Research Papers On Gender Relations In Class Group Assignments

Abstract

Group work is used as a means for learning at all levels in educational systems. There is strong scientific support for the benefits of having students learning and working in groups. Nevertheless, studies about what occurs in groups during group work and which factors actually influence the students’ ability to learn is still lacking. Similarly, the question of why some group work is successful and other group work results in the opposite is still unsolved. The aim of this article is to add to the current level of knowledge and understandings regarding the essence behind successful group work in higher education. This research is focused on the students’ experiences of group work and learning in groups, which is an almost non-existing aspect of research on group work prior to the beginning of the 21st century. A primary aim is to give university students a voice in the matter by elucidating the students’ positive and negative points of view and how the students assess learning when working in groups. Furthermore, the students’ explanations of why some group work ends up being a positive experience resulting in successful learning, while in other cases, the result is the reverse, are of interest. Data were collected through a study-specific questionnaire, with multiple choice and open-ended questions. The questionnaires were distributed to students in different study programs at two universities in Sweden. The present result is based on a reanalysis and qualitative analysis formed a key part of the study. The results indicate that most of the students’ experiences involved group work that facilitated learning, especially in the area of academic knowledge. Three important prerequisites (learning, study-social function, and organization) for group work that served as an effective pedagogy and as an incentive for learning were identified and discussed. All three abstractions facilitate or hamper students’ learning, as well as impact their experiences with group work.

Keywords: group work, collaborative learning, cooperative learning, higher education, students’ perspectives, qualitative research

INTRODUCTION

Group work is used as a means for learning at all levels in most educational systems, from compulsory education to higher education. The overarching purpose of group work in educational practice is to serve as an incentive for learning. For example, it is believed that the students involved in the group activity should “learn something.” This prerequisite has influenced previous research to predominantly focus on how to increase efficiency in group work and how to understand why some group work turns out favorably and other group work sessions result in the opposite. The review of previous research shows that in the 20th century, there has been an increase in research about students’ cooperation in the classroom (Lou et al., 1996; Gillies and Boyle, 2010, 2011). This increasing interest can be traced back to the fact that both researchers and teachers have become aware of the positive effects that collaboration might have on students’ ability to learn. The main concern in the research area has been on how interaction and cooperation among students influence learning and problem solving in groups (Hammar Chiriac, 2011a,b).

Two approaches concerning learning in group are of interest, namely cooperative learning and collaborative learning. There seems to be a certain amount of confusion concerning how these concepts are to be interpreted and used, as well as what they actually signify. Often the conceptions are used synonymously even though there are some differentiations. Cooperative group work is usually considered as a comprehensive umbrella concept for several modes of student active working modes (Johnson and Johnson, 1975; Webb and Palincsar, 1996), whereas collaboration is a more of an exclusive concept and may be included in the much wider concept cooperation (Hammar Chiriac, 2011a,b). Cooperative learning may describe group work without any interaction between the students (i.e., the student may just be sitting next to each other; Bennet and Dunne, 1992; Galton and Williamson, 1992), while collaborative learning always includes interaction, collaboration, and utilization of the group’s competences (Bennet and Dunne, 1992; Galton and Williamson, 1992; Webb and Palincsar, 1996).

At the present time, there is strong scientific support for the benefits of students learning and working in groups. In addition, the research shows that collaborative work promotes both academic achievement and collaborative abilities (Johnson and Johnson, 2004; Baines et al., 2007; Gillies and Boyle, 2010, 2011). According to Gillies and Boyle (2011), the benefits are consistent irrespective of age (pre-school to college) and/or curriculum. When working interactively with others, students learn to inquire, share ideas, clarify differences, problem-solve, and construct new understandings. Gillies (2003a,b) also stresses that students working together are more motivated to achieve than they would be when working individually. Thus, group work might serve as an incentive for learning, in terms of both academic knowledge and interpersonal skills. Nevertheless, studies about what occur in groups during group work and which factors actually influence the students’ ability to learn is still lacking in the literature, especially when it comes to addressing the students’ points of view, with some exceptions (Cantwell and Andrews, 2002; Underwood, 2003; Peterson and Miller, 2004; Hansen, 2006; Hammar Chiriac and Granström, 2012). Similarly, the question of why some group work turns out successfully and other work results in the opposite is still unsolved. In this article, we hope to contribute some new pieces of information concerning the why some group work results in positive experiences and learning, while others result in the opposite.

GROUP WORK IN EDUCATION

Group work is frequently used in higher education as a pedagogical mode in the classroom, and it is viewed as equivalent to any other pedagogical practice (i.e., whole class lesson or individual work). Without considering the pros and cons of group work, a non-reflective choice of pedagogical mode might end up resulting in less desirable consequences. A reflective choice, on the other hand, might result in positive experiences and enhanced learning (Galton et al., 2009; Gillies and Boyle, 2011; Hammar Chiriac and Granström, 2012).

GROUP WORK AS OBJECTIVE OR MEANS

Group work might serve different purposes. As mentioned above, the overall purpose of the group work in education is that the students who participate in group work “learn something.” Learning can be in terms of academic knowledge or “group knowledge.” Group knowledge refers to learning to work in groups (Kutnick and Beredondini, 2009; Gillies and Boyle, 2010, 2011; Hammar Chiriac, 2011a,b). Affiliation, fellowship, and welfare might be of equal importance as academic knowledge, or they may even be prerequisites for learning. Thus, the group and the group work serve more functions than just than “just” being a pedagogical mode. Hence, before group work is implemented, it is important to consider the purpose the group assignment will have as the objective, the means, or both.

From a learning perspective, group work might function as both an objective (i.e., learning collaborative abilities) and as the means (i.e., a base for academic achievement) or both (Gillies, 2003a,b; Johnson and Johnson, 2004; Baines et al., 2007). If the purpose of the group work is to serve as an objective, the group’s function is to promote students’ development of group work abilities, such as social training and interpersonal skills. If, on the other hand, group work is used as a means to acquire academic knowledge, the group and the collaboration in the group become a base for students’ knowledge acquisition (Gillies, 2003a,b; Johnson and Johnson, 2004; Baines et al., 2007). The group contributes to the acquisition of knowledge and stimulates learning, thus promoting academic performance. Naturally, group work can be considered to be a learning environment, where group work is used both as an objective and as the means. One example of this concept is in the case of tutorial groups in problem-based learning. Both functions are important and might complement and/or even promote each other. Albeit used for different purposes, both approaches might serve as an incentive for learning, emphasizing different aspect knowledge, and learning in a group within an educational setting.

WORKING IN A GROUP OR AS A GROUP

Even if group work is often defined as “pupils working together as a group or a team,” (Blatchford et al., 2003, p. 155), it is important to bear in mind that group work is not just one activity, but several activities with different conditions (Hammar Chiriac, 2008, 2010). This implies that group work may change characteristics several times during a group work session and/or during a group’s lifetime, thus suggesting that certain working modes may be better suited for different parts of a group’s work and vice versa (Hammar Chiriac, 2008, 2010). It is also important to differentiate between how the work is accomplished in the group, whether by working in a group or working as a group.

From a group work perspective, there are two primary ways of discussing cooperation in groups: working in a group (cooperation) or working as a group (collaboration; Underwood, 2003; Hammar Chiriac and Granström, 2012). Situations where students are sitting together in a group but working individually on separate parts of a group assignment are referred to as working in a group. This is not an uncommon situation within an educational setting (Gillies and Boyle, 2011). Cooperation between students might occur, but it is not necessary to accomplish the group’s task. At the end of the task, the students put their separate contributions together into a joint product (Galton and Williamson, 1992; Hammar Chiriac, 2010, 2011a). While no cooperative activities are mandatory while working in a group, cooperative learning may occur. However, the benefits in this case are an effect of social facilitation (Zajonc, 1980; Baron, 1986; Uziel, 2007) and are not caused by cooperation. In this situation, social facilitation alludes to the enhanced motivational effect that the presence of other students have on individual student’s performance.

Working as a group, on the other hand, causes learning benefits from collaboration with other group members. Working as a group is often referred to as “real group work” or “meaningful group work,” and denotes group work in which students utilizes the group members’ skills and work together to achieve a common goal. Moreover, working as a group presupposes collaboration, and that all group members will be involved in and working on a common task to produce a joint outcome (Bennet and Dunne, 1992; Galton and Williamson, 1992; Webb and Palincsar, 1996; Hammar Chiriac, 2011a,b). Working as a group is characterized by common effort, the utilization of the group’s competence, and the presence of problem solving and reflection. According to Granström (2006), working as a group is a more uncommon activity in an educational setting. Both approaches might be useful in different parts of group work, depending on the purpose of the group work and type of task assigned to the group (Hammar Chiriac, 2008). Working in a group might lead to cooperative learning, while working as group might facilitate collaborative learning. While there are differences between the real meanings of the concepts, the terms are frequently used interchangeably (Webb and Palincsar, 1996; Hammar Chiriac, 2011a,b; Hammar Chiriac and Granström, 2012).

PREVIOUS RESEARCH OF STUDENTS’ EXPERIENCES

As mentioned above, there are a limited number of studies concerning the participants’ perspectives on group work. Teachers often have to rely upon spontaneous viewpoints and indications about and students’ experiences of group work in the form of completed course evaluations. However, there are some exceptions (Cantwell and Andrews, 2002; Underwood, 2003; Peterson and Miller, 2004; Hansen, 2006; Hammar Chiriac and Einarsson, 2007; Hammar Chiriac and Granström, 2012). To put this study in a context and provide a rationale for the present research, a selection of studies focusing on pupils’ and/or students’ experiences and conceptions of group work will be briefly discussed below. The pupils’ and/or students inside knowledge group work may present information relevant in all levels of educational systems.

Hansen (2006) conducted a small study with 34 participating students at a business faculty, focusing on the participants’ experiences of group work. In the study different aspects of students’ positive experiences of group work were identified. For example, it was found to be necessary that all group members take part and make an effort to take part in the group work, clear goals are set for the work, role differentiation exists among members, the task has some level of relevance, and there is clear leadership. Even though Hansen’s (2006) study was conducted in higher education, these findings may be relevant in other levels in educational systems.

