University Teaching Research Articles

A Study on Lectures Teaching Quality from Students Perspective in Education Faculty of Bamyan University in 2022

Research on teaching quality in universities is one of the most important issues that provide valuable feedback for analyzing educational issues, making critical decisions, and strategic planning for educational authorities and practitioners. On the other hand, with knowledge of their own performance quality during teaching, instructors will be able to improve teaching methods and approaches, thus enhancing the quality of their teaching. The aim of this research is to assess the teaching quality at the Faculty of Education in Bamyan University. In this study, a sample of 283 students from the Faculty of Education was selected using the Four-Multiplier Cochran technique, which employed a convenience sampling method. The Rasouli Teaching Quality Questionnaire (2010) was used to collect the data, which has good validity (0.8) and reliability. It consists of 28 Likert-scale items ranging from "very low" to "very high" and is composed of dimensions such as subject mastery, lesson planning and design, guidance and counseling, communication skills, ethical considerations, and classroom management. This research is a descriptive-survey study with practical applications based on its results. It has a foreign background, and among them, Piry Mohammad study conducted in 2018 at Malayer University in Iran titled "Satisfaction with the Quality of University Teaching," Arzo Mohammadi and colleagues' study in 2015 at Tehran University of Medical Sciences titled "Teaching Quality and its Relationship with Academic Motivation," and Hermz Seynai Nasab and colleagues' study in 2019 at Shahid Modarres University titled "Investigating the Quality of Teaching from the Perspective of Students" can be mentioned. The findings of this research indicate that the teaching quality at the Faculty of Education in Bamyan University is at a desirable level, SPSS21 software was used for data analysis, and a one-sample t-test was employed to analyze the research questions.

THE NATURAL HISTORY OF UNDISPLACED LISFRANC-TYPE INJURIES INITIALLY TREATED CONSERVATIVELY

BackgroundUndisplaced Lisfranc-type injuries are subtle but potentially unstable fracture-dislocations with little known about the natural history. These injuries are often initially managed conservatively due to lack of initial displacement and uncertainty regarding subsequent instability at the tarsometatarsal joints (TMTJ). The aim of this study was to determine the secondary displacement rate and the need for delayed operative intervention in undisplaced Lisfranc injuries that were managed conservatively at initial presentation.MethodsOver a 6-year period (2011 to 2017), we identified 24 consecutive patients presenting to a university teaching hospital with a diagnosis of an undisplaced Lisfranc-type injury that was initially managed conservatively. Pre-operative radiographs were reviewed to confirm the undisplaced nature of the injury (defined as a diastasis< 2mm at the second TMTJ). The presence of a ‘fleck’ sign (small bony avulsion of the second metatarsal) was also noted. Electronic patient records and sequential imaging (plain radiographs/CT/MRI) were scrutinized for demographics, mechanism of injury and eventual outcome.ResultsThe mean age of the patients at the time of injury was 42 years (19 Female). 96% (23/24) were low energy injuries and 88% (21/24) had a positive ‘fleck sign’. The secondary displacement rate in this group of patients was 62.5% (15/24) over a median interval of 14 days (range 0 to 482 days). 12 patients underwent open reduction internal fixation after a median interval of 29 days (range 1 to 294 days) from their initial injury. One patient required TMTJ fusion at 19 months and two patients were managed non-operatively. The injury remained undisplaced in 37.5% patients (9/24) with only one patient requiring subsequent TMTJ fusion at 5 months.ConclusionUndisplaced Lisfranc injuries have a high rate of secondary displacement and warrant close follow-up. Early primary stabilisation of undisplaced Lisfranc injuries should be considered to prevent unnecessary delays in surgical treatment.

Reform and Innovation of College English Teaching Under the Background of Mobile Internet and Big Data

The rapid development of mobile Internet has brought new development opportunities to college education and teaching. Taking university English teaching as the research object, this paper analyses the characteristics of mobile Internet in the classroom, WeChat platform, English learning app and other forms of teaching, the changes and influence of mobile Internet on English teaching, and its application in university English teaching. According to the actual teaching situation, a comprehensive evaluation system based on the learning process and results was established. The results show that the university English teaching model based on mobile Internet and the innovative evaluation and examination system can effectively improve the teaching efficiency and students' independent and sustainable learning ability. Through the reform of university English teaching, students' academic performance and learning ability have been improved. The research results are of great practical significance for promoting the reform and innovative practice of university English teaching.

