Statistics Online Computational Resource
The Statistics Online Computational Resource (SOCR)[1] is a suite of online tools and interactive aids for hands-on learning and teaching concepts in statistical analysis and probability theory developed at the University of California, Los Angeles. The SOCR resource is HTML, XML and Java based and all materials and tools are freely available over the Internet.
SOCR consists of Interactive Distribution Applets, Statistical Analysis Modules, Data Modeler, Graphics Tools, Instructor's Notes and Additional resources[2] [3].
SOCR resources are peer-reviewed, integrated internally and acknowledged by dozens of international digital libraries, professional societies and scientific organizations[4] like NSDL, Open Educational Resources, Mathematical Association of America and California Digital Library.
See also
External links
References
- ^ Dinov, Ivo D. (2008). "Pedagogical Utilization and Assessment of the Statistic Online Computational Resource in Introductory Probability and Statistics Courses". Computers and Education. 50 (1): 284–300. doi:10.1016/j.compedu.2006.06.003. PMC 2740633. PMID 19750185.
{{cite journal}}: External link in|journal=|coauthors=ignored (|author=suggested) (help) - ^ Dinov, Ivo D. (2006). "Statistics Online Computational Resource". Journal of Statistical Software. 16 (1): 1–16.
- ^ Christou, Nicolas (2010). "A Study of Students' Learning Styles, Discipline Attitudes and Knowledge Acquisition in Technology-Enhanced Probability and Statistics Education" (PDF). Journal of Online Learning and Teaching. 6 (3): 546–572.
{{cite journal}}: External link in|journal=|coauthors=ignored (|author=suggested) (help) - ^ Peer-reviewed SOCR papers and SOCR integration in international digital libraries