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Connecting to “The Who”: The Primacy of Supportive Relationships

  • David J. Shernoff
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Part of the Advancing Responsible Adolescent Development book series (ARAD)

Abstract

In this chapter, we review the literature on the importance of different kinds of supportive relationships, including support from teachers, mentors, parents, and peers. We next present results from our ESM and video studies investigating the primary characteristics of the learning environment as a whole when students are engaged in classrooms. The primary characteristic of such learning environments was environmental complexity or the simultaneous combination of environmental challenge and environmental support. Environmental challenge was characterized by working on tasks of sufficient complexity for the learner’s skill level (usually with domain-specific tools), clear goals and perceived importance of the task, the building of conceptual understanding and/or language skills (including academic literacies such as “talking like a scientist”), and the opportunity to demonstrate one’s performance, as through assessment. Environmental support was characterized by positive relationships with teachers and peers, support for motivational drives (e.g., support of the learners sense of autonomy or perceived competency), constructive feedback (especially timely performance feedback), and opportunities to be both active and interactive. Environmental support was found to be engaging all by itself, whereas environmental challenge was engaging only in combination with environmental support. This suggests that students are engaged when supported to reach challenges, but not in absence of such support. Overall, supportive dimensions of students’ experience, including relationship support and support for student motivation, had a strong impact on students’ engagement in public school classrooms.

Keywords

Learning Environment Student Engagement Environmental Challenge Instructional Practice Environmental Support 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Introduction

A useful question one might repeatedly ask oneself when reflecting on engagement is why children or adolescents should be engaged in the first place. Why should they care about school, about doing what teachers ask of them? When students come to believe that teachers or other meaningful adults do not care about them, it is only human nature for them not to care either. Adolescents report that they would learn more if teachers cared about them personally, but that those connections are rare (Johnson 1997). While there is no lack of truly wonderful and caring teachers, the design of traditional public classrooms works against mutually caring and respectful relationships. Unfortunately, the quality of relationships is frequently an afterthought in the battle over curricula, testing, funding, and other aspects of school structure (Pianta and Allen 2008). Although grades are a primary motivator for students in school, a deeper reason for students’ caring so much about them is often how success and failure effects their relationships with parents and peers (Steinberg et al. 1996). If this principle were fully understood and taken seriously, many other problems of teaching and learning would likely be of only secondary importance. Although often subconscious, one of the only true answers to why students do care, other than believing that they are getting something of value out of school, is the belief that they are cared about in the process of schooling; thus, they usually welcome participating in a mutually caring social arrangement with willing adults. In this chapter, we review the literature on the importance of different kinds of supportive relationships, including support from teachers, mentors, parents, and peers. We next present results from our ESM and video studies suggestive that the supportive dimensions of students’ experience, including relationship support, have a profound impact on students’ engagement in public school classrooms.

The Primacy of Interpersonal Relationships in Adolescent Development

It is almost an understatement that adolescents are fully embedded in a world of social relationships. As students enter middle school, their social networks have an increasingly important social–emotional influence on their attitudes towards school and motivation to succeed (Furlong et al. 2003). Adolescents come to live for their social relationships, with many students suffering for years if unaccepted by their peers (Noddings 2003). Despite the increased salience of relationships, children’s feelings of relatedness tend to drop by the middle school years (Davidson et al. 2010; Eccles et al. 1993; Roeser and Eccles 1998).

Overall, the presence of a caring relationship is a critical mediator for growth and has an appreciable effect on whether or not students thrive (Deci and Ryan 1985; Eccles and Gootman 2002). Due to the pervasive influence of relationships on multiple facets of student motivation, Martin and Dowson (2009) recently demonstrated how most of the dominant motivational theories may be conceptualized in primarily relational terms. In other words, relationships can be seen as the major mediator through which dynamics such as vicarious reinforcement, attributions for success and failure, and achievement motivation operate. For example, relationships may have a powerful effect on one’s sense of self-worth, which in turn has been shown to impact motivation. Adolescents not only learn self-efficacy through building their skills while interacting with peers, but they also see self-efficacy modeled in their relationships with adults.

A growing number of studies help to support this view. Typically, research has examined the effect of feelings of connectedness with specific social partners—with teachers, parents, and mentors being the most common adult categories. Studies have found that relatedness in all of these categories have an important and unique contributions to school engagement (e.g., Furrer and Skinner 2003; Rhodes 2002; Steinberg et al. 1996). In fact, social support from parents, friends, teachers, and classmates is one of the strongest predictors of life satisfaction (Gilman et al. 2009). As a focus on relationships has been the fastest growing area of engagement research in the past 15 years, we have quickly gone from the realization that “relationships matter” (Klem and Connell 2004) to understanding that few things may matter more.