The utility of the respiratory rate-oxygenation index as a predictor of treatment response in dogs receiving high-flow nasal cannula oxygen therapy.

This study aims to evaluate the respiratory rate-oxygenation index (ROX) and the ratio of pulse oximetry saturation (SpO2) to the fraction of inspired oxygen (FiO2) (SpO2/FiO2, [SF]) to determine whether these indices are predictive of outcome in dogs receiving high-flow nasal cannula oxygen therapy (HFNOT). This is a prospective observational study. This study was carried out at two university teaching hospitals. In total, 88 dogs treated with HFNOT for hypoxemic respiratory failure due to various pulmonary diseases were selected. The ROX index was defined as the SF divided by the respiratory rate (RR). ROX and SF were calculated at baseline and for each hour of HFNOT. The overall success rate of HFNOT was 38% (N = 33/88). Variables predicting HFNOT success were determined using logistic regression, and the predictive power of each variable was assessed using the area under the receiver operating curve (AUC). ROX and SF were adequately predictive of HFNOT success when averaged over 0-16 h of treatment, with similar AUCs of 0.72 (95% confidence interval [CI] 0.60-0.83) and 0.77 (95% CI 0.66-0.87), respectively (p < 0.05). SF showed acceptable discriminatory power in predicting HFNOT outcome at 7 h, with an AUC of 0.77 (95% CI 0.61-0.93, p = 0.013), and the optimal cutoff for predicting HFNC failure at 7 h was SF ≤ 191 (sensitivity 83% and specificity 76%). These indices were easily obtained in dogs undergoing HFNOT. The results suggest that ROX and SF may have clinical utility in predicting the outcomes of dogs on HFNOT. Future studies are warranted to confirm these findings in a larger number of dogs in specific disease populations.

Computer vision digitization of smartphone images of anesthesia paper health records from low-middle income countries

BackgroundIn low-middle income countries, healthcare providers primarily use paper health records for capturing data. Paper health records are utilized predominately due to the prohibitive cost of acquisition and maintenance of automated data capture devices and electronic medical records. Data recorded on paper health records is not easily accessible in a digital format to healthcare providers. The lack of real time accessible digital data limits healthcare providers, researchers, and quality improvement champions to leverage data to improve patient outcomes. In this project, we demonstrate the novel use of computer vision software to digitize handwritten intraoperative data elements from smartphone photographs of paper anesthesia charts from the University Teaching Hospital of Kigali. We specifically report our approach to digitize checkbox data, symbol-denoted systolic and diastolic blood pressure, and physiological data.MethodsWe implemented approaches for removing perspective distortions from smartphone photographs, removing shadows, and improving image readability through morphological operations. YOLOv8 models were used to deconstruct the anesthesia paper chart into specific data sections. Handwritten blood pressure symbols and physiological data were identified, and values were assigned using deep neural networks. Our work builds upon the contributions of previous research by improving upon their methods, updating the deep learning models to newer architectures, as well as consolidating them into a single piece of software.ResultsThe model for extracting the sections of the anesthesia paper chart achieved an average box precision of 0.99, an average box recall of 0.99, and an mAP0.5-95 of 0.97. Our software digitizes checkbox data with greater than 99% accuracy and digitizes blood pressure data with a mean average error of 1.0 and 1.36 mmHg for systolic and diastolic blood pressure respectively. Overall accuracy for physiological data which includes oxygen saturation, inspired oxygen concentration and end tidal carbon dioxide concentration was 85.2%.ConclusionsWe demonstrate that under normal photography conditions we can digitize checkbox, blood pressure and physiological data to within human accuracy when provided legible handwriting. Our contributions provide improved access to digital data to healthcare practitioners in low-middle income countries.

