Factors Affecting the Academic Achievement of First-year Nursing Students in the Cloud-based University Learning Model for Anatomy and Physiology
Keywords:
academic achievement, cloud university teaching, model anatomy and physiology courseAbstract
The Cloud University teaching model is a type of learning that requires the use of modern technology. Learners are able to study independently, a process where they analyze their learning needs, set goals, seek knowledge, and assess their learning outcomes on their own. This research aims to examine predictive relationships and is intended to study the factors that influence the academic performance of first-year nursing students using the Cloud University learning model, specifically in the Anatomy and Physiology course. The study population consisted of first-year nursing students and employed a simple random sampling method. A total of 137 students completed the questionnaire. The tool used was an online survey with a 5-point Likert scale. The validity was reviewed by three experts, showing a validity coefficient between 0.67 and 1.00, and the reliability coefficient was 0.99. The statistical methods used included descriptive statistics and multiple stepwise regression analysis.
The research findings indicate that the average scores for learner-related factors and learning support factors are at a moderate level, while the average scores for teaching-related factors and assessment factors are at a high level. When analyzing the factors influencing the academic performance of first-year nursing students using the Cloud University teaching format for anatomy and physiology, learner factors jointly predicted 21.40%. Therefore, the college should be prepared to ensure the students are well-equipped with devices for online learning before the course begins to help promote their confidence in their studies
Downloads
References
Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski RA, et al. A view of cloud computing. ACM Journals. 2010;53(4):50-8.
Panich V. Ways to create learning for students in the 21st century. Bangkok: Sodsri-Saridwong Foundation; 2012. (in Thai)
Boromarajonani College of Nursing Nakhon Si Thammarat. Bachelor of nursing science program, 2023. Faculty of Nursing, Praboromarajchanok Institute; 2023. (in Thai)
Uttra S, Taengphukieo R. To-on P. Self-assessment report measurement model for online learning during the COVID-19 pandemic. Journal of Humanities and Social Sciences Mahasarakham University 2023;42(4):632-46. (in Thai).
Alibak M, Talebi H, Neshat-Doost HT. Development and validation of a test anxiety inventory for online learning students. J Educ Online. 2019;16:16.
Saraburi G, Yeam G. Students’ attitudes towards e-learning and behavior of students due to use moodle program and the conclusions were that the students had attitudes towards online education at a good level and were willing to use online education at a good level. In: Rungsawanpoo D, editor. The 7th Aoademlo Metting National and International Conference; 2016 June 10; Suan Sunandha Rajabhat University, Bangkok; 2016;7(3):1-9. (in Thai)
Sabthanadon T. Factors affecting the teaching and learning management of online lessons at Nakhon Ratchasima Rajabhat University. Veridian E-Journal SU. 2011;4(1):652-63. (in Thai)
Wayo W, Charoennukul A, Kankaynat C, Konyai J. Online learning under the COVID-19 epidemic: concepts and applications of teaching and learning management. Regional Health Promotion Center 9 Journal. 2022;14(34):285-98. (in Thai)
Lamcahona T, Klinhom T, Thongdonngaw N, Sriruang L, Pradit R. Factors affect the achievement of online learning, case study: Phibunsongkhram Rajabhat University. Academy Journal of Northern. 2022;9(1):54-68. (in Thai)
Adithepsathit T, Adithepsathit U. Relationship between attitudes towards online learning and English learning achievement among students at Prince of Songkla University, Surat Thani Campus. Journal of Industrial Education. 2023;22(1):88-98. (in Thai)
Faul F, Erdfelder E, Lang AG, Buchner A. G*power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175-91.
Cohen J. Statistical power analysis for the behavioral sciences. (2ed). Hillsdale, NJ: Lawrence Erlbaum Associates; 1998.
Artiwitchayanon A, Srisopa P, Wacharasin C. Factors predicting nursing students’ learning outcomes through online learning during COVID-19 pandemic. Songklanagarind Journal of Nursing. 2022;42(2):85-97. (in Thai).
Best JW. Research in education. (3ed). Englewod Cliffs: Prentice-hall. 1981.
Niratechaphat W. Online study problems in higher education students. Journal of Humanities and Social Sciences Nakhonratchasima Rajabhat University. 2022;2(2):75-87. (in Thai)
Sawangsri B, Gerdpanya P. Study of the effectiveness of online learning and the academic achievement of undergraduate students. RMUTSB Acad J (Humanities and Social Sciences). 2021;6(2):273-90. (in Thai)
Jantakeeree T. Online instructional management in the digital era. Journal of Modern Learning Development. 2022;7(10):349-63. (in Thai)
Pakdeeteva S, Bangthamai E. New era learning and online instruction in higher education institutions. Sukhothai Thammathirat Open University Journal. 2021;34(1):1-18. (in Thai)
Uttra S, Taengphukieo R. Factors influencing midterm achievement and psychological motivation for online learning using multiple regression analysis. Kalasin University Journal of Humanities Social Sciences and Innovation. 2024;3(1):97-111. (in Thai).
Yuktananda T. A study of factors affecting the achievement of online learning of students under the spread of the COVID-19 virus. Journal of MCU Peace Studies. 2022;10(2):509-22. (in Thai)
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of Nursing and Therapeutic Care
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
