This study focused on teachers' awareness of students' learning situations during distance learning. It took place at the Nueva Ecija University of Science and Technology (NEUST) - Gabaldon Campus during the academic year 2021-2022. The study employed descriptive-comparative and descriptive-correlational designs. The 249 students were selected using a stratified sampling technique, whereas the 25 teachers were selected using a purposive sampling technique. Findings revealed that teachers are aware of their students' situations. The students believe that they faced learning challenges during distance learning. There is a significant difference between male and female teachers in terms of student learning environment awareness, but no statistically significant difference in the teacher's awareness of the student's learning situation across age groups, service years, and academic rank. There is a significant difference in the learning anxiety of male and female students but not in the learning environment and blended learning readiness. The learning environment and readiness for blended learning do not differ significantly across age groups of students, but anxiety does. A statistically significant difference in student readiness in blended learning was observed based on students' courses but not on the learning environment or anxiety. There is no significant difference in students' learning situations based on family income or parental educational attainment. There was no significant difference in student achievement based on the teachers' level of awareness. Achievement is positively correlated with learning environment and readiness but negatively associated with anxiety. In addition, the study discussed its theoretical and practical implications.  

This research aims to examine the effect of coding education on the analytical thinking skills of gifted students. The participants are 18 students, 11 to 12 years old. An embedded experimental mixed design was used in the research. The data collection was carried out with the Analytical Thinking Skill Scale to determine the difference in the analytical thinking skills of the study group before and after the coding training; the Analytical Thinking Skill Observation Form to determine the analytical thinking skill levels during the implementation process; and the semi-structured interview form to get their opinions on the coding training. The data were analyzed with a pre-test-post-test quasi-experimental design, descriptive analysis, and content analysis. The results show that coding education developed the participants' analytical thinking skills. The difference in the analytical thinking skills of the study group was not statistically significant in terms of gender. According to the students' views on the coding education application process, there was an improvement in the sub-dimensions of sorting, classification, comparison, and evaluation in analytical thinking skills; coding education developed problem-solving and thinking skills, was useful, encouraged students to choose a profession, and was entertaining, as well as negative opinions such as being difficult, boring, and requiring a lack of time.

The influence of COVID-19 has caused a sudden change in learning patterns. Therefore, this research studied the learning achievement modified by online learning patterns affected by COVID-19 at Rajabhat Maha Sarakham University. This research has three objectives. The first objective is to study the cluster of learning outcomes affected by COVID-19 at Rajabhat Maha Sarakham University. The second objective is to develop a predictive model using machine learning and data mining technique for clustering learning outcomes affected by COVID-19. The third objective is to evaluate the predictive model for clustering learning outcomes affected by COVID-19 at Rajabhat Maha Sarakham University. Data collection comprised 139 students from two courses selected by purposive sampling from the Faculty of Information Technology at the Rajabhat Maha Sarakham University during the academic year 2020-2021. Research tools include student educational information, machine learning model development, and data mining-based model performance testing. The research findings revealed the strengths of using educational data mining techniques for developing student relationships, which can effectively manage quality teaching and learning in online patterns. The model developed in the research has a high level of accuracy. Accordingly, the application of machine learning technology obviously supports and promotes learner quality development.

This research analyzes the effects of restricting face-to-face classes during the lockdown and students' preparation for face-to-face instruction. During the academic year 2021-2022 break, it was conducted at Nueva Ecija University of Science and Technology (NEUST)-Gabaldon Campus's College of Education. This study employed a descriptive correlational and descriptive comparative research design. The 151 education students who participated in this study were chosen using a stratified sampling method. According to the study, students received satisfactory to very satisfactory grades during the lockdown. The study also showed that after the lockdown and after the Commission on Higher Education recommended face-to-face classes, the majority of respondents agree that they are academically, socio-emotionally, and physically prepared to go through a face-to-face mode of learning. The majority of them prefer face-to-face classes to any other form of distance learning. The general weighted average of a student is a predictor of academic readiness in face-to-face classes. In addition, students' general weighted averages have direct link to their socio-emotional readiness. Students' profiles, on the other hand, have no impact on their physical readiness. There is no significant difference in student preparation in face-to-face classes when students are grouped by gender, year and section, and civil status. There is no association between the student profile and their preferred mode of learning. The theoretical and practical ramifications of the research were also addressed.

