Higher education institutions have focused their efforts on promoting research seedbeds as a strategy for formative research. In this regard, the impact of such a strategy remains unknown due to the lack of models that enable its evaluation. Therefore, this study aimed to design an evaluation model for the academic productivity of research seedbeds based on the available evidence in the literature. To achieve this, a systematic review was conducted following the PRISMA model, analyzing 53 documents including articles, book chapters, and conference proceedings from the SCOPUS, ProQuest, Jstor, Scielo, and ScienceDirect databases. The results identified indicators that allowed for the design of a model based on six constructs: research training, institutional capabilities, bibliographic production, innovation and development, social appropriation of knowledge, and human resource training. It was concluded that the indicators evaluating research seedbeds seek greater scientific development involving students and improving the quality of research products, which directly impacts the institutional research mission.

This research aimed to explore the influence of a robotic program using the robot kit "RoboBuilder RQ+110" on students' attitudes toward effective communication. The study used a quantitative research design and involved 475 grade 4 (10 years old) students from Malaysia's Selangor and Malacca states. A quasi-experimental research (pre-test & post-test) approach with control and experimental groups was adopted, and the data were analyzed with inferential statistical test and repeated measures analysis of variance (ANOVA) using SPSS 25 software at 0.05 significance level. Questionnaires were administered to collect data from the experimental and control groups. The results showed statistically significant changes (α ≤ .05) in attitudes toward effective communication for the experimental group that received a robotics program compared with the control group. The study results suggest that innovative technological tools or programs such as robotics programs are recommended as innovative science, technology, engineering, and mathematics (STEM) program rooted in constructivism to improve students' attitudes toward effective communication.

In the early stages of adopting online learning, both learners and teachers displayed resistance, but the COVID-19 pandemic has forced a widespread shift to digital learning. To facilitate this transition, there is a growing focus on highlighting the effectiveness of online learning, which directly impacts learning outcomes. This study investigates online learning effectiveness through an integrated framework that considers online assessment practices and online course design as independent variables, with online learning support as a moderating variable. Understanding the effectiveness of online learning is crucial as hybrid learning becomes the "new norm" in education, combining online and offline methods for teaching the digital generation. Using a quantitative research design involving 232 students at Universiti Kebangsaan Malaysia, the study found that online assessment practices and course design significantly influence students perceived learning outcomes in an online learning environment. Additionally, online learning support positively moderates this relationship. These findings offer a comprehensive perspective on how online assessment practices, course design, and support systems contribute to the quality of higher education in Malaysia amidst evolving educational practices.

Since psychological satisfaction is influenced by the interaction between individuals and their environment, it is necessary to create a cooperative climate at the organizational level and strengthen collective innovativeness at the individual level to improve teachers' job satisfaction. Therefore, the study investigated whether collective innovativeness can be mediated by the school climate to enhance teacher job satisfaction. This study extensively examined survey data with a sample of 3,976 teachers in Shanghai through Structural Equation Modeling, obtained from Teaching and Learning International Survey (TALIS). The findings revealed that teachers' collective innovativeness served as a significant mediator between school climate and job satisfaction. Furthermore, higher levels of collective innovativeness among teachers amplified the influence of school climate on their job satisfaction. These findings show that schools should strive to foster a collaborative school climate and provide support for teachers in implementing innovative and collaborative teaching activities with the aim of enhancing their job satisfaction. Above all, efforts are needed to support teachers' active and cooperative practice capabilities in building teacher-student relationships.

One of the ways to enhance and improve the quality of learning delivery is through the use of technology, particularly the Internet, which facilitates faster and easier access to information. This research aims to explore the degree to which factors such as digital literacy, metacognitive awareness, meaningful learning, habits of using smartphones, and personal learning competence are related to one another. Both the relationship between metacognitive awareness and personal learning competence, as well as the relationship between smartphone habits and personal learning competence, are moderated by a moderating variable known as the fear of missing out. Fear of missing out is a moderating variable. Structural equation modeling, specifically partial least squares, was employed to analyze data from 597 engineering students. SmartPLS version 4 was the tool used for this analysis. The study found that the moderating variable, fear of missing out, significantly impacts metacognitive awareness, learning personal competence, and smartphone habits, making it a crucial factor to investigate. This result is significant because it is a variable that influences the learning that students go through for their education and because it is an extremely important thing to investigate.

School dropout intention and reduced academic achievement are two crucial indicators of school dropout risk. Past studies have shown that school performance plays a mediating role in the models explaining dropout intentions. School burnout and test anxiety have been identified as predictors of both academic performance and school dropout. However, their combined effects on the intention to leave school have not yet been investigated. We aimed to address this gap by exploring the predictors of school dropout intention in a sample of 205 French secondary school students. Structural equation modelling analyses have revealed the specific facets of school burnout (devaluation) and test anxiety (cognitive interference) that explained the school dropout intentions and academic performance. Grade Point Average (GPA) was a mediator of the effects of these variables on the intention to drop out of school. The findings highlight the need to acknowledge assessments as a school stress factor that could contribute to health problems and intentions to drop out of school.

