¶ … memory on Learning Disabilities. I believe that there is a strong correlation between the two and that short-term memory is directly affected by Learning Disabilities. Participants in this first study (Mastropieri, Scruggs, Hamilton, Wolfe, Whedon & Canevaro, 1996) included 29 students identified by their schools as having Learning Disabilities (LD) and were attending seventh- and eighth-grade special education classes in both urban and rural or small-town schools in a Midwestern state. On average, the 10 boys and 19 girls were 14 years 9 months old ( SD = 9 months) and had an average IQ (Wechsler Intelligence Scale for Children-Revised, Wechsler, 1974; Wechsler Intelligence Scale for Children-Third Edition, Wechsler, 1991) of 87.7 ( SD = 13.0). Average reading grade equivalent, as measured by the Wide Range Achievement Test-Revised, Basic Academic Skills Individual Screener, Kaufman Test of Educational Achievement, or Woodcock-Johnson Psycho educational Battery, was 3.5 ( SD = 1.6); average math grade equivalent. The sample included seven African-American students, one Hispanic student, 1 American Indian student, and 20 White, non-Hispanic students. Students had been enrolled in special education, on average, for 5.0 years (SD = 1.4). Twenty-four students received all academic instruction in special education settings, four students were in special education for half of the school day, and one student received special education services for 2 hr/day.

Students were trained and tested individually by one of three (one male, two female) graduate students with teaching certifications in LD. As students entered a quiet area near their regularly assigned classroom, they were stratified by grade level and randomly assigned to one of two conditions.

Because the mean IQ of the experimental group students (85.7) differed somewhat from the mean IQ of control group students (89.5), and because IQ was correlated significantly (p < .01) with recall and explanation scores (r = .45), factual recall and explanation scores were entered into a one-way analysis of covariance, using IQ as the covariate. Analysis was conducted on number of items from each category scored correctly, using means adjusted for the covariate. For factual recall, the adjusted mean for experimental condition students was 68.4% correct, whereas the adjusted mean for control students was 66.8% correct. These scores were not significantly different, F (1, 26) = 0.02, p = .886. For explanation scores, the adjusted mean for experimental condition students was 29.2% correct, whereas the adjusted mean for control condition students was 14.3% correct. These scores were significantly different, F (1, 26) = 5.76, p = .024 (Mastropieri, Scruggs, Hamilton, Wolfe, Whedon & Canevaro, 1996, p. 8).

Further descriptive analysis by Mastropieri, Scruggs, Hamilton, Wolfe, Whedon & Canevaro (1996), conducted for heuristic purposes, and revealed that 71.4% of experimental students and 46.6% of control students scored above 50% correct on the recall measure. On the explanation measure, only one student in each condition scored above 50% correct. However, on that same measure, 42.9% of experimental students and 13.3% of control students scored above 25% correct. Results of this investigation suggest that students who are instructed in actively reasoning through content were able to provide more accurate explanations for that content than were students who were simply encouraged to try to remember the information. This suggests that prompting and training students to use active reasoning resulted in higher levels of comprehension of that information, as measured by their ability to explain underlying relationships. Students did not statistically differ by experimental condition on recall of facts, although a descriptively higher percentage of experimental condition students answered more than half of the recall questions correctly.

Students who were instructed to reason actively through new content information did not remember that information any better statistically than students who were simply instructed to try to remember the information. This result does not replicate the findings of the three previous investigations, in which enhanced factual recall was obtained from active coaching of each item. It was also disappointing to note the relatively low explanation scores. Although experimental students exceeded control students in overall correct explanations, neither group provided what may be considered an acceptable level of explanations for the presented information. That control students would explain little of the information that they had read was expected; however, it was disappointing to note the relatively small increase in explanation scores that resulted from training students to reason independently through expository prose. Results of generalization training have suggested that students with LD may exhibit difficulty with cognitive strategies that require independent insight on the part of students. In the case of mnemonic strategies, students appeared to exhibit difficulty accessing relevant, acoustically similar keywords from their prior knowledge (e.g., "Think of a word that sounds like Taft"). Similar to the results...

According to a definition offered by Roberts and Pennington (1996), working memory (WM) is "the ability to maintain and manipulate short - term information needed for generating upcoming action" (p. 105). Thus, WM and short - term memory (STM) are similar, if not the same. All communication is believed to pass through the working memory system and WM has been linked to both executive functioning and attention. Working memory has further been viewed as a pervasive subsystem within the brain and problems within this domain are evident in all cognitive disorders.
(Zera & Lucian, 2001, p. 107) emphasize the importance of working memory in all aspects of higher-order functioning including reasoning, planning, problem solving, and language comprehension. Working memory (WM) is "the ability to maintain and manipulate short - term information needed for generating upcoming action." Thus, WM and short - term memory (STM) are similar, if not the same. All communication is believed to pass through the working memory system and WM has been linked to both executive functioning and attention. Working memory has further been viewed as a pervasive subsystem within the brain and problems within this domain are evident in all cognitive disorders.

As working memory plays an important role in all forms of complex thinking, it follows that difficulties in working memory impact LD. Specifically, working memory difficulties have been implicated in reading disabilities, writing difficulties, and problems with mathematics.

Likewise, the impact of executive functioning on learning disabilities should be thoroughly considered. For example, it has been suggested that executive functions are pivotal to higher cortical operations and are therefore intricately involved with attention and memory. (Zera & Lucian, 2001) point out that executive functioning is future-oriented and "vital to both human development and to the individual's social and intellectual success," p. 107).

Overall, researchers have found that executive functioning typically involves planning, decision making, self-directed goal selection, and monitoring and altering outgoing behavior to achieve a goal as well as behavioral inhibition and delay of responding. Others have noted that executive functions are related to working memory in addition to orchestrating and regulating the management and association of information. It has also been pointed out that students with LD lack executive control and self-regulation in learning as they often have difficulty selecting appropriate strategies for problem solving in reading comprehension, analytical reasoning, and mathematics (Zera & Lucian, 2001, p. 107)

Not only may students with LD possess limited problem-solving strategies and experience difficulties engaging in self-regulatory techniques, Zera & Lucian (2001) report that they may also have difficulties accessing, organizing, and coordinating mental activities simultaneously and often display limited cognitive flexibility. When describing the meta-cognitive processes of students with learning disabilities, it is suggested that these individuals often display inefficient cognitive processing strategies and maladaptive learning patterns. Because students who have learning disabilities typically expend so much energy and exert such tremendous effort on processing basic information, they are unable to allocate sufficient processing energy and time to the more complex, higher-order academic components such as reasoning and comprehension. Academic performance, thus, seems to rely upon adequate executive functioning (p. 107).

Scruggs & Mastropieri (2002) proposed that differences in phonological processes could discriminate between "dyslexic" and "garden-variety poor readers," particularly in reading achievement at early grade levels. Generally supporting this idea, Torgesen and Wagner (1998) have proposed the use of tests of phonological awareness, rapid automatic naming, and verbal short - term memory in identification of reading disabilities at the early grade levels (Wagner, Torgesen, & Rashotte, 1999). Similarly, Fletcher et al. (1998), arguing against the utility of discrepancy models of learning disabilities, suggested that learning disabilities be considered for any student failing to reach the 25th percentile for specific reading skills, including core reading process measures. They noted that this consideration would result in higher numbers identified, but may have greater relevance than present policy-based decisions, which in their view merely fulfill a "gate-keeping function" (p. 199), that is, to keep numbers down.

Chronological age definitions. As have other researchers, Siegel (1989) suggested that IQ…