Scientific Publications

Publication Title: Preservice Science Teachers’ Preparedness for Integrating AI in Science Teaching: A Structural Equation Modeling

Author/s: Maricel Amandoron, Cleford Yanson, Sherelyn Banzon, Joy Salundaguit, Lenny Rose Tejero, Ryan Mahilum, Emerita Tan, Lynne Graham-Wilberforce, Christeodoflor Ramos, Edralin General, Reynaldo Tondo Jr., Gerly Alcantara, Romel Mutya

Title of Journal Publication: Journal of Technology and Science Education

Date: January 2026

Vol. No. & Issue No.: Vol. No. 15, Issue No. 3

ISSN/ISBN: p-ISSN: 2016-6374

DOI/LINK: https://doi.org/10.3926/jotse.3555 

Indexed: SCOPUS

ABSTRACT:

The integration of artificial intelligence (AI) in science education is becoming essential, yet research on preservice science teachers’ preparedness for AI adoption remains scarce. This study addressed this gap by examining the factors influencing AI integration readiness using a Structural Equation Modeling (SEM) approach. Data were collected from 350 preservice science teachers in private and public higher education institutions through a structured survey. The SEM results revealed that prior technology experience significantly predicted AI readiness (ß = 0.257, p < 0.001), confidence in learning AI (ß = 0.273, p < 0.001), and self-transcendent goals (ß = 0.267, p < 0.001). Additionally, attitude towards AI strongly influenced AI readiness (ß = 0.504, p < 0.001) and confidence in learning AI (ß = 0.338, p < 0.001). Engagement in AI learning emerged as the strongest predictor of preparedness for AI integration (ß = 0. 803, p < 0.001). These findings highlight the importance of AI-focused teacher training programs and experiential learning strategies to enhance AI competency. The study underscores the need for curriculum enhancements to foster AI engagement and mitigate AI-related anxiety, ensuring that future educators are well-equipped for AI-driven pedagogy in science education. 

KEYWORDS:

AI integration, Preservice science teachers, Science teaching, Structural equation modeling (SEM)

Publication Title: Sewing New Lives: The Dual Impact of Service-Learning on Sewing Technology Skills on Persons Who Used Drugs and University Student Volunteers

Author/s: Jacquiline Dela Cruz, Emily Costan, Aurelio Vilbar, Gerly Alcantara, Felix Costan, Ivy Carascal, Lislee Valle

Title of Journal Publication: Springer Nature Link

Date: 02 January 2026

Vol. No. & Issue No.:

ISSN/ISBN:

DOI/LINK:

Indexed: SCOPUS

ABSTRACT:

Persons who used drugs” (PWUD) refers to individuals who engage in the consumption of illegal substances and other wide-ranging drugs. Previously stereotyped as “drug addicts,” PWUDs dream to rebuild life but often receive social sigma and work discrimination. Cognizant of the importance of retooling the PWUDs’ skills for employment, the 46 students of Clothing Construction of Cebu Technological University-Danao Campus conducted a service-learning (SL) project to teach the nine PWUDs in operating high-speed embroidery machines to sew skirts and blouses for technological skills and on the students’ course content and personal growth. It employed the following mixed-methods data-gathering procedures to determine the SL impact: in-depth interviews, observations, and focus group discussions conducted by independent researchers to minimize bias. As a triangulation, three independent assessors evaluated the PWUDs’ skirts and blouses using the National Competency standardized assessment tool. After The SL, the findings were as follows: (1) Students perceived that their mastery of sewing technology improved personal growth and public service. (2) The PWUDs received the National Certificate II from the assessors, which certified sewing technological competence. The program helped them develop their confidence, which enabled them to rebuild their lives. The study highlighted the impact of SL as a transformative method in teaching technology through community volunteerism.

Publication Title: Bibliometric mapping of mathematical pedagogies

Author/s: Lislee C. Valle

Title of Journal Publication: Malque Publishing

Date: February 17, 2026

Vol. No. & Issue No.: Vol. No. 9, Issue No. 11

ISSN/ISBN:

DOI/LINK: https://doi.org/10.31893/multirev.2026538

Indexed: SCOPUS

ABSTRACT:

Over the years, continuous developments in mathematics pedagogy have contributed to improved instructional outcomes across diverse educational contexts. In response to these developments, this study examines the evolving landscape of mathematics pedagogies through a bibliometric analysis of peer-reviewed research published between 2015 and 2024. This study aims to identify dominant themes, research trajectories, and emerging trends that characterize contemporary mathematics education. A total of 1,642 journal articles indexed in the Scopus database were analyzed using Bibliometrix and VOSviewer. Keyword co-occurrence analysis, thematic clusters, overlay visualizations, and trend topic mapping were employed to reveal the field’s intellectual structure and evolution. Results revealed an annual growth rate of 11.43%, suggesting increasing scholarly attention to mathematics pedagogy. The United States of America and Australia emerged as the top contributors in terms of research output and collaboration. The analysis highlights two major themes: technology-enhanced learning and pedagogies, as well as teaching strategies and instructional design. The study revealed a shift from conventional instructional models to a more progressive approach that prioritizes innovative teaching methods and technology integration. This significant change aimed for a more adaptive, data-driven, and integrative approach, promoting a method that prioritizes students in mathematics instruction. Additionally, the study highlights a growing interest in advanced technologies, such as artificial intelligence, within the field of mathematics education. Despite these contributions, the study has several limitations. The analysis is only used Scopus-indexed journal articles published within a ten-year period, excluding relevant studies indexed in other databases or disseminated through non-indexed sources. Moreover, as a bibliometric study, the findings describe publication patterns and thematic trends but do not evaluate the effectiveness of pedagogical practices in the classroom. Overall, this study provides a comprehensive overview of current trends in mathematics pedagogy and offers evidence-based insights to inform future research, instructional innovation, and policy development in mathematics education.

KEYWORDS:

Mathematics education, learning strategies, technology-enhanced learning, educational technology, bibliometric analysis

Publication Title: Why Structured Instruction Matters: A Comparative Effect of Four Instructional Models on Mathematics Achievement in Printed Modular Distance Learning

Author/s: Quennie Rose H. Abao, Gerly A. Alcantara

Title of Journal Publication: International Journal of Learning, Teaching and Educational Research

Date: February 20, 2026

Vol. No. & Issue No.: Vol. No. 25, Issue No. 3

ISSN/ISBN: p-ISSN: 1694-2493, e-ISSN: 1694-2116

DOI/LINK: https://doi.org/10.26803/ijlter.25.3.9 

Indexed: SCOPUS

ABSTRACT:

The COVID-19 pandemic made substantial changes in educational delivery, prompting the Philippine public school system to implement printed modular distance learning to maintain instructional continuity. Prior studies have examined modular learning outcomes; however, empirical studies comparing instructional models within a fully printed modular approach are limited. Addressing this gap, the study examined the comparative effect of four instructional models, 5A, 5E, explicit direct instruction, and Gagné’s nine events of instruction, on Grade 10 students’ mathematics achievement within a printed modular learning environment. Using a quasi-experimental design, the study involved 80 Grade 10 students from four public junior high schools in northern Cebu, Philippines. Instructional modules aligned with each model were developed and administered, followed by a summative assessment to measure students’ achievement. The results of a one-way analysis of variance revealed statistically significant differences in achievement across the instructional models (F(3, 76) = 17.40, p < .001), with post hoc results indicating that Gagné’s nine events of instruction resulted in significantly higher student performance than the other approaches. Qualitative findings from student reflections further showed that clear explanations, guided practice, and structured feedback were important in the modular context. These findings contribute theoretically by reinforcing the role of structured instructional sequencing in self-directed learning and provide practical implications for the design of printed mathematics modules in low or no-connectivity settings

