Showing 17 results for Learning
H Dargahi, M Ghazi Saidi, M Ghasemi,
Volume 1, Issue 2 (2-2008)
Abstract
Background and Aim: Ever-increasing development of access to appropriate software and hardware for e-learning especially development of worldwide web has suggested new horizons for educational institutes. It is much important in medical sciences, because Medical Sciences deal with the health of human beings. Since beside issues related to education, research and information production, appropriate treatment of the patients is possible through having up to date and new information as well. For this reason Medical Sciences utilize information technology as soon as possible in order to prepare essential information for physicians quickly. This article discusses the role of e-learning in Medical Sciences universities.
Materials and Methods: in this literature review article, gathering information has been done by using paper and paperless documents related to the topic.
Results: For implementing of e-learning in Medical Sciences organization there should be some infra-structures, standards and skills which are to be noted prior to commencing e-learning. These infra-structures, standards and skills play a special role in successful implementation of e-learning.
Conclusion: Regarding the advantages of e-learning naturally possesses, there is no doubt in necessity of developing Medical Sciences e-learning. But the ways of efficient access to this sort of education is much more important. So, it is recommended that by comparing the existing process in the world and using the experiences of prominent countries in this field, the most appropriate method be chosen and applied.
H Dargahi, M Ghazi Saidi, M Ghasemi,
Volume 3, Issue 3 (3-2010)
Abstract
Background and Aim: Electronic learning system is a new educational process which designed upon basis of computerized technology, multimedia and processors. It has several potentials and contexts.
To do comparative study and utilizing of successful electronic learning in developed countries could help us to develop this new process in Iran's Universities of Medical Sciences.
Materials and Methods: This research is developed descriptive comparative study in 2007 - 2008 by using of developed countries universities websites information and 62 references and keywords such as Electronic Educations,Medical Sciences Courses,Commutation Technology, Comparative Study and University in the field of electronic medical sciences. Then, the findings will compare with each developed countries universities and Iran's Universities of Medical Sciences.
Results: The results showed that Manchester and Dekin University have much experience in developing of electronic learning. The Students should be assessed by attendance, online and blended in developed universities.
Degree based courses are only present in South - Africa University, meanwhile single courses and training are present in other universities. Electronic health sciences courses and training are developed much more in compressive with others.
Discussion and Conclusion: The studied universities are different in history of construction, student assessment type, homework presence type, registration procedures, electronic medical education type with each other.
Iran's Universities of Medical Sciences, electronic education have several deficiencies in comparison with developed countries universities. We suggest appropriate technological and cultural infrastructure and use's skill improvement to develop this process in our country's universities of Medical sciences.
Mahdi Sattari-Ghahfarrokhi, Mehdi Abzari,
Volume 6, Issue 4 (11-2012)
Abstract
Background and Aim: Learning may be the only sustainable competitive advantage for all organizations. A learning organization is an organisation where people continually expand their capacity to create results they truly desire new and expansive patterns of thinking are nurtured collective aspirations are set free people are continually learning from what others have learned. The aim of this research is to study whether a learning organization and its subsystems are established in Shahrekord University of Medical Sciences (SKUMS).
Materials and Methods: This descriptive-survey study was conducted in 2012. Marquardt's standard questionnaire was used to measure learning organization based on Likert's scale with a Cronbach's Alpha coefficient of 0.946. The research sample consisted of 177 staff members (bachelor's degree holders and bove) in seven vice-chancellorships of SKUMS, selected through simple random sampling.
Results: The findings of the study are twofold. (1) According to the results of one-sample t-test with a 95% confidence interval, the mean scores in learning organization and sub-systems of learning dynamics, people empowerment, knowledge management and technology application subsysems were higher than the assumed mean of 3 however, the figure turned out to be equal to the assumed mean for the organization transformation subsystem, and (2) Based on Freidman Test, there was a significant difference between the means of at least 2 learning organization subsystems.
Conclusion: According to the research findings, more attention should be paid to the subsystems of learning organization establishment and balanced development of these subsystems.
