Jupeth Pentang

Alternative livelihood programs have been promoted to reduce fishing pressure and improve coastal community resilience. In Palawan, Philippines, fisherfolk from Dumaran and Araceli participated in training programs supported by WPU-ATBI and PBCAI, covering aquaculture, processing, and enterprise management. This study assessed training outcomes using a survey adapted from USAID and analyzed responses with descriptive and inferential statistics. Results showed that men and lower-income households (≤ ₱10,000) perceived training as more effective, while no significant differences were observed by household size, education, or policy participation. Women represented a majority (53.70%), reflecting their cultural assignment to post-harvest and marketing roles, as well as their growing participation in fisheries value chains. Program outcomes revealed mixed results: 63.89% of participants continued their projects, yet nearly half of initiatives faced discontinuation due to financial and management challenges. Aquaculture and processing were the most frequently adopted livelihoods, showing alignment with local skills and resources. Financial literacy and business management training helped some participants sustain enterprises, but limited time, market access, and contextual gaps constrained broader success. Income improvements were reported by 70.67% of households, though gains in housing and education were modest. The findings underscore that one-time training is insufficient; sustained support, access to finance, and stronger market linkages are crucial. Tailoring training to local contexts, fostering collective organization, and building long-term support systems can enhance the sustainability of alternative livelihoods. By addressing financial and operational barriers while leveraging women’s active roles, livelihood programs can strengthen both household resilience and resource sustainability in coastal communities.

Action research serves a pivotal purpose in enhancing educational practices as well as the achievement of students, as teachers can now take a more proactive role in the process. Success in action research initiatives depends on the self-efficacy of teacher researchers, their capability to handle their research roles, and the challenges they experience in initiating action research. This study looked into the research self-efficacy, productivity, and the issues the teachers face in conducting action research in one school district in the Philippines. Data were collected through interviews with eight teacher-researchers. Findings show the tendency of less self-efficacy in the teachers’ research activities caused by inadequate research time due to their demands for teaching and poor self-confidence in engaging in research. Teachers experienced work overload, compounding the problem of observing time for research activities. They also lack sufficient funding for action research and institutional support from schools to help facilitate it. To address such challenges and warrant the participation of the teachers in research, there is a need for improved work schedules and a boost in institutional support for capacitating teachers.

Proficiency in solving mathematical problems is essential for preservice elementary teachers, as they will teach foundational math concepts and foster problem-solving abilities among young learners. However, many studies found low problem-solving performance among preservice teachers. In line with this, the present study examined how problem-solving disposition relates to the performance of preservice elementary teachers, conducted at a selected higher education institution in Nueva Ecija, Philippines, with 134 participants. The study utilized a mathematical problem-solving disposition and beliefs scale questionnaire and a problem-solving test scored using the identify, define, explore, act, and look (IDEAL) model. Results indicated an average problem-solving disposition and high problem-solving performance among preservice teachers. Linear regression analysis showed that overall problem-solving disposition is a predictor of performance. Further, stepwise regression analysis revealed that two disposition parameters, mathematical mindset (β = 2.413, p < 0.01) and community of practice (β = 1.866, p < 0.01), significantly predicted problem-solving performance. These findings show the significance of developing a problem-solving disposition, mindset, and learning communities to improve future teachers’ problem-solving ability by providing more learning opportunities, interdisciplinary problems, and social engagements.

Faculty members’ beliefs in their ability to conduct research and publish research outputs are expected to impact research productivity directly. Thus, the study described the research self-efficacy and productivity among faculty members, their research self-efficacy influence on productivity, and their challenges in research writing and publication. The study utilized a mixed-method sequential explanatory research design, with 36 and nine faculty member-participants for the quantitative and qualitative study. For the quantitative study, the faculty members’ research self-efficacy was ascertained using a validated questionnaire, and their research productivity was determined through a researcher-made survey instrument. Meanwhile, the qualitative study focused on the faculty members’ research writing and publication challenges, which were gathered through focus group discussions. Results showed average research self-efficacy and low research productivity among faculty members. Research self-efficacy significantly predicted research productivity regarding refereed and indexed publications, paper presentations, and bibliometrics. Further, themed findings showed that the faculty members encountered challenges such as a lack of research exposure, time constraints, lack of institutional support, and publication pressure. The study may serve as an inference for higher education institutions in designing faculty development plans and in-service training programs to capacitate its members.

