The objective of this study was to confirm the factor structure for two versions of the Statistics Anxiety Scale (SAS) created for American undergraduate statistics students. To address the inconsistent factor structure of SAS across different populations, Lorenzo-Seva et al. (2022) revised the SAS. This version reduced the number of questions and added a 4th factor called social desirability. They reported a good fit without the need for introducing correlations between error terms, which were outcomes found in different versions of the SAS including this study. This revised SAS considers a 4th dimension called social desirability, suggesting that this dimension could account for much of the error variance found in previous studies. That dimension was not included in this study. A modified three factor model explained construct validity in the original version of the SAS. A modified five factor model explained construct validity in a version of the SAS with additional items. Both versions of the SAS and their factors displayed acceptable levels of fit, were found to have reliability coefficients above .70, and generally shared moderate negative relationships with Wise’s Attitude Toward Statistics scale.
Bullying is a destructive social phenomenon that, contrary to common perception, is not only a problem in childhood and adolescence but affects all age groups and communities. This study concentrates on the experience of being a victim of bullying during higher education studies, aiming to describe the victimization process from start to finish. The research question is: How is the phenomenon of bullying of higher education students described by victims? To answer this question, the study analyzes the bullying experiences of 19 participants using a narrative approach. Two datasets were gathered, using an anonymous online questionnaire and interviews. The findings illustrate the multiformity of victims’ perceptions and the complexity of the phenomenon. They show that although every experience is unique, they share common factors, especially at the beginning and end of the bullying process; that instead of sticking to official bullying definitions, it is imperative to prioritize the perception of the victim, and that it is important to recognize the multilateral loneliness of victims. Furthermore, the study reflects on possible solutions drawing on the findings and previous research.
This study investigated assessment literacy development among 250 pre-service teachers at Xavier University, Philippines, from 2020 to 2024, using the Assessment Literacy Progression and Perception (ALiPP) framework. Employing a convergent parallel mixed-methods design, the study integrated quantitative data, including comprehensive examination scores, GPA, program, gender, and year level, with qualitative data from semi-structured interviews and written reflections to examine performance trends, predictors, and perceptions within the Philippine Outcomes-Based Education context. Statistical analyses included paired t-tests, correlation, ANOVA, and multiple regression, while thematic analysis explored challenges, supports, and perceived relevance. The ALiPP framework modeled assessment literacy as iterative cycles of performance and reflection, addressing gaps in longitudinal research. Findings informed curriculum recommendations emphasizing scaffolded learning, enhanced feedback, and early practicum integration. The study contributes to teacher education by offering a context-specific, mixed-methods approach to assessment literacy that is adaptable to diverse educational settings.
This study examined the awareness, attitudes, and likelihood of action on sustainability among 130 secondary students in the southern Philippines. Grounded in Social Cognitive Theory and Transformative Learning Theory, the research utilized a 51-item SDG-based survey aligned with UNESCO's (2017) learning objectives for Education for Sustainable Development (ESD). Descriptive statistics revealed high levels of awareness in familiar sustainability issues such as waste reduction, mental health, and water conservation. In contrast, lower awareness was observed in more technical and abstract domains, such as ICT infrastructure and economic growth. Attitude responses were positive, particularly concerning empathy, education, and environmental responsibility. Action-related items showed variability, with stronger intentions linked to education and climate-related topics, and weaker intentions in areas requiring technical knowledge or leadership. Pearson correlation analysis indicated significant, positive relationships among awareness, attitudes, and actions, with the strongest correlation between attitudes and actions. The findings underscore the need for sustainability education that builds knowledge and empowers students through experiential, skill-based, and values-driven learning to turn awareness into transformative action.
This study aimed to develop electronic instructional anchor, Video-on-Demand Cast (VODCast), to address the identified least-mastered competencies in the General Physics 1 of Grade 12-STEM, particularly the competencies of “Measurement errors”; “Addition of Vectors”; and “Uniformly Accelerated Motion”. The study engaged 52 Grade 12-STEM students and 5 evaluators: educational technology, information technology (IT), English, curriculum development or instructional materials development, and teacher of General Physics 1. Data collection involved the General Physics Test (GPT) and adopted Generic Instrument for the Review, Evaluation, and Approval for Use of Instructional Materials (GIREAUIM). Findings revealed that while VODCast effectively enhanced students' engagement and skill mastery, challenges and areas for improvement were noted. Expert evaluations highlighted its strong usability, suitability, engagement, and alignment with science content. The acceptability of the VODCast as evaluated by students and experts in general and in terms of contents, format and presentation, efficacy of materials, and performance assessment was rated “Highly Acceptable”. Future research should investigate its long-term effects and scalability to maximize its impact as a transformative educational tool. This study affirms the potential of multimedia learning in addressing critical learning gaps and advancing student-centered science education.
