Author: irjstem_f1

Predicting Product Placement Marketing through Screen, Script, and Plot Placement Attributes

irjstem_f1 Abstract , , ,

Predicting Product Placement Marketing through Screen, Script, and Plot Placement Attributes
Corresponding email: [email protected]

A B S T R A C T

This study develops a model to predict product placement marketing effectiveness by examining three placement attributes: screen placement, script placement, and plot placement. The objective is to clarify how these attributes are associated with product placement marketing effectiveness and to provide a quantitative basis for product placement strategy and content creation. Drawing on the three-dimensional classification of product placement, the study represents the three attributes as screen, script, and plot placement and measures their relationships through the distance among the attributes. A probability density function is constructed to characterize the relationship between the distance-based placement attributes and marketing effectiveness. Empirical data were collected from a fashion brand’s product placement campaign involving 21 YouTube videos and 15 podcast episodes, covering cosmetics, apparel, and handbags. The effectiveness of product placement was assessed through audience responses concerning satisfaction, interest, and entertainment value. A total of 2,658 valid observations were obtained. Of these, 1,063 observations were randomly selected for parameter estimation using maximum likelihood estimation, while the remaining 1,595 observations were used for model calibration. The calibrated model produced a Theil U statistic of 0.3354, indicating acceptable goodness of fit. The findings suggest a positive, concave relationship between product placement marketing effectiveness and the distance-based characteristics of the three placement attributes. The study concludes that balancing and aligning screen, script, and plot placement can improve product placement strategy. Marketing managers and content creators are therefore recommended to coordinate these three attributes when designing placement campaigns and developing branded content.

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Bayesian Models in Biostatistics

irjstem_f1 Abstract , , , ,

Bayesian Models in Biostatistics
Corresponding email: [email protected]

A B S T R A C T

Bayesian models constitute a fundamental theoretical and methodological framework in biostatistics, offering a coherent probabilistic approach for statistical inference under uncertainty. Grounded in probability theory and Bayes’ theorem, Bayesian methods systematically update prior knowledge with observed data and represent uncertainty through posterior distributions. This paper presents a comprehensive theoretical and methodological overview of Bayesian models in biostatistics, with emphasis on their mathematical foundations, inferential principles, and practical applicability in biomedical research. Key concepts discussed include the axiomatic basis of probability, prior and posterior distributions, likelihood functions, credibility intervals, conjugate Bayesian models, and Bayesian parameter estimation. The study further examines the role of numerical methods, particularly Monte Carlo and Markov Chain Monte Carlo (MCMC) algorithms, in approximating posterior distributions when analytical solutions are unavailable. Illustrative examples, including the Poisson-Gamma conjugate model and MCMC-based inference, are used to demonstrate the practical implementation of Bayesian reasoning in biostatistical contexts. The paper highlights the advantages of Bayesian models in handling complex data structures, small sample sizes, uncertainty, and the integration of prior information, while also discussing key methodological challenges such as prior specification and computational demands. In all, the study underscores the relevance and robustness of Bayesian models as a powerful framework for contemporary biostatistical analysis and biomedical decision-making.

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Artificial Intelligence in Physics Education: A Critical Integrative Review

irjstem_f1 Abstract , , , ,

Artificial Intelligence in Physics Education: A Critical Integrative Review
Corresponding email: [email protected]

A B S T R A C T

Artificial intelligence (AI) is now used in physics education for tutoring, feedback, assessment, problem-solving, laboratory analysis, and teacher support, yet the literature often treats model capability, user satisfaction, and learning as equivalent. This review examines why similar technologies can lead to different educational consequences. A critical integrative design synthesized literature published from January 2018 to April 2026, while retaining earlier methodological sources where necessary. Physics-specific studies were prioritised, and science or STEM research was included only when it clarified mechanisms directly relevant to physics. A retrospective PRISMA-style audit identified 48 papers at the initial selection stage, of which 23 were included in the substantive critical synthesis. Six recurring functions were identified, but none were beneficial by definition. Positive effects were most credible when AI supported intermediate reasoning, operated within bounded tasks, drew on domain-relevant grounding, and remained subject to human verification. Evidence for affective and efficiency gains was more consistent than evidence for durable conceptual learning. The literature also revealed category errors in treating accurate answers as learning, conversational responsiveness as personalization, and fluent language as representational competence. Graphical, spatial, and multimodal tasks were especially vulnerable to reliability mismatch. The review proposes the Pedagogical Contingency Framework for AI in Physics Education, which explains outcomes through the interaction of pedagogical role, epistemic position, representational demand, and governance or grounding. Its central contribution is a move away from tool cataloguing towards an explanatory account of when AI augments disciplinary agency and when it substitutes for it.