In the Philippines, improving pre-service math teachers’ critical thinking is receiving increasing attention, emphasizing the importance of tailoring instructional methods to students’ learning approaches for a more equitable environment and enhanced mathematics performance. Thus, this study aimed to determine if the critical thinking disposition subscales (reflective, attentiveness, open-mindedness, organization, perseverance, and intrinsic motivation) and learning approach (deep approach and surface approach) predict the mathematics performance of pre-service math teachers. This study employed a descriptive-correlational research design to randomly selected 125 pre-service math teachers from Central Luzon, Philippines. The survey instruments are administered through the student-educator negotiated CTDs scale, the revised two-factor study process questionnaire, and the 40-item validated test. Using descriptive analysis, findings revealed that preservice mathematics teachers have moderate levels of CTD, most of which use a deep approach and have average mathematics performance. Regression analysis showed that CTD and the deep approach were predictors. Therefore, pre-service mathematics teachers with a higher CTD and a deep approach are likelier to perform better in mathematics. These findings provide valuable insights into enhancing mathematics teacher education.

The reading abilities of Filipino students have been a challenge for educators and policymakers alike. Despite government efforts to improve literacy rates in the Philippines, recent studies have shown that many students need help with reading comprehension, vocabulary development, and critical thinking skills. This research note examines the current state of reading abilities among Filipino students and potential areas for improvement. The poor reading abilities can be attributed to several factors, including a lack of resources and socioeconomic factors. However, there are identified potential areas for improvement, such as promoting early literacy programs, investing in teacher training, and developing reading materials that are culturally relevant and engaging for Filipino students. These findings have important implications for education policies and practices in the Philippines and for educators and researchers seeking to improve reading abilities among Filipino students.

Mathematical modeling offers a promising approach to improving mathematics education. This study aims to determine if the concept of metacognitive awareness in the learning process is associated with mathematical modeling. This study also considers the interaction effect of sex and academic year level on both variables. Focusing the study on preservice elementary teachers might address potential issues and targeted intervention in their preparation program concerning their ability to teach and guide young learners in modeling activities. The research sample includes 140 preservice elementary teachers at Central Luzon State University, Philippines. Data collection used an adapted metacognitive awareness inventory and a validated researcher-made mathematical modeling competency test aligned with the K-12 mathematics curriculum in the Philippines. Results revealed that the preservice elementary teachers had a high metacognitive awareness and mathematical modeling competency, ranging from 22 to 31 out of 36 points. Besides, Factorial ANOVA indicates that academic year level positively affects both variables regardless of sex, and stepwise regression analysis unveiled that information management, declarative knowledge, and planning significantly predict 41.4% of the mathematical modeling competency variance. This suggests that developing metacognitive awareness supports preservice elementary teachers in performing modeling tasks that improve their competency level in mathematics.

The ability to solve problems is a prerequisite in preparing mathematics preservice teachers. This study assessed preservice teachers’ problem-solving difficulties and performance, particularly in worded problems on number sense, measurement, geometry, algebra, and probability. Also, academic profile differences in the preservice teacher’s problem-solving performance and common errors were determined. A descriptive-comparative research design was employed with 158 random respondents. Data were gathered face-to-face during the first semester of the school year 2022-2023, and data were analyzed with the aid of jamovi software, ensuring ethical measures. Overall findings revealed that the preservice teachers experienced average difficulty in solving problems. The low performance of the preservice teachers on the given problems was also demonstrated. Further analysis revealed a significant difference between the preservice teachers’ problem-solving performance based on their subject preference and program. Moreover, the error analysis revealed that the preservice teachers incurred comprehension errors in misrepresentation, misinterpretation, and miscalculation. These results will serve as a measure for policymakers and curriculum developers of the teacher education institution concerned to make relevant enhancements to the math courses offered in the elementary and secondary education programs.

