effects of partner's ability on the achievement and conceptual organization of high-achieving...

LEARNING

Gregory J. Kelly and Richard E. Mayer, Section Editors

Effects of Partner’s Ability on theAchievement and ConceptualOrganization of High-AchievingFifth-Grade Students

GLENDA CARTERDepartment of Mathematics, Science, and Technology Education, North CarolinaState University, Raleigh, NC, USA

M. GAIL JONES, MELISSA RUACollege of Education, University of North Carolina at Chapel Hill, NC, USA

Received 5 October 1999; revised 27 July 2001; accepted 27 November 2001

ABSTRACT: This study investigated high-achieving fifth-grade students’ achievementgains and conceptual reorganization during a unit on convection. Specifically, the achieve-ment and cognitive gains that occurred as a result of interactions of high-achieving studentswith a high-achieving or low-achieving laboratory partner were compared. The study de-sign included an instructional sequence of three dyadic inquiry investigations related toconvection currents as well as pre- and postassessments consisting of a multiple-choicetest, card sorting task, construction of a concept map, and an interview. Results showed nosignificant differences for achievement of high-achieving students regardless of the partner’sachievement level and only slight differences in conceptual reorganization. The implica-tions of this study for heterogeneous grouping and construction of knowledge by dyads isdiscussed. C© 2002 Wiley Periodicals, Inc. Sci Ed 87:94–111, 2003; Published online in WileyInterScience (www.interscience.wiley.com). DOI 10.1002/sce.10031

INTRODUCTION

Nearly all of the current reform documents in education call for students to work insmall cooperative or collaborative groups. Within science, The National Science EducationStandards advocate for the use of small student learning groups:

Correspondence to: Glenda Carter; e-mail: glenda [email protected]

C© 2002 Wiley Periodicals, Inc.

EFFECTS OF PARTNER’S ABILITY 95

An important stage of inquiry and of student science learning is the oral and written discoursethat focuses the attention of students on how they know what they know and how theirknowledge connects to larger ideas, other domains, and the word beyond the classroom. . . Using a collaborative group structure, teachers encourage interdependency among groupmembers, assisting students to work together in small groups so that all participate in sharingdata and in developing group reports. (National Research Council, 1996, p. 36)

Specific instructional strategies such as peer tutoring, cooperative learning, and Padaeiaseminars are founded on the belief that student–student discourse promotes cognitivegrowth. Research on learning in small group settings is beginning to provide evidencethat peer interactions influence students’ learning (Carter & Jones, 1994; Jones and Carter,1994; Swing & Peterson, 1982). This verbalization among students can be an important partof learning as noted by Slavin (1991), “as any teacher knows, we learn best by describingour current state of knowledge to others” (p. 70). There is preliminary evidence that it isnot just the verbal interactions that impact learning but who a student interacts with duringsmall group interactions can impact concept attainment (Carter, 1990).

Initial research has supported the general benefits of peer interactions and small grouplearning (Slavin, 1986, 1990). However, more recent studies are starting to uncover thecomplexities of small group learning and evaluate the impact of the composition of smallgroups on students of different abilities. There is evidence that middle-achieving studentsbenefit from working in homogeneous groups (Lou et al., 1996; Webb, 1982) and forlow-achieving students, heterogeneous grouping seems to provide the greatest opportunityfor learning (Carter & Jones, 1994; Jones & Carter, 1994; Webb et al., 1998). However,there are conflicting results from studies that have examined grouping effects for high-achieving students. Some studies report no advantage for homogeneous placements ofhigh-achieving students (Lou et al., 1996; Webb, 1995). Results from other studies suggestthat homogeneous grouping provides high-achieving students with enhanced opportunitiesfor intellectual growth (Allan, 1991; Fuchs et al., 1998; Webb et al., 1998). Feldhusenand Moon (1992) maintain that “grouping them (high-achieving students) with low oraverage level achievers cannot help but retard progress in learning” (p. 63). Futhermore,Feldhusen and Moon argue that “(g)rouping heterogeneously and providing cooperativelearning in heterogeneous groups leads to lowered achievement and motivation as well aspoorer attitudes toward school” (p. 63). Robinson (1990) and Ellett (1993) suggest thatusing bright students to teach others can be exploitative of those who are more able. Theconcern is that high-achieving students are “robbed . . . of consistent opportunities to learnthrough real struggle” (Fiedler-Brand, Lange, & Winebrenner, 1992, p. 6).

Some of the most vocal criticism of heterogeneous small learning groups has emergedfrom advocates of gifted education who argue that high-achieving students should havethe stimulation of working along side of other high-achieving students. In addition, somegifted education researchers have suggested that long-term placement of high-achievingstudents with low-achieving students in small group instructional settings can limit thehigh-achieving students’ opportunities to learn. A study of gifted students’ perspectives ofgroup learning found that gifted students indicate that they do not understand the materialbetter as a result of explaining it to others and resent having to explain material to otherstudents (Mathews, 1992).

Educators from different arenas hold contrasting views of heterogeneous grouping prac-tices. Gallagher, Coleman, and Nelson (1995) surveyed middle-school educators and educa-tors of the gifted about their views on the use of heterogeneous grouping of students. Theyfound that middle-school educators were not supportive of grouping students by ability,whereas educators from the gifted education felt that gifted students benefited from being

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grouped together. One educator of gifted students explained, “I am concerned that movementaway from ability grouping will hurt the development of gifted students” (p. 73). In contrast,a middle-school educator said, “I feel strongly that middle level students should not be abil-ity grouped” (p. 73). Educators of gifted students strongly agreed with the survey item thatstated, “gifted students resent being the ‘junior teacher’” (p. 70), whereas middle-schooleducators tended not to agree with the statement. The researchers asked the two groups toagree or disagree with the premise that “(g)ifted students develop critical social and leader-ship skills in cooperative learning” (p. 70). Again, middle-school educators agreed with thestatement in support of the value of cooperative learning, and the gifted educators disagreed.

In a previous study on the effects of dyad pairing, we found the achievement of high-achieving students in a science classroom was not negatively affected by working with a low-achieving partner (Carter & Jones, 1994; Jones & Carter, 1994). Although achievement wasnot significantly different, these studies revealed that there were significant differences in theverbal and laboratory behaviors of high-achieving students dependent on the achievementlevel of their partner. High-achieving students working with low-achieving students spokemore words, took more turns speaking, and exhibited more helping behaviors than whenworking with a high-achieving partner. The differences in verbal and laboratory behaviorslend credence to the hypothesis that a high-achieving student may be able to construct a moreflexible, applied conceptual framework by mediating learning for a less capable student.However, the type of data collected in the previous study was not sufficient to elucidatedifferences in the conceptual constructions of the high-achieving students.

Work by Bargh and Schul (1980) suggests that high-achieving students working with low-achieving partners could build richer constructions as a result of the cognitive restructuringthat takes place as a result of giving explanations. Or high-achieving students may encodeinformation by means of multiple representations as a result of the increase in the amountof time they spend processing information when working with low-achieving students (Chiet al., 1989). Alternatively, high-achieving students could regress as a result of interactingwith a partner whose thinking is at a lower level. This is particularly true if the high-achievingstudent is not confident about her own knowledge level (Tudge, 1990).

As widespread use of heterogeneous groups increases, it is imperative that we examinehigh-achieving students’ achievement in a variety of contexts to ensure that grouping strate-gies maximize learning for all students. Our goal in the present study is to look carefullyat the science achievement and conceptual organization of high-achieving students in rela-tionship to the ability of their partner. Examining conceptual outcomes of student pairingsis an important first step to understanding the impact of grouping in science classes.

The traditional instruments that are selected to measure achievement of students in smallgroups may not measure the complex changes that take place as students work together whilelearning higher order concepts. Findings from longitudinal studies (Maher, 1996) suggestthat evidence of the effects of instructional interactions may not emerge until several yearsafter instruction because some effects are not generally elucidated through traditional as-sessments. In this study, unlike other studies, we expand the assessment net to includemultidimensional scaling, concept mapping, interviews, and achievement tests in an effortto capture additional information about the impact of peer grouping on high-achieving stu-dents’ cognitive outcomes. The use of only standard achievement tests has been criticized aslacking sufficient sensitivity to measure the academic achievement of high ability students(Fiedler-Brand, Lange, & Winebrenner, 1992; Kulik, 1991; Slavin, 1990). In particular,Slavin (1991) suggests that “standardized tests are certainly not designed to adequatelymeasure the achievement of the top 33 percent of students” (p. 69). The use of multidi-mensional scaling, interviews, and concept mapping allows us to examine the knowledgeconnections, applications, and representations of high-achieving students and to test the


hypotheses proposed by Chi et al. (1989) that high-achieving students may encode infor-mation differently as a result of whether or not they work with a low-achieving student.

In this study we explored the following questions:

1. Does the achievement level of the laboratory partner of a high-achieving studentaffect the achievement of the high-achieving student?

2. Does the achievement level of the laboratory partner of a high-achieving studentaffect the organization or application of concepts of the high-achieving student?

METHODOLOGY

Subjects

This study was conducted in a suburban school in the southeastern region of the USA usingthe fifth-grade population (9–11-year-olds) of students from whom parental permission hadbeen obtained. Students were identified as high-achieving1 (upper 25%), average-achieving(middle-range), or low-achieving (lowest 25%) based on their California Achievement TestScores for Reading (CAT-R). CAT-R standardized scores provide a reasonable indicationof a student’s ability to read and comprehend novel material. The rationale for using thesescores was threefold. One, within the school system these achievement scores are usedas one of the indicators for placing students into ability-grouped enrichment or remedialclasses since the scores are reasonable predictors of a student’s aptitude and success inschool. Two, a student’s relative verbal achievement may influence the types of interactionsthat would occur. And three, the level of language development can be an indication of thelevel of thinking (Pressley, 1995).

In elementary classrooms, students typically work with a partner or in small groups duringscience instruction. In order to situate this study in an instructionally relevant context, weassigned each student a laboratory partner. Students were accustomed to working with theother students in the class as partners during regular instruction. The study took place inthe spring of the year, increasing the likelihood that pairings for this study were not novel.Additionally, each classroom teacher reviewed partner assignments prior to beginning thestudy and changed assignments if partners had previously not worked well together.

