This study investigated the effect of cloze item practice on
reading comprehension, where cloze items were either created by humans,
by machine using natural language processing techniques, or randomly.
Participants from Amazon Mechanical Turk (N = 302) took a pre-test,
read a text, and took part in one of five conditions, Do-Nothing, Re-Read,
Human Cloze, Machine Cloze, or Random Cloze, followed by a 24-hour
retention interval and post-test. Participants used the MoFaCTS sys-
tem [27], which in cloze conditions presented items adaptively based on
individual success with each item. Analysis revealed that only Machine
Cloze was significantly higher than the Do-Nothing condition on post-
test, d = .58, CI95[.21, .94]. Additionally, Machine Cloze was significantly
higher than Human and Random Cloze conditions on post-test, d = .49,
CI95[.12, .86] and d = .71, CI95[.34, 1.09] respectively. These results sug-
gest that Machine Cloze items generated using natural language process-
ing techniques are effective for enhancing reading comprehension when
delivered by an adaptive practice scheduling system.