The Don Honorio Ventura State University (commonly referred to as DHVSU) is a state university in Bacolor, Pampanga, Philippines. It has six satellite campuses in Apalit, Candaba, Porac, Mexico, Santo Tomas and Lubao in the province of Pampanga. It is considered as the oldest vocational school in Far East Asia.
Understanding the psychological drivers of student engagement is essential in advancing educational outcomes, particularly in Physical Education in the higher education. This study explored the interconnection between curiosity and study engagement among students enrolled in PE and related disciplines across various Philippine universities. Adopting a quantitative research design, responses were gathered from 1,273 students using validated instruments that assessed two dimensions of curiosity (stretching and embracing) and three components of study engagement (vigor, dedication, and absorption). Statistical analysis using Spearman's rho revealed a significant and positive relationship between curiosity and engagement, indicating that students who exhibit greater curiosity also demonstrate higher levels of academic engagement. Notably, both dimensions of curiosity were strongly correlated with all facets of engagement. These findings highlight the reciprocal nature of curiosity and engagement, suggesting that when learners are encouraged to explore, question, and embrace new experiences, they become more energized, committed, and immersed in their academic tasks. This underscores the potential of curiosity as a catalyst for enhancing motivation and persistence in PE learning environments. The results emphasize the need for educators to create pedagogical approaches that nurture curiosity and support meaningful engagement. Additionally, the study contributes to the broader discourse on student-centered learning by positioning curiosity not merely as a trait but as a powerful enabler of sustained academic involvement. Future investigations may benefit from exploring these relationships over time or in varying educational contexts to further illuminate the mechanisms underlying student engagement in PE.
This study aimed to assess students' readiness for online learning, academic motivation, academic buoyancy, academic performance, and these constructs’ direct, indirect, and mediation effects. It employed multivariate statistical analysis using structural equation modeling, specifically confirmatory factor analysis and path analysis. It utilized the descriptive method to assess the respondents’ profile, levels of online learning readiness, academic motivation, academic buoyancy, and academic performance during the 2021–2022 school year. Data were gathered by administering adapted Likert scales: Online Learning Readiness Scale, Academic Motivation Scale, and Academic Buoyancy Scale. Furthermore, the fit, construct reliability, convergent, and discriminant validities of the measurement models were assessed using confirmatory factor analysis. Results revealed that the respondents have high levels across all sub-constructs of online learning readiness, academic motivation, and academic buoyancy. Moreover, path analysis established a significant direct effect of OLR of students on academic buoyancy and motivation and a significant indirect effect on academic motivation and academic performance via the mediating variable of academic buoyancy. The significant mediating effect of academic buoyancy puts forward issues on students’ capability to overcome difficulties and challenges that affect their academic performance. Hence, a campus-based program is strategically proposed to enhance students’ confidence, control, commitment, and communication.
This study aims to uncover the perceptions of offshore accountants concerning their job satisfaction and career development, as well as the kinds of career management strategies that promote the welfare of the accountants and their employers. The researchers utilized qualitative research design using a phenomenological approach and made use of Maslow’s Hierarchy of Needs Theory and Albert Bandura’s Social Cognitive Theory (SCT) as their guides. Purposive sampling was used in the selection of participants. To gather data, researchers mobilized a researcher-made questionnaire as a data collection tool. The collected data was then analyzed with the use of thematic analysis. The results suggest that to influence job satisfaction, career growth, a healthy working environment, a competitive salary, and work-life balance need to be satiated. As for career development, a good attitude towards growth, adequate training provided by the firms, and a positive relationship with clients, colleagues, and superiors. Lastly, Australian taxation training, job rotation, soft skill enhancement, and mentoring were suggested to be implemented within the organization as these strategies appeared appropriate for the welfare of both parties. This paper also offers a framework, namely the “GLAMED Job Career Fulfillment Framework,” which helps to expedite the process of identification and fulfillment of the needs and wants of offshore accountants.
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.
With the increased role of local authorities in creating policies, gathering information on how successful and sustainable local heritage conservation policies are established will be valuable in crafting future policies. Local government heritage conservation policies were investigated in the City of San Fernando, Pampanga, Philippines, to determine predictors of community support for heritage conservation policy - why communities support the policies and what community characteristics lead towards support for them. Data was collected from stakeholders through a self-administered online survey and analyzed using Structural Equation Modeling (SEM). The data suggested that for San Fernando, (1) knowledge and awareness, (2) sense of belonging and attachment, (3) place image and community identity, and (4) evaluation of value are predictors of support for heritage conservation policies, with evaluation of value as a mediator for the first three. These were incorporated into a model for predictors of community support for local heritage conservation policy.
