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讀書會召集人領導功能之研究 / A study of the conveners' leadership of study circles游淑靜 Unknown Date (has links)
讀書會(study circles)為一種志願團體,若立案為社團法人者,為非營利組織,回顧台灣讀書會自民國七十四年台北「媽媽充電會」及高雄「揚帆主婦社」成立發軔至今,隨著解嚴、社區主義及女性主義的抬頭,已有長足進展,依據民國九十年十月第五屆全國讀書會博覽會之統計,目前全國有案可稽之讀書會有1,912個。
表面數字雖值得欣慰,但這其中卻不乏中途倒會、進入冬眠或目標變質者,因此,讀書會泡沫式的現象非常值得觀察研究。大致說來,讀書會發展有四階段,即籌組期、發展期、倦怠期和成熟期,在發展過程中,如果無法渡過倦怠期危機,很容易就倒會,名存實亡。國內雖有讀書會暴起暴落,然而成立超過十年,成員超過五十人者(甚至超過二百人),也大有所在。因此,讀書會的領導與管理,攸關讀書會之成敗,是值得探討之主題。
借鏡於國外案例,美國的讀書會發展,據一九九七年統計,已有五十萬個讀書會;瑞典的讀書會據一九九六年統計,有三十五萬個讀書會在運作。以目前台灣約兩千三百萬人,約有兩千個讀書會,相較於美國及瑞典,台灣民眾參與讀書會比例,顯然偏低,值此全民學習、終身學習的時代,讀書會尚有極大發展空間,值得政府及民問來共同推廣。
有鑑於此,本論文期經由文獻探討、深度訪談、比較研究及焦點團體座談,從讀書會不同發展階段、Yuk1的有效領導管理行為、易經啟示理念等不同理論,來建立不同面向之讀書會領導功能模型,並針對讀書會召集人領導功能、讀書會未來發展方向提出結論及建議,供讀書會及各相關單住參考。
本論文結論重點為:一、讀書會是否成立為法人、繳費多寡,和讀書會經營成敗無關,最重要是讀書會能給會員什麼收穫。二、不同發展階段有不同領導功能特色及重點,領導功能可概分為決策、影響力、建立關係、取給資訊和權變等五種面向,其中權變領導為核心。三、領導功能有智慧面及知識面,二者相輔相成,相互為用。四、讀書會可參與社區議題和公共政策,促進社群意識,建立公民社會。
建議重點為:一、讀書會會員應以「自我導向學習」(self-direction learning)來參加讀書會,達成終身學習、豐裕心靈。二、讀書會召集人日久可能有倦怠現象,應培養接班人,使讀書會能薪火相傳,永續發展。三、讀書會應尋求市場區隔,結合社會資源,配合社會發展,尋找讀書會定位及舞台。四、讀書會可辦理新生訓練、發行出版品、辦理各種活動等方式,提昇會員社會化程度及組織凝聚力。五、召集人應加強領導管理智能及人文素養,有如領航人,帶領讀書會邁向新世代。六、轉換型領導、服務型領導是較適於讀書會召集人運用的領導類型。七、政府輔導讀書會政策應有一貫性,不要人去政息。入、政府應協助成立讀書會資源中心,整合各種資源經驗,促進讀書會發展。
關鍵詞:讀書會、召集人、自我導向學習、轉換型領導、服務型領導。 / Study Circles are voluntary groups until registered formally in which case they are called non-profit organizations. Taking a view backward, the development of study circles in Taiwan was triggered by“Mama chong diann hwei”in Taipei and“Yang farn juu fuh sheh”in Kaohsiung. Since the remoal the Martial law and the promotion of cormnunitarialism and feminism in Taiwan, study circles have progressed steadily until today. According to statistics printed by the 5th National Study Circles Fair in October 2001, the number of Study Circles in Taiwan has reached 1,912.
Though the number is encouraging, we found that a great deal of study circles have disbanded, stopped activities or replaced their original goals. Though the bubble-phenomenon regarding study circles is worthy of research and observation, generally speaking, the development of study circles has typically followed 4 stages: preparation, development, fatigue and maturation. During the development process, if particular study circles can't pass through the fatigue stage, they will usually dissolve very soon, normally not lasting for longer than half year. Though some study circles are like bubbles, there are also a lot of study circles that have existed more than 10 years, have more than 50 members (some more than 200 members), and continue to be more stable and reputable. It seems that the leadership and management of study circles' conveners is directly related to the success of the organizations. This tendency has become the theme to be further researched by this study.
In USA, there were 500,000 study circles in 1997. In Sweden, there were 350,000 study circles In 1996. Presently, there are 1,912 study circles in Taiwan with about 23 million population Compared to the USA and Sweden, the participation rate is quite low. During this“life-long” learning age, there is quite a bit of latitude in regards to the development of study circles.