This capstone project aimed to develop an offline computer-based assessment (CBA) tool that uses a computer instead of a traditional paper test in evaluating student learning. This addresses the difficulties faced by teachers in administering quarterly assessments. Incorporating technology into student assessment can increase student interest because of the immediate feedback generated automatically and can help teachers improve their work performance. This capstone project employed a developmental approach and utilized a modified ADDIE (Analysis, Design, and Development) model to design the tool using Microsoft PowerPoint and Excel. Ten experts in mathematics, ICT, and assessment validated the face and content validity of the developed CBA tool. Based on the panel’s evaluation, the developed offline CBA tool in Statistics and Probability has passed all the assigned criteria, such as functionality, usability, efficiency, technicality, and accessibility. Overall, the developed CBA tool is suitable for use to address assessment-related issues.

E-Government refers to the administration of Information and Communication Technologies (ICT) to the procedures and functions of the government with the objective of enhancing the transparency, efficiency and participation of the citizens. E-Government is tough systems that require distribution, protection of privacy and security and collapse of these could result in social and economic costs on a large scale. Many of the available e-government systems like electronic identity system of management (eIDs), websites are established at duplicated databases and servers. An established validation and management system could face a single failure point and the system is prone to Distributed Denial of Service Attacks (DDoS), denial of service attacks (DoS), malware and other cyber attacks. The execution of a privacy preserving and a secure decentralized system is enabled by the block chain technology. Here any third-party organizations do not have any control over the transactions of the Government. With the help of block chain technology, new and existing data are encapsulated within ledger or blocks, which are evenly distributed through the network in an enduring and sustainable way. The privacy and security of information are improved with the help of block chain technology, where distribution and encryption of data are performed through the total network. This analytical paper maps out the analysis of the security in the e-government system, utilizing the block chain technology that provides privacy and security of information and thereby enhancing the trust among the public sector. Qualitative and theoretical analysis is made for the proposed topic and implications of privacy and security of the proposed system is made.

Understanding quantitative research instrumentation is critical for advancing educational research, both theory and practice since it contributes to the accuracy and credibility of research findings (Creswell & Plano Clark, 2017; DeVellis, 2017; Streiner et al., 2014). Using inappropriate or poorly designed instruments can result in inaccurate or unreliable data, compromising the quality of the research findings and limiting the research's usefulness. Understanding the appropriate use of quantitative research instruments is critical from a theoretical standpoint for ensuring that research questions are answered accurately. Researchers (pre-service teachers, in-service teachers, teacher educators, and educational leaders) can get high-quality data that can be used to create and test theories in a particular field by selecting and designing the relevant instrument. Furthermore, using reliable and valid quantitative research instruments can boost the credibility of research findings and aid in developing new research questions and hypotheses. From a practical perspective, understanding quantitative research instrumentation can improve the quality of research practice. Researchers can ensure that the data acquired is accurate and reliable by selecting and creating appropriate instruments, which can help to guide decision-making in a particular subject. Furthermore, reliable and valid instruments can guide policy decisions, program development, and evaluation, resulting in more effective interventions and better outcomes. Where and How to Begin? The choice of research instrument depends on the research question, the nature of the phenomenon being studied, and the available resources (Bryman, 2016; Creswell, 2014; Dörnyei, 2007; Hair et al., 2014). Researchers can acquire accurate and valid data to answer their research questions and contribute to the knowledge base in their field by carefully selecting and building instruments. In education and the social sciences, quantitative research frequently involves using various instruments or tools to collect and analyze data.

