A Conjoint Analysis Approach, Implications, and Mitigation Plans in Analyzing Students' Preferences for Online Learning Delivery Types during the COVID-19 Pandemic for Engineering Students: A Case Study in the Philippines

Traditional face-to-face classes were replaced with online learning when the COVID-19 pandemic happened. Students were unfamiliar with the virtual setup, as well as the technological challenges, which led to dissatisfaction and affected their academic performance. This research study surveyed 230 engineering students and applied conjoint analysis to analyze their preferences in online learning delivery. Using SPSS Statistics software, we revealed the top three attributes for delivery type: interaction, flexibility, and proctored exam. In addition, the most favored combination from the generated stimuli was a form of blended mode delivery. The synchronous meetings and asynchronous activities allowed students to manage their time efficiently. It could be deduced from the findings that students highly preferred the combination considering learner-instructor, live chats, real-time lecture meetings, and automatic availability, with a focus on synchronous online learning modes. Higher education institutions may reflect on the results of this study to reassess the online learning environment they implement among students. Incorporating a student's learning style to determine the relationship between their preference for online learning delivery type will be helpful for further research through application and study extension. It is suggested that the perceptions of instructors and students enrolled under different learning modalities and their effectiveness should also be addressed. This is a recommendation for future research to consider. Especially near the end of the COVID-19 pandemic, traditional face-to-face learning was being implemented. Thus, future studies may want to consider an analysis of the behavioral intentions of students. On the other hand, analyses such as student behavioral intentions for the future applications of the different modalities and comparisons thereof may be conducted to enhance the implications for, policies of, and strategies of universities.

Factors Influencing Intention to Enroll in The Online Academic Year among Undergraduate Students in the Philippines during the COVID-19 Pandemic

The COVID-19 pandemic has resulted in the loss of the number of enrollees at universities in many developing countries, including the Philippines. The current study integrated the Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) to determine factors affecting intention to enroll in the online academic year among undergraduate students during the COVID-19 pandemic. 370 Filipino undergraduate students filled the online survey, which contained 71 questions. The Structural Equation Modeling (SEM) indicated that attitude, subjective norms, and perceived behavioral control had significant direct effects on perceived usefulness which subsequently led to an engagement. Regarding the perceived ease of use, SEM indicated that it had a significant direct effect on perceived performance. Furthermore, SEM also indicated that perceived performance and engagement had significant direct effects on perceived effectiveness which subsequently led to the intention to enroll. The integrated TPB and extended TAM can be extended and applied in evaluating the behavioral motives of students to enroll in the online academic year globally that are currently affected by the COVID-19 pandemic. © 2022 ACM.

The Impact of the COVID-19 Pandemic on the Organizational Commitment in Semiconductor Industry: The Mediator Effect of the Job Satisfaction

Due to the COVID-19 pandemic, employees are required to respond to changes and conform to stringent safety laws and regulations. This study aimed to analyze the impact of the COVID-19 pandemic on the organizational commitment among employees in the semiconductor industry. A total of 272 employees working in the semiconductor industry answered a self-administered questionnaire that considered 51 questions, distributed online. Utilizing Structural equation modeling (SEM), the results showed that the COVID-19 was found to have a significant direct effect on employees' perceived job outcomes (PO) and a negative direct effect on job demands (JD). Moreover, PO had a positive effect on job motivation (JM) and job satisfaction (JS). Subsequently, JM presented a significant positive direct effect on JS, while JD showed a negative effect on JS. Lastly, JS showed a significant positive direct effect on organizational commitment (OC). Intriguingly, an indirect effect of PO on JS was seen. This study is one of the first studies that analyzed the organization commitment among semiconductor workers during the COVID-19 pandemic. This paper could be utilized as a foundation to enhance organizational commitment, particularly in the semiconductor industry worldwide. © 2022 IEEE.

Determining Factors Affecting Customer Loyalty to Internet Service Provider during the COVID-19 Pandemic: A Structural Equation Modeling Approach

Internet Service Provider (ISP) has been a critical aspect during the COVID-19 pandemic especially in developing countries such as Indonesia. The purpose of this study was to determine factors affecting customer loyalty to ISP in Indonesia during the COVID-19 pandemic by utilizing a structural equation modeling (SEM) approach. There were 252 respondents who voluntarily answered an online questionnaire which consisted of 49 questions that covered several factors such as Customer Service Performance (CSP), Internet Quality (IQ), Router Quality (RQ), Payment Method (PM), Internet Package (IP), Security & Privacy (SP), Promotion (P), COVID-19 impact (CV), Customer Satisfaction (CS), and Customer Loyalty (CL). SEM showed that IQ was found to have the highest effect on CS which subsequently led to CL, followed by SP, CSP, RQ, and PM. This study is one of the first studies that explored customer loyalty to Internet Service Providers during the COVID-19 pandemic. The SEM construct can be applied and extended to enhance customer satisfaction on ISP particularly in developing countries. © 2022 IEEE.

Factors Affecting Students’ Happiness on Online Learning during the COVID-19 Pandemic: A Self Determination Theory Approach

Happiness is a debatable concept as it is a term without any exact or precise way of measurement and evaluation and the current COVID-19 pandemic has affected the students with their happiness leading to a decrease in learning. The present study aimed to determine the factors that affect the students’ happiness during online learning brought by the COVID-19 pandemic. 622 senior high school students who underwent online learning were given a questionnaire composed of 45 questions grouped into 10 factors under autonomy, competence, and relatedness that were based on the self-determination theory. Structural Equation Modeling (SEM) was utilized in this research to determine the causal relationships between latent variables construct. SEM showed that autonomy was the most significant factor to students’ happiness because students can cope with the current COVID-19 pandemic. The second variable was relatedness because continuous communication and support are evident among respondents. Lastly, competence was found to be a negative predictor because students are knowledgeable when it comes to the current state of the COVID-19 pandemic. As the first study that utilized the self-determination theory approach in the happiness context during the COVID-19 pandemic, the study can provide areas for better innovation in online learning given that there is no definite timeline for this pandemic. Moreover, the education sector may take into consideration students’ autonomy and relatedness to help increase happiness leading to satisfaction and continue online learning despite the COVID-19 pandemic. © 2022 by the authors.