This thesis used "documentary-type methods" ,"in depth interviews" , "comparative study" and "focus group" styles to try to establish various leadership models such as "different development stage leadership model", "Yuki's valid leadership behavior model" and "Yin-and promote their respective study circles.
The conclusion is 1.The member fees and official registration of study circles do not determine the success of a study circle versus what the study circle can give to the members. 2.Different stages need different leadership, leadership includes decision making, influence, relations, information and contingency. Contingency leadership is the center of all leadership. 3.Leadership has the dual dimensions of wisdom and knowledge , those two help and engender each other. 4.Study circles can participate in community issues and public policies to help establish a more civil society.
The suggestions are 1.The members of the study circles should base themselves on "self-directional learning" to participate and target "life long" learning. 2. The conveners of the study circles have the phenomenon of exhaustion, the study circles should cultivate suitable members to take over the role of leaders to progress the study circles. 3.The study circles should choose their market segment, follow the development of the society, and find their own performing stage. 4.The study circles can organize new member training programs, publishing books and another activities to upgrade the cohesion of study circles. 5. The conveners of the study circles should improve their leadership and knowledge to lead the organization to walk into the new age. 6.Transformational leadership and servant leadership are more appropriate style for study circles' conveners. 7.The government's policy of sponsoring the study circles should be maintained to help develop the study circles. S.The government should help to establish a study circle resource center to promote the progress of the study circles on a national front.
Key words: study circles; conveners; self-direction learning;transformational leadership; servant leadership.
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Design av en digital utbildningsmodul med kristermer på svenska och norska : Hur utformas utvärdering av lärande? / Design of a digital ecucation modele with crisis terms in Swedish an Norwegian : How to design evaluation of learning?Norén Persson, Erika January 2018 (has links)
CriseIT är ett projekt som arbetar med att bidra till god krisberedskap genom att skapa mindre gränsregionala hinder i krisövningar över den svenska och norska gränsen mellan Värmland och Hedmarks Fylke. I tidigare krisövningar över gränsen har det varit tydligt att det uppstår språkliga barriärer. Därför har en parlör tagits fram i syfte att överbrygga dessa hinder. Syftet med detta arbete i att designa en digitalt utbildningsmodul är att ta reda på hur man kan lägga upp en utbildning som hjälper användaren i att öva på svenska och norska kristermer. Det kan vara genom att lära sig ord utantill eller genom att öva på att söka på ord och begrepp i parlören. Som metod användes ett pilottest med 11 deltagare från området krisledningsövning av en prototyp innehållande ett par olika typer av ordinlärningsfrågor samt ett kortare frågeformulär. Pilottestet gjordes på distans via det webbaserat systemet Ozlab. Upplägget av frågorna i utbildningsdelen i pilottestet fungerar övervägande bra som ett sätt att lära sig ord och som en övning i att leta på ord och begrepp i ordlistan. I slutsatserna diskuteras lämpligt LMS (Learning Management System) för en sådan utbildningsmodul. Testpersonernas kommentarer var övervägande positiva kring parlören och att hitta svar i den till utbildningsmodulen. Bland de brister som uppmärksammades var själva sökfunktionen i den pdfbaserade parlören. Det ges även synpunkter kring utveckling av parlören.
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Academic staff perception of performance management : a case study of an open distance learning institutionMaimela, Esther Matsetselane 11 1900 (has links)
Higher education institutions (HEIs) are now adopting the management styles that are being practised in profit-making organisations in the private sector. The top management in HEIs embark on monitoring performance of all categories of their employees, including academic staff. This has become necessary in order to encourage and enhance quality in teaching and also to achieve increased research productivity. This means that the same principles involved in managing the private sector, such as introducing performance management systems, are now applied in the public sector. Empirical evidence from previous studies suggests that the introduction and implementation of performance management systems in academic institutions often result in tension between academic employees and management, thereby heightening the age-long debate on the necessity for academic freedom in institutions of higher learning globally.
