Unpacking the Unique Relationship Between Set for Variability and Word Reading Development: Examining Word- and Child-Level Predictors of Performance

Set for variability (SfV) is an oral language task which requires an individual to disambiguate the mismatch between the decoded form of an irregular word and its actual lexical pronunciation. For example, in the task, the word wasp is pronounced to rhyme with clasp (i.e., /wæsp/) and the individual must recognize the actual pronunciation of the word to be /wɒsp/. SfV has been shown to be a significant predictor of both item-specific and general word reading variance above and beyond that associated with phonemic awareness skill, letter-sound knowledge, and vocabulary skill. However, very little is known about the child characteristics and item features that affect SfV item performance. In this study we explored whether word features and child characteristics that involve phonology only are adequate to explain item-level variance in SfV performance or whether including predictors that involve the connection between phonology and orthography explain additional variance. To accomplish this we administered the SfV task (N=75 items) to a sample of grade 2-5 children (N=489) along with a battery of other reading related measures. Results suggest that variance in SfV performance is uniquely accounted for by measures tapping phonological skill along with those capturing knowledge of phonology to orthography associations, but only in children with better decoding skill. Additionally, word reading skill was found to moderate the influence of other predictors suggesting that how the task is approached may be impacted by word reading and decoding ability

Unpacking the unique relationship between set for variability and word reading development : Examining word and child-level predictors of performance

Set for variability (SfV) is an oral language task that requires an individual to disambiguate the mismatch between the decoded form of an irregular word and its actual lexical pronunciation. For example, in the task, the word wasp is pronounced to rhyme with clasp (i.e. /wæsp/), and the individual must recognize the actual pronunciation of the word to be /wɒsp/. SfV has been shown to be a significant predictor of both item-specific and general word reading variance above and beyond that associated with phonemic awareness skill, letter-sound knowledge, and vocabulary skill. However, very little is known about the child characteristics and word features that affect SfV item performance. In this study, we explored whether word features and child characteristics that involve phonology only are adequate to explain item-level variance in SfV performance or whether including predictors that involve the connection between phonology and orthography explains additional variance. To accomplish this, we administered the SfV task (N = 75 items) to a sample of grade 2–5 children (N = 489), along with a battery of reading, reading related, and language measures. Results suggest that variance in SfV performance is uniquely accounted for by measures tapping phonological skill along with those capturing knowledge of phonology to orthography associations, but more so in children with better decoding skill. Additionally, word reading skill was found to moderate the influence of other predictors suggesting that how the task is approached may be impacted by word reading and decoding ability. Educational Impact and Implications Statement: Set for variability (SfV) is a powerful predictor of word recognition skill in developing readers. The measure taps children’s ability to go from the decoded form of a word (e.g., /wʌz/for was) to the correct form (e.g., /wɒz/ for was), which is considered an important second step in word decoding. In the current study, we worked to determine what factors lead to variability in children’s ability to perform the task. We found that performance on the SfV task was highly correlated with children’s phonemic awareness skill and also related to their reading and decoding skill. This suggests that children with advanced reading and decoding skill may be using both phonological and spelling skills to go from the decoded form of a word to the correct pronunciation. The findings suggest that further studies evaluating the causal influence of SfV on reading development are warranted. (PsycInfo Database Record (c) 2022 APA, all rights reserved

Data_Sheet_1_The impact of computer–assisted technology on literacy acquisition during COVID-19-related school closures: Group–level effects and predictors of individual–level outcomes.zip

IntroductionThe COVID-19 pandemic led to school closure and loss of in-person instruction during the 2019–2020 academic year across the United States, which had a profound impact on the reading development of beginning readers. In this study we tested if a research-informed educational technology (EdTech) program–GraphoLearn–could help alleviate the COVID-19 slide. We also sought to understand the profiles of children who benefitted most from this EdTech program.MethodsWe tested participants’ (N = 172 K-2 children) early literacy skills using a standardized measure (STAR) before and after playing GraphoLearn, and used the pre to post difference as the dependent variable. We first compared children’s STAR actual and expected growth. Then we conducted a multiple regression analysis with data about engagement with GraphoLearn included as predictors. Additional predictors were extracted from GraphoLearn performance at study onset to assess children’s letter-sound knowledge, rime awareness, and word recognition.ResultsThe difference between actual average reading growth and expected growth in a regular school year was not statistically significant. This suggests that children in our sample seem to be gaining reading skills as expected in a regular school year. Our multiple linear regression model (which accounted for R2 = 48% of reading growth) showed that older children, with higher baseline GraphoLearn word recognition, who played more units in a fixed number of days, made significantly more early literacy progress.DiscussionWhile lacking a control group, our preliminary results suggest that an EdTech program such as GraphoLearn may be a useful reading instructional tool during school shutdowns. In addition, our results suggest that practice with GraphoLearn was more effective and efficient when foundational instruction was already in place.</p

A multi-disciplinary perspective on emergent and future innovations in peer review.

Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure? Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research. With the advent of web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review. We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation. Ideally, any new systems will demonstrate that they out-perform and reduce the biases of existing models as much as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages. We also propose a novel hybrid platform model that could, at least partially, resolve many of the socio-technical issues associated with peer review, and potentially disrupt the entire scholarly communication system. Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments