This study examined relationships between students' self-beliefs (self-construal and self-efficacy), observed behaviors, and performance in friendship and acquaintance groups working on a problem-solving task. Data was collected through self-reports and observations of 126 students in 42 groups from 5 high schools. The study found that higher self-efficacy for working with acquaintances related to more on-task behaviors like developing and critically reviewing ideas. This provides insights into relatively unexplored phenomena of group work with friends and acquaintances.

1. Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=vjer20
Download by: [University of California, San Diego] Date: 31 October 2016, At: 01:28
The Journal of Educational Research
ISSN: 0022-0671 (Print) 1940-0675 (Online) Journal homepage: http://www.tandfonline.com/loi/vjer20
A multilevel study of self-beliefs and student
behaviors in a group problem-solving task
José Hanham & John McCormick
To cite this article: José Hanham & John McCormick (2016): A multilevel study of self-beliefs
and student behaviors in a group problem-solving task, The Journal of Educational Research,
DOI: 10.1080/00220671.2016.1241736
To link to this article: http://dx.doi.org/10.1080/00220671.2016.1241736
Published online: 27 Oct 2016.
Submit your article to this journal
Article views: 7
View related articles
View Crossmark data

2. A multilevel study of self-beliefs and student behaviors in a group
problem-solving task
Jos
e Hanhama
and John McCormickb
a
School of Education, Western Sydney University, Penrith, Australia; b
School of Education, University of Wollongong, Wollongong, Australia
ARTICLE HISTORY
Received 8 February 2016
Revised 20 July 2016
Accepted 3 September 2016
ABSTRACT
Relationships among self-construal, self-efficacy, and group behaviors during a group problem-solving task
with friends and acquaintances were hypothesized. The sample comprised 126 students in Grades 8–11,
from 5 randomly selected government high schools, organized into 42 groups. Data collection involved
self-reports and observations. Self-report data measured self-construal, self-efficacy for working with
friends, and self-efficacy for working with acquaintances, and the observational data captured salient
student behaviors. Data were analyzed using exploratory factor analysis and multilevel modeling. Self-
efficacy for working with acquaintances was related to the development of ideas and also the critical
review of ideas in groups. This study provides insights into the relatively underexplored phenomena of
group work with friends and acquaintances.
KEYWORDS
Friendship; group work;
multilevel; self-efficacy
Problem solving is a central part of the learning experience of
students in schools. Students can work on problem-solving
tasks individually or in groups. Although there has been a long-
standing interest in individual problem solving (Atkinson,
Derry, Renkl, Wortham, 2000; Ayres Paas, 2009; Sweller,
1999), there is increasing attention on problem solving in group
contexts (Kirschner, Paas, Kirschner, 2009; Sears Reagin,
2013). This arguably is due in part to the recognition that group
problem-solving skills are critical for success in postsecondary
education and the workforce (Organization for Economic
Cooperation and Development, 2015).
Teachers typically use some form of group work to nurture
students’ group problem solving and interpersonal skills
(Gillies, 2007; Webb Palincsar, 1996). Group work can be
defined as students working together on a common problem-
solving task set by the teacher (Galton Williamson, 1992).
Research-informed teachers have, as part of their instructional
repertoires, a range of approaches for organizing group work in
the classroom, including peer tutoring (Robinson, Schofield,
Steers-Wentzell, 2005), collaborative learning (DiDonato, 2013;
J€
arvel€
a, Volet, J€
arvenoja, 2010), and cooperative learning
(Gillies, 2004).
Despite the proliferation of various methods of structuring
group work in the classroom, there are still many aspects of
group work in schools that are not well understood. One such
aspect concerns how students’ pre-existing self-beliefs may
impact group work processes in the classroom. Self-beliefs are
often predictive of indexes of motivation including effort, choice,
and persistence (Pintrich Schunk, 2002). It has been suggested
that in group work settings students bring with them motiva-
tional beliefs that play a role in how they engage with peers.
Because learners possess an immense range of different types of
self-beliefs, a challenge for researchers is to identify particular
types of self-beliefs that are most likely to have an impact on
how students interact with peers in group learning contexts.
An emerging line of research (Hanham McCormick, 2008,
2009, 2010) on group work in secondary schools has focused on
the role of self-beliefs when students work in friendship and
acquaintance groups. Friendship groups comprise peers who
consider each other close friends and acquaintance groups
comprise peers who may know each other, but who do not con-
sider each other close friends. In a series of studies by Hanham
McCormick (2008, 2009), two sets of self-beliefs, indepen-
dent and interdependent self-construal and self-efficacy for
group work, were predictive of students’ attitudes toward coop-
erating with friends and acquaintances. Independent and inter-
dependent self-construal refer to self-schemas that reflect the
extent to which individuals perceive themselves connected
with, or separate from, others (Markus Kitayama, 2010).
Self-efficacy for group work refers to individuals’ beliefs about
their capabilities to successfully engage in group processes such
as building on others’ ideas and coordinating the activities of
the group (Hanham McCormick, 2009).
Although Hanham and McCormick (2008, 2009) found self-
construal and self-efficacy for group work correlated with stu-
dents’ attitudes toward cooperation, they argued the need for
future researchers to examine relationships between self-beliefs
and actual student behaviors or performance. In the present
study we focused on investigating relationships among self-
beliefs (self-construal, self-efficacy), observed behaviors, and
performance scores of friendship and acquaintance groups on a
problem-solving task. It appears that no other published
research has investigated relationships among self-construal,
self-efficacy, observed behaviors, and group performances.
In addition to examining the role of self-beliefs, we also
investigated relationships between group level characteristics
CONTACT Jos
e Hanham j.hanham@westernsydney.edu.au School of Education, Western Sydney University, Locked Bag 1797, Penrith, NSW 2797, Australia.
© 2016 Taylor Francis
THE JOURNAL OF EDUCATIONAL RESEARCH
http://dx.doi.org/10.1080/00220671.2016.1241736

3. (group means of i.e., interdependent self) and individual behav-
iors. Examining individual and group level data arguably is
important for unpacking the complexities of group-based activ-
ities (Arvaja, Salovaara, H€
akkinen, J€
arvel€
a, 2007). This study
provides an important contribution to current literature on
group work in schools, as it appears to be one of the first to
take into account the multilevel structure of group activities
with friends and acquaintances.
Friendship and acquaintance groups
Teachers typically grapple with a number of issues when
employing group work as an instructional strategy. One com-
mon issue is whether it is more advantageous to assign students
to friendship groups than to acquaintance groups, and vice
versa (Mitchell, Reilly, Bramwell, Solonsky, Lilly, 2004).
Unfortunately, very few empirical studies have focused on
school-based group work with friends and acquaintances. Con-
sequently, teachers have had to rely on anecdotal experiences
when deciding group composition.
The literature on friendship relations suggests that friends
have greater levels of shared knowledge (Miell MacDonald,
2000), cooperation (Hartup, 1998), positive affect (Newcomb
Bagwell, 1995), and prosocial exchanges (Barry Wentzel,
2006) than nonfriends. This has led some scholars to theorize
that friends are likely to be better colearners than nonfriends
(Newcomb Bagwell, 1995; Hartup, 1996). Despite theoretical
arguments in favor of organizing students into friendship
groups, it appears some teachers are reluctant to do so. A criti-
cal issue centers on the perception that friends are more likely
to exhibit off-task behaviors when working together (Zajac
Hartup, 1997).
On-task and off-task behaviors
In educational research, categorization of on-task and off-task
behaviors has varied and is considered to be context dependent
(Gill Remedios, 2013). Broadly, on-task behaviors are consis-
tent with curricular goals and off-task behaviors deviate from
curricular goals (Hofer, 2007). On-task behaviors have been
linked to positive student outcomes such as academic achieve-
ment (Kiuru et al., 2014) and off-task behaviors have been asso-
ciated with negative student outcomes such as loss of
instructional time (Lee, Kelly, Nyre, 1999).
Independent and interdependent self
Current conceptualizations of self-construal suggest that
human beings generally define self as separate, distinct from
others (independent self), or interconnected with others (inter-
dependent self; Markus Kitayama, 2010). Evidence from neu-
roscience research suggests that these schemas may have a
neurobiological basis (Wang, Oyserman, Liu, Lee, Han,
2013) and cognitive-based studies suggest that independent
and interdependent selves likely represent stable differences in
how self relates to groups (T€
auber Sassenberg, 2012). When
guided by an independent self-schema, people generally per-
ceive themselves as autonomous entities, unique and distinct
from others; priority tends to be given to individual interests,
needs, and goals (Hannover, Birkner, P€
ohlmann, 2006). This
has implications for the types of behaviors we expect individu-
als with independent mindframes to exhibit in groups. When
working in groups, situations in which the goals of the group
do not align with an individual’s goals can arise. In such cir-
cumstances, we may expect group members with independent
mindframes to disengage from the group and exhibit off-task
activities. This contrasts with when the interdependent mind-
frame is salient. In the latter case, typically the needs of others
and group goals are prioritized; those with interdependent
mindframes typically will adjust their individual goals so they
are aligned with goals of the group (Hannover, et al., 2006;
Markus Kitayama, 2010). Thus, we would expect individuals
with an interdependent mindframe to emphasize being on task
when working in groups.
Self-efficacy for group work
Social cognitive theory (Bandura, 1997) proposes successful
accomplishment of tasks requires not only requisite resources
(e.g., knowledge and skills), but also a belief that one can effec-
tively utilize these resources to achieve specific goals. Self-effi-
cacy encapsulates this belief, and has been found to be a key
predictor of learner performance across multiple academic
domains (Bandura, 1997; Pajares, 1996). In general, learners
tend to seek out tasks for which they perceive themselves self-
efficacious, expend considerable effort on the tasks, and persist
with the tasks even when faced with obstacles (Bandura, 2012).
For example, students who have relatively high self-efficacy for
group work may be expected generally to seek out group work
activities, and actively engage in group work processes; they
may be expected to learn optimally when working in groups.
On the other hand, learners generally tend to avoid tasks for
which they do not perceive themselves self-efficacious, and
when required to do such tasks, generally expend minimal
effort and give up when confronted with obstacles (Bandura,
2012). Consequently, it is unlikely they would learn optimally
when working in groups.
Self-efficacy beliefs are domain-specific and likely to be
important for two distinct domains of group work: content
(task work) and process (group work; Johnson, Johnson,
Holubec, 1994). The former relates to content knowledge about
a topic that students’ possess and utilize when contributing to
collective efforts with peers. Self-efficacy for group work refers
to individuals’ beliefs about their capabilities to successfully
engage in group processes such as building and sharing ideas,
resolving conflict, and coordinating the activities of the group.
Theoretical framework, hypotheses, and research
questions
Our theoretical framework is focused on three sets of phenom-
ena: self beliefs (self-efficacy and self construal), individual
group member behaviors (on task and off task), and group
behavior characteristics (means of interdependent self and
problem-solving ability [PSA]). Drawing on previous group-
based studies (e.g., Gillies, 2004), we use task-related talk and
non–task-related talk as indicators of on-task and off-task
behavior, respectively (Gill Remedios, 2013).
2 J. HANHAM AND J. MCCORMICK

4. Past research has demonstrated that school students dif-
fer in the extent to which they perceive themselves indepen-
dent from, or interdependent with, classmates (Hanham
McCormick, 2008, 2009). Consistent with current under-
standing of independent self (Hannover et al., 2006; Oyser-
man, Coon, Kemmelmeier, 2002), we expected school
students with an independent mindframe to prioritize indi-
vidual goals over group goals. Thus, when working on a
group problem-solving task, we expected group members
with independent self-construal to be more likely to engage
in off-task behaviors than on-task behaviors. In accordance
with current knowledge about interdependent self-construal
(Markus Kitayama, 2010), we expected school students
with an interdependent mindframe to align individual goals
with the goals of the group. Consequently, we expected
group members with interdependent self-construal to be
more likely to display on-task behaviors than off-task
behaviors. Hence, the following hypotheses were posited:
Hypothesis 1: The more independent the self-construal is the fewer
on-task behaviors and the more off-task behaviors there will be.
Hypothesis 2: The more interdependent the self-construal is the more
on-task behaviors and the fewer off-task behaviors there will be.
The role played by self-efficacy beliefs in the theoretical
framework is consistent with social cognitive theory generally
(Bandura, 1997), and past group problem-solving research
(Hanham McCormick, 2009; Tasa, Taggar, Seijts, 2007).
First, given that the higher a person’s self-efficacy for a task is,
the more likely she or he will engage in that task (Bandura,
1997; Pajares, 1996), we proposed that the greater the self-effi-
cacy (working with friends and working with acquaintances) is,
the more students may be expected to exhibit on task behaviors,
and fewer off task behaviors. Hence we posit the following
hypotheses.
Hypothesis 3. The higher the self-efficacy for group work with
friends is the more on-task behaviors and the fewer off-task behav-
iors there will be.
Hypothesis 4. The higher the self-efficacy for group work with
acquaintances is the more on-task behaviors and the fewer off-task
behaviors there will be.
We indicated earlier that several scholars have advanced vari-
ous theoretical arguments to suggest that school students are
more likely to work effectively with friends than with acquain-
tances. However, when examining the limited number of empiri-
cal studies in which the performances of the two composition
types have been compared, the results have been mixed. Some
studies (e.g., Azmitia Montgomery, 1993) found that friend-
ship groups outperformed acquaintance groups, whilst, other
studies (e.g., Berndt, Perry, Miller, 1988) found no significant
performance differences between the two categories of groups.
Thus, in light of the mixed results, we did not consider there to
be strong a priori justification for stating a directional hypothesis.
Rather we posited the research question: Are there performance
differences between friendship and acquaintances groups?
Method
Sample
As often is the case when it does not involve a pre-existing data
set, sampling was constrained by budget and other practical
considerations (Snijders Bosker, 1999). Nevertheless, the rec-
ommendation that the number of groups should exceed 30,
was met, and considered adequate, given that only fixed param-
eters were to be estimated (Stegmueller, 2013). The sample
comprised 126 students (52.4% boys) from Grade 8 (n D 15),
Grade 9 (n D 15), Grade 10 (n D 42), and Grade 11 (n D 54)
science classes, in five randomly selected government high
schools in Sydney, Australia. Grade membership is controlled
for in the analyses. Students from Science classes were targeted
due to expert advice and previous literature (e.g., Galton
Hargreaves, 2009) which suggested that group work was likely
more prevalent in science classes than in most other school
subjects. Consequently, we reasonably could expect our partici-
pants to have had prior experience of working in groups. We
considered this important for assessing self-efficacy for group
work as experience in an activity is likely a source of meaning-
ful self-efficacy. The participants ranged from 13 to 17 years
old (M D 15.27 years, SD D 1.13 years).
Instruments
Prior to being allocated to groups, participants were asked to
complete a questionnaire entitled: “Group Work in Secondary
Schools.” Nine items adapted from previous research (Singelis,
1994) were used to measure self-construal. Responses were
scored on a 7-point Likert-type scale ranging from 1 (not true
of me) to 7 (true of me). The stem presented to the participants
stated the following: “Please respond to the statements below in
terms of how you think about yourself and your classmates at
school. Please circle the most appropriate response.”
Eight items were used to measure self-efficacy for group
work. These items were developed in previous studies (Han-
ham McCormick, 2008, 2009). In fact, the original items
were adapted from Eby and Dobbins (1997). Participants were
asked to rate how confident they were that they could success-
fully execute skills such as, “coordinate the activities of the
group.” The response options were presented on an 11-point
scale ranging from 0% (not all confident) to 100% (completely
confident). The 11-point scale was divided into 10% incre-
ments. Matching sets of the eight self-efficacy items were placed
in separate sections of the questionnaire, one prefaced with the
statement, “This section refers to working in groups with your
close-friends,” and the other with, “This section refers to work-
ing in groups with not-close friends.” Items for self-efficacy
friends, self-efficacy acquaintances, and self-construal are pre-
sented in Table 2.