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Students’ Achievement in Similar Triangles Using Game-Based Formative Assessment: A Quasi-Experimental Study

irjstem_f1 Abstract , , , , ,

Students’ Achievement in Similar Triangles Using Game-Based Formative Assessment: A Quasi-Experimental Study
Corresponding email: [email protected]

A B S T R A C T

This study compared Grade 9 students’ achievement in geometric proportion and triangle similarity following formative assessment through Quizizz, Gimkit, or Google Forms. A pre-test–post-test comparison involved two intact classes at a private school in Angeles City, Philippines, during School Year 2021–2022. Classes were randomly assigned to either the experimental or control group. A total of 58 students completed both assessments, with 27 in the experimental group and 31 in the control group. The intervention lasted two weeks and included four formative assessment sessions. Both groups received equivalent lesson content, teacher instruction, and assessment questions and followed the same schedules. Achievement was measured using researcher-developed 50-item multiple-choice assessments aligned with a table of specifications and reviewed by mathematics teachers. Independent- and paired-samples t-tests showed similar pre-test scores and significant improvements in both groups, with medium effect sizes. The experimental group had a higher post-test average and greater improvement, but the post-test difference between groups was not significant and had a small effect size. These findings indicate improvement under both assessment conditions without establishing an additional achievement benefit from game-based platforms. The short intervention and inclusion of only one class per condition limit interpretation and generalizability. Mathematics teachers should select assessment platforms according to instructional objectives, learner access, and classroom conditions, while prioritizing aligned questions, informative feedback, and teacher facilitation to support students’ mathematical learning.

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Technological Knowledge and TPACK of SHS Biology Teachers in Ghana

irjstem_f1 Abstract , , , , , ,

Technological Knowledge and TPACK of SHS Biology Teachers in Ghana
Corresponding email: [email protected]

A B S T R A C T

The study aimed to examine the technological knowledge (TK) and technological pedagogical content knowledge (TPACK) of senior high school (SHS) biology teachers in some municipalities in the Greater Accra Region, Ghana. Methods: Guided by two research objectives, the study employed an explanatory sequential mixed-methods design. The quantitative data in this study were obtained from 73 senior high school biology teachers in 31 senior high schools using a validated structured questionnaire, which was adapted from the Items for TPACK Survey (ITS). Data were collected using qualitative methods such as classroom observations and semi-structured interviews with two teachers who were purposively selected. Results: Teachers’ self-reported technological knowledge was moderate (M = 4.25; SD = 0.77), while the availability of modern digital tools was limited, with 63% of the teachers stating that there was no access to ICT in their schools. The results showed that students’ self-reported TPACK was found to be positive (M = 4.22, SD = 0.76); however, classroom observation data indicated that students rarely used technology in their biology lessons, and the use of technology was consistently low. The results of an independent-samples t-test revealed that there was no significant difference in TPACK between the two groups of teachers, professionally qualified and non professionally qualified (t = −1.20; df = 71; p = 0.24; Cohen’s d = 0.19). Implications: The results reveal a serious discrepancy between the perceived and real technological competency, which is partly due to the lack of ICT infrastructure and systemic deficiencies in pre-service and in-service teacher training. Policy issues related to the provision of ICTs, pre-service training of teachers, and in-service training of teachers are discussed.

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Awareness, Knowledge, and Attitude of Teachers towards Specific Learning Difficulties

irjstem_f1 Abstract , , , , ,

Awareness, Knowledge, and Attitude of Teachers towards Specific Learning Difficulties
Corresponding email: [email protected]

