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University of Kentucky Team

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Curriculum Conversion and Implementation

Research Site:      University of Kentucky, Lexington, Kentucky
Researchers:        Preston Lewis, Linnie Lee, and Stephen Noble
Study Title:          Math Curriculum Digital Conversion Phase 2, Spring 2011

Study Description

The team at the University of Kentucky employed new technologies to provide students with disabilities an accessible electronic version of math curriculum materials which could be read aloud from a laptop computer using a MathML-aware text-to-speech (TTS) engine. The research was divided into three phases. The overall hypothesis was that if students’ mathematics textbooks, workbooks, handouts, and other print materials were made accessible, students would be able to comprehend these materials more readily, improve their understanding of mathematics, and consequently perform better on assignments and tests. Although significant progress has been made through the passage and implementation of NIMAS in creating accessible versions of textbooks and supplementary materials, a good curriculum is not solely based on these items. In operation, a good curriculum draws from a combination of published and locally made or derived materials, much of which can only be made accessible by ongoing local digital conversion. In addition, while some publishers now routinely include MathML when encoding math content in what is submitted to the NIMAC, many still do not yet incorporate this XML-based tag set, since it is not yet required in NIMAS, although this change may be forthcoming from the federal level. 

Phase 2, conducted from January 1, 2011 to June 30th 2011, piloted digital conversion procedures and student use of math content in 6th grade to identify and resolve any technological and student usage issues requisite to ongoing implementation in a classroom context. From this process research procedures were developed for conducting a case study during Phase 3 (July 1, 2011- June 30, 2012) of the extent to which a 7th grade math curriculum can be converted to an accessible digital format and integrated into instructional routine as an oral accommodation for use by students with disabilities served in a resource setting. 

Methods

Data were gathered from four sources: (a) student observations (b) teacher observations, (c) math material review, and (d) student interviews.

Student Observation. The student observation protocol asked the observer to distinguish between reading words and reading mathematical expressions. Observers recorded the frequency that individual students requested help with reading words and expressions in mathematical text.

Teacher Observation. On the teacher observation protocol, a teacher was observed for one class period. Observers recorded the mathematics content, the nature of the activity, format, time spent, and the frequency that the teacher was observed reading text aloud, reading math aloud, directing students to read silently, reading text individually to a student reading, math expressions individually to a student, directing peer work, and/or using MathML.

Math Material Review. All mathematics materials submitted by teachers for conversion were evaluated for conversion. The conversion processes were standardized for types of source text.

Student Interview. An individual student interview protocol was designed to ask each a student to read mathematics text and expressions aloud. The interviewer noted the degree of independent reading performed by the student. The student also answered questions about reading mathematical text and expressions in textbooks, handouts, Smart Board, and on screen.

Sample

Two grade 6 resource rooms, an intervention class, and two general education classes participated in the Phase 2 pilot. During the Phase 2 pilot, six teachers made up the mathematics team: 17 teacher observations and 28 student observations were conducted in general education, intervention and special education resource room settings. Seventeen student interviews were also completed. A “Technology Skills Checklist” was developed and used as a training protocol with 15 students.

Findings

Teachers in all five classes were asked to identify daily math content one week ahead to allow time for the digital conversion and delivery process, however, typically math content was available only 1-2 days prior to when it was needed for use. Teachers found it difficult to predict how much of each day's lesson students would complete. This “just in time” approach required last minute scanning, conversion, and proofing of material in order to have it ready for next day delivery. In addition, the math materials used from class to class differed from day to day limiting efficiency in the conversion process. Short turnaround times for conversion and variation in the amount of content that needed conversion was a major challenge.

Classroom observations conducted revealed that out of 44 instructional math sessions analyzed, 43% of them were clearly amenable to digital conversion and electronic presentation, while another 23% were feasible for digital conversion and electronic presentation, but with qualifications, primarily requiring additional teacher prior planning and preparation. The remaining 34% of the materials used were not conducive to digital conversion or electronic presentation as they involved things such as use of manipulatives, board work, or presentations too brief in nature to allow time for computer startup and usage.

Interviews with 17 students revealed distinctions of how well students read math content that was literary in nature vs. reading of purely math symbol content.  A stark contrast was found in students’ ability to read these two types of math content.  While the average error rate in reading a sample of literary math content was 6.7%, the average error rate for reading the sample of math symbol content was 36%. This could point to one of the great benefits of students being able to use TTS to read not just words, but also math symbols, especially complex equations made accessible using MathML.

Use of the Technology Skills Checklist showed that 13 of the 15 students were able to independently use text-to-speech with digital math content that included MathML by their third session. 

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