Dyads were formed on the basis of CAT-R quartiles scores. As a result, high-achievingstudents were paired either with another high-achieving student or with a low-achievingstudent for the series of instructional investigations. Dyads were used in this study (ratherthan small groups) to maximize the opportunity to trace the potential effect of each individ-ual’s participation. Additionally, the work of Kempa and Ayob (1991) suggests that evenwithin larger groups the exchange is most frequently limited to two members at a giventime. Therefore using dyads seemed likely to increase the engagement of each member andperhaps enhance the effects of the social interactions yet still reflect normal classroom in-struction. All middle-achieving students were placed in homogeneous dyads, and althoughthey participated in the project in the context of the class, dyads of interest for this studywere those containing at least one high-achieving student (n = 54). Within five differentelementary classes, a subset of two high–high and two high– low achieving dyads wererandomly selected as target dyads for intense case study. These dyads were the focus offield observations as well as subjects for individual pre- and postinstruction interviews. Thestudy began with 40 case study students (20 targeted dyads); however, because of student

1 This study addresses high-achieving students. Although some authors have defined gifted students asthe top 33%, others define gifted students as the top 3% (Rogers, 1993). The present study addresses onlyhigh-achieving students and does not claim to address gifted students.

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absences only 32 students (16 dyads; 10 high– low, 6 high–high) were able to completethe entire sequence of instruction and two additional days of pre- and postassessments.High– low dyads were single gender (4 female dyads, 6 male dyads) as were the high–highdyads with the exception of one group (4 female dyads, 1 male dyad, 1 male– female dyad).The research study was conducted over a 4-week period with five classes of fifth-grade stu-dents, targeting approximately eight students in each class for intense data collection. Eachstudent worked with his or her assigned partner for the duration of the study. The principalinvestigators planned and directed the assessment and implemented the instruction.

A pilot study was carried out prior to the beginning of the research study to assess theusefulness of the quantitative and qualitative measures selected and to evaluate the formatof instruction. The overall utility of the plan was confirmed during the pilot study althoughminor changes were made in the type of equipment used and the length of the investigations.

Classroom Activities

After examining the state mandated course of study for fifth-grade science, the topicof convection was chosen as the instructional focus. This concept was not indicated inthe course of study for earlier grades and was one for which developmentally appropriateactivities could easily be devised. Howe et al. (1995) argue that the use of heat and coolingare particularly appropriate topics for research on peer collaboration since these are complexinstructional topics that elicit prior experiences from nearly all students. After reviewingrelevant objectives and perusing available materials relating to convection, three laboratoryinvestigations were developed which averaged 50 min per session and could be carriedout in the context of the students’ normally scheduled science classes. Although this is arelatively brief period of instruction (150 min), this exceeds the time typically allotted to thetopic of convection in fifth-grade and we wanted to come as close as possible to duplicatingconditions of “standard” instructional practices.

During the laboratory sessions, the investigator–student interaction was limited to pro-cedural directions and monitoring. There was little direct interaction between teacher-researcher and students so that possible effects would be dependent on student–studentinteractions, rather than student– teacher interactions. Students were instructed to workonly with their partners, and with few exceptions students complied with this request. Stu-dents were given laboratory sheets which outlined the procedure for the investigations andprovided questions to promote student reflections and interactions about observed phenom-ena. During the first two investigations students participated in a series of activities thatrequired them to make detailed observations of convection currents using food coloring andwater. During the third investigation, dyads observed convection currents in air and workedtogether to answer questions about the similarities and differences they had observed forconvection currents in water and in air. Throughout instruction only one laboratory recordsheet was provided per dyad, and students were instructed to discuss all answers and reachconsensus with their partners before recording observations or responding to questions onthe lab sheets. This was done to further encourage verbal interactions between dyad partners.

Research Methods and Instruments

A 20-item, multiple-choice (four response choice/item) convection test was developedand reviewed by a panel of four physicists and two physics educators for content validityand technical correctness. Test items were modified based on the panel’s assessment ofeach item’s validity. The test was piloted to ascertain readability and clarity with a classof fifth-grade students from a school demographically similar to the one used in the study.


Figure 1. Sample items from the convection test.

The resulting form of the test has a reliability (KR-20) of 0.73. Sample items used on thefinal form are illustrated in Figure 1.

The convection test was administered to the students 2 weeks prior to instruction. Oneweek prior to instruction students were asked to construct a concept map focused on thetopic of heat. Before drawing the concept map on heat, each student was instructed on theprocedures for drawing a concept map, practiced drawing a concept map on an unrelatedtopic, and received feedback and additional practice on map drawing skills when needed.After mastering the basic skills of map construction, students were instructed to brainstorma list of concepts they attributed to the topic of heat and to construct their map. Upon com-pletion of the mapping task, students were given 20 cards on which terms had been printedthat related to heat. These terms were selected based on the frequency of usage in explana-tions of convection found in fifth-grade textbooks. Students were asked to individually sortthe cards into piles according to the way in which they believed the words were related.After the sorting was completed, the students placed a paperclip on each of the piles andplaced the clipped piles into a plastic bag with their name on it. Then target students wereindividually interviewed regarding their card sorting rationale, their concept map organiza-tion, and their ideas about heat. In the second phase of the preinstruction interview studentswere given a picture of an ocean and beach (Gould, 1988) and were asked to draw arrowsindicating how they thought air would move in the situation pictured.

