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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Evaluation and Research in Education (IJERE) Journal of Education and Learning (EduLearn) International Journal of Multidisciplinary: Applied Business and Education Research Conference Proceedings International Conference on Education Innovation and Social Science IJOT
Miranda, John Paul P.
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Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Social Sciences Other

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A Comprehensive Bibliometric Analysis of School-Based Physical Activity Research Dofredo, Kyla H.; Pinlac, Jelene T.; Pineda, Kylah R.; Gatus, Lovely L.; Briñas, Norlito Nickson N.; Miranda, John Paul P.; Tolentino, Julius Ceazar G.
International Journal of Multidisciplinary: Applied Business and Education Research Vol. 4 No. 10 (2023): International Journal of Multidisciplinary: Applied Business and Education Res
Publisher : Future Science / FSH-PH Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/ijmaber.04.10.26

Abstract

Physical activity has captured considerable interest from international academic scholars due to its fundamental role in maintaining optimal health. Thus, this study sought to examine the scholarly articles on school-based physical activity, employing a comprehensive bibliometric analysis extracted from the Scopus database spanning 2013 to 2023. A filtering protocol was utilized to guide the selection of articles, and analyses were facilitated solely by Python programming. This research yielded extensive insights encompassing document type, publication rates, citation rates, prevalent keywords, and geographic distribution. The results revealed the prominence of "Articles" as the primary document category. Notably, the year 2020 was observed as the highest publication count, with 2014 being the peak year for citation rates. However, both publication and citation patterns exhibited substantial fluctuations. These analyses collectively identify the United States as the largest contributor among the top ten countries, accompanied by substantial contributions from European nations. The analysis of the top 50 most-cited journal articles indicates a prevalence of articles authored by one to five individuals, with a peak in publications during 2014, followed by a gradual decline. Notably, the keyword "children" prominently emerges across the datasets, underscoring its frequent utilization in the context of school-based physical activity research.
The shifting classroom: impact of heightened seasonal heat in education through sentiment and topic modeling Miranda, John Paul P.; Penecilla, Elmer M.; Gamboa, Almer B.; Hernandez, Hilene E.; Dianelo, Roque Francis B.; Simpao, Laharni S.
International Journal of Evaluation and Research in Education (IJERE) Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v13i4.28918

Abstract

This research applies text mining techniques to examine sentiments and themes among Filipino students adjusting to full in-person classes after pandemic-driven flexible learning, focusing on their experiences during April to June 2023–a period usually marked by vacations due to intense heat. By applying the natural language toolkit (NLTK) for sentiment analysis and Scikit-learn for topic modeling, the study gathered data from Filipino students on their in-person class experiences during this unique calendar shift. Post data cleaning, NLTK was used for sentiment analysis and latent Dirichlet allocation for topic modeling. The findings indicate that the high temperatures adversely affected students, as evidenced by frequent references to terms such as “room,” “focus,” and “hard.” The study identified a mix of positive and negative sentiments and highlighted key issues like academic challenges and the learning environment’s impact. This study also offered insights into students’ coping strategies during extreme heat. These results stressed the importance of considering environmental factors in educational planning and provide actionable insights for institutions to enhance the in-person learning experience, particularly in challenging weather conditions. Moreover, this study demonstrates the effectiveness of sentiment analysis and topic modeling in understanding and unraveling student experiences in specific contexts.
Opinion to Emotion Mining: A Sentiment Analysis towards Super Typhoon Ompong Vinluan, Albert; Goneda, Mamerto T.; Atienza, Francis Arlando L.; Miranda, John Paul P.; Fajardo, Rolando R.; Cabauatan, Dominic C.
International Journal on Orange Technologies Vol. 3 No. 5 (2021): IJOT
Publisher : Research Parks Publishing LLC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31149/ijot.v3i5.1779

Abstract

Twitter as one of the microblogging websites has gained its popularity dues to ease sharing of contents in various forms, which include text, images and links. Social media users post and share real time messages about their opinions or comments on a variety of topics, express their typhoon. The Super typhoon Ompong has been considered as powerful typhoon that struck the Island of Luzon September 15, 2018. It has been the strongest typhoon to strike Luzon since Typhoon Megi in 2010. With this, many tweets have been generated expressing people’s real time reactions and opinions whether it is positive, negative or neutral regarding this phenomena. Owing to the increasing high coverage and impact of Twitter, opinions of people on some issues and their emotion towards the super typhoon ompong were shared through social media can be significantly influenced. It is in this context, that the researchers conducted this study to perform the opinion to emotion mining based on the sentiment analysis towards super typhoon ompong were data was generated and collected through a post and message on twitter. Specifically, it sought to determine the sentiments before, during and after the landfall; and perform data visualization using word cloud.
Assessing novice programmers’ perception of ChatGPT: performance, risk, decision-making, and intentions Miranda, John Paul P.; Yambao, Jaymark A.
Journal of Education and Learning (EduLearn) Vol 19, No 4: November 2025
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v19i4.22328

Abstract

This study explores the novice programmers’ intention to use chat generative pretrained transformer (ChatGPT) for programming tasks with emphasis on performance expectancy (PE), risk-reward appraisal (RRA), and decision-making (DM). Utilizing partial least squares structural equation modeling (PLS-SEM) and a sample of 413 novice programmers, the analysis demonstrates that higher PE of ChatGPT is positively correlated with improved DM in programming tasks. Novice programmers view ChatGPT as a tool that enhances their learning and skill development. Additionally, novice programmers that have a favorable RRA of ChatGPT tend to make more confident and effective decisions, acknowledging potential risks but recognizing that benefits such as quick problem-solving and learning new techniques outweigh these risks. Moreover, a positive perception of ChatGPT’s role in DM significantly increases the inclination to use the tool for programming tasks. These results highlight the critical roles of perceived capabilities, risk assessment, and positive DM experiences in promoting the adoption of artificial intelligence (AI) tools in programming education.
Insights from the vision-mission statements of Philippine and other ASEAN universities: a K-means clustering analysis Tolentino, Julius Ceazar G.; Miranda, John Paul P.
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp3386-3394

