Journal of Innovative Technology Convergence
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111 research outputs found
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Longitudinal Analysis of Software Development Skill Demand: Evidence from the Philippine IT Workforce
No full textThe rapid diversification of software development technologies has intensified the need for academic programs to remain responsive to industry-driven skill requirements. This study investigates longitudinal patterns in programming language adoption among software professionals in the Philippines using publicly available professional profile data. A ten-year dataset (2013–2023) comprising 250 LinkedIn profiles of practicing developers was analyzed through automated text extraction and frequency-based trend analysis. The results reveal sustained dominance of web-oriented technologies, particularly JavaScript, HTML, PHP, and MySQL, alongside a pronounced rise in modern JavaScript frameworks, mobile development tools, and cross-platform technologies. In contrast, traditional content management systems and legacy libraries demonstrate declining relevance over time. To contextualize these findings, the observed industry skill patterns were compared with the prescribed programming components of the Commission on Higher Education (CHED) computing curricula. While foundational languages remain well represented, emerging frameworks and development paradigms receive comparatively limited emphasis. The findings underscore the necessity of adaptive curriculum strategies that balance stable core competencies with evolving industry technologies. The study contributes a data-informed basis for curriculum enhancement aimed at improving graduate employability and long-term workforce relevance in the Philippine IT sector
Developmental Leadership, Behavior, and Instructional Practices of School Heads
No full textThe quality of education, student achievement, and the general school climate can all be significantly impacted by the developmental leadership, conduct, and teaching methods of school administrators. Therefore, this study looked into how school heads' developmental leadership and behavior relate to their instructional practices in Maasin District Maasin, Leyte, Philippines. In order to collect data from the respondents, the study used a descriptive-correlational research design with a survey. Developmental leadership, behavior, and instructional practices of school heads can be profoundly instrumental on the quality of education and the overall school environment. Thus, this study investigated the relationships between developmental leadership and behavior of school heads in relation to instructional practices of the school heads in Maasin District Maasin, Leyte, Philippines. The study utilized a descriptive-correlational research design using survey to gather data from the respondents. Results revealed that highly significant relationships existed between school heads’ developmental leadership and behavior on their instructional practices both in their subcomponents and overall mean. The findings showed that school administrators can foster a collaborative, empowering, and encouraging atmosphere that supports instructional leadership practices by exhibiting developmental leadership and positive behaviors. It recommends that in order to implement effective teaching practices, school administrators should place greater emphasis on school culture, providing oversight and feedback, encouraging teamwork, and allocating resources to demonstrate a caring, encouraging, and growth-oriented environment that will ultimately improve student learning and achievement
Development and Performance Evaluation of a Mobile Solar Generator
No full textThis study aims to develop a mobile solar generator using the analysis, design, development, implementation, testing, and evaluation (ADDIE) development model. The Mobile Solar Generator (MSG) was created to offer a backup source of electricity for homes, businesses, and schools, especially during power outages caused by natural disasters. It uses both solar power technology and the idea of a conventional AC generator. The MSG comprises two 250 ampere-hour, 12-volt gel-type deep cycle batteries; a 3-kilowatt inverter; a 40-ampere solar charge controller; and four 330-watt monocrystalline photovoltaic panels affixed to the roof of the minibus. The performance testing concentrated on component voltage, battery voltage, charging current, charging capacity, and abnormality codes. The findings showed that charging is feasible between 7:00 AM and 5:00 PM and best between 8:30 AM and 3:30 PM during sunny weather. The charging capacity was best during sunny weather without load (SWOL) conditions, with 210.5 ampere-hours on average. Discharging time with load was longer during sunny weather, and charging during cloudy weather is still feasible. The payback period for this system is estimated to be twenty-five (25) months
Bangladeshi Migrant workers English Language Learning with the help of Multimedia
No full textThe high territory of English within a worldwide economy of dialects has implied that English dialect instruction is progressively being adapted in global advancement activities. However, English language learning in Bangladesh is one of the most difficult of all problems. People are always afraid of this language. It’s true that they want to learn and show a lot of interest in English, but when the time comes to learn this language practically, they always run away. This paper deals with the study of the difficulty and eagerness of Bangladeshi people to learn English. The different factors on learning English were identified, and findings were discussed with regards to critical perspectives discovered from the examination that the dimensions of instruction and proficiency of the migrant workers, even in their home dialect, were commonly low, with the majority of them having ceased formal training at essential dimensions
A Study on the Development of a Web-based Collaborative Project Management Platform