One week following the completion of the convection investigations, the convection testwas readministered and students were asked to complete another card sorting task. Theywere provided with their original concept maps and were instructed to review them. Oncethe students had an opportunity to study their preinstruction maps, they were asked to draw a

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postinstruction concept map on heat by redrawing their maps with no changes, revising theirpreinstruction map, or drawing a new map. The use of successive maps has been utilized inother studies as a mechanism to examine the restructuring and growth of knowledge (Jones& Vesilind, 1996; Cary, 1986).

The target dyads were again interviewed individually about the way they had sorted thecards and the organization of their concept maps. Then each student was provided withanother beach picture and an additional picture illustrating and identifying hot mountainsand a cool lake (Gould, 1988). For both pictures, students were asked to draw arrowsindicating how they thought air would move in the picture and to explain their drawingsto the interviewer. Both pictures were provided to assess students’ ability to apply theirunderstanding of convection currents to a novel context.

DATA ANALYSES

Convection Test

Assessments were chosen in an effort to examine the impact of the laboratory investi-gations from a multilevel perspective. The convection test was administered to determineachievement gains and is representative of the type of test a classroom teacher would ad-minister following instruction. The convection test analysis was carried out using ANCOVAcomparisons of pre- and posttest score means to help identify achievement differences.

Card Sort

The card sorting task provided an opportunity to examine the interconnectedness ofconcepts related to heat. The analysis involved the creation of a matrix that representedhow frequently students placed any one of the 20 concepts from the card sorting task withanother concept. Multidimensional scaling algorithms (Young & Rheingans, 1991) thentook pairwise proximity estimates for the set of concepts and generated multidimensionalmodels of these concepts. As a component of the analysis the multidimensional scalings wererotated along the axes to examine how the concepts clustered in more than one dimension.Once concept clusters were identified, interpretation was a subjective process in whichwe sought to understand the underlying attributes of the clustering concepts (Kruskal &Wish, 1991). Multidimensional scaling solutions have been shown to be psychologicallymeaningful for analogy completion (Rips, Shoben, & Smith, 1973), similarity judgment time(Hutchinson & Lockheed, 1977), categorical judgment time (Shoben, 1976), and judgmentsin an inductive reasoning task (Rips, 1975).

Concept Maps

Concept mapping was used to examine the organization of the students’ knowledgeand to provide evidence of conceptual change (Markham, Mintzes, & Jones, 1994; Novak& Gowin, 1984). In this process examples, relationships, hierarchies, and crosslinks wereidentified using the following criteria. Examples were identified as specific events or objectson concept maps that were judged as valid instances of a concept. Relationships were definedas the connecting lines and linking words between two concepts, between a concept andan example, or between two examples. Hierarchies were connections among concepts andexamples, from general to specific. Crosslinks were connections between a segment ofone hierarchy and a segment of another hierarchy. The concept maps were coded andscored, using procedures described by Novak and Gowin (1984) and Markham, Mintzes,and Jones (1994). Map scores of the two groups of high-achieving students were thencompared.


Interview and Observation Analyses

Although the multidimensional scalings and the concept maps provided “snapshots”of changes in students’ schema organization related to convection, the transcripts of thepre- and postinstruction interviews and instructional sessions provided us with the richcontexts in which these changes took place. The transcripts were analyzed for each studentand for the dyad type (high–high or high– low) within and across each time period, aswell as across different interview questions. The transcripts and drawings were examinedfor evidence of the organization and applications of students’ knowledge of convectionand were also used to assist with and document interpretation of the results of the otherassessments. To quantify students’ ability to apply their knowledge of convection, a rubricwas constructed to assess students’ conceptual understanding of convection as indicatedduring the postinstruction interview. This rubric is described in detail in the results section.

RESULTS AND DISCUSSION

Convection Test

Convection pretest scores for the total sample ranged from a raw scores of 2–16 with anoverall mean of 8.90 (N = 130, SD = 3.1). The posttest scores ranged from 4 to 19 itemscorrect with an overall mean of 11.72 (N = 128, SD = 3.79). In order to examine posi-tive effects of pairing on gain scores, an analysis of covariance was performed which onlyinvolved high-achieving students (N = 43). The covariate, pretest scores had a significanteffect on posttest scores but the partner’s level did not (Table 1). That is, there was no signif-icant difference in posttest scores of high-achieving students regardless of the achievementlevel of the high-achieving student’s partner. These results parallel the results of a previousstudy (Carter & Jones, 1994) with levers that found no achievement gain score differencesfor high-achieving students who were partnered with other high-achieving students, or thosewho were partnered with low-achieving students.

Multidimensional Scaling

Both the H-h group and the H-l group altered their card sorts after instruction, indicating achange in their conceptual organization. The visual representation that results from multidi-mensional scaling is generally a geometric configuration of points, as on a map (Kruskal &Wish, 1991). These points can be interpreted as cognitive “distances” among concepts. Forexample, the more frequently two concepts are associated in a sorting task, the shorter thedistance between them in the scaling. Therefore, distance may be thought of as a measureof the strength of association a person forms between concepts. On the preinstruction cardsorts, high-achieving students from both the H-h (Figure 2) and the H-l (Figure 3) groupstended to group “hot,” “cold,” “heat,” and “temperature” together. They also grouped “wind”with “air,” “up” with “down,” and “water,” “liquid,” and “fluid” together. The initial group-ing on the preinstruction card sorting task provided a view of the “everyday” knowledge

TABLE 1ANCOVA on Posttest Scores with Pretest Scores as a Covariate

Source df MS F p

Partner’s level 1 4.21 0.81 0.37Pretest 1 145.18 28.01 .0001∗

∗p < 0.05.