Researchers have recognized the need for updates of test anxiety scales for more measurement accuracy. However, studies that investigated the measurement invariance of the Test Anxiety Inventory (TAI), and identified the latent profiles remain scare not withstanding its wide usage in Nigeria. This might have an impact on how generalizability and reliance on outcomes from such an instrument are handled. We investigated the measurement invariance of TAI and the latent profiles among Nigerian adolescents. Gender constituted our focus in the measurement invariance given its significance in test anxiety research. Adolescent students (n=539) formed the sample of our study. We employed the confirmatory factor analysis (CFA) and the latent profile analysis (LPA) to measure the invariance and identify the class profiles. We found evidence of a measurement invariance across gender in both competing models given that we obtained strict measurement invariance. We also identified a four-class profile model for both male and female students: low (17.50%; 19.00%), moderate (17.50%; 34.40%), high (36.80 %; 32.80%), and very high (12.60%; 13.80%) test anxiety profiles respectively. We concluded that while the composed factors are equivalently scaled across gender that test anxious students were not monolithic given the identified profiles.

This study explores the impact of gender on the preferred English language learning strategies of self-perceived introverted students in Vietnam, given the burgeoning role of English as an international lingua franca. A mixed-methods approach, involving survey questionnaires and follow-up interviews, was utilized to gather both quantitative and qualitative data from a cohort of 68 English major undergraduates, 29 of whom self-identified as introverted via the Myers-Briggs Type Indicator (MBTI). The investigation provides a comprehensive understanding of the preferred language learning strategies among introverted learners, and specifically examines how gender influences these strategic choices. The results reveal that gender does not present significant differences in the preferred English language learning strategies of self-perceived introverted individuals. Regardless of gender, introverted language learners demonstrate a tendency towards compensation learning strategies, with specific strategies such as deductive reasoning, organizing physical environs, and error rectification receiving almost identical responses from both male and female participants. These findings suggest that the role of personality traits, such as introversion, should be considered in tailoring pedagogical approaches to meet individual learning preferences and needs. Further research is needed to explore this area in greater depth and to examine its broader implications for English language teaching pedagogy.

The iNaturalist application has been gaining traction in both biodiversity research and education. Increasingly more research is being carried out, looking into using the iNaturalist application in biology education, to promote biodiversity and educate students about this topic. We used the PRISMA systematic literature review method to examine research carried out using the iNaturalist application in biology education by searching Web of Science and Scopus, and including citizen science in the process. We searched through the iNaturalist forum, where users contribute research performed using iNaturalist. We found that an increasing number of articles have been published on this topic over the years. Researchers are using iNaturalist to improve BioBlitz activities, to enhance outdoor education activities, and to help make herbaria. Summarizing the work performed in this area, we suggest guidelines for including and preparing the iNaturalist application in a school context to be used by teachers and researchers alike.

Education systems worldwide have been significantly disrupted due to the COVID-19 pandemic, creating an immediate need for a revamp of conventional teaching and learning techniques. To explore how this has affected the educational landscape, a scoping review was conducted. This scoping review aimed to examine the changes that occurred in the education field and to explore how it has transformed the educational landscape review. Using Arksey and O'Malley's methodology, 51 articles were selected for analysis from two leading databases: Scopus and Web of Science. All chosen articles were then subjected to thematic analysis. Three main aspects impacted by this global event were uncovered, which are technological advancements and digital transformation, changes in pedagogy and teaching methods, and mental health and well-being issues. This scoping review provides valuable insights into one of the most critical sectors affected by COVID-19, which can assist with planning future strategies for similar crises.

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.

This paper explores information related to misconceptions and conceptual change during the last thirty years 1992-2022 to be used as a preliminary study in science education. This study used bibliometric analysis with the help of the Scopus database. This paper used a bibliometric analysis study with the Scopus database and the help of MS Excel, VosViewer, and Rpackage software to visualize the data obtained. The results of this research found that Indonesian researchers have contributed the most in terms of the number of documents published in Australia and the United States. Additionally, research on these two topics has decreased since 2019 due to the Covid-19 pandemic. In addition, these findings present trends in the areas of misconceptions and conceptual change that can be used as baseline data for future research. Studies related to misconceptions will continue to develop because they cannot be separated from the inside of education, whether at any level of elementary school, middle school, or college. This is an opportunity that must be taken advantage of by institutions and policies in an effort to improve and create quality of education, teacher resources, and students.

