Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A Digital Nervous System for Elementary Statistics Education in the Mobile Age: SmartNote

모바일시대의 기초통계학 교육용 디지털 신경시스템: SmartNote

  • Received : 20110400
  • Accepted : 20110400
  • Published : 2011.05.31
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Abstract

Many students in introductory statistics courses do not engage in learning under traditional classroom settings. A statistics instructor is often irritated by student behaviors such as sleeping, talking out of place, and acting bored or apathetic during lectures. The lecture and exercises in the computer laboratory should constantly compete with materials via the Internet to draw the attention of the student. To address problems in statistics education, we propose a digital nervous system in which a teacher and students can communicate with each other.

전통적인 강의실의 기초통계학 수업에서 많은 학생들이 수업에 집중하지 못하고 있다. 수업 시간에 졸거나, 잡담하거나, 휴대폰을 만지작거리면서 다른 생각에 잠겨 있다. 인터넷이 가능한 컴퓨터실에서의 강의와 실습은 인터넷이 제공하는 콘텐츠와 부단히 경쟁을 해야 한다. 이러한 문제를 조금이나마 해결해 보려고 시도한 방안이 교수와 학생을 하나의 유무선 네트워크로 묶는 교육용 디지털 신경시스템 하에서 기초통계학을 가르치고 학생들이 공부하게 하자는 것이다.

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References

  1. Anderson, D. R., Sweeney, D. J. and Williams, T. A. (2007). Statistics for Business and Economics, 류귀열 등역, 한올출판사.
  2. Bloom, B. S. (1968). Learning for mastery, Evaluation Comment, 1, 1-2.
  3. Bloom, B. S. (1976). Human Characteristics and School Learning, McGraw-Hill, New York.
  4. Dryver, A. (2009). The enhancement of teaching materials for applied statistics courses by combining random number generation and portable document format files via LATEX, Journal of Statistical Software, 31, 1-9.
  5. Guskey, T. R. (2007). Closing achievement gaps: Revisiting Benjamin S. Bloom's learning for mastery, Journal of Advanced Academics, 19, 8-31. https://doi.org/10.4219/jaa-2007-704
  6. Lalonde, R. N. and Gardner, R. C. (1993). Statistics as a second language? A model for predicting performance in psychology students, Canadian Journal of Behavioral Science, 25, 108-125. https://doi.org/10.1037/h0078792
  7. Lass, D., Morzuch, B. and Rogers, R. (2007). Teaching with technology to engage students and enhance learning, University of Massachusetts Amherst Working Paper No., 2007-1.
  8. Mann, P. S. (2010). Introductory Statistics, 7th Edition, Wiley.
  9. Mills, J. D. (2004). Students' attitudes toward statistics: Implications for the future, College Student Journal, 38, 349-361.
  10. Moore, D. S. (1997). New pedagogy and new content: The case of statistics, International Statistical Review, 65, 123-165. https://doi.org/10.1111/j.1751-5823.1997.tb00390.x
  11. Mun, G. S. (2011). On Developing an Integrated Teaching and Learning Environment Providing a Bridge between Research Findings and Teaching Practice in Statistics Education, PhD thesis, Chonbuk National University, Available from: http://www.stat.auckland.ac.nz/ iase/publications/dissertations/11.Mun.Dissertation.pdf
  12. Onwuegbuzie, A. J., Slate, J. R., Paterson, F. R. A., Watson, M. H. and Schwartz, R. A. (2000). Factors associated with achievement in educational research courses, Research in the Schools, 7, 53-65.
  13. Retkute, R. (2009). Exploring technology-based continuous assessment via electronic voting systems in mathematics and statistics, MSOR Connections, 9, 24-28.
  14. Zanakis, S. H. and Valenzi, E. R. (1997). Student anxiety and attitudes in business statistics, Journal of Education for Business, 73, 10-16. https://doi.org/10.1080/08832329709601608