This model arose from the SVR, and regards the two core elements of word decoding and linguistic comprehension as basic independent information processing systems that
utilise internal representations of symbols and objects. Joshi and Aaron (2000) undertook a study with elementary school-aged children to identify whether an additional factor of speed, when added to the SVR, improved the model’s ability to predict reading comprehension skill. The results of the assessments of both D and LC demonstrated that these two components could explain approximately 50 percent of the variance in reading comprehension, with the speed of processing letters explaining a further 10 percent in addition to D and LC. The authors therefore proposed a revised version of the SVR presenting the formula (where S = speed):
R = D x LC + S
The additional factor of speed of processing was considered to be an additional rather than a multiplicative component, as Joshi and Aaron did not consider it to be entirely independent of word decoding. They suggested that speed only emerges as an important element in children at approximately grade four, as until this point children rely more heavily on word decoding and building sight vocabularies. It is only once these skills have been consolidated that speed emerges as a more prominent factor (Joshi & Aaron, 2000).
Aaron et al. (2008) utilised the CMR in a subsequent study that sought to identify reading disabilities in a cohort of school children. In this updated version, the CR was outlined as comprising three domains: a cognitive domain, psychological domain, and ecological domain. The authors envisaged that satisfactory levels of literacy skill may not be acquired due to deficits in any one of these three components. Aaron et al. (2008) sought to validate the cognitive domain of reading in their study of 204 children aged between grade two and five. The participants completed assessments of reading comprehension, listening comprehension, word decoding, and processing speed of letter naming. The results confirmed support for the SVR with D and LC accounting for between 38 and 41 percent of the variance in reading comprehension, with speed of processing contributing a further 11 percent in
children of second grade age. However, by fifth grade, this element of speed of processing had diminished to just 2.5 percent. This finding was concurrent with results from a study conducted with children of fourth- and eighth-grade age (Adlof, Catts, & Little, 2006) whereby rate and accuracy in reading connected text was not found to be a significant contributing factor in reading comprehension. The findings of Aaron et al. (2008) supported the hypothesis of the CMR that speed of processing is not an independent component but a by-product of word recognition skill. However, the diminishing contribution of speed of processing with age suggests that this may not be a significant contributor to reading comprehension within the adult population.
2.2.5.2. Further Component Models
Mellard and Fall (2012) proposed a component model of reading for adults with low literacy skills. Mellard and Fall’s model was comprised of: word skills, language
comprehension, memory, and fluency. These four combined components were shown to account for 75 percent of the variance in reading comprehension in 312 adults. This group comprised individuals who were accessing basic and secondary education services, with over half reporting reading difficulties in childhood, and almost three-quarters with incomplete secondary education. The authors reported that amongst these individuals, recruitment of different components was evident in the process of reading, depending on their level of reading skill (Mellard & Fall, 2012). Adults with the lowest ability in their study were found to rely predominantly on word reading skills, drawing on memory to support their word recognition. Mid-level readers relied on word reading skills but also recruited memory and language comprehension components for reading comprehension. Adults with the highest level of reading skill demonstrated almost equivalent contributions from each of the four components to their reading comprehension. This model is one of the primary models to
specifically address the reading comprehension abilities of adults. However, the point at which adult readers make the transitions from low- to mid-, and mid- to high-levels of reading ability is unclear. Moreover, the component of memory comprised measures of working memory and a language based measure (listening comprehension), the latter of which may have confounded this measurement, due to the reliance on language skills. This strong role of memory in reading comprehension, contradicts many other views of reading comprehension (Daneman & Merikle, 1996; Hannon, 2012; Van Dyke, Johns, & Kukona, 2014).
Mellard and Fall’s (2012) study focussed on individuals with relatively low levels of literacy skill. Even the participants who demonstrated a high level of literacy skill within this group were typically functioning at a level below expected in the adult population. It is therefore not possible to extend these findings wider, or to adults with relatively high levels of reading ability. Furthermore, the participants who demonstrated the highest level of
reading proficiency in this study recruited skills consistent with more basic models of reading comprehension such as the SVR (word level skills, language and listening comprehension, with smaller contributions made by additional measures such as fluency). These findings therefore do not explicitly argue for the application of a more complex model of reading comprehension to describe the skills of this population, rather the component model proposed produces similar results to that of the SVR.
Mellard, Fall, and Woods (2010) conducted a path analysis of reading comprehension to ascertain whether a model representing the relationship between the component skills of reading would be predictive of reading comprehension ability amongst adults with low levels of literacy. Their model used the foundations of the SVR but regarded the skills required for reading comprehension as component parts. However, they adopted an additive rather than multiplicative model of the SVR as per Dreyer and Katz (1992). The participants of Mellard,
Fall et al.’s (2010) study comprised 174 adults accessing basic education services who were reading at a level equivalent to approximately fifth-grade (a similar level to the participants of the Mellard and Fall (2012) study outlined above). Results demonstrated that these
participants relied heavily on word reading ability, with only a marginal contribution made by linguistic comprehension skills such as summarising and inferencing. Mellard et al. (2010) concluded that this model, and other existing models of reading comprehension, could not accurately describe the skills of the population examined. They did however acknowledge that greater linguistic comprehension would be expected in adults with increased levels of reading comprehension ability. Furthermore, they considered the role of strategies that call upon higher level language skills (such as summarising and inferencing), which were shown to be minimally used by adults with low levels of literacy skill in this study (Mellard et al., 2010).
Although these two studies examining component models of reading comprehension have been designed and applied directly to the adult population, their results and lack of specificity for adults with low levels of literacy suggest that these may not be suitable models for adults with higher reading proficiency.