Sentiment analysis has been extensively researched for the purpose of analyzing qualitative data using a computation technique. However, there are only a few research papers that focus on analyzing sentiments in terms of teachers’ evaluation. Analyzing comments on teacher evaluations can lead to understanding more of what faculty development programs can be provided to improve teachers’ academic performance. Thus, this study presents an opinion-mining system utilizing the Bayesian technique of the Naïve Bayes algorithm. The descriptive research method was used in this study, with a questionnaire serving as the instrument for testing the acceptability of the application. One hundred (100) evaluators were surveyed for the teachers’ evaluations. The application performance attributes are defined using the functionality, usability, reliability, performance and security (FURPS) model. The mean formula was used to analyze the data. The usability and security were evaluated as perfectly acceptable, with a weighted mean of 4.64, and 4.56, respectively. Furthermore, the functionality, reliability, and performance were evaluated at acceptable evaluation ratings with a weighted mean of 4.29, 4.02, and 4.11. The overall quality of the system was given an acceptable rating with a weighted mean of 4.32, indicating that the application provided and managed ratings and comments on individual teachers’ performance.

HWYL (meaning “a stirring feeling of emotional motivation and energy”) is a 3D isometric puzzle adventure game for Android devices. The whole game revolves around the adventures of Thomas as he unknowingly helps the mayor and the townspeople in solving environmental problems through playing meaningful mini games. The mini games comprise of different casual games that focus on teaching the players about the major environmental issues such as ozone depletion, and disposal of wastes. The interactive learning experience educates players how to mitigate environmental problems. The game garnered very satisfactory results from the play testers, proving that the game has been successful in promoting environmental awareness through edutainment, and the game as a system works as intended with compliance to software quality factors.

Urban systems have a central role in the transition toward circular economy. Systematic analysis of drivers is needed because of the complex interplay of social, economic, and political factors. Such analysis requires a good understanding of direct and indirect influences on urban circularity. Because of the presence of indirect influences, visualizing the causal networks is necessary for systematic analysis. Existing methods for formulating causal network maps (CNMs) rely on subjective approaches which inhibit robust assessment. The generation of robust CNMs can provide more accurate representation of direct and indirect influences. Therefore, this study generates a robust CNM for drivers of urban circular economy through a hybrid decision-making and trial laboratory-fuzzy cognitive map (DEMATEL-FCM) framework. DEMATEL is used for building the initial structure of the network map. The network is then trained using FCM with data obtained from the Sustainable Cities Index. A 70:30 training–testing ratio is used to partition the training and testing datasets. The trained CNM has 92.75% accuracy during training and 96.77% accuracy during testing. The trained CNM provides an empirical depiction of driver interrelationships in urban circular economies. It indicates the importance of ‘affordability’ and ‘economic development’ in the network structure. The network yields significant insights for the development of city-level plans and policies to stimulate a transition to a more circular economy. Data-driven visualization of interactions among drivers give stakeholders insights on the most effective measures to implement.

This research project presents the development of a video game entitled “Chyilax” – an innovative three-dimensional video game about a person’s struggle against mental breakdown while trying to alleviate its symptoms. The game was developed to be a medium that would raise awareness about the risks and conditions of mental health breakdown. The player can choose to take the role of either a college student or a working adult, both experience symptoms due to a tangled situation in their past. The player was tasked to help the protagonist to overcome the symptoms before it leads to a nervous breakdown. In order to help the protagonist, make up with the people who got involved in their past circumstances through puzzle-solving, role-playing, and problem-solving. Chyilax was developed using Unity as its game engine while 3D models were created using Autodesk Maya. The project was tested and evaluated via a virtual open house. The questionnaires were collated online using an online form that assesses the following as criteria for the game: effectiveness, visuals, mechanics, audio, and enjoyment while the website: functionality, usability, reliability, performance, and supportability as criteria. The game received an overall mean of 4.32 while the website received an overall mean of 4.35, both of which have a verbal interpretation of “Strongly Agree”, which interprets that the objectives were achieved and drawn impact to raise awareness on issues focusing on mental breakdown.

During the outbreak of COVID-19, the productivity gap between working in the office and at home has become a more critical issue in the labor market. For teachers with numerous vital responsibilities, the inescapable increased workload results in less productivity and efficiency. Following the reliance on productivity applications to lessen labor, we investigated the moderating effects of sociodemographic profiles of teachers through the Technology Acceptance Model. The demographic makeup of our participants (n = 513) was dominated by assistant professors, females, married, licensed teachers, aged 25 to 34 with a teaching experience of 6 to 10 years, and permanent and full-time in a public university. Our findings demonstrate that sociodemographic variables moderate the effects of perceived usefulness (PU) and perceived ease of use (PEOU) on teachers’ behavioral intention to use (BITU), except for the effects of gender in PEOU → BITU, teaching experience in PEOU → BITU, and educational attainment in PU → BITU.