Most research on relationships in school focuses on relationship support from teachers, parents, mentors, or peers. We focus below primarily on teacher support, but also discuss some of the other important sources of relationship support. Following this, we share what our studies in high school classrooms combining video and ESM showed about relational support in the classroom.

Teacher Support

What is teacher support and what does it look like? First, teachers provide emotional support by being involved in students’ welfare and getting to know each student individually (Klem and Connell 2004). The teacher encourages, accepts, trusts, respects, and otherwise demonstrates that he or she cares about students’ emotional well-being. When their relationship with their teacher is emotionally supportive, students experience more enjoyment and interest in their schoolwork, have more positive self-concept and higher self-efficacy, are more likely to use self-regulatory strategies, and persevere in the face of difficulty and criticism (Furrer and Skinner 2003; Patrick et al. 2007; Ryan and Patrick 2001). Students are also more likely to view teachers with whom they share a close relationship as a source of support to achieve their academic goals (Birch and Ladd 1997). Teachers can also facilitate a positive social environment and promote interaction among peers which includes the mutual exchange of ideas, perspective taking, and reflective thinking (Ryan and Patrick 2001).

A particular area in which teachers can demonstrate their trust is in supporting a student’s ability to make his or her own decisions; researchers refer to this as autonomy support (Deci and Ryan 1985; Reeve et al. 2004). They also provide instrumental support by effectively scaffolding through structured questioning intended to help students progress and reach a higher level of understanding. Instrumental support also includes providing materials for students to complete assignments (e.g., calculators, worksheets, art materials, and measurement instruments), listening to students’ opinions before making instructional decisions, and encouraging them to ask questions and seek help as needed.

Teachers’ support and students’ engagement are found to be bidirectional and reciprocal: As students receive more support from teachers, teachers receive greater engagement from students and vice versa (Connell and Wellborn 1991; Furrer and Skinner 2009; Martin and Dowson 2009; Osterman 2000). In addition, teacher support has been found to mitigate downward trends in intrinsic motivation and engagement (Marchand 2011). The relationship is also interactive over time. For example, the potency of supportive teacher relations appears to be greater in middle school than elementary school (Klem and Connell 2004), with middle school students’ reports of teacher caring predicting changes in their motivational outcomes over 2 years (Wentzel 1997). Middle school students with high levels of teacher support are almost three times more likely to have high levels of engagement, which makes sense when we consider the salience of interpersonal relations as students reach adolescence (Furrer and Skinner 2003; Klem and Connell 2004).

When teachers make efforts to form personal connections with adolescent students, such that students feel acknowledged, they dramatically enhance students’ motivation and functioning both in and outside of school (Roeser et al. 1998; Skinner et al. 1998). Positive emotional support from teachers is related to emotional well-being, whereas lack of support is related to internalizing problems like depression, pervading life outside of school (Mitchell-Copeland et al. 1997; Reddy et al. 2003; Way et al. 2007; Wentzel 1997, 1998). Studies have shown that students who maintain caring and supportive relationships have more positive academic attitudes and mastery-oriented goals, higher levels of interest and self-efficacy, and are more satisfied with school (Battistich et al. 1997; Midgley et al. 1989; Mitchell-Copeland et al. 1997; Murdock and Miller 2003; Ryan and Patrick 2001; Sanchez et al. 2005; Solomon et al. 2000; Valeski and Stipek 2001; Wentzel 1997, 1998). Hence, a key feature distinguishing at-risk adolescents who succeed in school from those who do not is a close and supportive relationship with a teacher (Resnick et al. 1997). Supportive relationships with teachers and other school adults have been found to be supportive to the academic motivation and success of minority students in particular, because caring adults can offer information about cultural practices, help students to overcome language difficulties, and buffer the stresses of migration and discrimination (Garcia-Reid 2007; Green et al. 2008a).

