Poverty, Reading, and Technology

Lynn ZimmermannBy Lynn Zimmerman
Associate Editor
Editor, Teacher Education

In his article “Technology Holds Promise for Students With Poor Vocabulary Skills” (Education Week, 23 July 2015), Steven L. Miller argues that technology offers one solution for creating individualized learning experiences for students to develop better literacy skills.

Miller’s premise is that children, especially from impoverished backgrounds, also come to school with impoverished language skills. He asserts that “children with lower vocabulary skills are often poor readers, so they continue to fall further and further behind in academic language and cognitive skills.”

While Miller’s article offers an effective solution to the problem of building vocabulary and consequently literacy skills, we have to be careful about generalizations regarding students from low-income or poverty situations. He bases his argument on research demonstrating that they hear more negative communication while students from professional families hear more positive and encouraging communications.

However, there is a broader range of research on the impact of poverty on learning, showing that while communication may be one aspect of literacy development, there are other factors such as poor nutrition and inadequate healthcare.

Regardless of the causes, education and educational technology can, as Miller states, help students with poor vocabulary skills. For example, he says:

Using speech-recognition software … students receive one-on-one guidance and real-time feedback from an unbiased listener as they read aloud. Using this approach, students can improve their reading grade level by up to 50 percent more than the students who only receive classroom instruction in the same time period.

Miller’s article is based on Betty Hart and Todd R. Risley’s 1995 study Meaningful Differences in the Everyday Experience of Young American Children. For a summary, see Hart and Risley’s “The Early Catastrophe: The 30 Million Word Gap by Age 3”  (American Educator, spring 2003).

3 Responses

  1. I really like the speech-recognition idea. Knowing the founders of Dragon, the premier speech recognition software, I find this application particularly interesting. How many other technologies might there be that could find innovative uses in education?

  2. “Using speech-recognition software … students receive one-on-one guidance and real-time feedback from an unbiased listener as they read aloud”. Whatever makes you think that technology in itself is unbiased? It will most certainly be influenced by the socio-linguistic background of the developers as well as the anticipated target audiences of the software. Depending on the learner’s linguistic environment and background, it may or may not be a good fit.
    And, for that matter, research is just as likely to refelct cultural, social and racial bias, which is especially apparent in the research design of the 1995 Hart & Risley study. The 30 Million word gap is one of these findings that are repeated again and again, but seldom with a review of the methodology. Should six families who were studied in 1995 really shape our understanding of how parents with less money interact with their children?
    http://cedar.wwu.edu/cgi/viewcontent.cgi?article=1028&context=jec
    http://academic.evergreen.edu/curricular/med/langpoor.pdf
    http://www.learninglandscapes.ca/images/documents/ll-no13/michaels.pdf

  3. @ Stefanie Panke: Actually, with Dragon, you have to train the software yourself – a friend who uses it in French once joked that she was getting quite tired of reading aloud the same excerpt from a Jules Verne’s novel each time she upgrades it.

    So this should eliminate a possible developer’s bias. However, doing that might be problematic for someone who is not a proficient reader. Workaround: they could record their repeating of someone else reading aloud the excerpt.

    Generic speech to text, like Google’s that creates the automatic captions on YouTube, might be culturally biased, perhaps. Nevertheless, the same Google speech to text, but on an Android smartphone, does seem to get progressively trained to the main user’s voice.

    @ Harry Keller, re “How many other technologies might there be that could find innovative uses in education?” Greg McCall, who teaches students who have reading/writing difficulties in Hawaii, has them make karaoke-like same language subtitles: see their videos collected in his YouTube channel, and his and and Carmen Craig’s Same-Language-Subtitling (SLS): Using Subtitled Music Video for Reading Growth 2009 paper.

    Unfortunately, karafun, the karaoke editor they use to make all these nice effects, was discontinued due to copyright issues. However there are other ones around. And the nice thing with karaoke editors is that they allow you to markedly slow down the video in order to time the written words with the audio.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s