Successfully solving reality-based tasks requires both mathematical and text comprehension skills. Previous research has shown that mathematical tasks requiring language proficiency have lower solution rates than those that do not, indicating increased difficulty through textual input. Therefore, it is plausible to assume that a lack of text comprehension skills leads to performance problems. Given that different sociodemographic characteristics and cognitive factors can influence task performance, this study aims to determine whether text comprehension mediates the relationship between these factors and competence in solving reality-based tasks. Additionally, it examines the impact of systematic linguistic variation in texts. Using an experimental design, 428 students completed three reality-based tasks (word count: M = 212.4, SD = 19.7) with different linguistic complexities as part of a paper-pencil test. First, students answered questions about the situation-related text comprehension of each text, followed by a mathematical question to measure their competence in solving reality-based tasks. The results indicate that: a) Tasks with texts of lower linguistic complexity have a significantly higher solution rate for both text comprehension (d = 0.189) and mathematical tasks (d = 0.119). b) Cognitive factors are significant predictors of mathematical solutions. c) Text comprehension mediates the relationship between the impact of students’ cultural resources and cognitive factors and their competence to solve reality-based tasks. These findings highlight the importance of linguistic complexity for mathematical outcomes and underscore the need to reinforce text comprehension practice in mathematical education owing to its mediating role.

Augmented reality offers diverse potential applications for STEM education, enabling students to engage directly with virtual elements in real-time and providing them with immersive, natural experiences. This study conducted a bibliometric analysis of articles on this topic on the Scopus database to determine some quantitative information, such as general information about publications, countries, institutions, authors with the most contributions, and key trends in applying augmented reality technology in STEM education. An analysis of 201 studies published from 2005 to 2023 using Biblioshiny software and VOSviewer reveals that the United States leads in the number of studies conducted on this issue. Kryvyi Rih National University, Ukraine, has the most studies. The authors who contributed the most studies with the most citations on this issue are Lindner, C. and Rienow, A. from Ruhr University Bochum, Germany. Two primary research trends emerge, focusing on how Augmented Reality technology is utilized, particularly in STEM fields like Chemistry, which combines learning forms with other learning support tools and media such as mobile applications. Secondly, integrating augmented reality and virtual reality technologies into STEM programs at the university level, design of games, and virtual tools. This study offers important data for researchers looking to explore future applications of augmented reality technology within STEM education.

This study aimed to optimize critical thinking by empowering reflective and impulsive students' collaboration, communication, and information literacy skills through information literacy-oriented e-books in STEM-integrated problem-based learning (PBL). The research method used was a descriptive explorative approach. The study subjects consisted of five reflective students and five impulsive students. The measurement of cognitive style used the Matching Familiar Figure Test (MFFT) instrument. Collaboration skills were assessed through observation sheets, critical thinking and communication skills were assessed through student worksheets based on problem-solving tasks, and information literacy was assessed through a questionnaire. The study found that reflective students excelled in critical thinking and information literacy, while impulsive students demonstrated superior collaboration skills. As for communication skills, reflective and impulsive students have different advantages for each indicator of communication skills. This study can conclude that implementing information literacy-oriented e-books through STEM-integrated PBL can optimize reflective and impulsive students' critical thinking, collaboration, communication, and information literacy skills. The implication of this study is the importance of integrating 21st century skills holistically in learning practices, especially in the digital era, to prepare the younger generation to face the challenges of the 21st century.

This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.

Sensory integration (SI)-based intervention programs aim to improve the motor performance of children with moderate autism spectrum disorder (MASD), which may contribute to the development of their gross and fine motor skills. This study aimed to explore the effectiveness of a SI-based training program in developing gross and fine motor skills in 70 children with MASD aged 6–9 years (M = 7.11, SD ± 1.19) and selected intentionally from a daycare center in Al-Ahsa in Saudi Arabia. The study used the quasi-experimental approach and followed the experimental design with two groups, which were randomly distributed and examined for equivalence. The study also used the Gross Motor Skills Scale (GMSS), the Fine Motor Skills Scale (FMSS), and the training program based on SI. The study found that the experimental group had significantly higher post-test scores in the GMSS and the FMSS than the control group, with these differences being statistically significant. However, no significant difference was observed between the post-test scores and the follow-up test scores within the experimental group, indicating stability in their performance over time. This indicates the effectiveness of the training program used in developing the targeted skills and the continuation of the training effect after the program’s application period. The study suggests that children should use SI-based training programs to enhance their motor skills.