KEYWORDS:

Distance learning; Gagné’s nine events of instruction; instructional models; mathematics performance; printed modular learning

Publication Title: Structural Analysis of Public Trust and the Mediating Role of Government Image in Typhoon-Induced Disaster Response

Author/s: Reciel Ann Cullano, Ann Myril Tiu, Purity Mata, Kafferine Yamagishi, Gamaliel Gonzales, Fatima Maturan, Samantha Shane Evangelista, Angelo Burdeos, Lanndon Ocampo

Title of Journal Publication: Journal of Public Affairs

Date: February, 2026

Vol. No. & Issue No.: Vol. No, 26, Issue No. 1

ISSN/ISBN:

DOI/LINK: https://doi.org/10.1002/pa.70103

Indexed: SCOPUS

ABSTRACT:

Recent reports modeled the quality of government disaster response via service quality, public trust, perceived justice, and government image in disaster situations. This study explores the mediating role of government image in the relationships between service quality, perceived justice, and public trust, thereby addressing the existing gaps in understanding these complex interactions. Using a cross-sectional survey with non-probability sampling, 860 valid responses were analyzed to test the hypothesized direct and mediating effects related to Typhoon Rai, which hit the Philippines in December 2021. The case was chosen for its significant disaster event, which caused broad spatial and temporal impacts, and the Philippines’ frequent exposure to about 20 typhoons annually. Results from Partial Least Squares-Structural Equation Modeling generate insights from the proposed model’s five hypothesized paths and two mediation effects. We uncover salient results to serve as inputs for disaster risk reduction management. All of the main hypothesized structural paths are statistically supported, except for the path from service quality to public trust, whose significance changed after the Gaussian copula analysis was performed to remove possible endogeneity problems. Thus, public trust is developed when there is quality information and fairness in the delivery of services. The government image fully mediates the overall relationship between service quality and public trust, while a partial mediating effect was found between perceived justice and public trust. We discussed insights in light of findings and systematically connected the results to the emerging discussions in the field.

KEYWORDS:

Publication Title: Modeling behavioral Intention toward generative AI use in higher education English language teaching

Author/s: Ronnel Victor B. Kilat

Title of Journal Publication: Frontiers in Education

Date: February 20, 2026

Vol. No. & Issue No.: Vol. No. 11

ISSN/ISBN: 

DOI/LINK: https://doi.org/10.3389/feduc.2026.1743380 

Indexed: SCOPUS

ABSTRACT:

The rapid emergence of generative artificial intelligence (AI) presents new opportunities and challenges for English language teaching (ELT) in higher education, particularly in developing and resource-diverse contexts. Responding to limited empirical evidence from the Philippine higher education, this study examines the behavioral intention of higher education English language teachers in Cebu to adopt generative AI in instructional practice. Guided by an integrated framework combining the Unified Theory of Acceptance and Use of Technology (UTAUT) and Expectancy-Value Theory (EVT), and extended with perceived knowledge of AI and perceived privacy concerns, the study adopts a predictive, theory-guided design. Survey data were privacy concerns, the study adopts a predictive, theory-guided design. Survey data were collected from 488 higher education teachers across urban and rural state universities and local colleges in Cebu and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show that performance expectancy predicts  perceived attainment value, effort expectancy predicts perceived utility value, and social influence shapes perceived attainment value, perceived intrinsic value, and perceived cost. Among downstream mechanisms, perceived attainment value and perceived utility value significantly predict perceived knowledge of AI, which emerges as the strongest direct predictor of behavioral intention. Perceived intrinsic value does not significantly predict perceived knowledge of AI, and perceived privacy concerns do not significantly predict behavioral intention after accounting for value-based and knowledge-based predictors. Moderation analysis indicates that age does not significantly moderate any structural relationships, while sex moderates only the relationship between effort expectancy and perceived utility value. Overall, the findings indicate that behavioral intention to adopt generative AI in higher education ELT is primarily driven by performance-related beliefs, value-based appraisals, and self-assessed AI competence, rather than by demographic characteristics or privacy concerns alone. The study contributes a context-sensitive, theory-integrated explanation of AI adoption intentions and offers implications for AI literacy, professional development, and responsible institutional integration in higher education English language teaching.

Publication Title: Modeling the Relationship between Leadership Styles and Good Governance Practices in Predicting Effective Leadership among Youth Government Officials

Author/s: Romel C. Mutya, Marian Mae Sapanta, Jefrey M. Tagud, Reynaldo C. Tondo Jr., Janine Recopelacion, Angeline M. Pogoy

Title of Journal Publication: Frontiers in Political Science

Date: March 23, 2026

Vol. No. & Issue No.: Vol. No. 8

ISSN/ISBN:

DOI/LINK: https://doi.org/10.3389/fpos.2026.1817178

Indexed: SCOPUS

ABSTRACT:

Effective leadership among youth government officials is crucial to fostering accountable, participatory governance at the grassroot level. However, limited research has explored how leadership in youth-led public service. This study examined the relationships among leadership styles, good governance practices, and effective leadership among youth government officials. A cross-sectional research design using a standardized survey was employed with 332 youth government officials across local government units in Central Visayas, Philippines. A partial least squares structural equation modeling approach was employed to examine the direct and indirect relationships among the variables. The path analysis showed that transactional leadership style significantly predicted all five dimensions of good governance: transparency, participation, accountability, rule of law, and continuous implementation. Meanwhile, the transformational leadership style has a significant influence on the rule of law, rather than on other governance dimensions. Regarding the predictors of effective leadership, significant effects were found from transparency, accountability, and the rule of law, indicating their strong contribution to youth leadership effectiveness. The findings conclude that transactional leadership exerts a more substantial influence on good governance practices than transformational leadership, particularly in promoting transparency, participation, accountability, the rule of law, and continuous implementation. This implies that youth leadership training programs should emphasize practical, results-oriented leadership strategies aligned with governance principles to enhance leadership effectiveness in public service.

Publication Title: Bloomigo: A Wireless IoT-Based Hydroponics Control System for Efficient and Sustainable Farming

Author/s: Tomashita P. Arenas, Vincent Alen P. Castro, Chona R. Dagatan, Krisha Ann O. Hermosilla, Gem Felix T. Otadoy, Kyle Jake S. Serie, Jestoni P. Tan, Joel Jr. Ypil

Title of Journal Publication: Conference Proceedings 6th Cebu International Congress on Science, Engineering, Social Sciences & Education

Date: March 27, 2026

Vol. No. & Issue No.: 

ISSN/ISBN: e-ISSN: 978-989-9121-63-8

DOI/LINK: https://uruae.org/siteadmin/upload/UA0326180.pdf?

