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Author(s):  
Aneta Mazouchová ◽  
Tereza Jedličková ◽  
Lucie Hlaváčová

This paper aims to reveal the beliefs of students and fresh university graduates about teaching statistics during their university studies with focus on using statistical software. The objective is to detect the approach of faculties to statistics education and to find out which didactic materials and teaching methods are mainly used. Students’ opinions are captured by means of a questionnaire survey and analysed both quantitatively and qualitatively. The results show the increasing importance of quantitative research and the necessity of improving statistical thinking. Unfortunately, the teaching methods used in various statistical courses are outdated and unattractive for most students. They call for an active and modern approach. Teaching statistics with the statistical software support seems to be the right way to make statistics accessible to students. The recommendation is to take students’ notions into account when preparing statistical courses.


CHANCE ◽  
2021 ◽  
Vol 34 (4) ◽  
pp. 30-33
Author(s):  
Carol Bigelow ◽  
Amy S. Nowacki

2021 ◽  
pp. 1-5
Author(s):  
Cosima Meyer

ABSTRACT This article introduces how to teach an interactive, one-semester-long statistics and programming class. The setting also can be applied to shorter and longer classes as well as introductory and advanced courses. I propose a project-based seminar that also encompasses elements of an inverted classroom. As a result of this combination, the seminar supports students’ learning progress and also creates engaging virtual classes. To demonstrate how to apply a project-based seminar setting to teaching statistics and programming classes, I use an introductory class to data wrangling and management with the statistical software program R. Students are guided through a typical data science workflow that requires data management and data wrangling and concludes with visualizing and presenting first research results during a simulated mini-conference.


Author(s):  
George A. Mangiero ◽  
Arif Qayyum ◽  
Charles J. Cante
Keyword(s):  

2021 ◽  
Vol 7 (3) ◽  
pp. 852-871
Author(s):  
Zeynep Medine Özmen ◽  
Adnan Baki

The present study aimed to investigate the statistical literacy perceptions of instructors who teach undergraduate statistics courses in different disciplines. Instructors were asked questions on their statistical literacy definitions, organization of the course content, topics emphasized or avoided by instructors in teaching statistics, and instructors post-course expectations from their students. Qualitative data gathered from interviews were analyzed and categorized under five main themes. The instructors' ultimate expectations from the students and the topics they emphasized during the courses are mostly stated in relation with statistical literacy.  They provided less information related statistical literacy about two themes: course content and the issues they avoid. Recommendations from this study include reviewing and revising statistics course content and methods to reveal the components of statistical literacy.


