يعرض 1 - 20 نتائج من 26 نتيجة بحث عن '"类实验"', وقت الاستعلام: 0.45s تنقيح النتائج
  1. 1
    Academic Journal

    المؤلفون: 张旭, 刘炳峰

    المصدر: Zhongshan Daxue xuebao. Yixue kexue ban, Vol 45, Pp 511-518 (2024)

    وصف الملف: electronic resource

  2. 2
  3. 3
    Dissertation/ Thesis
  4. 4
    Academic Journal
  5. 5
    Academic Journal

    المؤلفون: 夏希原

    المساهمون: 北京大学社会学系

    المصدر: 知网

    Relation: 北京大学研究生学志.2012,(Z1),126-130.; 1111619; http://hdl.handle.net/20.500.11897/28897

  6. 6
    Academic Journal

    المؤلفون: 孙昕雵, 郭岩, 汪思顺, 孙静

    المساهمون: 北京大学公共卫生学院社会医学与健康教育系,北京,100083, 北京大学医学部公共卫生学院卫生政策与管理学系,北京,100083, 贵州省疾病预防控制中心卫生监测检所,贵州,贵阳,550004, 中国疾病预防控制中心营养与食品安全所,北京,100050

    Relation: 中国健康教育.2007,23,(8),563-566,578.; 1173996; http://hdl.handle.net/20.500.11897/274090

  7. 7
    Academic Journal
  8. 8
    Academic Journal
  9. 9
    Academic Journal
  10. 10
    Academic Journal

    المؤلفون: 冯小兵, 章立源, 孙久勋

    المساهمون: 北京大学物理系

    المصدر: 知网

    Relation: 物理学报.1997,(03),181-188.; 1044226; http://hdl.handle.net/20.500.11897/88297

  11. 11
    Report

    المؤلفون: 马陶武, 王子健

    Relation: 环境科学学报; 马陶武;王子健.环境内分泌干扰物筛选和测试研究中的鱼类实验动物,环境科学学报,2005,1(2):135-142; http://ir.rcees.ac.cn/handle/311016/11542

  12. 12
    Dissertation/ Thesis

    المؤلفون: 林廷怡

    المساهمون: 醫務管理系, 吳世望

    مصطلحات موضوعية: 本研究主要對象與目的為以南部地區某大專校院教職員生為研究調查對象,了解其身體組成包含體重、體脂肪、身體質量指數(BMI)及健康行為自我效能包含營養、運動、心理安適及健康責任等四個層面之現況,以及實施有氧舞蹈運動後對其身體組成以及健康行為自我效能之影響。本研究方法為類實驗型研究,以60 位教職員生為研究對象,依其意願分配到實驗組及對照組各30 名。實驗組接受六週,每週2次,每次1小時的有氧舞蹈運動,對照組則維持正常作息,二組受試者在實驗前後均接受體重、體脂肪以及身體質量指數(BMI)量測,並填寫健康行為自我效能問卷,將回收問卷及參與實驗成員之各項指標數據,進行描述性分析、獨立t檢定、成對t檢定、單因子變異數分析,以及皮爾森積差相關等統計分析。結果驗證,此一單一策略,有氧舞蹈運動的介入,對大學教職員生體重、體脂肪以及健康行為自我效能有改善之效益,但身體質量指數則無顯著差異。本研究結果可作為相關領域推動健康促進計畫之參考,並可與複合式健康促進策略所帶來的效益作一比較,以權衡選擇各場域合適所需的方案。, This thesis is aimed at faculty and students in a university in the southern region of Taiwan, and the purpose of major is to understand the body composition including body weight, body fat, body mass index (BMI) and health behavioral self-efficacy, which includes four levels as nutrition, exercise, psychological comfort and health responsibility. Meanwhile, the author explored the effects of aerobic dance exercise on body composition and self-efficacy of healthy behavior. The method used in this study is Quasi-Experimental Design, which is based on 60 faculty members and are assigned to 30 experimental and control groups as their willingness. The experimental group received a total of six weeks, twice a week, one hour of aerobic dance, while the control group maintained normal routine. Both groups received measurements of body weight, and body mass index (BMI) before and after the experiment, and asked them to fill out the Health Behavior Self-Efficacy Questionnaire. The researchers have collected the questionnaire and conducted descriptive analysis, independent t-test, paired t-test, one-way analysis of variance, and Pearson product-moment correlation for the data of the participating members. The results of the data validation indicate that this single strategy, the intervention of the aerobic dance movement, has improved outcomes for university faculty and learners' body weight, and healthy behavioral self-efficacy. However, there is no significant difference in body mass index between the methods. The results of this study can be integrated as a reference for promoting health programs in related fields and can be compared to the benefits of a composite health promotion strategy to balance the optimal options needed to be selected in each field, 健康促進, 身體組成, 有氧舞蹈運動介入, 健康行為自我效能, health promotion, aerobic dance intervention, body composition