Zhila Najafpoor , Faezeh Fartaj, Mandana Shirazi , Fatemeh Keshmiri,
Volume 7, Issue 6 (3-2014)
Abstract
Background
and Aim: Learning styles are
among efficient factors in the teaching-learning process. The aim of the
present study was to assess healthcare management students’ learning styles at
Tehran University of Medical Sciences (TUMS).
Materials
and Methods: This descriptive
cross-sectional study was conducted on healthcare management students selected
randomly through stratified sampling (response rate = 85%). The data collection
tool used in this study was Kolb learning style questionnaire (Cronbach Alpha
was 0.7-0.9). The data were analyzed through descriptive and analytical tests
(χ2 and t-test).
Results:
Most postgraduate students preferred the Accommodate Style (55.6%
of PhD students and 64% of MCs students). The
majority of undergraduate students, however, preferred the Convergent Style (45.67%).
Conclusion: As to these students’
dominant learning styles, the results of the study emphasized the use of
“teaching methods based on Role Playing and Simulation” among postgraduate
students and “Problem-Based Learning” among undergraduate students.
Edris Kakemam, Afife Irani, Mobin Sokhanvar, Amin Akbari, Hossein Dargahi,
Volume 9, Issue 5 (2-2016)
Abstract
Background and Aim: Scientific and technological developments have promoted the status of organizational learning as a reasonable way to deal with the present changing circumstances. The development of organizational learning improves the performance of employees, and makes them feel satisfied. The aim of this study is to investigate the relationship between job satisfaction and organizational learning capabilities among the employees of Tehran hospitals.
Materials and Methods This descriptive, analytical study was conducted among 290 employees in 2014 in Tehran hospitals. For data collection, a three-part questionnaire (including demographic characteristics, Gomez`s Organizational Learning Capability Questionnaire and Minnesota Job Satisfaction Questionnaire) was given to 290 employees. Data were analyzed using the SPSS-20 software with Spearman test.
Results: Mean scores of organizational learning capability and job satisfaction were (3.03± 0.61) and (2.8± 0.61), respectively. Among the dimensions of organizational learning capability, the highest score pertained to systematic perspective (3.29± 0.78); regarding job satisfaction, the highest score was related to organizational climate (3.23± 0.1). The results showed that there was a significant correlation between the dimensions of organizational learning capability and job satisfaction. Also, a significant correlation was observed between organizational learning capabilities and job satisfaction.
Conclusion: Organizational learning improves the performance of employees and is positively correlated with their satisfaction. Also, employee satisfaction is one of the factors affecting their performance. Therefore, managers can make employees satisfied and develop their organization through improving organizational learning.
Bahaman Khosravi, Moslem Sharifi, Ahmad Fayaz-Bakhsh, Mostafa Hosseini,
Volume 9, Issue 6 (3-2016)
Abstract
Background and Aim: Learning is essential in healthcare environments, where knowledge and skills are quickly outdated due to continuous advances in medical science. Organizational learning is a dynamic process that enables learning organizations to be campatible with change in good time. The aim of this study was to determine the status of organizational learning in an Iranian healthcare organization in Tehran, and to assess the extent to which this organization could be considered as a learning organization.
Materials and Methods: In this cross-sectional and descriptive study, 200 nurses were selected in an Iranian healthcare organization. Dimension Learning Organizational Questionnaire (DLOQ) was used to collect data to be analyzed using descriptive statistics methods by frequency, percentage, mean, and standard deviation.
Results: The mean overall score for organizational learning was 3.36±0.69. Among the various dimension of organizational learning, continuous learning had the highest average (3.44±0.39), and the empowerment had lowest amount (2.72±0.06).
Conclusion: The findings from this study provide useful information for these organization's managers regarding the areas where there is a need for improvement in OL and to make it a more LO.
Mina Sadat Hashemiparast, Roya Sadeghi, Mohammadreza Ghaneapur , Kamal Azam , Azar Tol ,
Volume 10, Issue 3 (7-2016)
Abstract
Background and Aim: Effective educational programs, is one of the most basic methods in prevention of Nosocomial infection. This study aimed to compare the effects of E-learning versus lecture-based education in prevention of Nosocomial infections among hospital staffs.