With respect to engagement specifically, a substantial amount of research has yielded remarkably consistent results in support of the proposition that the quality of student–teacher relations, or relational support from the teacher, is positively associated with the quality of students’ engagement in school or classrooms (Connell and Wellborn 1991; Furrer and Skinner 2003; Garcia-Reid 2007; Green et al. 2008b; Hudley et al. 2003; Hughes and Kwok 2007; Hughes et al. 2006; Kalil and Ziol-Guest 2008; Klem and Connell 2004; Meyer and Turner 2007; Patrick et al. 2007; Roeser and Eccles 1998; Ryan and Patrick 2001; Sharkey et al. 2008; Skinner and Belmont 1993; Tucker et al. 2002; Urdan and Schoenfelder 2006; Voelkl 1995; Wentzel 1997, 1998). These findings were also reflected in Roorda and colleague’s (2009) meta-analysis. Various studies have found that when students believe that the teacher is warm and caring, is understanding and dependable, and supports their autonomy, they are more likely to feel accepted, have more positive affect, work hard, persevere in the face of difficulty, accept direction and criticism, seek help more, cope better with stress, and are more attentive to the teacher (Hughes and Kwok 2007; Martin and Dowson 2009). In addition, studies have shown that students who feel supported by teachers perceive themselves as being more autonomous, which in turn predicts higher engagement (Marchand 2011).

Teacher support has also been found to lead to improved student academic performance and achievement (Burchinal et al. 2002; Furrer and Skinner 2003; Klem and Connell 2004; Marchant et al. 2001; Pianta et al. 1997; Roeser et al. 1996, 2000; Roorda et al. 2009; Woolley and Bowen 2007), with the relationship between teachers’ academic support and achievement mediated by an academic engagement (Chen 2005; Furrer and Skinner 2003; Hughes and Kwok 2007).

The natural implication from this body of research is the importance of creating more personalized educational environments, strengthening relationships among student and teachers, and taking more collective responsibility for every child’s success (Klem and Connell 2004). Both teacher support and high expectations for learning lead to improved engagement and achievement, and the combination of the two exceeds outcomes associated with either one individually. The higher the environmental challenge and teacher expectations, the more of a need there is for relational support, and the greater the payoff.

Mentoring Relationships

A mentor is conceived as someone who serves as advisor, sponsor, host, exemplar, and/or guide for a younger or less experienced person (Levinson 1978). In youth mentoring relationships, effective mentors bestow responsibility, trust, and opportunities to help youth fulfill their aspirations and work towards goals that are beneficial for their development. Studies have revealed that mentoring relationships are significantly associated with positive developmental outcomes for youth (Rhodes 2002; Zimmerman and Bingenheimer 2002). While the sizes of the effects are small on average, that is likely due to the variability in the quality of the mentoring relationship. A trusting, close relationship appears to be the key ingredient for effective mentoring to occur (Langhout et al. 2004). Without a close and trusting connection, the dynamics that can make mentoring so beneficial are not likely to be in place (Herrera et al. 2000). At the crux of the mentoring relationship is the bond that is formed. If one fails to form, then the two parties may disengage before the relationship has lasted long enough to exert an influence. On the other hand, the most documented asset among resilient children is a strong bond to a competent and caring adult (Anderson et al. 2004; Rhodes 2002).

What types of mentoring relationships are most effective? Relationships that are youth centered in their orientation, as opposed to being driven by the expectations and interests of the mentor, have been found to predict greater relationship quality and duration (Herrera et al. 2000). Not surprisingly, among the most common characteristics of effective mentoring relationships are that they are both supportive and challenging. That is, developmental outcomes are most favorable when youth reported that their mentors provided both structure and support; the support was unconditional, but the nature of the relationship was beyond a “mere friendship” (Langhout et al. 2004). Effective mentors scaffolded and structured youth’s experience for the benefit of their growth while simultaneously remaining sensitive to their need for autonomy and ownership of new initiatives.

Because the search for identity and possible selves is a major developmental task during adolescence (Cross and Markus 1991, 1994; Erikson 1968, 1980; Fletcher 2007; Markus and Nurius 1986; Oyserman et al. 2004; Oyserman and Markus 1990; Plimmer and Schmidt 2007), adolescents are keen observers of individuals with whom they identify, searching for role models who connect with their interests and values. When mentors introduce young people to a domain of interest, model their own curiosity and passion, and help youths to develop the self-confidence to build competencies even in the face of obstacles, there can be a lasting influence on youths’ capital E “Engagement” and lifelong commitment to an area of interest (Nakamura and Shernoff 2009). In addition, mentors can provide their mentees with social capital, helping those who might otherwise be adrift to make connections with other caring and cooperative individuals or organizations within the community.