Indexed: SCOPUS

ABSTRACT:

This study presents the development and evaluation of Bloomigo, a wireless Internet of Things (IoT)-based automation system designed to optimize environmental conditions in hydroponic greenhouses. The project addresses key challenges in traditional farming, including labor-intensive monitoring, inconsistent climate control, and inefficient resource use. Bloomigo integrates temperature and humidity sensors with actuators for fans, lights, misting, and irrigation, all controlled via an Android mobile application. The system features three control modes-Manual, Automation, and Machine Learning-to provide flexibility and precision in managing growing environments. Field deployment across three greenhouse locations in Cebu, Philippines, demonstrated high sensor accuracy (MAE < 0.254 °C for temperature and < 0.698% for humidity), rapid actuator response times (average delay of 1.83 seconds),  and strong user satisfaction (UI usability mean score of 4.39/5). Post-implementation results show significant reductions in manual tasks, enhanced operational efficiency, and improved environmental stability. This research highlights Bloomigo’s potential to make hydroponic farming more accessible, efficient, and sustainable, particularly for small-to-medium-scale urban agriculture initiatives.

KEYWORDS:

Bloomigo, Hydroponic Farming, IoT Automation, Environmental Monitoring, Smart Agriculture

Publication Title: Characterization and Emission Control Potential of Shell-Based Sorbents in Internal Combustion Engine Exhaust System

Author/s: Marlon D. Mata

Title of Journal Publication: Conference Proceedings 6th Cebu International Congress on Science, Engineering, Social Sciences & Education

Date: March 27, 2026

Vol. No. & Issue No.:

ISSN/ISBN: e-ISSN: 978-989-9121-63-8

DOI/LINK: https://doi.org/10.17758/URUAE32.

Indexed: SCOPUS

ABSTRACT:

Despite the enactment of the Philippine Clean Air Act over thirty years ago, effective control of air pollution remains a persistent challenge, particularly from vehicular emissions, which account for 20-35% of air pollutants. This study aims to explore sustainable alternatives for capturing vehicular emission pollutants using calcium oxide (CaO) derived from waste materials such as oyster shells, mussel shells, and chicken eggshells. These biomaterials were analyzed to determine their potential as low-cost and eco-friendly sorbents. X-Ray Fluorescence (XRF) was used to assess elemental composition, Fourier Transformed Infrared Spectroscopy (FTIR) to identify functional groups, and Thermo-Gravimetric Analysis (TGA) to evaluate thermal stability under simulated exhaust conditions. Results revealed that all samples contained high levels of calcium carbonated (CaCO₃ ), with mussel shells having the highest calcium concentration (38.371%). FTIR confirmed the presence of CaCO₃ functional groups, while TGA showed favorable thermal decomposition properties, particularly in mussel shells, which began decomposing above 600°C. The presence of hydroxyl compounds in mussel shells further suggests enhanced adsoption capabilities. Overall, mussel shells emerged as the most promising material for emission pollutant capture, but further testing in real-world conditions is recommended to validate their practical application in environmental pollution control systems.

KEYWORDS:

Calcium Carbonate, Elemental Composition, Emission Pollutant, Functional Group, Material Characterization, Thermal Stability, Waste Shells

Publication Title: ChatGPT in research and practice: Insights into applications, challenges, and future prospects

Author/s: Lislee C. Valle

Title of Journal Publication: Multidisciplinary Reviews

Date: April 10, 2026

Vol. No. & Issue No.: Vol. No. 9, Issue No. 11

ISSN/ISBN:

DOI/LINK: https://doi.org/10.31893/multirev.2026524  

Indexed: SCOPUS

ABSTRACT:

The emergence of ChatGPT, a sophisticated language model developed by OpenAI, has revolutionized the fields of artificial intelligence (AI) and natural language processing (NLP). This study offers a comprehensive overview of current research directions related to ChatGPT, analyzing its applications, challenges, and prospects. This most up-to-date study extracts and through overview using text mining techniques. The evaluation, conducted through descriptive statistical analysis of keyword frequency, co-occurrence, and related metrics, highlights current research issues, indicating that efficacy evaluation remains an ongoing area of investigation. Distinct from previous studies, this research extends the findings by classifying the overarching impact of ChatGPT across all fields, leveraging deep learning algorithms through Generative Artificial Intelligence (Gen AI), utilizing BERT Base Multilingual Uncased for sentiment analysis. Concurrency, it contrasts these results with those obtained from traditional analysis using the Vader Lexicon machine learning approach, revealing a consistent and overwhelmingly positive impact that significantly outweighs negative biases. While ChatGPT demonstrate transformative potential across diverse sectors, ranging from enhancing business operational strategies and content innovation to streamlining programming tasks and fostering personalized learning or clinical simulations, results also underscore critical concerns regarding academic integrity, biased AI responses, and diminished critical thinking. The metrics evaluation using Gen AI and machine learning shows good performance; The findings further suggest that Gen AI opens more promising avenues for enhancing bibliometric analysis, providing a robust framework for evaluating academic documents specifically, and advancing natural language processing methodologies more broadly.

KEYWORDS:

Publication Title: Lived experienced of Pre-service Elementary teachers on blended learning

Author/s: Krystal Marie Ceniza, Jessica Marie Cuesta, William Mae Gatab, Rhonamie Loro, Hanna Mae Tagalog, Dianne Lyn Tagra, Mia Laurito, Ronnel Victor Kilat, Bsyche Rivera, Lislee Valle

Title of Journal Publication: Journal of Education and Learning

Date: 2026

Vol. No. & Issue No.:  Vol No. 20, Issue No. 02

ISSN/ISBN: e-ISSN: 2089-9823

DOI/LINK: https://doi.org/10.11591/edulearn.v20i2.23199 

Indexed: SCOPUS

ABSTRACT:

The primary purpose of this study was to determine: i) experiences; ii) various resources; iii) varied activities; iv) 21st-century skills acquisition; v) challenges experienced; and vi) solutions to the challenges of the pre-service elementary teachers in blending learning. The study employed qualitative research and utilized Straussian grounded theory as a research design to guide data collection and coding to identify emerging categories and generate theory. Purposive sampling was employed to select the ten pre-service elementary informants with experience with blended learning. In analyzing the data gathered, Strauss and Corbin’s coding methods, namely open, axial, and selective coding, were employed. The six themes were created based on the raw responses of informants, namely; i) varied online resources; ii) tangible learning materials; iii) varied learning activities; iv) acquired 21st-century skills; v) challenges of blended learning; and vi) addressing the challenges. A theory emerged, “magma theory” , which further strengthens the characterization of having “shared experiences” , as manifested by the pre-service elementary teachers in this blended learning. The primary findings of this study were that pre-service teachers can overcome challenges in blended learning with adequate support from tools. Furthermore, they can also improve their 21st-century skills through appropriate activities that contribute to lifelong learning.

KEYWORDS:

21st-century skill; Blended learning; Online resources; Pre-service teacher; Straussian grounded theory; Tangible learning material

Publication Title: Beyond Instagram: Aspect-based sentiment analysis and cross-platform opinion mining in Philippine tourism user-generated content

Author/s: Marites Bejoc, Gladies Mae Olivar

Title of Journal Publication: Edelweiss Applied Science and Technology

Date: April 24, 2026

Vol. No. & Issue No.: Vol. No. 9, Issue No. 9

ISSN/ISBN:

DOI/LINK: https://doi.org/10.55214/2576-8484.v9i9.10064 

Indexed: SCOPUS

ABSTRACT:

This study examines how diverse social media platforms contribute uniquely to the promotion of Philippine tourism destinations through user-generated content (UGC), moving beyond the Instagram-centric focus of previous research. Using a mixed-methods approach that combines quantitative content analysis, platform analytics, and qualitative surveys, this research analyzes UGC patterns across Instagram, TikTok, YouTube, Google Reviews, TripAdvisor, and travel blogs for five popular Philippine tourist destination over a 12-month period. The study reveals significant platform differentiation in content types, audience engagement, and influence on travel decisions within the Philippine tourism context. TikTok emerged as the primary driver for spontaneous travel decisions within the among Gen Z Filipino and international travelers, with 78% of survey respondents indicating this platform’s influence. Google Reviews maintained the strongest influence on accommodation and restaurant choices, with an 89% consultation rate. YouTube travel vlogs demonstrated the highest conversion rate for island-hopping and adventure travel planning, with 34% of viewers booking featured Philippine destinations within six months. While Instagram maintains the largest volume of Philippine destination leverage complementary strengths across multiple platforms rather that concentrating efforts on a single channel. These finding suggest that Philippine tourism marketers should adopt platform-specific content strategies rather than cross-posting identical content, with implications for the Department of Tourism’s budgets and destination marketing campaigns.

Publication Title: Early Prediction of Student Academic Status Using SMOTE-Driven Multiclass Classification

Author/s: Ivy Batican, Lislee Valle, Edralin General, Joshlen Lim, Sarah Jane Colina

Title of Journal Publication: 8th International Conference on Electronics, Computer, and Computation

Date: April 24, 2026

Vol. No. & Issue No.:

ISSN/ISBN: p-ISSN: 979-3315-4525-3, e-ISSN: 979-3315-4524-6

DOI/LINK: https://doi.org/10.1109/ICECCO67619.2026.11488765

Indexed: SCOPUS

ABSTRACT:

Early identification of students at academic risk is essential for timely intervention and improved educational outcomes. However, predictive modelling in this domain is challenged by class imbalance and the need for interpretable models that support institutional decision-making. This study proposes a SMOTE-driven multiclass machine learning framework for the early prediction of student academic status. Using institutional records, relevant academic, demographic, and engagement features were prepocessed through appropriate encoding and normalization techniques. Synthetic Minority Over-sampling Technique (SMOTE) was applied to address class imbalance across multiple outcome categories. Several machine learning models, including Logistic Regression and tree-based classifiers, were trained and evaluated using stratified k-fold cross-validation to ensure robustness and reproducitibility. Model performance was assessed using accuracy, precision, recall, F1-score, and multiclass confussion matrices. the results demonstrate that class balancing significantly improves predictive performance, particularly for minority academic outcome classes. Feature interpretation revealed that prior academic performance, assessment engagement, and attendancerelated variables were the most influential predictors across models. The findings confirm the effectiveness of combining data balancing with interpretable machine learning for early academic risk detection. This work contributes a practical and explainable framework that can support data-driven academic monitoring and targeted student support strategies in higher education institutions.

Publication Title: Educational Data Mining for Predicting Student Retention and Performance: A Supervised Learning Approach

Author/s: Ivy Batican, Sarah Jane Colina, Lislee Valle, Edralin General, Joshlen Lim

Title of Journal Publication: 18th International Conference on Electronics, Computer, and Computation (ICECCO 2026)

Date: April 24, 2026

Vol. No. & Issue No.:

ISSN/ISBN: p-ISSN: 979-8-3315-4525-3, e-ISSN: 979-8-3315-4524-6

DOI/LINK: https://doi.org/10.1109/ICECCO67619.2026.11488782

Indexed: SCOPUS

ABSTRACT:

Student dropout and academic failure affect both academic performance and student futures, with them being major concerns in higher education. Predictive analytics has become a valuable tool for identifying at-risk students and supporting timely interventions with the increasing availability of educational data. Many educational institutions often encounter huge struggles in identifying which influential factors most accurately or precisely affect or predict dropout and academic failure outcomes despite having large amounts of student data. This research study addresses the need for data-driven techniques in being able to quickly identify at-risk students, to develop specific study intervention strategies in higher education by applying machine learning algorithms to analyze student data to predict dropout and academic success and identifying the most influential factors that affect student dropout or academic outcomes. A student dataset from the UCI Machine Learning Repository is studied by this analysis. Supervised machine learning algorithms such as Decision Tree, Logistic Regression, Random Forest, and XGBoost predict dropout and academic success and conduct feature selection, followed by model evaluation using performance metrics such as accuracy, precision, recall, and F1-score. Students with a lower number of approved courses in the second semester are most likely to drop out according to the condition of preliminary investigations. This study can help educational institutions identify at-risk students in time and implement targeted interventions to reduce dropout rates.

Publication Title: Teaching beyond expertise: a case study of out-of-field teachers by qualifications in basic education

Author/s: Jeanette Rose Durano, Marjorie L. Layasan, Olcee C. Maramara, Precious Dianne N. Neri, Psyber V. Orio, Emerita M. Tan, Romel C. Mutya

Title of Journal Publication: Journal of Education and Learning

Date: May 2026

Vol. No. & Issue No.: Vol. No. 20, Issue No. 02

ISSN/ISBN: e-ISSN: 2089-9823

DOI/LINK: https://doi.org/10.11591/edulearn.v20i2.22552 

Indexed: SCOPUS

ABSTRACT:

In a global context of increasing demands for diverse skill sets and innovative teaching, the phenomenon of out-of-field teachers (OFT) by qualification has gained attention. This study explored teachers’ experiences transitioning between elementary and high school teaching. A descriptive case study phenomenological approach was employed, involving 7 participants selected through purposive sampling. Colaizzi’s seven-step method was utilized to analyze the data. Results indicated that OFT faces challenges such as limited subject matter knowledge, staying current in evolving fields, and adapting to diverse student needs. To cope, they seek professional development, collaborate with colleagues, and understand different learning styles. Teaching outside their expertise makes educators adaptable, resilient facilitators committed to continuous professional development. Handling unfamiliar content enhances problem-solving skills and resourcefulness in discovering effective teaching strategies. The research highlights the transformative impact of transitioning between elementary and high school levels, resulting in versatile, creative, and passionate educators dedicated to continuous improvement in education.