The study determined the problem solving skill and performance of elementary pre-service teachers (EPTs). This was conducted in Benguet State University on the first semester of SY 2018-2019. The problem solving performance of the EPTs was ascertained through a problem set composed of word problems on number sense, measurement, geometry, algebra and probability. Verschaffel, Greer and De Corte’s (2000) Problem Solving Model was used to describe the EPTs’ problem solving skill. Sequential-explanatory mixed method research design was used. One hundred thirty-one (131) EPTs participated in the study through purposive total population sampling. Big percentage of the elementary pre-service teachers preferred to teach other subjects than mathematics. EPTs who preferred math showed satisfactory performance while pre-service teachers who opted other subjects showed unsatisfactory performance. The EPTs’ unsatisfactory performance suggested the need for remediation to advance the mathematical content knowledge and to enrich the problem solving abilities of these future teachers of primary schools. ANOVA and Regression Analysis showed that subject preference highly influenced and predicted the EPTs’ problem solving performance. EPTs who preferred to teach mathematics performed significantly better than their counterpart, hence, mathematics as a field of specialization in the Bachelor of Elementary Education program may be considered by teacher education institutions. Besides, majority of the EPTs especially those who preferred to teach other subjects displayed lacking problem solving skill in understanding the text, situation modeling, mathematical modeling, and analysis and derivation of result, thus, a Problem Solving subject is recommended for the EPTs.

Mathematical confidence and critical thinking are essential in preparing preservice teachers. Thus, this study explored the perceived confidence and critical thinking levels in mathematics of elementary and secondary preservice teachers. A descriptive-correlational-comparative research design was employed, with a sample of 107 randomly selected preservice teachers enrolled in the Bachelor in Elementary and Secondary Education programs of a state university in West Philippines. The study used arithmetic mean, standard deviation, Spearman’s rank-order correlation, and independent samples t-test to analyze and draw conclusions from the data. The findings revealed that the preservice teachers have high confidence and critical thinking skills. Their program significantly correlates with their perceived critical thinking and confidence level. Besides, the preservice teachers’ confidence levels and perceived critical thinking skills significantly correlate. Further analysis found significant confidence and critical thinking differences favoring the secondary over the elementary preservice teachers. These findings provide insights that would benefit mathematics educators in providing priority programs to enhance the preparation of future math teachers.

Elementary preservice teachers (EPTs) substantially impact the quality of mathematics education, and their subject preference and problem-solving performance are essential indicators of their readiness to teach. The study described EPTs’ subject preference and problem-solving performance. Through a sequential explanatory research design, the quantitative inquiry involved 125 random samples, while the qualitative inquiry was participated by 30 non-random samples. Data were obtained by using an online survey and conferencing. Quantitative data were analyzed through descriptive statistics and analysis of variance, whereas qualitative data were themed accordingly. The EPTs displayed unsatisfactory problem-solving performance and preferred to handle subjects other than math. Besides, the analysis found no significant performance differences with the EPTs’ subject preferences. Further, the EPTs who preferred to teach mathematics expressed their confidence in mathematics. Meanwhile, the EPTs who preferred other subjects displayed math avoidance. The study revealed an alarming result indicating that the EPTs are unprepared for teaching. As agents in cultivating the nation’s mathematics education status, these EPTs must be equipped with fundamental content knowledge. It is suggested that educational decision-makers take measures to address the issues identified concerning EPTs’ readiness to teach mathematics successfully.

The potential benefits of cognitive skills in enhancing mathematics ability have been claimed by numerous researchers. Since mathematics requires a complete understanding and grasp of abstract concepts, it is essential to explore how learning with metacognitive skills affects mathematics learning. Thus, the study investigates the students' metacognitive awareness and conceptual understanding of integers. A descriptive-correlational method approach was utilized, and it was carried out on 303 seventh-grade students. The data were obtained using a metacognitive awareness inventory and achievement test on integers. It was further revealed that the students have average metacognitive awareness and performed well in the fundamental operation of integers. Follow-up qualitative analysis revealed that students who were high achievers had the best understanding, average achievers had corrected or incomplete understanding, and low achievers had a functional misconception of integers. Moreover, the student's metacognitive awareness was significantly related to their conceptual understanding of integers. This indicates that student's higher-order thinking skills, such as metacognition, are essential since they are associated with building conceptual skills. Thus, teachers should encourage students' metacognitive awareness to improve students' conceptual understanding of integers. The study provides relevant information for educational managers on the potential factors to be considered in improving mathematics education practices, particularly in promoting metacognition among high school students.