Because mentors often have a broader, more informed knowledge base about professions, as well as an intimate familiarity with the interests and talents of the youth they mentor, they are in a unique position to provide guidance especially with respect to future careers. Such a finding was supported by Nakamura and Shernoff’s (2009) study of successful mentoring relationships in the context of graduate advisorships in the field of genetics. The study found that in close mentoring relationships, the mentee not only learned specific scientific knowledge and skills from the mentor but also, perhaps more importantly, frequently internalized or “absorbed” the mentor’s professional values. Observing the mentor’s practices and beliefs in action became a powerful vicarious motivator. New professionals in training not only observed the contagious enthusiasm of their mentors while doing good work (Gardner et al. 2001), but also had the opportunity to emulate such behavior while highly engaged within a chosen field.

Despite increasing evidence of the value of mentoring and other interpersonal relationships for healthy adolescent development (Noam and Fiore 2004; Rhodes 2004), little attention has been paid to the process of relationship formation and the competencies involved. However, one study attempted to peer into the black box of relationship formation and found that the processes involved were related to flow experiences. Markowitz et al. (in press) conceptualized the relationship-building process in the context of the Young Women Leaders Program (YWLP) as engaging in “relational flow,” involving a balance between relational challenges and competencies such as listening, sharing, and communication skills (see  Chap. 13 for a full profile of the program). When in relational flow, one is totally absorbed in the social processes of relationship building; and the specific nature of the activity seems secondary to engagement with a significant mentor or peer. Experiencing enjoyment, focused attention, and interest in this process was found to be essential to relational flow.

Parental Relationships

In the tradition of Baumrind (1971, 1989), a great deal of research has corroborated the finding that children with parents who combine demandingness (e.g., high expectations for success, doing one’s best, adhering to rules) and supportiveness (e.g., acceptance, involvement, and autonomy support) in their upbringing are more engaged and intrinsically motivated, spend more time doing homework, have higher achievement, and have less problematic behaviors than children with parents failing to provide one or both of these two essential dimensions (see Rathunde 1996; Steinberg et al. 1996). The motivational effectiveness of combining challenge or structure with emotional supportiveness applies not only to parental relationships but also to teaching relationship and styles (Ford 1992; Skinner and Belmont 1993; Turner et al. 2002, 2003; Wentzel 2002). Thus, students are more likely to adopt the academic and social goals of teachers who provide clear directions and expectations about those goals as well as the help, advice, and guidance to achieve them (Wentzel 2009).

Relationships with Peers

Peers can be one of the most potent influences on adolescents’ day-to-day behavior (Steinberg et al. 1996). In fact, peers are thought to be more influential than parents when it comes to making day-to-day decisions about schooling such as whether to attend class, how much time to spend on homework, and how hard to try—all of which impacts what grades students get and their academic achievement (Steinberg et al.). Adolescents who are more secure with their friends also tend to have higher self-esteem and better integrated identities (Ryan et al. 1994). Research has demonstrated that peer acceptance is associated with student engagement and school satisfaction specifically (Ryan 2000), with support from peers related to both emotional and behavioral forms of engagement (Li et al. 2010). Just as with the relationship between teacher support and engagement, the process is interactive and reciprocal (Ladd et al. 1999). For example, when adolescents become rejected by their peers, their interest and engagement in school decreases, they become at increased risk for alienation and dropout, and this in turn impacts how they relate to their peers (Buhs and Ladd 2001).

The Problem: Human Relationships Not Yet at the Center

Despite the overwhelming evidence testifying to the importance of supportive relationships in fostering engagement, it is difficult to create a personalized educational environment in typical public high schools (Darling-Hammond 2002). Often adolescence are treated as children whose behaviors need to be controlled rather than “independently acting and thinking individuals,” in Einstein’s words (see  Chap. 2), deemed worth getting to know. One might say that typical schools are more curricular and achievement centric than people-centric. In the emotional climate created, students are often open about their desire to do the minimum work necessary to obtain their goals (Rayyes 2011). Fortunately, research indicates that the meaningful relationships that promote engagement as well as other positive outcomes for youth can be fostered in authentic learning communities (Rayyes 2011; Zhao and Kuh 2004).

The Importance of Classroom Climate

Because of the vast importance of supportive relationships, researchers have attempted to identify various dimensions of support. For example, A. L. Davidson and Phelan (1999) characterized the central components of student–teacher relationships as trust, respect, and care. Wentzel (2009) characterized the motivational aspect of teacher–student relationships as including challenge and support dimensions in the tradition of Baumrind, as well as teacher communications and expectations, willingness to provide advice and instruction, and emotional support and safety. When teachers have been asked specific things that they do to demonstrate caring to their students, almost two-thirds of those asked referred to affective qualities of interpersonal interactions like supporting self-esteem and creating a climate of positive rapport, trust, and respect (Weinstein 1998). Ethnographic research has supported the proposition that these are indeed important aspects of perceived support (Moje 1996).