To gain more knowledge and understand about the essence behind high-quality group work, Hammar Chiriac and Einarsson (2007) turned their focus toward students’ experiences and conceptions of group work in higher education. A primary aim was to give university students a voice in the matter by elucidating their students’ points of view and how the students assess working in groups. Do the students’ appreciate group projects or do they find it boring and even as a waste of time? Would some students prefer to work individually, or even in “the other group?” The study was a part of a larger research project on group work in education and only a small part of the data corpus was analyzed. Different critical aspects were identified as important incitements for whether the group work turned out to be a success or a failure. The students’ positive, as well as negative, experiences of group work include both task-related (e.g., learning, group composition, participants’ contribution, time) and socio-emotional (e.g., affiliation, conflict, group climate) aspects of group work. The students described their own group, as well as other groups, in a realistic way and did not believe that the grass was greener in the other group. The same data corpus is used in this article (see under Section The Previous Analysis). According to Underwood (2003) and Peterson and Miller (2004), the students’ enthusiasm for group work is affected by type of task, as well as the group’s members. One problem that recurred frequently concerned students who did not contribute to the group work, also known as so-called free-riders (Hammar Chiriac and Hempel, 2013). Students are, in general, reluctant to punish free-riders and antipathy toward working in groups is often associated with a previous experience of having free-riders in the group (Peterson and Miller, 2004). To accomplish a favorable attitude toward group work, the advantages of collaborative activities as a means for learning must be elucidated. Furthermore, students must be granted a guarantee that free-riders will not bring the group in an unfavorable light. The free-riders, on the other hand, must be encouraged to participate in the common project.

Hammar Chiriac and Granström (2012) were also interested in students’ experiences and conceptions of high-quality and low-quality group work in school and how students aged 13–16 describe good and bad group work? Hammar Chiriac and Granström (2012) show that the students seem to have a clear conception of what constitutes group work and what does not. According to the students, genuine group work is characterized by collaboration on an assignment given by the teacher. They describe group work as working together with their classmates on a common task. The students are also fully aware that successful group work calls for members with appropriate skills that are focused on the task and for all members take part in the common work. Furthermore, the results disclose what students consider being important requisites for successful versus more futile group work. The students’ inside knowledge about classroom activities ended up in a taxonomy of crucial conditions for high-quality group work. The six conditions were: (a) organization of group work conditions, (b) mode of working in groups, (c) tasks given in group work, (d) reporting group work, (e) assessment of group work, and (f) the role of the teacher in group work. The most essential condition for the students seemed to be group composition and the participants’ responsibilities and contributions. According to the students, a well-organized group consists of approximately three members, which allows the group to not be too heterogeneous. Members should be allotted a reasonable amount of time and be provided with an environment that is not too noisy. Hence, all six aspects are related to the role of the teacher’s leadership since the first five points concern the framework and prerequisites created by the teacher.

Näslund (2013) summarized students’ and researchers’ joint knowledge based on experience and research on in the context of shared perspective for group work. As a result, Näslund noticed a joint apprehension concerning what constitutes “an ideal group work.” Näslund (2013) highlighted the fact that both students and researchers emphasized for ideal group work to occur, the following conditions were important to have: (a) the group work is carried out in supportive context, (b) cooperation occurs, (c) the group work is well-structured, (d) students come prepared and act as working members during the meetings, and (e) group members show respect for each other.

From this brief exposition of a selection of research focusing on students’ views on group work, it is obvious that more systematic studies or documentations on students’ conceptions and experiences of group work within higher education are relevant and desired. The present study, which is a reanalysis of a corpus of data addressing the students’ perspective of group, is a step in that direction.

AIM OF THE STUDY

The overarching knowledge interest of this study is to enhance the body of knowledge regarding group work in higher education. The aim of this article is to add knowledge and understanding of what the essence behind successful group work in higher education is by focusing on the students’ experiences and conceptions of group work and learning in groups, an almost non-existing aspect of research on group work until the beginning of the 21st century. A primary aim is to give university students a voice in the matter by elucidating the students’ positive and negative points of view and how the students assess learning when working in groups. Furthermore, the students’ explanations of why some group work results in positive experiences and learning, while in other cases, the result is the opposite, are of interest.

MATERIALS AND METHODS

To capture university students’ experiences and conceptions of group work, an inductive qualitative approach, which emphasizes content and meaning rather than quantification, was used (Breakwell et al., 2006; Bryman, 2012). The empirical data were collected through a study-specific, semi-structured questionnaire and a qualitative content analysis was performed (Mayring, 2000; Graneheim and Lundman, 2003; Elo and Kyngäs, 2007).

PARTICIPANTS

All participating students attended traditional university programs where group work was a central and frequently used pedagogical method in the educational design. In addition, the participants’ programs allowed the students to be allocated to the same groups for a longer period of time, in some cases during a whole semester. University programs using specific pedagogical approaches, such as problem-based learning or case method, were not included in this study.

The participants consisted of a total of 210 students, 172 female and 38 male, from two universities in two different cities (approximately division: 75 and 25%). The students came from six different populations in four university programs: (a) The Psychologist Program/Master of Science in Psychology, (b) The Human Resource Management and Work Sciences Program, (c) Social Work Program, and (d) The Bachelor’s Programs in Biology. The informants were studying in their first through eighth terms, but the majority had previous experiences from working in other group settings. Only 2% of the students had just started their first term when the study was conducted, while the vast majority (96%) was participating in university studies in their second to sixth semester.

The teacher most frequently arranged the group composition and only a few students stated that they have had any influence on the group formation. There were, with a few exceptions, between 6 and 10 groups in each of the programs included in this study. The groups consisted of between four to eight members and the differences in sizes were almost proportionally distributed among the research group. The groups were foremost heterogeneous concerning gender, but irrespective of group size, there seems to have been a bias toward more women than men in most of the groups. When there was an underrepresented sex in the group, the minority mostly included two students of the same gender. More than 50% of the students answered that in this particularly group, they worked solely with new group members, i.e., students they had not worked with in previous group work during the program.

MATERIALS

To collect data about students’ experiences and conceptions of group work, a study-specific, semi-structured questionnaire was constructed. The questionnaire approached the students’ experiences regarding the specific group work they were working in at the time of the data collection (spring 2006), not their experiences of group work in general. The questionnaire contained a total of 18 questions, including both multiple choice and open-ended questions. The multiple choice questions concerned background variables and information about the present group. The seven open-ended questions were designed to gather data about the students’ experiences and perceptions of group work in higher education. The questionnaires were distributed to the different populations of students (some populations studied at the same program) at two universities in Sweden. During the time the questionnaires were completed, the researcher or an assistant was present to answer possible questions. In all, 210 students answered the questionnaire.

ANALYSIS

The previous analysis

As described above (Section Previous Research of Students’ Experiences) a previous analysis based on the same data corpus revealed that most of the students included in the study found group work to be an enjoyable and stimulating working method (Hammar Chiriac and Einarsson, 2007). The data were analyzed using a qualitative content analysis based on three different research questions. There were two main criticisms of the previous study presented from other researchers. The criticism conveyed applied mostly to the question of whether we could assemble these groups into a joint research group and second to the fact that the results were mostly descriptive. To counter this criticism and to elaborate on the analysis, a further analysis was conducted.

The present analysis

The present analysis (or reanalysis) was conducted by using an inductive qualitative content analysis based on three open-ended research questions:

(1) In what ways does group work contribute to your learning?

(2) What positive experiences have you had while working in your present group?

(3) What negative experiences have you had while working in your present group?

Each question corresponds to one aspect of the research’s objective, but together, they might support and enrich each other and unravel new information based on the students’ experiences and conceptions of group work. Research question 1, listed above, was not included in the first analysis and is being investigated for the first time in this study, while the other two questions are being reanalyzed. An inductive, qualitative content analysis is applicable when the aim of the research is a description of the meaning or of a phenomenon in conceptual form (Mayring, 2000; Graneheim and Lundman, 2003; Elo and Kyngäs, 2007).

The analysis was carried out over several steps, following the basic principles of an inductive, qualitative content analysis (Mayring, 2000; Graneheim and Lundman, 2003; Elo and Kyngäs, 2007). The steps included three phases: preparation, organizing, and reporting (Elo and Kyngäs, 2007). Each question was treated as a unit of analysis and was thus analyzed separately. In the preparation phase, the researcher tried to make sense of the data by becoming familiar with the data corpus. In the current study, this included transcription and thorough reading of the answers. An open coding system composed of marginal notes and headings began the second phase, which included organizing the data. This second phase, in turn, included open coding, creating categories, and abstraction. The notes and the headings from the open coding were transferred to coding sheets and then grouped into categories. Categories were formed through the interpretation of the codes that described the same meaning or phenomenon. Finally, an abstraction process began, where a general description of the grouped categories formed an abstraction (see Table ​1). An abstraction was denominated using the content-characteristic words for this paper: learning, study-social function, and organization. The third phase, reporting, addressed the presentation of the process of analysis and the results.

Table 1

Examples from the organization phase of the coding process.

The final aim of this study is to present the phenomenon studied in a model or conceptual map of the categories (Elo and Kyngäs, 2007). In following these procedures, we aim to expand our understanding of the existing work and to counter the second part of the criticisms, which included criticisms stating that the results were mostly descriptive in nature. To counter the criticisms regarding the question of whether we could assemble these groups into a joint research group, the qualitative abstraction that emerged from the qualitative content analysis was compared to background information by using SPSS. Three background variables were used: gender, cities, and programs.

ETHICS AND QUALITY

The ethical principles provided by the British Psychology Society have formed a guideline [British Psychology Society (BPS), 2006] for the present study. The ethical principles, which emphasize the concern for participants’ interest, have been applied throughout the study [American Psychological Association (APA), 2002; British Psychology Society (BPS), 2004; Barett, 2007]. To facilitate trustworthiness, a thorough description of the analysis process has been presented (Graneheim and Lundman, 2003; Elo and Kyngäs, 2007). Translated citations are also included to increase trustworthiness.