    وصف الملف: 102 bytes; text/html

    Relation: 電子全文公開日期:2024-08-26; 學年度:107,99頁; https://ir.cnu.edu.tw/handle/310902800/33104; https://ir.cnu.edu.tw/bitstream/310902800/33104/1/index.html

  13. 13
  14. 14
    Dissertation/ Thesis
  15. 15
    Dissertation/ Thesis
  16. 16
    Dissertation/ Thesis
  17. 17
    Dissertation/ Thesis

    المؤلفون: 吳岳勳, Wu, Yueh Hsun

    المساهمون: 楊立行, Yang, Lee Xieng

    Relation: Anderson, A., Ross, B., & Chin-Parker, S. (2002). A further investigation of category learning by inference. Memory & Cognition, 30(1), 119-128.\nAshby, F. G., & Alfonso-Reese, L. A. (1995). Categorization as Probability Density Estimation. Journal of Mathematical Psychology, 39(2), 216-233.\nAshby, F. G., & Gott, R. E. (1988). Decision rules in the perception and categorization of multidimensional stimuli. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(1), 33-53.\nAshby, F. G., & Lee, W. W. (1991). Predicting similarity and categorization from identification. Journal of Experimental Psychology: General, 120(2), 150-172.\nAshby, F. G., Maddox, W. T., & Bohil, C. (2002). Observational versus feedback training in rule-based and information-integration category learning. Memory & Cognition, 30(5), 666-677.\nBrown, G. D. A., Neath, I., & Chater, N. (2007). A temporal ratio model of memory. Psychological Review, 114(3), 539-576.\nCarey, S. (1987). Conceptual change in childhood. Cambridge, MA: MIT Press.\nCohen, A., Nosofsky, R., & Zaki, S. (2001). Category variability, exemplar similarity, and perceptual classification. Memory & Cognition, 29(8), 1165-1175.\nEstes, W. K. (1986). Array models for category learning. Cognitive Psychology, 18(4), 500-549.\nFried, L. S., & Holyoak, K. J. (1984). Induction of category distributions: A framework for classification learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10(2), 234-257.\nHsu, A. S., & Griffiths, T. L. (2010). Effects of generative and discriminative learning on use of category variability. Proceedings of 32nd Annual Conference of the Cognitive Science Society.\nKeil, F. C. (1989). Concepts, kinds, and conceptual development: Cambridge, MA: MIT Press.\nKomatsu, L. K. (1992). Recent views of conceptual structure. Psychological Bulletin, 112(3), 500-526.\nKruschke, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning. Psychological Review;Psychological Review, 99(1), 22-44.\nLockhead, G. R. (1966). Effects of dimensional redundancy on visual discrimination. Journal of Experimental Psychology, 72(1), 95-104.\nLove, B. C., Medin, D. L., & Gureckis, T. M. (2004). SUSTAIN: A Network Model of Category Learning. Psychological Review;Psychological Review, 111(2), 309-332.\nMaddox, W. T., & Ashby, F. G. (1993). Comparing decision bound and exemplar models of categorization. Attention, Perception, & Psychophysics, 53(1), 49-70.\nMaddox, W. T., Molis, M., & Diehl, R. (2002). Generalizing a neuropsychological model of visual categorization to auditory categorization of vowels. Attention, Perception, & Psychophysics, 64(4), 584-597.\nMarkman, A. B., & Ross, B. H. (2003). Category use and category learning. Psychological Bulletin, 129(4), 592-613.