The realization that the classroom climate and the affective aspect of interactions play the critical role in students’ perceptions of support poses a special challenge for researchers. One problem is: What is the appropriate unit of analysis? For example, should researchers be comparing individual students, classrooms, or schools (Fraser and Fisher 1982)? For the most part, studies seek to relate differences in individual students’ perception of support to differences in student outcomes. By focusing on individual differences, much research disregards the possibility that teacher and classroom effects may be drivers of student perceptions of support and related outcomes. This possibility may be a probability when considering that instructional styles and interventions exist at the teacher or class level (Wentzel 2009). A small literature on classroom climate does exist (Allodi 2010; Fraser 1998; Fraser and Fisher 1982; Galini and Efthymia 2009; Opolot-Okurut 2010). Because most of these studies utilize surveys of individual students’ perceptions of the classroom climate, however, the unit of analysis in researching even classroom-level differences is still the individual student.

To gain some theoretical guidance on this issue, a useful question is not “what is learning?” but “where is learning?” Vygotsky and others illustrated the nature in which learning is seen as a social, cultural, and transactional process mediated through language and other cultural tools. Much of contemporary educational psychology has largely followed in this constructivist tradition, highlighting the reciprocal, situated, and collaborative nature of learning within authentic contexts and learning communities (Brown and Campione 1994; Brown et al. 1989; Paavola et al. 2004; Palincsar and Herrenkohl 1999; Rogoff 1990, 1995, 2003; Scardamalia 1989; Zhang et al. 2009). However, research methods largely lag behind, dominated by surveys to tap individual constructs rather than characteristics of salient relationships, interactions, and communities of learners that characterize learning environments. This is only one of perhaps several reasons that research on learning environments, including the social and relational climate, has arguably not received due attention by researchers (Allodi 2010).

Linking the Learning Environment with Students’ Subjective Experiences While in Class

In  Chap. 6, we described our study examining the immediate effect of instructional practices on the moment-by-moment engagement of high school students. A focus on instructional practices as controlled by the teacher can be helpful in terms of implications for teacher practice and professional development, but may be somewhat reductionistic. That is, the expectation was to find one-way, linear effects of individual instructional practices on individual students. If engagement with learning arises from the reciprocal interaction between learners and a learning environment as suggested by contemporary educational psychology, however, a more holistic approach may be needed. The teacher’s potential to engage students exists as a function of his or her ability to create, shape, and influence the whole learning environment, which may then become a greater factor than the teacher’s more specific instructional behaviors within it. Methodologically, we therefore devised a new instrument to capture dimensions of the classroom environment that theory and research suggests would influence motivation and engagement to learn. We used the instrument to investigate the following research question: What is the influence of research-based dimensions of the motivational and learning environment on students’ engagement while participating in that environment? Given the prevailing literature, we expected that support or relational dimensions of the learning environment would be particularly influential (see Shernoff et al. 2011, for a fuller description of the study).

As suggested in  Chap. 6, the immediate learning environment is likely to be among the most salient, if not the very most salient, factors contributing to children’s engagement to learn. By definition, engagement is created by characteristics of optimal learning environments. As we have seen, the primary theoretical feature of optimal learning environment is environmental complexity consisting of combined dimensions of environmental challenge and environmental support. To summarize, features of the challenge dimension included optimally challenging tasks, a focus on conceptual and/or language development, clear goals, the use of tools for fashioning products or solving problems, task importance, high expectations for mastery, and the assessment of competencies. Components of the support dimension include motivational/autonomy supports, opportunities for activity and interactivity, feedback or scaffolding, and positive relationships with adults and peers (see  Chap. 6).

Observing and Studying the Learning Environment

The participants and methods were the same as described in  Chap. 6. Seven high school classes were observed and videotaped in five different subjects in two schools. Students also participated in the ESM, and their responses were linked to what was happening in the classroom. Our research team coded the learning environment as a whole for those dimensions expected to facilitate engagement in learning. A learning environment observational assessment instrument was created for this purpose. Categories included in the assessment instrument were based on previous research of student engagement from the perspective of flow theory, a thorough review of the engagement literature, and literature on learning environments and classroom climate (e.g., American Psychological Association 1997; Brophy and Good 1986; Fraser 1998; Larson 2011; Reeve et al. 2004; Shernoff 2010, 2012; Skinner and Belmont 1993; Turner 2010; Urdan and Turner 2005; Zedan 2010). We called the instrument the Optimal Learning Environment–Observational Log and Assessment (OLE-OLA). Although still under development, a complete list of all 12 dimensions and their subcomponents can be found in the Appendix.

