2. Who we are Rob Wall Emerson, Dawn Anderson Western Michigan University Under contract from MeTRC (Mathematics eText Research Center) at University of Oregon Mark Horney

3. What we are looking at How best to describe the image components found in typical math textbooks (not the math equations) What types of images require what level of description? Are there types of images whose content cannot be adequately conveyed by any description? We are not looking technological solutions but try to present material in a way as close as possible to a common student educational experience

6. Identifying image categories We categorized images in representative math texts from grades 5, 8, and 11. Identified 21 exhaustive and mutually exclusive image categories Some were more common than others (e.g., line graphs and tables more common than pie charts and models) To control the study we limited use to “math heavy” categories

7. Category frequency First tier categories appear either on nearly every page of a text or several times on a page within certain areas of a text. Second tier images are more specific and appear occasionally, usually to serve a specific purpose. Third tier images appear infrequently. Note: 4465 pages of text were involved in the counting. The most commonly occurring image categories (from most to least) in the first tier were: 1. Side images (background picture, graphic unrelated to question, organizational banners, headers, icons, extra features notation) 2. balloon/sidebar 3. shapes/2D or 3D representation 4. question specific image (1926) 5. table (1785) 6. scatterplot/line graph (1305) 7. equation (1109)

8. The most commonly occurring image categories (from most to least) in the second tier were: 1. models (used to indicate similarity) (755) 2. ray/line diagram (722) 3. calculator stuff (509) 4. organizational aid (397 5. procedural aid (266) 6. number line (252) 7. directions/illustrations of a physical task (197) The most commonly occurring image categories (from most to least) in the third tier were: 1. pattern/series (101) 2. pie chart (92) 3. screen shot (87) 4. bar graph (87) 5. flow chart (72) 6. maps (50) 7. picture in a picture (9)

9. Meta categories 4 “meta categories” represent context for the images introducing concepts guided example short question real world manipulative

10. Differences between grade Minor variations between texts for different grades Main differences were that grade 5 used more models, procedural aids, and number lines Grade 8 and 11 used more calculator stuff, line graphs, and ray/line diagrams

11. Playing the files Word documents were created that mirrored the physical page in layout and coloring. Each file contains images and ancillary text to provide context. Math content that was not image related was translated using MathML and MathType and the entire file spoken using JAWS.

12. Our basic approach Files had varying levels of description. None (“image”) Terse (“image of a graph”) NCAM standard Extended Files longer than 90 seconds were eliminated after pilot trials Students were assessed on capture of content, ease of capture of audible material, and preference of presentation. Students each performed between 9 and 20 trials

13. Participants 44 students, mainly in grades 8 and 11 (3 in grade 5) 5 in Illinois, 31 in Texas, 8 in Tennessee Only 16 of the 44 were caucasian Based on their reading format, 25 were braille users (used as a proxy for blind), 19 used some form of print (used as a proxy for low vision)

14. Their relationship with math 25 were positive about math, 11 were negative 32 felt they were good at math 18 had no issues with their texts. Of the others, most common complaints were braille errors in the text and graphs or images not made correctly or not read out 34 had no issues with assessments. Only 3 mentioned issues with inability to access graphs or images

15. Good and bad impressions Keeping it short was good, not enough info given Giving detailed information, giving too much information Voice changed to illustrate text changes, voice changed too much Voice was easy to understand, voice was confusing Things were described well, things were not described well

16. What needs more description? Pictures 16 Graphs16 Maps4 Tables4 Shapes and lines2 Everything2 Page formatting1 Angles1 Histograms1 Pie charts1

17. What needs less description? Nothing13 One picture7 I don’t know4 Graphs with extra info4 Words, letters3 Irrelevant stuff3 Equations, formulas2 Some diagrams1 Tables1 Maps1 A couple of pictures1 Line segments1

18. Would you like everything described? Yes22 No13 Maybe7

19. Results of first content question (I don’t know = wrong) χ 2 (3) = 20.91, p <.0001 WrongRight Control12422 Terse12519 NCAM10543 Extended10646

20. Results of first content question (I don’t know = wrong) χ 2 (3) = 9.12, p =.028 (with manipulative group) χ 2 (2) = 8.05, p =.018 (without manipulative group) WrongRight Intro15053 Short example18935 Guided example11237 Manipulative105

21. Results of first content question (I don’t know = wrong) χ 2 (10) = 31.61, p <.0001 (with manipulative group) χ 2 (9) = 28.43, p =.001 (without manipulative group) WrongRight Question specific image6712 Equation332 Shapes4112 Table3416 Line graph4522 Bar graph4914 Manipulative65 Pie chart376 Number line2316 Ray diagram5914 Map6711

22. General findings For many images more description is counter productive (especially tables and line graphs) It is surprising how much students do not know what they do not know Students often do not realize they are missing key information When only the word “image” is presented, they often think that what comes next is a description of the image, causing further confusion

23. Multi modal presentation A major trend seems to be that many image categories would benefit from a multi-modal presentation of content Have an audio version with description and for image related content, also have a braille version of the “description” and a tactile image.

24. Thank you Robert Wall Emerson Western Michigan University Department of Blindness and Low Vision Studies robert.wall@wmich.edu Dawn Anderson Western Michigan University Department of Blindness and Low Vision Studies dawn.l.anderson@wmich.edu