Predicting factors influencing perceived online learning experience among primary students utilizing structural equation modeling Forest Classifier approach.

Introduction: Amid the COVID-19 pandemic, the temporary closure of educational institutions led to the adoption of remote or online learning delivery. Challenges, especially for grade schools were evident. Objective: This study aimed to identify factors affecting the perceived online discussion experience of Filipino primary students through distance learning in the National Capital Region, Philippines. Method: Variables such as cognitive presence, teaching presence, social presence, and online discussion experience were investigated simultaneously by utilizing the structural equation modeling (SEM) and random forest classifier (RFC) approach. A total of 385 currently enrolled Filipino grade school student participants were surveyed. Results: Results show that cognitive presence has the most significant impact on the perceived online discussion experience, followed by teaching presence, and social presence. This study is the first study that analyzed the online discussion experience among grade school students in online education in the Philippines considering SEM and RFC. It was seen that highly significant factors such as teaching presence, cognitive presence, social presence, triggering events, and exploration will lead to high and very high learning experience with grade school students. Conclusion: The findings of this study would be significant for teachers, educational institutions, and government agencies to improve the online delivery of primary education in the country. In addition, this study presents a reliable model and results which can be extended and applied for academicians, educational institutions, and the education sector to develop ways in enhancing the online delivery of primary education worldwide.

Introduction: Au milieu de la pandémie de COVID-19, la fermeture temporaire des établissements d'enseignement a conduit à l'adoption de la prestation d'apprentissage à distance ou en ligne. Les défis, en particulier pour les écoles primaires, étaient évidents. Objectif: Cette étude visait à identifier les facteurs affectant l'expérience de discussion en ligne perçue des élèves philippins du primaire par le biais de l'apprentissage à distance dans la région de la capitale nationale, aux Philippines. Méthode: Des variables telles que la présence cognitive, la présence dans l'enseignement, la présence sociale et l'expérience de discussion en ligne ont été étudiées simultanément en utilisant l'approche de structural equation modeling (SEM) et de Random Forest classifier (RFC). Un total de 385 élèves philippins actuellement inscrits à l'école primaire ont été interrogés. Résultats: Les résultats montrent que la présence cognitive a l'impact le plus significatif sur l'expérience de discussion en ligne perçue, suivie de la présence pédagogique et de la présence sociale. Cette étude est la première étude qui a analysé l'expérience de discussion en ligne parmi les élèves du primaire dans l'éducation en ligne aux Philippines en tenant compte du SEM et du RFC. Il a été constaté que des facteurs très importants tels que la présence d'enseignement, la présence cognitive, la présence sociale, les événements déclencheurs et l'exploration conduiront à une expérience d'apprentissage élevée et très élevée avec les élèves du primaire. Conclusion: En outre, cette étude présente un modèle et des résultats fiables qui peuvent être étendus et appliqués aux universitaires, aux établissements d'enseignement et au secteur de l'éducation afin de développer des moyens d'améliorer la prestation en ligne de l'enseignement primaire dans le monde entier.

Evaluating factors influencing customers' intention to eat Korean cuisine "Samgyeopsal" in the Philippines: A structural equation model forest classifier approach.

Samgyeopsal has become a widely popular cuisine in the Philippines since 2014. The rise of Samgyeopsal is evident worldwide as it is available in countries such as the United States, Northern, and Southern Asia. This study aimed to explore the intention to eat Samgyeopsal during the COVID-19 pandemic utilizing structural equation modeling and random forest classifier. With a total of 1014 responses collected online, the result showed that utilitarian and hedonic motivation, Korean influence, and attitude led to very high actual behavior in east Samgyeopsal in the Philippines. Moreover, subjective norm, perceived behavioral control, and intention led to significant results influencing intention to actual behavior. Lastly, the COVID-19 safety protocol showed the least significant result. This study is the first study that evaluated the intention of consumers to eat Samgyeopsal in the Philippines during the COVID-19 pandemic. The results of this study would be beneficial to Korean BBQ restaurateurs and the further development of their marketing strategies even in other countries. Finally, the model construct of this study can be extended and applied in evaluating the consumers' eating intention toward other varieties of food or cuisines worldwide.

