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Does Grouping Students by Ability Promote Students’ Achievement? Nora El-Bilawi

Does Grouping Students by Ability Promote Students’ Achievement? Nora El-Bilawi

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Does Grouping Students by Ability Promote Students’

Achievement?Nora El-Bilawi

General Policy claim

When grouping students, factors need to put in consideration other than students’ shared abilities or achivement rates.

Article 1• Wing-yi Cheng, R., Lam, S.-F., &

Chung-yan Chan, J. (2008). When high achievers and low achievers work in the same group: The roles of group heterogeneity and process in project-based learning. British journal of educational psychology, (78), 205-221. Retrieved from http://web.ebscohost.com

Background/Research Hypothesis

• would the quality of group processes predict the discrepancy between collective- and self-efficacy;

• would student achievement predict the discrepancy between collective- and self-efficacy;

• would there be an interaction between student achievement and group processes to predict the discrepancy between collective- and self-efficacy.

Effect of heterogeneity on

Low High

Self collective

efficacydiscrepancies

literature review

Grouping in project-based learning (Webb, 1982), (Lou et al., 1996) heterogeneous vs. homogeneous

Group process/four elements (Johnson, & Holubec, 1993; Kagan, 1994)

Social cognitive theory (Bandura, 1993; Bandura, 1997)

Self-efficacy collective efficacyinteraction

Interdependence, accountability, participation, social skills

MethodsParticipants:

• The participants were 1,921 students (49.9% males, 50.1% females; 39.8% seventh graders, 33.3% eighth graders and 26.8% ninth graders) from eight secondary schools in Hong Kong.

• The eight schools were located in different districts and varied in socioeconomic backgrounds and academic standards.

Grouping and projects:

students were divided into small groups and each group worked on one topic. The topics were open-ended and students were required to make discussions.

• The ways that students were grouped varied across the different schools.

• Total # of groups was 367; they were supervised individually by the teacher.

Methods..Instruments/Measures:

Hierarchical linear modeling (HLM)

Observation notes (of students quality and dynamic in groups)

sub-scales

Procedures:

Students completed questionnaire before submitting the project. Group administered in class sessions

Data analysis:

Discrepancies between collective and self efficacy equation

Results

Results indicated an interaction effect of group process and students’ within-group achievement on the discrepancy between collective and self-efficacy.

When compared with low achievers, high achievers reported lower collective efficacy than self-efficacy when group process were of low quality.

Both low and high achievers reported higher collective efficacy than self-efficacy when group process were of high quality.

Strengths

Organized lay-out

Weaknesses

Data analysis strategy

Objectives in relation to framework

Relevance to Claim

Group heterogeneity, group gender composition and group size were not related to the discrepancy between students’ collective and self-efficacy.

Article 2

• Eder, D. (1991, July). Ability grouping as a self-fulfilling prophecy: A micro-analysis of teacher-student interaction. Sociology of education, 54, 151-162. Retrieved from http://web.ebscohost.com

Background/research question

First, the importance of ability and maturity levels for assignment decisions will be discussed.

Then, the nature of teacher-student interaction will be examined as well as differences in interaction patterns across group levels.

Finally, group differences in actual and perceived reading achievement will be analyzed.

It will be argued that it is differences in learning contexts which makes ability grouping as a self-fulfilling prophecy.

literature review

Attentive behavior (Goffman, 1963)

Management (Goffman, 1967)

Methods

Participants:

• A first-grade classroom

Instruments & data collection

Over an entire academic year

Observation notes ( three day a week, three hours long, )

32 reading group lessons were video taped

Interviews with teachers

Methods..

Data analysis:

Observation notes were compared to video-tapes

• During the first stage of analysis four video-taped lessons, one from each of the four reading groups, were viewed repeatedly.

• A sociolinguistic approach will be used to analyze these data.

Results

Learning contexts varied dramatically across ability groups.

Lower ability groups were found to have more inattentiveness, teacher management, and reading turn disruptions and violations, contributing to their lower achievement.

Homogeneous grouping compounds initial learning problems by placing those children who have learning problems in the same groups.

Heterogeneous grouping might be difficult or high students, but is essential for students with lower abilities.

Strengths

Topic

Discussion

Weaknesses

Lay-out

Instruments

Sampling size

Relevance to Claim

Indicates that the common practice of ability grouping should be questioned..use some of heterogeneous grouping.

Article 3

• Signor-Buhl, S. J. (2006). Conducting district-wide evaluations of special education services: A case example. Psychology in the schools, 43(1), 109-115. Retrieved from www.interscience.wiley.com

Background/research question

Evaluate the academic outcomes of children served in self-contained versus inclusive models of special education programming.

Q.1: Can the academic progress of students, served in self-contained and inclusion programs, be compared?

