Teaching an Introductory Statistics Course with CyberStats, an Electronic Textbook

Symanzik, Jürgen; Vukasinovic, Natascha

doi:10.1080/10691898.2006.11910575

Cited by 20 publications

(8 citation statements)

References 9 publications

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“…However, the studies arrive at different conclusions. Evaluations of the performance show a range from worse achievements for students in online courses [4] through comparable results [5], [6], [7], [8], [9], [10], [11], [12] to significant better outcomes in the online teaching [13], [14]. The same holds for studies measuring the attitudes towards online teaching compared to traditional teaching.…”

Section: Introductionsupporting

confidence: 49%

“…The same holds for studies measuring the attitudes towards online teaching compared to traditional teaching. Also in this area we can find a range from negative attitudes towards online courses compared to traditional teaching [6], [8], [10] through similar satisfaction [12], [15] to more positive attitudes [16], [17], [18]. Despite this indeterminate picture, we decided to develop a blended learning module in statistics, since such a course addresses issues occurring in our teaching situation at FRA-UAS.…”

Section: Introductionmentioning

confidence: 99%

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A Blended Learning Module in Statistics for Computer Science and Engineering Students Revisited

Andersson¹,

Logofătu

2017

Int. J. Eng. Ped.

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Abstract-Teaching a statistics course for undergraduate computer science students can be very challenging: As statistics teachers we are usually faced with problems ranging from a complete disinterest in the subject to lack of basic knowledge in mathematics and anxiety for failing the exam, since statistics has the reputation of having high failure rates. In our case, we additionally struggle with difficulties in the timing of the lectures as well as often occurring absence of the students due to spare-time jobs or a long traveling time to the university. This paper reveals how these issues can be addressed by the introduction of a blended learning module in statistics. In the following, we describe an elearning development process used to implement time-and locationindependent learning in statistics. The study focuses on a six-step-approach for developing the blended learning module. In addition, the teaching framework for the blended module is presented, including suggestions for increasing the interest in learning the course. Furthermore, the first experimental in-class usage, including evaluation of the students' expectations, has been completed and the outcome is discussed.

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Section: Introductionsupporting

confidence: 49%

Section: Introductionmentioning

confidence: 99%

A Blended Learning Module in Statistics for Computer Science and Engineering Students Revisited

Andersson¹,

Logofătu

2017

Int. J. Eng. Ped.

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“…The importance of statistics software packages in facilitating student learning cannot be overstated in the extant literature (Smith 2003;Hulsizer and Woolf 2009;Šebjan and Tominc 2015). Similarly, employing an appropriate and well-integrated textbook, whether print or electronic, is integral to improving student outcomes (Forte 1995;Symanzik 2006).…”

Section: Pedagogical Tools Employed At Undergraduate Levelmentioning

confidence: 99%

Statistics Education for Undergraduate Sociology Majors: Survey Findings across Institutions

Deckard¹,

M²

2017

Numeracy

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The need to close the quantitative literacy gap for sociology majors is a perennial topic in discussions of undergraduate sociological training. More and better statistical education with a greater focus on active research and engaged analysis is recommended by the major disciplinary association, as well as virtually all pedagogical agencies. This project explores these differences in the implementation of these recommendations, employing a survey (n=90) to report on the structure of quantitative training for undergraduates majoring in sociology. It finds that the type and extent of this education available to, and required for, sociology majors varies widely across not only institutions but by type of institutional context. The pedagogical resources and tools employed also vary widely. It explores the curricular elements that departments view as the strengths and weaknesses of their quantitative programs in terms of perceived student outcomes and competencies.

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“…Many recent attempts (Blasi & Alfonso, 2006; Dinov, Christou, & Sanchez, 2008; Dinov, 2006c; Mishra & Koehler, 2006) have demonstrated the power of this new paradigm of technology-based blended instruction. In particular, in statistics education, there are a number of excellent examples where fusing new pedagogical approaches with technological infrastructure has allowed instructors and students to improve motivation and enhance the learning process (Forster, 2006; Lunsford, Holmes-Rowell, & Goodson-Espy, 2006; Symanzik & Vukasinovic, 2006). In this manuscript, we build on these and other similar efforts and introduce a general, functional and dynamic law-of-large-numbers (LLN) applet along with a corresponding hands-on activity.…”

Section: Introductionmentioning

confidence: 99%

Law of Large Numbers: The Theory, Applications and Technology-Based Education

Dinov

Christou

Gould

2009

Journal of Statistics Education

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Modern approaches for technology-based blended education utilize a variety of recently developed novel pedagogical, computational and network resources. Such attempts employ technology to deliver integrated, dynamically-linked, interactive-content and heterogeneous learning environments, which may improve student comprehension and information retention. In this paper, we describe one such innovative effort of using technological tools to expose students in probability and statistics courses to the theory, practice and usability of the Law of Large Numbers (LLN). We base our approach on integrating pedagogical instruments with the computational libraries developed by the Statistics Online Computational Resource (www.SOCR.ucla.edu). To achieve this merger we designed a new interactive Java applet and a corresponding demonstration activity that illustrate the concept and the applications of the LLN. The LLN applet and activity have common goals – to provide graphical representation of the LLN principle, build lasting student intuition and present the common misconceptions about the law of large numbers. Both the SOCR LLN applet and activity are freely available online to the community to test, validate and extend (Applet: http://socr.ucla.edu/htmls/exp/Coin_Toss_LLN_Experiment.html, and Activity: http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_Activities_LLN).

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Teaching an Introductory Statistics Course with CyberStats, an Electronic Textbook

Cited by 20 publications

References 9 publications

A Blended Learning Module in Statistics for Computer Science and Engineering Students Revisited

A Blended Learning Module in Statistics for Computer Science and Engineering Students Revisited

Statistics Education for Undergraduate Sociology Majors: Survey Findings across Institutions

Law of Large Numbers: The Theory, Applications and Technology-Based Education

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