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Reading Skills: The Case of Frustration Level Learners in Northern Iloilo, Philippines
No full textThis case study examined four learners to determine the factors contributing to the learners\u27 frustration level and the areas where they struggled with reading skills. The data were gathered through interviews and were analyzed using categorical aggregation to identify significant themes and meanings. The findings revealed that fear and anxiety, limited and unavailability of reading materials, and personalized and guided practice were the contributing factors to the reading skills of frustration-level learners. The difficulty in reading skills of frustration-level learners was building their strong reading foundation, especially in word recognition and syllabication of words, and comprehension of what they read. The cases of Seth, Krislen, Ejay, and Venice showed that several factors shape their reading skills and abilities. The factors that contributed to their reading skills include emotional states such as nervousness, anxiety, fear, hesitation, and physical discomfort. Availability and accessibility of reading materials, appropriate reading approaches, and personalized guidance were also influential factors. It is recommended that creating a positive and supportive learning environment for learners involves providing emotional support, accessible reading materials, personalized instruction, and addressing difficulties in building reading skills
ICT Competency and Computer Attitude among Computer Studies Students
No full textThis study assessed the Information and Communication Technology (ICT) competency and attitudes of Computer Studies students at Iloilo Science and Technology University—Miagao Campus, examining the differences in their ICT skills based on age, gender, years of computer use, section, and computer access. The study also explored the relationship between ICT competency and students\u27 attitudes toward technology. Using a descriptive research design, 82 respondents participated in the study, with data collected through a survey questionnaire. Statistical tools such as Mann-Whitney U, Kruskal-Wallis, and Dunn’s post hoc tests were employed to analyze the data. Results revealed that students had moderately positive attitudes toward ICT regardless of demographic factors. However, significant differences were found in ICT competency based on computer access, with students using rented computers showing higher competency in some aspects compared to others. The study found no significant differences in attitudes based on age, gender, years of computer use, section, or computer access. Additionally, the relationship between ICT competency and attitude was not statistically significant. The findings suggest that while students\u27 attitudes toward ICT are consistent, access to computers plays a crucial role in developing ICT competency
Motivation, Commitment and Job Satisfaction: It’s Influence on Faculty Performance in the Work From Home (WFH) Perspective
No full textThis descriptive study investigated the influence of motivation, commitment and job satisfaction on faculty performance in the Work from Home (WFH) perspective of ISAT U faculty members. The participants of this study were the two hundred seventeen (217) regular and part-time faculty members of ISAT U System, AY 2021-2022. Random sampling technique was used in selecting the samples to ensure a fair representation of the target population. The sample size was determined using Slovin’s Formula. The researcher-made instrument using remote data gathering method (google form) and face to face gathering of data was utilized to collect the data. The instrument was subjected to content validation with the three experts. The study revealed that the faculty members were extremely motivated, extremely committed, extremely satisfied in their jobs and had very satisfactory teaching performance in the work from home perspective. A significant relationship was observed between motivation and commitment, between motivation and job satisfaction, and between commitment and job satisfaction in the work from home perspective of faculty members. Finally, no significant relationship was observed between motivation and teaching performance, between commitment and teaching performance, and between job satisfaction and teaching performance in the work from home perspective of faculty members
A*Grid2D: Optimized Grid-Based A* Pathfinding for 2D Game Environments
No full textIn recent years, the complexity of 2D game environments has increased, requiring more sophisticated AI-driven solutions to ensure seamless and immersive gameplay experiences. Traditional pathfinding algorithms often struggle to adapt in real time to dynamic obstacles and multi-agent interactions, making advancements like A*Grid2D crucial for modern game development. This study significantly impacts modern 2D game development by refining NPC pathfinding and enhancing gameplay immersion, efficiency, and realism. A*Grid2D addresses key challenges—dynamic obstacles, multiple agents, goal shifts, and smooth movement—ensuring seamless navigation in complex environments. Its optimized performance benefits developers by enabling more responsive AI behaviors without compromising computational efficiency. In today\u27s 2D games, this results in smarter NPCs, faster decision-making, and more dynamic interactions, ultimately improving the player’s experience. By providing a tailored pathfinding solution, A*Grid2D contributes to the evolution of AI-driven mechanics in 2D games, ensuring fluid movement, realistic behavior, and strategic gameplay while shaping the future of NPC navigation
Dynamics of Financial Management Among Higher Education Institutions (HEI) Faculty in the New Normal
No full textThe study utilized a qualitative research design, specifically a Key Informant Interview, in which faculty members were interviewed about the dynamics of their financial management practices. This involved a progressive identification and integration of categories based on the lived experiences of faculty when it comes to financial management practices in the new normal conditions. The data collection was from fifteen participants from different higher education institutions for the academic year 2022-2023. These participants were selected for their first-hand knowledge or experiences in handling their finances. The interviews are loosely structured, relying on a list of issues of the financial management practices of faculty, the challenges they encountered, and the insights they gained from the experience. Methods of analysis were discussed. Themes were generated from the experiences of these faculty: Fair Financial Management Practices, Insufficient Salary, Prioritization and Proper Allocation of Income and Expenses, The Pandemic Savings, Budget Frequency, Factors that Affect Budgeting, “Needs First, Wants Later” "Academic Ranks vs. Budgeting, and Importance and Effectiveness of Budget Plan.