The study aimed to determine if differentiated instruction effectively addresses learning gaps in mathematics. In particular, it explored how it can improve the student’s learning gaps concerning mathematical performance and confidence. The study employed a quasi-experimental design with 30 purposively-selected Grade 10 participants divided into differentiated (n = 15) and control groups (n = 15), ensuring the utmost ethical measures. The mean and standard deviation were used to describe the participants’ performance and confidence. Independent samples t-tests were used to determine the significant differences in the performance and confidence between the two groups. In contrast, dependent samples t-tests were used to determine the significant differences in each group’s pre and posttest performance and confidence. Findings bared that the differentiated instruction successfully addressed students’ performance in mathematics even in a short period. It also increased the participants’ confidence when answering fundamental problems. Continuing differentiated instruction activities are recommended since it benefits students who struggle in mathematics, particularly in answering fundamental operations. Differentiated teaching activities in mathematics can boost academic achievement and engagement and prepare students for future success while fostering a positive and inclusive classroom culture that values individual learning needs and preferences.

Everyone who works in the classroom does their best to learn available and applicable pedagogy so that they can deliver their lessons effectively. They, too, put their best foot forward by implementing a variety of assessment tasks and tools to assess and evaluate how well their students are learning. The curriculum is essential not only for curriculum developers but for everyone involved in the teaching-learning process. Crucial processes are involved in the development, implementation, evaluation, and revision of a curriculum, thus, its foundations - philosophical, psychological, and social - are taken into consideration.

The study’s goal was to provide an educational intervention in Algebra through GeoGebra that would boost students’ confidence, improve their learning, and correct their most minor mastered skills, allowing them to improve their Algebra performance. The research design was quasi-experimental, with 40 nonrandomly chosen participants comprising the GeoGebra and control groups. Mean and standard deviation was employed to describe the algebra performance and confidence of the respondents. At the same time, independent and dependent t-tests were used to determine the students’ significant difference in algebra performance and confidence in the pre-and post-test between the control and GeoGebra groups. GeoGebra effectively improved algebra confidence, enhanced learning, and remedied the students’ least mastered skills. GeoGebra is recommended as an instructional material in teaching and learning Algebra and can be extended to other mathematics content areas.

Math prospective teachers must be able to think creatively and solve problems. The study looked into preservice teachers’ creative thinking and problem-solving abilities in statistics. The investigation was guided by a correlational design in a public university in the Philippines. Stratified random sampling was used to select the 103 study participants from two teacher education programs. Through google forms, data were collected using Torrance et al. (2008)’s tests of creative thinking and researcher-made statistics problem test. The findings revealed that preservice teachers have commendable creative thinking, particularly fluency, flexibility, and elaboration skills. Still, they lack problem-solving skills in statistics, specifically with central tendency, dispersion, and position measures. The correlational analysis revealed no link between creative thinking and problem-solving. Still, creative thinking and problem-solving courses are recommended to help preservice teachers develop their fundamental skills as mathematics educators.

This correlational study investigated the relationship between preservice teachers’ math self-concept, self-efficacy, and attitude with their math achievement. Participants were chosen using stratified random sampling from BEEd and BSEd mathematics majors (n = 117). From the findings, preservice teachers had moderate to high math self-concept, self-efficacy, and attitude. These variables were statistically correlated with each other and with math achievement. The inclusion of training programs for developing the preservice teachers’ math self-concept, self-efficacy, and attitude, as well as designing curricula that engage and encourage them to do mathematics and problem-solving, must be considered among teacher education institutions.