Research on the Model of Public Physical Teaching in Universities in the Context of Modern Information Technology

With the advent of the information and network era, new opportunities have emerged for the development of educational and teaching work. In the context of public physical teaching in universities, the rational application of modern information technology based on actual development situations plays a significant role. It can enrich teaching methods, improve teaching efficiency, meet students' diverse learning experiences, and ensure the quality and efficiency of teaching. However, due to objective factors, there are still some problems in the actual application process, such as the limited ability of some teachers to use information technology and the lack of investment in teaching resources, which directly limit the advantages of information technology and even affect the final teaching effectiveness, leading to counterproductive effects. Therefore, in the future development, it is necessary to strengthen the information technology training for teachers, improve their application ability and information literacy, so that they can better integrate modern information technology with physical teaching. When conditions permit, increase the investment in information technology, improve infrastructure construction, and provide necessary hardware support for public physical teaching in universities.

Occupational, academic, and personal determinants of wellbeing and psychological distress in residents: results of a survey in Lyon, France.

The mental health of residents is a growing significant concern, particularly with respect to hospital and university training conditions. Our goal was to assess the professional, academic, and psychological determinants of the mental health status of all residents of the academy of Lyon, France. The Health Barometer of Lyon Subdivision Residents (BASIL) is an initiative which consists in proposing a recurrent online survey to all residents in medicine, pharmacy, and dentistry, belonging to the Lyon subdivision. The first of these surveys was conducted from May to July 2022. Participants should complete a series of validated questionnaires, including the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS), and the Kessler Psychological Distress Scale (K6), respectively, and ad-hoc questions assessing their global health and hospital and academic working conditions. A Directed Acyclic Graph (DAG) analysis was conducted prior to multivariable analyses, to explore the determinants associated with low wellbeing (WEMWBS <43) and high psychological distress (K6 ≥ 13). A total of 904 residents (response rate: 46.7%) participated in the survey. A low level of wellbeing was observed in 23% of participants, and was significantly associated to job strain (OR = 2.18; 95%CI = [1.32-3.60]), low social support (OR = 3.13; 95%CI = [2.05-4.78]) and the experience of very poor university teaching (OR = 2.51; 95%CI = [1.29-4.91]). A high level of psychological distress was identified for 13% of participants, and associated with low social support (OR = 2.41; 95%CI = [1.48-3.93]) and the experience of very poor university teaching (OR = 2.89, 95%CI = [1.16-7.21]). Hospital working conditions, social support, and the perception of teaching quality, were three major determinants of wellbeing and psychological distress among health profession residents. Demographic determinants, personal life and lifestyle habits were also associated. This supports a multilevel action in prevention programs aiming to enhance wellbeing and reduce mental distress in this specific population and local organizational specificities.

Knowledge, Perception and Acceptance of COVID-19 Vaccination among Healthcare Personnel in Osun State University Teaching Hospital Osogbo, Osun State

No Abstract.

Transformational Healthcare Leadership in Improving Tele-Health System and Safety Performance Sustainability in University Teaching Hospitals

In developed countries, telehealth system applications are available in hospitals, hospital-based telemedicine centers, and rehabilitation centers. However, in contrast to developing countries, the telehealth system has not been implemented properly. Countries that implement telehealth systems experience different benefits, especially in developed countries. In developing countries, implementation remains challenging due to the requirement for literacy about the telehealth system itself in addition to using smartphone and tablet cellular technology for access. This research is motivated by concerns about the role of transformational leadership in providing a telehealth system to ensure the safety of medical personnel. The study adopts a quantitative approach with primary data collected at three major Indonesian university teaching hospitals—Gajah Mada Hospital, Diponegoro National Hospital, and Sebelas Maret Hospital—with medical personnel and administrative staff as the observation units. Hypothesis testing is conducted using Smart PLS 3.0. The study’s results reveal that traditional health services remain problematic despite efforts to make long-term changes. This study aligns with previous research, emphasizing that strategic flexibility serves as a proactive and reactive strategy for effecting long-term changes in key aspects of a company fostering innovation processes that contribute to sustainable business growth. Received: 21 November 2023 / Accepted: 12 March 2024 / Published: 5 May 2024

Analysis of Teaching Mode of College Music Composition Theory Course Based on Data Analysis