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that students brought with them to the formalized tasks on convection. As expected, theterm “convection” was isolated from the other terms since students had not been introducedto the concept in school.

A comparison of the multidimensional analysis of the postinstruction card sort showedthat the two groups of high-achieving students had changed their conceptual organizationin slightly different ways. The H-h students’ (Figure 2) multidimensional scalings showedthat the concept “heat” moved from a concept “cluster” including heat, temperature, hot,and cold, toward concepts such as “move,” “wind,” and “molecules.” In addition, the H-hdyad members’ multidimensional scaling also showed movement of convection from nogeneral concept cluster to a cluster that included the concepts move, up, and down. Thisshift in location on the multidimensional scalings suggests that these students now see arelationship of convection with movement.

The H-l (Figure 3) multidimensional scalings showed that the concept convection movedfrom an isolated concept to a new cluster with “currents.” These students’ scalings alsoshowed a movement of the concept heat from a cluster of hot, cold, energy, and temperature,toward the concepts “convection,” “ocean,” and “water.”

The way that the two groups of high-achieving students organized this new term inrelationship to the other terms after instruction suggests differences in cognitive organi-zation. For H-h students the term convection became linked with terms move, up, anddown, all terms used by students to describe the observations of food coloring in water.However, for H-l students the term convection became linked with currents and also hada degree of connectedness to the terms ocean and water. These terms are more closelyrelated to the application of convection concepts rather than simply descriptive of thephenomenon and may be indicative of a difference in cognitive structuring. The termheat became disembedded from original linkages with hot, cold, and temperature for bothgroups. This disembedding could be characteristic of the schemata bond breaking neces-sary for conceptual growth and indicative that new connections are in the process of beingmade.

Concept Mapping

A multivariate analysis of variance was used to test for effect of partner’s achievementlevel on gains shown on the five subscales of the postconcept map. The results of theanalysis were not significant at α = 0.05 (using Wilks’s Lambda, F = 0.21). Therefore theconcept mapping provided no evidence that high-achieving students were advantaged ordisadvantaged as a result of working with a low-achieving partner.

A comparison of pre- with postinstruction concept maps for high-achieving studentsshowed evidence of initial integration of “spontaneous” knowledge and formal knowl-edge. A sample (Figure 4) of a high student’s preinstruction map clearly indicates thatthe concept heat is defined by the real life experiences of this student as well as for-malized instruction. The postinstruction map shows how this student linked her priorideas about heat with the instructional experiences targeting convection (shown as shadedconcepts).

Preinstruction Interview

Responses from students during preinstruction interviews provided further evidence oflack of formalized knowledge of convection. Interviewing the students about the way inwhich they grouped the cards validated for the researchers that students had a definiterationale for the grouping and that the card sorts were a reflection of their understanding


Figure 4. Pre- and postinstruction concept map of a high-achieving student.

of the relationships of the terms. The interview further substantiated the idea that studentshad not been introduced to convection and that the way in which they grouped the termswas built primarily upon prior informal experiences. For example, a high-achieving studentplaced liquids, solids, and fluids together because of his association of the terms with goingto the doctor. He explained that he needed liquids and fluids when he was sick. He gavecough drops as an example of a solid needed for medicinal purposes.

During the preassessment interview students were shown a picture of an ocean and abeach and asked to predict air movements. No student drew a “convection current” orindicated an awareness of this phenomenon.

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Postinstruction Interview

During the postinstruction interview researchers once again were able to ascertain thatstudents had grouped cards according to a particular rationale based on their understandingof the terms. Most of the target students interviewed now recognized the term convectionand were able to identify the term with the activities that had taken place in class. The cardsort assessment showed that students became more focused on the terms as they related tothe activities in which they had been engaged. The following is an excerpt from a high-achieving student’s post-interview. This excerpt shows that as a result of the instructionalactivities this student realized that all of the words from the card sort were related:

I put all the cards in one pile . . . First I had them in different groups like hot and all thestuff that had to do with hot. And then I decided they could all go together and that the hotstuff could go with the cold stuff because temperature has to do with both of them. I hadconvection and current and air and wind and move and gas and I just started figuring outhow they could all go together. And ocean, it can be hot or cold and has water in it andcurrents in it and there can be currents in the air . . .

Most of the students were able to verbalize an understanding of convection currents duringthe postinstruction interview. However, during the process of applying their knowledge to thedrawings of air movements in the two pictures, many students’ explanations indicated an in-complete understanding of convection. To further analyze the drawings and the informationgarnered during the interview, a rubric was prepared to score the level of students’ knowledgeabout convection currents. Table 2 illustrates this hierarchical rubric. That is, for studentsto construct an understanding of convection currents at the most basic level, they wouldneed to make accurate observations in the context of class activities and be able to relatethese observations to the term convection current. Next on the continuum of understanding,students needed to discuss the drawings in the context of the convection classroom activities(noting circular movement of hot and cold air). Finally, students that could apply their under-standing of convection currents to a new situation were considered to be conceptually moreadvanced than students who could not. Therefore, a total of zero points would indicate thatthere was no evidence of understanding even at the most basic level. A maximum score of 6would indicate that the student was able to relate the laboratory activities to convection cur-rents, articulate observations of convection currents, and appropriately apply understanding

TABLE 2Rubric Used to Score Level of Understanding About Convection

Relating classroom activities to convection currents0: No connection made between convection and activities1: States that convection was the topic in class activities but unable to recall any

specific observations2: Describes convection currents as observed during class activities

Verbalizing understanding of convection currents0: Not able to verbally give an accurate description of convection current1: Gives a partial description of convection current2: Able to accurately describe a convection current

Application of understanding of convection currents0: Not able to apply understanding of convection current1: Partial application, i.e., can apply for one picture only2: Correctly draws arrows indicating convection currents


of convection currents on drawings specifically designed for this purpose. The mean rubricscore for high-achieving students grouped with other high-achieving students was 3.08(SD = 2.02) and for high-achieving students grouped with students of low-achieving was3.20 (SD = 1.55). A t-test indicated that there was no significant difference (p < 0.05) inrubric scores for high-achieving students regardless of the partner’s ability level.

CONCLUSIONS

This study suggested no significant achievement differences for high-achieving studentsregardless of the achievement level of the dyad partner as measured by the 20-item instru-ment described in this paper. This strengthens the assertion that in terms of achievement asmeasured by a traditional test it is not detrimental for a high-achieving student to work witha low-achieving partner. The original hypothesis of the study, that is, high-achieving stu-dents construct knowledge differently as a result of working with low-achieving studentswas not supported by the data. Neither the concept maps nor the rubric scores from theinterviews showed a significant difference in the conceptual construction or the ability toapply knowledge about convection as a result of the achievement level of the dyad partner.Although the multidimensional scalings were somewhat different from each other for pre-and postinstruction, it isn’t clear how much of the differences are artifacts of the individualconceptual organizations within the dyad group. A study using a greater number of subjectswould be needed to determine if instruction significantly alters the conceptual organizationas shown by the multidimensional scaling.

Within a few H-h dyads, we noted behaviors that were more characteristic of H-l dyads.This suggests that while the role of a high-achieving student in a dyad may not affect theachievement of that high-achieving person, the role of the high-achieving student within thedyad might influence the high-achieving student’s cognitive structuring. Bargh and Schul(1980) suggest that richer constructions occur as a result of the cognitive restructuring thattakes place as a result of giving explanations. It would be expected that the functioning roleof the high-achieving student, and not necessarily the partner’s achievement level, might im-pact cognitive growth. From a Vygotskian perspective (Vygotsky, 1986) one might predictthat the assumption of a mediating role may take precedence over achievement-level in pre-dicting the effect on cognitive structuring. That is, within an H-h dyad, the high-achievingstudent who serves as the more capable peer is as likely to exhibit a cognitive advantage at theconceptual level as the one who serves as a more capable peer in an H-l dyad. Conversely, if ahigh-achieving student for some reason does not function as a more capable peer within theH-l dyad, then any conceptual advantage to that high-achieving student is lost. Since Vygot-sky emphasized that language is the most important mediator of learning, our original inter-pretation of a more capable peer was one who has advanced language skills as measured bythe CAT-R scores. Alternatively, the notion of a more capable peer could be considered as onewho can effectively use laboratory materials to construct understanding, can work collabo-ratively with other people, or has prior experiences with which to make sense of new ideas(Carter, Westbrook, & Thompkins, 1999). In light of work reported by Alexopoulou andDriver (1996) the possibility of multiple interpretations of “more capable peer” may explaintheir findings that working in a group of four seems to be more effective than dyad grouping.Increasing the number of group members would increase the likelihood that a more capablepeer would be present in a majority of the mediating contexts. Therefore when looking atcognitive restructuring perhaps it may be more important to compare the organizational dif-ferences of high-achieving students that serve as a more capable peer with those who do not.

The use of multiple assessments provided opportunities to trace the impact of a part-ner’s ability to cognitive outcomes on the postinstruction assessments. There were multiple

108 CARTER ET AL.

samples from the transcripts of the impact of these interactions and the examples describedin the section that follows are typical of the ones we noted.

In the following excerpt, Mike who was working in H-h dyad, searched among his existingschema looking for one that might be related to their observations. At the conclusion of thefirst lab session Mike identified evaporation as convection.

Hot water is starting to evaporate. Write that on the other sheet . . . Hot water was trying toevaporate and pressure pushes the food coloring up . . . In the vial the warmest water alwaysmoves up the evaporation moves up . . . Hot water is trying to evaporate and pushed the foodcoloring up.

On the last day of instruction his partner, Inez, has accepted Mike’s idea that evaporationis responsible for the phenomena they are observing even though Mike now rejects thatidea. “That’s what I thought it was but it couldn’t be evaporation.” Nevertheless, Inez hasadopted Mike’s idea as illustrated by this excerpt from her postinstruction interview.

Interviewer: You’re not sure, OK. Let’s take a look at a couple of pictures. Let’s start withwind and water. Do you think there might be any air currents or air movement in this picture?

Inez: Yes.

Interviewer: Yes, Can you draw with arrows how the air might move?

Inez: It would probably rise up like evaporation because the ocean is right there.

Interviewer: Show me how it could move over with arrows. You show it coming up fromthe ocean.

Inez: It would probably would rise up and go out in directions like the food coloring.

Interviewer: What happened with the food coloring?

Inez: It was trying to evaporate and the heat pressure made it spread up and it came backdown.

