Regardless of the importance of accreditation and the role faculty play in a such process, not much attention was given to those in dental colleges This study aimed to explore faculty perceptions of accreditation in the College of Dental Medicine and its impact, the challenges that hinder their involvement in accreditation, and countermeasures to mitigate these barriers using a convergent mixed methods approach. The interviewees were faculty who hold administrative positions (purposeful sample). The remaining faculty were invited for the survey using convenience sampling. Quantitative data were analyzed by Mann-Whitney and Kruskal-Wallis tests at 0.05 significance. A consensus was achieved on the positive impact of accreditation with an emphasis on the collective responsibility of faculty for the entire process. Yet their involvement was not duly recognized in teaching load, promotion, and incentives. Quality Improvement and Sustainability Tools and Benchmarking were identified as common themes for the value of accreditation to institutions and faculty. Global ranking and credibility as well as seamless service were key themes for institutional accreditation, while education tools and guidance or unifying tools were central themes for faculty. Regarding the challenges, five themes were recognized: Lack of Resources, Rigorous Process, Communication Lapse, Overwhelming Workload, and Leadership Style and Working Environment. To mitigate these challenges, Providing Enough Resources and Leadership Style and Working Environment were the identified themes. This research endeavors to achieve a better understanding of faculty perceptions to ease a process that requires commitment, resources, and readiness to change.

This study explores the complex dynamics of handling augmented reality (AR) data in higher education in the United Arab Emirates (UAE). Although there is a growing interest in incorporating augmented reality (AR) to improve learning experiences, there are still issues in efficiently managing the data produced by these apps. This study attempts to understand the elements that affect AR data management by examining the relationship between the investigated variables: faculty readiness, technological limits, financial constraint, and student engagement on data management in higher education institutions in the UAE, building on earlier research that has identified these problems. The research analyzes financial constraints, technological infrastructure, and faculty preparation to understand their impact on AR data management. The study collected detailed empirical data on AR data management in UAE higher education environments using a quantitative research methods approach, surveys. The reasons for choosing this research method include cost-effectiveness, flexibility in questionnaire design, anonymity and confidentiality involved in the chosen methods. The results of this study are expected to enhance academic discourse by highlighting the obstacles and remedies to improving the efficiency of AR technology data management at higher education institutions. The findings are expected to enlighten decision-making in higher education institutions on maximizing AR technology’s benefits for improved learning outcomes.

This research aimed to explore the concerning characteristics of information literacy in the physical education faculty of higher education institutions in Yunnan Province. This study provides a systematic meta-analysis of 33 peer-reviewed papers from 2019 to 2023. It discusses that information literacy includes basic research skills, critical thinking, and problem-solving, which include their application in the learning process. The paper describes some approaches that can be used to implement information literacy into teaching and learning, including courses with learning objectives, learner-centered approaches, and institutional support. The study also explored technology and its relation to adopting competencies for the growing technologies’ evolution within the region’s education sector. In addition, the following factors could have enhanced the process: time constraints, differences in discipline, and variations in the usage of information technology. The results indicate the need for context-specific professional learning and policy intervention to facilitate the practice of physical education faculty in Yunnan. The information collected here serves as the framework for effective regional policies regarding education, curriculum, and teacher training, among other related aspects.

Over the past decade, the integration of technology, particularly gamification, has initiated a substantial transformation within the field of education. However, educators frequently confront the challenge of identifying suitable competitive game-based learning platforms amidst the growing emphasis on cultivating creativity within the classroom and effectively integrating technology into pedagogical practices. The current study examines students and faculty continuous intention to use gamification in higher education. The data was collected through an online survey with a sample size of 763 Pakistani respondents from various universities around Pakistan. The structural equation modeling was used to analyze the data and to investigate how continuous intention to use gamification is influenced by, extended TAM model with inclusion of variables such as task technology fit, social influence, social recognition and hedonic motivation. The results have shown that task technology has no significant influence on perceived usefulness (PU) where as it has a significant influence on perceived ease of use (PEOU). Social influence (SI) indicates no significant influence on perceived ease of use. Social recognition (SR) indicates positive influence on perceived usefulness, perceived ease of use, and continuous intention. The dimensional analysis indicated that perceived ease of use has insignificant influence on perceived usefulness. Both PEOU and PU exhibit positive influence on attitude. Hedonic motivation (HM) and attitude were observed to have a positive influence on continuous intention (CI). Moreover, gamification is found to efficiently and effectively achieve meaningful goals by tapping intrinsic motivation of the users through engaging them in playful experiences.

In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.