Predictive assessment of reading

Study 1 retrospectively analyzed neuropsychological and psychoeducational tests given to N=220 first graders, with follow-up assessments in third and eighth grade. Four predictor constructs were derived: (1) Phonemic Awareness, (2) Picture Vocabulary, (3) Rapid Naming, and (4) Single Word Reading. Together, these accounted for 88%, 76%, 69%, and 69% of the variance, respectively, in first, third, and eighth grade Woodcock Johnson Broad Reading and eighth grade Gates-MacGinitie. When Single Word Reading was excluded from the predictors, the remaining predictors still accounted for 71%, 65%, 61%, and 65% of variance in the respective outcomes. Secondary analyses of risk of low outcome showed sensitivities/specificities of 93.0/91.0, and 86.4/84.9, respectively, for predicting which students would be in the bottom 15% and 30% of actual first grade WJBR. Sensitivities/specificities were 84.8/83.3 and 80.2/81.3, respectively, for predicting the bottom 15% and 30% of actual third grade WJBR outcomes; eighth grade outcomes had sensitivities/specificities of 80.0/80.0 and 85.7/83.1, respectively, for the bottom 15% and 30% of actual eighth grade WJBR scores. Study 2 cross-validated the concurrent predictive validities in an N=500 geographically diverse sample of late kindergartners through third graders, whose ethnic and racial composition closely approximated the national early elementary school population. New tests of the same four predictor domains were used, together taking only 15 minutes to administer by teachers; the new Woodcock-Johnson III Broad Reading standard score was the concurrent criterion, whose testers were blind to the predictor results. This cross-validation showed 86% of the variance accounted for, using the same regression weights as used in Study 1. With these weights, sensitivity/specificity values for the 15% and 30% thresholds were, respectively, 91.3/88.0 and 94.1/89.1. These validities and accuracies are stronger than others reported for similar intervals in the literature.     

The Disruptive Qualities of Linked Data in the Library Environment: Analysis and Recommendations

Libraries are looking for a better way to encode and share their data. Christensen's disruptive technologies theory provides a framework for evaluating linked data and thinking about future uses of library technology. Because of its lack of use and technical weaknesses, linked data is not yet poised to emerge as a disruptive innovation. It has the potential, however, to become disruptive and should be explored first in spin-offs that supplement library data or provide access to other electronic content. Library systems under development should focus on remaining nimble and open to unforeseen future technologies and uses.     

Fostering children's acceptance of educational apps: The importance of designing enjoyable learning activities

Educational applications (apps) offer opportunities for designing learning activities children enjoy and benefit from. We redesigned a typical mobile learning activity to make it more enjoyable and useful for children. Relying on the technology acceptance model, we investigated whether and how implementing this activity in an app can increase children's intention to use. During the 27-day study, children (N = 103, 9–14 years) used the app to memorize one-sentence learning plans each day. Children used three different app-based learning activities throughout the study. In two standard activities, children reread or reassembled the words of the plan. In the redesigned activity, children represented the meaning of the plan with emojis. Children repeatedly reported on their attitude towards each activity. Subsequently, children reported perceived enjoyment and intention to use the app. Results showed children found the emoji activity most enjoyable, and enjoyment of the emoji activity contributed uniquely towards intention to use. Additionally, children's enjoyment of the app mediated their intention to use the app in the future. Overall, the study suggests that children's enjoyment of an app is crucial in predicting their subsequent intention to use, and it provides a concrete example of how emojis can be used to boost enjoyment.

Practitioner notes

What is already known about this topic

• Educational applications provide children with unrestricted access to mobile learning resources.
• Positive attitudes towards educational applications predict behavioural intention to use these applications, at least in young adults.
• There is a need for more research examining the relevance of enjoyable learning activities in fostering children's sustained usage of an educational application.

What this paper adds

• Positive attitude towards the use of emojis during learning activities uniquely contributed to children's behavioural intention to use the application.
• Perceived enjoyment predicted behavioural intention to use the application.
• Perceived enjoyment mediated the effect of attitude towards using learning activities on the behavioural intention to use the mobile educational application.

Implications for practice and/or policy

• These findings highlight the importance of enjoyment for children's' acceptance of educational applications.
• Enjoyable learning activities are necessary to ensure sustained usage of educational applications.
• The paper provides a concrete example of how emojis can be used to boost enjoyment of a typical mobile learning activity.