This study delves into the attitudes of educators toward online teaching, their technological proficiency, and access to technology, with a particular emphasis on examining potential gender distinctions. Employing a quantitative-descriptive-correlational research design, this research meticulously examines the intricate relationships among these variables. The primary objectives of this investigation involve scrutinizing teachers' attitudes toward online instruction, evaluating their technological competency, and gauging their accessibility to technology. The results reveal that, by and large, teachers exhibit a moderately favorable disposition toward online teaching, signifying their eagerness to embrace this pedagogical approach. Furthermore, these educators demonstrate a commendable level of technological competence, showcasing their adeptness in harnessing technology for instructional purposes. In the context of technological accessibility, most teachers report encountering minimal impediments; however, science teachers disclose relatively restricted access. A gender-based analysis of the data suggested a notable absence of significant disparities in attitudes, technological proficiency, and access between male and female educators. This finding substantiates the assertion that gender exerts a negligible influence on shaping teachers' perspectives regarding online teaching and their technological adeptness. Moreover, this research revealed a substantial positive correlation between teachers' attitudes toward online teaching and their technological competence, as well as their access to technology. This implies that educators endowed with enhanced technological proficiency and enhanced access are more likely to harbor favorable attitudes toward online teaching. The implications of these findings underscore the paramount significance of supporting teachers in augmenting their technological competence while simultaneously ensuring equitable access to technology resources. These two factors emerge as pivotal catalysts for facilitating the seamless integration of online teaching into contemporary education. In the era of the COVID-19 pandemic, where online instruction has become indispensable, the imperative for ongoing professional development and support has become unmistakably evident. This study calls for a sustained commitment to nurturing and further enhancing teachers' affirmative attitudes toward online teaching to effectively navigate the ever-evolving landscape of education.

Gender and age are critical factors in understanding attitudes toward artificial intelligence (AI) in education, yet limited research has directly explored their influence on teacher aspirants’ perspectives on AI integration. This study employed random sampling to select 603 respondents from two state-managed institutions. Findings indicate that prospective teachers generally hold neutral attitudes toward AI (M=2.84), reflecting uncertainty about preferring AI over human interaction in routine tasks, consistent with prior research. Male respondents (M=2.91) exhibited significantly more positive attitudes toward AI in education than females, as evidenced by a t value of -2.66 and a p value of 0.008. Additionally, adults (M=2.86) demonstrated significantly higher attitude scores than adolescents (M=2.80), with a t value of -2.05 and a p value of 0.040. These results highlight the role of demographic variables in shaping perceptions of AI in educational contexts, emphasizing the need for targeted interventions to address concerns and optimize AI adoption in teacher training programs.

This study investigated the extent of prospective teachers’ acceptance, attitudes, and perceived effectiveness of artificial intelligence (AI) in education. It also examined whether these perceptions varied according to gender and age group. Using a descriptive-correlational design, data were gathered from 392 teacher education students enrolled in a state-managed university in southwestern Mindanao. The results revealed that the respondents generally demonstrated moderate acceptance, favorable attitudes, and positive perceptions of AI effectiveness in the teaching and learning process. While no statistically significant differences were found between genders, moderate effect sizes suggested subtle variations worth further exploration. Significant differences were observed across age groups, with older individuals reporting higher levels of AI acceptance. Strong and significant correlations among acceptance, attitude, and perceived effectiveness affirmed the interconnected nature of belief, emotion, and evaluation in shaping readiness for AI integration. These findings support the Technology Acceptance Model and the Theory of Planned Behavior. In light of these results, it is recommended that teacher education programs integrate AI literacy and practical training, with targeted support for younger students to enhance digital confidence and preparedness.

This study explores the role of artificial intelligence (AI) in teacher education, focusing on preservice teachers’ preparedness for AI integration. It examined the levels of AI literacy, readiness-confidence, and acceptance among preservice teachers in Philippine higher education institutions, and investigated differences across gender, academic discipline, and internet connectivity. Using a cross-sectional survey design, data were collected from 384 preservice teachers through validated instruments that measured AI literacy, readiness-confidence, and acceptance. Analyses included descriptive statistics, independent samples t-tests, and correlation analysis. Findings revealed high readiness-confidence and moderate to high literacy and acceptance levels. Significant differences emerged, with male preservice teachers, STEM students, and those with reliable internet access reporting higher scores, particularly in readiness-confidence. Strong positive correlations among literacy, readiness-confidence, and acceptance underscored their interdependent relationship in shaping preparedness for AI integration. These results emphasize the need for tailored and inclusive AI education and training programs that address demographic and infrastructural disparities. Beyond equipping preservice teachers with skills, preparing them for AI adoption is about shaping the future of education by ensuring that tomorrow’s classrooms are led by educators who are competent, confident, and capable of driving innovation, equity, and progress in a rapidly evolving digital age.

University extension programs have become an important strategy for promoting inclusive livelihood development and employment generation among disadvantaged communities. However, empirical evidence on whether these interventions translate into measurable livelihood and employment outcomes remains limited. This study assessed the impact of the Multi-Phase Community Enterprise Development Program of Jose Rizal Memorial State University (JRMSU) on the livelihood and employment outcomes of community beneficiaries in Barangay Sta. Catalina, Libertad, Zamboanga del Norte. A with-or-without impact evaluation design was employed involving 60 respondents, comprising 30 program beneficiaries and 30 comparable nonbeneficiaries selected from the same community. Descriptive statistics, chi-square tests, Mann-Whitney U tests, and binary logistic regression were used to compare livelihood and employment outcomes and to estimate the association between program participation and selected outcome indicators while controlling for respondents' socioeconomic characteristics. The findings revealed that beneficiaries exhibited significantly higher levels of livelihood establishment, participation in service-related enterprises, certification attainment, enterprise membership, and knowledge sharing compared with non-beneficiaries. Beneficiaries also reported higher livelihood-related income and greater engagement in community-based enterprise activities. However, regression analysis indicated that program participation was not a statistically significant predictor of employment status or livelihood establishment after controlling for observable characteristics. Instead, access to capital emerged as the most influential determinant of employment, while larger household size reduced the likelihood of employment. These findings suggest that although the program substantially enhanced beneficiaries' livelihood capabilities and enterprise participation, sustainable livelihood and employment outcomes depend not only on capacity-building interventions but also on access to productive resources and complementary institutional support.