Materials and Methods: A randomized pre and posttest control group design was conducted on 98 hospital staffs in 2013 after allocating into two groups of "lecture-based education" and "E-learning”. Data were collected by a researcher-made questionnaire which its validity and reliability was confirmed by a pilot study. Wilcoxon, Paired and Independent sample T-test was conducted using SPSS, version18.
Results: There was a significant difference for outcomes before and after education based on two approach of lecture-based (p=0.01) and E-learning (p=0.01).The mean and standard deviation of knowledge in lecture-based education and E-learning group were 12.73± 2.76, 11.50 ± 2.64 respectively. The level of knowledge in the lecture group was significantly higher than that of participants in the E-learning group (p=0.02).
Conclusion: Despite the effectiveness of E-learning in learning and raising awareness of the learners, using of this method among health-related organizations need to empower employees, remove the barriers and suitable infrastructure.
Badri Razeghi, Haideh Saberi,
Volume 11, Issue 1 (5-2017)
Abstract
Background and Aim: E-learning would provide learners with this opportunity. In this study we compared self regulation and academic achievement in traditional and virtual students.
Materials and Methods: This was a cross sectional study among 49 face to face and virtual master students of virtual school of Tehran University of Medical Sciences in 2015, in which the O Nil & Hong’s valid and reliable questionnaire was used to assess self regulation. Also we assessed academic achievement by students' courses mean scores. Data were analyzed by SPSS version 21.
Results: Forty seven students participated in the study. There was no difference between groups considering sex and age. Traditional and virtual students' scores were significantly different only in the “self assessment” factor (P-value= 0.050). There was no difference in other factors of self regulation or academic achievement.
Conclusion: Results of this study showed that e-learning is at least as effective as face to face teaching. On the other hand in some cases has more effects on self regulation factors. So considering e-learning advantages, it is recommended to be used as a suitable substitute.
Azam Orooji , Mostafa Langarizadeh , Maryam Aghazadeh, Mehran Kamkarhaghighi, Marjan Ghazisaiedi , Fateme Moghbeli,
Volume 12, Issue 4 (11-2018)
Abstract
Background and Aim: Artificial intelligence is a branch of computer science that has the ability of analyzing complex medical data. Using artificial intelligence is common in diagnosing, treating and taking care of patients. Warfarin is one of the most commonly prescribed oral anticoagulants. Determining the exact dose of warfarin needed for patients is one of the major challenges in the health system, which has attracted the attention of researchers. The purpose of this study was to determine the exact dose of warfarin needed for patients with artificial heart valves using artificial neural networks (ANN).
Materials and Methods: A total of 9 multi-layer perceptron ANNs with different structures were constructed and evaluated based on a dataset including 846 patients who had referred to the PT clinic in Tehran Heart Center in the second half of the year 2013. Finally, the best structure of ANN for warfarin dose was investigated. All simulations including data preprocessing and neural network designing were done in MATLAB environment.
Results: The effectiveness of ANNs was evaluated in terms of classification performance using 10-fold cross-validation procedure and the results showed that the best model was a network that had 7 neurons in its hidden layer with an average absolute error of 0.1, turbulence rate of 0.33, and regression of 0.87.
Conclusion: The achieved results reveal that ANNs are able to predict warfarin dose in Iranian patients with an artificial heart valve. Although no system can be guaranteed to achieve 100% accuracy, they can be effective in reducing medical errors.
Mohsen Rezaei, Nazanin Zahra Jafari, Hossein Ghaffarian, Masoud Khosravi Farmad3, Iman Zabbah, Parvaneh Dehghan,
Volume 13, Issue 5 (1-2020)
Abstract
Background and Aim: Timely diagnosis and treatment of abnormal thyroid function can reduce the mortality associated with this disease. However, lack of timely diagnosis will have irreversible complications for the patient. Using data mining techniques, the aim of this study is to determine the status of the thyroid gland in terms of normality, hyperthyroidism or hypothyroidism.
Materials and Methods: Using supervised and unsupervised methods after data preprocessing, predictive modeling was performed to classify thyroid disease. This is an analytical study and its dataset contains 215 independent records based on 5 continuous features retrieved from the UCI machine learning data reference.
