Computer Assisted Instruction to Teach Academic Content to Students With Intellectual Disability: A Review of the Literature.

Izadi-Najafabadi et al. (2019) read every paper they could find on using computers to teach reading, math, and science to students with intellectual disability. They did not run new kids; they simply mapped what had already been tried. The team looked at how each program worked, how the researchers tested it, and what happened to the students.

The review shows the field is busy but scattered. Dozens of small studies exist, yet no two use the same software or measure success the same way. Because of this mix, the authors could not say “this works” or “this fails.” They only listed what is known and what is still missing.

Yakubova et al. (2013) gives one clear success story. Three students with autism or ID ran their own video modeling on a SMART Board and quickly learned new task chains. Their tight single-case design shows CAI can work when it is self-paced and visual.

Schertz et al. (2018) also saw strong gains. Eight students with ID learned dozens of real words with a text-centered curriculum that used plain direct instruction. Both studies sit inside the Sara map, proving that positive results are possible.

Mukherjee et al. (2021) sounds a warning. Their mega-review of AAC studies found that most technology reviews in the ID world use weak methods. Izadi-Najafabadi et al. (2019) echo the same worry: without better designs and shared metrics, we still can’t tell which computer lessons to trust.

If you teach academics to students with ID, treat the Sara map as your shopping list, not your shopping cart. Pick programs that already have single-case proofs like Gulnoza or H. Add brief daily probes so you can see if the skill really grows. Finally, share your data; every new graph helps the field move from scattered stories to solid answers.