AT research can be an important source of information when making decisions. It can inform and guide decisions about what AT tools to consider and what outcomes are reasonable to expect for AT use. IDEA 2004 requires that special education, related services and supplemental aids and services be based on peer reviewed research to the extent practicable. Since AT will always be part of either special education, related services or supplementary aids and services, it makes sense that AT services providers need to know the peer reviewed research on assistive technology. This section of the website contains a variety of information and resources about understanding and using assistive technology research. Information is divided into three sections: Finding AT Research Reading and Understanding AT Research Evaluating AT Research Summaries of AT Research articles
Finding AT Research
AT research can be found in a variety of places. Certainly there are a lot of reports of AT research on the internet. Many vendors now include reports of research on their web sites. However, professional peer-reviewed journals are the best source of AT research. A peer reviewed journal is one that seeks and publishes research that is first analyzed by knowledgeable reviewers. The reviewers are always listed somewhere in the journal or on their website.They are generally referred to as the Editorial Review Board. It is prestigious to be on an editorial review board. The members take their role of judging the quality of the research very seriously and seek to publish only studies that are well designed and rigorously carried out.
A recent review of research on assistive technology (Ocolo & Bouck, 2008) found high quality AT research in 27 different journals. Some of the journals that regularly publish assistive technology research include those in the following list. Note that the first two journals account for the majority of research published in the last eight years.
- Journal of Special Education Technology (JSET)
- Augmentative and Alternative Communication
- Education and Training in Mental Retardation and Developmental Disabilities
- Journal of Visual Impairment and Blindness
- Remedial and Special Education
- Journal of Speech, Language, and Hearing Science
- Topics in Early Childhood Special Education
- Learning Disability Quarterly
- Journal of Research on Technology in Education
- Journal of Rehabilitation Research
- Assistive Technology Journal
There are, of course, many other special education and rehabilitation journals in which you may find research about AT.
Additionally there are non research journals devoted to assistive technology, such as Closing the Gap and Special Education Technology Practice. However, these are not peer reviewed journals and tend to have first person accounts and suggestions for effective implementation strategies rather than research.
Websites maintained by AT vendors have begun to include reports of research about their products. In some cases this may be well designed, experimental research. However, unless it has also been published in a peer reviewed journal, you may want to look for additional research that has been peer reviewed.
Sources of AT research ranked by their likelihood to be valid. reliable and trust worthy:
- Published in peer reviewed journal
- Published in non-peer reviewed source
- Published in non peer review source and completed by publisher or other vested person
- Not published
Reading and Understanding AT Research
Assistive technology research runs the gamut from small action research projects in classrooms to formal experimental research conducted by skilled researchers. To understand research it is important to understand the terminology. Following are definitions of some of the key words that are used.
Definitions of research terms
When there is only one subject, researchers try to establish a causative relationship by collecting data on a student’s performance both with and without the use of the tool being studied. The data collected before the AT is provided is called baseline data or condition A (e.g. the child is successful in their attempts to communicate 3 out of every 10 attempts with no AT). Then they introduce the use of the tool and take data about any changes in performance that occur. This is condition B (e.g. given a spelling board and pointing to the first letter in the word he is saying, results in successful communication 7 out of 10 tries.) Taking away the board for a short time or collecting data in a situation where it is not available (return to condition A) helps to show that it is the use of the board that is making the difference. Repeating conditions A and B help to rule out other things that might have caused the improvement such as time of day, more interesting activity, or accidently taking data at a time of day when the student’s articulation is always more understandable, etc.
Case Control Studies
Case control studies in education are similar to case control methodology often used in cancer research. Think about a huge database full of information. Start with all the records and match them on areas of relevant background factors, dropping the records where no match occurs. Match on things like age, disability, behaviors, technology, achievement, etc. Match these records on every variable possible, dropping more and more records in the process, until the only variables in the database left unmatched are the ones you are interested in researching. For this example, let’s say the use of graphing vs. non-graphing calculators in Algebra. Perhaps, after all this matching and dropping of records is done, there are as many as 20 cases left. These cases are matched on all the variables in the database, with some number (let’s say 9) using graphing calculators and the others (the remaining 11) taking Algebra with regular calculators. The difference in performance on some criterion measure—like a state assessment test score—should be a direct indicator of the "graphing calculator effect" for these 20 cases.