RESULTS

As described above, the analysis resulted in three abstraction emerging: learning, study-social function, and organization. Each abstraction includes both a positive variant (i.e., facilitating learning, study-social function, and/or organization) as well as a negative alternative (i.e., hampering learning, study-social function, and/or organization). The results will be presented in three different sections, with each section corresponding to one abstraction. However, we would like to call attention to the fact that one fifth (20%, including missing value 8%) of the students included in this study did not perceive and/or mention any negative experiences at all in their present group. From a general point of view, there is no difference with respect to gender or city regarding the distribution of positive and negative experiences concerning the abstractions, neither concerning different programs nor the distribution of negative experiences (all p > 0.05). In contrast, there is a difference between the various programs and the distribution of positive experiences (χ2 = 14.474; df: 6; p < 0.025). The students from the social work program display a higher amount of positive experiences in connection with a study-social function and organizing in comparison with the other programs.

LEARNING

The majority of the students (97%) responded that working in group somehow facilitated learning, academic knowledge, collaborative abilities or both. They learned more or different things when working in groups than they would have if working alone. By discussing and questioning each other’s points of view and listening to their fellow students’ contributions, thus obtaining different perspectives, the participants experienced an enhanced academic learning, compared to working alone. “I learn much more by working in groups than working individually. I obtain more through interaction with the other group members.” Academic knowledge is not the only type of knowledge learned through group work. In addition to academic knowledge, students also gain advanced knowledge about how groups work, how the students function as individual members of groups and how other members behave and work in groups. Some of the respondents also argued that group work in group courses strengthen the combination between empirical and theoretical learning, thus learning about groups by working in groups. “Through practical knowledge demonstrate several of the phenomena we read about in theory (group psychology and sociology).”

The results show no difference when considering either gender or city. However, when comparing the four programs included in the study and the types of learning, a difference occurs (χ2 = 14.474; df: 6; p < 0.025). A division into two parts seems to generate the difference. On the one hand, the students from the Bachelor’s Program in Biology and the students from the Human Resource Management and Work Sciences Program emphasize academic knowledge. On the other hand, students from the Psychologist Program/Master of Science in Psychology and Social Work Program more often mentioned learning collaborative abilities single handed, as well as a combination of academic knowledge and group learning.

Even though the participants did not expressly report that group work hampered learning, they often mentioned that they perceived group work as being ineffective due to loss of focus and the presence of conflicts, thereby hampering conceivable learning. One respondent stated, “that you sometimes are out of focus in the discussion and get side-tracked instead of considering the task.” Another offered the following perspective: “Occasionally, it is too little task related and feels unnecessary sometimes. Individual work is, in certain situations, preferable.” Group work might be perceived as ineffective and time consuming considering long working periods with tedious discussions. One participant stated, “The time aspect, everything is time consuming.” The absence or presence of conflicts in the group affects students’ experiences, and conflicts not handled may influence learning in a negative way. The students perceived that it was difficult to come to an agreement and experience those conflicts and the need to compromise hampered individual learning. Accordingly, the absence of conflicts seemed to be an important incitement for learning. However, fear of conflicts can lead to reduced learning and cause negative experiences, but to a considerably lesser extent than does the presence of actual conflicts. “A great fear of conflicts sometimes raises an oppressive atmosphere.” “Fear of conflicts leads to much not made known.”

A STUDY-SOCIAL FUNCTION

Group work also has an important study-social function according to the students. They describe their membership in groups as an important aspect of affiliation. In general, the total number of students at a program is approximately 60–80 or more. In contexts with a large population of students, the smaller group gives the participants an opportunity to feel affiliated with the group and to each other. “Feels safe to have a certain group to prepare oneself together with before, for instance, an upcoming seminar.” The group gives the individual student a platform of belonging, which might serve as an important arena for learning (facilitate) and finding friends to spend leisure time with. Many of the participants also reported feeling a positive atmosphere in the group, which is important for the satisfaction of being in the group together with the fellow students.

To be a member of a group may also serve as a function of relief, both academically and socially, for the individual student. The participants reported that many of the tasks assigned by the university teachers are difficult to handle on their own. “The others explain to me. We help one another.” However, the students reported that they helped and supported each other, even if the task did not demand cooperation. “As a student, you get more active. You help one another to extract the groups’ common knowledge. Forward info if somebody is missing.” Being a member of a group also affects students’ motivation to study. They prepare themselves by reading texts and other material before the next group session. Group work may also have positive effects on achievement. Students’ total amount of time and effort on their work may also increase. Through group work, the participants also get confirmation of who they are and what their capacities are.

Being a member of a group also has its downside, which often has to do with the group climate and/or group processes, both of which have multiple and complex features. Many students reported that both the group climate and group processes might be the source of negative conceptions of the group and hamper learning. “Process losses.” The respondents described negative conceptions based on the feeling of not having enough time to get to know each other in the group or being in situations where no cooperation occurred. Other students referred to the fact that the group’s life is too long, which may lead to group members not only wearing each other out, but also having a negative effect on each other’s mood. “Influenced by each other’s mood.” Examples of negative experiences are process losses in general, including insufficient communication, unclear roles, and problems with one group member. As mentioned above, the students from the Social Work Program display a higher number of positive experiences in connection with a study-social function and organizing in comparison with students from the other programs.

ORGANIZATION

Organization concerns the structure of group work and includes different aspects, all describing group work from different angles. The aspects are relevant no matter how the participants perceive the group work, whether as positive or negative. Unlike the other two abstractions (learning and study-social function), organization includes the same aspects no matter what the experiences are, namely group composition, group structure, way of working and contributions.

Whether the group is composed in a homogeneous or heterogeneous way seems to be experienced in both a positive and negative sense. A well-thought-out group composition, including both group size and mix of members, is essential. A just large-enough group for the task, consisting of a population of members that is not too heterogeneous, facilitates a joyful experience and learning. A homogeneous mix of members might be perceived as positive, as the students feel that they have similar life situations, opinions, and skills, thereby causing positive conditions for collaboration within the group. Conversely, in a group with a heterogeneous mix, different members contribute with different knowledge and/or prior experiences, which can be used in the group for collective and collaborative learning. “Good group composition, distribution of age groups that leads to fruitful discussions.”

An additional facilitating prerequisite is that the group develops adequate ways of working together, which includes a well-organized group structure. Well-working groups are characterized as having developed adequate ways of working together, while groups that work less well together lack a developed way of cooperation. “Well-organized working group with clear and distinct rules and structure.” Preparation and attendance for group work are aspects mentioned as facilitating (and hampering) incitements. Group work in educational settings sometimes entails that you, as a student, are forced to read and learn within a certain period of time that is beyond your control. Some participants find the pressure positive, hence “increase the pressure to read chapters in time.” The members’ contribution to the group is also a central factor for the students’ apprehension of how the group works. This is, in short, about how much each member ought to contribute to the group and to the work. Groups considered to be well-working are ones where all members contribute to the group’s work, but the content of the contribution may vary according to the single member’s qualifications. “We work well together (most of us). Everybody participates in different ways and seems committed.” “Good, everybody participates the same amount. We complement each other well.”

The same prerequisites can lead to the reverse result, i.e., hampering learning and stirring up negative experiences. If the group members are too identical (a homogeneous group composition), it might lead to a lack of opinions, which several participants perceived as being negative. “That we do not get a male perspective about the subject. We are all girls, at the age of 20, which also means that we have pretty much the same experiences that may be seen as both positive and negative. The negative is the lack of opinion.” If the group is considered to be too small, students seems to find it troublesome, as the relationships are few, but there are also few people who are available to handle the workload allotted to the group. Nevertheless, a group that is too large could also lead to negative experiences. “It is far too large a group.”

A lack of group structure might lead to a lower degree of satisfaction with the group’s way of working. A commonly expressed point of view seen in the students’ answers involved the occurrences of when all members did not attend the meetings (absence). In these cases, it was also viewed that the work in the group often was characterized as unstructured. “Sometimes a bit unclear structures, some students have difficulties with coming in time.” Not attending or coming unprepared or badly prepared to the group work is other aspect that is commented on. “Low degree of fellowship, punctuality is a problem, an insecure group.” Some students find it frustrating to prepare for a certain time decided that is beyond their control. “A necessity to read certain chapters within a specific period of time is never stimulating.”

One characteristic of groups that are not working well is that contribution varies among the members. In group work, students with different levels of ambition are assembled, which may result in different levels of interest and commitment, as well as differences in the willingness to take on responsibilities or part of the workload of the group’s work. Some members are active and do much of the work, while others barely contribute at all. “Some don’t do anything while others pull the heaviest burden. Two out of three prepare before the meeting, the rest think that they are able to read during the group work and do not supply the group with anything else other than delays and frustration.” A common answer seen in the questionnaires that concerns negative experiences of group work as they relate to contribution is: “Everybody does not contribute just as much.” or “There is always someone who just glides along and doesn’t take part.”

SUMMARY OF THE RESULTS

The results are summarized in a model illustrating the relationship between abstractions (i.e., learning, study-social function, and organization) and result (i.e., enhanced or reduced learning), as well as positive or negative experiences (see Figure ​1).

FIGURE 1

A model illustrating the relationship between abstractions and result.

The figure shows that all three abstractions may facilitate or hamper learning as well as the experiences of group work. To piece together, the difficult and extensive jigsaw puzzle concerning why some group work result in positive experiences and learning, while in other cases the result is the reverse is still not solved. In this article, we propose that the prerequisites learning, study-social function, and organization influence learning and experiences of working in group, thus, providing additional pieces of information to the jigsaw puzzle (Figure ​2).

FIGURE 2

Pieces of jigsaw puzzle influence learning and experiences.

DISCUSSION

The current study focuses on university students’ experiences and conceptions of group work and learning in groups. A primary aim was to give university students a voice in the matter by elucidating the students’ positive and negative points of view, as well as how the students’ assess learning when working in groups. The analysis resulted in the emergence of three different abstractions: learning, study-social function, and organizations. Each abstraction also included a positive and a negative variant. In other words, all three abstractions either facilitated or hampered university students’ learning, as well as their experiences of group work.

