Role of E-Learning Readiness on Workload: Perspective Engineering and Non-Engineering Students - Litasari W. Suwarsono; Atya N. Aisha; Fida N. Nugraha (International Journal of Innovation in Enterprise System, 2022)
Changes in learning methods from face-to-face to online learning due to pandemic covid19 have an impact on student readiness in learning and the mental workload felt by students,that can determine the achievement of the learning process. There are differences in thecharacteristics of learning demands in engineering and non-engineering majors. Therefore,this study aims to evaluate the level of readiness and mental workload of students duringthe implementing full online learning based on the characteristics of the educationdepartment. Data collected by distributing online questionnaires to 180 students (90students majoring in engineering and 90 students in non-engineering). Self-directedlearning (SDL), technical readiness (TC), and comfort with non-face to face communication(CFT) used to measure e-learning readiness, meanwhile NASA TLX used to measuremental workload. Results showed differences between engineering and non-engineeringstudents, especially in the Self-Directed Learning (p < 0,05). Non-engineering studentsperceived that they are more prepared to manage their learning process independentlyduring online learning. Related to mental workload students perceive higher demands fromonline learning activities, the engineering group had higher level of time-related demands.According to correlation testing there was a negative and significant correlation betweenthe self-directed learning dimension scores of E-Learning Readiness and the NASA TLXscores (p < 0,05). These results indicated the role of student’s e-learning readiness,especially self-directed learning readiness can reduce perceptions related to the mentalworkload experienced by engineering students in online learning. This condition was notapplied on non-engineering students. Future study needed to explore the characteristics ofstudy programs that relate to both variables and if the condition applied on other learningconditions such as hybrid learning.