Homework Emotion Management at the Secondary School Level: Antecedents and Homework Completion


by Jianzhong Xu - 2011

Background/Context: For many children, doing homework becomes an emotionally charged event and one of the most disappointing aspects of school life. It is surprising to note, however, that homework emotion management is noticeably absent from much contemporary homework literature.

Purpose: The primary propose of the present study was to propose and test empirical models of variables posited to predict homework emotion management at the secondary school level, with the models informed by (a) research and theory on emotion regulation and (b) findings from homework research that alluded to a number of factors that may influence homework emotion management. Another purpose of the present study was to examine whether homework emotion management is related to homework completion, one of the major outcome variables in the homework process.

Research Design: The study reported here used cross-sectional survey data. The participants were 1,895 students from 111 classes in the southeastern United States, including 1,046 eighth graders from 63 classes and 849 11th graders from 48 classes.

Results: Results from the multilevel analyses revealed that most of the variance in homework emotion management occurred at the student level, with grade level appearing as the only significant predictor at the class level. At the student level, the variation in homework emotion management was positively associated with teacher feedback, peer-oriented reasons for doing homework, arranging the environment, managing time, and monitoring motivation. Girls reported statistically significant higher scores in managing homework emotion than did boys. Follow-up analyses further revealed that homework emotion management was positively associated with homework completion.

Conclusion: As most of the variance in homework emotion management occurred at the student level rather than at the class level, homework emotion management was largely a function of individual student characteristics and experiences. The present study further suggests that monitoring motivation and managing time play a predominant role in homework emotion management (compared with other variables included in the present study). Consequently, there is a critical need to conceptualize these variables in the process of emotion regulation in general, and in homework emotion management in particular. In addition, there is a critical need for secondary schools to strategically engage students in the homework process to better manage their emotion while doing homework.

Frequently, the mere mention of the word of “homework” evokes strong unpleasant emotional responses among many school-aged children. Indeed, for many children, doing homework becomes an emotionally charged event (Corno, 1996, 2000; Epstein & Van Voorhis, 2001; Hoover-Dempsey et al., 2001; Xu & Corno, 1998) and one of the most disappointing aspects of school life (Cooper, 2001; Kouzma & Kennedy, 2002; Larson & Richards, 1991; Leone & Richards, 1989; Ratnesar, 1999; Verma, Sharma, & Larson, 2002). Not surprisingly, doing homework was portrayed by one popular magazine as something in which “every night, millions of parents and kids shed blood, sweat and tears over the kitchen table” (Begley, 1998, p. 50). It is surprising to note, however, that homework emotion management is noticeably absent from much contemporary homework literature (Knollmann & Wild, 2007; Xu, 2005a).


In a homework model, Cooper (1989) proposed that student ability, motivation, grade level, and other individual differences (e.g., gender) are exogenous factors that may influence the effectiveness of homework. The model’s endogenous factors divide the homework process into characteristics of the assignment (e.g., purpose), initial classroom factors (e.g., provision of materials), home-community factors (e.g., home environment and others’ involvement), and classroom follow-up (e.g., teacher feedback). However, this model does not conceptualize homework emotion management as one of the variables that may influence the effectiveness of homework. Given that homework is an emotionally charged event (e.g., Xu & Corno, 1998; Verma et al., 2002) and “a source of complaint and friction between homework and school more often than other teaching activity” (Cooper, 2001, p. ix), it would be important to examine homework emotion management as one of the important variables in the homework process.


Gross (1998, 2002) conceptualized emotion regulatory processes as consisting of antecedent- and response-focused emotion regulation. Antecedent-focused regulation refers to “things we do before the emotion response tendencies have become fully activated” (Gross, 2002, p. 282), including strategies such as situation selection and situation modification. Situation selection and situation modification are somewhat parallel to arranging the environment in the present study or environmental control in the literature on volitional control (Corno, 1993; Kuhl, 1987). On the other hand, Gross’s model does not tap into two important emotion regulation strategies (i.e., managing time and monitoring motivation) suggested by other theorists (Corno, 1993; Corno & Kanfer, 1993; Kuhl, 1985; Op ’t Eynde & Turner, 2006; Pekrun, 2006; Schutz, Hong, Cross, & Osbon, 2006).


There is a critical need to propose and test models of factors that predict homework emotion management. This line of research is important, as (a) managing one’s unpleasant emotional states is crucial for successful academic performance (e.g., Corno & Kanfer, 1993; Corno & Xu, 2004; Pekrun, 2006) and psychological well-being (e.g., Frijda, 1986; Pekrun, 2006) and as (b) students’ unpleasant emotional states are more pronounced for homework than for classwork (Leone & Richards, 1989; Verma et al., 2002). This line of research is particularly important at the secondary school level, as these students spend more time doing homework. According to the National Assessment of Educational Progress (Perie, Moran, & Lutkus, 2005), 18% of 9-year-olds reported doing more than 1 hour of homework each day; this figure jumped to 34% for 13-year-olds and 33% for 17-year-olds.


Whereas no specific model of homework emotion management has emerged, two bodies of literature pertain to students’ management of homework emotion. These include (a) research and theory that bear direct relevance to the issue of emotion regulation and (b) findings from homework research that allude to a number of factors that may influence homework emotion management.