Results: In supervised method, multilayer perception(MLP), learning vector quantization(LVQ), and fuzzy neural network(FNN) were used; and in unsupervised method, fuzzy clustering was employed. Besides, these precision figures(0.055, 0.274, 0.012 and 1.031) were obtained by root mean square error(RMSE) method, respectively.
Conclusion: Reducing the diagnosis error of thyroid disease was one of the goals of researchers. Using data mining techniques can help reduce this error. In this study, thyroid disease was diagnosed by different pattern recognition methods. The results show that the fuzzy neural network(FNN) has the least error rate and the highest accuracy.
Niloofar Mohammadzadeh, Ziba Mosayebi, Hamid Beigy, Mohammad Shojaeinia,
Volume 14, Issue 6 (1-2021)
Abstract
Background and Aim: Sepsis is the most important disease in the first 28 days of life and one of the main causes of infant mortality in the intensive care unit. Its definitive diagnosis is possible by performing blood culture. Neonatal sepsis can be a clinical sign of nosocomial infections that are often resistant to antibiotics. Therefore, the purpose of this study was to create and evaluate a hospital sepsis prediction model and present its results to health care providers.
Materials and Methods: In this descriptive-applied study, the research population includes neonates admitted to the intensive care unit of Valiasr Hospital in Tehran and the research sample is the data of 4196 neonates admitted to this ward from 2016 to August, 2020. The initial features for creating a predictive model of sepsis were prepared by examining the relevant information sources and under the supervision of professors and officials of Valiasr Hospital's mother and fetus research center and its validity was confirmed by 5 neonatal professors of this hospital. In this research, machine learning algorithms have been used to create a sepsis prediction model.
Results: Accuracy and AUROC(area under the ROC curve) parameters were used to evaluate the generated models. The highest values of Accuracy and AUROC are related to Adaptive Boosting and random forest algorithms, respectively.
Conclusion: Learning curves show that using different training examples and more complex selection of combination features improves the performance of the models. Further research is needed to evaluate the clinical effectiveness of machine learning models in a trial.
Nida Abdolahi, Mohamad Reza Nili Nili Ahmadabadi, Soghra Ebrahimi Qavam, Khadijeh Aliabadi, Mohammad Asgari,
Volume 15, Issue 1 (3-2021)
Abstract
Background and Aim: Deep and sustainable learning requires a safe and healthy environment. Moreover, paying attention to the intertwined emotional, motivational, cognitive and social processes in the teaching-learning process is vital. Academic achievement motivation and self-regulated learning (SRL) are two important elements in this process that are influenced by the achievement emotions in the learning environment. Therefore, the aim of this study is to evaluate the effectiveness of instructional design model based on control-value theory of achievement emotions (CVT), on academic achievement motivation and self-regulation learning.
Materials and Methods: The research was quantitative and performed by Nonequlment design control group. The statistical population included female second year high school students in Tehran in the academic year of 1997-98, who were selected by multi-stage cluster random sampling in two experimental and control groups. The experimental group was trained according to the instructional design model based on CVT theory and the control group did not receive this training method. The questionnaire of academic achievement motivation and self-regulated learning was administered to the experimental and control groups as pre-test and post-test before and after the implementation of the model. Data were analyzed by inferential and descriptive statistics using SPSS software and multivariate covariance.
Results: The results of univariate analysis of covariance of group effect on the scores of dependent variables show that there is a significant difference between the experimental and control groups in cognitive strategy (F=11/94, P>0/05, η2=0/14), metacognition strategy (F=56/06, P>0/05, η2=0/44), motivational beliefs (F=6/36, P>0/05, η2=0/08) and academic achievement motivation (F=10/69, P>0/05, η2 =0/13).
Conclusion: The result of this study show that the use of instructional design model based on CVT theory has a positive effect on cognitive strategies, metacognition strategies, motivational beliefs and learners' academic achievement motivation.