LEARNING IN GROUP WORK

The result shows that the majority of the students (97%) experience that working in group facilitated learning, either academic knowledge, collaborative abilities or both, accordingly confirming previous research (Johnson and Johnson, 2004; Baines et al., 2007; Gillies and Boyle, 2010, 2011). According to the students, they learn more or different things when working in groups compared with working individually. Academic knowledge was not the only type of knowledge learned through group work. In addition to academic knowledge, students also gained advanced knowledge about how groups work, how the students function as individual members of groups and how other members behave and work in groups. Some of the respondents also argued that group work might strengthen the combination between empirical and theoretical learning, thus the students were learning about groups by working in groups. This implies that group work, from a learning perspective, serves several functions for the students (Kutnick and Beredondini, 2009; Gillies and Boyle, 2010, 2011; Hammar Chiriac, 2011a,b). Group work also seems to have an important study-social function for the university students, hence confirming that group work serves more functions than just being a pedagogical mode.

Affiliation, fellowship, and welfare seem to be highly important, and may even be essential prerequisites for learning. Accordingly, group work functions as both as an objective (i.e., learning collaborative abilities), and as the means (i.e., a base for academic achievement), or both, for the students (Gillies, 2003a,b; Johnson and Johnson, 2004; Baines et al., 2007). Moreover, the students from the Bachelor’s Program in Biology and the students from the Program for Human Resources seem to use group work more as means for obtaining academic knowledge. In contrast, students from the Psychologist Program/Master of Science in Psychology and Social Work Program more often mentioned learning collaborative abilities alone, as well as a combination of academic knowledge and group learning, thus using group work as an objective, as a means, or as a combination of both. One interpretation might be that the type of task assigned to the students differs in various programs. This can be valid both concerning the purpose of group work (group work as objective or as the means), but also arrangement (working in a group or as a group; Underwood, 2003; Hammar Chiriac and Granström, 2012). Another possible explanation might be that the main emphasis in the Bachelor’s Program in Biology and the Program for Human Resources is on product and academic knowledge, while in the Psychologist Program/Master of Science in Psychology and Social Work Program, the process is more articulated and demanded. However, this is only speculation and further research is needed.

Even though the participants did not explicitly state that group work hampered learning, they mentioned that they perceived group work to be ineffective due to the loss of focus and/or the presence of conflicts with other group members, thereby hampering conceivable learning. This may also be an effect of the purpose or arrangement of the group work (Cantwell and Andrews, 2002; Underwood, 2003; Peterson and Miller, 2004; Hansen, 2006; Hammar Chiriac and Granström, 2012; Hammar Chiriac and Hempel, 2013).

EXPERIENCES OF GROUP WORK

The results revealed that several aspects of group work are important incentives for learning. In addition, this study revealed students’ experiences of group work (i.e., facilitating or hampering positive/negative experiences), which is in line with the previous studies on students’ experiences of working in groups (Cantwell and Andrews, 2002; Underwood, 2003; Peterson and Miller, 2004; Hansen, 2006; Hammar Chiriac and Granström, 2012; Hammar Chiriac and Hempel, 2013). Group composition, group structure, ways of working, and participants’ contributions are aspects put forward by the university students as either facilitating or hampering the positive experience of group work (Underwood, 2003; Peterson and Miller, 2004; Hansen, 2006; Hammar Chiriac and Granström, 2012; Hammar Chiriac and Hempel, 2013).

Several of the aspects bear reference to whether the group members work in a group or as a group (Underwood, 2003; Hammar Chiriac and Granström, 2012). Working as a group is characterized by common effort, utilization of the group’s competence, and includes problem solving and reflection. All group members are involved in and working on a common task to produce a joint outcome (Bennet and Dunne, 1992; Galton and Williamson, 1992; Webb and Palincsar, 1996; Hammar Chiriac, 2011a,b). According to the results, not all groups are working as a group but rather working in a group, which, according to Granström (2006), is common in an educational setting.

Due to problems with group composition, members’ contributions, and group structure, including rules and ways of cooperation, some students end up with negative experiences of group work. Additionally, the university students allude to the fact that a well-functioning supportive study-social context is an essential prerequisite not only for positive experiences of group work, but also for learning (Hammar Chiriac and Hempel, 2013). Both working in a group and working as group might be useful in different parts of the group work (Hammar Chiriac, 2008) and cause learning. Hence working in a group causes cooperative learning based on social facilitation (Zajonc, 1980; Baron, 1986; Uziel, 2007) while working as group causes learning benefits through collaboration with other group members. Although both approaches might cause positive or negative experiences, a conceivable interpretation is that working as a group has a greater potential to enhance positive experiences. The findings suggest a need for further research to fully understand why some group work causes positive experiences and other instances of group work cause negative experiences.

The findings in the current study develop the findings from Hammar Chiriac and Einarsson (2007). First, it shows that it is possible to assemble all groups in to a joint research group (see below). Second, a thorough reanalysis, using an inductive qualitative content analysis, resulted in the emergence of three different abstractions: learning, study-social function, and organizations as either facilitating or hampering learning, and experiences.

METHODOLOGICAL CONSIDERATIONS

There are some limitations in the current study and most of them have to do with the construction of the study-specific, semi-structured questionnaire. First, the questions do not discriminate between (a) the type of group work, (b) the purpose with the group work, (c) the structure of the group work (i.e., extent and/or time); or (d) ways of working in the group (i.e., cooperation or collaboration). Second, the design of the questionnaire does not facilitate comparison between the populations included in the group. The questionnaire treated group work as one activity and did not acknowledge that group work can serve different functions and include various activities (Hammar Chiriac, 2008). This simplification of the phenomena group work causes criticism concerning whether or not it is possible to assemble these populations into a joint research group. An elaborated description of the analysis process and the comparison to three background variables has been used to counter this criticism. The thin results from the comparison, indicate that based on the question used in the study-specific questionnaire, it is possible to assemble the results into a corpus of joint results.

CONCLUSION/CONCLUDING REMARKS

The results indicate that most of the students’ experienced that group work facilitated learning, especially concerning academic knowledge. Three important prerequisites (learning, study-social function, and organization) for group work that serve as an effective pedagogy and as an incentive for learning were identified and discussed. All three abstractions either facilitated or hampered university students’ learning, as well as their experiences of group work. By listening to the university students’ voices and elucidating their experiences and conceptions, we have been able to add new knowledge and understanding of what the essence is behind successful group work in higher education. Furthermore, the students’ explanations of why some group work results in positive experiences and learning, while in other cases, the result is the opposite, can be of use for further development of group work as a pedagogical practice.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The author acknowledges Ph.D. Faculty Program Director, Charlotta Einarsson, for her contribution to the design of this study and contribution to early stages of the data analysis and manuscript.

