New Technologies, Software, and e-Learning – Enriching Courses in Introductory Statistics and Probability

Yıl 2017, Cilt: 1 Sayı: 2, 62 - 78, 29.12.2017

Manfred Borovcnık

Öz

New Technologies changed the applications of
statistics completely so that more statistics is applied nowadays than 25 years
ago, which generates a need for a wider education in statistics even at an
introductory level. At the same time, these technologies open the way to teach
the subject matter of statistics completely differently than in the
pre-computer era. We illustrate various approaches of technology-based teaching
and identify key issues for their success. Large-scale e-learning projects,
locally organised computer-based learning environments, and additional applets
used to illustrate complex concepts, calculations outsourced to software are
some of the many options to enrich the statistics course. The recommendations are
for students of non-mathematical studies. The future class at university
includes a diversity of information sources and a new role for academic
teachers as organisers of the work in small groups rather than communicating
the content in a big lecture hall. We illustrate the potential of systemic
solutions for an introductory course in probability and statistics by a general
discussion and by the extensive and long-term feedback from our own students.

Anahtar Kelimeler

Success criteria for e-learning, Feedback for students, Exemplary solutions to tasks

Kaynakça

• [1] C. Batanero, M. Borovcnik, “Statistics and Probability in High School”, Sense Publishers, Rotterdam (2016).
• [2] M. Borovcnik, “The Influence of Software Support on Stochastics Courses”, Edited M. I. Gomes, J. A. Pinto Martins and J. A. Silva, Bulletin 56. Session of the International Statistical Institute (ISI), ISI, Voorburg, (2007), pp. 4602-4605.
• [3] M. Borovcnik, “New Technologies Revolutionize the Applications of Statistics and its Teaching”. Edited M. I. Gomes, J. A. Pinto Martins and J. A. Silva, Bulletin 56. Session of the International Statistical Institute (ISI), ISI, Voorburg, (2007), pp. 823-826.
• [4] M. Borovcnik, “Key Properties and Central Theorems in Probability and Statistics – Corroborated by Simulations and Animations”, Selçuk Journal of Applied Mathematics. Special Issue of Statistics, (2011), pp. 3-19.
• [5] M. Borovcnik, R. Kapadia, “Modelling in Probability and Statistics – Key Ideas and Innovative Examples”, Edited J. Maaß, J. O’Donoghue, Real-World Problems for Secondary School Students – Case Studies, Sense Publishers, Rotterdam (2011).
• [6] B. Chaput, “An Organizational Memory as Support of Learning in Applied Mathematics”, Edited M. I. Gomes, J. A. Pinto Martins and J. A. Silva, Bulletin 56. Session of the International Statistical Institute (ISI), ISI, Voorburg, (2007), pp. 808-812.
• [7] K. Cramer, U. Kamps, C. Zuckschwerdt, St Apps and EMILeA-Stat: “Interactive Visualizations in Descriptive statistics”, Edited J. Antoch, Proceedings in Computational Statistics, Physica, Heidelberg, (2004), pp. 101-112.
• [8] C. Duller, „Einführung in die Statistik mit Excel und SPSS“, Physica, Heidelberg, (2007).
• [9] EMILeA, „Eine multimediale, internetbasierte, interaktive Lehr- und Lernumgebung in der angewandten Statistik“, Online: www.emilea.de/, (n.d.).
• [10] M. Esfandiari, M., H. Nguyen, Y. Yaglovskaya, R. Gould., “Enhancing Statistical Literacy through Short Open-Ended Questions that Involve Context, Data, and upper Level Thinking”, Edited C. Reading, Data and Context in Statistical Education: Towards an Evidence-based Society, ISI, Voorburg, (2010).
• [11] GMW. Gesellschaft für Medien in der Wissenschaft, „Medidaprix“, (n.d.).
• [12] M. I. Gomes, J. A. Pinto Martins and J. A. Silva, “Bulletin 56. Session of the International Statistical Institute (ISI)”, ISI, Voorburg, (2007).
• [13] R. Gould, “Statistics Online Computational Resource (SOCR). Visualisation of the Normal Distribution”, Online: socr.stat.ucla.edu/htmls/SOCR_Distributions.html, (n.d.).
• [14] W. Härdle, S. Klinke, and U. Ziegenhagen, “On the Utility of e-Learning in Statistics”, International Statistical Review, vol 75, no. 3, (2007), pp. 355–364.
• [15] W. Härdle, S. Klinke, & U. Ziegenhagen, “e-Learning Statistics – A Selective Review”, SFB 649 Discussion Paper 2006-024, Humboldt University, Berlin (2006).
• [16] L. Johnson, S. Adams Becker, M. Cummins, V. Estrada, A. Freeman, A., C. Hall, “NMC Horizon Report: 2016 Higher Education Edition”. Austin, Texas: The New Media Consortium. (2016), Online: cdn.nmc.org/media/2016-nmc-horizon-report-he-EN.pdf.
• [17] D. Moore, S. Braun, J. Blatt, P. Girshman, J. Singer, J. Rubin, S. Stewart, D. Huntley, R.Buderi, “Against all Odds: Inside Statistics”, (1995), Online: www.learner.org/courses/againstallodds/unitpages/index.html.
• [18] M. Mougeot, “Impact of New Technologies for Teaching Statistics”. Edited M. I. Gomes, J. A. Pinto Martins and J. A. Silva, Bulletin 56. Session of the International Statistical Institute (ISI), ISI, Voorburg, (2007), pp. 813-816.
• [19] D. Nolan; D. Temple Lang, “Dynamic, Interactive Documents for Teaching Statistical Practice”, International Statistical Review, vol. 75, no. 3, (2007), pp. 295–321.
• [20] G. Schuyten and O. Thas, “Statistical Thinking in computer-Based Learning Environments”, International Statistical Review, vol. 75, no. 3, (2007), pp. 365–371.
• [21] H. Tamura, “Foundational Value of Statistics Education for Management Curriculum”, International Statistical Review, vol. 75, no. 3, (2007), pp. 397–405.
• [22] The Chronicle of Higher Education, “The Minds behind the MOOCs”, Online: chronicle.com/article/The-Professors-Behind-the-MOOC/137905/?cid=at&utm_source=at&utm_medium=en#id=overview, (n.d.).
• [23] B.Ward, “The Best of both Worlds: A Hybrid Statistics Course”, Journal of Statistics Education, vol 12, no. 3, (2004), pp. 74–79.
• [24] C. Wild, “Virtual Environments and the Acceleration of Experiential Learning”, International Statistical Review, vol. 75, no. 3, (2007), pp. 322–335.