A B S T R A C T

Millions of students globally experience Specific Learning Difficulties (SLDs) such as dyslexia, dyscalculia, and dysgraphia, which represent significant educational challenges. The role of teachers is fundamental in identifying and providing assistance to students experiencing learning difficulties. The study examined the level of awareness and knowledge of secondary school teachers regarding SLDs and explored whether sex, educational qualification, and years of teaching experience influence their attitudes toward these students. With five hypotheses guiding the study, the study employed a descriptive survey design with 125 teachers who were randomly selected using a stratified sampling technique. A structured questionnaire, which assessed awareness, knowledge, and attitudes regarding dyslexia, dyscalculia, and dysgraphia, was used to obtain data. Validity was ensured using expert judgement and empirical evidence from factor analysis. Cronbach’s alpha was used to obtain reliability coefficients of .973,.950, and .849 for the three sections of the scale, respectively, while a coefficient of .975 was obtained for the scale as a whole. Data were analyzed using mean, standard deviation, t-test, and one-way ANOVA. The research reveals that there were statistically significant differences in teachers’ levels of awareness and knowledge of SLDs. However, sex, educational qualification, and years of teaching experience did not significantly influence teachers’ attitudes toward students with SLDs. The findings highlight the need for continued professional development to strengthen teachers’ understanding of learning difficulties and enhance the support provided to students in secondary schools.

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Agronomic and Yield Assessment of High-Yielding Sugarcane Varieties (Phil 99-1793 and Phil 2004-1011) in Response to Integrated Nutrient Management

irjstem_f1 Abstract , , , , ,

Agronomic and Yield Assessment of High-Yielding Sugarcane Varieties (Phil 99-1793 and Phil 2004-1011) in Response to Integrated Nutrient Management
Corresponding email: [email protected]

A B S T R A C T

Sugarcane farming plays a vital role in rural livelihoods, agro-industrial development, and national economic growth. Evaluation of two high-yielding sugarcane varieties: Phil 99-1793 and Phil 2004-1011 under different nutrient management strategies: full recommended inorganic fertilizer (70-140-260 kg NPK ha⁻¹), mud press at 10 t ha⁻¹, and an integrated nutrient management (INM) approach consisting of 50% recommended inorganic fertilizer (35-70 130 kg NPK ha⁻¹) combined with 5 t ha⁻¹ mud press. The experiment was arranged in a Factorial Randomized Complete Block Design with three replications in Kabankalan City, Negros Occidental, Philippines, from June 2021 to April 2022. Standard cultural management practices were employed. Agronomic and juice quality parameters were analysed at the 5% threshold level. Nutrient treatments did not differ significantly in stalk diameter, number of nodes, or number of internodes. Phil 2004-1011 outperformed Phil 99-1793 in plant height (149.89 cm), stalk length (198.84 cm), plot weight (111.44 kg), cane yield (30.89 t ha⁻¹), sucrose yield (2.06 LKg TC⁻¹), and sugar yield (1.63 LKg ha⁻¹), demonstrating superior genetic potential. Full inorganic fertilizer (IF) positively increased tiller count, Brix, sucrose yield, and sugar yield. INM application enhanced the number of millable canes and produced comparable cane yield (30 t ha⁻¹), indicating potential as a cost-efficient and sustainable alternative. Combination of high-performing varieties with optimized nutrient management strategies can improve productivity, resource-use efficiency, and sustainable sugarcane production. Findings recommended exploring root architecture, physiological responses to stress conditions, nutrient dynamics, soil microbial interactions, and molecular characterization under diverse environmental conditions.

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Volume 6 | No. 3 | September 2026 Issue

irjstem_f1 Issue

September 2026

Agronomic and Yield Assessment of High-Yielding Sugarcane Varieties (Phil 99-1793 and Phil 2004-1011) in Response to Integrated Nutrient Management
Edreson G. Torteo, Angelie Rose L. Lumba
Regional Plant Genetic Resources and Conservation Management Laboratory
Integrated Laboratory Division, Department of Agriculture – Negros Island Region
Graduate School, University of the Philippines Los Baños, Laguna, Philippines
Faculty, Central Philippine State University, Kabankalan City, Negros Occidental
Office of the Research and Development Services, Central Philippines State University

Full Paper PDF Abstract 1-10

Awareness, Knowledge, and Attitude of Teachers towards Specific Learning Difficulties
Stella Eteng-Uket, Vincent Chukwubuike Ekezigbo, Christiana Ijeoma Jumbo-Egwurugwu
University of Port Harcourt, Nigeria
Full Paper PDF Abstract 11-24

Technological Knowledge and TPACK of SHS Biology Teachers in Ghana
Philip Ebo
University of Education Winneba, Ghana
Full Paper PDF Abstract 25-36

Students’ Achievement in Similar Triangles Using Game-Based Formative Assessment: A Quasi-Experimental Study
Francis Joko E. Guira, Alaisah A. Cayanan, Crizalyn F. Silos, Daisy O. Muyano
Republic Central Colleges, Angeles City, Philippines
Full Paper PDF Abstract 37-44