KEYWORDS:

Basic education; Case study; Lived experiences; Out-of-field teachers; Qualitative study

Publication Title: Development and Validation of a Good Governance Practices (GGP) Scale of Student Leaders

Author/s: Romel C. Mutya

Title of Journal Publication: Masyarakat, Kebudayaan dan Politik

Date: May 2026

Vol. No. & Issue No.: Vol. No. 38, Issue No. 04

ISSN/ISBN: e-ISSN: 2086-7050

DOI/LINK: https://doi.org/10.20473/mkp.V38I42025.401-417 

Indexed: WOS

ABSTRACT:

Good governance is becoming an increasingly important component of public institutions; however, the instruments used to assess good governance practices among students leaders are inadequate, resulting in a gap in assessing and improving leadership. This study aims to produce an assessment instrument that can identify and measure the good governance practices (GGP) of prospective student leaders. The method used is a quantitative research design with 349 survey responses from student leaders comprises 20 items distributed across five dimensions—accountability (3), effectiveness and efficiency (6), participation (5), rule of law (3), and transparency (3)—and shows strong factor loadings (0.710-0.907). The scale exhibited good reliability and model fit, as indicated by X²/df = 2.444, RMSEA = 0.054, SRMR = 0.038, and CFI = 0.948. Composite reliability values ranged from 0.780 to 0.904, while Cronbach’s alpha coefficients varied between 0.793 and 0.902, confirming strong internal consistency. Results report a psychometrically sound instrument to measure good governance practices of student leaders. This study concludes that the resulting instrument can educate leadership and inform policymaking to establish quality student governance.

Publication Title: Translanguaging Toward Learning Productivity

Author/s: Rhodora G. Magan

Title of Journal Publication: IGI Publishing

Date: 2026

Vol. No. & Issue No.:

ISSN/ISBN: e-ISSN: 9798337350394

DOI/LINK: https://doi.org/10.4018/979-8-3373-5037-0.ch002 

Indexed: SCOPUS

ABSTRACT:

This chapter reports on a study conducted to assess the added value of enhanced translation in terms of depth of understanding-specifically when translation goes beyond banal replication into another language and instead takes cultural aspects into account, through various language-assistance methods, each differing in practicality, cost, time, investment, and effectiveness. The findings indicate a preference for translating both professors’ lectures and students’ interactions, despite the time-intensive nature of this approach. Translation helps students overcome shyness and concentrate on the content of discussions. While some students actively participate in dialogue, many remain silent, posing challenges for teachers accustomated to interactive teaching methods. Nevertheless, translation significantly improves material comprehension, reflecting mutual appreciation from both students and instructors, despite the added costs. This study contributes to the ongoing discourse on the positive role of translation in enhancing students’ learning productivity.

Publication Title: Weathering the Off-Season: The Future of Uttarkashi’s Hotel Industry

Author/s: Rhodora G. Magan

Title of Journal Publication: Ivey Publishing

Date: 2026

Vol. No. & Issue No.:

ISSN/ISBN:

DOI/LINK: https://www.iveypublishing.ca/…/weat…/01tOF00000A7u4XYAR

Indexed: SCOPUS

ABSTRACT:

In October 2025, the newly elected president of Hotel Association Uttarkashi in the beautiful yet fragile landscape of Uttarkashi, India was grappling with the region’s economic and environmental challenges. Uttarkashi’s tourism-driven economy was highly depended on a narrow six-month window (May to November) aligned with pilgrimage to sacred sites. The surge in tourists during this peak period tended to drive short-term profits, but it also overburdened local infrastructure, degraded the ecology, and left workers unemployed during the harsh off-season. Discussions on the various dilemmas the association was facing revolved around one major issue. Should the association build up its economic resilience by investing in expanding year-round tourism offerings (e.g., adventure, wellness, ecological, rural tourism) or just continue optimizing six-month seasonal pilgrimage tourism for higher, but short-lived, returns? The association’s president had to weigh all options to ensure a thriving economy for his members, inclusive growth for the association, preserved ecological integrity, and a safeguard for the spiritual identity of the region.

Publication Title: Medieval European Witchcraft and the Perception of Women in Select Philippine Short Stories

Author/s: Rhodora G. Magan

Title of Journal Publication: IIUM Journal of English Language and Literature

Date: 2026

Vol. No. & Issue No.: Vol. No. 18, Issue No. 1

ISSN/ISBN: e-ISSN: 1985-3106

DOI/LINK: https://doi.org/10.31436/asiatic.v18i1.3212 

Indexed: SCOPUS

ABSTRACT:

This study addresses the persistent narrative of witchcraft-related violence in the contemporary era by delving into its historical root – the medieval practice of witch-hunts. It investigates gendered motifs linked to women accused of witchcraft and sorcery, using Morgan le Fay in Thomas Malory’s Morte Darthur as a reference. By examining gender stereotypes, we aim to demonstrate how medieval European concepts of witchcraft and sorcery have become entrenched in modern perceptions of women. This investigation employs Philippine literary texts – The Witch by Edilberto Tiempo and May Day Eve by Nick Joaquin, characterising women exhibiting postcolonial dispositions. Our central hypothesis holds that these contemporary stories adapt the medieval classic. The findings point to the medieval traces in the characters of Minggay and Agueda, leading to their societal categorisation as metaphorical witches. Textual analysis exemplifies strategies such as “un/belonging” the self to demonstrate “herstory,” acknowledging one’s beliefs to express innate tendencies, and challenging social structures to promote reclamation of oppressive structures. This study contributes to understanding the challenged “mythical” nature of women’s identity in the modern era. Hence, the adaptive platform of medieval European influence lends support to stablishing women’s positionality rather than their essentiality.

Publication Title: From waste to taste: Assessing the viability of coconut (Cocos nucifera) pulp as an ingredient in meatball production

Author/s: Niño Cris H. Casas, Ginalen B. Martel, Fedilis Dei B. Atis, Rizelle M. Pasana, Rolly Shem M. Perez, Felix C. Costan, Jacquiline R. Dela Cruz, Romel C. Mutya, Catherine C. Terana 

Title of Journal Publication: Journal of Applied and Natural Science

Date: 2026

Vol. No. & Issue No.: Vol. No. 18, Issue No. 1

ISSN/ISBN: e-ISSN: 1985-3106

DOI/LINK: https://doi.org/10.31436/asiatic.v18i1.3212 

Indexed: SCOPUS

ABSTRACT:

One by-product of the coconut (Cocos nucifera) is the coconut pulp (sapal), obtained from the coconut meat after the extraction of the coconut milk. This residue is typically discarded as waste. The nutritional value of this underutilised waste is particularly significant, with a notable protein concentration. The present study aimed to assess the viability of coconut pulp as an ingredient in meatball production and to explore its potential for use in new product development. The respondents in this study were identified in Danao City, Cebu, Philippines, through a random sampling technique, and served as the source of the necessary data. This study employs a descriptive quantitative research method. This experimental study used four formulations (F1-F4). This study determined the most preferred formulation through sensory evaluation, including descriptive testing of the product’s taste, texture, aroma, appearance, and overall acceptability across for formulations. The evaluation was conducted by 20 food-experts and 80 non-experts. Analysis of Variance was used to examine statistically significant differences among the distinct groups. F4 got the highest mean score of the different attributes, namely taste (x̄ = 4.40; x̄= 4.55) texture (x̄ = 4.25; x̄ = 4.59) aroma (x̄ = 4.55; x̄ = 4.66) appearance (x̄ = 4.65; x̄ = 4.65), and overall acceptability (x̄ = 4.55; x̄ = 4.74), as perceived by experts and non-experts, respectively. This implies that among the four formulations, the F4 is the most preferred coconut-based meatball substitute. Overall, this study offers a healthier option and addresses the underutilization of coconut pulp.