Parental factors impact students’ self-concept and academic performance during the pandemic. Thus, this study determined the students’ self-concept and academic performance and the parental factors related to it. The research design was descriptive-correlational, and 500 nonrandom college students in West Philippines participated in the study. Researcher-made instruments were used, which were subjected to reliability and validity evaluation. Data were collected online from June 2021 to July 2022 and were analyzed using descriptive (frequency counts and percentage) and inferential statistics (Spearman correlation). Results revealed a positive self-concept and satisfactory academic performance among the students. Besides, parental factors such as educational attainment and school/classroom involvement are significantly related to self-concept and academic performance. Further, self-concept is significantly associated with academic performance. This shows that some parental factors are vital in developing the student’s self-beliefs and supporting their studies and academic endeavors amid the COVID-19 pandemic. Future studies may consider more factors related to academic achievement and self-concept. Other researchers may find the mediation or moderation effect of self-concept between parental factors and students’ scholastic achievement.

The Internet of Things (IoT) connects schemes, programs, data management, and operations, and as they continuously assist in the corporation, they may be a fresh entryway for cyber-attacks. Presently, illegal downloading and virus attacks pose significant threats to IoT security. These risks may acquire confidential material, causing reputational and financial harm. In this paper hybrid optimization mechanism and deep learning,a frame is used to detect the attack prevention in IoT. To develop a cybersecurity warning system in a huge data set, the cybersecurity warning systems index system is first constructed, then the index factors are picked and measured, and finally, the situation evaluation is done.Numerous bio-inspired techniques were used to enhance the productivity of an IDS by lowering the data dimensionality and deleting unnecessary and noisy input. The Grey Wolf Optimization algorithm (GWO) is a developed bio-inspired algorithm that improves the efficacy of the IDS in detecting both regular and abnormal congestion in the network. The smart initialization step integrates the different pre-processing strategies to make sure that informative features are incorporated in the early development stages, has been improved. Researchers pick multi-source material in a big data environment for the identification and verification of index components and present a parallel reduction approach based on the classification significance matrix to decrease data underlying data characteristics. For the simulation of this situation, grey wolf optimization and whale optimization were combined to detect the attack prevention and the deep learning approach was presented. Utilizing system software plagiarism, the TensorFlow deep neural network is intended to classify stolen software. To reduce the noise from the signal and to zoom the significance of each word in the perspective of open-source plagiarism, the tokenization and weighting feature approaches are utilized. Malware specimens have been collected from the Mailing database for testing purposes. The experimental findings show that the suggested technique for measuring cyber security hazards in IoT has superior classification results to existing methods. Hence to detect the attack prevention in IoT process Whale with Grey wolf optimization (WGWO) and deep convolution network is used.

At the beginning of 2020, the world was experiencing the Covid-19 pandemic, and Indonesia was no exception. The occurrence of this affects the learning system in Indonesia, the learning system that was originally face-to-face was forced to online form, in this case the teachers are required to provide a creative, efficient and optimal learning system for students. So the purpose of this study is to find out the difference in the average learning result of elementary school students during the pandemic. The method used in this study is quantitative with a posttest-only control group design. The population in this study were grade 4 elementary school students in Majalengka district, Indonesia. There were 64 samples and was taken by purposive sampling. The results of this study are that there are differences in the average student learning results where students who study with the hybrid learning system are higher than the face-to-face learning system. The hybrid learning system is very reliable in the 4.0 era as well as learning during the Covid-19 pandemic. However, for the record, it is necessary to look at the facilities and infrastructure considering that this system relies on technology, it is necessary to understand and be able to control the learning media for both teachers and students so that learning outcomes can be optimal and minimize the occurrence of obstacles. The present study revealed the implementation of 21st century learning.