This article aims to answer the research question: How do 5th grade students experience the use of artificial intelligence (AI) tools to create a comic strip describing the survival struggle between the Myna and the Lesser Kestrel? This study utilized a case-study approach to examine the advantages and challenges experienced by 5th grade students using AI tools to create a comic strip about the Lesser Kestrel's survival struggle. Data were collected through qualitative methods, including student reflections, drawings, and analyses of the comic strips they created. Additionally, a questionnaire was used to assess students' attitudes towards the four components of 21st century skills: Creativity, critical thinking, collaboration, and communication. The study indicates that the development of 21st century skills among students requires a collaborative effort involving both parents and teachers. It is not sufficient to rely solely on technological tools; there must be intermediary processes and support from teachers, who are obliged to adjust their teaching methods. Additionally, a teaching approach that supports the creation of a future citizen with a humanistic outlook and awareness of the complexity of life, is essential. This approach develops students' environmental citizenship, which is also an important 21st century skill. This involves integrating ethical, inclusive, and holistic perspectives to address complex problems, such as the survival struggle between the Lesser Kestrel and Myna.

With the introduction of the new curriculum, primary school Croatian fine arts teachers faced many challenges. The fundamental problem, the lack of school lessons, is highlighted by the challenges of implementing problem and project work and integrating technology into the teaching process. Therefore, it is important to organise activities where pupils use modern tools and media for high-quality educational purposes. The animation was chosen as a fine arts technique that can fulfil these requirements. Qualitative action research was conducted in city Split in the school year 2023/2024. The 5th and 8th grade pupils (125) and their fine arts teachers (3) participated in the research. A total of 75.23% of respondents were positive about the occasional introduction of technology into fine arts classes. After completing the fine arts project, 77.98% of pupils stated that they now have the knowledge and skills to create an animation themselves, while 77% of pupils consider their digital stories to be interesting and original. All three fine arts teachers cite a lack of continuity due to the small number of lessons as a shortcoming. The results point to poor material conditions: overheating of old projectors, low-quality tablets, poor internet connection and lack of power sockets. The research has shown that there are discrepancies between the prescribed theoretical requirements for learning outcomes and the possibilities for their practical realisation. As a result, teachers need to take a keen interest and receive additional training to ensure that the projects designed are in line with the requirements of the curriculum.

The field of engineering education is constantly evolving to meet the challenges of technological and societal advancements. Continuous research should be conducted to identify the potential match between the skills that employers seek and the ones engineering graduates gain at college. The purpose of this study is to identify areas of agreement and disagreement between the faculty and employers regarding the skills and knowledge that engineering students acquire during their undergraduate education. The study uses an explanatory sequential design method by employing a questionnaire that was developed based on the Engineering Competency Model (ECM) by the Employment and Training Administration of the USA Department of Labor and responded to by 125 volunteer engineering faculty. Additionally, interviews were conducted with 2 industry professionals to gain deeper qualitative insights. The study found that while faculty mainly stated that students acquire personal effectiveness, academic, and workplace competencies in college, employers disagreed with these perceptions, particularly regarding interpersonal skills, integrity, professionalism, writing, and communication. Additionally, the study found a significant mismatch between faculty and employer assessments of industry-wide competencies, with employers expressing concerns about graduates' preparedness in areas like design, business, and sustainability. These findings suggest significant updates and cooperation with industry experts in engineering curricula and their implementation.

Children diagnosed with moderate autism spectrum disorder (MASD) exhibit a range of socially unacceptable behaviors, which notably include social withdrawal behavior (SWB); these individuals tend to disengage from various social contexts, consequently impeding their communication and social interaction capabilities. The primary objective of this research was to employ miniatures (diorama) as a methodological approach to construct semi-naturalistic scenarios for children with MASD that authentically represent their quotidian experiences and facilitate interaction, contributing to the alleviation of their SWB. The research sample comprised 21 children with MASD, aged between 6 and 9 years, who were enrolled at the Al-Jabr Institute in Al-Ahsa, Saudi Arabia. A quasi-experimental methodology was adopted to align with the research's inherent characteristics, using a three-group design. The instruments utilized included the Social Withdrawal Behavior Scale (SWBS) alongside a training program devised by the authors. The results showed a significant reduction in SWB among those children to whom the diorama program was applied. Results also indicated the continuation of this effect after the end of the diorama program period for two consecutive months. The outcomes encourage further implementation of the diorama methodology on more extensive samples and across a broader geographic scope within Saudi Arabia, thereby facilitating the generalization of the findings to the entire population of children diagnosed with MASD. Findings also encourage the enhancement of the diorama's role in forthcoming experimental inquiries to ascertain its efficacy in mitigating other socially maladaptive behaviors exhibited by children with MASD.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication and repetitive behaviors. The Picture Exchange Communication System (PECS) has been widely utilized to support communication in children with ASD by using picture cards to convey needs and responses. However, traditional PECS can be limited by its static nature and lack of immediate feedback. Recent technological advances, particularly Augmented Reality (AR), offer new avenues for enhancing these communication strategies. This study explores the integration of AR into PECS and its impact on improving basic communication skills, specifically answering questions and commenting, in children with ASD. The research involved a multiple baseline design with four participants aged 7-12 years, recruited from autism centers in Melaka, Malaysia. Results showed significant improvements in both the frequency and accuracy of responses and relevant commenting skills after the AR-based intervention. Answering skills improved by 83%, and commenting skills increased by 122%, with the average number of relevant comments rising from 3 (SD = 0.89) to 6.67 (SD = 2.25). Statistical analysis (paired t-test) revealed a significant effect (p = 0.00272). Compared to traditional methods, AR-based PECS accelerated the achievement of target communication skills. Future research should focus on larger sample sizes and explore long-term impacts to solidify these promising outcomes.