Consumer preference analysis on the attributes of samgyeopsal Korean cuisine and its market segmentation: Integrating conjoint analysis and K-means clustering.

Samgyeopsal is a popular Korean grilled dish with increasing recognition in the Philippines as a result of the Hallyu. The aim of this study was to analyze the preferability of Samgyeopsal attributes which includes the main entree, cheese inclusion, cooking style, price, brand, and drinks using Conjoint Analysis and market segmentation using k-means clustering. A total of 1018 responses were collected online through social media platforms by utilizing a convenience sampling approach. The results showed that the main entrée (46.314%) was found to be the most important attribute, followed by cheese (33.087%), price (9.361%), drinks (6.603%), and style (3.349%). In addition, k-means clustering identified 3 different market segments: high-value, core, and low-value consumers. Furthermore, this study formulated a marketing strategy that focused on enhancing the choice of meat, cheese, and price based on these 3 market segments. This study has significant implications for enhancing Samgyeopsal chain businesses and helping entrepreneurs with consumer preference on Samgyeopsal attributes. Finally, conjoint analysis with k-means clustering can be utilized and extended for evaluating food preferences worldwide.

Investigating Preceding Determinants Affecting Primary School Students Online Learning Experience Utilizing Deep Learning Neural Network

The pandemic has caused all of the programs that are offered in primary schools to be interrupted. Evaluating the student's learning at this level is essential because education development throughout the epidemic is critical, as there was no other educational alternative available during the pandemic. This study examines the use of deep learning neural network (DLNN) to evaluate the parameters influencing primary school students' online learning experiences during the COVID-19 pandemic. The researchers considered this issue since primary students' online learning experiences needed more attention. To carefully analyze the relationships between the parameters of primary students' learning experience, an online questionnaire was utilized, subject to parents' participation. A total of 385 Filipino elementary school students were selected and surveyed using a purposive sampling method. Participants in this research ranged in age from seven to thirteen and were supervised by their parents or legal guardians. The result of the study showed that open communication, social presence, design and organization, and facilitation had the most impact on predicting students' experiences with online education, having a high accuracy from DLNN of 96.12%. This demonstrates the significance of open communication, draws attention to the importance of helping students feel welcomed and appreciated, and demonstrates the influence that instructors have on the overall positive learning experiences of their students. Finally, the findings of this study gave a strong framework and clear conclusions that both schools and the government's education department could use to improve the way primary education is taught online across the country. Finally, the results and findings of this study could be applied and extended to other related education studies worldwide.

Classification modeling of intention to donate for victims of Typhoon Odette using deep learning neural network.

The need for stability in the economy for world development has been a challenge due to the COVID-19 pandemic. In addition, the increase of natural disasters and their aftermath have been increasing causing damages to infrastructure, the economy, livelihood, and lives in general. This study aimed to determine factors affecting the intention to donate for victims of Typhoon Odette, a recent super typhoon that hit the Philippines leading to affect 38 out of 81 provinces of the most natural disaster-prone countries. Determining the most significant factor affecting the intention to donate may help in increasing the engagement of donations among other people to help establish a more stable economy to heighten world development. With the use of deep learning neural network, a 97.12% accuracy was obtained for the classification model. It could be deduced that when donors understand and perceive both severity and vulnerability to be massive and highly damaging, then a more positive intention to donate to victims of typhoons will be observed. In addition, the influence of other people, the holiday season when the typhoon happened, and the media as a platform have greatly contributed to heightening the intention to donate and control over the donor's behavior. The findings of this study could be applied and utilized by government agencies and donation platforms to help engage and promote communication among donors. Moreover, the framework and methodology considered in this study may be extended to evaluate intention, natural disasters, and behavioral studies worldwide.