Sociometric mapping
Sociometric procedures (Finegold Eilam, 1995; Henrich,
Kuperminc, Sack, Blatt, Leadbeater, 2000) were used to iden-
tify friendship and acquaintance groups within each participat-
ing class. To identify friendship groups, each student was asked
to nominate, in order, up to five students in her or his class
THE JOURNAL OF EDUCATIONAL RESEARCH 3

5. whom he or she regarded as close friends. Consistent with Hen-
rich et al.’s (2000) approach to sociometric mapping, recipro-
cated friendship nominations were used for the identification
and formation of friendship groups. That is, a participant who
is a reciprocated close friend with two others in a class was
placed into a friendship group. To identify acquaintance
groups, students were asked to nominate fellow students, in no
particular order, whom they did not regard as close friends.
Students who nominated each other as not-close friends were
placed into acquaintance groups. The researchers deliberately
chose not to require ranking to avoid possible priming of
antagonistic thoughts about fellow students. The data collected
from student nominations were provided to an educator who
had extensive experience with sociometric mapping, who iden-
tified 21 friendship and 21 acquaintance groups, each of three
students. Because it was important for the researchers to
remain blind to the nature of each group, the educator simply
provided the researchers with the names of the students for
each group. Prior to the commencement of the group problem-
solving task, Jos
e Hanham read out the names of three stu-
dents, who then were placed into a group and the group moved
to a room allocated specifically for the study.
To provide a measure of perceived prior ability, teachers of
each participating class rated each student’s general PSA. The
7-point Likert-type scale ranged from 1 (low PSA) to 7
(high PSA).
Group problem-solving task
An experienced science educator developed the group problem-
solving activity, the content of which was not directly related to
formal curriculum, but was considered by the expert to be suit-
able for students in any high school grade. Furthermore the
group problem task was designed as an open-ended, ill-struc-
tured problem in which learners may generate multiple solu-
tions (i.e., no single correct answer). The deliberate choice of
an open-ended problem solving task, was based on previous
recommendations (Cohen, 1994), which suggested that open-
ended tasks encourage group members to interact.
Procedure
Each group was located in a room with no other occupants
apart from one of the researchers. Each group received identical
verbal and written directions for carrying out the task. No prior
training was provided by the researchers. Directions began
with the following statement: “As members of the local council
you have been asked to come up with a strategy to reduce or
eliminate the impact of cigarette butts on the environment.”
Each group engaged in four subtasks: (a) brainstorm possible
strategies which could be used to reduce or eliminate the
impact of this pollutant on the environment; (b) choose the
best strategy from your brainstorm and describe the strategy;
(c) why do you think this is the best strategy?; and (d) how
would you educate the public about this strategy? The prob-
lem-solving task was pilot tested with 10th- and 11th-grade stu-
dents (n D 30) from a nongovernment school. Based on the
feedback from students a 20-min time limit was set for each
group to complete the task.
Scoring of problem-solving task
The written responses to the problem-solving task were scored
by an independent expert without knowledge of the composi-
tion of each group. Each question was marked out of 5, and
subsequently adjusted according to different weightings
decided by the expert. These weightings were based on hierar-
chical performance bands, which described what knowledge
and skills the groups demonstrated by their responses. This
replicated how performances of science students were assessed
within secondary schools and in external high stakes examina-
tions in New South Wales, Australia (Board of Studies
Teaching and Educational Standards NSW, 2016). Teachers
and students generally were familiar with this assessment
approach, as it was consistent with the standards-referenced
approach required by the Board of Studies, the State curriculum
authority. We scored the problem-solving task to compare the
performances of friendship and acquaintance groups.
Observations
All groups were videotaped. Drawing in part from the work of
Veerman and Veldhuis-Diermanse (2001) and Gillies (2004),
and viewing footage from a pilot study, Jos
e Hanham devel-
oped an initial schedule consisting of eleven behavior catego-
ries. As a second step, Jos
e Hanham reviewed the pilot study
footage again, this time in collaboration with John McCormick.
There was disagreement between Jos
e Hanham and John
McCormick concerning the extent to which nonverbal behav-
iors could be accurately and meaningfully interpreted. From
discussions between the authors, it was decided to exclude cod-
ing of nonverbal behaviors. Consequently, the final observation
schedule comprised eight categories of behavior. For the main
study, the first author and a trained observer, blind to the pur-
poses of the study, viewed and analyzed the video data. The
training of the second observer involved 2-hr direct instruction
about the behavior categories and definitions for each category.
Also, the second observer was given several practice sessions
using the pilot study footage. The unit of analysis was a com-
plete turn, which represents an opportunity taken by the stu-
dent to speak with fellow group members (Sharan Shachar,
1988). A tally mark was entered each time a student in the
observed group was deemed to have taken a turn and exhibited
one of the eight verbal behaviors (i.e., on-task and off-task
behaviors) listed in the observation schedule. On-task and off-
task behaviors were scored for each student. Each observation
period lasted 20 min. For intercoder reliability we calculated
two statistics, percentage agreement and Cohen’s kappa. These
two measures are widely reported in educational literature,
although a limitation of the former is that it does not correct
for chance agreement. However, we retained percentage agree-
ment for comparative purposes. There is no consensus regard-
ing criterion values for these measures, although values of .70
and above for percentage agreement are considered reliable
and values of .75 and above for Cohen’s kappa are considered
excellent (De Wever, Schellens, Valcke, Van Keer, 2006).
The set of behaviors with accompanying examples and reliabil-
ity scores is described in Table 1. An extract with an example of
the coded peer discussions is in Appendix A.
4 J. HANHAM AND J. MCCORMICK

6. Analyses and results
Exploratory factor analyses
Exploratory factor analysis (EFA) was employed, rather than
confirmatory factor analysis because of the sample size. Princi-
pal axis factoring with varimax rotation was separately applied
to the items of the self-construal, self-efficacy for group work
with friends, and self-efficacy for group work acquaintances
scales as per previous studies (Hanham McCormick, 2008,
2009). The criteria for extraction were eigenvalues greater than
one, scree plot, and most importantly, theoretical considera-
tions. Regression factor scores were generated for subsequent
analysis.
In the initial factor analysis of the self-construal items, the
following item, “I usually feel a strong sense of pride when a
classmate has an important accomplishment,” had high cross
loadings. This item was dropped from the final factor analysis
in which two self-construal factors were identified. The first
was labeled as interdependent self (33% variance explained,
Cronbach’s a D .76) and contained five items reflecting stu-
dents’ interdependence with classmates (e.g., “The well-being
of my classmates is very important to me”). The second factor
was labeled as independent self (24% variance explained, Cron-
bach’s a D .75) and contained three items related to students
perceiving themselves as unique and standing out from class-
mates (e.g., “I am a unique person separate from my class-
mates”). With respect to self-efficacy for group work with
friends, a single, eight-item factor was identified and labeled as
self-efficacy friends (65% variance explained, Cronbach’s
a D .92). For self-efficacy for group work with acquaintances, a
single, eight-item factor was identified and labeled as self-
efficacy acquaintances (69% variance explained, Cronbach’s
a D .93).
As a cross-check, the same items were submitted to an over-
all principal axis factor analysis with varimax rotation. The
solution is consistent with the earlier factor solutions and is
reported in Table 2.
With the goal of data reduction, EFA was also applied to the
set of observed behaviors. Two factors were identified and
labeled idea development and critical review. Idea development
(39% variance explained, a D 71) comprised five behavior cate-
gories: Idea generation, explanation, strategy direction, building
ideas, and accepting ideas. Critical review (17% variance
explained, Cronbach’s a D .67) included two behavior catego-
ries: questioning and disagreeing. Although the Cronbach’s
alpha is just below .70, we retained the factor as it was consid-
ered theoretically coherent and Cronbach’s alpha tends to be
sensitive to small numbers of items (Cortina, 1993). The off-
task behavior item emerged as a single-item factor.