2021 ◽  
Vol 3 (2) ◽  
pp. 63-74
Author(s):  
Diego Alonso Villegas Zamora

Anderson, D.; Sweeney, D. & Williams, T (2008). Estadística para administración y economía. 0 ed. México. Cengage Learning Azcárate, P. (2006). ¿Por qué no nos gusta enseñar estadística y probabilidad? Conferencia realizada en XII, Jornadas  de  Investigación en el Aula de Matemáticas: Estadística y azar, Granada, España Batanero, C. (2002a). Los retos de la cultura estadística, Jornadas interamericanas de enseñanza de la estadística, Buenos Aires, conferencia inaugural Batanero, C.  (2002b).  Estadística  y  didáctica  de  la  matemática:   Relaciones,   problemas  y aportaciones mutuas. En M. Penalva, G. Torregrosa y J. Valls (Coords.). Aportaciones de la didáctica de la Matemática a diferentes perfiles profesionales (pp. 95-120). Murcia: Editorial Compobell Batanero, C. (2005). Significados de la probabilidad en la educación secundaria. Revista Latinoamericana de Investigación en Matemáticas, 8(3), 247-264 Batanero, C., Godino, J. D., Green, D. R., Holmes, P & Vallecillos, A. (1994). Errors and difficulties in understanding elementary statistical concepts. International Journal of Mathematics Education in Science and Technology, 25(4), 527-547 Behar, R. & Ojeda, M. (2000). El proceso de aprendizaje de la estadística: ¿Qué puede estar fallando? Heurística, 10, 26-43 Blalock, H. M. (1998). Estadística social. México. FCE. 6” reimpresión Casas-Sánchez, J. M. & Santos-Peñas, J. (2002). Introducciónalaestadísticaparaadministración y dirección de empresas segunda edición DeGroot, M. H. (2012). Probability and statistics. Pearson DeGroot, M. H., & Fienberg, S. E. (1981). Assessing Probability Assessors: Calibration and Refinement. CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF STATISTICS   Easterby-Smith, M., Thorpe, R., Jackson, P.  R.,   & Jaspersen, L. J. (2018). Management and business research. Sage Friz, C. M.; Sanhueza, H. S. & Figueroa, M. E. (2011). Concepciones de los estudiantes para profesor de Matemáticas sobre las competencias profesionales implicadas en la enseñanza de la Estadística. Revista electrónica de investigación educativa, 13(2), 113-131 Gómez, L. (2013). Diseño de un sistema de información de marketing. Tesis para optar por el título de Máster en Dirección, Universidad de La Habana. 2008. [2]. s/a, (2013). Los sistemas de Marketing, Recuperado el 2013, de cvh. ehu.es: http://cvb.ehu.es/open_course_ware/ castellano/social_juri /marketing/tema-5/ tema-5.pdf Holmes, P. (1980). Teaching Statistics, 11-16. Sloug: Foulsham Educational Lent, B., Dost, S., Redden, R. F., & Liu, Y. (2002). Mathematical simulation of the traveling heater method growth of ternary semiconductor materials under suppressed gravity conditions. Journal of crystal growth, 237, 1876-1880 Mood, A.M. & Graybill, E.A, (1972). Introducción a la teoría estadística. México Moreno, J.L. (1998), “Statistical Literacy. Statistics Long after School”, en L., Pereira- Mendoza et al. (ed.), Proceedings of the 5th International Conference on Teaching Statistics, Singapur, pp. 447-452 Muñoz, E. D. (2007). El aprendizaje de la estadística en estudiantes universitarios de profesiones no matemáticas. Educación Matemática, 19(2), 41- 66 Ottaviani, M. G. (1998). Developments and perspectivesinstatistical education. Documento presentado en el Congreso Estadística para el desarrollo Económico y Social, Aguascalientes, México Pacheco, E. A. (2013). La estadística aplicada como herramienta para la dirección integral de las organizaciones. (Spanish). Gestión Y Estrategia, (44), 125-138       Pomilio, C., Miño, M., Brignone, N., Facal, G., Telesnicki, M., Fass, M., Filloy, J., Cueto, G., Fernández, M., & Perez, A. (2017). Análisis de actividades sobre estadística descriptiva en libros de educación media: ¿Qué se pretende que los estudiantes aprendan? Porter, M. E. (2015). Estrategia competitiva: técnicas para el análisis de los sectores industriales y de la competencia. Grupo Editorial Patria Ritchey, E. J. (2008). Estadística para las ciencias sociales. México. McGraw-Hill. 2da edición Rowley, J.,  & Farrow, J. (2018). Organizing Knowledge: An Introduction to Managing Access to Information: Introduction to Access to Information. Routledge Sosa-Escudero, W. (2014). Qué es (y qué no es) la estadística: Usos y abusos de una Disciplina clave en la vida de los países y las personas. Buenos Aires: Siglo Veintiuno Editores   Tovar, C. J.; Castillo, S. H. & Marín, M. del P. (2010). Preconcepciones de estudiantes de la Pontificia Universidad Javeriana Cali sobre el curso de estadística. Pensamiento Psicológico, 3(9). Recuperado a partir de //revistas.javerianacali. edu.co/index.php/pensamientopsicologico/ article/view/60 Utts, J. (2002), “What Educated Citizens Should Know About Statistics and Probability”, Proceedings of the 6th International Conference on Teaching Statistics, Sudáfrica Webster, A. L., & García, Y. M. (2000). Estadística aplicada a los negocios y la economía


2021 ◽  
Vol 43 (S1) ◽  
Author(s):  
Neville Davies ◽  
Neil Sheldon

2021 ◽  
Author(s):  
Chris Aberson

Introduction: Faculty are increasingly tasked with online teaching duties. This paper provides a how to guide to using the learnr package for R. This package allows instructors to create seamless interactive tutorials that can use video, quizzes, and exercises run in R to foster student engagement and learning of statistics. Statement of the Problem: Since the beginning of the Covid-19 pandemic, more faculty than every are teaching online. learnr tutorials provide a format that allows for greater student engagement with materials by providing opportunities to test knowledge and practice after viewing short videos on topics. Teaching Implications: I provide concrete instructions for developing learnr tutorials for teaching introductory statistics and provide insights from having applied these technologies for over a year. Conclusion: learnr is a tool that can assist instructors in leveraging valuable teaching opportunities afforded by the technology is a manner that requires only small changes in their more prevalent approaches to teaching online.


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