• Title/Summary/Keyword: learning outcomes

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The Development of Mathematics Teaching Efficacy Instrument (수학 교수 효능감 측정 도구 개발 연구)

  • Kang, Moonbong;Kim, Jeongha
    • Journal of Elementary Mathematics Education in Korea
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    • v.18 no.3
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    • pp.519-537
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    • 2014
  • Teacher efficacy influences teacher's own behaviors in class and students outcomes such as achievement, motivation and their own self-efficacy. In recent years, self efficacy and teacher efficacy are becoming more popular in many educational aspects. Teacher efficacy depends on him/her and each tasks and goals. Therefore, we need special instrument for measuring mathematics teacher efficacy. On this study, we derived educationally meaningful factors on mathematics teacher efficacy from previous literature. We developed Mathematics Teaching Efficacy Instrument(MTEI) consisted of 30 items with 6-point Likert scale. The six factors are as follows; mathematics teaching efficacy expectancy, mathematics teaching outcome expectancy, mathematics teaching content knowledge, teacher belief on their own students, the past mathematics learning experience for teacher own, influence from social-cultural environment.

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Drives and Motion Control Teaching based on Distance Laboratory and Remote Experiments

  • Vogelsberger, Markus A.;Macheiner, Peter;Bauer, Pavol;Wolb, Thomas M.
    • Journal of Power Electronics
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    • v.10 no.6
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    • pp.579-586
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    • 2010
  • This paper presents the organisation and the technical structure of a remote controlled laboratory in the field of high dynamic drives and motion control. It is part of the PEMCWebLab project with the goal of providing students with practical experience on real systems in the field of power electronics and drives. The whole project is based on clear targets and leading ideas. A set of experiments can be remotely performed on a real system to stepwise identify a two axes positioning system and to design different cascaded control loops. Each single experiment is defined by its goals, the content of how to achieve them, and a verification of the results as well as the achieved learning outcomes. After a short description of the PEMCWebLab project, the structure of the remote control is presented together with the hardware applied. One important point is error handling as real machines and power electronics are applied. Finally, a selection of experiments is presented to show the graphical user interface and the sequence of the laboratory.

Robot-Assisted Thoracic Surgery in Non-small Cell Lung Cancer

  • Lee, Jun Hee;Hong, Jeong In;Kim, Hyun Koo
    • Journal of Chest Surgery
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    • v.54 no.4
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    • pp.266-278
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    • 2021
  • Lobectomy is the standard treatment for early non-small cell lung cancer. Various surgical techniques for lobectomy have been developed, and minimally invasive thoracic surgery, such as video-assisted thoracic surgery or robot-assisted thoracic surgery, has been considered as an alternative to conventional open thoracotomy. The recently robotic lobectomy technique has developed since the first case series was published in 2002. Several studies have reported that robotic lobectomy has comparable oncologic and perioperative outcomes to those of video-assisted thoracic surgery lobectomy and open lobectomy. However, robotic lobectomy remains a challenge for surgeons because of the steep learning curve, reduced tactile sensation, difficulty in port placement, and challenges in cooperation between the surgeon and assistant. Many studies have reported on robotic lobectomy, but few have presented surgical techniques for robotic lobectomy. In this article, the surgical techniques and optimal performance of robotic lobectomy are described in detail for all 5 types of lobectomy for surgeons beginning with robotic lobectomy.

Current Status of 'Professional Identity Formation' Education in the Medical Professionalism Curriculum in Korea (우리나라 의학전문직업성 교육과정에서의 '전문직 정체성 형성' 교육 현황)

