CONTEXT: Learning in the medical school of the study university is still by the traditional face-to-face approach with minimal e-communication. AIM: This paper assesses student's perspectives of E-learning readiness, its predictors and presents a model for assessing them. SETTINGS AND DESIGN: A descriptive cross-sectional study of medical students. SUBJECTS AND METHODS: By proportional quota sampling 284 students responded to a semi-structured self-administered questionnaire adapted from literature. Ethical issues were given full consideration. STATISTICAL ANALYSIS USED: Analysis was with SPSS version 20, using descriptive statistics, ANOVA, Spearman's correlation, and multiple regression. Statistical significance was considered at P < 0.05. RESULTS: Medical students are ready for E-learning (Mlr = 3.8 > Melr = 3.4), beyond reliance on the face-to-face approach (69.7%), expecting effective (51.1%), and quality improvement in their learning (73.1%). Having basic information and communications technology skills (68.9%) (Mict = 3.7 > Melr = 3.4), access to laptops (76.1%), ability to use web browsers confidently (91.8%) (Mwb = 4.3 > Melr = 3.4), with only few able to use asynchronous tools (45.5%), they consider content design important to attract users (75.6%), and agree they need training on E-learning content (71.4%). They however do not believe the university has enough information technology infrastructure (62.4%) (Mi = 2.7 < Melr = 3.4) nor sufficient professionals to train them (M = 2.9). Predictors are attitude, content readiness, technological readiness, and culture readiness. The model however only explains 37.1% of readiness in the population. CONCLUSIONS: Medical students in this environment are ready to advance to E-learning. Predicted by their attitude, content, technological and cultural readiness. Further study with qualitative methodology will help in preparing for this evolution in learning.
CONTEXT: Learning in the medical school of the study university is still by the traditional face-to-face approach with minimal e-communication. AIM: This paper assesses student's perspectives of E-learning readiness, its predictors and presents a model for assessing them. SETTINGS AND DESIGN: A descriptive cross-sectional study of medical students. SUBJECTS AND METHODS: By proportional quota sampling 284 students responded to a semi-structured self-administered questionnaire adapted from literature. Ethical issues were given full consideration. STATISTICAL ANALYSIS USED: Analysis was with SPSS version 20, using descriptive statistics, ANOVA, Spearman's correlation, and multiple regression. Statistical significance was considered at P < 0.05. RESULTS: Medical students are ready for E-learning (Mlr = 3.8 > Melr = 3.4), beyond reliance on the face-to-face approach (69.7%), expecting effective (51.1%), and quality improvement in their learning (73.1%). Having basic information and communications technology skills (68.9%) (Mict = 3.7 > Melr = 3.4), access to laptops (76.1%), ability to use web browsers confidently (91.8%) (Mwb = 4.3 > Melr = 3.4), with only few able to use asynchronous tools (45.5%), they consider content design important to attract users (75.6%), and agree they need training on E-learning content (71.4%). They however do not believe the university has enough information technology infrastructure (62.4%) (Mi = 2.7 < Melr = 3.4) nor sufficient professionals to train them (M = 2.9). Predictors are attitude, content readiness, technological readiness, and culture readiness. The model however only explains 37.1% of readiness in the population. CONCLUSIONS: Medical students in this environment are ready to advance to E-learning. Predicted by their attitude, content, technological and cultural readiness. Further study with qualitative methodology will help in preparing for this evolution in learning.
Entities:
Keywords:
Assessment; E-learning; medical students; readiness
Authors: Weijie Xing; Linjun Ao; Huiting Xiao; Li Cheng; Yan Liang; Junqiao Wang Journal: Int J Environ Res Public Health Date: 2018-07-15 Impact factor: 3.390