The computing and creative skills of students in Indonesia are still low since the government has not focused on student creativity and computational empowerment programs. This research aims to develop a science, technology, engineering, art, mathematics, and reflection (STEAMER) hybrid learning project model for teachers' creative and computational thinking abilities, as well as analyze elementary school teacher candidates' perceptions of the use of STEAMER hybrid learning model to improve teachers' creative and computational thinking abilities. This research is development research with an analysis, design, development, implementation, and evaluation (ADDIE) model. The instruments used in this study were questionnaires and interviews with experts, lecturers, and elementary school teacher candidates. The research was conducted at eight universities in Indonesia with a total sample of 100 elementary school teacher candidates. Through quantitative and qualitative data analysis, the research results have developed the STEAMER hybrid learning project model based on learning theory, syntax, social systems, support systems, and the instructional impact of learning models. The results of the validation show that the developed learning model is feasible in terms of model, material, media, and language experts. The model is suitable for elementary school teacher education. Furthermore, based on the perceptions of the teacher candidates, it is stated that the STEAMER hybrid learning project can develop the ability of the teacher candidates to think creatively and computationally.

The research on the pedagogical knowledge of teachers in technological education arises from the need to address the problem of pedagogical practices, which are traditional. The classes are at the graduate level, focusing on lecturing the student while the student remains with a passive attitude. It is believed that making explicit that teachers' pedagogical knowledge will allow reflection and awareness, thereby transforming pedagogical practices. Therefore, the objective is to understand the teachers’ constructions on pedagogical knowledge in technology programs in Plant Operations and Industrial Instrumentation of the Faculty of Engineering in order to reconstruct it theoretically, as well as identify its characteristics and trace action routes for teacher training. In this way, it allows education to be accessible to low-income and resource-poor populations, whose purpose is to strengthen the productivity and competitiveness of the economy through the training of human talent according to the needs of the working sector in a unique context. This research uses grounded theory as a methodological tool for data processing. In this sense, data collection procedures such as in-depth interviews were conducted with 16 teachers and seven of them were related to the industry. Whereas, 9 were linked to the teaching(educational) sector including elementary, high school and college level. The results showed differentiated, and socially constructed pedagogical knowledge that responds to teachers’ nature in a particular context. These results contribute to consolidate a broad vision about the pedagogical knowledge’s characteristics that the teacher builds.

Certain demographics of students may prefer certain modalities, and certain demographics may achieve higher mean grades in some teaching modalities than others. This study used student-section data from five years of all the undergraduate courses at Kennesaw State University (KSU) from 2015 to 2019. This data set with individual student course outcomes included full student demographics and course types, including previous university grade point average (GPA), sex, age, ethnicity, course department, modality, etc. The study only used data from those instructors who taught hybrid sections, as well as in-person and online sections, to avoid the effect of instructor bias. Previous research found that instructors who taught hybrid sections gave higher grades for their online and F2F sections compared to those instructors who had not taught hybrid sections. The results showed that that hybrid-teaching instructors gave higher mean course grades for their hybrid sections than their online or F2F sections and higher mean course grades than non-hybrid teaching instructors in all modalities. This effect held for all demographics.

There are studies in the learning management literature examining the measure of system usage, but few explore how users apply the software tools to achieve specific work tasks, which in turn leads to perceived benefits. In the context of distance education, this study focuses on how Learning Management Systems (LMS) are fully used by faculty for their instructional needs. It extends existing research on LMS adoption by investigating how faculty members or instructors use the LMS tools for effective class teaching to achieve educational outcomes. Four usage patterns were identified: communication, content management, assessment, and class management. A model is presented to examine how these usage patterns interplay to achieve the perceived benefits. Data were collected from 544 instructors using LMS, such as Blackboard Learn, etc. Structural equation modeling using LISREL was employed to assess the research model. The results suggest that the usage for communication, content, and assessment activities positively impacts the usage for class management. In turn, the usage for class management influences the net benefits perceived by the instructors, and the usage for content also impacts perceived net benefits directly. These results provide practical guidelines for LMS developers’ design improvements and institutions’ policies, such as training instructors to fully utilize LMS features to achieve the maximum benefits of distance education.