Determination of Factors Influencing the Behavioral Intention to Play 'Mobile Legends: Bang-Bang', during the COVID-19 Pandemic: Integrating UTAUT2 and System Usability Scale for a Sustainable E-Sport Business

The rise of mobile games during the COVID-19 pandemic era was evident, especially in Asia. One of the most popular online mobile games that has been evident across the world due to its live worldwide competition is 'Mobile Legends: Bang Bang';(MLBB). This study aimed to determine factors influencing the behavioral intention to play MLBB by utilizing the integrated model of UTAUT2 and System Usability Scale (SUS). A total of 507 MLBB players voluntarily answered an online questionnaire that consisted of 69 items. Through convenience sampling, the online survey was collected from November 2021-January 2022 from different social media platforms. Several factors such as hedonic motivation, effort expectancy, performance expectancy, perceived usefulness, security, perceived usability, facilitating conditions, social influence, habit, behavioral intention, and SUS were considered in this study. Using Structural Equation Modeling (SEM), results showed that habit was the most significant factor in behavioral intention, followed by perceived usability, facilitating conditions, social influence, and hedonic motivation. In addition, it was evident from the results that when the mobile application is free and resources are available, then continuous patronage of the mobile application will be considered. In-game resources may be capitalized on by developers after gaining these habits and hedonic motivations among users. This is the first study that evaluated MLBB by utilizing the integrated models of UTAUT2 and SUS during the COVID-19 pandemic. The results of this study could be beneficial for developers to entice users for team play and entertainment-based mobile applications. Finally, the model considered may be extended and applied to other mobile applications worldwide.

Using Online Grocery Applications during the COVID-19 Pandemic: Their Relationship with Open Innovation

This present research examines the behavioral intentions of Filipinos to use online grocery applications during the novel COVID-19 pandemic. The study proposes an integration of the health belief model (HBM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) to identify the factors affecting the acceptance and usage of Filipinos of online grocery applications in terms of the impact of health risk for COVID-19. To accurately measure the factors and their relationship to behavioral intentions and usage behavior, a questionnaire was developed and distributed to 373 residents in the Philippines. Partial least squares structural equation modeling (PLS-SEM) was applied as an analytical method for this study. The results revealed that performance expectancy, perceived benefits, perceived severity, and cues to action significantly influenced the behavioral intentions and usage of online grocery apps during the COVID-19 pandemic. The study's findings can be utilized as a theoretical framework for future researchers of consumer behavior;e-commerce developers;and grocery industry retailers, to enhance the innovation and services of online grocery applications. The results of this study may also be used and capitalized on by investors and managers to apply in strategizing when developing and marketing online grocery applications among consumers. Moreover, the framework of this study may be adopted and utilized by other online markets, even in different counties. Further theoretical and practical aspects are discussed in this paper.

Determination of factors influencing young adults' intention to have COVID-19 vaccine in the Philippines: An integration of Health Belief Model and the Theory of Planned Behavior.

Objectives: The COVID-19 pandemic continues to increase around the world and businesses and markets across the world significantly decreased. The purpose of this study was to determine the factors that affect the intention to be vaccinated for the COVID-19 vaccine among young Filipino adults by integrating the Health Belief Model and Extended Theory of Planned Behavior. Study design: A cross-sectional study design was utilized. Methods: Factors such as understanding of the COVID-19 vaccine, self-efficacy, cues to action, perceived barriers, perceived benefits, perceived side effects, perceived behavioral control, attitude, subjective norm, and intention to be vaccinated were analyzed by utilizing Structural Equation Modeling (SEM). Results: With 865 young Filipino adults who answered a self-administered survey, it was seen that Understanding of the COVID-19 vaccine has the highest direct significant effect on cues to action, followed by perceived barriers, and perceived benefits. Interestingly, the primary factor was Understanding COVID-19 vaccines which had an indirect significant effect on the intention to get vaccinated. This is because knowing what the vaccine is for, its effects, and the application would lead to the acceptance of the COVID-19 vaccine. Moreover, the impact of being known to have the COVID-19 vaccine would lead to the intention to get vaccinated. Conclusions: The findings of this study can be utilized especially by the government in developing strategies for encouraging people to take the COVID-19 vaccine. Finally, the model construct of the study can be applied to explore more factors that can affect the intention to be vaccinated with the COVID-19 vaccine and other vaccines people worldwide.

Evaluating the influence of service quality, hedonic, and utilitarian value on shopper's behavioral intentions in urban shopping malls during the COVID-19 pandemic.