This research investigated the validity of measurement and causal model of online scam protection behavior (OSPB) among at risk Thai students. The sample comprised 286 high school students from three demonstration schools under the University. Data were analyzed using descriptive statistics, confirmatory factor analysis (CFA), and structural equation modeling (SEM). The factor loadings for all items satisfied the standard criteria with scores ranging from .40 to .80, item-total correlations ranging from .405 to .718, and Cronbach’s alpha coefficients ranging from .773 to .928. The modified model demonstrated a better fit with the empirical data (χ² = 47.62, df = 37, p = .113,  χ²/df = 1.287, RMSEA = .032, SRMR = .028, GFI = .97, CFI = 1.00, NFI = .99). All factors: a) awareness of online risks, b) inhibitory control, c) game-based learning, d) social support, and e) motivation to prevent online scams can predict 81% of OSPB. The motivation to prevent online scams strongly influenced OSPB, with an effect size of .60. Additionally, all factors can predict 88% of the motivation for online scam prevention, suggesting that Protection Motivation Theory (PMT) is a suitable framework for understanding and evaluating Thai students' preventive behaviors in online deception scenarios. This newly developed instrument is highly reliable and can be effectively used by researchers and educators to assess the risk of online fraud victimization among high school students.

This study analyzes trends, collaborations, and research developments on augmented reality (AR) in mathematics education using a bibliometric approach. Data were collected from the Scopus database on July 31, 2024, identifying 542 documents published between 2015 and 2024. After screening, 194 journal articles were selected for analysis. Using VOSviewer, the study produced visualizations related to document types, publication trends, journal sources, research subjects, institutions, countries, keywords, and author collaborations. The results show that 88.7% of the documents are journal articles, indicating that this topic is predominantly published in scholarly journals. Publication trends reveal significant growth since 2016, peaking in 2024, reflecting increasing global interest. Education Sciences and IEEE Access are among the top journal sources. Subject-wise, social sciences and computer science are the main disciplines exploring AR in mathematics education. Chitkara University (India) and Johannes Kepler University Linz (Austria) are leading institutions, while the United States, Malaysia, and Spain contribute the most publications. Keyword analysis shows rapid growth in research using terms such as "augmented reality" and "mathematics education," emphasizing the role of immersive technology in enhancing student engagement and conceptual understanding through visual and interactive learning. Influential authors like Lavicza, Mantri, and Haas highlight the importance of global collaboration. Based on a thematic analysis of the most-cited articles, this study proposes the AI Mathematical Education Impact and Outcome Framework. In conclusion, although research on AR in mathematics education has significantly advanced, further studies are needed to evaluate its effectiveness across varied educational contexts.

This study aims to evaluate the effectiveness of cooperative learning models in improving critical reading skills. This study uses a meta-analysis study method by analyzing 28 articles extracted from the databases of Scopus, Google Scholar, EBSCO, EmeraldInsight, Science & Direct, SpringerLink, Taylor & Francis, and ProQuest. The meta-analysis allows researchers to combine the results of previous research, providing a more comprehensive picture of how effective a particular approach is in teaching critical reading. The research findings show that cooperative learning models significantly improve essential skills of reading more effectively than traditional ones. This is shown by the effect sizes based on the fixed model, showing the overall standard difference in the mean is 0.784 (95% CI, 0.689 to 0.880) with p-values = 0.00 (<0.05). Using a cooperative learning model, The measure showed positive effect sizes on critical reading learning. Based on these results, it can be concluded that the cooperative learning model effectively improves essential reading skills. However, several factors, such as the quality of the facilitators and the teaching methods, influence the results. The implications of this study show the need for a broader application of cooperative learning models to improve critical reading skills in schools and other educational institutions, with adjustments to the needs and characteristics of students.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.