Scopus ID: 105030149087
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2024), pp. 1-6
Conference Paper | Published: January 1, 2024
Abstract
The Technology Acceptance Model (TAM) serves as a foundational framework for assessing user acceptance of emerging technologies, particularly in organizational settings. In education, digital governance has become a transformative tool for enhancing operations within State Universities and Colleges (SUCs). However, many SUCs face challenges due to their reliance on commercial applications that lack the capacity for comprehensive and accurate reporting. To address this issue, the researcher developed an enterprise-level information system tailored to integrate research, teaching, and extension functions for SUCs in the Philippines. Utilizing the Agile Development Model, which emphasizes iterative progress through continuous improvement, the study employed a descriptive developmental approach to system creation and evaluation. The TAM criteria guided the evaluation process, resulting in an overall weighted mean of 3.55, interpreted as “Acceptable.” While the system has been positively received, the findings highlight the need for further refinement to optimize its effectiveness. Despite this, the system is strongly recommended for deployment in SUCs, as it offers a comprehensive, customizable solution for enhancing digital governance in higher education. This study underscores the importance of applying frameworks such as TAM to evaluate and refine technological innovations, ensuring their alignment with organizational needs and their contribution to improving digital governance within SUCs.
Scopus ID: 105030199608
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2024), pp. 1-6
Conference Paper | Published: January 1, 2024
Abstract
This study presents an e-commerce platform with customer analysis using hybrid collaborative filtering, developed specifically for the EveryDay streetwear brand to enhance their online presence and improve their business operations. With the rise of online shopping and social commerce in the Philippines, the platform aims to enhance user experience by providing tailored product suggestions using hybrid collaborative filtering. It integrates features like order, payment, inventory management, and product customization, allowing users to personalize their shopping experience, while customer behavior analysis and monthly reporting help improve decision-making and operational efficiency. To guide the development of the platform, the team used the SCRUM methodology. The system's architecture emphasizes data security, user privacy, and reliability through the ISO 25010 Software Quality Model. Surveys were conducted with a total of 75 respondents to measure the system's performance based on the model's parameters. The system scored a weighted mean of 4.81 from customers, 5.00 from both staff and admin, and 4.88 from IT experts, resulting in an overall rating of “Excellent.”. This study highlights the potential of hybrid recommender systems in enhancing e-commerce platforms and driving customer engagement and sales.
Scopus ID: 105030194141
2024 IEEE 16th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2024), pp. 1-5
Conference Paper | Published: January 1, 2024
Abstract
This study aims to identify the most critical attributes influencing retention and dropout risk in the Alternative Learning System (ALS) by analyzing various demographic, socio-economic, academic, and behavioral factors. Using Gradient Boosting Decision Trees (GBDT) for predictive modeling, the research explores feature importance scores to rank and prioritize the key attributes. The researcher used Knowledge Discovery in Databases as analytics methodology. Using principal component analysis, it was identified that regular attendance, availability, financial support, parental cohabitation (living together), and internet access positively influence retention. Furthermore, attending public schools, having a widowed parent, and possibly other features like distance to school are linked to increased dropout risk. The results provide insights into the main factors affecting student success, enabling more focused and data-driven interventions. The findings can help ALS administrators and educators develop personalized support plans for at-risk students and allocate resources more effectively.
Scopus ID: 85145502802
International Journal of Human–Computer Interaction, (2024), Vol. 40, No. 10, pp. 2546-2559
Journal Article | Published: January 1, 2024
Abstract
Teachers play a central role in achieving the mission, vision, and goals of educational institutions. However, the multitude of responsibilities and obligations they must fulfill demands a high level of productivity. Consequently, productivity software is increasingly becoming a necessity for teachers to lessen their day-to-day work pressure and instead focus on offering quality education. Despite their popularity, the key antecedents and precursors affecting the intention to use productivity software have yet to be investigated. Therefore, the goal of this study was to determine what factors contribute to the adoption of productivity software by applying the theoretical lens of the Technology Acceptance Model (TAM). A total of 947 responses from basic and higher education teachers were analyzed using a structural equation modeling approach. Results show that the usefulness and ease of use of productivity software are key in predicting behavioral intention. It is also indirectly affected by external variables such as subjective norms, professional reputation, job relevance, and output quality through perceived usefulness as well as facilitating conditions and self-efficacy through perceived ease of use. Overall, the findings of this study support the applicability of the specific TAM version as well as its employment in the context of productivity software.
Scopus ID: 105008055489
Global Innovations in Physical Education and Health, (2024), pp. 439-472
Book Chapter | Published: January 1, 2024
Abstract
Education for Sustainable Development (ESD) is essential for promoting sustainability and environmental stewardship among students. However, the intent of Filipino teachers to incorporate ESD principles into Physical Education and Health remains underexplored. This study examines the relationships between attitudes towards ESD, subjective norms, perceived behavioral control, behavioral intentions, self-reported behavior, subjective task value, ESD knowledge, and ESD integration beliefs among 363 educators. Utilizing PLS-SEM, the study finds perceived behavioral control as the strongest predictor of both behavioral intentions and self-reported behaviors, underscoring its role in enabling educators to implement ESD practices. ESD knowledge significantly influences perceived behavioral control, suggesting that enhancing knowledge could boost educators' confidence in ESD integration. Additionally, ESD integration beliefs impact attitudes and behavioral intentions. These findings offer insights for targeted interventions to support ESD integration within PE and Health curricula.
