Hawaii State School Readiness Assessment School Results: School Year 2009-2010

2009 ◽  
Keyword(s):  
School Readiness ◽  
State School ◽  
Readiness Assessment ◽  
School Year

scholarly journals The Application of Artificial Neural Networks in Predicting Children’s Giftedness

2016 ◽  
Vol 19 (1) ◽  
pp. 49-59 ◽  
Author(s):  
Nina Pavlin-Bernardić ◽  
◽  
Silvija Ravić ◽  
Ivan Pavao Matić ◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
School Readiness ◽  
Multilayer Perceptron ◽  
Gifted Students ◽  
Test Sample ◽  
Hyperbolic Tangent ◽  
Readiness Assessment ◽  
Artificial Neural

Artificial neural networks have a wide use in the prediction and classification of different variables, but their application in the area of educational psychology is still relatively rare. The aim of this study was to examine the accuracy of artificial neural networks in predicting students’ general giftedness. The participants were 221 fourth grade students from one Croatian elementary school. The input variables for artificial neural networks were teachers’ and peers’ nominations, school grades, earlier school readiness assessment and parents’ education. The output variable was the result on the Standard Progressive Matrices (Raven, 1994), according to which students were classified as gifted or non-gifted. We tested two artificial neural networks’ algorithms: multilayer perceptron and radial basis function. Within each algorithm, a number of different types of activation functions were tested. 80% of the sample was used for training the network and the remaining 20% to test the network. For a criterion according to which students were classified as gifted if their result on the Standard Progressive Matrices was in the 95th centile or above, the best model was obtained by the hyperbolic tangent multilayer perceptron, which had a high accuracy of 100% of correctly classified non-gifted students and 75% correctly classified gifted students in the test sample. When the criterion was the 90th centile or above, the best model was also obtained by the hyperbolic tangent multilayer perceptron, but the accuracy was lower: 94.7% in the classification of non-gifted students and 66.7% in the classification of gifted students. The study has shown artificial neural networks’ potential in this area, which should be further explored. Keywords: gifted students, identification of gifted students, artificial neural networks

scholarly journals PILOTING SUPPORTIVE WAYS TO EFFECTIVELY IMPLEMENT SCHOOL READINESS PROGRAM ON THE EXAMPLE OF TBILISI KINDERGARTENS

2021 ◽  
Author(s):  
Nino Labartkava ◽  
Tamar Saginadze
Keyword(s):  
School Readiness ◽  
Role Playing ◽  
First Grade ◽  
Effective Implementation ◽  
Role Playing Games ◽  
School Year ◽  
Educational Standard ◽  
Large Size ◽  
Different Types ◽  
Selection Of

In 2015, a school readiness program was created for children who will turn 5 before the start of the school year and will start studying at the first grade of school in September. The components of the school readiness program are: «School Readiness Educational Standard», a teacher’s guideline, a collection of activities describing specific activities and provided relevant supplements.The goals of the study are: Study of the course of school readiness program on the example of Tbilisi kindergartens; Based on the situation, developing methodology for effective implementation of school readiness program. The project was implemented in Tbilisi. The selection of experimental and controlled preschool institutions was based on the existence of similar infrastructure (newly built building, existence of a yard) and three or four large size school readiness groups in kindergartenAs a result of the works carried out, experimental preschool institutions have improved in the following directions: Educators conduct dialogue and ask children questions individually and in small groups; Children have the opportunity to engage in different types of activities and games (games with rules, role playing games, movable games, creative activities); Children can independently take and use learning and gaming resources; The group uses handmade and secondary resources; Group space is organized into thematic centers; The natural materials are used in the group; Children can independently take toys and resources; Educators have planned and prepared a wide variety of activities (activity, games with rules, role playing games, project) related to the topic; Educator observes children in order to evaluate them.

scholarly journals Is more child-initiated always better? Exploring relations between child-initiated instruction and preschoolers’ school readiness

2022 ◽  
Author(s):  
Julie Vaisarova ◽  
Arthur J. Reynolds
Keyword(s):  
School Readiness ◽  
Instructional Practices ◽  
Measurement Tool ◽  
Learning And Development ◽  
Readiness Assessment ◽  
Main Effect ◽  
Sociodemographic Risk ◽  
Using Data ◽  
Shaped Pattern ◽  
Activity Report

AbstractAlthough research suggests that the use of child-initiated vs. teacher-directed instructional practices in early childhood education has implications for learning and development, the precise nature of these effects remains unclear. Using data from the Midwest Child-Parent Center (CPC) Expansion Project, the present study examined the possibility that a blend of child- and teacher-directed practices best promotes school readiness among preschoolers experiencing high levels of sociodemographic risk and explored whether the optimal blend varies based on child characteristics. Sixty-two CPC preschool teachers reported their instructional practices throughout the year, using a newly developed questionnaire—the Classroom Activity Report (CAR). The average reported proportion of child-initiated instruction was examined in relation to students’ end-of-year performance on a routine school readiness assessment (N = 1289). Although there was no main effect of child-initiated instruction on school readiness, there was a significant interaction between instruction and student age. Four-year-olds’ school readiness generally improved as the proportion of child-initiated time increased, while 3-year-olds showed a U-shaped pattern. The present findings add to the evidence that child-initiated instruction might support preschoolers’ school readiness, although they also suggest this relation may not always be linear. They also point to the importance of examining instructional strategies in relation to student characteristics, in order to tailor strategies to the student population. The CAR has potential as a brief, practical measurement tool that can support program monitoring and professional development.

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