The study highlights that elderly residents' positive evaluations of service functionality, convenience, and safety, along with multi-level support from family, community, and society, are crucial factors in enhancing the demand for smart elderly care services. A total of 630 participants joined in this study. Structural equation modelling (SEM) was used to examine research hypotheses. Attitudes, subjective norm and perceived behavioral control have a positive effect on Behavioral actual to use smart elderly care services directly and indirectly towards behavioral intention. Smart elderly care services can improve quality of life and foster social connections, providing emotional support and reducing feelings of isolation. Digital literacy is crucial; those with higher skills tend to have more positive attitudes, leading to greater intention to use these services. Perceived behavioral intention, which reflects seniors' beliefs about engaging with technology, is critical. Social support further motivates seniors to adopt these technologies. Understanding these dynamics is essential for stakeholders to promote smart elderly care services, ultimately enhancing the quality of life for older adults.
This study investigates the relationships among AI utilization, professional development, and teacher performance in learning contexts. A total of 100 teachers from preschool to high school in the Greater Blitar region, Indonesia, participated. Data were collected using a cross-sectional survey and analyzed via PLS-SEM to examine direct and indirect relationships. Quantitative results served as the primary source, followed by qualitative interviews to provide deeper contextual insights and interpret the quantitative findings. Results show that AI utilization is positively associated with professional development, which is also positively associated with teacher performance. Furthermore, AI utilization demonstrates an indirect relationship with teacher performance through professional development, while no significant direct relationship between AI utilization and teacher performance was identified. Findings highlight the potential mediating role of professional development in explaining how AI utilization may be associated with effective teaching practices.
Mathematical skills acquired during early childhood are widely recognized as strong predictors of later academic achievement. However, studies systematically mapping the global knowledge structure of research on preschool mathematical development remain limited. This study examined 143 academic publications from the Web of Science (WoS) database between 2006 and 2025 using bibliometric analysis, aiming to provide a comprehensive, integrated structural map of the field. Publication trends, author, country, and institution distributions, citation patterns, and keyword co-occurrence clusters were analyzed using VOSviewer 1.6.20. Findings revealed a significant increase in publications after 2015, with the United States, Germany, and Belgium as leading countries, and KU Leuven as the most productive institution. A longitudinal study on executive functions received the highest number of citations. Keyword analysis demonstrated that executive functions and cognitive processes constitute the dominant research focus; however, notable gaps exist in digital technology integration, cross-cultural perspectives, and play-based learning approaches.
Artificial intelligence is quickly altering education, especially in mathematics instruction, by providing instructors with effective creatures that can develop how they teach and increase student engagement. The purpose of this study was to assess how basic education mathematics instructors integrate AI into mathematics instruction, focusing on their practical use, perceptions, and the challenges they face. The research used a mixed-methods design, using a highly designed 18-item questionnaire with a 5-point Likert scale. The questionnaire was distributed to 164 mathematics teachers across five governorates, while interviews were conducted with 12 instructors to identify the main challenges they face when integrating artificial intelligence tools into mathematics instruction.Top of Form The study found that instructors possess a moderate level of AI knowledge but strongly recommend integrating AI to achieve key educational outcomes, notably boosting student motivation, enhancing understanding of mathematical concepts, and promoting higher-order thinking skills. Consequently, the main challenges to integration were identified as instructors’ insufficient knowledge and experience, limited resources and inadequate infrastructure, and the additional time and effort required for lesson planning. Key recommendations include the immediate implementation of comprehensive capacity-building programs for instructors and the systematic enhancement of schools’ technological infrastructure. These measures are essential to ensure the effective and sustainable integration of AI into mathematics instruction. Thus, AI empowers instructors to streamline lesson planning and assessment while providing students with personalized feedback and interactive practice opportunities.