After learning the Soviet model and developing it today, the rudiment of professional music education established in the 1930s has formed the burden of various historical problems. At the same time, in the ideological collision between China and the West, various concepts and viewpoints around music teaching also appeared, but this is not the main research object because there is no answer at all; therefore, it is necessary to make more rational improvements to the relevant experience, new ideas and new ideas. Based on the theoretical basis of in-depth algorithm and constraint solving, this research starts from the current music teaching in colleges. It explores the curriculum mode that is conducive to the development of music in the author’s country. The experimental results show that in the teaching mode of music composition theory courses in colleges and universities, the music composition optimization algorithm (MMC) has a profound impact on the teaching effect of the course. When solving Madcap’s, the current optimal solution significantly impacts the results. In the curriculum problem, due to the constraints of the curriculum schedule problem, MMC does not show a promising solution effect but has good performance on the curriculum scheduling problem with relatively few constraints, so when solving problems with fewer constraints, the reader can choose MMC.

Application of Q-learning algorithm based on heterogeneous sensor networks in higher education teaching management

With the rapid advancement of information technology and online technologies, it has become imperative for all colleges and universities to address the challenge of leveraging modern management methods to enhance management efficiency, level, and practices. In the realm of educational institution management, the learning management system stands as the cornerstone of contemporary campus management and the entire campus computer network. In this article, the Q-learning algorithm, specifically applied to a heterogeneous cellular network, is employed to investigate the issues pertaining to teaching management in colleges and universities.The design and implementation of the university teaching management system mainly uses heterogeneous cellular networks to establish a physical model of the Q-learning algorithm, and then in the Rayleigh channel, the coverage factor and the system rate expression are derived in a closed form, and in a closed form Derive the energy efficiency expression, and then optimize the density of the basic micro-station algorithm to maximize performance. In the process of system design, this paper uses an algorithm to analyze the current research status of university teaching management, then proposes the research purpose and subject content, and analyzes the university's teaching management function and potential future functional requirements. When designing the university learning management system, it describes in detail the overall design concept, key technologies, system structure, and operating system structure and system topology. This research mainly focuses on the research of campus information management and Q learning algorithm. Based on the cellular network, a large number of campus management cases were analyzed and data fitting at the same time, and a set of Q-learning algorithm teaching management system based on heterogeneous cellular network was designed.

Intelligent Internet of Things and Privacy Protection Technology for IPE Data Analysis

In the process of shaping the personality and forming the ideal and belief of innovative talents, education plays a unique role that cannot be replaced by other forms of education. The application of an intelligent Internet of Things has been well developed in college teaching. AI is the reality of technological development in the training of higher talents in the new era, and it is the realistic demand for IPE in the training of higher talents, which requires political and ideological empowerment. Positioning the role of "educational assistant" in AI and then defining it as a "quasi-subjective object", is the basic positioning of the introduction of higher-talent IPE at this stage. 1) Build a model of teacher-student interaction supported by "human-computer cooperation"; 2) Construct intelligent learning and intelligent teaching modes supported by "algorithm databases"; 3) Establish the mechanism principle of "people-oriented" assessment and goal orientation, and further improve the quality of IPE in China's higher education personnel training. This paper aims to explore the use of artificial intelligence technology to build an ideal ideological and political education paradigm in the process of training higher-level talents in Chinese universities.

Innovative Financial Management in Higher Education: A Multi-Scale Deep Learning Approach for Risk Reduction and Quality Enhancement

This paper presents a novel university financial management system leveraging multi-scale deep learning. With rising college enrollment and teaching complexities, traditional financial models require adaptation to mitigate risks and improve management quality. The system integrates hardware and software innovations: multiple sensors enhance data scanning, coordinated by a central coordinator, ensuring comprehensive financial database coverage. Software-wise, a structured database establishes attribute-based financial connections, crucial for weight assignment. Employing a multilayer perceptual network topology, a full interconnection model based on multi-scale deep learning facilitates profound data extraction. Experimental evaluations demonstrate the system's superior financial risk assessment capabilities compared to traditional approaches, extracting a broader spectrum of financial parameters for comprehensive risk warnings. By embracing multi-scale deep learning, this system promises significant advancements in university financial management, enhancing adaptability and risk mitigation in college finance departments.

Factors Associated with Obstetric Anal Sphincter Injury During Vacuum-Assisted Vaginal Delivery.

