Presentation on theme: "Does Grouping Students by Ability Promote Students’ Achievement?"— Presentation transcript:
1 Does Grouping Students by Ability Promote Students’ Achievement? Nora El-Bilawi
2 General Policy claimWhen grouping students, factors need to put in consideration other than students’ shared abilities or achivement rates.
3 Article 1Wing-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), Retrieved from
4 Background/Research Hypothesis Effect of heterogeneity onLow HighSelf collectiveefficacywould 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.discrepancies
5 literature reviewGrouping in project-based learning (Webb, 1982), (Lou et al., 1996) heterogeneous vs. homogeneousGroup process/four elements (Johnson, & Holubec, 1993; Kagan, 1994)Social cognitive theory (Bandura, 1993; Bandura, 1997)Self-efficacy collective efficacyInterdependence, accountability, participation, social skillsinteraction
6 Methods Participants: 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.
7 Methods.. Instruments/Measures: Hierarchical linear modeling (HLM) Observation notes (of students quality and dynamic in groups)sub-scalesProcedures:Students completed questionnaire before submitting the project. Group administered in class sessionsData analysis:Discrepancies between collective and self efficacy equation
8 ResultsResults 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.
9 Strengths Weaknesses Organized lay-out Data analysis strategy Objectives in relation to framework
10 Relevance to ClaimGroup heterogeneity, group gender composition and group size were not related to the discrepancy between students’ collective and self-efficacy.
11 Article 2Eder, D. (1991, July). Ability grouping as a self-fulfilling prophecy: A micro- analysis of teacher-student interaction. Sociology of education, 54, Retrieved from
12 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.
13 literature review Attentive behavior (Goffman, 1963) Management (Goffman, 1967)
14 Methods Participants: Instruments & data collection A first-grade classroomInstruments & data collectionOver an entire academic yearObservation notes ( three day a week, three hours long, )32 reading group lessons were video tapedInterviews with teachers
15 Methods.. Data analysis: Observation notes were compared to video-tapesDuring 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.
16 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.
18 Relevance to ClaimIndicates that the common practice of ability grouping should be questioned..use some of heterogeneous grouping.
19 Article 3Signor-Buhl, S. J. (2006). Conducting district-wide evaluations of special education services: A case example. Psychology in the schools, 43(1), Retrieved from
20 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?
21 literature reviewInclusive models (Banerji & Dailey, 1995)IDEA’s LRE
22 Methods Participants: 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 importantto ensure that each student selected had participated in a special education program for aAt 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.
23 Methods.. Measures: Design/ Instruments: 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 studyDesign/ 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.
24 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 ( z = -2.31) on individual measures of reading achievementWhereas, students in the inclusive classrooms achieved a mean standard score of ( 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.
25 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 =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 levelwhereas, the inclusion group ( M = 614) fell one performance level higher.
27 Relevance to Claimstudents 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.
28 Article 4Chang, 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), Retrieved from
29 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.
30 literature reviewMeta-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)
31 Methods Instruments/ Models: Early Childhood Longitudinal Survey Kindergarten Cohort (ECLS-K), a nationwide longitudinal datasetcross-sectional and the longitudinal growth models used four waves of assessment of cognitive growth of children from kindergarten through fifth grade from 1998 to 2003The total of 21,260 students who were in kindergarten in the fall of 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
32 Methods.. Signification of model Data collection & Data analysis Cross-sectional analysisLongitudinal growth modelsIRTSignification of model