Supplemental Material for Supporting Teachers’ Use of Data-Based Instruction to Improve Students’ Early Writing Skills

Data from a small randomized control trial of teachers’ use of Data-Based Instruction (DBI) for early writing were analyzed to determine the influence of teacher knowledge, skills, and treatment fidelity on student Curriculum-Based Measurement (CBM) slope. Participants included 11 elementary grade teachers who delivered intensive intervention in early writing and their students ( n = 31), all identified as either at risk for or with disabilities that affect their writing. Teachers received professional development and ongoing coaching to support the implementation of DBI for improving their students’ early writing skills. Results from a multiple regression analysis suggest that teacher knowledge and skills in DBI was strongly related to student CBM slope in early writing ( p < .01) and a small but significant relation between fidelity of writing instruction and student CBM slope ( p < .01). Implications for instructional coaching and improving student writing progress are discussed.

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International Perspectives on Understanding and Improving Teachers’ Data-Based Instruction and Decision Making: Introduction to the Special Series

Journal of Learning Disabilities ◽

10.1177/00222194211017531 ◽

2021 ◽

Vol 54 (4) ◽

pp. 239-242

Author(s):

Christine A. Espin ◽

Natalie Förster ◽

Suzanne E. Mol

Keyword(s):

Decision Making ◽

General Education ◽

International Perspective ◽

Series Data ◽

Instructional Decision Making ◽

Special Series ◽

Use Of Data ◽

International Perspectives ◽

Based Instruction ◽

Instructional Decision

This article serves as an introduction to the special series, Data-Based Instruction and Decision-Making: An International Perspective. In this series, we bring together international researchers from both special and general education to address teachers’ use (or non-use) of data for instructional decision making. Via this special series, we aim to increase understanding of the challenges involved in teachers’ data-based instructional decision making for students with or at-risk for learning disabilities, and to further the development of approaches for improving teachers’ ability to plan, adjust, and adapt instruction in response to data.

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Effects of Early Writing Intervention Delivered Within a Data-Based Instruction Framework

Council review ◽

10.1177/0014402916667586 ◽

2016 ◽

Vol 83 (3) ◽

pp. 281-297 ◽

Cited By ~ 5

Author(s):

Pyung-Gang Jung ◽

Kristen L. McMaster ◽

Robert C. delMas

Keyword(s):

Students With Disabilities ◽

Significant Interaction ◽

Control Treatment ◽

Early Writing ◽

Writing Intervention ◽

Significant Treatment ◽

Education Status ◽

Based Instruction ◽

Business As Usual ◽

Preliminary Support

We examined effects of research-based early writing intervention delivered within a data-based instruction (DBI) framework for children with intensive needs. We randomly assigned 46 students with and without disabilities in Grades 1 to 3 within classrooms to either treatment or control. Treatment students received research-based early writing intervention within a DBI framework for 30 min, 3 times per week, for 12 weeks. Control students received business-as-usual writing instruction. We measured writing performance using curriculum-based measures (CBM) and Woodcock Johnson III Tests of Achievement (WJ III). We found significant treatment effects on CBM outcomes (Hedges g = 0.74 to 1.36). We also found a significant interaction between special education status and condition on the WJ III favoring treatment students with disabilities (Hedges g = 0.45 to 0.70). Findings provide preliminary support for using a combination of research-based intervention and DBI with students with intensive writing needs.

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A Recommender System Supporting Teachers to Author Learning Sessions in Decision-Making

Intelligent Techniques in Recommendation Systems ◽

10.4018/978-1-4666-2542-6.ch001 ◽

2013 ◽

pp. 1-29

Author(s):

Arnoldo Rodríguez

Keyword(s):

Decision Making ◽

Automatic Generation ◽

Teaching Materials ◽

Web Based ◽

Problem Of Time ◽

Use Of Data ◽

Network Topologies ◽

Time To Learn ◽

Time Required ◽

Supporting Teachers

This chapter pays attention to the automatic generation and recommendation of teaching materials for teachers who do not have enough time to learn how to use authoring tools for the creation of materials to support their courses. To overcome the difficulties, the research is intended to solve the problem of time needed to create adapted case studies for teaching decision-making in network design. Another goal is to reduce the time required to learn the use of an authoring tool to create teaching materials. Thus, the author presents an assistant that provides adapted help for teachers, generates examples automatically, verifies that any generated example fits in the class of examples used by the teacher, and recommends personalized examples according to each teacher’s preferences. He studies the use of data related to teachers to support the recommendation of teaching materials and the adaptation of Web-based support. The automatic generation and test of examples of network topologies are based on a probabilistic model, and the recommendation is based on Bayesian classification. This investigation also looks at problems related to the application of Artificial Intelligence (AI) to support teachers in authoring learning sessions for Adaptive Educational Hypermedia (AEH).

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