Shopping malls are subjected to a lot of changes during the COVID-19 pandemic, especially in the Philippines. The objective of the study was to evaluate the influence of service quality, hedonic, and utilitarian value of malls on shopping mall goers' behavioral intentions during the COVID-19 pandemic. SERVQUAL five dimensions were utilized to represent the service quality aspect, while utilitarian and hedonic values are used to embody the shopping mall values among Filipino citizens. Additionally, we included convenience and social experience as part of our model, to which relationships were assessed toward the utilitarian and hedonic shopping mall values, respectively. An online survey was distributed and collected 519 valid responses among Filipino shopping mall goers. Using Structural Equation Modeling (SEM), results showed that for service quality aspect, tangibles, empathy, and assurance had significant effects on shopper's shopping mall satisfaction during the COVID-19 pandemic. On the other hand, both shopping mall values present positive effects on shopper's satisfaction on which utilitarian value gave the strongest influence in the overall model, followed by the hedonic value. Convenience and social experience also showed positive effects on utilitarian and hedonic values, respectively. The utilized extended framework from SERVQUAL dimensions and hedonic and utilitarian values to measure satisfaction and behavioral intentions was seen to be applicable to measure human behavior and lifestyle studies. Overall, the satisfaction from both service quality and shopping mall values aspect strongly influences shoppers' behavioral intention in going to the mall.

Plantitas/Plantitos Preference Analysis on Succulents Attributes and Its Market Segmentation: Integrating Conjoint Analysis and K-means Clustering for Gardening Marketing Strategy

Many people have switched to gardening as their new hobby during the COVID-19 pandemic, including Filipinos. With its increasing popularity, Filipinos called the new hobbyists 'plantitas';and 'plantitos';instead of the old-fashioned term 'plant people';. Among different plants, succulents are one of the most popular for plant lovers as they can thrive with even minimal care, making them suitable to be an indoor/outdoor plant. This study aims to determine the various preferences of plantitas and plantitos based on succulent attributes using a conjoint analysis approach, and to discover the market segments using a k-means clustering approach. The attributes presented in this study are the types of succulents, succulent variegation, price, size of the succulent (in terms of diameter), size of the pot, pot material, and payment method. The conjoint analysis results indicated that the price was the attribute that significantly affected consumer buying behavior, followed by the diameter size of the succulent. On the other hand, the k-means cluster analysis identified three customer segments based on the buying frequency of customers, namely high-value customers, core-value customers, and lower-value customers. A marketing strategy for succulent sellers was proposed based on these segmentations, particularly on how to gain and attract more customers. This study is one of the first studies that analyzed the preferences related to succulent attributes. Finally, the conjoint analysis approach and k-means clustering in this study can be utilized to analyze succulent preferences worldwide.

Choosing a package carrier during COVID-19 pandemic: An integration of pro-environmental planned behavior (PEPB) theory and service quality (SERVQUAL).

Sustainability and safety have become the two most important considerations of consumers of the current century. The limited movement of consumers and significant shift to online business as effects of the current health pandemic led to an increased demand for package delivery services worldwide. This study investigated the factors that influence the intention of consumers in the Philippines to choose a package delivery or carrying service during the COVID-19 pandemic using the integrated pro-environmental planned behavior (PEPB) theory and service quality (SERVQUAL). An online questionnaire was distributed as the instrument data collection, and 400 respondents who have utilized the package delivery service during the pandemic participated in the study. The theoretical model was examined using the partial least square structural equation modeling (PLS-SEM) with higher-order constructs. Testing the different parameters of structural model, measurement model, and the model fit presented values within the threshold. Moreover, the HTMT and Fornell & Larcker discriminant validity analysis was performed to determine the overall fit of the constructs of the model. These tests demonstrated the acceptability of the model. The findings revealed that perceived environmental concern, perceived authority support, subjective norm, attitude, service quality, customer perceived value, and customer satisfaction significantly influence the consumer's intention to choose a package delivery service during the pandemic. The consumers' perception of pro-environmental activities was also an essential contributor since perceived environmental concern and perceived authority support indirectly affect behavior intention. The findings contribute to developing and validating an integrated model on sustainability and service quality in package delivery services. The study also provides suggestions to service providers to ensure quality and safety on package delivery during the pandemic.