Metacognitive ability plays a crucial role in the Combinatorics course, which requires a deep understanding of concepts and complex problem-solving strategies. This study aims to examine the relationship between the Felder-Silverman learning style model and students' metacognitive knowledge in the context of the Combinatorics course. The primary focus is on analyzing metacognitive gaps among students with similar learning styles. Using a qualitative descriptive approach, data were collected through learning style questionnaires, open-ended questions, semi-structured interviews, and participatory observations of four students with diverse academic backgrounds and learning styles. The findings indicate that although two students share the same learning style combination (active, sensing, visual, and sequential), their level of metacognitive knowledge differs significantly. One student demonstrated strong declarative, procedural, and conditional understanding, while the other could only theoretically identify strategies without concrete implementation. This difference suggests that learning styles are not always the sole predictor of metacognitive achievement. Factors such as self-reflection, emotional regulation, and active learning habits also influence the effectiveness of learning strategy implementation. These findings challenge conventional views on the linear correlation between learning styles and metacognition and offer new insights into the design of learning approaches that integrate learning styles and reflective abilities in a more adaptive and personalized manner.
Early childhood science education has gained increasing recognition as a critical foundation for developing scientific literacy and environmental consciousness. This study investigates the development and implementation of science learning environments based on real-world experiences and nature for preschool children aged 3-6 years in Vietnamese educational contexts. Using a mixed-method approach, we conducted comprehensive research involving 186 participants across 15 kindergartens in three major regions of Vietnam, including structured observations, surveys, and in-depth interviews with educators, parents, and educational experts. Results demonstrate that nature-based science learning environments significantly enhance children's scientific inquiry skills, environmental awareness, and overall cognitive development compared to traditional classroom-based approaches. Children participating in nature-based programs showed 34.7% improvement in scientific observation skills, 28.3% increase in environmental awareness, and 31.2% enhancement in collaborative problem-solving abilities. The main contribution of this research is the development of the "Nature-Integrated Science Learning Environment Model for Vietnamese Preschoolers (NISLE-VN)" with 4 core pillars, specific operational procedures, and implementation conditions suitable for tropical climate, biodiversity, and Vietnamese cultural characteristics. Policy recommendations focus on implementing the NISLE-VN model as a national pilot program, establishing standards and specialized teacher training programs, creating support networks and financial funds for model replication.
Teachers have adopted lesson study to enhance learning outcomes and promote continuous professional development in one of the divisions in the province of Albay, Philippines. However, despite its implementation, there is a lack of empirical data describing teachers' experiences in lesson study for improving the approach. Thus, the current inquiry determines teachers' significant experiences, attitudes, and perceived competence toward lesson study. A mixed-methods approach was employed on the thirty-four teacher respondents, and the data were obtained through surveys and focus group discussions. Qualitative data were analyzed thematically, while quantitative data were calculated and interpreted using descriptive statistics. Results indicate that higher participation among female teachers than male teachers was observed, with most participants having at least a Bachelor's degree and three or more years of teaching experience. Teachers in the lesson study reported significant experiences, including (1) impacts on teaching practices, (2) collaboration and professional development, and (3) challenges and reflections in the lesson study process. Meanwhile, respondents' attitudes prioritize teacher-student interaction over social expectations and recognition from superiors. Additionally, data revealed high perceived competence in reflection on learning outcomes, followed by subject knowledge, instructional skills, and teaching strategies. Lastly, this current scholarly work provides essential insights that help develop a comprehensive program and policy framework for effectively implementing lesson study in the locality.