A similar example is illustrated by the dialogue of an H-l dyad. Note that Helen (H) offersLydia (l) the idea of molecules while they are answering questions about the lab they havejust completed.

[Convection current] is like when heat cools, like hot and cold matter, moves, movesmolecules of air, water and takes something with it in whatever direction it goes . . . cold orhot matter speeds up or slows down the molecules . . . I think that’s really molecules.

Lydia (l) illustrates that she has accepted Helen’s idea that molecules are responsible forwhat is occurring and although clearly has no concept of molecules, offers molecules as anexplanation during her postinstruction interview.

Interviewer: Why have you placed the cards with the terms convection, currents andmolecules together in a stack?

Lydia: I thought back to when we did the activities and then we had to write about convectioncurrents and these were these two cards and then molecules and I think that molecules havesomething to do with convection currents so I put them in the stack.

Interviewer: OK. Do you have any idea what molecules have to do with convection currents?

Lydia: Not really.


LIMITATIONS

These results should be interpreted carefully within the limits of this study. There aremany variables that can impact cognitive outcomes, and achievement grouping compositionis just one variable. Learning in small groups is influenced by a variety of variables includingthe complexity of the task (Hooper & Hannafin, 1988) interactions of personality (e.g., Joneset al., 2000; Windschtl, 2001), gender composition of the group (Webb, 1991), and perceivedexpertise (Carter, Westbrook, & Thompkins, 1999). Any or all of these variables may, incertain contexts, dilute the influence of pairing effects for high-achieving students. Thestudy needs to be repeated with a larger sample size before results can be substantiated.

Additionally, the types of measures used in this study may not be sufficient to measure thecomplex facets of intellectual growth. There may have been learning differences for studentsdepending on the ability of the partner, but our assessments may not have been sufficientor sensitive enough to detect such differences. It is also possible that if dyads had workedtogether for an extended period of time, then differences in achievement may have emerged.

RECOMMENDATIONS FOR FUTURE RESEARCH

One interpretation of these results is that achievement as measured by a specific tradi-tional, multiple-choice test and cognitive restructuring may be two very different phenom-ena. The interactions of variables that will affect the outcome of restructuring that takes placeas a result of working with a partner may be different from those same factors examined interms of achievement. Conditions necessary for cognitive restructuring may implicate fac-tors that are not critical to achievement. Although achievement may not be influenced, wemight assume that high-achieving students who do a majority of the explaining, regardlessof dyad type, would be more likely to exhibit cognitive structuring differences. The condi-tions under which this is likely to take place as well as identifying specific roles adoptedby high-achieving students should be the focus of future research in this area. Additionally,there may be other important mediators that need to be examined within the group dynamicenvironment. Future research can provide an insight into other factors such as the impactof gender, socioeconomic levels, or the structure of the learning task.

We thank William Boone, Indiana University; Tom Andre, Iowa State University; and Eric Wiebe,North Carolina State University, for their advice on the statistical analyses.

REFERENCES

Alexopoulou, E., & Driver, R. (1996). Small-group discussion in physics: Peer interaction modes inpairs and fours. Journal of Research in Science Teaching, 33(10), 1099–1114.

Allan, S. (1991). Ability-grouping research reviews: What do they say about grouping and the gifted?Educational Leadership, 48(6), 60–65.

Bargh, J., & Schul, Y. (1980). On the cognitive benefits of teaching. Journal of Educational Psychology,72, 593–604.

Carter, G. (1990). The effect of external verbalization by fifth graders in the development of leverconcepts. Unpublished doctoral dissertation, North Carolina State University, Raleigh.

Carter, G., & Jones, M. G. (1994). The effects of ability-paired interactions by fifth graders on balanceconcept attainment. Journal of Research in Science Teaching, 31(8), 847–856.

Carter, G., Westbrook, S., & Thompkins, C. (1999). Examining tools as mediators of students’ learningabout circuits. Journal of Research in Science Teaching, 36(1), 89–105.

Cary, S. (1986). Cognitive science and science education. American Psychologist, 41(10), 1123–1130.

110 CARTER ET AL.

Chi, M., Bassok, M., Lewis, M., Reimann, P., & Glaser, R. (1989). Self explanations: How studentsstudy and use examples in learning to solve problems. Cognitive Science, 13, 145–182.

Ellett, P. (1993). Cooperative learning and gifted education. Roeper Review, 16(2), 114–121.Feldhusen, J., & Moon, S. (1992). Grouping gifted students: Issues and concerns. Gifted Child

Quarterly, 36, 63–67.Fiedler-Brand, E., Lange, R. E., & Winebrenner, S. (1992). Tracking, ability grouping and the Gifted.

PAGE Bulletin, 1–7.Fuchs, L., Fuchs, D., Hamlett, C. L., & Karns, K. (1998). High-achieving students’ interactions and

performance on complex mathematical tasks as a function of homogeneous and heterogeneouspairings. American Educational Research Journal, 35(2), 227–267.

Gallagher, J., Coleman, M., & Nelson, S. (1993). Cooperative learning as perceived by educators ofgifted students and proponents of cooperative education. Gifted Education Policy Studies Program.Chapel Hill, NC: University of North Carolina at Chapel Hill.

Gould, A. (1988). Convection a current event. Great explorations in math and science. Berkeley, CA:Lawrence Hall of Science, University of California at Berkeley.