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
University Prescribed Student Uniform Classification Machine Learning Modeling
Get PDFThis study evaluates the performance of three machine learning models, Support Vector Machine (SVM), Neural Network (NN), and Random Forest (RF), in classifying student uniform compliance at ISAT U Miagao using image data. The classification focused on three categories: Not in School Uniform, Female Complete Uniform, and Male Complete Uniform. Model performance was assessed using standard classification metrics. Among the models tested, the Neural Network consistently outperformed the others across all categories, demonstrating its effectiveness in accurately identifying uniform compliance through image data. The SVM also produced strong and reliable results, indicating its viability as an alternative model for this task. In contrast, the Random Forest model showed relatively weaker performance, particularly in recognizing students not in uniform, which may limit its effectiveness in high-accuracy monitoring environments. Overall, the findings highlight the superior capability of deep learning, particularly neural networks, in handling image-based classification tasks. The strong performance of SVM also supports the use of kernel-based approaches for institutional compliance systems. Meanwhile, the lower performance of Random Forest suggests potential limitations in more nuanced visual classification scenarios. These insights support the integration of advanced machine learning models in real-world applications that require reliable and automated compliance monitoring
Gender Performance and Attitudes in Learning Programming
No full textThis study examined the gender differences, academic performance, and attitudes towards programming among students, employing a mixed-methods approach. The study sample consists of male and female students enrolled in programming courses, with data collected through surveys and academic records. Statistical analyses include descriptive statistics, Mann-Whitney tests, Spearman\u27s rank correlation, and coefficient of concordance to examine differences in performance and attitudes between genders and the relationship between academic performance and attitudes towards programming. Descriptive statistics reveal subtle gender disparities, with female students achieving slightly higher grades on average and exhibiting marginally more positive attitudes towards programming across various dimensions, including interest/enthusiasm, comfort/ease, outlook on utility, and importance of programming in future jobs. Mann-Whitney tests confirm significant differences in performance between male and female students, highlighting the need to address gender disparities in programming education. Spearman\u27s rank correlation helps examine how academic performance and attitudes are connected, showing detailed patterns. While the overall correlation between performance and attitudes towards programming is weak, specific dimensions, such as comfort/ease and outlook on utility, show notable negative correlations with grades, suggesting potential areas for intervention. The study\u27s findings underscore the interconnected nature of attitudes toward programming and the complex interplay between academic performance and attitudes. By fostering an inclusive learning environment and implementing evidence-based strategies, educators and policymakers can work towards ensuring equitable learning outcomes and promoting positive engagement in programming education for all students, regardless of gender or perceived academic aptitude
Improved QDCM library & Use of Quadratic Bezier Function for Carotid Artery Plaque System
No full textAtherosclerosis risk assessment through the use of MRI (magnetic resonance imaging) allows the classification of carotid artery plaque into low-risk or high-risk. MRI is generally used for identifying the effect of atherosclerosis on vessel lumens but it can also show the composition, size as well as give information on the plaque, hence providing data that simple stenosis does not offer. The paper reports on methods to: (i) improve the performance of an existing open-source library, and (ii) smoothen the generated 3D view. The QDCM (DICOM library for Qt) was modified by utilizing registers and pointers for faster operation to improve its loading & display of the image by a factor of 10,000% while the generated 3D view was smoothened with the use of quadratic Bezier function
Modeling Faculty Acceptance of LMS: A PLS-SEM Validation of the Technology Acceptance Model in Philippine Higher Education
No full textThis study investigates the structural relationships among perceived ease of use, perceived usefulness, attitude toward use, and acceptance of Learning Management Systems (LMS) among faculty members in Philippine higher education. Grounded in the Technology Acceptance Model (TAM) and validated through Partial Least Squares Structural Equation Modeling (PLS-SEM), the study surveyed 306 faculty from selected State Universities and Colleges (SUCs) in Leyte and Biliran. Results revealed that perceived ease of use significantly influenced both perceived usefulness and attitude toward LMS use, while perceived usefulness had a strong positive effect on both attitude and LMS acceptance. Additionally, attitude toward LMS use emerged as the most substantial predictor of actual LMS acceptance. The measurement model demonstrated strong reliability and validity, and the structural model indicated high explanatory power and predictive relevance. These findings affirm the applicability of TAM in the Philippine academic context and highlight the critical role of faculty attitudes in driving successful LMS adoption. The study recommends institutional strategies that enhance system usability, provide targeted training, and cultivate positive faculty attitudes to support sustainable digital transformation in higher education.