Utilizing technology in science classes can be crucial to actively implementing the secondary school curriculum. These days, a substantial portion of Bangladesh's secondary science education is conducted through the use of digital content combined with technology and the internet. Students' attitudes, motivations, and participation in science classes in secondary schools are significantly transformed by the use of digital content. The purpose of this study was to determine what difficulties arise when using digital content in secondary science classrooms. Survey research design was followed to conduct the study. To collect data for this research, a total of 180 science teachers of secondary school were selected as a sample. Data was gathered through survey questionnaires. The quantitative data that were gathered through questionnaire were subjected to analysis using SPSS and MS Excel. The results of the study showed that secondary school science teachers employ digital content and technologies in their science instruction, but that their use is still subpar due to a lack of infrastructure and stakeholder perception. However, most schools still do not use a lot of technology in their science classrooms. Due to time constraints, a lack of experience integrating technology into their teaching, stringent policies from the school administration, issues with electricity, and other factors, the majority of teachers are not interested in utilizing technology in the classroom. Nevertheless, time is required to get past these challenges and influence teachers' and students' behavior in order to successfully integrate digital content into science classrooms in Bangladesh's secondary education system.
Public school teachers have low research competencies, which contributes to poor action research production. Furthermore, few studies have been conducted to improve the action research competencies of public school teachers in the Philippines. As a result, this study improved the action research competencies of public school teachers through online research training, including research templates, coaching, and mentoring sessions. A practical action research method was used, with sixty-four public school teachers freely participating in and completing a five-day training program. Action research competencies were assessed before and after training using a validated questionnaire developed by field specialists, and semi-structured interviews were performed to elicit feedback. Statistical analyses such as median, interquartile range, Wilcoxon signed-rank test, and rank biserial were performed using Jamovi (v 2.4.14), while interview transcripts were analyzed thematically. The findings revealed that participants' action research competencies improved, as evidenced by a statistical difference between before and after participating in the online research training. However, suggestions were made, including extra writing time for peer review exercises, face-to-face training with more examples of each section of research articles, and a longer proposal presentation period. As a result, twelve action research proposals were presented to their supervisors for feedback. The study was conducted in one location and focused solely on public school teachers. Therefore, DepEd authorities may continue to improve public school teachers' action research competencies through online or in-person research training to generate more action research addressing educational problems in the classroom.
Shadow education is highly prevalent in Hong Kong, driven by parents’ and students’ desire to succeed in public examinations. However, the quality of these supplementary lessons, which exist in various forms, has often been questioned by educators, parents, and students alike. The methods for enhancing the quality of shadow education have become a widely discussed topic among scholars and educators. This study involved 10 local tutorial centers that integrated Artificial Intelligence (AI) into their English lessons. Additionally, 24 participants, including center owners, tutorial center tutors, and students, were invited to share their perspectives on AI in shadow education through interviews. The results indicated that AI could offer students a ‘second opinion,’ but its responses often lacked clarity. As this is an experimental study, further research is needed on this topic, particularly regarding practical methods for integrating AI into shadow education settings.
This meta-analysis investigates the impact of innovative learning models—such as problem-based learning, blended learning, and metaverse-based instruction—on students’ critical thinking skills in mathematics and statistics education. Based on data from 19 studies, the analysis revealed a large overall effect (Hedges’ g = 1.03) in favor of innovative methods compared to conventional approaches. Substantial heterogeneity (I² = 91.37%) indicates potential moderating factors influencing the outcomes. Results from publication bias analyses—including funnel plots, Egger’s test, Trim and Fill, and Rosenthal’s Fail-Safe N (N = 1559) showed no significant bias, supporting the validity of the findings. These results underscore the transformative potential of innovative teaching practices in mathematics and statistics classrooms. However, the limited representation of statistical critical thinking studies suggests a need for further research across diverse contexts and long-term implementations. Overall, the findings highlight the importance of adopting student-centered learning strategies to meet the demands of 21st-century education.
As large language models (LLMs), such as ChatGPT, gain traction in higher education, pressing questions emerge regarding their pedagogical utility, ethical implications, and adoption drivers. This systematic review synthesises 29 empirical studies examining student adoption of LLMs through established models such as the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). Adopting a theory-informed, mixed deductive–inductive methodology, the review integrates thematic analysis with synthesis of reported beta coefficients to assess conceptual patterns and theoretical limitations. Findings reaffirm Perceived Usefulness and Performance Expectancy as dominant predictors; however, traditional models exhibit a utilitarian bias, underrepresenting constructs vital to educational contexts, such as ethical ambiguity, pedagogical misalignment, and institutional trust. Facilitating Conditions were notably context-dependent, often shaped by these broader socio-ethical dimensions. Importantly, there was no consistent alignment between a construct’s theoretical prominence and empirical predictive power. To address these gaps, the review proposes the Generative Adoption Model in Education (GAME), which centres trust calibration, ethical ambiguity, and pedagogical fit as key mediators of adoption. GAME encourages a shift from performance-based models toward frameworks that better capture the socio-institutional dynamics underpinning student engagement with generative AI.