Marsa Gholamzadeh, Seyed Mohammad Ayyoubzadeh, Hoda Zahedi, Sharareh Rostam Niakan Kalhori,
Volume 15, Issue 3 (8-2021)
Abstract
Background and Aim: Due to the important role of radiological images for identifying patients with COVID-19, creating a model based on deep learning methods was the main objective of this study.
Materials and Methods: 15,153 available chest images of normal, COVID-19, and pneumonia individuals which were in the Kaggle data repository was used as dataset of this research. Data preprocessing including normalizing images, integrating images and labeling into three categories, train, test and validation was performed. By Python language in the fastAI library based on convolution technique (CNN) and four architectures (ResNet, VGG MobileNet, AlexNet), nine models through transitional learning method were trained to recognize patients from healthy persons. Finally, the performance of these models was evaluated with indicators such as accuracy, sensitivity and specificity, and F-Measure.
Results: Of the nine generated models, the ResNet101 model has the highest ability to distinguish COVID-19 cases from other cases with 95.29% sensitivity. Other applied models showed more than 96% accuracy in correctly diagnosis of various cases in test phase. Finally, the ResNet101 model was able to demonstrate 98.4% accuracy in distinguishing between healthy and infected cases.
Conclusion: The obtained accuracy showed the accurate performance of developed model in detecting COVID-19 cases. Therefore, by implementing an application based on the developed model, physicians can be helped in accurate and early diagnosis of cases. an application based on the developed model, physicians can be helped in accurate and early diagnosis of infected cases.
Arman Bahari, Behnoosh Moody,
Volume 15, Issue 4 (10-2021)
Abstract
Background and Aim: Increasing the use of smartphones, improving the state of World Wide Web, and also the need for flexibility in the education process have made the implementation of e-learning in human society inevitable, eliminated time and space limitations, and provided equal education. However, the pace of its creation and development, especially in universities and higher education centers in developing countries such as Iran, is very slow. Therefore, the present study aims to investigate the factors affecting the creation and development of e-learning from the viewpoint of students of Zahedan University of Medical Sciences.
Materials and Methods: This is an applied and descriptive-survey study. The sample includes 313 students studying at Zahedan University of Medical Sciences during 2016-2017, who were selected by simple random sampling. Data were collected using a researcher-made questionnaire and analyzed using statistical tests and SPSS software.
Results: The findings show that the six selected factors of this study affect the creation and development of e-learning from the viewpoint of Zahedan University of Medical Sciences students. From the highest to the lowest effect, these factors include the quality of information and content (4.25), learners’ willingness (4.11), system quality (4.10), facilitators (4.05), student-professor interaction (3.98) and professor quality (3.84).
Conclusion: According to the findings of the present study, it can be concluded that policy makers and university administrators, considering the importance of each factor, invest and develop e-learning to provide better services to students and faculty.
Mostafa Roshanzadeh, Mina Shirvani, Ali Tajabadi, Mohammad Hossein Khalilzadeh, Somayeh Mohammadi,
Volume 16, Issue 2 (5-2022)
Abstract
Background and Aim: Clinical learning is an important part of the health field, where the student interacts with the environment and applies the learned concepts in practice. Clinical environments such as operating rooms are challenging for students due to their special complexity and can have a negative impact on their learning process. In order to identify students ‘learning challenges in the operating room environment, the present study was conducted to explain students’ experiences in the field of clinical learning challenges.
Materials and Methods: The present qualitative study was performed by contract content analysis method in 2022 in Shahrekord University of Medical Sciences. Fourteen surgical technology students were purposefully selected and data were collected using in-depth semi-structured individual and group interviews and analyzed using the Granheim and Landman approaches.
Results: The participants were interviewed over a period of 5 months. 9 face-to-face interviews were conducted with 14 participants. There were 6 individual interviews and 3 group interviews. The average duration of the interview was 30 minutes. The interviews continued until data saturation and when no new themes or categories were obtained from the interviews. The findings included a theme of “unfavorable learning environment” and three categories of “confusion in learning educational content, improper professional behavior of staff and insufficient self-confidence”. The main challenge that students faced in the field of clinical learning was the unfavorable learning environment. Conditions such as confusion in learning educational content, improper professional behavior of staff and insufficient self-confidence experienced by the students in the operating room, cause the students to find the learning atmosphere in the operating room unfavorable.