  • Lee, Young-Hee
    • Korean Medical Education Review
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    • v.23 no.2
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    • pp.90-103
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    • 2021
  • This study examined the current status of the medical professionalism curriculum in Korea to suggest a plan to move towards the formation of a professional identity. Professionalism education data from 28 Korean medical schools were analyzed, including the number of courses, required or elective status, corresponding credits, major course contents, and teaching and evaluation methods. Considerable variation was found in the number of courses and credits in the professionalism curriculum between medical schools. The course contents were structured to expand learners' experiences, including the essence and knowledge of professionalism, understanding of oneself, social interaction with others, and the role of doctors in society and the healthcare system. The most common teaching methods were lectures and discussions, while reflective writing, coaching, feedback, and role models were used by fewer than 50% of medical schools. Written tests, assignments and reports, discussions, and presentations were frequently used as evaluation methods, but portfolio and self-evaluation rates were relatively low. White coat ceremonies were conducted in 96.2% of medical schools, and 22.2% had no code of conduct. Based on the above results, the author suggests that professional identity formation should be explicitly included in learning outcomes and educational contents, and that professional identity formation courses need to be added to each year of the program. The author also proposes the need to expand teaching methods such as reflective writing, feedback, dilemma discussion, and positive role models, to incorporate various evaluation methods such as portfolios, self-assessment, and moral reasoning, and to strengthen faculty development.

Conformance of Accounting Education in Saudi Arabia Universities to the International Accounting Education Standards: An Exploratory Study

  • AL-DHUBAIBI, Ahmed Abdullah Saad
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.6
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    • pp.313-324
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    • 2022
  • The goal of this research is to see how closely accounting programs in Saudi Arabian colleges comply with the International Accounting Education Standards (IESs). Further, it aims to assess the level of awareness and knowledge of IESs among accounting academics and to examine the possible explanatory factors for their variation. A structured questionnaire was sent to accounting faculty members at 37 Saudi universities. Out of 541 distributed questionnaires, a total of 102 usable responses were received from 26 universities. The findings show that accounting programs in Saudi universities are partially compliant with the guidelines of IESs and accounting academics in those universities are moderately aware of IESs. High variation in the level of academics' knowledge of IESs was detected and was significantly influenced by industry work experience, academic ranks, and professional qualification. The findings of this study suggest that Saudi Universities should work closely with the local and international accounting professional bodies, i.e. the Saudi Organization for Chartered and Professional Accountants (SOCPA) and the International Federation of Accountants (IFAC) to improve accounting programs based on the guidelines of IESs to cope with the recent changes in the capital market of the kingdom and the adoption of the International Financial Reporting Standards.

Application of machine learning and deep neural network for wave propagation in lung cancer cell

  • Xing, Lumin;Liu, Wenjian;Li, Xin;Wang, Han;Jiang, Zhiming;Wang, Lingling
    • Advances in nano research
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    • v.13 no.3
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    • pp.297-312
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    • 2022
  • Coughing and breath shortness are common symptoms of nano (small) cell lung cancer. Smoking is main factor in causing such cancers. The cancer cells form on the soft tissues of lung. Deformation behavior and wave vibration of lung affected when cancer cells exist. Therefore, in the current work, phase velocity behavior of the small cell lung cancer as a main part of the body via an exact size-dependent theory is presented. Regarding this problem, displacement fields of small cell lung cancer are obtained using first-order shear deformation theory with five parameters. Besides, the size-dependent small cell lung cancer is modeled via nonlocal stress/strain gradient theory (NSGT). An analytical method is applied for solving the governing equations of the small cell lung cancer structure. The novelty of the current study is the consideration of the five-parameter of displacement for curved panel, and porosity as well as NSGT are employed and solved using the analytical method. For more verification, the outcomes of this reports are compared with the predictions of deep neural network (DNN) with adaptive optimization method. A thorough parametric investigation is conducted on the effect of NSGT parameters, porosity and geometry on the phase velocity behavior of the small cell lung cancer structure.

A Systematic Career Advising Model and Strategies for Medical Students (의과대학생을 위한 체제적 진로상담 모델과 전략)

  • Lee, Young-Hee
    • Korean Medical Education Review
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    • v.24 no.3
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    • pp.193-204
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    • 2022
  • One of the important roles of medical schools is to support medical students in deciding upon their future career path or choosing their specialty. The purpose of this study is to suggest a career advising model and strategies for medical students through a systematic approach. This study consists of three parts. The first part introduces some main career theories: super's career development theory, career decision-making theory, social cognitive career theory, and ecosystem theory. The second part proposes a systematic career advising model using the results acquired from previous studies and theories. This model considers a medical school as a social system that consists of two domains (internal and external). This social system is considered as a complex where various factors interact with each other: students' individual characteristics, institutional policies and culture, curriculum and learning experience, students' perceived specialty characteristics, and aspects of the external environment such as healthcare systems. The third part suggests some career advising strategies based on a systematic approach that medical schools can apply. These research results can be used for designing career advising courses for medical students, integrating various career advising programs and resources of medical schools, and evaluating the outcomes of career advising programs at an institutional level.