This systematic review analyzes research on the application of Large Language Models (LLMs) to enhance the quality of learner support in the context of university autonomy. The study aims to evaluate the current applications of LLMs in providing personalized and adaptive learning paths, identify ethical challenges, and analyze the role of prompt engineering and human-in-the-loop supervision. The research method involves a systematic analysis of scientific works published up to mid-2024. The findings indicate that LLMs significantly enhance personalized feedback and adaptive tutoring, thereby promoting self-regulated learning and student engagement. However, challenges related to feedback accuracy and ethical issues persist, requiring robust governance frameworks. The conclusion emphasizes that effective LLM integration requires combining technological power with pedagogical expertise and human oversight to optimize the educational experience and successfully support autonomous learners.
The research aims to examine the effectiveness of learner-centred strategies (LCS) in the teaching of natural sciences in grade 5 classrooms in Timor-Leste, where the teaching-learning process is still characterized by teacher-centred learning (TCL), despite the curricular reforms. The qualitative descriptive design was employed, where the data were collected using semi-structured interviews, observation in classrooms, and analysis of documents by five science teachers in three schools in Baucau. The results indicate that inquiry-based learning theories and constructivist theories have been adopted by teachers who are increasingly adopting LCS strategies, including questioning, group work, problem solving, and guided demonstration. These plans have increased student engagement and participation, but the implementation process is limited due to insufficient resources, lack of ICT integration, and structural restrictions, including inappropriate classroom infrastructure and lack of access to science-related materials. Even though there was a positive attitude of teachers toward LCS, the lack of systematic assessment tools hampered the evidence of long-term learning outcomes. The study concludes that to ensure that Timor-Leste students develop critical, creative, and scientific skills in the 21st century, science education must be supported more effectively by institutions, teachers, and resources.
The adoption of task-based language teaching (TBLT) has gained prominence recently, especially in teaching English as a foreign language (EFL) writing to teenagers. While much research centered on teachers’ attitudes, perceptions, and implementation, learners’ voices seem unheard in the literature. Therefore, this study aimed to investigate teenagers’ experiences with TBLT in their English language acquisition journey, specifically focusing on their perceived advantages and challenges on this approach. Through qualitative interviews with a select group of six teenagers, this study explored their perceptions, feelings, and challenges faced during TBLT sessions. Participant responses were analyzed thematically and informed by constructivism, sociocultural theory, self-determination theory, and flow theory theoretical frameworks. The results revealed several advantages of TBLT, including an enhancement in writing affection, the appropriateness of the teaching method, and the enrichment in writing outcomes in terms of vocabulary, content, organization, and grammar. However, challenges were also identified, including the unfamiliarity with the TBLT lesson process, content knowledge deficiencies, vocabulary constraints, mother tongue interferences, and time restrictions. These findings were discussed in light of the theoretical underpinnings, offering a deeper understanding of the learner experience.
The possibilities for integrating generative artificial intelligence (AI) and large language models (LLMs) into higher education may revolutionise approaches to pedagogical practices and curriculum design, while LLMs could be transformative in how students approach their learning. This conversation with ChatGPT, and associated critical evaluation, provides an insight into the capabilities and limitations of LLMs and informs on the possibilities for incorporating AI into bioscience education, teaching modalities, assessment and feedback practices and curriculum design, with a particular focus on bioscience education. The conversation highlights how LLMs can facilitate personalized feedback, tutoring, and concise explanations of scientific terms, enhancing student comprehension, self-directed learning, and critical thinking. However, there are concerns regarding the risks of LLMs, such as plagiarism and breaches of academic integrity, algorithmic bias and limitations in contextual understanding. Despite these limitations, AI offers opportunities for enriching undergraduate bioscience curricula by integrating innovative teaching strategies and assessment modalities aligned with subject benchmark statements. Future research directions include exploring ethical implications, equitable access and digital literacy training in higher education settings. Overall, the integration of LLMs in bioscience education offers significant potential for innovative pedagogical approaches and transformative learning experiences.