Obstetric anal sphincter injury (OASI) is a major complication associated with vacuum-assisted vaginal delivery (VAVD). The aim of this study was to evaluate risk factors related to vacuum extraction that are associated with OASI. This was a case-control study performed at a tertiary university teaching hospital. Included were patients aged 18-45years who had a singleton pregnancy resulting in a live, term, VAVD. The study group consisted of women diagnosed with OASI following vacuum extraction. The control group included women following VAVD without OASI. Matching at a ratio of 1:2 was performed. Groups were compared regarding demographic, obstetric. and labor-related parameters, specifically focusing on variables related to the vacuum procedure itself. One hundred and ten patients within the study group and 212 within the control group were included in the final analysis. Patients in the OASI group were more likely to undergo induction of labor, use of oxytocin during labor, increased second stage of labor, higher likelihood of the operator being a resident, increased number of pulls, procedure lasting under 10min, occipito-posterior head position at vacuum initiation, episiotomy, increased neonatal head circumference, and birthweight. Multivariate logistic regression analysis revealed that increased week of gestation (OR 1.67, 95% CI 1.25-2.22, p < 0.001), unsupervised resident performing the procedure (OR 4.63, 95% CI 2.17-9.90), p < 0.001), indication of VAVD being fetal distress (OR 2.72, 95% CI 1.04-7.10, p = 0.041), and length of procedure under 10min (OR 4.75, 95% CI 1.53-14.68, p = 0.007) were associated with OASI. Increased maternal age was associated with lower risk of OASI (OR 0.9, 95% CI 0.84-0.98, p = 0.012). When performing VAVD, increased week of gestation, unsupervised resident performing the procedure, fetal distress as vacuum indication, and vacuum procedure under 10min were associated with OASI. In contrast, increased maternal age was shown to be a protective factor.

Synthetic, non-person related panoramic radiographs created by generative adversarial networks in research, clinical, and teaching applications

ObjectivesGenerative Adversarial Networks (GANs) can produce synthetic images free from personal data. They hold significant value in medical research, where data protection is increasingly regulated. Panoramic radiographs (PRs) are a well-suited modality due to their significant level of standardization while simultaneously displaying a high degree of personally identifiable data. MethodsWe produced synthetic PRs (syPRs) out of real PRs (rePRs) using StyleGAN2-ADA by NVIDIA©. A survey was performed on 54 medical professionals and 33 dentistry students. They assessed 45 radiological images (20 rePRs, 20 syPRs, and 5 syPRcontrols) as real or synthetic and interpreted a single-image syPR according to the image quality (0–10) and 14 different items (agreement/disagreement). They also rated the importance for the profession (0–10). A follow-up was performed for test-retest reliability with >10 % of all participants. ResultsOverall, the sensitivity was 78.2 % and the specificity was 82.5 %. For professionals, the sensitivity was 79.9 % and the specificity was 82.3 %. For students, the sensitivity was 75.5 % and the specificity was 82.7 %. In the single syPR-interpretation image quality was rated at a median of 6 and 11 items were considered as agreement. The importance for the profession was rated at a median score of 7. The Test-retest reliability yielded a value of 0.23 (Cohen's kappa). ConclusionsThe study marks a comprehensive testing to demonstrate that GANs can produce synthetic radiological images that even health professionals can sometimes not differentiate from real radiological images, thereby being genuinely considered authentic. This enables their utilization and/or modification free from personally identifiable information. Clinical significanceSynthetic images can be used for university teaching and patient education without relying on patient-related data. They can also be utilized to upscale existing training datasets to improve the accuracy of AI-based diagnostic systems. The study thereby supports clinical teaching as well as diagnostic and therapeutic decision-making.

Higher Education in Northern Cyprus: The Path from Isolation to Oversaturation

Abstract This study explores the problems related to university teaching and academic research within de facto states in the context of their non-recognition via an analysis of the current situation in the higher education sector of Northern Cyprus. It reveals that although Northern Cyprus is a world leader in terms of the number of universities per capita, as well as the proportion of international students and the proportion of higher education students in its population, its higher education system nevertheless faces numerous problems. Among the most serious of these are the inconsistent and often very low quality of Northern Cyprus’s universities, the politicisation of and lack of confidence in the accreditation authorities responsible for the quality and sustainability of the higher education system, and the unregulated activities of “agents” who recruit new students.