Abstract

This study analyzed the vision and mission statements (VMS) of 117 Philippine state universities and colleges (SUCs) and compared them with 330 other ASEAN universities to identify thematic trends and institutional priorities. Using web scraping and K-means clustering, the study identified thematic clusters in VMS. Thematic trends through word frequency and collocation analyses provided further insights and a comparative analysis examined differences between Philippine SUCs and other ASEAN universities. Philippine SUCs’ vision statements formed three clusters: global competitiveness, premier recognition, and regional leadership in science and technology. Mission statements clustered into: mandated functions, global innovation, and advancement in the sciences. Philippine SUCs emphasized institutional prestige, workforce development, and sustainability while other ASEAN universities focus more on knowledge creation, student empowerment, and internationalization. Philippine SUCs aligned their VMS with national development and global ranking metrics and prioritizes institutional recognition and economic contributions more than the other ASEAN universities. Future studies should expand to more private institutions and international comparisons to assess broader higher education trends.
Employers' Perspective on Successful Accounting Information System Internships: A Case Study in Pampanga, Philippines Guanlao, Benedict M.; Calma, Patricia Ann; Jacinto, Janelle A.; Quilicol, Kimberly G.; Estacio, Regine C.; Orlanes, Aljiec M.; Yangga, Angelica Mae G.; Sonza, Andrea R.; Cuellar, Sugar Kate M.; Tua, Ronalyn R.; Calara, Heart MacKenzie N.; Miranda, John Paul P.; Mallari, Gienahlyn M.
Proceedings International Conference on Education Innovation and Social Science 2023: Proceedings International Conference on Education Innovation and Social Science
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This qualitative case study aims to identify the essential skills required by employers when hiring AIS student interns. Additionally, it explores potential recommendations for the university to ensure a successful internship experience for AIS undergraduates. Ten employers were interviewed in person, including six from the accounting and banking industries and four from non-accounting or government sectors. Thematic analysis was employed to analyze the collected data. The study emphasizes the significance of employers' perspectives in helping students prepare for actual work in the industry and guiding the university in enhancing its program structure. The study identified both hard and soft skills necessary for student interns. Hard skills encompass technical proficiency and fundamental accounting knowledge, while soft skills encompass effective communication, teamwork ability, analytical aptitude, time management, adaptability, willingness to learn, trustworthiness, and discipline. Employers emphasize these skills when considering student interns. Furthermore, the study reveals employers' recommendations to the university, including conducting an initial assessment before deployment, ensuring well-trained interns, providing comprehensive support throughout the internship, fostering collaboration between the university and employers, and enabling students to focus on internships without additional subjects. These suggestions serve as valuable insights for the university to enhance the internship program not only for AIS undergraduates but also for students pursuing other professions. The findings of this research can be used as a foundation for future implementation of internship programs, aiming to facilitate successful internships for Accounting Information System undergraduates and students in various field.
A text mining analysis of preservice teachers’ reflective discourses in online teaching: basis for a policy brief Tolentino, Julius Ceazar G.; Miranda, John Paul P.
Journal of Education and Learning (EduLearn) Vol 20, No 1: February 2026
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v20i1.22344

Abstract

This study examined the reflections of 142 preservice teachers who taught online during the COVID-19 pandemic. This study identified common themes, emotions, and patterns in their experiences using sentiment analysis and hierarchical clustering. The most frequently used words, such as “learn,” “experience,” and “time,” highlight themes of learning and action. Sentiment analysis shows that most of their reflections are positive, using words like “well,” “good,” and “great.” Hierarchical clustering revealed three main themes in their reflections: i) professional growth and development; ii) passion for teaching and connection; and iii) adaptability and resilience. These themes show the complex nature of their experiences. While focusing on personal and professional growth, a strong commitment to teaching, and adaptability in challenging situations was evidenced. The findings of this study will help create a policy brief addressing these themes. Recommendations include strategies for professional growth in online teaching, encouraging a love for teaching through online platforms, and improving teacher training programs to build adaptability and resilience. Policymakers and educators can use these insights to develop effective policies and practices that support preservice teachers in online teaching even during health crises or similar disruptions.
Co-Authors Atienza, Francis Arlando L. Briñas, Norlito Nickson N. Cabauatan, Dominic C. Calara, Heart MacKenzie N. Calma, Patricia Ann Cuellar, Sugar Kate M. Dianelo, Roque Francis B. Dofredo, Kyla H. Estacio, Regine C. Fajardo, Rolando R. Gamboa, Almer B. Gatus, Lovely L. Goneda, Mamerto T. Guanlao, Benedict M. Hernandez, Hilene E. Jacinto, Janelle A. Mallari, Gienahlyn M. Orlanes, Aljiec M. Penecilla, Elmer M. Pineda, Kylah R. Pinlac, Jelene T. Quilicol, Kimberly G. Simpao, Laharni S. Sonza, Andrea R. Tolentino, Julius Ceazar G. Tua, Ronalyn R. Vinluan, Albert Yambao, Jaymark A. Yangga, Angelica Mae G.