Determining factors affecting customer satisfaction of the national electric power company (MERALCO) during the COVID-19 pandemic in the Phillippines.

This study aimed to determine factors affecting customer satisfaction of national electric power companies during the COVID-19 pandemic by integrating SERVQUAL and Expectation-Confirmation Theory approaches. A total of 529 participants voluntarily participated and answered an online questionnaire of 49 questions. Structural equation modeling indicated that Tangibility, Empathy, and Responsiveness were positively related to Service Quality which subsequently led to Customer Expectation, Energy Consumption, and Perceived Performance (PE). In addition, a higher PE was positively related to Confirmation, which eventually led to Customer Satisfaction. It was evident that integrating SERVQUAL and ECT could holistically measure customer satisfaction among electricity service providers.

Factors Affecting Customer Satisfaction in Fast Food Restaurant 'Jollibee' during the COVID-19 Pandemic

Jollibee is one of the most widely known fast food in Filipino-based restaurants in the world. However, the COVID-19 pandemic has impacted restaurants across the world. The decrease in profit and dividend, and even closure of branches were evident. This study aimed to determine the relationships between Jollibee's price, food quality, culture/social influence, and service quality through the SERVQUAL dimensions on customer satisfaction during the COVID-19 pandemic using the structural equation modeling (SEM) approach. A total of 303 respondents were recruited using a purposive sampling approach to answer an online survey through social media platforms. This study found that among the factors mentioned, responsiveness, reliability, and assurance dimensions yielded to be statistically insignificant to the service quality. Due to the normal attributes the staff and restaurant have, the different factors were deemed insignificant. At the same time, the service quality was observed to have the largest significant direct relationship with customer satisfaction, followed by the cultural influence, food quality, COVID-19 protocols, and pricing. It was also seen that cleanliness and appearance, empathetic staff, food quality, price, and proper implementation of COVID-19 protocol prevention would lead to high levels of satisfaction among customers in Jollibee fast-food restaurant. Moreover, cultural/social influence has played a big role seeing that the indicators represent the feeling of belongingness since childhood. This study is the first study that analyzed the factors affecting the customer satisfaction of Jollibee. Finally, this study could be used as a basis for fast-food companies and service-related industries to increase its performance by enhancing customer satisfaction worldwide.

Predicting factors affecting the intention to use a 3PL during the COVID-19 pandemic: A machine learning ensemble approach.

The COVID-19 pandemic had brought changes to individuals, especially in consumer behavior. As the government of different countries has been implementing safety protocols to mitigate the spread of the virus, people became apprehensive about traveling and going out. This paved way for the emergence of third-party logistics (3PL). Statistics have proven the rapid escalation regarding the use of 3PL in various countries. This study utilized Artificial Neural Network and Random Forest Classifier to validate and justify the factors that affect consumer intention in selecting a 3PL service provider during the COVID-19 pandemic integrating the Service Quality Dimensions and Pro-Environmental Theory of Planned Behavior. The findings of this study revealed that attitude is the most significant factor that affects the consumers' behavioral intention. Other factors such as customer satisfaction, customer perceived value, perceived environmental concern, assurance, responsiveness, empathy, reliability, tangibility, perceived behavioral control, subjective norm, and perceived authority support, are all contributing factors that affect behavioral intention. Machine learning algorithms, specifically ANN and RFC, resulted to be reliable in predicting factors as they obtained accuracy rates of 98.56% and 93%. Results presented that consumers' attitude, satisfaction, perceived value, assurance by the 3PL, and perceived environmental concerns were highly influential in choosing a 3PL package carrier. It was seen that people would be encouraged to use 3PL service providers if they demonstrate availability and environmental concerns in catering to the customers' needs. Subsequently, 3PL providers must assure safety and convenience before, during, and after providing the service to ensure continuous patronage of consumers. This is considered to be the first study that utilized a machine learning ensemble to measure behavioral intention for the logistic sector. The framework, analysis tools, and findings of this study could be extended and applied among other behavioral intentions regarding transportation worldwide. Managerial insights among service providers are discussed.