The raw scale means, standard deviations, and correlations
of the individual level variables are reported in Table 3. It is
important to note that the correlations take no account of the
multilevel structure of the data. It is notable that the correlation
with the largest magnitude (r D .60) is between self-efficacy
friends and self-efficacy acquaintances. Perusal of the correla-
tions between the self-efficacy variables and individual behav-
iors indicates that that there are no statistically significant
correlations between self-efficacy friends and any of the
individual behaviors. However, self-efficacy acquaintances has
statistically significant relationships with the on-task group
Table 1. Behavior categories with descriptors, examples, total rater scores, and reliability scores.
Behavior category Descriptor Example Rater r1 Rater r2 Final reliability scores (n D 42)
New idea Group member offers new ideas,
suggestions, and opinions with
minimal supporting details
“We should provide bio-degradable
cigarette butts”
544 551 Interrater agreement D 96%;
Cohen’s k D .96
Explanation Group member provides reasons,
justifications and clarifications for her
or his propositions
“Bio-degradable cigarette butts can be
effective because they not only reduce
litter but there is no chance of
cigarette butts entering the storm
water system and therefore impacting
marine life”
284 283 Interrater agreement D 96%;
Cohen’s k D .95
Accepting ideas
Group member provides verbal
indicators that propositions offered
by group members have been
accepted
“Yes that’s a good idea, we should write it
down”
527 527 Interrater agreement D 94%;
Cohen’s k D .93
Building ideas Group member extends another group
member’s proposition to make it
more substantive
“Extending on your idea of butt collection
bins near drains, we can also have
mesh covering the drains so that the
butts are collected there”
241 238 Interrater agreement D 96%;
Cohen’s k D .95
Strategizing Group member makes explicit decisions
about with which ideas the group
should proceed, how to articulate
them, and which ideas should be
discarded
“I think we go with this idea over all of the
others, though we should make sure it
is more clear and concise”
359 361 Interrater agreement D 91%;
Cohen’s k D .89
Questioning Group member questions the validity of
one or more of the propositions put
forward by another group member
“Are you sure that having harsher fines
will work? Fines already exist for
littering but that has not stopped
people from doing it”
124 122 Interrater agreement D 98%;
Cohen’s k D .98
Disagreeing Group member openly disagrees with
one or more of the propositions
offered by another group member
“I don’t agree at all with your idea of
simply having more bins”
85 83 Interrater agreement D 98%;
Cohen’s k D .97
Off-task behavior Group member engages in talk not
related to the problem-solving task
“How was the ski trip last week?” 409 411 Interrater agreement D 92%;
Cohen’s k D .90
THE JOURNAL OF EDUCATIONAL RESEARCH 5

7. behaviors (idea development and critical review) and is uncor-
related with off-task behavior. Hence, Hypothesis 4 is sup-
ported in terms of the on-task behaviors.
Multilevel modeling
As an initial step, fully unconditional variance decomposi-
tion models were estimated. All variables had statistically
significant variance at the individual level, but only
teachers’ ratings of students’ general PSA and interdepen-
dent self were statistically significant at the group level
(see Table 4).
Three multilevel models were developed with individual
behaviors as dependent variables. We adopted the hierarchi-
cal approach (Pedhazur, 1982) because we wished to ascer-
tain the statistical significance, or otherwise, of individual
variables. In general, we followed the strategy outlined by
Hox (2010) and Snijders and Bosker (1999). As a first step
all demographic variables (i.e., sex, age, school, and grade)
were entered as control variables. Following the entry of the
control variables, all of the following variables were entered
one step at a time based on the rationale described
subsequently.
Teacher ratings of students’ PSA was entered first because
PSA was fundamental to the group task. Given that the friend-
ship and acquaintanceship group distinction was a key aspect
of the study, the dummy variable (friendship group D 1), group
type, was entered next. As independent self and interdependent
self are considered to represent relatively long-standing,
chronic differences between individuals (Markus Kitayama,
1991), these variables were entered next, starting with indepen-
dent self followed by interdependent self. The order of entry
here was based on the fact that the study was carried out in an
individualist country (Hofstede, 2001) in which independent
Table 2. Items and factor loadings for exploratory factor analysis with varimax rotation of self-efficacy friends, and self-efficacy acquaintances, and self-construal scales.
Factors and loadings
Items
Self-efficacy
friends
Self-efficacy
acquaintances
Interdependent
self
Independent
self
I can coordinate the activities of the group (FR) .77a
.26 .11 .21
I can ask other group members for their ideas (FR) .77a
.24 .23 .08
I can play an effective role in running the group (FR) .72a
.31 .12 .30
I can encourage other group members to express their viewpoints (FR) .72a
.27 .13 .21
I can build on other group members’ ideas (FR) .72a
.19 ¡.03 .01
I can clearly explain my ideas to the group (FR) .69a
.29 .00 .36
I can make a valuable contribution to a group project (FR) .67a
.34 ¡.03 .27
I can accept other group members’ viewpoints (FR) .66a
.18 .12 ¡.07
I can accept other group members’ viewpoints (ACQ) .24 .79a
.06 .03
I can ask other group members for their ideas (ACQ) .34 .77a
.21 .05
I can play an effective role in running the group (ACQ) .27 .76a
.28 ¡.02
I can coordinate the activities of the group (ACQ) .40 .76a
.26 .10
I can clearly explain my ideas to the group (ACQ) .36 .74a
.26 ¡.01
I can build on other group members’ ideas (ACQ) .29 .72a
.01 .12
I can encourage other group members to express their viewpoints (ACQ) .16 .63a
.26 .00
I can make a valuable contribution to a group project (ACQ) .39 .57a
.29 .07
In general, my relationships with my classmates are an important part
of how I see myself
.15 .17 .64a
¡.04
I enjoy spending time with my classmates .20 .21 .62a
.00
My classmates help define who I am ¡.05 .11 .60a
¡.04
The well-being of my classmates is very important to me .24 .14 .56a
.07
When I think of myself I often think of my classmates with whom I often
associate
.01 .30 .47a
.12
I prefer to be distinguished from my classmates .13 ¡.09 ¡.02 .77a
I like to stand-out from my classmates .17 ¡.02 .14 .70a
I am a unique person separate from my classmates .13 .19 ¡.07 .60a
Note. ACQ D self-efficacy acquaintances items; FR D self-efficacy friends items.
a
Factor loadings .40.
Table 3. Raw means, standard deviations, and Spearman intercorrelations of the individual-level variables.
M SD Min, Max 1 2 3 4 5 6 7
1. PSA 5.19 1.37
2. Independent self 4.61 1.34 .15
3. Interdependent self 4.47 1.13 .21
.00
4. SE friends 7.46 1.81 .22
.28
.24
5. SE acquaintances 6.57 2.15 .08 .09 .42
.60
6. Idea development 3.11 2.01 0, 9 .33
¡.03 .17
.07 .23
7. Critical review 0.82 1.17 0, 7 .19
.01 ¡.09 .10 .21
.58
8. Off task 3.25 5.35 0, 30 ¡.22
¡.10 ¡.10 ¡.03 .10 ¡.04 .29
Note. Max D maximum scores for observed behaviors; Min D minimum scores for observed behaviors; PSA D teacher ratings of students’ problem solving ability; SE
acquaintances D self-efficacy acquaintances; SE friends D self-efficacy friends.
p .05.
6 J. HANHAM AND J. MCCORMICK

8. self is likely to be salient in more contexts than interdependent
self. Because friendship groups are the most salient group for
adolescents (Newcomb Bagwell, 1995), self-efficacy friends
was entered next followed by self-efficacy acquaintances. Fol-
lowing the entry of the self-constructs, the group means of the
variables with significant variation at the group level were then
entered into the model. The order of entry was consistent with
the individual variables: Mean PSA, followed by the means for
interdependent self. The models at each step were checked for
an improvement in the log-likelihood statistic, and statistically
nonsignificant variables were removed.
Multilevel model with idea development as the
dependent variable
Table 5 shows the development of a multilevel model with
idea development as the dependent variable. The first statisti-
cally significant predictor in the final model is self-efficacy
acquaintances, with the higher a student’s self-efficacy for
group work with acquaintances, the more likely she or he
engaged in behaviors related to idea development. As idea
development reflects on-task behaviors, this result provides
some support for Hypothesis 4. Mean PSA is the next and
strongest statistically significant predictor; the higher the
mean PSA of members the group, the more likely individual
group members exhibited idea development behaviors. This
result makes sense as people in group contexts generally tend
to match their performances with those around them
(Shepherd, Briggs, Reinig, Yen, Nunamaker, 1996). It is
also worth noting there is some evidence that mean PSA
mediated the relationship between PSA and idea develop-
ment. Possibly, whilst the problem-solving abilities of individ-
ual group members may predict idea development, they may
be less important when the average PSA of members of the
group is taken into account.
It should be noted that interdependent self was a statis-
tically significant predictor when first entered into the
model, and to this extent provides partial support for
Hypothesis 2. However, when self-efficacy friends was
entered into the model, interdependent self was no longer
a statistically significant predictor of idea development,
suggesting shared variance between interdependent self
and self-efficacy friends.
Multilevel model with critical review as the
dependent variable
Table 6 shows the development of a multilevel model with
critical review as the dependent variable. Self-efficacy
acquaintances was the only statistically significant predictor
of critical review. Compared to friendship groups, acquain-
tance groups are generally considered to have more challeng-
ing environments in which to engage in effective group
processes (Jehn Shah, 1997). Given that self-efficacy is con-
sistently linked with effort, perseverance, and engagement in
tasks (Bandura, 2012), it makes sense that the more self-effica-
cious students were for working in groups with acquaintances
the more likely they were to display critical review behaviors.
Furthermore, this result provides some added support for
Hypothesis 4.
Table 4. Fully unconditional variance decomposition models.
Individual level Group level
Variable Variance SE p Variance SE p
Intraclass
correlation
Independent self .96
.15 .00 .02 .09 .80 .02
Interdependent self .51
.08 .00 .26
.10 .01 .34
SE friends .87
.13 .00 .06 .09 .51 .06
SE acquaintances .79
.12 .00 .15 .10 .13 .16
PSA 1.13
.17 .00 .74
.25 .00 .40
Note. PSA D teacher ratings of students’ problem solving ability; SE acquaintances
D self-efficacy acquaintances; SE friends D self-efficacy friends.
p .05 (t statistic).
Table 5. Development of a multilevel model with idea development as the dependent variable.
Parameter 1 2 3 4 5 6 7 8 9
Fixed effects
Intercept 1.79 ¡0.02 ¡0.01 ¡0.06 ¡0.54 ¡0.26 0.36 ¡1.33 ¡1.46
(1.75) (1.80) (1.80) (1.80) (1.79) (1.86) (1.78) (1.94) (1.96)
Level 1
1. Control variables
2. PSA 0.15
(0.05) 0.15
(0.05) 0.14
(0.05) 0.14
(0.05) 0.14
(0.05) 0.12
(0.05) 0.08 (0.05)
3. Group type ¡0.09 (0.21)
4. Independence 0.06 (0.07)
5. Interdependence 0.15
(0.07) 0.15 (0.08)
6. SE friends 0.02 (0.07)
7. SE acquaintances 0.14
(0.06) 0.14
(0.06) 0.17
(0.06)
Level 2
8. Mean PSA 0.25
(0.12) 0.42
(0.13)
9. Mean interdependence ¡0.30 (0.20)
Random parameters
Level 2 intercept/intercept 0.40
0.35
0.36
0.38
0.38
0.38
0.38
0.34
0.32
(0.11) (0.10) (0.10) (0.10) (0.10) (0.10) (0.10) (0.09) (0.09)
Level 1 intercept/intercept 0.29
0.28
0.28
0.27
0.25
0.26
0.26
0.25
0.26
(0.05) (0.04) (0.04) (0.04) (0.04) (0.04) (0.04) (0.04) (0.04)
¡2 log likelihood 271.08 269.39 262.20 261.55 258.16 258.10 257.16 252.99 253.21
Note. Group type D friendship and acquaintance groups; Independence D independent self; Interdependence D interdependent self; Mean interdependence D group
mean of interdependent self; Mean PSA D group mean of teacher ratings of students’ problem-solving ability; PSA D teacher ratings of students’ problem solving abil-
ity; SE acquaintances D self-efficacy acquaintances; SE friends D self-efficacy friends. Standard errors are in parentheses.
THE JOURNAL OF EDUCATIONAL RESEARCH 7

9. Multilevel model with off-task behavior as the
dependent variable
Table 7 shows the development of a multilevel model with
off-task behavior as the dependent variable. None of the
independent variables was a statistically significant predictor of
off-task behavior. As such, in this model, none of the
hypotheses were supported.
After development of the final theoretical models,
competing models were developed. Two strategies were
employed. The first entailed a backward approach in which
all variables were entered initially and the highest
statistically nonsignificant variables were removed one at a
time. The second strategy was a mixed approach whereby
all of the statistically significant variables from the
theoretical and backwards models were entered and
statistically nonsignificant variables were removed one at a
time. The final theoretical, backward, and mixed-approach
models were then compared with particular attention to
the log-likelihood function. Although there was very slight
improvement in the log-likelihood function in favor of the
backwards and mixed-approach models, it was decided to
retain the final theoretically derived models rather than
risk capitalizing on chance, which could be the case with
the competing models.
Table 6. Development of a multilevel model with critical review as the dependent variable.
Parameter 1 2 3 4 5 6 7 8 9
Fixed effects
Intercept 4.41
4.32
4.41
4.41
4.21
4.26
4.64
4.03 4.88
(1.84) (2.00) (1.84) (1.85) (1.86) (1.83) (1.83) (2.17) (1.82)
Level 1
1. Control variables
2. PSA 0.01 (0.06)
3. Group type ¡0.04 (0.19)
4. Independence 0.02 (0.09)
5. Interdependence 0.01 (0.07)
6. SE friends 0.02 (0.07)
7. SE acquaintances 0.16
(0.08) 0.16
(0.08) 0.17
(0.08)
Level 2
8. Mean PSA 0.05 (0.10)
9. Mean interdependence ¡.22 (.17)
Random parameters
Level 2 intercept/intercept 0.18
0.18
0.18
0.19
0.20
0.18
0.20
0.20
0.19
(0.08) (0.08) (0.08) (0.08) (0.09) (0.08) (0.08) (0.08) (0.08)
Level 1 intercept/intercept 0.50
0.50
0.50
0.50
0.50
0.50
0.48
0.48
0.47
(0.08) (0.08) (0.08) (0.08) (0.08) (0.08) (0.07) (0.07) (0.07)
¡2 log likelihood 302.56 302.54 302.52 302.48 301.79 300.38 298.25 297.98 296.44
Note. Group type D friendship and acquaintance groups); Independence D independent self; Interdependence D interdependent self; Mean interdependence D group
mean of interdependent self; Mean PSA D group mean of teacher ratings of students’ problem-solving ability; PSA D teacher ratings of students’ problem solving
ability; SE acquaintances D self-efficacy acquaintances; SE friends D self-efficacy friends. Standard errors are in parentheses.
Table 7. Development of a multilevel model with off-task behaviors as the dependent variable.
Parameter 1 2 3 4 5 6 7 8 Final 9
Fixed effects
Intercept 1.72 2.78 1.78 1.70 1.23 2.81 1.59 4.94 1.33
(10.33) (11.04) (10.33) (10.33) (10.43) (10.35) (10.34) (12.14) (10.35)
Level 1
1. Control variables
2. PSA ¡0.08 (0.31)
3. Group type 2.07 (1.20)
4. Independence 0.02 (0.43)
5. Interdependence 0.15 (0.46)
6. SE friends ¡0.36 (0.37)
7. SE acquaintances ¡0.11 (0.38)
Level 2
8. Mean PSA ¡0.34 (0.68)
9. Mean interdependence 0.46 (1.09)
Random parameters
Level 2 intercept/intercept 11.79
11.77
10.80 11.79
11.74
11.92
11.85
11.72
11.71
(3.42) (3.41) (3.21) (3.42) (3.41) (3.44) (3.43) (3.40) (3.40)
Level 1 intercept/intercept 11.00
11.00
11.00
11.00
11.00
10.85
10.97
10.99
11.00
(1.70) (1.70) (1.70) (1.70) (1.70) (1.67) (1.69) (1.70) (1.70)
¡2 log likelihood 720.14 720.06 717.28 720.13 720.00 719.19 7.20.05 719.88 719.96
Note. Group type D friendship and acquaintance groups); Independence D independent self; Interdependence D Interdependent self; Mean interdependence D group
mean of interdependent self; Mean PSA D group mean of teacher ratings of students’ problem-solving ability; PSA D teacher ratings of students’ problem solving
ability; SE acquaintances D self-efficacy acquaintances; SE friends D self-efficacy friends. Standard errors are in parentheses.
8 J. HANHAM AND J. MCCORMICK

10. Multilevel model comparing the performance of
friendship versus acquaintance groups on the
problem-solving task
A multilevel test found no statistically significant differences
between the performances of the friendship and acquaintance
groups, t(41) D ¡0.84, p D .40, answering the first research
question.
Discussion
This research investigated relationships between students’ self
beliefs and their individual behaviors when working on a prob-
lem-solving task with friends or acquaintances. It was hypothe-
sized that the more independent the self-construal was the fewer
on-task behaviors and the more off-task behaviors there would
be (Hypothesis 1), and the more interdependent the self-con-
strual was the more on-task behaviors and the fewer off-task
behaviors would be (Hypothesis 2). The results from the multi-
level models provided partial support for Hypothesis 2; no sup-
port was found for Hypothesis 1. Hypotheses were also
generated concerning self-efficacy for working with friends and
self-efficacy for working with acquaintances in which it was
hypothesized (Hypothesis 3 and Hypothesis 4) that the stronger
the self-efficacy beliefs were the more on-task behaviors and the
fewer off-task behaviors there would be. Findings from the mul-
tilevel modeling provided partial support for Hypothesis 4, with
self-efficacy for working with acquaintances predicting idea
development and individual critical review behaviors.
Of the two self-efficacy variables, self-efficacy friends and self-
efficacy acquaintances, only the latter emerged as a predictor of
on-task behaviors. Past research has suggested a flow-on effect
from self-efficacy for working with friends, generalizing to self-
efficacy for working with acquaintances (Hanham McCor-
mick, 2009). Because self-efficacy in one domain may generalize
to related domains (Bandura, 1997), it is logical that students
who are self-efficacious for working with acquaintances may also
be self-efficacious for working with friends. Interpreted in this
light, it is not that surprising students who had high self-efficacy
for working with acquaintances exhibited behaviors related to
idea development and critical review, irrespective of whether the
groups comprised friends or acquaintances.
This finding has implications for theories concerning friend-
ship and group work. Scholars interested in peer relations (e.g.,
Azmitia Montgomery, 1993; Hartup, 1996) have tended to
advocate grouping students with friends, as friendship groups
are thought to provide environments conducive to the develop-
ment of students’ skills as colearners. The findings from this
research suggest that this may generally be a good strategy,
although consideration should also be given to how students
can extend skills developed in friendship groups to acquain-
tance groups. From a practical perspective, the extension of
skills from friends to acquaintances is likely to be of importance
for preparing students for future participation in the workforce,
as individuals often are required to collaborate with others who
are not friends (O’Neil, Allred, Barker, 1997).
As group work is often positioned as an instructional strat-
egy for honing students’ teamwork and interpersonal skills
(Slavin, 1996), the link between self-efficacy for working with
acquaintances and behaviors related to idea development and
critical review has practical implications. Building, accepting,
explaining, and questioning ideas are key components of team-
work (Webb Palincsar, 1996). To increase the likelihood of
students exhibiting such behaviors when working in groups in
general, teachers could strategically target sources (Pajares,
1996) known to influence self-efficacy. These include providing
students with opportunities to obtain mastery experiences
working with less familiar peers. Teachers should also model
strategies, which demonstrate how one may disagree or ques-
tion the ideas of others in ways that are nonthreatening and
inoffensive. Similarly, teachers should ask students with experi-
ence of working successfully in groups to model effective inter-
action behaviors to less experienced peers. It is possible for
teachers to use another source known to influence self-efficacy,
verbal persuasion; teachers should actively persuade students
that questioning and disagreeing with others’ ideas, especially
those whom they do not know well, can be done in a construc-
tive and nonthreatening manner.
With respect to the research question (Are there perfor-
mance differences between friendship and acquaintances
groups?), there was no statistically significant difference
between friendship and acquaintance groups on the problem-
solving task. There were also no statistically significant differen-
ces in individual behaviors exhibited by students working in
these two different group types.
Of the level 2 variables tested in this study, mean PSA pre-
dicted idea development in groups. This result reinforces past
research and literature, which has identified ability level as a
key factor in group problem-solving performance (e.g., Saleh,
Lazonder, De Jong, 2007). A meta-analysis on within-class
grouping by Lou et al. (1996) suggested that low-ability stu-
dents may obtain significant learning gains from being grouped
with ability students, and that high-ability students are unlikely
to be negatively impacted from being grouped with low-ability
students.
Conclusions
This study has limitations that need to be acknowledged. First,
PSA and off-task behavior were single-score variables. Second,
only a limited number of theoretical constructs were used to
predict students’ behaviors. It is possible that other constructs
could have similar or stronger relationships with students’
behaviors in group work settings. Third, because students were
aware they were being videotaped, some students might have
acted atypically. Fourth, the data are cross-sectional and causal-
ity may not be inferred. Fifth, although adequate, a larger sam-
ple would have been desirable. However, perhaps more
importantly, the study should be replicated with different
within-group sample sizes, as group size could affect behaviors
and outcomes. Sixth, in this study we used a single-task design,
which limited generalizability. Having stated this, the problem-
solving task used in the study falls within the category of open-
ended, ill-structured problems. As such, it may be argued that
the findings from this study may cautiously be generalizable to
similar types of open-ended problems. Indeed, some research-
ers (e.g., Cohen, 1994) recommend using open-ended,
ill-structured problems when employing group work in the
THE JOURNAL OF EDUCATIONAL RESEARCH 9

11. classroom and such problem-types have been used in previous
studies of group work in schools (e.g., Gillies, 2000).
Despite limitations, the findings from this study represent
an important step forward in unpacking the complex rela-
tionships between students’ self-beliefs and their behaviors
during group work activities. Based on the results of this
research, there are some directions for future research that
scholars may wish to pursue. As self-efficacy beliefs are
changeable, future research may involve gathering longitudi-
nal data that examine how self-efficacy for working in
friendship or acquaintanceship groups develops over time. It
may also be worthwhile investigating the dynamics of other
efficacy beliefs, such as collective efficacy (Bandura, 1997).
Also, combining self-reports and observations with interview
data (Summers Volet, 2010) that capture students’ insights
about working with friends and acquaintances should pro-
vide researchers and teachers with a more complete picture
of this group-based phenomenon. Finally, future researchers
should attempt to identify under what conditions friendship
and acquaintance groups are likely to differ on group
achievement scores for problem-solving tasks.
References
Arvaja, M., Salovaara, H., H€
akkinen, P., J€
arvel€
a, S. (2007). Combining
individual and group-level perspectives for studying collaborative
learning in context. Learning and Instruction, 17, 448–459. http://dx.
doi.org/10.1016/j.learninstruc.2007.04.003
Atkinson, R. K., Derry, S. J., Renkl, A., Wortham, D. W. (2000). Learn-
ing from examples: Instructional principles from the worked examples
research. Review of Educational Research, 70, 181–214. http://dx.doi.
org/10.2307/1170661
Ayres, P., Paas, F. (2009). Interdisciplinary perspectives inspiring a new
generation of cognitive load research. Educational Psychology Review,
21, 1–9. http://dx.doi.org/10.1007/s10648-008-9090-7
Azmitia, M., Montgomery, R. (1993). Friendship, transactive dialogues,
and the development of scientific reasoning. Social Development, 2,
202–201. http://dx.doi.org/10.1111/j.1467-9507.1993.tb00014.x
Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY:
Freeman.