The present study evaluated the perception of academic staff members regarding the implementation of a performance management system in an open distance learning institution in South Africa. The study adopted a survey research design, using a quantitative research approach. The total sample of the study comprised of 492 academic staff members of the institution. A structured self-administered web-based questionnaire that was tested for high reliability and validity content was used to collect primary data from the respondents. The data were analysed using both descriptive and inferential (one-way sample t-test) statistics. The research findings indicate that academic staff members at the institution are satisfied with the performance management system implemented by management. The study further found that academics do not consider the resultant performance bonus from the implementation of the performance management system sufficiently motivating and that it should therefore be reviewed by management. Overall, the outcome of the present study was to a large extent inconsistent with the empirical evidence presented by previous studies. / Business Management / M. Com. (Business Management)
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Research of Left Ventricular Segmentation on Two-dimensional Ultrasound Images Based on Different Deep Learning Models : master's thesisЛи, Б., Li, B. January 2024 (has links)
В последние годы распространенность сердечно-сосудистых заболеваний, а также уровень смертности растет, что серьезно угрожает здоровью человека, что требует от врачей ранней диагностики сердечно-сосудистых заболеваний, чтобы выиграть время для последующего лечения пациентов, а результаты сегментации ультразвуковых изображений левого желудочка могут помочь врачам в диагностике сердечно-сосудистых заболеваний, но ультразвуковые изображения левого желудочка имеют характеристики сильного шума, слабых границ и сложной структуры ткани, что делает сегментацию изображения сложной, низкой эффективностью и плохой точностью. Одним из важнейших этапов оценки здоровья сердца является отслеживание и сегментация эндокардиальной границы левого желудочка (ЛЖ) с помощью ЭхоКГ, которая используется для измерения фракции выброса и оценки движения региональной стенки. Недостатком этих методов является необходимость применения обработки изображений вручную или в полуавтоматическом режиме, что требует специальных знаний и навыков. В результате вопрос автоматического отслеживания и сегментации ЛЖ на ЭхоКГ-изображениях является актуальной и практической проблемой. В моем проекте изучается способность полностью обученных моделей глубокого обучения U-Net, U-Net++, MANet, LinkNet, FPN, PSPNet, PAN, DeepLabv3 и DeepLabv3+ автоматически определять область левого желудочка. В то же время в архитектурах U-Net, U-Net++, MANet, LinkNet, PSPNet, PAN, FPN, DeepLabv3 и DeepLabv3+ модули кодировщика затем последовательно заменялись на ResNet18, ResNet34, ResNet5, ResNet101, EfficientNet-b0, EfficientNet-b1, EfficientNet-b3, EfficientNet-b5, EfficientNet-b7 и MobileNetv2, а ImageNet использовался в качестве весов предварительной подготовки; Добавление магистральных сетей в архитектуру модели приводит к более высокой точности сегментации по сравнению с исходной моделью. В рамках той же архитектуры модели EfficientNet в качестве кодировщика достигает лучших результатов сегментации, а EfficientNet-b3 работает лучше. Аналогично, в рамках серии ResNet ResNet34 работает лучше. В модели сегментации этого эксперимента Deeplabv3+ показывает превосходную производительность. Это указывает на то, что в архитектуре модели этого эксперимента интеграция модулей ResNet34 и EfficientNet-b3 в качестве кодировщиков может эффективно и осуществимо автоматизировать распознавание эндокардиальной границы левого желудочка на ультразвуковых изображениях. Кроме того, аугментация данных также в определенной степени повысит точность сегментации модели. / In recent years, the prevalence of cardiovascular diseases. as well as the mortality rate is increasing, which has seriously threatened human health, which requires doctors to diagnose cardiovascular diseases early to gain time for patients' later treatment, and the segmentation results of left ventricular ultrasound images can assist doctors in the diagnosis of cardiovascular diseases, but the left ventricular ultrasound images have the characteristics of strong noise, weak edges and complex tissue structure, which makes the image segmentation difficult, low efficiency and poor precision. One of the most important steps in estimating the health of the heart is the tracking and segmentation of the left ventricular (LV) endocardial border from EchoCG, which is used for measuring the ejection fraction and assessing the regional wall motion. The disadvantage of these methods is the necessity to apply image processing manually or in a semi-automatic mode, which requires special knowledge and skills. As a result, the issue of an automatic tracking and segmentation of the LV on EchoCG-images is an actual and practical problem. In my project, the ability of fully trained Deep Learning Models U-Net, U-Net++, MANet, LinkNet, FPN, PSPNet, PAN, DeepLabv3and DeepLabv3+ to automatically identify the left ventricular region is explored. At the same time, in the U-Net, U-Net++, MANet, LinkNet, PSPNet, PAN, FPN, DeepLabv3 and DeepLabv3+ architectures, the encoder modules were then sequentially replaced with ResNet18, ResNet34, ResNet5, ResNet101, EfficientNet-b0, EfficientNet-b1, EfficientNet-b3, EfficientNet-b5, EfficientNet-b7and MobileNetv2, and ImageNet was used as the pre-training weights; The addition of backbones to the model architecture leads to higher segmentation accuracy compared to the original model. Within the same model architecture, EfficientNet as the encoder achieves better segmentation results, with EfficientNet-b3 performing the best. Similarly, within the ResNet series, ResNet34 performs better. In the segmentation model of this experiment, Deeplabv3+ shows superior performance. This indicates that in the model architecture of this experiment, integrating ResNet34 and EfficientNet-b3 modules as encoders can effectively and feasibly automate the recognition of the endocardial boundary of the left ventricle in ultrasound images. Furthermore, data augmentation will also enhance the model’s segmentation accuracy to a certain extent.
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