id: 06649329
dt: j
an: 2016f.01447
au: Erhardt, Robert J.; Shuman, Michael P.
ti: Assistive technologies for second-year statistics students who are blind.
so: J. Stat. Educ. 23, No. 2, 28 p., electronic only (2015).
py: 2015
pu: Taylor \& Francis, Abingdon, Oxfordshire; American Statistical Association
(ASA), Alexandria, VA
la: EN
cc: U75 K15 C45
ut: stochastics; statistics; university teaching; special education; visual
impairments; blind students; learning assistance; assistive
technologies; statistical models; tactile image; Braille; computer
programming; producing images; interpreting images; scatterplots
ci:
li: http://ww2.amstat.org/publications/jse/v23n2/erhardt.pdf
ab: Summary: At Wake Forest University, a student who is blind enrolled in a
second course in statistics. The course covered simple and multiple
regression, model diagnostics, model selection, data visualization, and
elementary logistic regression. These topics required that the student
both interpret and produce three sets of materials: mathematical
writing, computer programming, and visual displays of data. While we
did find scattered resources for blind students taking mathematics
courses or introductory statistics courses, we found no complete
account of teaching statistical modeling to students who are blind. We
also discovered some challenges in stitching together multiple partial
solutions. This paper outlines our specific approach. We relied heavily
on integrating the use of multiple existing technologies. Specifically,
this paper will detail the extensive use of screen readers, \LaTeX, a
modified use of R and the BrailleR package, a desktop Braille embosser,
and a modified classroom approach.
rv: