Does Grouping Students by Ability Promote Students’ Achievement?

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

2. General Policy claim • When grouping students, factors need to put in consideration other than students’ shared abilities or achivement rates.

3. 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

4. Effect of heterogeneity on Low High Self collective efficacy discrepancies 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.

5. Interdependence, accountability, participation, social skills interaction 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 efficacy

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-scales • Procedures: • Students completed questionnaire before submitting the project. Group administered in class sessions • Data analysis: • Discrepancies between collective and self efficacy equation

8. 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.

9. Strengths • Organized lay-out • Weaknesses • Data analysis strategy • Objectives in relation to framework

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

11. 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

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: • 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

15. 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.

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.

17. Strengths • Topic • Discussion • Weaknesses • Lay-out • Instruments • Sampling size

18. Relevance to Claim • Indicates that the common practice of ability grouping should be questioned..use some of heterogeneous grouping.

19. 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

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 review • Inclusive 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 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.

23. 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.

24. Results • Students 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.

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 = .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.

26. Strengths • Lay-out • Analysis • Weaknesses • “Intelligences” • Participants’ description • Measures

27. 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.

28. 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

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 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)

31. Methods • Instruments/ 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

32. Methods.. • Data collection & Data analysis • Cross-sectional analysis • Longitudinal growth models • IRT • Signification of model

33. Results • Preliminary analysis • cross-sectional analysis • longitudinal analysis

34. Strengths • Instruments • Weaknesses • Unexplained tools • confusing lay-out and analysis

35. Relevance to Claim • Increased use of achievement grouping in elementary classrooms had a negative influence on mathematics achievement.

36. Overall Relevance to Policy • Equitable access to education