Biotechnology literacy is essential for enhancing students’ ability to comprehend and critically assess biotechnological applications. However, standardized biotechnology literacy instruments tailored to the context of science students in Indonesia remain limited. This study aims to test the validity and reliability of a biotechnology literacy instrument using a SEM approach with CFA. A total of 340 science students participated in this study. The instrument tested consisted of 59 items based on the constructs of knowledge, perception, and attitude. The analysis results indicated a reasonably good model fit (RMSEA = 0.071; RMR = 0.028; CFI = 0.903; GFI = 0.909), adequate construct validity (factor loadings = 0.163-0.837), and acceptable internal reliability (CR = 0.62-0.68). Furthermore, the three constructs were significantly correlated, although the correlation coefficients did not all exceed the threshold. These findings confirm that the tested instrument is sufficiently valid and reliable for measuring biotechnology literacy among science students in Indonesia; however, further refinement is needed to improve the quality of measurement.
This study investigated the perceptions of readiness among 46 fifth-year pre-service teachers enrolled in the education department of a private university. Using purposive sampling, participants were selected to ensure variation in teaching practice experiences and subject specializations. The study aimed to understand the extent to which these future teachers feel prepared for real classroom teaching. A qualitative phenomenological approach was employed, and data were collected through semi-structured interviews. Thematic analysis following Braun and Clarke’s six-phase framework was applied to analyze the data. Six major themes were identified: (1) perceived preparedness anxiety, (2) theory–practice disconnect, (3) influence of mentorship, (4) curriculum training gaps, (5) program improvement recommendations, and (6) impact of preparedness on motivation and retention. The findings revealed a noticeable gap between theoretical knowledge and authentic classroom application, particularly in classroom management, inclusive pedagogy, and technology integration. Theoretically, the study proposes a developmental continuum of teacher readiness linking experiential learning and professional identity formation. Practically, the findings highlight the need for practice-embedded curricula, structured mentorship systems, and strengthened school–university partnerships to enhance readiness and teacher retention.
In this study, the cognitive-linguistic features of teacher roles and word patterns were explored through imaginary mathematical dialogues constructed by preservice mathematics teachers. First, preservice mathematics teachers were given mathematical communication training. This training is a dialogic training on how to conduct mathematical dialogues from beginning to end by introducing mathematical dialogues to pre-service teachers. After 14-week communication lessons, preservice mathematics teachers were asked to write an imaginary mathematical dialogue. The preservice mathematics teachers wrote imaginary dialogues according to four discourse types (Teacher, Teacher-Students, Teacher-Student, Student-Student). The data of the study were analysed by content analysis. Content analysis was carried out in qualitative analysis software. It was concluded that pre-service teachers were able to create quality and different types of mathematical dialogues by using discourse types. Mathematical dialogues were found to be affected by the linguistic features used by the pre-service teachers. For this reason, it was revealed that the word patterns used by the teacher are important. Strong relationships were found between the teacher’s roles and the word patterns used in imaginary mathematical dialogues. It was also found that some of the word patterns were specific to the discourse type.
This study aims to identify the degree of self-efficacy in teaching science at the elementary level among student teachers in the Higher Diploma in Science at Najran University. The study was conducted using the mixed method (quantitative/qualitative). The Science Teaching Efficacy Belief Instrument scale was applied to all student teachers enrolled in the science diploma program for the elementary stage (15 teachers) in 2022. Also, interviews ten teachers were conducted. The results revealed that the degree of personal science teaching efficacy among the study sample was high. Also, there was no statistically significant effect of specialization, educational stage, and teaching experience on self-efficacy beliefs in teaching science. In addition, the interviews showed that most of the teachers in the study sample believed in their ability to teach science at the elementary level.
This study aims to examine how the concept of slope is structured in middle school and secondary school mathematics textbooks on the basis of the praxeological approach within the framework of the Anthropological Theory of the Didactic (ATD). Designed as a qualitative study, ecological and praxeological analyses were conducted on nationally used mathematics textbooks through the method of document analysis. As a result of the analyses, three fundamental mathematical organizations related to the concept of slope and a total of 20 task types within these organizations were identified. These organizations were classified as determining and interpreting slope, constructing the equation of a line using slope, and interpreting slope depending on the position of the line. The findings indicate that as grade levels increase, there is a dominant praxeological progression in the teaching of slope from concrete and visually based tasks toward more abstract and analytical approaches. The results provide didactic implications regarding how the praxeological structures presented in textbooks shape students’ access to the concept of slope and reveal important consequences for textbook design and instructional decision-making in mathematics education.