The attraction of such research is clear. First, it involves no expensive additional testing, data collection, treatment or experimental designs. Second, it can be done quickly and efficiently because the data already exists in an electronic database and is easily accessible. Third, it can be done over and over again with different matches and different variables at essentially no additional costs and can be done year after year such that true longitudinal research can be conducted. In the past, databases may not have been in place to support such intense data manipulation. With improvements in technology, it is possible to see integrated data systems becoming more and more sophisticated and much larger.
Case Series with no Control group
A case series with no control group is similar to a case control study in that it is carried out by reviewing existing data. However there is no attempt to identify a control group. It is simply a compilation of numbers of cases where two things occurred together. An example is the 1998 study in which a link was suggested between mumps-measles-rubella (MMR) vaccination and autism. This was based on an uncontrolled case series of 12 children referred to a pediatric gastroenterology unit with a history of normal development followed by loss of acquired skills, including language, together with diarrhea and abdominal pain. It was suggested that the gastrointestinal and developmental symptoms were a syndrome that could have been triggered by MMR vaccination. The conclusion was based simply on finding these cases where children both had the two things occur. Subsequent reviews have concluded that they could not prove or refute the suggested associations between MMR vaccine and autism. The problem with using a case series with no control group is that a causative relationship can be the conclusion that is reached, when that may not be true at all. It could be coincidence or it could be the result of some other factor that you have failed to identify.
The group of participants in an experiment who do not receive the treatment (e.g. use of an AT tool) that is being studied.
The strategy used in scientific research to regulate the effects of variables in a study that are not intended to influence the results or conclusions. For example if a researcher is studying the impact of using a portable word processor versus a computer, the students participating in the study would get to use the tools for a set of amount of time for the same number of days, at the same time of day and for the same assignments to ensure that amount of time, time of day, day of the week or type of assignment were not the cause of any differences found in the completed assignments produced by the students.
A type of research that has the goal of determining whether something causes an effect.
Experimental (true) Research Design
A research design in which (1) an independent variable (e.g. use of a spell checker) is directly manipulated to measure its effect on a dependent variable (e.g. number of words spelled correctly), and (2) participants are randomly assigned to different groups that receive different amounts of the independent variable. This is sometimes referred to as randomized field trials or randomized controlled trials. For example if a researcher wanted to study the effect of using software that reads text on the comprehension of text book passages, he might randomly assign 30 students with reading difficulties to participate in one of two programs: (1) standard teaching of reading or (2) eight weeks of using scan and read software (such as Kurzweil 3000, Read and Write Gold, WYNN, etc.) in addition to the standard reading teaching. After the end of the eight weeks, the researcher compares the student’s scores on a standard reading assessment. The addition of the scan and read software is the independent variable, and performance on the test is the dependent variable. Group 1 is the control group. Group 2 is the treatment group because they participate in the special treatment (independent variable).
Introducing the intervention in specific activities or settings at different times is a way to help prove that it is the use of the new AT tool that is causing the change in performance. For example a student may begin to use a portable spell checker in Language Arts class in October. His spelling improves on Language Arts assignments. It is then also introduced in Social Studies in December. At that point his spelling improves in Social Studies and continues at the improved level in Language Arts. In January the staff arranges for him to use it in all classes and similar improvement results. Because of the staggered introduction of the use of the AT, the change in his spelling ability is shown to be caused by the use of the portable spell checker rather than maturation, change in difficulty of assignments, use of a new teaching strategy or some other undocumented event.
Students are randomly assigned to participate in one of two different situations. For example a researcher conducts a study of two different programs for teaching math skills to students with learning disabilities. The researcher controls for differences among students by randomly assigning them to one of the two groups (one group will get program A and one group will get program B). The researcher controls for differences among teachers by having a single person teach both classes.
When students are not randomly assigned, sometimes a whole class in one school gets one treatment (e.g. text to speech software to support reading) while a whole class in another school gets a different treatment (e.g. standard reading instruction with no text to speech). To compensate for lack of random assignment, researchers often try to match students on such factors as age, disability, reading level, etc., but it is not as effective in controlling for undocumented events (e.g. differences in the teacher’s skills, differences in motivation at one school, etc.) as random assignment.