The Role and Characteristics of Tactile Graphics in Secondary Mathematics and Science Textbooks in Braille

By Smith, Derrick W.; Smothers, Sinikka M. | Journal of Visual Impairment & Blindness, September 2012 | Go to article overview

The Role and Characteristics of Tactile Graphics in Secondary Mathematics and Science Textbooks in Braille


Smith, Derrick W., Smothers, Sinikka M., Journal of Visual Impairment & Blindness


Abstract: Introduction: The purpose of the study presented here was to determine how well tactile graphics (specifically data analysis graphs) in secondary mathematics and science braille textbooks correlated with the print graphics. Method: A content analysis was conducted on 598 separate data analysis graphics from 10 mathematics and science textbooks. The researchers (the authors) cross-validated the findings through a comparative analysis of the tactile graphics of five shared textbooks. Results: Discrepancies were found between the print graphic and the tactile graphic in 12.5% of the sample. The most common discrepancy was differences in how data lines and data points were individualized in the print graphic compared to the tactile graphic. On the basis of the reviews of the graphics, the researchers answered a 5-point Likert-scale question (from 1 = strongly disagree to 5 = strongly agree) asking if the "tactile graphic is a valid representation of the print graphic." The overall score for the sample was 3.71 (SD = 1.60), with a Krippendorff alpha of 0.6328 (the measure of disagreement and alpha > 0.70 are consider moderate). Discussion: The findings demonstrate that while the majority of tactile graphics have good correlations to their print counterparts, there is still room for improvement. Some transcribers omitted a tactile graphic without providing a reason. Forty graphics (6.7%) were omitted from the braille transcription. Two textbooks were missing more than 85% of the tactile graphics of the data graphs. Implications for Practitioners: Tactile graphics in math and science books are important for a student to understand. Although most transcribers do an excellent job of creating valid tactile graphics, problems with many graphics still exist in textbooks. Practitioners need constantly to review the tactile graphics that are used in all classrooms and be prepared to create their own if needed.

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The impact of visual impairment (that is, blindness or low vision) is widely recognized to be particularly significant for learning mathematics (McDonnall, Geisen, & Cavenaugh, 2009; National Science Foundation (NSF, 2009). The highly visual nature of mathematics and science content, because of its use of graphics to present important information, is an obvious obstacle for students with visual impairments. This obstacle is especially obvious in the area of data analysis, with its strong emphasis on the graphical representations of data in tables, charts, graphs, and plots. To accommodate students with visual impairments, graphics are typically transformed to a tactile format, called a "tactile graph." Tactile graphs, defined as "graphics intended to be read principally by touch (haptics) rather than vision" (Aldrich, Sheppard, & Hindle, 2003, p. 284), are created using a variety of materials and methods (Kapperman, Heinze, & Sticken, 2000).

Although all aspects of mathematics are important because of the relationship of mathematics to scientific reasoning, data analysis is unique because it transcends all domains of knowledge. The importance of understanding the concepts of data analysis is evident as one surveys the amount of data analysis concepts that individuals encounter. Graphs and statistics bombard the public in such areas as advertising, opinion polls, reliability estimates, population trends, health risks, and progress of students in schools. The National Council of Teachers of Mathematics (NCTM, 2000, p. 249) went so far as to state that the ability to reason statistically "is essential to be an informed citizen, employee, and consumer."

Thus, it is apparent that mathematics education must include rigorous instruction in the concepts of data analysis. To guide the field of mathematics education, the NCTM (2000) established the following standards for data analysis and probability:

Instructional programs from prekindergarten through Grade 12 should enable all students to

* formulate questions that can be addressed with data and collect, organize, and display relevant data to answer them;

* select and use appropriate statistical methods to analyze data;

* develop and evaluate inferences and predictions that are based on data; and

* understand and apply basic concepts of probability (p. …

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