KEYWORDS:

Cocos nucifera, Coconut pulp, Meatball production, Sensory evaluation, Underutilized waste

Publication Title: Brain Drain Factors as Determinants of Teachers’ Intention to Teach Abroad in the Philippine Education

Author/s: Ryan M. Mahilum, Romel C. Mutya

Title of Journal Publication: International Journal of Learning, Teaching and Educational Research

Date: 2026

Vol. No. & Issue No.: Vol. No. 25, Issue No. 5

ISSN/ISBN:

DOI/LINK: https://doi.org/10.26803/ijlter.25.5.29

Indexed: SCOPUS

ABSTRACT:

Brain drain compromises teacher retention and continuity of teaching in developing countries, such as the Philippines. This study explored the brain drain factors predicting the intention of public school teachers in Cebu, the Republic of the Philippines. a structured survey questionnaire was used to gather data on push and pull factors, and the intention to teach abroad; descriptive statistics, Pearson correlations, and multiple regression analyses were conducted. The results indicated a high intent to teach abroad and that most teachers agreed with actively considering overseas opportunities. Push and pull factors were both highly correlated with intention; however, regression indicated that only pull factors were significant (? = 0.371, p = 0.000), while push factors were not (? = 0.027, p = 0.638). The results imply that migration intentions are more influenced by expectations of opportunities abroad than by local dissatisfaction. This study adds to the literature by revealing a dominance of opportunity-driven motivators.

KEYWORDS:

Brain drain factors; intention to teach abroad; push-pull factors; Philippine basic education

Publication Title: Mathematics learners’ adoption of generative artificial intelligence: A structural equation modeling approach

Author/s: Lislee Valle

Title of Journal Publication: Social Sciences and Humanities Open

Date: June, 2026

Vol. No. & Issue No.: Vol. No. 13

ISSN/ISBN:

DOI/LINK: https://doi.org/10.1016/j.ssaho.2026.103053 

Indexed: SCOPUS

ABSTRACT:

21st-century learners, including in mathematics education, are increasingly utilizing Generative Artificial Intelligence (GenAI). This study examines how various factors influence students’ adoption of generative AI in mathematics. It focuses on components of the Unified Theory of Acceptance and Use of Technology (UTAUT) 3 model with external variables such as system accessibility, self-efficacy, knowledge of AI, and perceived privacy concerns. Data were collected from 960 respondents and analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The results revealed that among the main components of UTAUT 3 model, facilitating conditions, social influence, habit, and knowledge were the strongest ang most consistent predictors of students’ behavioral intention to use GenAI tools. In contrast, UTAUT constructs such as performance expectancy, effort expectancy, hedonic motivation, personal innovativeness, price value, and perceived privacy concerns did not directly affect behavioral intention. These findings present a shift in the primary drivers of AI adoption, from perceived usefulness and ease of use to factors rooted in familiarity, social influence, and routine engagement. System accessibility, however, significantly affects key constructs, particularly facilitating conditions, performance expectancy, effort expectancy, and social influence. Moreover, self-efficacy significantly affects hedonic motivation, habit, personal innovativeness, price value, and knowledge, implying their role in supporting AI use. The study emphasizes the importance of AI literacy programs, habitual engagement strategies, and socially supportive learning environments to encourage the meaningful integration of generative AI tools into mathematics education. 

Publication Title: Community-based cultural heritage preservation through the Purok system: a mixed-methods case study in a Philippine municipality

Author/s: Emily Costan

Title of Journal Publication: Frontiers in Sociology

Date: June 16, 2026

Vol. No. & Issue No.: Vol. No. 11

ISSN/ISBN:

DOI/LINK: doi.org/10.3389/fsoc.2026.1813600

Indexed: SCOPUS

ABSTRACT:

The preservation of cultural heritage is a universal concern that has to reach the local community to protect its history, identity, and pride. But despite various national and local heritage initiatives in the Philippines, limited research has examine the cultural heritage preservation of the Municipality of Liloan, Cebu. A survey of 264 members from six puroks was analyzed using linear regression models, and a focus group discussion with 20 purposively selected participants was conducted. The quantitative results show that awareness plays a more critical role than participation in influencing local government initiatives, indicating a positive relationship with the independent variables. This implies that higher awareness and greater participation are generally associated with more substantial government-led preservation efforts. Further, the participation in cultural activities has a positive, statistically significant effect on community initiatives; however, awareness of cultural heritage preservation shows a negative relationship, suggesting that awareness alone may not translate into active community preservation initiatives. The qualitative emphasizes themes of lived engagement, stewardship, and motivational pathways, demonstrating that preservation is reinforced through shared responsibilities, social interaction, collective identity, continuity, and community meaning rather than solely through knowledge. The findings also reveal that younger residents show lower levels of engagement, yet their digital skills offer opportunities for innovative documentation and promotion of heritage assets. These results indicate the potential of the Purok system as a community-based framework for strengthening participatory and sustainable cultural heritage preservation efforts.

Publication Title: Consumer perception and acceptability of sweet potato (Iponea batatas) cupcake enriched with butterfly pea (Clitoria ternatea) flower

Author/s: Jacquiline Dela Cruz

Title of Journal Publication:

Date: 2026

Vol. No. & Issue No.:

ISSN/ISBN:

DOI/LINK: https://doi.org/10.31018/jans.v18i2.7634

Indexed:

ABSTRACT:

The growing demand for functional and health-promoting foods has encouraged to development of nutrient-enhanced bakery products incorporating locally sourced ingredients. The present study formulated and evaluated sweet potato (Ipomoea batatas) cupcakes infused with butterfly pea (Clitoria ternatea) flower to assess sensory acceptability among expert and general consumers. Three formulations were prepared: F0 (0% sweet potato), F1 (50% sweet potato), F2 (25% sweet potato). A total of 101 respondents (33 experts; 68 general consumers) evaluated appearance, aroma, taste, and sweetness using a 9-point hedonic scale. Descriptive statistics and ANOVA with Tukey’s HSD test were applied to determine significant differences among formulations. Results showed that both sweet potato-based formulations (F1 and F2) received “like extremely” ratings across all sensory attributes, outperforming the control formulation. The appearance has a mean score of 8.47 (sd=0.76), from the expert and general consumers (x̄=8.28, sd=0.84), aroma, experts’ (x̄=8.41, sd=0.76) and non-experts’ (x̄=8.12, sd=0.92) for the taste, experts’ responses were (x̄=8.59, sd=0.66) and general consumers  (x̄=8.38, sd=0.81); products sweetness, the experts’  (x̄=8.46, sd=0.71) and the non-experts’  (x̄=8.11, sd=1.25), demonstrating optimal balance in flavor, aroma, and sweetness. ANOVA results indicated significant differences (p < 0.05) among formulations for all attributes. Findings confirm that sweet potato and butterfly pea flower can significantly enhance sensory quality while supporting the development of functional, locally sourced baked products. The strong acceptance of sweet potato-integrated cupcakes indicates promising market potential for healthier, culturally relevant snack alternatives.

Publication Title: New Diagnostic Framework for Transformer Health using IEEE C57.104 2019 with Gradient Boosting and PCA of DGA Data

Author/s: Apolinario Awit, Joseph Jay Brañanola, Maria Vina Presbitero, Edizar Sablas, Rannel Sinangote, John Kenneth Tabla, Jestoni Tan, Emerita Tan, Chona Dagatan

Title of Journal Publication:

Date: June 27, 2026

Vol. No. & Issue No.:

ISSN/ISBN:

DOI/LINK: https://doi.org/10.14445/22315381/IJETT-V74I6P118

Indexed:

ABSTRACT:

Transformers play an indispensable role in any power system. The health condition of these devices should be the top priority. Early fault detection of these devices is essential to have sustainable power flow. There are many routinary transformer tests like winding test, furan analysis, insulation resistance tests, but dissolved gas analysis stands to be one of the most critical tests among others. This is to the fact that the DGA test can evaluate the major condition of the transformer. Dissolved Gas Analysis (DGA) methods, while widely used, often struggle with accuracy and scalability under complex fault scenarios. This paper proposed a novel ML-based DGA framework that integrates the IEEE standard with Principal Component Analysis (PCA) and Gradient Boosting Machine (GBM) to enhance transformer fault diagnosis. PCA captures 95% of the variance with five principal components. The framework showed a test accuracy of 87.5% and a cross-validation accuracy of 86.05%, outperforming traditional methods such as the Duval Triangle (83.08%) and IEC Ratio Method (82.05%), as well as other machine learning models, including Random Forest (77%) and Support Vector Machines (37%). These findings demonstrate the effectiveness of the framework as a soft sensor in Transformer diagnostics.

KEYWORDS:

Dissolved Gas Analysis, Gradient Boosting Machine, Transformer Health, Principal Component Analysis

Publication Title: Exploring Second Life Potential of Retired EV Batteries: Data-Driven Criteria Development using Beta Variational Autoencoders and GMM Clustering

Author/s: Louie Jhyms Acidillo, Ralf Harold Cabanes, Joel Geralla, Kimjay Ihada, JV Mark Pasilaban, Gian Carlo Villahermosa, Jestoni Tan, Emerita Tan, Chona Dagatan, Donald Lalican

Title of Journal Publication: International Journal of Engineering Trends and Technology

Date: 2026

Vol. No. & Issue No.: 

ISSN/ISBN:

DOI/LINK: https://doi.org/10.14445/22315381/IJETT-V74I6P104

Indexed: 

ABSTRACT:

The increasing need for environmentally friendly ways to dispose of and reuse Electric Vehicle (EV) batteries shows how important it is to do a good end-of-life assessment. Second-life applications offer economic and environmental advantages; however, the classification of decommissioned batteries continues to pose difficulties. This research employs a data-driven methodology utilizing a ß-Variational Autoencoder (ß-VAE) in conjunction with Gaussian Mixture model (GMM) clustering to assess battery health classification. From the UNIBO Powertools Dataset, six engineered features were extracted: normalized Capacity, delta capacity (ΔSoH), capacity ratio, average voltage, temperature, and cycle count. We used ß-VAE to cluster the data by standardizing it and compressing it into a latent space. The silhouette score, Davies-Bouldin index, Calinski-Harabasz index, Bayesian Information Criterion (BIC), and Akaike Information Criterion (AIC) were all used to measure how well the clustering worked. The ß-VAE has an MAE of 0.3104 and an R² of 0.3384. GMM clustering found two good clusters (k = 2) with a silhouette score of 0.826 and a Davies-Bouldin index of 0.263. We turned the cluster-wise means into percentage thresholds to sort batteries into three groups: Healthy, Second-Life, and Disposal. For instance, Second-Life batteries has a voltage of at least 71.08 percent and a temperature of no more than 10.99 percent. The suggested ß-VAE-GMM framework is a strong and easy-to-understand way to figure out when a battery has reached the end of its life. Setting clear, data-driven criteria for second-life eligibility helps circular economy projects.

KEYWORDS:

Battery health assessment, Second-life batteries, B-Vae, Gaussian mixture model, Circular economy.

Publication Title: Social capital and educational justice as predictors of civic engagement in higher education: the mediating roles of institutional trust and student empowerment

Author/s: Marian Mae S. Sapanta, Romel C. Mutya

Title of Journal Publication: Frontiers in Sociology

Date: July 9, 2026

Vol. No. & Issue No.: Vol. No. 11

ISSN/ISBN: e-ISSN: 2297-7775

DOI/LINK: https://doi.org/10.3389/fsoc.2026.1869260

Indexed: SCOPUS

ABSTRACT:

Aligning with the Philippine Commission on Higher Education’s mission to produce socially responsible and civically active graduates, this study examined college students’ academic experiences in relation to social capital, educational justice, student empowerment, institutional trust, and civic engagement. A survey was conducted among 1,026 college students from selected state universities in Northern Cebu, Philippines. Descriptive and inferential statistics were employed to examine the relationships among the identified constructs. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to assess the direct and indirect mediating effects of student empowerment and institutional trust on civic engagement. The findings revealed acceptable levels of agreement across all constructs, with institutional trust obtaining the highest mean score (M = 4.16). Student empowerment demonstrated the strongest positive influence on civic engagement (ß = 0.477, t = 11.691, p < 0.001) and emerged as the most influential mediator, with indirect effects of ß =  0.199 and ß = 0.197. The results further indicated that social capital and educational justice exert significant indirect effects on civic engagement through the mediating roles of student empowerment and institutional trust. The findings suggest that fostering an inclusive, equitable, and supportive academic environment plays a vital role in strengthening civic attitudes, responsibility, and active citizenship among college students. The study recommends that higher education institutions sustain civic engagement by implementing practical, service-oriented student programs and community initiatives that promote student empowerment and institutional trust.

Publication Title: Exploring Queseo Festival in Compostela, Cebu, Philippines: a Socio-Cultural Analysis

Author/s: Marian Mae S. Sapanta

Title of Journal Publication: PERSPECTIVES ON SOCIETY – SELECTED READINGS IN SOCIAL SCIENCES

Date: 2026

Vol. No. & Issue No.: Vol. No.

ISSN/ISBN:

DOI/LINK: https://www.e-sentral.com/book/info/466856

Indexed:

ABSTRACT:

Publication Title: The Role of Student Engagement in Mediating the Relationship Between Interest and Mathematics Achievement

Author/s: Gerly A. Alcantara, Emma R. Sacan, Ayanna Trisha T. Vequiso, Julie Ann France A. Piscosb, Zyra Rose R. Zabateb, Joana Marie T. Leeb, Emerson D. Peteros

Title of Journal Publication: Malque Publishing

Date: 2026

Vol. No. & Issue No.:

ISSN/ISBN:

DOI/LINK:

Indexed:

ABSTRACT:

Student achievement in mathematics is a burning issue in the international educational system, especially in the Philippines secondary school system. This paper examined the multifactorial interaction of interest in mathematics and the mathematical performance of Grade 8 students, with the view of analyzing the mediation of the relationship between these two variables through student engagement in the chosen secondary schools in Talisay City, Cebu, Philippines. The main aim was to find out whether student engagement could be a good mechanism for enhancing psychological interest into a practical academic achievement. The research design was a descriptive-correlational type, whereby a sample of N =  443 students was utilized with the selection process of a systematic sampling procedure. The validated survey tools and academic records were then used to collect the data which were then analyzed using weighted mean, standard deviation, Pearson r correlation and multiple regression analysis to test the mediation effects. The research has shown that although the interest of students towards mathematics was moderate, the degree of engagement (behavioral, emotional, and cognitive) was at the mid-level score. Correlation analysis showed that there was a weak but statistically significant positive association between interest and achievement, engagement and achievement, as well as interest and engagement. More importantly, the mediation analysis proved that student engagement is a partial mediating variable between interest and mathematics achievement. This implies that although interest is a requisite, an initial step, its influence on final grades has been heavily mediated by the proactive involvement of the students and cognitive effort in the classroom. The findings of this research lead to the recommendation that school administrators and mathematics teachers should redirect their attention to more instructional interventions that emphasize multi-dimensional involvement. In this way, the educational leaders will be in a better position to close the gap between student interest and performance, so that the interest can be converted into academic achievement.

