Empirical Research

How to Identify At-Risk Students: Solutions and Strategies

Reference:

Fuchs, L. S., Fuchs, D., & Prentice, K. (2005). Responsiveness to mathematical problem-solving instruction: Comparing students at risk of mathematics disability with and without risk of reading disability. Journal of Learning Disabilities, 37 (4), 293-306.

Purpose/Objective/Research Question/ Focus of Study:

This study asks the following question: Does third-grade students’ responsiveness to effective classroom instruction on math problem solving vary as a function of disability risk status and performance dimension?

Setting:

The setting for the study was six schools in a southeastern urban district.

Populations/Participants/Research Subjects:

Sixteen third grade teachers volunteered to participate in the study. They were randomly assigned to two conditions which were 8 transfer plus self-regulation and 8 control. 301 students were present. Four groups of students were identified by using the following specific criteria: 1) not at risk of reading or mathematics difficulties (no disability risk- NDR), 2) at risk of math and reading disability only (MDR/RDR), 3) at risk of math disability only (MDR only), and at risk of reading disability only (RDR only). In the control group, there were 20 MDR/RDR students, 5 MDR-only students, 12 RDR-only students, and 60 NDR students. In the experimental condition, there were 12 MDR/RDR students, 8 MDR-only students, 15 RDR-only students, and 69 NDR students.

Intervention/Program/Practice:

16-week treatment and disability risk status on understanding and computation were examined. The effective treatment combined explicit instruction to transfer and self-regulated learning.

Base Treatment-All teachers followed the district’s curriculum. They used the math program, Math Advantage.

Experimental Treatment-One 3-week unit addressed basic math problem solving which included six lessons across three weeks. Next, four 3-week units combined transfer instruction with self-regulation. Two cumulative review sessions were conducted.

Transfer-Transfer included teaching of rules for problem solution, teaching for transfer, and cumulative review. Transfer lessons included the three components: teachers explicitly taught the concept of the transfer, familiar problems were formulated to look novel, and dyatic classroom, individual classroom, and homework practice occurred.

Self-regulation-Self-regulation incorporated six activities, interwoven throughout all six sessions of each unit: students scored the independent class problem, charted daily scores, inspected the charts, scored their homework prior to submitting it; teachers provided students with an opportunity to report examples of how they had transferred the unit’s problem structure to another part of the school day, teachers recorded the number of students who had completed, scored, and submitted their homework and the number of pairs that reported a transfer event.

Delivery- There were six lessons in each of the five units plus two cumulative review sessions after winter break. Each lesson lasted 25 to 40 minutes, for a total of 32 sessions. Research assistants taught the first problem solution lesson and the first transfer lesson of each unit to entire classes with teachers present. Teachers taught the remaining sessions.

Fidelity of Treatment-Before delivery of each lesson, research assistants made a checklist of the essential information in the script. Every session was audiotaped. At the end of the study, two research assistants independently listened to tapes while completing the checklist to identify the percentage of points deducted.

Data Collection and Analysis Measures:

-The scores from the preceding spring’s TerraNova state assessment were collected to identify the risk of disability using a 25^th percentile cutoff.

-Trained research assistants collected data in a whole-class arrangement. Pre-testing occurred within the 3 weeks before treatment. Post-testing occurred within 3 weeks following treatment.

-On each performance dimension (conceptual underpinnings, computation, and labeling), for each measure, a three-factor ANOVA was conducted.

-The TerraNova Computation subtest was used to measure responsiveness to treatment for mathematics. The Reading Comprehension subtest was used to index responsiveness in reading.

Results and Findings:

Immediate Transfer- On conceptual underpinnings, results indicated that MDR/RDR students improved the least as a function of treatment. On computation, results indicated that MDR/RDR, MDR-only, and RDR-only students improved less as a function of treatment than NDR students.

Near Transfer- On conceptual underpinnings, results indicated that MDR/RDR students improved less than NDR students. On computation, the results indicated that MDR/RDR, MDR-only, and RDR-only students improved less than NDR students. On labeling, results indicated that MDR/RDR, MDR-only, and RDR-only students improved less than NDR students.

Conclusions and Recommendations:

-The results revealed different levels of responsiveness as a function of students’ status. MDR and RDR students demonstrated less improvement than NDR students. Addressing the needs of children who enter problem-solving instruction with MDR or RDR may require explicit work in computation and labeling. To improve the study’s design in the future, students with MDR or RDR might be pre-selected and randomly assigned to treatment. Also, future research must also be designed to incorporate larger numbers of students.

-In response to the problem-solving treatment, students with MDR-only or RDR-only benefited comparable to those of their NDR peers. Students with MDR/RDR responded more slowly. For students with MDR-only, RDR-only, and MDR/RDR, supplementary instruction should focus on computation and labeling.

My Reaction to the Study

            My hypothesis was correct in this study. I assumed that the MDR/RDR students would improve the least and that the MDR/RDR, MDR-only, and RDR-only students would improve less than NDR students. It is obvious that students who are at risk of math and reading difficulties would perform worst than those students who are not at risk for either math or reading disabilities. The article implied that to identify at-risk students, one must administer several assessments to the students. In this study, the TerraNova assessment was administered to the students to identify the risk of disability. The article also stated that a solution or strategy was to provide explicit instruction in computation and labeling, especially for those students who were at-risk of reading and math disabilities.

            To my surprise, students with MDR-only or RDR-only benefited comparable to those of their NDR peers in response to the problem-solving treatment. However, students with MDR/RDR responded more slowly. It makes sense that students who are at-risk for both reading and math disabilities would perform more slowly than their peers. They are at-risk of two disabilities. The article stated a solution or strategy for students with MDR-only, RDR-only, and MDR/RDR was to provide supplementary instruction that focuses on computation and labeling.