This study aimed to develop an M6 learning model that meets the criteria of practicality and effectiveness in improving the mathematical critical thinking skills of Grade VIII students. This research employs a Research and Development (R&D) design. The product developed in this study takes the form of an M6 learning model book along with its supporting tools. The quality of the M6 learning model was assessed using the instruments developed for this purpose. The study focused specifically on whether the M6 learning model met the predetermined practicality and effectiveness indicators for improving students’ mathematical critical thinking skills. The average implementation scores of the learning model in Trial I and Trial II were 3.12 and 3.54, respectively, indicating that both fell within the practical category. The average student activity scores from Trial I and Trial II were 2.65 and 3.41, respectively, indicating that students were in the active category. The average student response scores in Trial I and Trial II were 2.54 and 2.73, respectively, indicating a positive class response.
This manuscript develops a conceptual instructional design framework for teaching Linear Programming to economics students under the ASEAN University Network - Quality Assurance (AUN-QA) approach. The study is not an empirical classroom intervention and does not claim to statistically demonstrate the effectiveness of the proposed measures. Instead, it adopts a design-oriented conceptual approach based on analysis of AUN-QA requirements, programme learning outcomes, course learning outcomes, the Linear Programming course structure, relevant literature on constructive alignment and active learning, and reflective teaching experience. The analytical procedure consisted of identifying recurrent pedagogical challenges in Linear Programming instruction, mapping these challenges to course learning outcomes, selecting theoretically justified instructional strategies, and specifying assessment evidence that can support outcome monitoring. The resulting framework proposes three mutually connected measures: Kolb-based experiential learning for modelling economic optimisation problems, visualisation-supported instruction for the simplex algorithm, and project-oriented assignments for authentic economic applications. The main contribution of the manuscript is an explicit alignment matrix linking learning difficulties, course learning outcomes, teaching and learning activities, and assessment evidence. The framework is intended to guide instructors, curriculum designers, and quality assurance practitioners in designing outcome-based Linear Programming instruction. Future empirical studies should validate the framework through classroom data, rubric-based assessment, pre-test and post-test designs, student feedback, and analysis of learner differences.
This study aimed to develop and empirically validate a language learning evaluation model grounded in indigenous cultural philosophy. The research addressed the limited availability of culturally grounded assessment frameworks by operationalizing the Lampung philosophy of Piil Pesenggiri into measurable constructs representing the Learning Process and Learning Outcomes. A non-experimental cross-sectional design was employed with data collected from 207 eleventh-grade students in North Lampung, Indonesia. The proposed model was tested using Structural Equation Modeling (SEM). The results indicated that the model demonstrated acceptable fit with the empirical data (p = 0.052; RMSEA = 0.072; CFI = 0.98; GFI = 0.95). The structural analysis also revealed a strong relationship between the culturally grounded learning process and learning outcomes (β = 0.91, p < 0.001), with the model explaining 83% of the variance in learning outcomes. These findings indicate that indigenous cultural values can be systematically translated into measurable indicators within a language learning evaluation framework. The study provides an empirical example of how culturally grounded assessment models can complement conventional evaluation approaches while reflecting the socio-cultural dimensions of language learning.