The integration of Internet Protocol and Embedded Systems can enhance the communication platform. This paper describes the emerging smart technologies based on Internet of Things (IOT) and internet protocols along with embedded systems for monitoring and controlling smart devices with the help of WiFi technology and web applications. The internet protocol (IP) address has been assigned to the things to control and operate the devices via remote network that facilitates the interoperability and end-to-end communication among various devices c,onnected over a network. The HTTP POST and HTTP GET command that supports the RESTful service have been used to ensure the transmission and reception of packets between the IOT Gateway and Cloud Database. The emerging smart technologies based on the Internet of Things (IoT) facilitated features like automation, controllability, interconnectivity, reliability which in turn turn paved the way for a wide range of acceptance amongst the masses. The Internet of Things (IoT) has brought in many new emerging technologies into varoius field like our daily lives, industry, agricultural sector, and many more. The world is experiencing the explosive growth with the advent of Internet of Things (IoT) these years. The potential growth of IoT is enoromous which is evidenced by all the human beings in our day to day life.

Academic institutions migrated to modular teaching-learning amid the COVID-19 pandemic. To ensure the quality of the pedagogical innovations employed, the study determined the students’ evaluation of the faculty prepared instructional modules for the courses they enrolled in during the first and second semesters of Academic Year 2020-2021. Employing a descriptive-correlational research design, the study was participated by 644 students from three colleges who were then available during the data gathering. Data gathered through online surveys were then analyzed using descriptive statistics and Spearman's rank correlation coefficient utilizing jamovi software. Results revealed that the faculty-prepared instructional modules were acceptable and satisfactory to the students. Besides, the students' evaluation of the instructional modules was positively related to their level of satisfaction. Still, the students recommended that a review of the modules be done before sending the modules; a more extended time allotment is considered, and sufficient concrete examples are given in the modules. With this, the faculty concerned are encouraged to review the phases involved in the design, development, and distribution of the instructional modules to make them highly acceptable and very satisfactory to the students while maintaining the quality of both the content and aesthetics of the learning materials. Considering the study’s limitations, further endeavors may be carried out to validate this pedagogical innovation.

When it comes to online fashion, this research focused on the interaction between three factors: preferences for online fashion goods, consumer buying choices for online fashion products, and brand image. A descriptive correlational approach was used. A total of 184 sampled active online purchasers of fashion items from a population of 350 online buyers in Thailand participated in the research. The study was carried out with the use of tools that had been adopted. Descriptive data showed that respondents had a high preference for online marketing, a positive attitude towards online fashion goods, a high degree of consumer buying choices towards online fashion products, and a high preference for favorable brand image in the research. There were significant variations in respondents' preferences for online shopping as well as attitudes toward fashion items and consumer purchase decisions based on age, civil status, education, monthly income, and profession, according to the results of a test of difference. A further connection test revealed that respondents' liking for online marketing tends to improve their attitude toward online fashion items and consumer buying choices. In the end, the results of multiple regression analysis revealed that age, civil status and education level, online marketing approach, attitude towards online fashion goods, and brand image and attitude are all predictors of buying choices. The study's practical consequences for an internet business are addressed. The study's practical consequences for an internet business are addressed.

Learner’s attitude towards modular distance learning catches uncertainties as a world crisis occurs up to this point. As self-learning modules (SLMs) become a supplemental means of learning in new normal education, this study investigated efficiency towards the learners’ attitude and performance. Specifically, the study described the learners’ profile and their attitude and performance towards SLMs. It also ascertained the relationship between the learner’s profile with their attitude and performance, as well as the relationship between attitude and performance relevant to SLMs. A descriptive-correlational research design was employed in the study with 88 non-randomly chosen participants from secondary schools in West Philippines. The learners’ GWA (general weighted average) was used to determine their performance and a survey questionnaire for their profile and attitude. Frequency counts, percentage, and Spearman’s rank correlation coefficient were used to analyze the data gathered with the aid of Jamovi software. Results revealed a strong correlation between attitude and performance, but there was no link between learner’s attitude and performance as to the learner’s profile. It was affirmed that attitude is a compelling factor that is related with performance. Hence, this research has broader ramifications that can direct the Bureau of Learning Delivery to orient the module writers to further contextualize the learning materials that can compound learner’s disposition and academic performance.