2016, doi: 10.3389/fpsyg.2016.01787.

Y. Hu, “Academic Resilience in Chinese EFL Classrooms: Relationship with Teacher Support Activities,” Front. Educ. Res., vol. 5, no. 5, 2022, doi: 10.25236/FER.2022.050507.

S. Butt, A. Mahmood, S. Saleem, T. Rashid, and A. Ikram, “Students’ Performance in Online Learning Environment: The Role of Task Technology Fit and Actual Usage of System During COVID-19,” Front. Psychol., vol. 12, Nov. 2021, doi: 10.3389/fpsyg.2021.759227.

T. Kirchhoff, C. Randler, and N. Großmann, “Experimenting at an outreach science lab versus at school—Differences in students’ basic need satisfaction, intrinsic motivation, and flow experience,” J. Res. Sci. Teach., Mar. 2023, doi: 10.1002/tea.21859.

J. J. F. Hair, G. T. M. Hult, C. M. Ringle, M. Sarstedt, and N. P. Danks, Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer Nature, 2021.

A. Afthanorhan, P. L. Ghazali, and N. Rashid, “Discriminant Validity: A Comparison of CBSEM and Consistent PLS using Fornell & Larcker and HTMT Approaches,” J. Phys. Conf. Ser., vol. 1874, no. 1, p. 012085, May 2021, doi: 10.1088/1742-6596/1874/1/012085.

J. Hair and A. Alamer, “Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example,” Res. Methods Appl. Linguist., vol. 1, no. 3, p. 100027, Dec. 2022, doi: 10.1016/j.rmal.2022.100027.

S. W. Vann and A. A. Tawfik, “Flow theory and learning experience design in gamified learning environments,” Learn. user Exp. Res., 2020, [Online]. Available: https://edtechbooks.org/ux/flow_theory_and_lxd/simple

M. A. Sahman, A. C. Cinar, I. Saritas, and A. Yasar, “Tree-seed algorithm in solving real-life optimization problems,” IOP Conf. Ser. Mater. Sci. Eng., vol. 675, no. 1, p. 012030, Nov. 2019, doi: 10.1088/1757-899X/675/1/012030.

F. Gunawan, R. Mayasari, W. Muna, and M. Masruddin, “No Title,” Arab World English J., vol. 10, no. 2, pp. 77–87, 2019, [Online]. Available: https://eric.ed.gov/?id=EJ1275232

Y.-H. Cheng, C.-C. Tsai, and J.-C. Liang, “Academic hardiness and academic self-efficacy in graduate studies,” High. Educ. Res. Dev., vol. 38, no. 5, pp. 907–921, Jul. 2019, doi: 10.1080/07294360.2019.1612858.

U. Mahmudah, M. S. Lola, S. Fatimah, and K. C. Suryandari, “Academic Resilience and Science Academic Emotion in Numeration under Online Learning: Predictive Capacity of an Artificial Neural Network,” J. Pendidik. IPA Indones., vol. 11, no. 4, pp. 542–551, Dec. 2022, doi: 10.15294/jpii.v11i4.39091.

R. Cubero-Pérez, M. Cubero, J. A. Matías-García, and M. J. Bascón, “Learner identity in secondary post-compulsory education students from Areas in Need of Social Transformation: an example of resilience,” Eur. J. Psychol. Educ., May 2023, doi: 10.1007/s10212-023-00704-6.

P. Bala and R. Verma, “Academic Resilience in Relation to Educational Aspirations among International Students,” Indian J. Public Heal. Res. Dev., vol. 10, no. 6, 2019, [Online]. Available: https://s.id/1TIlk

C. Agusta and R. D. Henderson, Student Academic Integrity in Online learning in higher education in the era of COVID-19. California: Informing Science Press, 2021.

B. Anthony et al., “Blended Learning Adoption and Implementation in Higher Education: A Theoretical and Systematic Review,” Technol. Knowl. Learn., vol. 27, no. 2, pp. 531–578, Jun. 2022, doi: 10.1007/s10758-020-09477-z.

D. Turnbull, R. Chugh, and J. Luck, “An Overview of the Common Elements of Learning Management System Policies in Higher Education Institutions,” TechTrends, vol. 66, no. 5, pp. 855–867, Sep. 2022, doi: 10.1007/s11528-022-00752-7.

C. B. Mpungose and S. B. Khoza, “Postgraduate Students’ Experiences on the Use of Moodle and Canvas Learning Management System,” Technol. Knowl. Learn., vol. 27, no. 1, pp. 1–16, Mar. 2022, doi: 10.1007/s10758-020-09475-1.

E. A. Pantu, “Online Learning: The Role Of Academic Self-Efficacy In Creating Academic Flow,” Psychol. Res. Interv., vol. 4, no. 1, pp. 1–8, Aug. 2021, doi: 10.21831/pri.v4i1.40381.

P. Abdolrezapour, S. Jahanbakhsh Ganjeh, and N. Ghanbari, “Self-efficacy and resilience as predictors of students’ academic motivation in online education,” PLoS One, vol. 18, no. 5, p. e0285984, May 2023, doi: 10.1371/journal.pone.0285984.

M. C. Sáiz-Manzanares, R. Marticorena-Sánchez, J. J. Rodríguez-Díez, S. Rodríguez-Arribas, J. F. Díez-Pastor, and Y. P. Ji, “Improve teaching with modalities and collaborative groups in an LMS: an analysis of monitoring using visualisation techniques,” J. Comput. High. Educ., vol. 33, no. 3, pp. 747–778, Dec. 2021, doi: 10.1007/s12528-021-09289-9.

M. F. Rice, “Special Education Teachers’ Use of Technologies During the COVID-19 Era (Spring 2020—Fall 2021),” TechTrends, vol. 66, no. 2, pp. 310–326, Mar. 2022, doi: 10.1007/s11528-022-00700-5.