REFERENCES

  • American Psychological Association (APA). (2002). The Ethical Principles of Psychologists and Code of Conduct. Available at: http://www.apa.org/ethics/code2002.html
  • Baines E., Blatchford P., Chowne A. (2007). Improving the effectiveness of collaborative group work in primary schools: effects on science attainment.Br. Educ. Res. J.33 663–680 10.1080/01411920701582231 [Cross Ref]
  • Barett M. (2007). “Practical and ethical issues in planning research,” inResearch Methods in Psychology eds Breakell G., Hammond S., Fife-Schaw C., Smith J. A., editors. (London: Sage Publications) 24–48
  • Baron R. S. (1986). Distraction-conflict theory: progress and problems.Adv. Exp. Soc. Psychol.19 1–40 10.1016/S0065-2601(08)60211-7 [Cross Ref]
  • Bennet N., Dunne E. (1992). Managing Classroom Groups. Hemel Hempstead: Simon & Schuster Education
  • Blatchford P., Kutnick P., Baines E., Galton M. (2003). Toward a social pedagogy of classroom group work.Int. J. Educ. Res.39 153–172 10.1016/S0883-0355(03)00078-8 [Cross Ref]
  • Breakwell G. M, Hammond F., Fife-Schaw C., Smith J. A. (eds) (2006). Research Methods in Psychology. London: Sage Publications
  • British Psychology Society (BPS). (2004). Code of Conduct, Ethical Principles, and Guidelines. Available at: http://www.bps.org.uk/document-download-area/document-download.cfm?file_uuid=6D0645CC-7E96-C67F-D75E2648E5580115&ext=pdf
  • British Psychology Society (BPS). (2006). Code of Ethics and Conduct. Available at: http://www.bps.org.uk/the-society/code-of-conduct/code-of-conduct_home.cfm
  • Bryman A. (2012). Social Research Methods. Oxford: University Press
  • Cantwell R. H., Andrews B. (2002). Cognitive and psychological factors underlying secondary school students’ feeling towards group work.Educ. Psychol.22 75–91 10.1080/01443410120101260 [Cross Ref]
  • Elo S, Kyngäs H. (2007). The qualitative content analysis process.J. Adv. Nurs.62 107–115 10.1111/j.1365-2648.2007.04569.x [PubMed][Cross Ref]
  • Galton M., Williamson J. (1992). Group Work in the Primary Classroom. London: Routledge
  • Galton M. J., Hargreaves L., Pell T. (2009). Group work and whole-class teaching with 11–14-years-old compared.Cambridge J. Educ.39 119–147 10.1080/03057640802701994 [Cross Ref]
  • Gillies R. M. (2003a). The behaviours, interactions, and perceptions of junior high school students during small-group learning.J. Educ. Psychol.95 137–147 10.1037/0022-0663.95.1.137 [Cross Ref]
  • Gillies R. M. (2003b). Structuring cooperative group work in classrooms.Int. J. Educ. Res.39 35–49 10.1016/S0883-0355(03)00072-7 [Cross Ref]
  • Gillies R. M., Boyle M. (2010). Teachers’ reflections on cooperative learning: Issues of implementation.Teach. Teach. Educ.26 933–940 10.1016/j.tate.2009.10.034 [Cross Ref]
  • Gillies R. M., Boyle M. (2011). Teachers’ reflections on cooperative learning (CL): a two-year follow-up.Teach. Educ.1 63–78 10.1080/10476210.2010.538045 [Cross Ref]
  • Graneheim U. H., Lundman B. (2003). Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness.Nurse Educ. Today24 105–112 10.1016/j.nedt.2003.10.001 [PubMed][Cross Ref]
  • Granström K. (2006). “Group phenomena and classroom management in Sweden,” inHandbook of Classroom Management: Research, Practice, and Contemporary Issues eds Evertson C. M., Weinstein C. S., editors. (Mahwah, NJ: Lawrence Erlbaum) 1141–1160
  • Hammar Chiriac E. (2008). A scheme for understanding group processes in problem-based learning.High. Educ.55 505–518 10.1007/s10734-007-9071-7 [Cross Ref]
  • Hammar Chiriac E. (2010). “Group work is not one, but a great many processes – understanding group work dynamics,” inGroup Theory: Classes, Representation and Connections, and Applications ed. Danellis C. W., editor. (New York: Nova Science Publishers, Inc.) 153–166
  • Hammar Chiriac E. (2011a). Research on Group Work in Education. New York: Nova Science Publishers, Inc
  • Hammar Chiriac E. (2011b). “Research on group work in education,” inEmerging Issues in Compulsory Education [Progress in Education. Volume 20] ed Nata R., editor. (New York: Nova Science Publishers, Inc.) 25–44
  • Hammar Chiriac E., Einarsson C. (2007). “Is the grass greener in the other group? Students’ experiences of group-work” [“är gräset grönare i den andra gruppen? Studenters erfarenheter av grupparbete”] [Published in Swedish], in Interaction on the Edge 2.Proceedings from the 5th GRASP Conference ed. Näslund J., editor. (Linköping: Linköping University)
  • Hammar Chiriac E, Granström K. (2012). Teachers’ leadership and students’ experience of group work.Teach. Teach. Theor. Pract.3 345–363 10.1080/13540602.2012.629842 [Cross Ref]
  • Hammar Chiriac E., Hempel A. (2013), Handbook for Group Work [Published in Swedish: Handbok för grupparbete – att skapa fungerande grupper i undervisningen]. Lund: Studentlitteratur
  • Hansen R. S. (2006). Benefits and problems with student teams: suggestions for improving team projects.J. Educ. Bus.82 11–19 10.3200/JOEB.82.1.11-19 [Cross Ref]
  • Johnson D. W., Johnson R. T. (1975). Learning Together and Alone. Cooperative, Competitive and Individualistic Learning (Englewood Cliffs, NJ: Prentice Hall)
  • Johnson D. W., Johnson R. T. (2004). Assessing Students in Groups: Promoting Group Responsibility and Individual Accountability. Thousand Oaks: Sage
  • Kutnick P., Beredondini L. (2009). Can the enhancement of group work in classrooms provide a basis for effective communication in support of school-based cognitive achievement in classrooms of young learners?Cambridge J. Educ.39 71–94 10.1080/03057640902836880 [Cross Ref]
  • Lou Y., Abrami P. C., Spence J. C., Poulsen C., Chambers B, d’Apllonia S. (1996). Within-class grouping: a meta analysis.Rev. Educ. Res.66 423–458 10.3102/00346543066004423 [Cross Ref]
  • Mayring P. (2000). Qualitative Content Analysis. Forum: Qualitative Social Research 1:2. Available at: http://qualitative-research.net/fqs/fqs-e/2-00inhalt-e.htm_140309
  • Näslund J. (2013). “Pupils’ and students’ view on group work” [Published in Swedish: Elevers och studenters syn på grupparbete] inHandbook for Group Work [Published in Swedish: Handbok för grupparbete – att skapa fungerande grupper i undervisningen] eds Hammar Chiriac E., Hempel A., editors. (Lund: Studentlitteratur) 233–242
  • Peterson S, Miller J. A. (2004). Quality of college students’ experiences during cooperative learning.Soc. Psychol. Learn.7 161–183
  • Underwood J. D. M. (2003). Student attitudes towards socially acceptable and unacceptable group working practices.Br. J. Psychol.94 319–337 10.1348/000712603767876253 [PubMed][Cross Ref]
  • Uziel L. (2007). Individual differences in the social facilitation effect: a review and meta-analysis.J. Res. Person.41 579–601 10.1016/j.jrp.2006.06.008 [Cross Ref]
  • Webb N. M., Palincsar A. S. (1996). “Group processes in the classroom,” inHandbook of Educational Psychology eds Berliner D. C., Calfee R. C., editors. (New York: Macmillan) 841–873
  • Zajonc R. B. (1980). “Compresence,” inPsychology of Group Influence ed. Paulus P. B., editor. (New York, NY: Lawrence Erlbaum) 35–60

Abstract

Socioeconomic, racial/ethnic, and gender inequalities in academic achievement have been widely reported in the US, but how these three axes of inequality intersect to determine academic and non-academic outcomes among school-aged children is not well understood. Using data from the US Early Childhood Longitudinal Study—Kindergarten (ECLS-K; N = 10,115), we apply an intersectionality approach to examine inequalities across eighth-grade outcomes at the intersection of six racial/ethnic and gender groups (Latino girls and boys, Black girls and boys, and White girls and boys) and four classes of socioeconomic advantage/disadvantage. Results of mixture models show large inequalities in socioemotional outcomes (internalizing behavior, locus of control, and self-concept) across classes of advantage/disadvantage. Within classes of advantage/disadvantage, racial/ethnic and gender inequalities are predominantly found in the most advantaged class, where Black boys and girls, and Latina girls, underperform White boys in academic assessments, but not in socioemotional outcomes. In these latter outcomes, Black boys and girls perform better than White boys. Latino boys show small differences as compared to White boys, mainly in science assessments. The contrasting outcomes between racial/ethnic and gender minorities in self-assessment and socioemotional outcomes, as compared to standardized assessments, highlight the detrimental effect that intersecting racial/ethnic and gender discrimination have in patterning academic outcomes that predict success in adult life. Interventions to eliminate achievement gaps cannot fully succeed as long as social stratification caused by gender and racial discrimination is not addressed.

Citation: Bécares L, Priest N (2015) Understanding the Influence of Race/Ethnicity, Gender, and Class on Inequalities in Academic and Non-Academic Outcomes among Eighth-Grade Students: Findings from an Intersectionality Approach. PLoS ONE 10(10): e0141363. https://doi.org/10.1371/journal.pone.0141363

Editor: Emmanuel Manalo, Kyoto University, JAPAN

Received: June 10, 2015; Accepted: October 6, 2015; Published: October 27, 2015

Copyright: © 2015 Bécares, Priest. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Data Availability: All ECLS-K Kindergarten-Eighth Grade Public-use File are available from the National Center for Education Statistics website (https://nces.ed.gov/ecls/dataproducts.asp#K-8).

Funding: This work was funded by an ESRC grant (ES/K001582/1) and a Hallsworth Research Fellowship to LB.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The US racial/ethnic academic achievement gap is a well-documented social inequality [1]. National assessments for science, mathematics, and reading show that White students score higher on average than all other racial/ethnic groups, particularly when compared to Black and Hispanic students [2, 3]. Explanations for these gaps tend to focus on the influence of socioeconomic resources, neighborhood and school characteristics, and family composition in patterning socioeconomic inequalities, and on the racialized nature of socioeconomic inequalities as key drivers of racial/ethnic academic achievement gaps [4–10]. Substantial evidence documents that indicators of socioeconomic status, such as free or reduced-price school lunch, are highly predictive of academic outcomes [2, 3]. However, the relative contribution of family, neighborhood and school level socioeconomic inequalities to racial/ethnic academic inequalities continues to be debated, with evidence suggesting none of these factors fully explain racial/ethnic academic achievement gaps, particularly as students move through elementary school [11]. Attitudinal outcomes have been proposed by some as one explanatory factor for racial/ethnic inequalities in academic achievement [12], but differences in educational attitudes and aspirations across groups do not fully reflect inequalities in academic assessment. For example, while students of poorer socioeconomic status have lower educational aspirations than more advantaged students [13], racial/ethnic minority students report higher educational aspirations than White students, particularly after accounting for socioeconomic characteristics [14–16]. Similarly, while socio-emotional development is considered highly predictive of academic achievement in school students, some racial/ethnic minority children report better socio-emotional outcomes than their White peers on some indicators, although findings are inconsistent [17–22].

In addition to inequalities in academic achievement, racial/ethnic and socioeconomic inequalities also exist across measures of socio-emotional development [23–26]. And as with academic achievement, although socioeconomic factors are highly predictive of socio-emotional outcomes, they do not completely explain racial/ethnic inequalities in school-related outcomes not focused on standardized assessments [11].

Further complexity in understanding how academic and non-academic outcomes are patterned by socioeconomic factors, and how this contributes to racial/ethnic inequalities, is added by the multi-dimensional nature of socioeconomic status. Socioeconomic status is widely recognized as comprising diverse factors that operate across different levels (e.g. individual, household, neighborhood), and influence outcomes through different causal pathways [27]. The lack of interchangeability between measures of socioeconomic status within and between levels (e.g. income, education, occupation, wealth, neighborhood socioeconomic characteristics, or past socioeconomic circumstances) is also well established, as is the non-equivalence of measures between racial/ethnic groups [27]. For example, large inequalities have been reported across racial/ethnic groups within the same educational level, and inequalities in wealth have been shown across racial/ethnic that have similar income. It is therefore imperative that studies consider these multiple dimensions of socioeconomic status so that critical social gradients across the entire socioeconomic spectrum are not missed [27], and racial/ethnic inequalities within levels of socioeconomic status are adequately documented. It is also important that differences in school outcomes are considered across levels of socioeconomic status within and between racial/ethnic groups, so that the influence of specific socioeconomic factors on outcomes within specific racial/ethnic groups can be studied [28]. However, while these analytic approaches have been identified as research priorities in order to enhance our understanding of the complex ways in which socioeconomic status and race/ethnicity intersect to influence school outcomes, research that operationalizes these recommendations across academic and non-academic outcomes of school children is scant.