Each dimension of the OLE-OLA was rated on a seven-point scale following the procedure and general rating categories of the Classroom Assessment Scoring System (CLASS; Pianta et al. 2008). For example, a scoring range from 1 (minimally characteristic) to 7 (highly characteristic) was given for each dimension representing the extent to which it was characteristic of the classroom learning environment. The overall learning environment in the instructional episode or situation preceding each of the 27 beeps across all classroom observations was the unit of analysis that was coded. The coder made a judgment regarding the frequency, intensity, and range of each dimension for each episode. Each dimension included several more specific descriptors or indicators. Each coder took notes while viewing the video which formed the basis of the score and was useful for comparing scores to other coders. Unlike the procedure for the CLASS, however, averages were not taken across episodes in favor of examining the variation from one time point to the next. Following the system outlined for the CLASS, Inter-rater agreement of the OLE-OLA was approximately .72.

Factor analysis of the 12 dimensions revealed a single underlying factor with high loadings for clear goals, complex tasks, conceptual and language development, motivational support, interactivity, and feedback. Given that these dimensions were somewhat evenly balanced between components of environmental challenge and environmental support, the underlying factor appeared to be environmental complexity in which challenge and support dimensions are well balanced. This underlying factor was significantly related to students’ perceptions of involvement, contributing ideas, positive affect, engagement, challenge, skill use, clear goals, feeling accepted, and effort. The validity and unidimensionality of this underlying construct was confirmed by good fit with the Rasch model (Cavanagh & Shernoff, in progress).

This finding underscored the notion that environmental complexity is likely the chief attribute of optimal learning environments in terms of stimulating flow, engagement, self-efficacy, and a strong sense of participation. In complex environments, students were significantly but appropriately challenged with high teacher expectations, but also given the supports to be successful, including competency, motivational, relational, and social/emotional supports. Thus, optimal learning environments were characterized by environmental complexity in which environmental challenge and support were combined. Predominant elements of the learning environment included the use of materials, optimal challenge, high teacher expectations, positive teacher–student and peer relationships, clearly expressed goals for the activity, teacher monitoring and feedback/scaffolding, and teacher enthusiasm/creativity. Optimal learning environments were frequently created through structured tasks in individual or small group work with teacher monitoring. One instructional practice that enhanced engagement during direct instruction or presentations, for example, was teacher instructions directing concurrent student action (e.g., solving board problems with a calculator simultaneous with the teacher). Another feature of optimal learning environments we observed was cognitive apprenticeship, in which the teacher modeled and made explicit his thinking processes with respect to complex problem solving. The overall function of these simultaneous conditions was to create strong scripts or prescriptions for directing student action. Simultaneously, students felt emotionally supported through a positive relational tone often created by very subtle uses of positive feedback and affirmation, expressions of student interest, and uses of humor.

The teacher, class, and school subject were a highly influential “mega-factor” in the study, which we sought to account for statistically, but without the ability to disentangle the distinct effect of each factor.1 We used school subject, representing the six subjects in the seven observed classes, as the class/subject/teacher “mega-factor.” School was another overlapping factor, but one that was also accounted for by the school subject variable control since two subjects were taught in one school and four in the other.

The structure of the data was nested due to multiple dependencies within it.2 Therefore, multilevel models (or HLM; Bryk and Raudenbush 2002) were used for analyses.3

The Results

Preliminary analyses revealed that some combination of teacher, class, subject, and school factors (i.e., the subject variable or “mega-factor” accounting for these variables in the study) exerted a large influence over average class engagement among instructional episodes, accounting for 60 % of the variation in engagement among them (see Shernoff et al. 2011).

The dimensions of the learning environment as rated on the OLE-OLA were highly predictive of engagement. Together, the dimensions of the learning environment and classroom climate as rated on the OLE-OLA accounted for 83 % of the variation in average engagement among instructional episodes. We also analyzed each dimension separately while controlling for the effects of class/subject/teacher (i.e., again, using the subject variable) and the effect of person-level characteristics. Person-level controls included grade level, gender, race/ethnicity, low SES, grade in course, and honors student. Results revealed that our global rating of environmental complexity (combination of environmental challenge and support) was a positive predictor of engagement after controls (B = 0.21, t = 2.60, p < .05). Next, global ratings for environmental support and environmental challenge were each tested.