Artificial Intelligence in Physics Education: A Critical Integrative Review
Joshua O. Okewale, Ibukunoluwa R. Omole, Abiola O. Ilori, Rachel I. Obed, N. Chetty
Department of Physics, University of Ibadan, Ibadan, Oyo State, Nigeria
School of Chemistry & Physics, University of KwaZulu-Natal, Pietermaritzburg, South Africa
Full Paper PDF Abstract 45-60

Bayesian Models in Biostatistics
Senad Orhani, Sadri Alija, Bright Asare
Faculty of Education, University of Prishtina, Prishtina, Kosovo
Faculty of Business and Economics, South East European University, Tetovo, North Macedonia
Department of Mathematics Education, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana
Full Paper PDF Abstract 61-71

Predicting Product Placement Marketing through Screen, Script, and Plot Placement Attributes
Hui-Hsin Huang
Department of Advertising &Public Relations / Fu Jen Catholic University, Taiwan
Full Paper PDF Abstract 72-78

Academic Setbacks and Contributing Factors Among Computing Students in Philippine Higher Education

irjstem_f1 Abstract , , , , ,

Academic Setbacks and Contributing Factors Among Computing Students in
Philippine Higher Education
email: [email protected]

A B S T R A C T

Academic setbacks such as incomplete (INC) grades and course failures remain persistent challenges to student retention in information technology programs in Philippine state universities. It is critical to distinguish between these two academic statuses: an INC grade signifies that a student has completed substantial coursework but has unfinished requirements due to valid, often extenuating, circumstances, whereas a failing grade denotes that the student did not meet the minimum academic standards for the course (Romero & Ventura, 2020). Adopting a proactive, preventive approach, this study analyzed contributing factors, support system utilization, and emotional impacts among 101 computing students at a state university in the Philippines using a validated structured survey. Quantitative techniques such as descriptive statistics, Spearman correlation, one-way ANOVA, chi-square, and multiple linear regression were applied. Financial difficulties (M=3.22), heavy course load (M=3.14), and time management issues (M=3.10) were the top-rated contributors. A regression model explained 37% of stress variance (R²=0.370; F(15,72)=2.82, p=.002), with lack of resources (β=0.433), work commitments (β=0.320), and subject difficulty (β=0.303) as significant predictors. Second-year students showed significantly higher resource and connectivity barriers across all ANOVA factors (p<.05, η²=0.07–0.12). Findings support the development of data-driven early warning systems and proactive academic advising frameworks within computing programs.

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Understanding Educational Inequalities in Rural Tanzania: A Qualitative Study of Infrastructural, Socioeconomic, and Geographical Challenges

irjstem_f1 Abstract , , , , ,

Understanding Educational Inequalities in Rural Tanzania: A Qualitative Study of Infrastructural, Socioeconomic, and Geographical Challenges 
email:  [email protected]

A B S T R A C T

Many rural schools in Tanzania still struggle with socioeconomic and infrastructure issues that lower educational standards. In this study, we examined the interrelated causes of educational inequalities in rural schools. We employed a qualitative research approach and a multiple-case study design. We collected data using semi-structured interviews and observations. We analysed data using a thematic approach to identify key challenges influencing educational inequalities in Tanzania’s rural schools. We found that some rural schools struggled with overcrowded or poorly maintained classrooms, leaking roofs, damaged floors, and insufficient desks and sanitation facilities. Many students also came from low-income households, which limited their ability to obtain basic educational materials such as textbooks, exercise books, uniforms, and transport. Geographical barriers, such as long distances between homes and schools and scattered settlements, further hindered regular attendance. Therefore, schools in rural areas operated with inadequate school physical infrastructure, limited family socioeconomic conditions, and limited geographic accessibility. These factors contributed much to the educational inequalities in rural schools. It remained important to address these challenges for equitable access to quality education and to reduce educational inequalities in rural Tanzania. Therefore, it is recommended that education authorities should improve school infrastructure by promoting secure and comfortable learning environments, strengthen support for disadvantaged students by strengthening programmes that aid vulnerable households, strengthen community and parental involvement, enhance school accessibility by reducing travel distance from home to school and home, and strengthen transportation systems by investing in school infrastructure, including roads and transportation networks, as well as in the strategic placement of school.

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