THE ROLE OF WOMEN IN THE TEACHING-RESEARCH IN TURKEY

There are 131 government, 75 private Universities in Türkiye. A demographic data on the number of women working as academic stuff in these Universites is missing and needs to be evaluated. However, the data related to Ankara University Faculty of Medicine show that on the number of female administrators and representatives in academic and administrative fields is higher than that of men

EL ROL DE LA MUJER EN LA DOCENCIA-INVESTIGACIÓN EN TURQUÍA

Hay 131 universidades gubernamentales y 75 privadas en Türkiye. Faltan datos demográficos sobre el número de mujeres que trabajan como académicos en estas universidades y deben evaluarse. Sin embargo, los datos relacionados con la Facultad de Medicina de la Universidad de Ankara muestran que el número de mujeres administradoras y representantes en los campos académico y administrativo es mayor que el de los hombres

Predicting At-Risk Students in an Online Flipped Anatomy Course Using Learning Analytics

When using the flipped classroom method, students are required to come to the lesson after having prepared the basic concepts. Thus, the effectiveness of the lecture depends on the students’ preparation. With the ongoing COVID-19 pandemic, it has become difficult to examine student preparations and to predict student course failures with limiting variables. Learning analytics can overcome this limitation. In this study, we aimed to develop a predictive model for at-risk students who are at risk of failing their final exam in an introductory anatomy course. In a five-week online flipped anatomy course, students’ weekly interaction metrics, quiz scores, and pretest scores were used to design a predictive model. We also compared the performances of different machine learning algorithms. According to the results, the Naïve Bayes algorithm showed the best performance for predicting student grades with an overall classification accuracy of 68% and with at-risk prediction accuracy of 71%. These results can be used as a traffic light project wherein the “at-risk” group will receive the red light, and thus, will require more effort to engage with the content and they might need to solve the quiz tests after an individual study period

Predicting At-Risk Students in an Online Flipped Anatomy Course Using Learning Analytics

When using the flipped classroom method, students are required to come to the lesson after having prepared the basic concepts. Thus, the effectiveness of the lecture depends on the students’ preparation. With the ongoing COVID-19 pandemic, it has become difficult to examine student preparations and to predict student course failures with limiting variables. Learning analytics can overcome this limitation. In this study, we aimed to develop a predictive model for at-risk students who are at risk of failing their final exam in an introductory anatomy course. In a five-week online flipped anatomy course, students’ weekly interaction metrics, quiz scores, and pretest scores were used to design a predictive model. We also compared the performances of different machine learning algorithms. According to the results, the Naïve Bayes algorithm showed the best performance for predicting student grades with an overall classification accuracy of 68% and with at-risk prediction accuracy of 71%. These results can be used as a traffic light project wherein the “at-risk” group will receive the red light, and thus, will require more effort to engage with the content and they might need to solve the quiz tests after an individual study period

Medical students' attitudes towards science and gross anatomy, and the relationship to personality

International audienc

Cadaver analysis of thoracic outlet anomalies

Esmer, Ali Firat/0000-0003-2511-9879; Apaydin, Nihal/0000-0002-7680-1766; ATINKAYA, CANSEL/0000-0002-8583-3479WOS: 000286413200013Background: This study aims to determinate the rate of thoracic outlet anomalies by means of analysis of cadavers. Methods: Supraclavicular incisions were applied by two anatomists and two thoracic surgeons in the thoracocervicoaxillary region of both extremities (n=40) in twenty cadavers (7 females, 13 males; mean age 46). The formation and type of fibrous bands, cervical ribs, C7 long transverse processes and anomalies of the clavicles, scalenus anterior and scalenus medius muscles, brachial plexus, subclavian arteries and veins were evaluated. The type and formation of fibrous bands were classified using Roos' classification. Results: Anomalies were found in 34 (85%) of extremities. The type 3-band was most frequently (15%) observed and all of them were on the right extremity. The type 4-band was rarely seen (2.5%). Two bands (type 9 and type 11) in the same extremity were notified in one cadaver. (2.5%). The occurrence rate of cervical rib and C7 long transverse process was 10%. Some fibers of m. scalenus medius emerged from a cervical rib in one extremity (2.5%). The arteria subclavia anterior passed through the scalene muscle in three extremities (7.5%). In 10% of extremities the C5 truncus passing through the anterior scalene muscle and upper truncus of brachial plexus passing anterior scalene muscle via perforation was found in 7.5% of patients. Conclusion: In our population, brachial plexus and subclavian artery variations are frequently observed. Therefore these types of anomalies should be taken into consideration to prevent morbidity and complications when muscle division or blockage applications are performed

The 'unskilled and unaware' : self-assessment in a real world setting

Self-assessment ability in medical students and practising physicians is generally poor yet essential for academic progress and professional development. The aim of this study was to determine undergraduate medical students ability to accurately self assess their exam performance in a real-world, high-stakes exam setting, something not previously investigated. Year 1 and Year 2 medical students (n = 199) participated in a self-assessment exercise. Students predicted their exam score (%) on the anatomy practical exam. This exercise was completed online, immediately after the exam. Students’ predicted exam scores were correlated with their actual attained exam scores using a Pearson’s correlation. Demographic data was analysed using an independent t-test. A negative correlation was found between students’ predicted and attained exam scores. There was no relationship between the students’ entry status into medical school and self-assessment ability or between males and females. However, a relationship was determined for these variables in year 2. The number of hours of additional self-directed learning undertaken did not influence students’ self-assessment. Our results demonstrate the ‘unskilled and unaware’ phenomenon in a real-world, higherstakes and practice-related setting. Students were unable to self-assess their exam performance. Poor performers were shown to overestimate their ability, and conversely, high achievers underestimated their performance. We present evidence of a strong, significant linear relationship between medical students’ ability to self-assess their performance in an anatomy practical exam, and their actual performance; in a real world setting. These findings will enable faculty to guide students on their journey to becoming reflective practitioners and reflective anatomy students

The Annular Ligament

Background: Despite documentations of ligamentous structures of the elbow, the anatomy and clinical and functional importance of the annular ligament has not been comprehensively defined in the orthopaedic literature

The annular ligament - An anatomical study

Background: Despite documentations of ligamentous structures of the elbow, the anatomy and clinical and functional importance of the annular ligament has not been comprehensively defined in the orthopaedic literature