The integration of Artificial Intelligence (AI) in education holds immense potential to enhance teaching and learning. However, its effective adoption depends on teachers' readiness, which is influenced by factors such as demographic characteristics, AI familiarity, self-efficacy, perceived benefits, challenges, and institutional support. This study assesses the AI readiness of selected teachers in the Northern Region of Ghana using a quantitative research approach. A structured survey was administered to 300 teachers across various educational levels and subject specializations. Findings reveal a balanced gender representation (51.3% female, 48.7% male) and diverse teaching experience, with 36.7% having 1–5 years of experience. While STEM teachers form the largest group (47.7%), Senior High School teachers constitute the majority (39.3%). AI familiarity varies, with 37% reporting high or very high familiarity, whereas 39.6% have low or very low familiarity. Statistical analysis indicates no significant relationship between AI familiarity and teaching experience (p = .096) or gender (p = .506). Teachers demonstrate moderate self-efficacy in AI use, with confidence levels averaging between 2.89 and 2.97 on a 5-point scale. Perceived benefits include workload reduction (M = 3.00) and personalized learning (M = 2.87), while key challenges encompass inadequate training (M = 3.08), limited infrastructure (M = 3.00), and ethical concerns (M = 2.92). Institutional support is moderate, with school encouragement (M = 3.07) ranking highest. To enhance AI readiness, the study recommends AI-focused professional development, investment in infrastructure, and dedicated technical support. Strengthening institutional policies, addressing ethical concerns, and fostering AI awareness through engagement initiatives will be critical for successful integration. AI adoption can be effectively leveraged to transform education in Ghana when these gaps are addressed.
When the revised and updated 2018 and 2024 science curricula are examined, it is seen that the integration of engineering, technology and mathematics disciplines into the teaching of science subjects is supported. The integration of these four disciplines is defined by the science-technology-engineering-mathematics (STEM or STEM) approach. As this approach has gained a foothold in schools, STEM education has become a topic of increasing focus. In order to provide STEM education in schools successfully, teachers' level of integration of STEM disciplines and their self-efficacy in this regard are important factors. In this sense, the aim of this study is to determine science teachers' views on their level of integrating STEM disciplines into science courses and their self-efficacy in this regard. The study group of research consists of 10 science teachers working in public schools in a provincial center located in the Eastern Anatolia region in the spring semester of 2022-2023. The study was designed in accordance with qualitative research methodology. Semi-structured interview technique was used as a data collection tool. In the interview, the participants were asked 10 open-ended questions developed by the researcher with expert opinion and audio recordings were taken during the interview. The voice recordings were analyzed and the data were analyzed, tables were created, categories were determined in the tables and teachers' opinions were expressed with codes. According to the findings, it was determined that science teachers correctly defined STEM, were able to associate STEM education with other disciplines, expressed their thoughts on integrating STEM disciplines into the science course, and expressed the problems they encountered or could encounter in STEM applications. Teachers mostly expressed the problems they encountered as insufficient materials, infrastructure problems, and insufficient teacher knowledge.
Teacher happiness is a critical component of effective teaching. When teachers are happy, it often translates into more effective and engaging teaching. This exploratory sequential research primarily aimed to explore the characteristics and sources of happiness of public-school teachers in the new normal and eventually develop a public-school teachers' happiness scale in the new normal. In gathering qualitative data, ten public school teachers underwent in-depth interviews while 302 public school teachers responded the initial survey questionnaire to determine the factor structures that significantly characterize the happiness of public-school teachers in the new normal through exploratory factor analysis utilizing the VARIMAX orthogonal rotation method with Kaiser normalization. Results revealed four significant themes generating 60 items for the preliminary questionnaire characterizing the happiness of public-school teachers in the new normal. After dimension reduction, the 60 items are distributed into six constructs which are all valid and reliable. The public-school teachers' happiness scale in the new normal captures the factor structures and sources of happiness of teachers in the new normal. The happiness scale in the new normal may help DepEd officials, school heads, teachers, and the community partners identify factors that enhance teacher well-being, leading to improved morale, job satisfaction, and overall school performance.