In addition to the complexity that arises from race/ethnicity, socioeconomic status, and intersections between them, different patterns in academic and non-academic outcomes by gender have also received longstanding attention. Comparisons across gender show that, on average, boys have higher scores in mathematics and science, whereas girls have higher scores in reading [2, 3, 29]. In contrast to explanations for socioeconomic inequalities, gender differences have been mainly attributed to social conditioning and stereotyping within families, schools, communities, and the wider society [30–35]. These socialization and stereotyping processes are also highly relevant determining factors in explaining racial/ethnic academic and non-academic inequalities [35, 36], as are processes of racial discrimination and stigmatization [37, 38]. Gender differences in academic outcomes have been documented as differently patterned across racial/ethnic groups and across levels of socioeconomic status. For example, gender inequalities in math and science are largest among White and Latino students, and smallest among Asian American and African American students [39–43], while gender gaps in test scores are more pronounced among socioeconomically disadvantaged children [44, 45]. In terms of attitudes towards math and sciences, gender differences in attitudes towards math are largest among Latino students, but gender differences in attitudes towards science are largest among White students [39, 40]. Gender differences in socio-developmental outcomes and in non-cognitive academic outcomes, across race/ethnicity and socio-economic status, have received far less attention; studies that consider multiple academic and non-academic outcomes among school aged children across race/ethnicity, socioeconomic status and gender are limited in the US and internationally.

Understanding how different academic and non-academic outcomes are differently patterned by race/ethnicity, socio-economic status, and gender, including within and between group differences, is an important research area that may assist in understanding the potential causal pathways and explanations for observed inequalities, and in identifying key population groups and points at which interventions should be targeted to address inequalities in particular outcomes [28, 46]. Not only is such knowledge critical for population level policy and/or local level action within affected communities, but failing to detect potential factors for interventions and potential solutions is argued as reinforcing perceptions of the unmodifiable nature of inequality and injustice [46].

Notwithstanding the importance of documenting patterns of inequality in relation to a particular social identity (e.g. race/ethnicity, gender, class), there is increasing acknowledgement within both theoretical and empirical research of the need to move beyond analyzing single categories to consider simultaneous interactions between different aspects of social identity, and the impact of systems and processes of oppression and domination (e.g., racism, classism, sexism) that operate at the micro and macro level [47, 48]. Such intersectional approaches challenge practices that isolate and prioritize a single social position, and emphasize the potential of varied inter-relationships of social identities and interacting social processes in the production of inequities [49–51]. To date, exploration of how social identities interact in an intersectional way to influence outcomes has largely been theoretical and qualitative in nature. Explanations offered for interactions between privileged and marginalized identities, and associated outcomes, include family and teacher socialization of gender performance (e.g. math and science as male domains, verbal and emotional skills as female), as well as racialized stereotypes and expectations from teachers and wider society regarding racial/ethnic minorities that are also gendered (e.g. Black males as violent prone and aggressive, Asian females as submissive) [52–57]. That is, social processes that socialize and pattern opportunities and outcomes are both racialized and gendered, with racism and sexism operating in intersecting ways to influence the development and achievements of children and youth [58–60]. Socioeconomic status adds a third important dimension to these processes, with individuals of the same race/ethnicity and gender having access to vastly different resources and opportunities across levels of socioeconomic status. Moreover, access to resources as well as socialization experiences and expectations differ considerably by race and gender within the same level of socio-economic status. Thus, neither gender nor race nor socio-economic status alone can fully explain the interacting social processes influencing outcomes for youth [27, 28]. Disentangling such interactions is therefore an important research priority in order to inform intervention to address inequalities at a population level and within local communities.

In the realm of quantitative approaches to the study of inequality, studies often examine separate social identities independently to assess which of these axes of stratification is most prominent, and for the most part do not consider claims that the varied dimensions of social stratification are often juxtaposed [56, 61]. A pressing need remains for quantitative research to consider how multiple forms of social stratification are interrelated, and how they combine interactively, not just additively, to influence outcomes [46]. Doing so enables analyses that consider in greater detail the representation of the embodied positions of individuals, particularly issues of multiple marginalization as well as the co-occurrence of some form of privilege with marginalization [46]. It is important to note that the languages of statistical interaction and of intersectionality need to be carefully distinguished (e.g. intersectional additivity or additive assumptions, versus additive scale and cross-product interaction terms) to avoid misinterpretation of findings, and to ensure appropriate application of statistical interaction to enable the description of outcome measures for groups of individuals at each cross-stratified intersection [46]. Ultimately this will provide more nuanced and realistic understandings of the determinants of inequality in order to inform intervention strategies.

This study fills these gaps in the literature by examining inequalities across several eighth grade academic and non-academic outcomes at the intersection of race/ethnicity, gender, and socioeconomic status. It aims to do this by: identifying classes of socioeconomic advantage/disadvantage from kindergarten to eighth grade; then ascertaining whether membership into classes of socioeconomic advantage/disadvantage differ for racial/ethnic and gender groups; and finally, by contrasting academic and non-academic outcomes at the intersection of race/ethnicity, gender and socioeconomic advantage/disadvantage. Intersecting identities of race/ethnicity, gender, and socioeconomic characteristics are compared to the reference group of White boys in the most advantaged socioeconomic category, as these are the three identities (male, White, socioeconomically privileged) that experience the least marginalization when compared to racial/ethnic and gender minority groups in disadvantaged socioeconomic positions.

Methods

Data

This study used data on singleton children from the Early Childhood Longitudinal Study—Kindergarten (ECLS-K). The ECLS-K employed a multistage probability sample design to select a nationally representative sample of children attending kindergarten in 1998–99. In the base year the primary sampling units (PSUs) were geographic areas consisting of counties or groups of counties. The second-stage units were schools within sampled PSUs. The third- and final-stage units were children within schools [62]. Analyses were conducted on data collected from direct child assessments, as well as information provided by parents and school administrators.

Ethics Statement

This article is based on the secondary analysis of anonymized and de-identified Public-Use Data Files available to researchers via the Inter-University Consortium for Political and Social Research (ICPSR). Human participants were not directly involved in the research reported in this article; therefore, no institutional review board approval was sought.

Measures

Outcome Variables.

Eight outcome variables, all assessed in eighth grade, were selected to examine the study aims: two measures relating to non-cognitive academic skills (perceived interest/competence in reading, and in math); three measures capturing socioemotional development (internalizing behavior, locus of control, self-concept); and three measures of cognitive skills (math, reading and science assessment scores).

For the eighth-grade data collection, children completed the 16-item Self Description Questionnaire (SDQ) II [63], where they provided self-assessments of their academic skills by rating their perceived competence and interest in English and mathematics. The SDQ also asked children to report on problem behaviors with which they might struggle. Three subscales were produced from the SDQ items: The SDQ Perceived Interest/Competence in Reading, including four items on grades in English and the child’s interest in and enjoyment of reading. The SDQ Perceived Interest/Competence in Math, including four items on mathematics grades and the child’s interest in and enjoyment of mathematics. And the SDQ Internalizing Behavior subscale, which includes eight items on internalizing problem behaviors such as feeling sad, lonely, ashamed of mistakes, frustrated, and worrying about school and friendships [62].

The Self-Concept and Locus of Control scales ask children about their self-perceptions and the amount of control they have over their own lives. These scales, adopted from the National Education Longitudinal Study of 1988, asked children to indicate the degree to which they agreed with 13 statements (seven items in the Self-Concept scale, and six items in the Locus of Control Scale) about themselves, including “I feel good about myself,” “I don’t have enough control over the direction my life is taking,” and “At times I think I am no good at all.” Responses ranged from “strongly agree” to “strongly disagree.” Some items were reversed coded so that higher scores indicate more positive self-concept and a greater perception of control over one’s own life. The seven items in the Self-Concept scale, and the six items in the Locus of Control were standardized separately to a mean of zero and a standard deviation of 1. The scores of each scale are an average of the standardized scores [62].

Academic achievement in reading, mathematics and science was measured with the eighth-grade direct cognitive assessment battery [62].

Children were given separate routing assessment forms to determine the level (high/low) of their reading, mathematics, and science assessments. The two-stage cognitive assessment approach was used to maximize the accuracy of measurement and reduce administration time by using the child’s responses from a brief first-stage routing form to select the appropriate second-stage level form. First, children read items in a booklet and recorded their responses on an answer form. These answer forms were then scored by the test administrator. Based on the score of the respective routing forms, the test administrator then assigned a high or low second-stage level form of the reading and mathematics assessments. For the second-stage level tests, children read items in the assessment booklet and recorded their responses in the same assessment booklet. The routing tests and the second-stage tests were timed for 80 minutes [62]. The present analyses use the standardized scores (T-scores), allowing relative comparisons of children against their peers.

Individual and Contextual Disadvantage Variables.

Latent Class Analysis, described in greater detail below, was used to classify students into classes of individual and contextual advantage or disadvantage. Nine constructs, measuring characteristics at the individual-, school-, and neighborhood-level, were captured using 42 dichotomous variables measured across the different waves of the ECLS-K.

Individual-level variables captured household composition, material disadvantage, and parental expectations of the children’s success. Measures included whether the child lived in a single-parent household at kindergarten, first, third, fifth and eighth grades; whether the household was below the poverty threshold level at kindergarten, fifth and eighth grades; food insecurity at kindergarten, first, second and third grades; and parental expectations of the child’s academic achievement (categorized as up to high school and more than high school) at kindergarten, first, third, fifth and eighth grades. An indicator of whether parents had moved since the previous interview (measured at kindergarten, first, third, fifth and eighth grades) was included to capture stability in the children’s life. A household-level composite index of socioeconomic status, derived by the National Center for Education Statistics, was also included at kindergarten, first, third, fifth and eighth grades. This measure captured the father/male guardian’s education and occupation, the mother/female guardian’s education and occupation, and the household income. Higher scores reflect higher levels of educational attainment, occupational prestige, and income. In the present analyses, the socioeconomic composite index was categorized into quintiles and further divided into the lowest first and second quintiles, versus the third, fourth and fifth quintiles.

Two variables measured the school-level environment: percentage of students eligible for free school meals, and percentage of students from a racial/ethnic background other than White non-Hispanic. These two variables were dichotomized as more than or equal to 50% of students belonging to each category. Both variables were measured in the kindergarten, first, third, fifth and eighth grade data collections.

To capture the neighborhood environment, a variable was included which measured the level of safety of the neighborhood in kindergarten, first, third, fifth and eighth grades. Parents were asked “How safe is it for children to play outside during the day in your neighborhood?” with responses ranging from 1, not at all safe, to 3, very safe. For the present analyses, response categories were recoded into 1 “not at all and somewhat safe,” and 0 “very safe.”