Publication Title: In the Shadow of Love and Death: An Existential Reading of the Decameron in the Time of the Black Death

Author/s: Rhodora G. Magan

Title of Journal Publication:

Date: 2026

Vol. No. & Issue No.:

ISSN/ISBN:

DOI/LINK: https://unis.bakircay.edu.tr/…/international…/lang=en

Indexed:

ABSTRACT:

Publication Title: Determining Pre-service Teachers’ Intention to Use Generative Artificial Intelligence through Expectancy-Value Theory

Author/s: Ronnel Victor B. Kilat, Lislee C. Valle, Jacquiline R. Dela Cruz, Joshlen B. Lim

Title of Journal Publication:

Date: 2026

Vol. No. & Issue No.:

ISSN/ISBN:

DOI/LINK: https://doi.org/10.1007/s44217-026-01963-3

Indexed: SCOPUS

ABSTRACT:

The rapid expansion of generative artificial intelligence (GenAI) has a significantly transformed digital learning environments in higher education. Despite the increasing use of AI-assisted tools among university students, limited empirical research has particularly within developing higher education contexts. This study investigates the factors influencing pre-service teachers’ behavioral intention to use generative AI by applying expectancy-value theory (EVT), focusing on attainment value, intrinsic value, utility value, and perceived cost. A quantitative research design was employed using an online survey administered to 380 pre-service teachers enrolled in a state university in Cebu, Philippines. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the relationships among EVT construct and behavioral intention. The study also explored whether sex moderates the relationship between perceived cost and behavioral intention. The findings indicate that attainment value and utility value significantly influence pre-service teachers’ intention to use generative AI tools, highlighting the importance of perceived usefulness and task relevance in shaping technology adoption. In contrast, intrinsic value and perceived cost did not demonstrate meaningful effects on behavioral intention. The moderating role of sex in the relationship between perceived cost and behavioral intention as likewise not supported. These results suggest that pre-service teachers’ intentions to engage with generative AI are primarily driven by perceived academic benefits rather than enjoyment or perceived barriers. The study contributes to the emerging literature on AI adoption in teacher education by providing an EVT-based explanation of motivational factors influencing GenAI use. The finding also offer practical implications for higher education institutions seeking to develop evidence-based policies, training programs, and pedagogical guidelines that support responsible and effective integration of generative AI in teacher preparation.

Publication Title: Development of a Smart Wearable Assistive device with Object Detection and Text-to Speech Functionality for Visually Impaired Individuals using Raspberry Pi

Author/s: Chona R. Dagatan, Jestoni P. Tan, Joy Stiffany A. Amodia, Lei Jo C. Bacu, Brett H. Callanga, Jeff Niño G. Caparoso, Avril Mae O. Malaga, Jedelou B. Pepito

Title of Journal Publication:

Date: August 29, 2026

Vol. No. & Issue No.: Vol. No. 8

ISSN/ISBN:

DOI/LINK: https://doi.org/10.14445/22315381/IJETT-V74I8P107

Indexed: SCOPUS

ABSTRACT: 

Visually impaired individuals struggle in terms of their mobility, awareness, and overall quality of life. Traditional aids, such as canes, offer only limited assistance. This capstone project aims to develop a smart  wearable device to enhance environmental awareness and assistance for visually impaired individuals in Danao City. The smart wearable assistive device is composed of a Raspberry Pi 4, ultrasonic sensors, a web camera, a text-to-speech technology that is used to deliver audio feedback that helps in better comprehension of information for these individuals. Experimental tests were conducted using percent error and paired t-tests to evaluate the overall performance of the wearable device. Survey questionnaires and interviews were also conducted to test the effectiveness of the device based on participants’ experiences. The quantitative results show that the smart wearable device consistently underperformed in its different functions. In distance range detection, the system has an average distance of 2.5 meters from the desired range, with a statistical analysis (t =  6.74, p < 0.05) indicating a significant difference. Object detection accuracy identifies an average of 9 out of 15 objects with a statistical analysis of 9t =  8.96, p < 0.001) and has an effect size of 2.31. The system shows an average of 1-2 missed words per trial and a statistical analysis of (t = -5.13, p < 0.001). Overall, the findings of this study confirm that the smart wearable device’s potential, specifically in text-to-speech systems, helps to enhance independence and confidence in common environments.

KEYWORDS:

Computer vision, Object detection, Text-to Speech, YOLO, Wearable device.

Publication Title: 

Author/s: Rose Mary L. Almacen, Ronnel Victor B. Kilat, Lislee C. Valle, Romel C. Mutya, Dawn Iris Calibo-Senit, Margarito B. Callao, Jennifer B. Carillo, Rowena P. Dato-on, Adrian P. Ybañez

Title of Journal Publication: Institute of Advanced Engineering and Science (IAES)

Date: October 2026

Vol. No. & Issue No.: Vol. No. 15, Issue No. 5

ISSN/ISBN: p-ISSN: 2252-8822, e-ISSN: 2620-5440

DOI/LINK: http://doi.org/10.11591/ijere.v15i5.40084

Indexed: SCOPUS

ABSTRACT: 

Multiplication fluently remains a persistent challenge for many Filipino learners, yet community-based evidence on low-cost supplementary interventions is limited. This study examined whether a six-week Trachtenberg speed math intervention was associated with improved multiplication performance among learners aged 8 to 13 years in three local communities in Danao City, Philippines. The study used a one-group pretest-posttest quasi-experimental pilot design conducted during a community-based numeracy intervention. Paired scores from 135 participants were analyzed using paired-samples t-tests, mean gains, 95% confidence intervals (95% CI), and within-subject effect sizes (dz). Scores increased significantly in Maslog from 27.31 to 49.82, in Sabang from 32.68 to 49.84, and in Taytay from 31.91 to 48.78 (all p<0.001). For the overall sample, scores improved from M=30.63 (SD= 16.54) to M= 49.47 (SD= 18.91), with a mean gain of 18.84 points (95% CI [ 16.61, 21.07]), t(134)= 16.72, p< 0.001, dz= 1.44. The findings suggest that Trachtenberg speed math may serve as a promising supplementary multiplication support in remedial and community settings. However, the absence of a comparison group and incomplete instrument validation require cautious, non-casual interpretation.

KEYWORDS:

Community extension; Multiplication fluency; Quasi-experimental pilot; Supplementary numerical support; Trachtenberg speed math