Conclusion: Improving the behavior and performance of staff and physicians in accordance with the standards of professional and ethical behavior and its regular evaluation from the perspective of students and other colleagues can play an effective role in maintaining professional conditions. Also, using experienced instructors who have the role of facilitating communication and learning of students in the operating room environment will play an effective role in reducing fear and controlling inappropriate behaviors of staff towards students. Educational officials are advised to solve the existing problems in order to improve the educational atmosphere of the operating room.
Ashraf Dehghani, Maryam Ghanbari Khoshnood, Somayeh Amini Sarteshnizi, Arezoo Farhadi,
Volume 17, Issue 1 (3-2023)
Abstract
Background and Aim: The emergence and continuity of Corona has forced universities and higher education centers to change their educational strategy to take appropriate and consistent action to improve their educational programs. Due to the importance of e-learning and e-learning in response to these conditions, the present study investigated the experience of students of Hamadan University of Medical Sciences from e-learning in the Covid-19 crisis condition.
Materials and Methods: This was a qualitative research with an interpretive phenomenological approach. The purposeful sampling method was used. Semi-structured interviews were used to collect data. After the thirteenth interview, the theoretical saturation of the data was achieved and the interview process with the sixteenth person was completed. In order to analyze the text of the interviews, the Colaizzi method was used.
Results: From the analysis of the obtained data, three main themes: “Communication and interaction” with five sub-themes (lack of proper interaction between student/professor and student/student, lack of motivation, security and mental health, knowledge sharing and efficiency atmosphere in time and cost), “Management of time and learning style” with six sub-themes (low quality of teaching, stress, access and provision of resources, exam health, gaining experience and skills and opportunity to learn again and innovation in education) and “Infrastructure and technical facilities” were extracted with three sub-themes (weak support, ignoring educational equality and promoting media literacy). Weak interaction between professor and student, increasing level of anxiety and individual responsibility to achieve success in learning and weak technical and management infrastructure were the main challenges obtained from these three themes. Providing a platform for research, self-regulation and self-management in learning, increasing the knowledge and skills of information and communication technology are among the opportunities that are included in these themes.
Conclusion: The results of the current research require attention to the approach of interaction and communication between the learner and the learner, to review the methods of teaching and skill-learning, to improve the quality of electronic learning and to prepare suitable infrastructures for optimal use of electronic learning.
Miss Fariba Moalem Borazjani, Azita Yazdani, Reza Safdari, Seyed Mansoor Gatmiri,
Volume 17, Issue 6 (2-2024)
Abstract
Background and Aim: Kidney failure is a common and increasing problem in Iran and worldwide. Kidney transplantation is recognized as a preferred treatment method for patients with end-stage renal disease (ESRD). Machine learning, as one of the most valuable branches of artificial intelligence in the field of predicting patient outcomes or predicting various conditions in patients, has significant applications. The purpose of this research was to predict kidney transplant outcomes in patients using machine learning.
Materials and Methods: Since CRISP is one of the strongest methodologies for implementing data mining projects, it was chosen as the working method. In order to identify the factors affecting the prediction of kidney transplant outcomes, a researcher-created checklist was sent to some of nephrologists nationwide to determine the importance of each factor. The results were analyzed and examined. Then, using Python language and different algorithms such as random forest, SVM, KNN, deep learning, and XGBoost the data was modeled.
Results: The final model was multilabel, capable of predicting various kidney transplant outcomes, including rejection probability, diabetic reactions, malignant reactions, and patient rehospitalization. After modeling the input data features, the model was able to predict the four kidney transplant outcomes such as rejection, diabetes, malignancy and readmission with an error rate of less than 0.01.
Conclusion: The high level of accuracy and precision of the random forest model demonstrates its strong predictive power for forecasting kidney transplant outcomes. In this study, the most influential factors contributing to patient susceptibility to the mentioned outcomes were identified. Using this machine learning-based system, it is possible to predict the probability of these outcomes occurring for new cases.