Hooper, S., & Hannafin, M. J. (1988). Cooperative CBI: The effects of heterogeneous versus ho-mogeneous grouping on the learning of progressively complex concepts. Journal of EducationalComputing Research, 4(4), 413–424.

Howe, C., Tolmie, A., Greer, K., & Mackenzie, M. (1995). Peer collaboration and conceptual growthin physics: Task influences on children’s understanding of heating and cooling. Cognition andInstruction, 13(4), 483–503.

Hutchinson, J., & Lockheed, G. (1977). Similarity as distance: A structural principle for semanticmemory. Journal of Experimental Psychology: Human Learning and Memory, 3, 660–678.

Jones, M. G., Brader-Araje, L., Carboni, L., Carter, G., Rua, M., Banilower, E., & Hatch, H. (2000).Tool time: Gender and students’ use of tools, control, and authority. Journal of Research in ScienceTeaching, 37(8), 760–783.

Jones, M. G., & Carter, G. (1994). Relationship between achieving-paired interactions and the de-velopment of fifth-graders’ concepts of balance. Journal of Research in Science Teaching, 31(6),603–620.

Jones, M. G., & Vesilind, E. (1996). Putting practice into theory: Changes in the organization ofpreservice teachers’ pedagogical knowledge. American Educational Research Journal, 33(1), 91–117.

Kempa, R. F., & Ayob, A. (1991). Learning interactions in group work in science. International Journalof Science Education, 13(3), 341–354.

Kruskal, J., & Wish, M. (1991). Multidimensional scaling. Beverly Hills, CA: Sage University Press.Kulik, J. (1991). Findings on grouping are often distorted: Response to Allan. Educational Leadership,

48(6), 67.Lou, Y., Abrami, P., Spence, J., Poulsen, C., Chmabers, B., & d’Apollonia, S. (1996). Within-class

ability grouping: A meta-analysis. Review of Educational Research, 66(4), 423–458.Maher, C. (1996, May ). The development of the idea of mathematical proof: A five year study. Paper

presented at the Tenth Annual Research Institute, North Carolina State University, Raleigh.Markham, K., Mintzes, J., & Jones, M. G. (1994). The concept map as a research and evaluation tool:

Further evidence of validity. Journal of Research in Science Teaching, 31(1), 91–101.Mathews, M. (1992). Gifted students talk about cooperative learning. Educational Leadership, 50(2),

48–50.National Research Council (1996). National science education standards. Washington, DC: National

Academy Press.Novak, J., & Gowin, D. (1984). Learning how to learn. Cambridge: Cambridge University Press.Pressley, M. (1995). Advanced educational psychology for educators, researchers, and policy makers.

New York: Harper Collins.Rips, L. (1975). Inductive judgments about natural categories. Journal of Verbal Learning and Verbal

Behavior, 14, 665–681.Rips, L., Shoben, E., & Smith, E. (1973). Semantic distance and the verification of semantic relations.

Journal of Verbal Learning and Verbal Behavior, 12, 1–20.


Robinson, A. (1990). Cooperation or exploitation? The argument against cooperative learning fortalented students. Journal for the Education of the Gifted, 14(1), 9–27.

Rogers, K. (1993). Grouping and gifted and talented: Questions and answers. Roeper Review, 16(1),8–12.

Shoben, E. J. (1976). A verification of semantic relations in same/different paradigm: An asymmetryin semantic memory. Journal of Verbal Learning and Verbal Behavior, 15, 365–379.

Slavin, R. (1986). Ability grouping and student achievement in elementary schools: A best-evidencesynthesis. (Report No. 1). Baltimore, MD: Center for Research on Elementary and Middle-Schools,Johns Hopkins University.

Slavin, R. (1990). Achievement effects of ability grouping in secondary schools: A best-evidencesynthesis. Review of Educational Research, 60(3), 471–499.

Slavin, R. (1991). Are cooperative learning and “untracking” harmful to the gifted? A response toAllan. Educational Leadership, 48(6), 68–71.

Swing, S., & Peterson, P. (1982). The relationship of student achieving and small group interactionto student achievement. American Educational Research Journal, 19(2), 259–274.

Tudge, J. (1990). Vygotsky, zone of proximal development, and peer collaboration: Implications forclassroom practice. In L. Moll (Ed.), Vygotsky and education (pp. 155–174). New York: CambridgeUniversity Press.

Vygotsky, L. (1986). Thought and language. Cambridge, MA: MIT Press.Webb, N. (1982). Peer interaction and learning in cooperative small groups. Journal of Educational

Psychology, 74(5), 642–655.Webb, N. (1991). Task-related verbal interaction and mathematics learning in small groups. Journal

for Research in Mathematics Education, 22(5), 366–389.Webb, N. (1995). Group collaboration in assessment. Educational Evaluation and Policy Analysis,

17, 239–261.Webb, N., Nemer, K., Chizhik, A., & Sugrue, B. (1998). Equity issues in collaborative group as-

sessment: Group composition and performance. American Educational Research Journal, 35(4),607–651.

Windschtl, M. (2001). Using simulations in the middle-school: Does assertiveness of dyad partnersinfluence conceptual change? International Journal of Science Education, 23, 17–32.

Young, F., & Rheingans, P. (1991). Visualizing structure in high dimensional multivariate data. IBMJournal of Research and Development, 35, 97–107.

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