Assistive Technology (AT) showing data displayed on computer screen

Data Tools to Inform AT for Reading and Writing

Author: Michelle Patterson; info@ciddl.org

Our series on assistive technology (AT) seeks to support teacher preparation programs as they guide preservice educators to consider, select, and implement AT with their students. Our last blog post provided three questions to determine if AT is needed. Once preservice educators know AT is required, how do they work with students to select the right AT? AT selection must be guided by data, not swayed by opinions or flashy advertisements. Implementation is most likely to have long-term success when there is a fit between the student, the task, and the tool. This blog post shares three free data collection tools for student reading and writing that faculty can incorporate into their teacher preparation program.

Reading

Students who have a print disability (e.g., vision impairment, learning disability, or physical disability making it difficult to hold a standard print book) may need AT to ensure they have access to grade-level text. Preservice educators can administer the Protocol for Accommodations in Reading (PAR) to determine if students need print or audio formats. During PAR administration, a student reads in three conditions- independently read text, human-narrated text, and digitized text (text-to-speech).  

Consider student A, a 5th-grade student who reads independently at the 2nd-grade level. Upon completing the PAR, the preservice educator finds this student can comprehend digitized text at grade level. This information guides the preservice educator to determine whether the student requires text in an accessible format and AT in the form of text-to-speech.  

On the other hand, the preservice educator administers the PAR to Student B, an 8th-grade student who reads print independently at the 4th-grade level. The student did not demonstrate improved comprehension when provided text in a human-narrated or digitized audio format. Instead, the educator decides to assess if digitized text with a picture dictionary supports comprehension. Preparation programs build confidence in their preservice educators when they create opportunities to base AT decisions on data. 

Don Johnston provides a  free print version (PAR) and a paid digital version (uPAR) online.

Writing

Our preservice educator again considers students A and B, who turn in illegible work. Should these students type their assignments instead? Data can guide the answer.  

Preservice educators can administer and analyze DeCoste’s Written Productivity Profile (the original free and revised paid versions available online) as part of their preparation program. The preservice educator gathers data across handwriting and keyboarding in three conditions. The first, dictation, parallels classroom note-taking. The second, copying, aligns with working from the board or a textbook. The third assesses handwritten and typed independent writing.  

In the first scenario, Student A types faster than writing by hand for the copying and independent conditions, but not for dictation. The preservice educator recommends the student keyboard as AT for writing assignments but not class notes. For class notes, the preservice educator recommends guided notes, in which the student only has to fill in parts of the information by hand.  

For our second student, Student B does not type faster than handwriting in any of the conditions; in this case, the student may be provided instruction in keyboarding and considered for speech recognition.  

In this case, the preservice educator may use Cochrane and Key’s Speech Recognition as AT for Writing: A Guide for K-12 education. This guide provides a comprehensive step-by-step process to consider, try, teach, assess, and implement dictation for students who might have difficulty with handwriting and keyboarding. Data collection includes legibility and productivity, spelling, conventions, word and sentence length, and procedural skills.  

What Data Tools Have You Used?

With thoughtful data collection, preservice educators build the capacity and confidence to select AT that will make a difference for students. Do your preservice educators feel confident in making data-driven AT decisions? What steps are you taking to guide them to make a connection between data, tasks, and tools? Join us in the CIDDL community; we’d love to hear from you!