Predictor Variables.

The race/ethnicity and gender of the children were assessed during the parent interview. In order to empirically measure the intersection between race/ethnicity and gender in the classes of disadvantage, a set of six dummy variables were created that combined racial/ethnic and gender categories into White boys, White girls, Black boys, Black girls, Latino boys, and Latina girls.

Statistical Analyses

This study used the manual 3-step approach in mixture modeling with auxiliary variables [64, 65] to independently evaluate the relationship between the predictor auxiliary variables (the combined race/ethnicity and gender groups), the latent class variable of advantage/disadvantage, and the outcome (non-cognitive skills, socioemotional development, cognitive assessments). This is a data-driven, mixture modelling technique which uses indicator variables (in this case the variables described under Individual and Contextual Disadvantage Variables section) to identify a number of latent classes. It also includes auxiliary information in the form of covariates (the race/ethnicity and gender combinations described under Predictor Variables) and distal outcomes (the eight outcome variables), to better explore the relationships between the characteristics that make up the latent classes, the predictors of class membership, and the associated consequences of membership into each class.

The first step in the 3-step procedure is to estimate the measurement part of the joint model (i.e., the latent class model) by creating the latent classes without adding covariates. Latent class analyses first evaluated the fit of a 2-class model, and systematically increased the number of classes in subsequent models until the addition of latent classes did not further improve model fit. For each model, replication of the best log-likelihood was verified to avoid local maxima. To determine the optimal number of classes, models were compared across several model fit criteria. First, the sample-size adjusted Bayesian Information Criterion (BIC) [66] was evaluated; lower relative BIC values indicate improved model fit. Given that the BIC criterion tends to favor models with fewer latent classes [67], the Lo, Mendell, and Rubin likelihood ratio test (LMR-LRT) statistic [68] was also considered. The LMR-LRT can be used in mixture modeling to compare the fit of the specified class solution (k-class model) to a model with fewer classes (k-1 class model). A non-significant chi-square value suggests that a model with one fewer class is preferred. Entropy statistics, which measure the separation of the classes based on the posterior class membership probabilities, were also examined; entropy values approaching 1 indicate clear separation between classes [69].

After determining the latent class model in step 1, the second step of the analyses used the latent class posterior distribution to generate a nominal variable N, which represented the most likely class [64]. During the third step, the measurement error for N was accounted for while the model was estimated with the outcomes and predictor auxiliary variables [64]. The last step of the analysis examined whether race/ethnic and gender categories predict class membership, and whether class membership predicts the outcomes of interest.

All analyses were conducted using MPlus v. 7.11 [70], and used longitudinal weights to account for differential probabilities of selection at each sampling stage and to adjust for the effects of non-response. A robust standard error estimator was used in MPlus to account for the clustering of observations in the ECLS-K.

Results

Four distinct classes of advantage/disadvantage were identified in the latent class analysis (see Table 1).

Class characteristics are shown in Table A in S1 File. Trajectories of advantage and disadvantage were stable across ECLS-K waves, so that none of the classes identified changed in individual and contextual characteristics across time. The largest proportion of the sample (47%; Class 3: Individually and Contextually Wealthy) lived in individual and contextual privilege, with very low proportions of children in socioeconomic deprived contexts. A class representing the opposite characteristics (children living in individually- and contextually-deprived circumstances) was also identified in the analyses (19%; Class 1: Individually and Contextually Disadvantaged). Class 1 had the highest proportion of children living in socioeconomic deprivation, attending schools with more than 50% racial/ethnic minority students, and living in unsafe neighborhoods, but did not have a high proportion of children with the lowest parental expectations. Class 4 (19%; Individually Disadvantaged, Contextually Wealthy) had the highest proportion of children with the lowest parental expectations (parents reporting across waves that they expected children to achieve up to a high school education). Class 4 (Individually Disadvantaged, Contextually Wealthy) also had high proportions of children living in individual-level socioeconomic deprivation, but had low proportions of children attending a school with over 50% of children eligible for free school meals. It also had relatively low proportions of children living in unsafe neighborhoods and low proportions of children attending diverse schools, forming a class with a mixture of individual-level deprivation, and contextual-level advantage. The last class was composed of children who lived in individually-wealthy environments, but who also lived in unsafe neighborhoods and attended diverse schools where more than 50% of pupils were eligible for free school meals (13%; Class 2: Individually Wealthy, Contextually Disadvantaged; see Table A in S1 File).

The combined intersecting racial/ethnic and gender characteristics yielded six groups consisting of White boys (n = 2998), White girls (n = 2899), Black boys (n = 553), Black girls (n = 560), Latino boys (n = 961), and Latina girls (n = 949). All pairs containing at least one minority status of either race/ethnicity or gender (e.g., Black boys, Black girls, Latino boys, Latina girls) were more likely than White boys to be assigned to the more disadvantaged classes, as compared to being assigned to Class 3, the least disadvantaged (see Table B in S1 File).

Racial/Ethnic and Gender Differences in Eighth-Grade Academic Outcomes

Table 2 shows broad patterns of intersecting racial/ethnic and gender inequalities in academic outcomes, although interesting differences emerge across racial/ethnic and gender groups. Whereas Black boys achieved lower scores than White boys across all classes on the math, reading and science assessments, this was not the case for Latino boys, who only underperformed White boys on the science assessment within the most privileged class (Class 3: Individually and Contextually Wealthy). Latina girls, in contrast, outperformed White boys on reading scores within Class 4 (Individually Disadvantaged, Contextually Wealthy), but scored lower than White boys on science and math assessments, although only when in the two most privileged classes (Class 3 and 4). For Black girls the effect of class membership was not as pronounced, and they had lower science and math scores than White boys across all but one instance.

In general, the largest inequalities in academic outcomes across racial/ethnic and gender groups appeared in the most privileged classes. For example, results show no differences in math scores across racial/ethnic and gender categories within Class 4, the most disadvantaged class, but in all other classes that contain an element of advantage, and particularly in Class 3 (Individually and Contextually Wealthy), there are large gaps in math scores across racial/ethnic and gender groups, when compared to White boys. These patterns of heightened inequality in the most advantaged classes are similar for reading and science scores (see Table 2).

Racial/Ethnic and Gender Differences in Eighth-Grade Non-Academic Outcomes

Interestingly, racialized and gendered patterns of inequality observed in academic outcomes were not as stark in non-cognitive academic outcomes (see Table 3).

Racial/ethnic and gender differences were small across socioemotional outcomes, and in fact, White boys were outperformed on several outcomes. Black boys scored lower than White boys on internalizing behavior and higher on self-concept within Classes 2 (Individually Wealthy, Contextually Disadvantaged) and 4 (Individually Disadvantaged, Contextually Wealthy), and Black girls scored higher than White boys on self-concept within Classes 2 and 3 (Individually Wealthy, Contextually Disadvantaged, and Individually and Contextually Wealthy, respectively). White and Latina girls, but not Black girls, scored higher than White boys on internalizing behavior (within Classes 3 and 4 for White girls, and within Classes 1 and 3 for Latina girls; see Table 3).

As with academic outcomes, most racial/ethnic and gender differences also emerged within the most privileged classes, and particularly in Class 3 (Individually and Contextually Wealthy), although in the case of perceived interest/competence in reading, White and Latina girls performed better than White boys. White girls also reported higher perceived interest/competence in reading than White boys in Class 4: Individually Disadvantaged, Contextually Wealthy.

Discussion

This study set out to examine inequalities across several eighth grade academic and non-academic outcomes at the intersection of race/ethnicity, gender, and socioeconomic status. It first identified four classes of longstanding individual- and contextual-level disadvantage; then determined membership to these classes depending on racial/ethnic and gender groups; and finally compared non-cognitive skills, academic assessment scores, and socioemotional outcomes across intersecting gender, racial/ethnic and socioeconomic social positions.

Results show the clear influence of race/ethnicity in determining membership to the most disadvantaged classes. Across gender dichotomies, Black students were more likely than White boys to be assigned to all classes of disadvantage as compared to the most advantaged class, and this was particularly strong for the most disadvantaged class, which included elements of both individual- and contextual-level disadvantage. Latino boys and girls were also more likely than White boys to be assigned to all the disadvantaged classes, but the strength of the association was much smaller than for Black students. Whereas membership into classes of disadvantage appears to be more a result of structural inequalities strongly driven by race/ethnicity, the salience of gender is apparent in the distribution of academic assessment outcomes within classes of disadvantage. Results show a gendered pattern of math, reading and science assessments, particularly in the most privileged class, where girls from all ethnic/racial groups (although mostly from Black and Latino racial/ethnic groups) underperform White boys in math and science, and where Black boys score lower, and White girls higher, than White boys in reading.

With the exception of educational assessments, gender and racial/ethnic inequalities within classes are either not very pronounced or in the opposite direction (e.g. racial/ethnic and gender minorities outperform White males), but differences in outcomes across classes are stark. The strength of the association between race/ethnicity and class membership, and the reduced racial/ethnic and gender inequalities within classes of advantage and disadvantage, attest to the importance of socioeconomic status and wealth in explaining racial/ethnic inequalities; should individual and contextual disadvantage be comparable across racial/ethnic groups, racial/ethnic inequalities would be substantially reduced. This being said, most within-class differences were observed in the most privileged classes, showing that benefits brought about by affluence and advantage are not equal across racial/ethnic and gender groups. The measures of advantage and disadvantage captured in this study relate to characteristics afforded by parental resources, implying an intergenerational transmission of disadvantage, regardless of the presence of absolute adversity in childhood. This pattern of differential returns of affluence has been shown in other studies, which report that White teenagers benefit more from the presence of affluent neighbors than do Black teenagers [71]. Among adult populations, studies show that across several health outcomes, highly educated Black adults fare worse than White adults with the lowest education [72]. Intersectional approaches such as the one applied in this study reveal how power within gendered and racialized institutional settings operates to undermine access to and use of resources that would otherwise be available to individuals of advantaged classes [72]. The present study further contributes to this literature by documenting how, in a key stage of the life course, similar levels of advantage, but not disadvantage, lead to different academic outcomes across racial/ethnic and gender groups. These findings suggest that, should socioeconomic inequalities be addressed, and levels of advantage were similar across racial/ethnic and gender groups, systems of oppression that pattern the racialization and socialization of children into racial/ethnic and gender roles in society would still ensure that inequalities in academic outcomes existed across racial/ethnic and gender categories. In other words, racism and sexism have a direct effect on academic and non-academic outcomes among 8th graders, independent of the effect of socioeconomic disadvantage on these outcomes. An important limitation of the current study is that although it uses a comprehensive measure of advantage/disadvantage, including elements of deprivation and affluence at the family, school and neighborhood levels through time, it failed to capture these two key causal determinants of racial/ethnic and gender inequality: experiences of racial and gender discrimination.