\nMedin, D. L. (1989). Concepts and conceptual structure. American Psychologist; American Psychologist, 44(12), 1469.\nMedin, D. L., Goldstone, R. L., & Gentner, D. (1993). Respects for similarity. Psychological Review, 100(2), 254-278.\nMedin, D. L., & Schaffer, M. M. (1978). Context theory of classification learning. Psychological Review, 85(3), 207-238.\nNosofsky, R. M. (1986). Attention, similarity, and the identification–categorization relationship. Journal of Experimental Psychology: General, 115(1), 39-57.\nNosofsky, R. M., Palmeri, T. J., & McKinley, S. C. (1994). Rule-plus-exception model of classification learning. Psychological Review, 101(1), 53-79.\nPalmeri, T. J., & Nosofsky, R. M. (1995). Recognition memory for exceptions to the category rule. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(3), 548-568.\nPosner, M. I., Boies, S. J., Eichelman, W. H., & Taylor, R. L. (1969). Retention of visual and name codes of single letters. Journal of Experimental Psychology, 79(1, Pt.2), 1-16.\nReed, S. K. (1972). Pattern recognition and categorization. Cognitive Psychology, 3(3), 382-407.\nRips, L. J. (1989). Similarity, typicality, and categorization. In S. Vosniadou & A. Ortony (Eds.), Similarity and analogical reasoning. (pp. 21-59): New York, NY, US: Cambridge University Press.\nRips, L. J., & Collins, A. (1993). Categories and resemblance. Journal of Experimental Psychology: General, 122(4), 468-486.\nRoss, B. H., & Murphy, G. L. (1996). Category-based predictions: Influence of uncertainty and feature associations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(3), 736-753.\nSakamoto, Y., Love, B. C., & Jones, M. (2006). Tracking Variability in Learning: Contrasting Statistical and Similarity-Based Accounts. Proceedings of Cognitive Science Society, Mahwah, NJ.\nShepard, R. N. (1964). Attention and the metric structure of the stimulus space. Journal of Mathematical Psychology;Journal of Mathematical Psychology, 1(1), 54-87.\nSmith, E. E., Langston, C., & Nisbett, R. E. (1992). The case for rules in reasoning. Cognitive Science, 16(1), 1-40.\nSmith, E. E., & Medin, D. L. (1981). Categories and concepts. Cambridge, MA: Harvard University Press \nSmith, E. E., & Sloman, S. (1994). Similarity- versus rule-based categorization. Memory & Cognition, 22(4), 377-386.\nSteinberg, J. C. (1937). Positions of Stimulation in the Cochlea by Pure Tones. The Journal of the Acoustical Society of America, 8(3), 176-180.\nStevens, S. S., Volkmann, J., & Newman, E. B. (1937). A scale for the measurement of the psychological magnitude pitch. Journal of the Acoustical Society of America, 8, 185-190.\nStewart, N., & Chater, N. (2002). The effect of category variability in perceptual categorization. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28(5), 893-907.; G0099752003; https://nccur.lib.nccu.edu.tw//handle/140.119/56875; https://nccur.lib.nccu.edu.tw/bitstream/140.119/56875/-1/200301.pdf

  18. 18
    Dissertation/ Thesis
  19. 19
    Dissertation/ Thesis
  20. 20
    Academic Journal

    المؤلفون: 应礼文, 胡学复, 庄守端

    المساهمون: 北京大学化学系

    المصدر: 知网

    Relation: 化学教育.1980,(02),41+12.; 1016346; http://hdl.handle.net/20.500.11897/80929