Q. 2: If so, what resultswould be generated?

literature review

Inclusive models (Banerji & Dailey, 1995)

IDEA’s LRE

MethodsParticipants:

• fourth-grade inclusion classrooms attending a midsize urban district in Upstate New York.

• Permission to complete this study was secured from the district, and student confidentiality and anonymity were maintained.

• A comparison group was chosen by selecting a group of students from self-contained classrooms within the same district.

• To compare academic outcomes of students in different instructional environments, it was important

• to ensure that each student selected had participated in a special education program for a

• At least two years.

• participants with significant disciplinary difficulties based on documentation of a previous superintendent hearing and/or a manifestation review were excluded from this study to avoid possible confounding variables related to student misbehavior.

Methods..

Measures:

• Intelligence test scores were used to control for cognitive differences between the inclusive setting and the self-contained setting groups.

• Performance on the state mandated high-stakes assessment of English and Language Arts (ELA) skills for all fourth-grade students was used as a measure of achievement for participants in the study

Design/ Instruments:

• quasi-experimental design was utilized.

• All data were collected through a review of class lists, cumulative folders, and databases that contained student scores on district- and state-wide assessments.

ResultsStudents in inclusive classrooms performed significantly better on individual measures of reading achievement then students in self-contained classrooms, F (1, 57) = 7.9, p = .007.

Students in self-contained classrooms attained a mean standard score of 65.35 ( z = -2.31) on individual measures of reading achievement

Whereas, students in the inclusive classrooms achieved a mean standard score of 73.61 ( z = -1.76).

After controlling for IQ, the children in the inclusion setting performed approximately .6 SDs better on measures of reading achievement, producing a moderate effect.

Results..students who participated in an inclusive classroom performed at a comparable rate to students who were in self-contained classes, F (1, 57) = .758, p = .39. A small,

positive, effect ( SDs = .18) was found for children in inclusive settings.

Finally, results of the ELA assessment comparison suggested students in the inclusive classrooms performed better on the ELA than students in self-contained classrooms, F (1, 53) = 12.38, p = .001.

Comparison of mean scores against the four performance levels described within the ELA suggested that the self-contained group ( M = 583) fell within the lowest performance level

whereas, the inclusion group ( M = 614) fell one performance level higher.

Strengths

Lay-out

Analysis

Weaknesses

“Intelligences”

Participants’ description

Measures

Relevance to Claim

students who are educated in inclusive settings achieve at a rate that is comparable to, if not slightly better than, those who are educated in self-contained settings.

Article 4

• Chang, M., Singh, K., & Filer, K. (2009, March). Language factors associated with achievement grouping in math classrooms: a cross-sectional and longitudinal study. School effectiveness and school improvement , 20(1), 27-45. Retrieved from http://web.ebscohost.com

Background/research question

Effects of achievement grouping of on the early mathematics performance of language-minority students and compares their mathematics achievement to that of English-speaking majority students.

analysis of the differential effects of within-class grouping on the math achievement scores of students from English-speaking and non-English-speaking groups.

comprehensive methodological approach, which employs both cross-sectional and longitudinal analytical tools to interpret data from the Early Childhood Longitudinal Study-Kindergarten Cohort (ECLS-K).

In the cross-sectional analyses, they explored the direct effect of grouping practices on student performance, while looking at the long-term progress of mathematics learning in the longitudinal analysis.

literature review

Meta-analyses of the effects of grouping on achievement point to different results based on grouping practice. (Slavin’s, 1987)

Longitudinal Study of American Youth (LSAY) (Hoffer, 1992)

The interaction dynamics governing teacher-student relation (Gamoran, 1986)

MethodsInstruments/ Models:

• Early Childhood Longitudinal Survey Kindergarten Cohort (ECLS-K), a nationwide longitudinal dataset

• cross-sectional and the longitudinal growth models used four waves of assessment of cognitive growth of children from kindergarten through fifth grade from 1998 to 2003

• The total of 21,260 students who were in kindergarten in the fall of 1998 participated in the data collection in the base-year data.

• The sampling method of the ECLS-K used a multistage probability sample design. In the primary sampling of the ECLS-K,

• The units were randomly selected from 90 strata of geographic areas consisting of counties.

• In the second stage, schools were randomly selected within sampled counties.

• A total of 1,277 schools, 914 public and 363 private, participated in the data collection.

At the final stage, all students within the selected schools became final unit

Methods..

Data collection & Data analysis

Cross-sectional analysis

Longitudinal growth models

IRT

Signification of model

Results

Preliminary analysis

cross-sectional analysis

longitudinal analysis

Strengths

Instruments

Weaknesses

Unexplained tools

confusing lay-out and analysis

Relevance to Claim

Increased use of achievement grouping in elementary classrooms had a negative influence on mathematics achievement.

Overall Relevance to Policy

Equitable access to education