A Research on the Development of Customized Curriculum (RAS) for Each Major for AI Education (AI 교육을 위한 전공별 맞춤형(RAS) 교육과정 개발연구)

  • Baik, Ran
    • Journal of Engineering Education Research
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    • v.25 no.5
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    • pp.44-54
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    • 2022
  • The purpose of this study is to effectively implement the artificial intelligence education required in the digital transformation era. As we enter the era of the 4th industrial revolution, the demand for a great digital transformation in industry is essential, and the nurturing of manpower is presented as an indispensable relationship in the industrial field based on it. The integration of various new technologies that have emerged from the era of the 4th industrial revolution has the greatest purpose in realizing artificial intelligence technology. As the importance of digital competency in the top curriculum reorganization has been highlighted, artificial intelligence education is necessary even in the curriculum reorganization in 2022, and there is a demand in the educational field that it should be converted into a mandatory education in middle and high schools. Artificial intelligence education according to the demands of the times is to develop an artificial intelligence curriculum in universities by reestablishing systematic artificial intelligence education in universities, setting educational goals, and presenting the goals of artificial intelligence education by major. The main direction of this study is to present the relationship between artificial intelligence and each major in university education, develop a curriculum based on artificial intelligence for each major, and link artificial intelligence software for AI education customized for each major. We would like to present a process that can measure the learning outcomes of AI education.

Evaluating Psychological Experiences of Saudi Students in Distance-Learning

  • Almaleki, Deyab A.
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.173-181
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    • 2021
  • The Ministry of Education in Saudi Arabia encourages Saudi students to continue their education at Saudi universities or abroad. Currently, an estimated 1,282,140 Saudi students are studying at Saudi universities. The extent of the research so far has not focused on Saudi student experiences, but it has shown that even a single negative event can dramatically reduce the chances of a student completing a degree. Thus, more research is necessary to identify and describe the context and obstacles (environmental and psychological) that Saudi students face. The evaluation was multifaceted to capture not only performance outcomes, but also other factors that have been suggested by research as influential to students' ability, such as the environmental, cultural, and psychological risks for graduation that Saudi students self-report. A single group pretest (survey) design was used in this study. Findings suggest depression stress and college stress predict stress levels, while subjective happiness predicts levels of scientific participations of the sample. Moreover, depression stress shows more consistency with hours spent on the internet for study purposes. These results should be considered in study support programs both institutionally and geopolitically by universities and governments.

Brain-Inspired Artificial Intelligence (브레인 모사 인공지능 기술)

  • Kim, C.H.;Lee, J.H.;Lee, S.Y.;Woo, Y.C.;Baek, O.K.;Won, H.S.
    • Electronics and Telecommunications Trends
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    • v.36 no.3
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    • pp.106-118
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    • 2021
  • The field of brain science (or neuroscience in a broader sense) has inspired researchers in artificial intelligence (AI) for a long time. The outcomes of neuroscience such as Hebb's rule had profound effects on the early AI models, and the models have developed to become the current state-of-the-art artificial neural networks. However, the recent progress in AI led by deep learning architectures is mainly due to elaborate mathematical methods and the rapid growth of computing power rather than neuroscientific inspiration. Meanwhile, major limitations such as opacity, lack of common sense, narrowness, and brittleness have not been thoroughly resolved. To address those problems, many AI researchers turn their attention to neuroscience to get insights and inspirations again. Biologically plausible neural networks, spiking neural networks, and connectome-based networks exemplify such neuroscience-inspired approaches. In addition, the more recent field of brain network analysis is unveiling complex brain mechanisms by handling the brain as dynamic graph models. We argue that the progress toward the human-level AI, which is the goal of AI, can be accelerated by leveraging the novel findings of the human brain network.