No full textThis study focuses on the development of a web-based collaborative project management platform for small teams working on multiple projects. It outlines the steps from conceptualization to deployment, evaluating the platform\u27s performance and usability using ISO/IEC 25010 software quality standards criteria. The study aims to compare evaluations among project managers, IT professionals, and end-users, providing insights into user perception and interaction. It also identifies problems encountered during system testing, aiming to refine the platform and address usability and functionality issues. The user manual was developed to provide a practical guide for users, providing instructions on how to navigate and utilize the platform effectively. The findings show a successful system implementation, with enthusiastic end-user adoption and positive endorsement from user groups
Jackfruit Disease Recognition Using Image Processing in Non-Destructive Method with Alternative Treatment Recommender
No full textThis study focuses on developing a mobile application for jackfruit disease recognition using advanced image processing techniques and hybrid algorithms. The proposed system combines Convolutional Neural Networks (CNN) with Support Vector Machines (SVM) to create a non-destructive method for accurately diagnosing jackfruit disease, particularly Rhizopus disease, through image analysis. By addressing the limitations of traditional disease detection methods, this application aims to provide a rapid, reliable, and automated solution for monitoring jackfruit health. Additionally, the study integrates an alternative treatment recommender that suggests organic and eco-friendly solutions for disease management, enhancing the sustainability and effectiveness of jackfruit cultivation. The system\u27s performance was evaluated using metrics such as accuracy, precision, recall, and F1 score, with the goal of creating a high-quality, user-friendly application based on ISO 25010 software quality standards
A Review on Strategies of Resilience for Human Computer Interaction
No full textThe idea of human-computer interaction comes because of the advancement in the development of computer technology. The new generation of people (i.e., young age group people), who are educated and technically knowledgeable, are involved in research experiments in human-computer interaction. Human-computer interaction (HCI) covers both technical and human behavioral concerns. The main purpose of practical research in human-computer interaction is to disclose unknown perceptions about the behavior of humans and its relationship to technology. Resilience is just a set of routines that allow us to recover from obstacles. The term resilience has been applied to almost everything from the economy, real estate, events, sports, business, psychology, the educational field, and more. Resilience is basically made up of a number of various abilities and skills for the purpose of building strong relationships, self-efficacy, optimism, self-awareness, and creating meaning from other experiences. In this process, people should use this for the increased quality of an organization’s resilience. For the purpose of building up knowledge of resources that are available to the people and for the purpose of confronting existing problems, all these things will be done by resilience
Enhancing Online Learning Through Feedback Analytics Using Descriptive Analytics and Topic Modeling
No full textAs online education continues to evolve, particularly within pioneering institutions offering fully online degree programs, the need for data-driven quality assurance becomes increasingly critical. From Academic Year 2018 to 2025, a substantial volume of student feedback was collected through Course and Mentor Evaluation (CME) and Voice of the Customer (VOC) surveys. The CME and VOC datasets offer greater insights into the learner experience. However, the amount and complexity of textual feedback present challenges for standard manual analysis. This study aims to extract meaningful insights from student feedback using a combination of descriptive analytics and Natural Language Processing (NLP) techniques—specifically, sentiment analysis and topic modeling. A total of 36,142 valid entries from the original dataset were kept after a rigorous data-cleaning procedure. To guarantee data quality and consistency, entries with missing, duplicate, or invalid responses were eliminated. Descriptive analytics were used to find recurring patterns and common problems, while topic modeling assisted in exposing underlying themes in the comments. A more detailed view of service gaps, student happiness, and instructional effectiveness is made possible by this dual approach. The study\u27s findings aim to inform institutional enhancements in mentor interaction, course content, and the overall delivery of online learning. The research helps to continuously improve the quality of fully online higher education environments by creating a framework that is influenced by feedback
A Digital Approach to Identifying Insider Threats in Higher Education Institutions
No full textInsider threats pose significant risks to higher education institutions (HEIs), where sensitive data through the Personally Identifiable Information (PII), intellectual property, and student information are prime targets. This paper proposes a digital approach to identifying insider threats by leveraging machine learning, behavioral analytics, and network monitoring. We present a framework that integrates user behavior profiling, anomaly detection, and real-time monitoring to detect potential malicious activities. Through a case study at a large university, we demonstrate the effectiveness of our approach in identifying suspicious behaviors with a detection accuracy of 92%. The results highlight the potential of data-driven methods to enhance institutional security while addressing challenges such as privacy concerns and false positives. This work provides a scalable model for higher education institutions to mitigate insider threats effectively
Medicare Payments Analysis Through an Adaptive Neural Fuzzy Inference System
No full textThere has been a great disparity in payments between different hospitals over the same diagnosis. This paper aims to identify cost change patterns for patients who are covered by Medicare and to reveal the hidden structures about costs for the same diagnosis and treatments from different healthcare providers. It deals with the study of an Adaptive Neural Fuzzy Inference System for Medicare payment data in order to understand these variations in hospital payments. Clustering algorithms have been utilized in order to identify the payment differences and reveal the hidden structures that make the amounts vary. Experiment results show that cost change patterns were clearly understood using hierarchical clustering algorithms