Bandura, A. (2012). On the functional properties of perceived self-efficacy
revisited. Journal of Management, 38, 9–44. http://dx.doi.org/10.1177/
0149206311410606
Barry, C. M., Wentzel, K. R. (2006). Friend influence on prosocial behavior:
The role of motivational factors and friendship characteristics. Developmen-
tal Psychology, 42, 153–163. http://dx.doi.org/10.1037/0012-1649.42.1.153
Berndt, T. J., Perry, T. B., Miller, K. E. (1988). Friends’ and classmates’
interactions on academic tasks. Journal of Educational Psychology, 80,
506–513. http://dx.doi.org/10.1037/0022-0663.80.4.506
Board of Studies Teaching and Educational Standards NSW. (2016). Board
of Studies and Reaching Educational Standards NSW course perfor-
mance band descriptors, science. Retrieved from http://arc.bostes.nsw.
edu.au/go/9-10/stage-5-grading/cpds/index/science
Cohen, E. G. (1994). Restructuring the classroom: Conditions for produc-
tive small groups. Review of Educational Research, 64, 1–35. http://dx.
doi.org/10.2307/1170744
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory
and applications. Journal of Applied Psychology, 78, 98–104. http://dx.
doi.org/10.1037/0021-9010.78.1.98
De Wever, B., Schellens, T., Valcke, M., Van Keer, H. (2006). Content
analysis schemes to analyze transcripts of online asynchronous discus-
sion groups: A review. Computers Education, 46, 6–28. http://dx.doi.
org/10.1016/j.compedu.2005.04.005
DiDonato, N. (2013). Effective self—and co-regulation in collaborative
learning groups: An analysis of how students regulate problem solving
of authentic interdisciplinary tasks. Instructional Science, 41, 25–47.
http://dx.doi.org/10.1007/s11251-012-9206-9
Eby, L. T., Dobbins, G. H. (1997). Collectivistic orientation in
teams: An individual and group level analysis. Journal of Organiza-
tional Behavior, 18, 275–295. http://dx.doi.org/10.1002/(SICI)1099-
1379(199705)18:3lt;275::AID-JOB796gt;3.0.CO;2-C
Finegold, M., Eilam, B. (1995). Sociometric analysis: A classroom
assessment tool for teachers. Studies in Educational Evaluation, 21,
57–71.
Galton, M., Hargreaves, L. (2009). Group work: Still a neglected art?
Cambridge Journal of Education, 39, 1–6. doi: http://dx.doi.org/
10.1080/03057640902726917
Galton, M., Williamson, J. (1992). Group work in the primary classroom.
London, England: Routledge.
Gill, P., Remedios, R. (2013). How should researchers in Education oper-
ationalise on-task behaviours? Cambridge Journal of Education, 43,
199–222. http://dx.doi.org/10.1080/0305764X.2013.767878
Gillies, R. M. (2000). The maintenance of cooperative and helping behav-
iours in cooperative groups. British Journal of Educational Psychology,
70, 97–111. http://dx.doi.org/10.1348/000709900157994
Gillies, R. M. (2004). The effects of cooperative learning on junior high
school students during small group learning. Learning and Instruction,
14, 197–213. http://dx.doi.org/10.1016/S0959-4752(03)00068-9
Gillies, R. M. (2007). Cooperative learning: Integrating theory and practice.
Thousand Oaks, CA: Sage.
Hanham, J., McCormick, J. (2008). Relationships between self-processes
and group processes with friends and acquaintances. Issues in Educa-
tional Research, 18, 118–137.
Hanham, J., McCormick, J. (2009). Group work in schools with close
friends and acquaintances: Linking self-processes with group processes.
Learning and Instruction, 19, 214–227. http://dx.doi.org/10.1016/j.
learninstruc.2008.04.002
Hanham, J., McCormick, J. (2010). Friendship and the development of
school students’ collaborative learning skills. In J. C. Toller (Ed.),
Friendships: Types, cultural and psychological aspects (pp. 101–116).
Hauppauge, NY: Nova Science.
Hannover, B., Birkner, N., P€
ohlmann, C. (2006). Ideal Selves and self-
esteem in people with independent or interdependent self-construal.
European Journal of Social Psychology, 36, 1, 119–133. http://dx.doi.
org/10.1002/ejsp.289
Hartup, W. W. (1996). The company they keep: Friendships and their
developmental significance. Child Development, 67, 1–13. http://dx.doi.
org/10.2307/1131681
Hartup, W. W. (1998). Cooperation, close relationships, and cognitive
development. In W. M., Bukowski, A. F., Newcomb, W. Hartup,
(Eds.), The company they keep: Friendship in childhood and adolescence.
Cambridge studies in social and emotional development (pp. 213–237).
Cambridge, UK: Cambridge University Press.
Henrich, C. C., Kuperminc, G. P., Sack, A., Blatt, S. J., Leadbeater, B. J.
(2000). Characteristics and homogeneity of early adolescent friendship
groups: A comparison of male and female clique and non-clique mem-
bers. Applied Developmental Science, 4, 15–26. http://dx.doi.org/
10.1207/S1532480XADS0401_2
Hofer, M. (2007). Goal conflicts and self-regulation: A new look at pupils’
off-task behaviour in the classroom. Educational Research Review, 2,
28–38. http://dx.doi.org/10.1016/j.edurev.2007.02.002
Hofstede, G. (2001). Culture’s consequences. Thousand Oaks, CA: Sage.
Hox, J. (2010). Multilevel analysis: Techniques and applications. New York,
NY: Routledge.
J€
arvel€
a, S., Volet, S., J€
arvenoja, H. (2010). Research on motivation in col-
laborative learning: Moving beyond the cognitive-situative divide and
combining individual and social processes. Educational Psychologist,
45, 15–27. http://dx.doi.org/10.1080/00461520903433539
Jehn, K., Shah, P. P. (1997). Interpersonal relationships and task perfor-
mance: An examination of mediating processes in friendship and
acquaintance groups. Journal of Personality and Social Psychology, 72,
775–790. http://dx.doi.org/10.1037/0022-3514.72.4.775
Johnson, D. W., Johnson, R. T., Holubec, E. J. (1994). The new circles
of learning: Cooperation in the classroom and school. Alexandria,
VA: Association for Supervision and Curriculum Development.
10 J. HANHAM AND J. MCCORMICK

12. Kirschner, F., Paas, F., Kirschner, P. (2009). Individual and group-based
learning from complex cognitive tasks: Effects on retention and transfer
efficiency. Computers in Human Behavior, 25, 306–314. http://dx.doi.
org/10.1016/j.chb.2008.12.008
Kiuru, N., Pakarinen, E., Vasalampi, K., Silinskas, G., Aunola, K., Poikkeus,
A.-M., … Nurmi, J.-E. (2014). Task-focus behavior mediates the associ-
ations between supportive interpersonal environments and students’
academic performance. Psychological Science, 25, 1018–1024. http://dx.
doi.org/10.1177/0956797613519111
Lee, S. W., Kelly, K. E., Nyre, J. E. (1999). Preliminary report on the rela-
tion of students’ on-task behavior with completion of school work. Psy-
chological Reports, 84, 267–272. http://dx.doi.org/10.2466/
PR0.84.1.267-272
Lou, Y., Abrami, P. C., Spence, J. C., Poulsen, C., Chambers, B., d’Apol-
lonia, S. (1996). Within-class grouping: A meta-analysis. Review of
Educational Research, 66, 423–458.
Markus, H. R., Kitayama, S. (1991). Culture and self: Implications for
cognition, emotion, and motivation. Psychological Review, 98, 224–253.
