Prediction and Stability of Mathematics Skill and Difficulty

Abstract

The present study evaluated the stability of math learning difficulties over a 2-year period and investigated several factors that might influence this stability (categorical vs. continuous change, liberal vs. conservative cut point, broad vs. specific math assessment); the prediction of math performance over time and by performance level was also evaluated. Participants were 144 students initially identified as having a math difficulty (MD) or no learning difficulty according to low achievement criteria in the spring of Grade 3 or Grade 4. Students were reassessed 2 years later. For both measure types, a similar proportion of students changed whether assessed categorically or continuously. However, categorical change was heavily dependent on distance from the cut point and so more common for MD, who started closer to the cut point; reliable change index change was more similar across groups. There were few differences with regard to severity level of MD on continuous metrics or in terms of prediction. Final math performance on a broad computation measure was predicted by behavioral inattention and working memory while considering initial performance; for a specific fluency measure, working memory was not uniquely related, and behavioral inattention more variably related to final performance, again while considering initial performance.

Symbolic and Nonsymbolic Equivalence Tasks: The Influence of Symbols on Students with Mathematics Difficulty

“…To compare students with and without MD, we split the 500 students into two groups based on performance on a measure of addition fluency (e.g., Powell et al., in press). This method for identification of students with MD is in line with current MD research practices (e.g., Martin et al., ; Powell & Fuchs, ). Students ( n = 108) scoring at or below the 21st percentile (i.e., 7 or fewer correct answers on Addition Fluency ) were categorized as MD; students ( n = 305) scoring at or above the 43rd percentile (i.e., 11 or more correct answers on Addition Fluency ) were categorized as typical performers.…”

“…In this article, we categorized students falling at or below the 21st percentile on Addition Fluency as students with MD. Typical cut‐scores for determining mathematics difficulty include students scoring at or below the 40th percentile (e.g., Jitendra et al., ), 32nd percentile (e.g., Martin et al., ), 25th percentile (e.g., Bryant et al., ; Fuchs et al., ), or 10th percentile (Geary, Hoard, Nugent, & Byrd‐Craven, ). Despite not having an agreed upon cut‐score in MD research, at or below the 21st percentile on fact retrieval based assessments is a stringent cut‐score in line with current literature.…”

Behavioral Executive Functions Among Adolescents With Mathematics Difficulties

“…Behavioral EFs. Although researchers have shown that adolescents (Swanson, 2012) and primary school children (Martin et al, 2012;Raghubar et al, 2009;Wu, Willcutt, Escovar, & Menon, 2014) with MD have more problems with teacher-and parent-rated attention behaviors than their peers with average or higher mathematics scores, other behavioral EFs among students with MD are not understood. Significant relations between parent- (Wu et al, 2014) and teacherrated (Fuchs et al, 2006;Martin et al, 2012;Raghubar et al, 2009) attention behaviors and mathematics performance were found but only in primary school.…”

The Portable Document Format (PDF) accessibility practice of four journal publishers

“…Nevertheless, when the documents were read with Adobe Acrobat XI Pro's Read Out Loud feature, all articles, including those that were not tagged were read in the correct reading order. Taking one article as an example, the NVDA screen reader did not have problems interpreting the article by Martin et al (2013) which was tagged and where all the elements were tagged, with the document having a logical reading order. This confirms the benefits of appropriate tagging.…”

“…Although the article by Martin et al (2013) did not pass the test for logical reading order with PAC 1.3, which showed a warning for this criterion, it had a better tag structure (Fig. 4), as the whole content in the document was represented in the tag structure in a logical way and could be read logically with NVDA.…”