The Virtual Dietitian (VD) application is a nutrition knowledge-based system that generates personalized meal plans in accordance with the one-size-does-not-fit-all concept of precision nutrition. A subset of the population that was not involved in its four-part developmental study was gym and fitness enthusiasts despite them being important target users. As part of our quality improvement (QI) plan, we initiated a two-phase user testing to inform modifications to VD. We recruited a total of 30 users with prior experience in nutrition applications. In phase 1, they used the current version of VD for a week and answered a mixed-form questionnaire afterward. We used the same questionnaire from our previous study, which is composed of System Usability Scale (SUS) items and open-ended questions. After months of system modification, the same set of users evaluated again the new VD version after another week of use. A paired-sample t-test showed a statistically significant difference in SUS scores before (SUS = 79) and after (SUS = 82) modifying VD based on the suggestions of the participants (p = 0.005). Some new features include water tracker and reminder modules, Google Fit integration, and other nutrition support services (e.g., teleconsultation with registered dietitians). Although further refinements to VD are still needed, we were able to incorporate a QI initiative typically employed by healthcare organizations into software development for a better and improved personalized nutrition application.

Governments and health agencies around the world have been at the forefront of managing the COVID-19 pandemic. To control the spread of the outbreak, mandatory safety protocols have been put into effect. Despite the continuous development and strict enforcement of these preventive guidelines, non-compliance with these mandatory safety protocols has been reported. Getting the message to the public is one of the key challenges in convincing people to follow mitigation policies. In this study, we employed the media of video games to advocate for COVID-19 safety protocols. We developed a video game called "Corona Larona" that features microgames with action gameplay playable on a mobile platform. Our video game concentrated on several preventive measures such as physical distancing, hand washing, wearing face masks as well as basic knowledge about the virus using in-game multiple choice questions. To our knowledge, this is the first video game dedicated to the COVID-19 outbreak and the mandatory safety protocols. In a time when many people play video games to survive their current situation, the Corona Larona game is a strategic example of using and maximizing this form of media for a more noble purpose.

Student engagement and enrichment are key factors as learners have shifted from the traditional classroom to the virtual classroom when a flexible learning environment has been in place. It has posed a challenge for educators to shift from traditional educational methods to the utilization of technology-enhanced learning all the more since online and flexible mode were often used since the pandemic. This paper intends to convey that students may exhibit engagement inside the virtual classroom by posting student-generated questions during a discussion forum in the Canvas LMS as question-based inquiries. More so, students have enjoyed and increase their academic performance by playing and participating in a gamified learning activity. This research discussed an activity in encouraging students' learning, curiosity, and involvement in online learning environments. The authors aim for this objective by fusing the 1) utilization of student-generated questions in the goal of promoting learning and thinking, and 2) boosting student engagement through the use of gamified activities which increases students’ academic performance. These intentions will be realized in the virtual classroom implementation and its assessment. Employing the Canvas New Analytics, 148 first year-second semester students questioned their teacher about a course topic and as their questions were each replied to, they were graded through discussion post with an average grade of 99% for all sections. The game Jeopardy was played as an examination review session for the same sections and 181 students from the four sections have an average grade score of 77.5% in their midterm examination. A course learning objective item is also measured with a university target that at least 60% of students should reach an average grade score of 80% and above. For the CLO target, average of four sections reached 68.3% which is descriptively attained. Generating questioned-based inquiry in the forum discussion showed an increase in engagement and enrichment from students. The findings have a positive impact on them as their posted inquiries and questions gained them grades which indicated high average grade for each section. Utilizing a gamified learning activity in a pure online setting for the school year 2021-2022, allowing the students to participate in educational games is necessary to boost engagement and enrichment as well.

Efficient and reliable medical image analysis is indispensable in modern healthcare settings. The conventional approaches in diagnostics and evaluations from a mere picture are complex. It often leads to subjectivity due to experts' various experiences and expertise. Using convolutional neural networks, we proposed an end-to-end pipeline for automatic Cobb angle measurement to pinpoint scoliosis severity. Our results show that the Residual U-Net architecture provides vertebrae average segmentation accuracy of 92.95% based on Dice and Jaccard similarity coefficients. Furthermore, a comparative benchmark between physician's measurement and our machine-driven approach produces an acceptable mean deviation of 1.57 degrees and a T-test p-value of 0.9028, indicating no significant difference. This study has the potential to help doctors in prompt scoliosis magnitude assessments.

The COVID-19 pandemic has caused disruption to the economy due to the increasing infection that affects the workforce in different sectors. The Philippine government has imposed lockdowns to control the spread of infection. This urged the different sectors to implement flexible work schedules or work from home setup. A work-from-home (WFH) setup burdens both the employee and employer by installing different equipment set-ups such as WiFi-equipped laptops, computers, tablets, or smartphones. However, the internet stability in some of the areas in the Philippines is not yet reliable. In this study, an application is used collect survey information and provide an estimate of the telework internet cost requirement of a given government employee or a given government employee implementing a work-from-home set up in their respective household. This involves survey results from different respondents who are currently on a work-from-home setup and significant factors from the survey have been analyzed using machine learning (ML) algorithms. Among the machine learning algorithms used, the ensemble bagged trees model outperformed the other ML models. This work can be extended by incorporating a wider scope of datasets from different industry doing work from home set-up. In addition, in terms of education, it is also recommended to determine the WFH set up not just with the government employee and employer but to also extend this into the education side.