Meta-Analysis on Math Interventions 2
Meta-Analysis on Math Intervention
The meta-analysis by Gersten et al. (2009) investigated instructional components that
enhance mathematics proficiency for students with learning disabilities (LD). The meta-analysis
synthesized findings from 42 interventions on instructional approaches that enhance mathematics
proficiency for students with learning disabilities. Four categories of instructional components
were examined:
1. Approaches to instruction and/or curriculum design: These include differentiated
instruction, the concreate-representational-abstract (CRA) approach, visual aids, real-
life contexts, problem solving strategies, task analysis, scaffolding, multisensory
approaches, and peer collaboration.
2. Formative assessment data and feedback to teachers on students’ mathematics
performance: Providing teachers with information on students’ mathematics
performance.
3. Formative data and feedback to students with LD on their performance: Offering
personalized feedback to students.
4. Peer-assisted mathematics instruction: Collaborative learning among peers.
All instructional components, except for student feedback with goal-setting and peer-assisted
learning withing a class, resulted in significant mean effects ranging from 0.21 to 1.56. Two
instructional components provided practically and statistically important increases in effect size:
teaching students to use heuristics and explicit instruction.
All instructional components, except for student feedback with goal-setting and peer-
assisted learning within a class. Teaching students to use heuristics and explicit instruction stood
out as particularly effective. Educators consider a combination of these evidence-based
approaches to enhance mathematics instruction for students with learning disabilities. Structure
formative assessments, individualized feedback, and collaborative learning can positivitely
impact student outcomes.
Meta-Analysis on Math Interventions 3
Approaches to Instruction and Curriculum Design.
This category focuses on the design of instructional approaches and curriculum materials
specifically tailored for students with learning disabilities. By providing differentiated instruction
it provides flexible and individualized instruction based on the students’ needs, learning styles,
and abilities. With the Concreate-Representational-Abstract (CRA) it gradually transitions
students from concrete hands on experiences to pictorial representations and finally to abstract
mathematical concepts. By using visual aids and manipulatives it helps to enhance
understanding. These visual aids can be diagrams, charts, and models. Manipulatives can be
physical objects. By providing scaffolding it provides temporary support to help students achieve
a task independently.
When it comes to explicit instruction, it involves clear, direct teaching of specific skills or
concepts. Having direct explanation teachers will explicitly explain concepts, procedures, and
strategies. When modeling the teachers demonstrate how to solve problems step-by-step. By
gradually shifting responsibility from teacher-led instruction to independent student practice.
Formative Assessment Data and Feedback.
Formative assessment involves ongoing, continuous assessment during instruction to
inform teaching and learning. Formative assessments occur while the students are actively
engaged in learning. Teachers collect data on students’ progress, understanding, and
misconceptions. The formative assessment data and feedback to teachers had significant impact
on mathematics outcomes for students with learning disabilities. The mean effects ranged from
0.21 to 1.56, except for the student feedback with goal-setting and peer-assisted learning within a
class. Educators should incorporate formative assessment practices to enhance mathematical
instruction for students with learning disabilities.
Meta-Analysis on Math Interventions 4
When it comes to data and feedback to students with learning disabilities, it aims to
enhance student learning by providing timely information about their progress. Students will
receive personalized feedback on their mathematical performance. The teacher will identify areas
of strength and areas the need improvement from the student. Students can adjust their learning
strategies based on the feedback that is provided. Formative data and feedback contributed
significantly to improving mathematics outcomes for students with learning disabilities. The
mean is ranged from 0.21-1.56 except for student feedback with goal-setting and peer-assisted
learning within a class. Educators should provide constructive feedback to empower students
with learning disabilities in their mathematical journey.
Peer Assisted Mathematics Instruction.
Peer-assisted instruction refers to students working together in pairs or small groups learn
and solve mathematical problems. Peers will provide a supportive learning environment where
students can discuss concepts, share strategies, and clarify doubts. By having peer assisted
instruction, it provides social interaction. Collaborative learning encourages social interaction,
which can enhance motivation and engagement.
To implement peer assistance students will be paired based on similar abilities or
complementary strengths. The peers will take on different roles during instruction. The students
will collaborate with problem-solving, explaining concepts to each other, and providing
feedback. The benefits are exploration, verbalization, and confidence. Peers will explore multiple
approaches to solving problems. The students will be explaining concepts to peers to reinforce
understanding. Educators can incorporate peer-assisted learning strategies in mathematics
classrooms. Structured activities, clear guidance, and teacher facilitation are essential.
Meta-Analysis on Math Interventions 5
References
Gersten, R., Chard, D. J., Jayanthi, M., Baker, S. K., Morphy, P., & Flojo, J. (2009).
Mathematics Instruction for Students with Learning Disabilities: A Meta-Analysis of
Instructional Components. Review of Educational Research, 79(3), 1202–1242.
http://www.jstor.org/stable/40469093
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