Laboratory activities are essential for developing students’ science process skills, yet many rural schools face limitations in conducting regular chemistry experiments due to inadequate laboratory resources. This study examined the effectiveness of structured inquiry engagement delivered through an Android-based, smartphone-delivered non-immersive virtual reality chemistry laboratory (VR-CL) in enhancing rural secondary students’ science process skills. The intervention was grounded in structured inquiry learning principles and supported by multimedia and flexible learning design. A quasi-experimental pre-test–post-test design with non-equivalent groups was conducted with 129 students (experimental n = 64; control n = 65) over eight weeks. Science process skills were measured using a validated instrument, and post-test differences were analysed using two-way ANCOVA with pre-test scores as the covariate. Results showed that students in the structured inquiry-based VR-CL environment demonstrated significantly greater improvement in science process skills than those receiving conventional instruction. The findings suggest that the observed learning gains are associated with the structured inquiry engagement embedded within the VR-CL learning environment, rather than the use of virtual technology alone. The study highlights the potential of integrating structured inquiry pedagogies with accessible non-immersive virtual environments to support chemistry learning in resource-limited rural contexts.
This study addresses the need for a reliable instrument to measure student persistence in mathematics education by developing and validating the Mathematics Multidimensional Persistence Scale (MMPS). The MMPS was adapted from the existing Multidimensional Persistence Scale through translation and expert review, resulting in a 22-item scale that includes newly developed items to better capture persistence in the context of mathematics learning. The scale was administered to 438 high school students from three schools in Manggarai, East Nusa Tenggara, Indonesia. Exploratory Factor Analysis revealed four factors: Strategic Persistence in Mathematics, Math Avoidance Due to Difficulty, Effortful Persistence Despite Math Anxiety, and Inappropriate Persistence. Confirmatory Factor Analysis supported a good model fit (CFI = 0.924, TLI = 0.903, RMSEA = 0.047), indicating the scale’s validity. These results provide a solid foundation for evaluating mathematics persistence and offer educators practical tools to support student engagement. Future research should examine the long-term impact of MMPS-informed interventions on student outcomes.
With the emergence of generative artificial intelligence (GenAI) in the field of education, the ability of the traditional Technological Pedagogical Content Knowledge (TPACK) framework to explain teacher competencies in the AI era has come under study. In this conceptual study, a new model aimed at explaining teacher competencies in the AI era has been proposed. The proposed Extended GenAI-TPACK framework draws its fundamental theoretical foundation from Demir’s model, which positions technology and theoretical framework as two inseparable facets in technology integration programs; it adapts this model to the AI era by transforming it into a tripartite core (Technology + Theoretical Framework + AI Agency). The proposed framework includes five new knowledge domains surrounding this tripartite core (Critical Evaluation, Prompt Engineering, Human-AI Role Sharing, Ethics and Social Judgment, Student-AI Interaction Management) and a Phronesis axis that anchors the entire system within the classroom context. Additionally, Hughes’ three-level technology integration model has been reframed through the Co-Agency axis to create a six-cell application matrix. The framework was developed to address the structural limitations of classical TPACK in the GenAI context and offers educational technology literature a conceptual tool that is both theoretical and operationally applicable.
This study investigates how teachers assess the pedagogical benefit of CloudClassRoom (CCR) in integrating STEM learning. The study is based on affordance theory and focuses on teachers’ perceptions of how CCR assists lesson design, collaboration, and assessment. Data were obtained from 76 teachers who took part in a professional development program based on the DECODER model, which emphasizes demonstration, co-design, and classroom application. According to thematic analysis, teachers recognized numerous important benefits of web-based tools, such as chances for interactive replies, instant feedback, flexible course design, and student participation. However, factors such as classroom infrastructure, digital familiarity, and platform usability influenced their experiences. The findings indicate that teachers’ professional backgrounds and training experiences have a substantial impact on how they interpret and apply CCR. The study advances our understanding of how teachers adapt web-based technologies to their contexts and emphasizes the necessity of professional development in facilitating meaningful STEM integration.
Critical mathematics education (CME) emerged in Western contexts that assume students will voice dissent and openly challenge mathematics as political. This qualitative phase 1 study examines how Thai secondary mathematics educators understand and enact CME in a hierarchical, examination-driven setting where those assumptions do not necessarily hold. Through semistructured interviews with five scholars and seven teachers, alongside observations of project-based instruction, thematic analysis produced three constructs. Depoliticization is the institutional process that removes political content from critical frameworks while retaining the language of critical thinking. Suppressed silence, inferred from teacher accounts and classroom observations rather than direct student data, describes critical awareness that students may hold but have learned not to voice. Gentle criticality describes critiques expressed through quiet questioning and community-oriented inquiry rather than open confrontation. As provisional constructs, they offer a vocabulary for theorizing CME in collectivist contexts not fully addressed by Western frameworks, grounding subsequent model development.