Despite this limitation, it is important to note that socioeconomic inequalities in the US are driven by racial and gender bias and discrimination at structural and individual levels, with race and gender discrimination exerting a strong influence on academic and non-academic inequalities. Racial discrimination, prevalent in the US and in other industrialized nations [38, 73] determines differential life opportunities and resources across racial/ethnic groups, and is a crucial determinant of racial/ethnic inequalities in health and development throughout life and across generations [37, 38]. In the context of this study’s primary outcomes within school settings, racism and racial discrimination experienced by both the parents and the children are likely to contribute towards explaining observed racial/ethnic inequalities in outcomes within classes of disadvantage. Gender discrimination—another system of oppression—is apparent in this study in relation to academic subjects socially considered as typically male or female orientated. For example, results show no difference between Black girls and White boys from the most advantaged class in terms of perceived interest and competence in math but, in this same class, Black girls score much lower than White boys in the math assessment. This difference, not explained by intrinsic or socioeconomic differences, can be contextualized as a consequence of experienced intersecting racial and gender discrimination. The consequences of the intersection between two marginalized identities are found throughout the results of this study when comparing across broad categorizations of race/ethnicity and gender, and in more detailed conceptualizations of minority status. Growing up Black, Latino or White in the US is not the same for boys and girls, and growing up as a boy or a girl in America does not lead to the same outcomes and opportunities for Black, Latino and White children as they become adults. With this study’s approach of intersectionality one can observe the complexity of how gender and race/ethnicity intersect to create unique academic and non-academic outcomes. This includes the contrasting results found for Black and Latino boys, when compared to White boys, which show very few examples of poorer outcomes among Latino boys, but several instances among Black boys. Results also show different racialization for Black and Latina girls. Latina girls, but not Black girls, report higher internalizing behavior than White boys, whereas Black girls, but not Latina girls, report higher self-concept than White boys. Black boys also report higher self-concept and lower internalizing behavior than White boys, findings that mirror research on self-esteem among Black adolescents [74, 75]. In cognitive assessments, intersecting racial/ethnic and gender differences emerge across classes of disadvantage. For example, Black girls in all four classes score lower on science scores than White boys, but only Latina girls in the most advantaged class score lower than White boys. Although one can observe differences in the racialization of Black and Latino boys and girls across classes of disadvantage, findings about broad differences across Latino children compared to Black and White children should be interpreted with caution. The Latino ethnic group is a large, heterogeneous group, representing 16.7% of the total US population [76]. The Latino population is composed of a variety of different sub-groups with diverse national origins and migration histories [77], which has led to differences in sociodemographic characteristics and lived experiences of ethnicity and minority status among the various groups. Differences across Latino sub-groups are widely documented, and pooled analyses such as those reported here are masking differences across Latino sub-groups, and providing biased comparisons between Latino children, and Black and White children.

Poorer performance of girls and racial/ethnic minority students in science and math assessments (but not in self-perceived competence and interest) might result from stereotype threat, whereby negative stereotypes of a group influence their member’s performance [78]. Stereotype threat posits that awareness of a social stereotype that reflects negatively on one's social group can negatively affect the performance of group members [35]. Reduced performance only occurs in a threatening situation (e.g., a test) where individuals are aware of the stereotype. Studies show that early adolescence is a time when youth become aware of and begin to endorse traditional gender and racial/ethnic stereotypes [79]. Findings among youth parallel findings among adult populations, which show that adult men are generally perceived to be more competent than women, but that these perceptions do not necessarily hold for Black men [80]. These stereotypes have strong implications for interpersonal interactions and for the wider structuring of systemic racial/ethnic and gender inequalities. An example of the consequences of negative racial/ethnic and gender stereotypes as children grow up is the well-documented racial/ethnic and gender pay gap: women earn less than men [81], and racial/ethnic minority women and men earn less than White men [82].

In addition to the focus on intersectionality, a strength of this study is its person-centered methodological approach, which incorporates measures of advantage and disadvantage across individual and contextual levels through nine years of children’s socialization. Children live within multiple contexts, with risk factors at the family, school, and neighborhood level contributing to their development and wellbeing. Individual risk factors seldom operate in isolation [83], and they are often strongly associated both within and across levels [84]. All risk factors captured in the latent class analyses have been independently associated with increased risk for academic problems [10, 71, 85, 86], and given that combinations of risk factors that cut across multiple domains explain the association between early risk and later outcomes better than any isolated risk factor [83, 84], the incorporation of person-centered and intersectionality approaches to the study of racial/ethnic, gender, and socioeconomic inequalities across school outcomes provides new insight into how children in marginalized social groups are socialized in the early life course.

Conclusions

The contrasting outcomes between racial/ethnic and gender minorities in self-assessment and socioemotional outcomes, as compared to standardized assessments, provide support for the detrimental effect that intersecting racial/ethnic and gender discrimination have in patterning academic outcomes that predict success in adult life. Interventions to eliminate achievement gaps cannot fully succeed as long as social stratification caused by gender and racial discrimination is not addressed [87, 88].

Supporting Information

S1 File. Supporting Tables.

Table A: Class characteristics. Table B: Associations between race/ethnicity and gender groups and assigned class membership (membership to Classes 1, 2 or 4 as compared to Class 3: Individually and Contextually Wealthy).

https://doi.org/10.1371/journal.pone.0141363.s001

(DOCX)

Acknowledgments

This work was funded by an ESRC grant (ES/K001582/1) and a Hallsworth Research Fellowship to LB. Most of this work was conducted while LB was a visiting scholar at the Institute for Social Research, University of Michigan. She would like to thank them for hosting her visit and for the support provided.

Author Contributions

Conceived and designed the experiments: LB. Performed the experiments: LB. Analyzed the data: LB. Wrote the paper: LB NP.

References

  1. 1. Jencks C, Phillips M. The Black-White Test Score Gap. Washington, D.C.: Brookings Institution Press; 1998.
  2. 2. (NCES) NCfES. The Nation’s Report Card: Science 2011(NCES 2012–465). Washington, D.C.: Institute of Education Sciences, U.S. Department of Education, 2012.
  3. 3. (NCES) NCfES. The Nation’s Report Card: A First Look: 2013 Mathematics and Reading (NCES 2014–451). Washington, D.C.: Institute of Education Sciences, U.S. Department of Education, 2013.
  4. 4. Ainsworth-Darnell J. Why Does It Take a Village? The Mediation of Neighborhood Effects on Educational Achievement. Social Forces. 2002;81(1):117–52.
  5. 5. Duncan G, Magnuson K. Can family socioeconomic resources account for racial and ethnic test score gaps? The Future of Children. 2005;15(1):35–54. pmid:16130540
  6. 6. Kao G, Tienda M, Schneider B. Racial and ethnic variation in academic performance. Research in Sociology of Education and Socialization. 1996;11:263–97.
  7. 7. Noble K, Tottenham N, Casey B. Neuroscience perspectives on disparities in school readiness and cognitive achievement. The Future of Children. 2005;15:71–89. pmid:16130542
  8. 8. Roscigno V. Family/school inequality and African-American/Hispanic achievement. Social Problems. 2000;47(2):266–90.
  9. 9. Warren J. Educational inequality among White and Mexican-origin adolescents in the American Southwest: 1990. Sociology of Education. 1996;69:142–58.
  10. 10. Brooks-Gunn J, Klebanov P, Duncan G. Ethnic differences in children's intelligence test scores: role of economic deprivation, home environment, and maternal characteristics. Child Development. 1996;67:396–408. pmid:8625720
  11. 11. Quinn D. Kindergarten Black–White test score gaps: Reexamining the roles of socioeconomic status and school quality with new data. Sociology of Education. 2015;88(2):120–39.
  12. 12. Ogbu J. Low performance as an adaptation: The case of blacks in Stockton, California. In: Gibson M, Ogbu J, editors. Minority Status and Schooling. New York: Grand Publishing; 1991.
  13. 13. Kao G, Tienda M. Educational aspirations of minority youth. American Journal of Education. 1998;106:349–84.
  14. 14. Ainsworth-Darnell J, Downey D. Assessing the oppositional culture explanation for racial/ethnic differences in school performance. American Sociological Review. 1998;63:536–53.
  15. 15. Cheng S, Starks B. Racial differences in the effects of significant others on students' educational expectations. Sociology of Education. 2002;75:306–27.
  16. 16. Qian Z, Blair S. Racial/ethnic differences in educational aspirations of high school seniors. Sociological Perspectives. 1999;42: 605–25.
  17. 17. Fagg J, Curtis S, Stansfield S, Congdon P. Psychological distress among adolescents, and its relationship to individual, family and area characteristics in East London. Social Science and Medicine. 63:636–48. pmid:16584825
  18. 18. Maynard MJ, Harding S. Perceived parenting and psychological wellbeing in UK ethnic minority adolsecens. Child Care Health and Development. 2010;36:630–8.
  19. 19. Maynard MJ, Harding S, Minnis H. Psychological well-being in Black Carribean, Black African, and white adolescentes in the UK Medical Research Council DASH study. Social Psychiary Psychiatric Epidemiology. 2007;42:759–69.
  20. 20. Priest N, Baxter J, Hayes L. Social and emotional outcomes of Australian children from Indigenous and culturally and linguistically diverse backgrounds. Australian and New Zealand Journal of Public Health. 2011. 8857.
  21. 21.

One thought on “Research Papers On Gender Relations In Class Group Assignments

Leave a Reply

Your email address will not be published. Required fields are marked *