Utilizing SEM-RFC to predict factors affecting online shopping cart abandonment during the COVID-19 pandemic.

Online shopping has accelerated during to the pandemic and an increase in online shopping cart abandonment (SCA) was also evident. The growth of online shopping is contributed by the rising middle class, high consumer spending, millennials, and a tech-savvy population which is valuable to the growth of e-commerce. This study aimed to predict the factors that affect SCA during the COVID-19 Pandemic utilizing the SEM-RFC hybrid. Several factors such as self-efficacy, attribute conflicts, hesitation at checkout, emotional ambivalence, choice process satisfaction, attitude, subjective norms, and perceived behavioral control were analyzed simultaneously. This study integrated the cognition-affect-behavior paradigm with the Theory of Planned Behavior to provide a conceptual framework measured through an online survey questionnaire answered by 1015 valid responses collected by convenience sampling. Results showed that Attitude, Attribute Conflict, Self-Efficacy, and Emotional Ambivalence are the primary significant factors affecting SCA. Amidst the pandemic, consumers still value the ease of use, convenience and safety of the mobile online shopping applications that they have, which they do not positively experience at this time. The findings of this study may be applied and extended by researchers, online retailers, and businesses to understand consumer's abandonment intentions. Moreover, the results and framework of this study may be capitalized on by the business sector to create marketing strategies and develop business models for a sustainable online shopping business worldwide.

How important is the tuition fee during the COVID-19 pandemic in a developing country? Evaluation of filipinos' preferences on public university attributes using conjoint analysis.

In a developing country like the Philippines, it is critical to understand the important factors which lead college students to their current colleges and universities, especially during the COVID-19 pandemic. This study utilized the conjoint analysis approach with an orthogonal design for evaluating understudy's inclination in choosing a college with the various attributes such as the tuition fee, distance or location, employability, academic reputation, recommended by friends and peers, recommended by family or relatives, and the availability to transfer was assessed. A total of 518 Filipino students studying at public and state universities participated in answering the 16 combined attributions about university preference using purposive sampling approach. Based on the utilities estimate, the most important attribute was the tuition fee of the preferred university with an importance value of about 32.839%, followed by the employability rate of the university with about 6% gap difference. The mid-concerned attributes were the distance/location with an estimated of 11.139%, recommendation of friends or peers with approximately 11.689% tying together, and the academic reputation with an estimated of 10.638%. The two least important attributes were identified to be the availability to transfer, having with only about 2.713%, and the recommendation of parents with only 2% difference at approximately 4.453%. The outcomes of this study can aid college chairmen and enrolment specialists tweak their advertising procedures by giving significant data to the chief gatherings engaged with settling college decision choices.

User Preference Analysis of a Sustainable Workstation Design for Online Classes: A Conjoint Analysis Approach

The impact of the COVID-19 pandemic has caused the sudden shift of the interactions between students and teachers from the four corners of the classroom to fully online learning through the workstations. By using a conjoint analysis approach, this study aimed to evaluate the preference of undergraduate students from the Philippines on the workstation design attributes during the pandemic. Seven attributes were examined through orthogonal design: the type of gadget, keyboard, mouse, earpiece, desk, kind of chair, and light device. Through a purposive sampling approach, a total of 315 undergraduate students from the Philippines were gathered. Through an online survey with two holdouts, the respondents voluntarily responded to 51 stimuli produced by IBM SPSS using a 7-point Likert scale. Type of gadget (37.925%) was found to be the most significant attribute preferred by the students, followed by the type of mouse (28.345%), kind of chair (14.840%), type of keyboard (7.548%), earpiece (7.177%), light device (2.109%), and desk (2.056%). It is worth noting that the preferred workstation design combination is the personal computer, mechanical keyboard, wired mouse, headset, height-adjustable table, high-back office chair with neck support, and floor lamp. This study is the first to use a conjoint technique to examine undergraduate students' preferences for workstation design attributes during the COVID-19 pandemic. Finally, by applying the attributes and design developed in this study, the conjoint method can be used and expanded to evaluate the workstation design attributes of other courses and even employees worldwide.

