Amongst courses and educational levels, the findings uncovered a discrepancy in students' satisfaction levels with the module. The research findings offer a deeper understanding of and contribute to the effectiveness of expanding online peer feedback tools for argumentative essay writing in various contexts. The findings yield recommendations for future investigation and educational applications.

Teachers' digital competence is a crucial prerequisite for the successful integration of technology into education. Although a variety of digital tools for creating educational resources has been designed, adjustments to digital education strategies, instructional methodologies, and professional enrichment initiatives are comparatively scarce. Consequently, this research effort aims at establishing a new evaluation instrument to assess teachers' DC in relation to their pedagogical practices and professional work within the context of digital schools and digital education models. Using a sample of 845 teachers from Greece's primary and secondary educational systems, this study investigates the total DC scores and contrasts teacher profiles. The instrument's 20 items are distributed among six components: 1) Teaching preparation; 2) Teaching delivery and student support; 3) Teaching evaluation and revision; 4) Professional development; 5) School development; and 6) Innovating education. The PLS-SEM model's factorial structure, internal consistency, convergent validity, and model fitness exhibited validity and reliability, as indicated by the analysis. The results highlighted the issue of DC inefficiency prevalent among Greek teachers. Primary school educators reported a considerable decline in scores pertaining to professional development, teaching delivery, and student support. Female instructors' scores concerning the introduction of innovative education methods and the improvement of schools showed a substantial decrease, while their scores for professional development were considerably higher. The contribution's practical relevance and implications are examined in the paper.

Any research project hinges on the essential step of finding relevant scientific papers. While the existence of a massive collection of published articles accessible online via digital databases (including Google Scholar and Semantic Scholar) is undeniable, it can unfortunately make the process of selection laborious and negatively affect a researcher's productivity. Scientific article recommendations are enhanced by a novel method described in this article, incorporating content-based filtering. The aim is to locate relevant information for researchers, transcending the boundaries of their specific research domains. Our recommendation method hinges on semantic exploration, utilizing latent factors as its core mechanism. We aim to develop an optimal topic model, which will form the basis for future recommendations. Our experiences underscore the relevance and objectivity of the results, which align with our performance expectations.

This study aimed to categorize instructors according to their patterns of implementing activities in online courses, to examine the causative factors behind cluster-specific differences, and to analyze whether instructor group membership correlated with their satisfaction levels. Employing a three-pronged approach, involving instruments to evaluate pedagogical beliefs, the implementation of instructional activities, and instructor satisfaction, data were gathered from faculty at a university in the western United States. By means of latent class analysis, instructor groups were categorized and examined for discrepancies in their pedagogical beliefs, characteristics, and satisfaction. Within the two-cluster solution, two orientations are present, namely content and learner-centric. Among the examined covariates, constructivist pedagogical beliefs and gender emerged as the key determinants of cluster membership. Online instructor satisfaction displayed a notable divergence between the predicted clusters, as indicated by the results.

This research project examined the opinions of eighth-grade students on digital game-based EFL (English as a foreign language) learning. Among the participants in the study were 69 students, aged 12 to 14 years. By means of a web 2.0 application, Quizziz, the vocabulary acquisition skills of students were examined. Data triangulation, incorporating the outcomes of a quasi-experimental research and the metaphorical viewpoints of the learners, formed the basis of the study. Data collection software was used to record student reactions to the test results, which were documented every fortnight. A pre-test, post-test, and control group approach was employed in the investigation. A pre-test was administered to the experimental and control groups prior to the start of the study. The experimental group engaged in vocabulary practice utilizing Quizziz, whereas the control group focused on memorization in their native language. The experimental group's post-test scores significantly diverged from the control group's results. To augment the analysis, content analysis was applied, categorizing metaphors and calculating their frequency distribution. Digital game-based EFL received overwhelmingly positive feedback from students, who described it as highly effective and successful. Students underscored the motivational benefits of in-game power-ups, competition with peers, and the rapid delivery of feedback.

Educational research is increasingly focusing on how teachers utilize data, particularly in light of the rising use of digital platforms for distributing educational data in digital formats, and the associated need for data literacy. A primary concern revolves around the use of digital data by educators for pedagogical enhancements, including fine-tuning their approaches to teaching. Using a survey of 1059 upper secondary school teachers in Switzerland, we explored the use of digital data by teachers and connected factors like available school technology. A survey of Swiss upper-secondary teachers revealed a disparity between their expressed agreement with the availability of data technologies and their demonstrated inclination toward their use, with only a fraction feeling confident in enhancing teaching through these methods. Using multilevel modeling, a thorough examination showed that disparities among schools, teacher's positive views of digital technologies (will), their self-assessed data proficiency (skill), access to digital data tools (tool), and general factors like student use of digital devices in lessons, predicted teachers' application of digital data. Although factors like age and teaching experience of teachers were present, their influence on student performance was relatively small. The results demonstrate a need to bolster the provision of data technologies alongside efforts to improve teachers' data literacy and application in schools.

The groundbreaking aspect of this research centers on creating a conceptual model to predict the non-linear relationships between elements of human-computer interaction and the ease of use and usefulness of collaborative web-based or e-learning systems. Ten models, including logarithmic, inverse, quadratic, cubic, compound, power, S-curve, growth, exponential, and logistic functions, were investigated to determine which best represented the effects compared to a linear model.
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The result shows the SEE values. Concerning the posed inquiries, a survey of 103 Kadir Has University students was conducted to gauge their perceptions of the e-learning interface and its interactive features. The results indicate that a significant number of the hypotheses developed for this project have been demonstrated to be accurate. Subsequent investigation confirms that cubic models, illustrating the link between ease of use and usefulness, visual design, course environment, learner-interface interactivity, course evaluation system, and ease of use, performed optimally in portraying the correlations between the listed variables.
The online document has supplemental information available at the designated URL 101007/s10639-023-11635-6.
An online version of the material provides supplemental resources, which are available at 101007/s10639-023-11635-6.

This study analyzed the consequences of group member familiarity on computer-supported collaborative learning (CSCL) in a networked classroom setting, emphasizing the importance of prior acquaintance in collaborative learning. The study also sought to differentiate between CSCL in online environments and collaborative learning in a face-to-face context. Structural equation modeling indicated that familiarity among group members positively influenced teamwork satisfaction, subsequently enhancing student engagement and the perceived construction of knowledge. Protein Conjugation and Labeling While face-to-face collaborative learning displayed higher levels of group member familiarity, satisfaction with teamwork, learner engagement, and perceived knowledge construction, a multi-group analysis indicated that the mediating influence of teamwork satisfaction was more prominent in online learning environments. bacterial immunity The findings of the study offered teachers ways to improve collaborative learning environments and adapt diverse teaching methods.

This study investigates the effective strategies employed by university faculty in response to the challenges of emergency remote teaching during the COVID-19 pandemic, along with the factors that contributed to these successes. Metabolism inhibitor The data emerged from interviews with 12 strategically chosen instructors, who expertly developed and implemented their initial online courses notwithstanding the challenges presented during the crisis. Applying the positive deviance methodology, a systematic analysis of interview transcripts identified exemplary behaviors in response to crises. The outcomes of the study reveal three unique and effective participant behaviors in their online teaching, characterized by a philosophy-driven decision-making process, informed planning, and continuous performance monitoring, and named 'positive deviance behaviors'.