Scopus ID: 105000327575
TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON), (2024), pp. 1290-1293
Conference Paper | Published: January 1, 2024
Abstract
To ensure students achieve timely and satisfactory graduation, it's essential to assess their future performance based on ongoing academic records and implement instructional interventions. Within the educational context, students fall into two categories: regular and irregular, each governed by distinct academic regulations. Regular students follow a predetermined curriculum, which provides a clear path to graduation and enhanced access to required courses, facilitating efficient progress toward degree completion. On the other hand, irregular students encounter challenges such as disruptions and delays, necessitating additional time and support to fulfill degree requirements. Guiding both regular and irregular students and improving their study plans require appropriate guidance and academic intervention. To address the existing research gap, this study presents a Criteria-based Recommender Platform for Achieving Optimal Time-to-Graduation Utilizing a Backward Chaining Algorithm. This platform automatically generates a personalized study plan by considering predefined criteria and parameters, enabling students to evaluate the timeline for completing their degree program. By leveraging the backward chaining algorithm, the platform's predictive model captures intricate relationships and dependencies within the data, providing valuable insights and predictions. This adaptive approach continuously refines predictions based on new data, enhancing accuracy and utility in guiding decision-making processes related to study plan generation.
Scopus ID: 105000234438
TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON), (2024), pp. 1286-1289
Conference Paper | Published: January 1, 2024
Abstract
Outcome-Based Education (OBE) emphasizes the importance of defining and assessing specific learning outcomes. Effective monitoring of these outcomes is crucial for ensuring student success and program effectiveness. Previous research has explored various approaches to enhance program outcome monitoring, however, have not fully addressed the need for individualized and comprehensive progress tracking that goes beyond binary pass or fail measurements. This paper presents a novel approach to enhance program outcome monitoring through the development of individualized dashboards and the application of an adaptive neuro-fuzzy logic (ANFIS) framework. Data were derived from CSV reports of students in a learning management system and Canvas New Analytics from a sample class in the pilot study. The ANFIS framework is based on formative and summative assessments, total and maximum page views and participation, and average weekly page views and participation. The ANFIS model and dashboard results demonstrate its effectiveness in providing students and educators with a deeper understanding of student progress in terms of program outcomes, enabling targeted interventions and personalized learning experiences. This comprehensive approach empowers educators with the tools and insights needed to optimize educational practices and ensure that all students achieve the desired learning outcomes.
Scopus ID: 105000426847
TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON), (2024), pp. 842-845
Conference Paper | Published: January 1, 2024
Abstract
Visual impairment continues to be a global health concern. People with visual impairment experience difficulty moving around indoors, especially in unfamiliar spaces. While existing assistive technologies like smart canes offer point-to-point navigation or rely on infrastructure like RFID tags or beacons, they lack the ability to provide comprehensive indoor navigation with obstacle detection and avoidance. This paper presents a novel indoor navigation system for visually impaired individuals using deep learning and audio guidance. The system utilizes 3D-printed glasses equipped with a Raspberry Pi v2 camera, audio user interface and a processing unit comprising a Raspberry Pi 4B and Google Coral Edge tensor processing unit (TPU). As validated in a controlled indoor environment, the deep learning models for localization, navigation, obstacle detection, and obstacle avoidance achieve high results in terms of accuracy, precision recall, and F1-score. Based on user tests using the System Usability Scale, this wearable assistive device appears to offer a promising solution for promoting independent navigation and spatial awareness among visually impaired individuals.
Scopus ID: 105000432387
TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON), (2024), pp. 1219-1222
Conference Paper | Published: January 1, 2024
Abstract
Amidst the clear-cut changes constantly happening in the educational landscape, Higher Education Institutions (HEIs) are continuously pursuing graduates that meet global standards. The rise of remote jobs from previous years opened a gateway of opportunities for Filipino graduates to ensure employment from various multinational employers. To maintain this, HEIs in the Philippines must be able to offer quality education and programs that meet exceptional standards. This study aims to address the inability of tertiary institutions to track the competencies that the students have gained by integrating the outcome-based education (OBE) framework through an online platform. This paper also enumerates the benefits of having an OBE Management system such as achieving a holistic view of evaluating students' competencies, the system integrates educational data from various sources such as grading system, Learning Management System (LMS), and surveys. The system development research process is conducted in this study. One of the objectives of this study is the integration of drill-down analysis into the OBE Management system. This allows users to create reports easily and faster, furthermore, it aids the country in achieving Sustainable Development Goal (SGD) 4 for Quality Education. The premise of the study also contributes to the impact of system development on attaining quality education for HEIs.
Scopus ID: 105000235910
TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON), (2024), pp. 1533-1536
Conference Paper | Published: January 1, 2024
Abstract
Social relationships are important to human well-being and interaction. Recently, there has been growing interest in how they are formed in various digital media, including social media and video games. Amid the rise of digital engagement, the metaverse has emerged as an essential virtual environment for social interaction. Unfortunately, there is limited understanding of how social relationships are developed and maintained within the metaverse. In this study, we explored the dynamics of social relationship development in a metaverse world. Using a one-shot case study, we assessed the roles of immersion and embodiment, as well as the moderating effect of copresence, in building social relationships through multiple regression analysis. Our findings show that with higher levels of immersion and embodiment, the formation of social relationships in the metaverse is significantly improved. Copresence further intensifies these effects, which is indicative of its crucial role in virtual social interactions. These results indicate that enhancing the immersion, embodiment, and copresence elements in metaverse environments can encourage stronger social bonds among users. Overall, this study advances our understanding of online social relationship formation in the metaverse environments and its design and development.