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Scholarship Management Information System for State University and Colleges in Rizal
No full textThe paper aims to design and developed a scholarship management system to optimize the processes associated with scholarship applications, including validation, monitoring, and disbursement activities. In order to assess its efficacy, the system underwent evaluation in accordance with the ISO/IEC 25010 Software Quality Standards, focusing on dimensions such as functional suitability, performance efficiency, usability, reliability, maintainability, security, and portability. A cohort of 161 participants, comprising scholars, scholarship coordinators, administrators, and IT professionals, contributed to the evaluative process. The results indicated that the system achieved an overall weighted mean score of 4.57, which corresponds to a verbal interpretation of "Highly Acceptable." The findings imply that the system satisfactorily addresses the functional and operational requirements of its users, thereby offering a dependable framework for the management of scholarship-related activities. In light of the evaluation outcomes, it is recommended that the University formally incorporate the SMIS and contemplate prospective enhancements through ongoing monitoring and additional research to optimize its influence on institutional operations
Are Quiz Configurations Affecting Student Performance in an Online Learning Environment?
No full textThis study investigates the impact of quiz configuration settings on student performance in a Moodle-based online learning environment. With the increasing reliance on Learning Management Systems (LMS) for digital instruction and assessment, understanding how configurable quiz parameters influence learning outcomes has become crucial. The research analyzes 56 quiz records from five online courses offered through the ourSOUL platform at Silliman University. Key quiz settings examined include time per question, number of attempts, grading methods, item shuffling, and the presence of a grade-to-pass threshold. Using descriptive statistics, correlation analysis, and multiple regression, the study reveals that the presence of a passing grade and the grading method significantly correlate with student scores. Specifically, quizzes with a defined grade-to-pass threshold were associated with higher performance. Other settings, such as time allocation and number of attempts, showed weaker or non-significant associations. The findings highlight the role of intentional assessment design in shaping learner outcomes and provide evidence-based recommendations for educators and institutions. By aligning quiz settings with pedagogical goals, digital assessments can become more effective tools for engagement, feedback, and performance enhancement. This study contributes to the growing literature on data-informed practices in online education and encourages further exploration of how LMS features can be optimized for student success
Analyzing Programming Language Trends Through LinkedIn Profiles: Implications for IT Curriculum Design in the Philippines
Get PDFIn the rapidly evolving field of technology, programming languages play a crucial role in shaping the competencies of future software developers. This study examined the trends in programming languages to assist educators in designing curricula that align with current industry demands. Analyzing LinkedIn profiles of software developers in the Philippines from 2013 to 2023, the study identifies prevalent programming languages and their usage trends. The findings reveal that JavaScript-based languages and mobile development languages have significantly increased in usage, while WordPress (CMS) and jQuery have declined. The study emphasizes the importance of incorporating JavaScript-based languages into IT programs to equip students for the rapidly evolving technology landscape. Furthermore, the analysis of the curriculum adopted by the Commission for Higher Education (CHED) shows a strong alignment with industry demands, particularly for key programming languages such as Java, PHP, and Python. The study suggests that continuous curriculum updates are necessary to keep pace with technological advancements and ensure graduates possess relevant skills
AI Meets Pedagogy: Transforming Writing Skills for Tomorrow’s Educators
No full textAs artificial intelligence (AI) continues to reshape the educational landscape, its integration into writing instruction offers both opportunities and challenges—particularly for pre-service educators. This quantitative study examines the perceived effectiveness of AI tools in academic writing, the attitudes of pre-service teachers (majoring in English) toward AI-assisted writing, and the perceived potential for integrating these technologies into future pedagogical practices. Data were collected from 26 participants through a structured survey instrument. Descriptive and inferential statistical analyses revealed a high level of perceived AI tool effectiveness in academic writing, with significant variations based on prior self-directed learning and exposure to AI tools. Respondents expressed generally positive attitudes toward AI writing assistants, highlighting their potential to improve writing quality, provide real-time feedback, and foster learner autonomy. Moreover, findings indicate strong support for the integration of AI writing tools in classroom writing activities, as they are seen to enhance lesson planning and collaborative writing experiences. Correlational analysis showed a strong positive relationship between perceived AI tool effectiveness and attitudes toward AI-assisted writing tools. Additionally, a moderate positive correlation emerged between perceived AI effectiveness and perceived pedagogical integration, as well as between pedagogical integration and attitudes toward AI tools. These results emphasize the im-portance of equipping future educators with targeted training and critical digital literacy skills to ensure the ethical and effective use of AI technologies in writing pedagogy
Teaching Styles, Students’ Motivation, and Grit as Correlates of Students’ Performance in English
No full textThis study was conducted to examine the relationship between students\u27 English performance and the following constructs: teaching styles, teachers\u27 leadership behavior, students\u27 motivation to learn English, and students\u27 level of grit. The statistical tools used in this descriptive research study were frequency analysis, mean computation, and correlation analysis. The performance of students in English is categorized as moderately proficient. As perceived by the students, the teachers frequently exhibit the four dimensions of teaching style. The findings reveal that the students are more integratively motivated than instrumentally; on average, they have a moderate level of grit. All constructs in this study show significant correlations with students\u27 English performance, except for instrumental motivation. The significant correlation between students\u27 performance in English and teaching style and integrative motivation is positive, but with grit, it is negative