Markus, H. R., Kitayama, S. (2010). Cultures and selves: A cycle of
mutual constitution. Perspectives on Psychological Science, 5, 420–430.
http://dx.doi.org/10.1177/1745691610375557
Miell, D., MacDonald, R. A. R. (2000). Children’s creative collabora-
tions: The importance of friendship when working together on a musi-
cal composition. Social Development, 9, 348–369. http://dx.doi.org/
10.1111/1467-9507.00130
Mitchell, S. N., Reilly, R., Bramwell, F. G., Solonsky, A., Lilly, F. (2004).
Friendship and choosing groupmates: Preference for teacher-selected
vs. student-selected groupings in high school science classes. Journal of
Instructional Psychology, 31, 20–32.
Newcomb, A. F., Bagwell, C. L. (1995). Children’s friendship relations: A
meta-analytic review. Psychological Bulletin, 117, 306–347. http://dx.
doi.org/10.1037/0033-2909.117.2.306
Oetzel, J. G. (2001). Self-construals, communication processes, and group
outcomes in homogeneous and heterogeneous groups. Small Group
Research, 32, 19–54. http://dx.doi.org/10.1177/104649640103200102
O’Neil, H. F. Jr., Allred, K., Baker, E. L. (1997). Review of workforce readi-
ness theoretical frameworks. In H. F. O’Neil, Jr. (Ed.), Workforce readi-
ness: Competencies and assessment (pp. 3–25). Mahwah, NJ: Erlbaum.
Organization for Economic Cooperation and Development. (2015). PISA
2015: Draft collaborative problem-solving framework. Retrieved from
http://www.oecd.org/pisa/pisaproducts/Draft%20PISA%202015%20Co
llaborative%20Problem%20Solving%20Framework%20.pdf
Oyserman, D., Coon, H. M., Kemmelmeier, M. (2002). Rethinking indi-
vidualism and collectivism: evaluation of theoretical assumptions and
meta-analyses. Psychological Bulletin, 128, 3–72. doi: http://dx.doi.org.
ezproxy.uws.edu.au/10.1037/0033-2909.128.1.3
Pajares, F. (1996). Self-efficacy beliefs in academic settings. Review of Edu-
cational Research, 66, 543–578. http://dx.doi.org/10.2307/1170653
Pedhazur, E. J. (1982). Multiple regression in behavioral research: Explana-
tion and prediction (2nd ed.). New York, NY: Holt, Rinehart, and
Winston.
Pintrich, P. R., Schunk, D. H. (2002). Motivation in education: Theory,
research, and applications (2nd ed.). Columbus, OH: Merrill-Prentice
Hall.
Robinson, D. R., Schofield, J. W., Steers-Wentzell, K. L. (2005). Peer and
cross-age tutoring in math: Outcomes and their design implications.
Educational Psychology Review, 17, 327–362. http://dx.doi.org/10.1007/
s10648-005-8137-2
Saleh, M., Lazonder, A. W., De Jong, T. (2007). Structuring collabo-
ration in mixed-ability groups to promote verbal interaction, learn-
ing, and motivation in average-ability students. Contemporary
Educational Psychology, 32, 314–331. http://dx.doi.org/j.
cedpsych.2006.05.001.
Sears, D. A., Reagin, J. M. (2013). Individual versus collaborative prob-
lem solving: divergent outcomes depending on task complexity.
Instructional Science, 41, 1153–1172. http://dx.doi.org/10.1007/s11251-
013-9271-8
Sharan, S., Shachar, H. (1988). Language and learning in the cooper-
ative classroom. New York, NY: Springer-Verlag. Sinclair,J. McH.,
Coulth
Shepherd, M. M., Briggs, R. O., Reinig, B. A., Yen, J., Nunamaker, J. F. Jr.
(1996). Invoking social comparison to improve electronic brainstorm-
ing: Beyond anonymity. Journal of Management Information Systems,
12, 155–170.
Singelis, T. M. (1994). The measurement of independent and interdepen-
dent self-construals. Personality and Social Psychology Bulletin, 20,
580–591. http://dx.doi.org/10.1177/0146167294205014
Slavin, R. E. (1996). Research on cooperative learning and achievement:
What we know, what we need to know. Contemporary Educational Psy-
chology, 21, 43–69. http://dx.doi.org/10.1006/ceps.1996.0004
Snijders, T. A., Bosker, R. J. (1999). Multilevel Analysis: An
introduction to basic and advanced multilevel modeling. London,
England: Sage.
Stegmueller, D. (2013). How many countries for multilevel modeling? A
comparison of frequentist and Bayesian approaches. American Journal
of Political Science, 57, 748–761.
Summers, M., Volet, S. (2010). Group work does not necessarily equal
collaborative learning: Evidence from observations and self-reports.
European Journal of Psychology of Education, 25, 473–492. http://dx.
doi.org/10.1007/s10212-010-0026-5
Sweller, J. (1999). Instructional design. Melbourne, Australia: ACER Press.
Tasa, K., Taggar, S., Seijts, G. H. (2007). The development of collective efficacy
in teams: A multilevel and longitudinal perspective. Journal of Applied Psy-
chology, 92, 17–27. http://dx.doi.org/10.1037/0021-9010.92.1.17
T€
auber, S., Sassenberg, K. (2012). Newcomer conformity: How self-con-
strual affects the alignment of cognition and behavior with group goals
in novel groups. Social Psychology, 43, 138–147. http://dx.doi.org/
10.1027/1864-9335/a000092
Veerman, A., Veldhuis-Diermanse, E. (2001). Collaborative learning
through computer-mediated communication in academic education. In
P. Dillenbourg, A. Eurelings, K. Hakkarainen (Eds.), European per-
spectives on computersupported collaborative learning. Proceedings of
the First European Conference on CSCL. Maastricht, the Netherlands:
McLuhan Institute, University of Maastricht.
Wang, C., Oyserman, D., Liu, Q., Li, H., Han, S. (2013). Accessible cul-
tural mindset modulates default mode activity: Evidence for the cultur-
ally situated brain. Social Neuroscience, 8, 203–216. http://dx.doi.org/
0.1080/17470919.2013.775966
Webb, N. M., Palincsar, A. S. (1996). Group processes in the classroom.
In D. Berliner R. Clafree (Eds.), Handbook of educational psychology
(3rd ed., pp. 841–873). New York, NY: Macmillan.
Zajac, R. J., Hartup, W. W. (1997). Friends as co-workers: Research
review and classroom implications. Elementary School Journal, 98,
3–13. http://dx.doi.org/10.1086/461881
Appendix
B: More ashtrays in the street (new idea).
C: I reckon having more bins next to the drain (new idea)..
B. What about like filters on drains (new idea).
A. You could have like grate over the drain – a mesh (builds on
ideas).
B. What about butts that are environmentally friendly? (New
idea.)
C. Yes, yes (accepts idea).
C. I reckon there should be more ads on tv showing “this is
what you are doing to the environment” (new idea).
A. Milk cartons (new idea).
B. Milk cartons, what the hell? No (disagrees).
A. Floating signs in the sea (new idea).
C. No (disagrees).
THE JOURNAL OF EDUCATIONAL RESEARCH 11

13. B. Are you sore from the ski trip? (Off-task.)
A. Ahh yes (off-task).
C. Here’s how to describe our strategy. Just write if the cigarette
is put down the drain—in the drain there is a filtering system
with mesh over the top so the water will drain through but the
cigarette butts and all the other gunk and rubbish will be caught
up in the mesh and once every 24 hours (strategizing).
A. Isn’t that too complicated? (Questioning.)
C. No. Once every 24 hours they replace the mesh and the rub-
bish will be recycled (explanation).
A. Nobody is going to want to clean it (disagrees).
C. Yes, there are council workers whose job will be clean and
recycle the rubbish and butts (explanation)..
A. Yes (accept), and we should get community service workers
to pick up butts and they have to reach a certain quota every
day (builds ideas).
12 J. HANHAM AND J. MCCORMICK