Both, environmental support and environmental challenge were positively related to engagement (B = 0.30, t = 2.48, p < .05; B = 0.16, t = 2.50, p < .05; respectively).

Five dimensions may conceptually be considered to be components of a supportive learning environment: motivation support, positive relationships, interactivity, feedback, and activity level. Five are conceptually more related to a challenging environment: task importance, complex tasks, clear goals, assessment, and conceptual/language development. Interestingly, the five support dimensions and five challenge dimensions formed composite scales with high reliabilities (α = .81 for the support composite and α = .82 for the challenge composite), supporting the premise of an underlying construct for each. One remaining dimension, teacher effectiveness, would appear to be important for both a challenging and supportive environment and, therefore, was conceptually neutral. The support scale was a significant predictor of engagement (B = 0.24, t = 2.11, p < .05); but the challenge scale was not.

When testing these more specific dimensions, those that were positively related to engagement included support for motivation (B = 0.18, t = 2.51, p < .05), positive relationships (B = 0.37, t = 2.90, p < .01), task importance (B = 0.30, t = 3.97, p < .01), and clear goals (B = 0.18, t = 2.20, p < .05). Positive relationships and the teacher’s direct role were significant predictors only when removing the control for class/subject/teacher (B = 0.52, t = 2.58, p < .05; B = 0.28, t = 2.91, p < .01; respectively). It makes intuitive sense that positive relations and the teachers’ direct role were accounted for by the influence of the class or teacher. In fact, the effect of positive relations was almost entirely accounted for by controlling on class/subject/teacher.

Results are illustrated in Table 7.1. In the table, challenge dimensions, including the global rating for environmental challenge, appear on the left side of the table and support dimensions on the right side. Significant predictors are bolded.
Table 7.1

Significant and nonsignificant dimensions of the learning environment predicting engagement

Environmental complexity (global rating)*

 

Teacher effectiveness*†

 

Challenge dimension (global rating)

Support dimension (global rating)*

Challenge composite (α = .82)

Support composite (α = .81)*

Task Importance**

Motivational support*

Complex tasks (e.g., with materials)

Positive relationships**†

Clear goals*

Interactivity

Assessment

Feedback

Conceptual/language development

Activity level

Note. Significant predictors are set in bold. *p < .05; **p < .10, † Significant only after removing control for class/subject/teacher

Environmental Complexity and Optimal Learning Environments

As hypothesized, the learning environment was extremely operative for shaping students’ immediate level of student engagement in the classroom. The global rating for environmental complexity was a significant predictor of student engagement as hypothesized. Interestingly, environmental support—both the global rating as well as several of its component dimensions—was found to be positively related to engagement. Components of environmental support predicting engagement included support for positive relationships, and feedback motivation and positive relationships. Dimensions thought to be components of environmental challenge such as importance and clear goals were significant predictors. The sample size was not large enough to detect all significant effects. It was interesting to find that environmental challenge was engaging only in combination with environmental support. Overall, findings were suggestive that the learning environment, and environmental complexity in particular, has a major influence on the engagement of students in traditional public school classrooms.

A classroom environment of belongingness and participation fostering strong relationships among students and the teacher was predictive of student engagement in high school classrooms. This supports the notion that classrooms are relational zones in which pedagogical caring and the quality of relationships play an integral role in students’ motivation to learn and succeed (Furrer and Skinner 2003). Not surprisingly, this effect was highly associated with the specific class and teacher creating these zones. When students feel secure, special, and important in their relationships, this triggers positive emotions like interest and enthusiasm. They become more likely to discuss their work and use self-regulatory strategies in a class climate of mutual respect and emotional support. Oppositely, when feeling unconnected, students are more likely to feel bored, worried, or frustrated and struggle to become constructively involved in activities.