Towards Effective Distance Education Implementation: Utilizing Descriptive Analytics, Opinion Mining, and Sentiment Analysis for Online Education Mentors and Learning Materials
No full textThis study utilizes sentiment analysis, an application of Natural Language Processing (NLP), to automate and improve the evaluation of online student feedback. Student comments from academic years 2018–2025, were cleaned, preprocessed, and analyzed using the VADER sentiment tool to label feedback as positive, negative, or neutral. These labeled data were further used to train a neural network model that uses Long Short-Term Memory (LSTM) to improve sentiment classification. Tokenization, stopword elimination, lemmatization, and contraction handling were all parts of the preparation step. VADER proved effective in detecting sentiment polarity and intensity in short student comments, while LSTM achieved an overall accuracy of 88.6%, particularly strong in classifying positive and neutral sentiments. A confusion matrix was used to assess model performance, measuring precision, recall, and F1-score. The descriptive method of textual data analysis provided insightful information about the issues that concerned students in various Online departments. The findings underscore the value of automated sentiment analysis as a feedback tool to continuously improve mentor performance and course delivery in online learning environments. The study also highlights the need for balanced training datasets to enhance the classification of all sentiment types
Web Performance and Usability of Web-Enabled Decision Support System for African Swine Fever Using ISO 25010 Standard
No full textThis study evaluated a web-enabled Decision Support System (DSS) for African Swine Fever (ASF) surveillance using the ISO 25010 standard. Conducted with 258 participants, including IT experts, ASF professionals, and policymakers, the mixed-methods approach combined surveys, interviews, document analysis, and external technical assessments. Findings indicated overall user satisfaction with the DSS, with "Acceptable" to "Highly Acceptable" ratings across most ISO 25010 characteristics like functional suitability, compatibility, and maintainability, signifying its effective alignment with organizational and user needs. However, technical analyses revealed critical discrepancies, particularly in performance efficiency (slow load times, high page size) and security (critical vulnerabilities), which contrasted with user perceptions. IT professionals also identified areas for improvement in learnability, user interface aesthetics, and confidentiality. These results emphasize the necessity of integrating both user feedback and rigorous technical validation to ensure the DSS\u27s true quality, robustness, and sustained utility in critical disease management efforts. Recommendations include enhancing usability and strengthening security through improved confidentiality, authentication, and encryption mechanisms
Navigating Academia: Lived Experiences of Graduate Students Under CMO 15, S. 2019
No full textThis phenomenological study explored the lived experiences of graduate students navigating the challenges of research publication as mandated by the Commission on Higher Education (CHED) through CMO No. 15, Series of 2019. The study sought to understand how students perceived and respond to the requirement to publish prior to graduation. Data were gathered from in-depth interviews with seven graduate students and analyzed to extract significant statements, formulated meanings, clustered themes, and developed exhaustive descriptions. The analysis revealed six major themes: (1) emotional responses to the publication requirement, such as anxiety, fear, and self-doubt; (2) recognition of publication as a tool for academic and professional growth; (3) limited awareness and understanding of the CMO 15 policy; (4) multifaceted challenges, including financial cost, time constraints, and difficulty selecting legitimate journals; (5) varied levels of support from advisers and institutions; and (6) the crucial role of institutional support mechanisms such as research trainings, workshops, and personalized mentoring. These findings suggest that while graduate students perceive the publication requirement as both daunting and valuable, successful compliance is heavily influenced by institutional scaffolding, advisor guidance, and access to financial and academic resources. The study recommends stronger implementation of structured mentoring programs, regular training workshops, and transparent communication of academic policies. The insights gained provide a foundation for improving graduate education policies and support systems that uphold both academic rigor and student well-being
A Study on the Classification of Local Varieties of Chili Pepper Using Convolutional Neural Networks
No full textThis study focuses on the classification of local varieties of chili pepper using a convolutional neural network (CNN). The four classes of local varieties of chili pepper that will be included are Siling Labuyo (Capsicum frutescens), Siling Haba (Capsicum annuum), Siling Tingala (a hybrid of Capsicum frutescens and Capsicum annuum), and Siling Demonyo (Naga Viper pepper). The ResNet50 model will be employed as the convolutional neural network, and it will be compared against different architectures such as EfficientNet and VGG16. The configuration of hyperparameters, including learning rate and epoch, will also be explored to enhance the performance of the ResNet50 architecture. A newly created chili pepper image dataset will undergo a review and be processed through data augmentation techniques to increase the number of training data. The comparative results show that the ResNet50 model outperformed the EfficientNet and VGG16 models throughout all tests in terms of accuracy, sensitivity, specificity, and precision
Evaluating the Effectiveness and User Satisfaction of Online Enrollment Systems in a Campus Setting: Implications for Upgrading and Enhancing Higher Education Institutions
No full textIn today’s digital age, online enrollment systems have become essential for higher education institutions. This study evaluated the effectiveness and user satisfaction of the online enrollment system at the Palompon Institute of Technology (PIT). A quantitative research design using a descriptive survey method was employed, with simple random sampling among all Bachelor of Science in Information Technology students. The findings indicate a high level of user satisfaction in terms of perceived usefulness, ease of use, and overall performance of the system. However, there are notable areas for improvement, particularly in user interface design and the accessibility of technical support. These aspects require enhancement to ensure a more seamless user experience. Moreover, the study identifies specific areas that need attention to improve the digital systems in education. Based on these findings, the researcher recommends strategic interventions, including the enhancement of the user interface for greater intuitiveness, improving the responsiveness of technical support, and implementing regular maintenance to ensure system reliability