This study aimed to explore the relationships between factors that affect learning and teaching in STEM education among Thai senior high school students. The study focused on four main factors: teacher learning design factor, student factor, teacher factor, and learning materials factor. A quantitative research design was used. Data were collected from 867 students in grade 10 to grade 12 from schools in Nakhon Sawan, Uthai Thani, and Chai Nat provinces during the 2024 academic year. The research instrument was a questionnaire with 57 items on a 5-point Likert scale. Statistical analyses included the Kolmogorov-Smirnov test, Shapiro-Wilk test, Kruskal-Wallis H test, pairwise comparisons analysis, and one-way ANOVA. The findings showed that the student factor, teacher factor, and learning materials factor had significant positive relationships with students’ perceptions of STEM education. Students who were more engaged, had effective teachers, and had access to good learning materials had more positive views of STEM learning. However, the teacher learning design factor did not have a significant impact, which may reflect Thailand’s traditional lecture-based teaching style. The study also found gender differences, especially in the perceptions of LGBTQ+ students compared to male and female students. These results suggest the need for student-centered teaching methods and better learning resources to improve student engagement in STEM education.
Academic staff play a central role in fulfilling the teaching, research, and community service missions of universities, yet their performance may be influenced by institutional conditions. This study examined how the relationships between institutional climate, culture, and perceived institutional size influence academic staff performance in teaching, research, and community service within universities in Cross River State, Nigeria. An ex post facto cross-sectional design was adopted, with data collected from 449 lecturers across three public universities using validated instruments assessing institutional characteristics and job performance. Multivariate analyses of variance were employed to examine differences in performance outcomes across institutional conditions. Results indicated that institutional climate was significantly associated with academic staff performance (Pillai’s trace = 0.691, F (6, 890) = 78.30, p < .001, partial η² = 0.345), with more supportive climates corresponding to higher self-reported teaching, research, and service engagement. Perceived institutional size was also significantly related to performance outcomes (Pillai’s trace = 0.672, F (6, 890) = 75.11, p < .001, partial η² = 0.336), while institutional culture demonstrated the strongest multivariate association (Pillai’s trace = 0.737, F (6, 890) = 86.52, p < .001, partial η² = 0.368), particularly in institutions characterized by collaborative norms. The findings suggest that institutional climate, culture, and size are meaningfully associated with variations in academic staff performance within the Nigerian university context. These findings support the importance of internal organizational conditions in shaping staff engagement, while highlighting the need for cautious interpretation given the cross-sectional and self-reported nature of the data.
This study aims to develop a prototype of the socio-cognitive conflict-integrated challenge-based learning model (SCC-ICBLM) to improve high school students’ scientific argumentation skills and scientific literacy. The research design used an early-stage research and development approach (analysis, design, and development). Data were collected through curriculum document analysis, student and teacher questionnaires, and expert validation. The student questionnaire measured perceptions of learning, barriers and needs, conceptual understanding, scientific argumentation skills, scientific literacy, learning styles, and collaborative participation, while the teacher questionnaire covered learning contexts and learning tasks. The analysis showed that although students’ perceptions of chemistry learning were high, their scientific argumentation skills and scientific literacy remained at a moderate level. In contrast, collaborative participation and readiness for learning contexts were high. Expert validation indicated that the SCC-ICBLM prototype was theoretically and pedagogically valid. This study contributes to pedagogical research by conceptualizing socio-cognitive conflict as a core, intentional mechanism in challenge-based learning, rather than as a peripheral discussion strategy. These findings provide an empirical basis for further research to test the model’s effectiveness in real classroom contexts.