Arima Model to Predict the Prevalence of Diabetes Type 1 and Type 2 Patients: A Case Study of Jos University Teaching Hospital

Diabetes Mellitus is a huge burden for human health, increasing number of patient is likely to result in rising demand for the medical emergencies. Due to limited number of hospitals with standard laboratory test kits to differentiate between type 1 and type 2 diabetes it is important to forecast the future incidences and prepare with proper resource planning. The monthly number of Diabetes patients obtained from Jos University Teaching Hospital is fitted by autoregressive integrated moving average (ARIMA) model. Dataset starting from January, 2010 to December,2020. Using ARIMA, several models were evaluated based on the Bayesian Information Criterion (BIC) and Ljung-Box Q statistics. ARIMA(3, 1, 1) is found to be better and used to describe and predict the future trends of Diabetes type 1 and ARIMA(1,1,1) is a better model to predict the future prevalence of diabetes type 2. Therefore, the proposed model will help in the appropriate planning and allocation of resources for emergencies.

The Effectiveness of the Just-in-Time Teaching Strategy on Female Students Achieving a Bachelor’s Degree as Classroom Teachers, Their Motivation to Learn in the Grammar and Morphology Course, and Their Teaching Methods

The study aimed to determine the effectiveness of the just-in-time teaching (JITT) strategy in female students’ achievement of a bachelor’s degree as a classroom teacher, their motivation to learn in the grammar and morphology course, and their teaching methods. To achieve the objectives of the study, a quasi-experimental approach was adopted, and the study sample consisted of 60 female students with a bachelor’s degree as classroom teachers who were studying the course of grammar and morphology and their teaching methods. They were distributed into two groups: the experimental group, which included 30 female students, and the control group, which included 30 female students. An achievement test was prepared and a questionnaire of motivation to learn was completed, and their validity and reliability were confirmed. The education program was prepared using the JITT strategy, and its validity was confirmed. The study results revealed that there were statistically significant differences between the average scores of the experimental group that studied by using the JITT strategy and the control group that studied by using the traditional method on the achievement test and the measure of motivation to learn in favor of the experimental group. The study recommended employing a timely teaching strategy in university teaching.

Statistical evaluation of effect of anthropometric measurements on adolescent idiopathic scoliosis

Scoliosis is a deformity in which there is sideways curvature to the spine. Curves are often S shaped or C shaped. Most common type is the idiopathic type which occurs in 10-12 years of age and early teens, females are more affected than males while the body is growing fast and the curve is commonly to the right side of the body. It however affect all ages of about 3% of general population. This study was set out to evaluate statistically, the effect of age, gender and anthropometric measurements (such as height, weight and body mass index) to the curve formed using 51 patients from Lagos State University Teaching Hospital, Ikeja. It was discovered from the analysis that the ailment is common among females than males. The result also shows that the curve is most common to right hand side. The test of hypothesis conducted reveals that the anthropometric measurements of height, weight and body mass index though positively correlated with but do not have significant effect on the Adolescent Idiopathic Scoliosis curve.

An in-fiber Mach–Zehnder strain sensor for studying multimode interference of light

Multimode interference of light is an optical interference phenomenon based on waveguides, which has broad applications in optical communication, lasers, and optical fiber sensing. Since optical fiber has become the most widely used optical waveguide in modern society, multimode interference in optical fibers is an ideal candidate for projects in university teaching laboratories. Here, we implement an in-fiber Mach–Zehnder strain sensor-based experiment to study multimode interference in optical fibers. The sensor is fabricated by fusion splicing a piece of thin core fiber between two single mode fibers. One end of the thin core fiber is spliced without a core offset, while the other end is spliced with a core offset. Due to the mode field diameter mismatch and core offset, cladding modes are excited and interfere with the core mode in thin core fiber. Students can observe the sensor fabrication demonstration and perform a strain test with an optical spectrum analyzer. The wavelength spectra captured by the optical spectrum analyzer under different strains are analyzed with the signal processing tools of fast Fourier transform and fast Fourier transform filter. Students then find characteristics of the multimode interference in the sensor from the analysis. The experiment extends undergraduates' knowledge of light interference and is an instructive exercise for them in modern coherence theory.