Investigating Factors Affecting Behavioral Intention among Gym-Goers to Visit Fitness Centers during the COVID-19 Pandemic: Integrating Physical Activity Maintenance Theory and Social Cognitive Theory

The COVID-19 pandemic has led to the closure of many fitness centers and has significantly affected the behavioral intentions of gym-goers. This study aimed to determine factors affecting the behavioral intentions of gym-goers regarding fitness centers during the COVID-19 pandemic in the Philippines by utilizing the Physical Activity Maintenance Theory within the framework of Social Cognitive Theory. A total of 1048 gym-goers voluntarily answered an online, self-administered survey comprising 68 questions. Structural Equation Modeling indicated that physical activity maintenance through understanding COVID-19 and self-motivation had the highest significant effect on behavioral intentions. Interestingly, life stress was found to have a significant negative direct effect on physical activity maintenance. The current study is one of the first to have analyzed factors affecting the behavioral intentions of gym-goers during the COVID-19 pandemic. Finally, the application of Physical Activity Maintenance Theory and Social Cognitive Theory in this study provided accurate predictors of behavioral intention. As a result, this integrated model could serve as a theoretical foundation that could be applied and extended to assess behavioral intentions among gym-goers during the COVID-19 pandemic worldwide.

Determining the Factors Affecting a Career Shifter's Use of Software Testing Tools amidst the COVID-19 Crisis in the Philippines: TTF-TAM Approach

The restrictions of the ongoing COVID-19 pandemic resulted in the downturn of various industries and in contrast a massive growth of the information technology industry. Consequently, more Filipinos are considering career changes to earn a living. However, more people still need to be upskilled. This study combines the extended Technology Acceptance Model and Task Technology Fit framework to determine factors affecting a career shifter's use of software testing tools and its impact on perceived performance impact amidst the COVID-19 pandemic in the Philippines. A total of 150 software testers voluntarily participated and accomplished an online questionnaire consisting of 39 questions. The Structural Equation Modeling and Deep Learning Neural Network indicated that Task Technology Fit had a higher effect on Perceived Performance Impact. Moreover, Task Technology Fit positively influenced Perceived Usefulness. Computer Self-Efficacy was a strong predictor of Perceived Ease of Use. Perceived Ease of Use confirmed the Technology Acceptance Model framework as a strong predictor of Actual System Use. Intention to Use, Perceived Usefulness, Actual Use, and Subjective Norm were also significant factors affecting Perceived Performance Impact. This study is the first to explore the career shifter's use of software testing tools in the Philippines. The framework would be very valuable in enhancing government policies for workforce upskilling, improving the private sector's training and development practices, and developing a more competitive software testing tool that would hasten users' adaptability. Lastly, the methodology, findings, and framework could be applied and extended to evaluate other technology adoption worldwide.

The perceived usability of the learning management system during the COVID-19 pandemic: Integrating system usability scale, technology acceptance model, and task-technology fit.

BACKGROUND: The education system has shifted from traditional to online during the COVID-19 pandemic. Thus, the Learning Management System (LMS) is one of the most important and comprehensive learning platforms that support and facilitate online learning during this pandemic. OBJECTIVE: This study explored the perceived system usability of LMS during the COVID-19 pandemic by utilizing Technology Acceptance Model (TAM), Task-Technology Fit (TTF), and System Usability Scale (SUS). METHODS: An online survey was utilized to collect data from 502 Filipino students from different academic institutions and different areas of study. RESULTS: Structural Equation Modeling (SEM) indicated that students' perceived ease of use of LMS had a significant effect on perceived usefulness which subsequently and positively led to students' perceived satisfaction of LMS. In addition, LMS technology characteristics was found to have a significant effect on LMS task-technology fit which subsequently led to perceived usefulness and perceived satisfaction. Interestingly, perceived satisfaction was found to have a significant effect on students' perceived system usability of LMS which was calculated using a System Usability Scale (SUS). CONCLUSION: The findings have implications within the education system globally, particularly in recognizing the relevance of LMS moving forward. Furthermore, since this is the first study that integrated SUS, TAM, and TTF, the conceptual framework can be utilized to evaluate the perceived usability of LMS worldwide.