The teacher’s direct role beyond shaping the learning environment was found to be another dimension related to engagement, and yet, for all of the time teachers spend preparing for this role, it is interesting to consider that their direct role in managing the classroom, time, and activities may not even be as salient of a factor in students’ engagement as their role in creating a motivational and relational environment in the classroom. In addition to managing the class, therefore, the teacher needs to demonstrate and model a degree of emotional understanding, a tacit form of understanding in which they empathize with student’s situations, circumstances, and predicaments, and also use this understanding to make instructional decisions (Downs and Smith 2004; Hargreaves 2000; Hargreaves et al. 2001; Orange 1995; Warren et al. 2008). When children feel emotionally supported and understood, they demonstrate a propensity to adopt an attitude of excitement, fun, and interest in learning. This makes clear that a large factor in student engagement is simply students’ desire to be in the presence of the teacher and classmates—their comfort with being where they are—which is typically a direct function of relationship quality. Essentially, when teachers showed interest in the students as opposed to adopting a functional relationship as a mere evaluator of them, students are more likely to feel comfortable in, interact with, and absorb what is available in the environment. This reaction is an interactive one, as teachers may become emotionally involved and attached with students as well (Meyer 2009).

Overall, student and teacher engagement did appear to be a highly interactive process. Although teaching and learning have traditionally been studied as separate processes (Kunter et al. 2008; Shuell 1993), in reality, teachers and students co-create the pattern of classroom interactions together—which, in turn, impacts both teacher and student motivation (Turner and Warzon 2009). Although teachers do exert more control than students over the content and process of activities, and can greatly impact the relational environment, the nature in which students and teachers engage each other in a cyclical interaction greatly influences both the students’ and the teacher’s motivation.

Despite some unique advantages of the method used in the study presented in this chapter, the potential for future applications may be far greater. The combination of the ESM with video techniques proved to be an effective technique for accounting for the dynamic nature of the classroom and discovering the relationship between instructional practices, the learning environment, engagement, and other student perceptions. The type of hypotheses able to be tested using this methodology in the future is numerous. The video data alone provided a wealth of information, with each videotape containing a large amount of data that can be coded and recoded in different ways. Together, the ESM and video data can make possible an in-depth investigation into classroom dynamics and students proximal reactions to them. Future studies may utilize similar methods in implementing theory-based interventions rather than studying only samples of ordinary instruction in typical public school classes. Even more important is the potential to apply such methods to determine the extent of variation not only within and between public schools but also private and alternative schools as well as after-school learning environments.

Conclusion

Increasingly, young people feel disconnected and disengaged. The findings discussed in this chapter suggest that to engage students in learning, educators should focus on developing a sense of community, belongingness, and connection through supportive relationships, and reducing the relational emphasis on teacher authority. When students are made to feel that their teachers believe in them and their capabilities, their self-esteem and confidence in successfully reaching their goals is strengthened (Shernoff 2001). This is achieved through appropriate praise and encouragement, celebrating personal achievements, speaking authentically about students’ strengths, and modeling humility. When these are the active elements of the learning environment, the virtues and exemplary characteristics of others become a source of inspiration rather than competition. Unfortunately, there is a mismatch between what research shows and what educational policies demand. Research strongly supports the wisdom of a new and different approach to school that puts relationships at the center (Smyth and Fasoli 2007). Studies such as those discussed in this chapter suggest that rather than focusing exclusively on course content or the quantity of student participation, educators would profitably focus on the quality of classroom experiences via supportive interactions and positive classroom climate.

Footnotes

  1. 1.

    Several class-level variables were highly overlapping, because the seven classes observed were all different subjects (with one exception—two were English), and all subjects were taught by different teachers, with one exception (one teacher taught both class in sociology and geography). Because we considered the two English classes taught by the same teacher to be similar, we believed the school subject variable was the simplest and most comprehensive variable to account for the effect of class, subject, and teacher collectively. We hope to be able to disentangle the independent effects of each in future studies collecting more data.

  2. 2.

    For example, there were self-reports about the same classroom situation at the same point in time from different students. Therefore, each self-report was not independent on the other. Classroom situations at these time points were a source of dependency, and there were others as well; see Shernoff et al. (2011) for a fuller discussion of how nestedness was conceptualized in this study.

  3. 3.

    In this statistical modeling, self-reports of all of the students’ in the class were “nested” within each instructional episode when the ESM signal was given, and the classroom climate of the learning environment during that episode was rated. These models partitioned the variance in engagement into a “within-episode” component, meaning different student reporters about the same instructional episode (referred to as level 1), and a “between-episode” component (i.e., level 2), meaning the average difference in engagement a classroom reported from one instructional situation to the next. This allowed us to examine the average engagement between instructional episodes as a function of the attributes of the learning environment, as well as the individual variation within each instructional episode as a function of the personal characteristics of the student reporters.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • David J. Shernoff
    • 1
  1. 1.Department of Leadership, Educational Psychology and Foundations College of EducationNorthern Illinois UniversityDeKalbUSA

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