RESEARCH AND THEORY ON EMOTION REGULATION


Over the last two decades, there has been a substantial increase in psychology literature and in popular culture’s interest in human emotionality in general, and in emotion regulation in particular (e.g., Cole, Martin, & Dennis, 2004; Dunn, 1996; Eisenberg, Champion, & Ma, 2004; Garber & Dodge, 1991; Goleman, 1995; Gross, 1998; Morris, Silk, Steinberg, Myers, & Robinson, 2007). Although a definition of emotion regulation is still a topic of considerable debate, this term typically refers to the processes involved in monitoring and modifying the occurrence, intensity, and expression of emotions (Eisenberg et al., 2004; Morris et al., 2007).


Some researchers include behaviors that preclude the actual experience of emotion in their definitions of emotion regulation (Gross, 2002), whereas others do not discuss this possibility (Eisenberg et al., 2004). Eisenberg and Spinrad (2004) argued for a broad working definition of emotion regulation that includes antecedent emotion regulation (Gross, 2002) or proactive coping (Aspinwall & Taylor, 1997). Their argument is based on the view that emotion regulation can occur by preventing the occurrence of an emotion or by creating circumstances that foster a different emotional experience (e.g., a shy person may avoid attending a large party or engaging in any anxiety- or fear-provoking activity, to regulate his or her emotion).


Yet there are many cases where an individual is unable to avoid certain activities, ranging from Y2K (the millennium bug; Aspinwall, Sechrist, & Jones, 2005) to completing homework assignments. Consequently, there is a need to revisit this definition, by distinguishing emotion regulation (i.e., focusing regulation on an emotion that is already under way) from proactive coping (i.e., efforts undertaken before a potentially stressful event to prevent it or to modify its form before the event occurs). In doing so, there are both theoretical and practical values in examining the influence of proactive coping on emotion regulation.


Focusing on regulating an emotion that is already under way is in line with models of self-regulated learning, particularly from a volitional perspective (Boekaerts & Corno, 2005; Corno, 1993, 2001, 2004; Corno & Kanfer, 1993; Husman, McCann, & Crowson, 2000; Kuhl, 1985, 1987, 2000). Volitional control focuses on issues of implementation that occur after goals are set and is characterized by the self-regulation activities of purposive and persistent striving, including, for example, organizing one’s study environment, budgeting time, and regulating motivation and emotion. In Kuhl’s (1985) taxonomy of volitional strategies that an individual might use to facilitate the enactment of an intention, motivation and emotion control were designated as two covert strategies (Corno, 1993). Motivation control strategies involve maintaining or strengthening the motivational base of the current behavior when the intention is weak relative to other possible competing intentions. Emotion control strategies involve keeping inhibiting emotional states in check (e.g., stress and frustration). It is reasonable to hypothesize that motivation and emotion control strategies are positively related, as an individual who strengthens his or her intention to compete a task is more likely to take initiative in coping with unpleasant emotions. This hypothesis is consistent with recent discussion on how motivation can alter affective experiences (Linnenbrink, 2006; Meyer & Turner, 2006; Pekrun, 2006).


In addition, many researchers point to the importance of goals in emotion regulation (Campos, Frankel, & Camras, 2004; Diamond & Aspinwall, 2003; Eisenberg & Spinrad, 2004; Larson & Brown, 2007; Op ’t Eynde & Turner, 2006; Thompson, 1994). Diamond and Aspinwall (2003) stated that “emotion regulation – at all stages of life – cannot be understood without some consideration of what people were trying to do in the situation that elicited the emotion or in which the emotion was experienced” (p. 137). This view is in line with social cognitive control-value theory of academic emotions and motivation (Pekrun, 2000), which posits how relationships of emotions, motivation, cognitions, and learning can be influenced by value-related beliefs that students bring to the learning situation.


Recent literature further suggests certain individual characteristics that may influence emotion regulation, including age, gender, parent education, and student ability. As effortful control increases with age (Eisenberg & Morris, 2002), as individuals mature and gain in life experience, they may increasingly learn to make greater use of emotion regulation strategies (e.g., Eisenberg & Spinrad, 2004; John & Gross, 2004; Morris et al., 2007). Meanwhile, girls are found to exhibit more effort to regulate their emotion than boys (e.g., McRae, Ochsner, Mauss, Gabrieli, & Gross, 2008; Morris et al., 2007; Raffaelli, Crockett, & Shen, 2005). Although no prediction is provided, several researchers have suggested there is a need to include student ability or consequence of achievement (e.g., Kuhl & Kraska, 1989; Op ’t Eynde & Turner, 2006; Pekrun, 2006) and parent education (e.g., Morris et al., 2007; Raver, 2004) in future research on emotion regulation. In addition, researchers argue that significant others (e.g., parents and teachers) may play an important role in helping students regulate their emotion (e.g., Diamond & Aspinwall, 2003; Eisenberg et al., 2004; Larson & Brown, 2007; Morris et al., 2007).


Other researchers point to the critical role of time management in volitional control in general (e.g., Corno & Kanfer, 1993; Husman et al., 2000; Kuhl, 2000), and in emotion regulation in particular (e.g., Op ’t Eynde & Turner, 2006; Schutz et al., 2006). From the perspective of a dynamic, component systems theory of emotions, Op ’t Eynde and Turner (2006) argued for the inclusion of time dimension in emotion regulation, as goals often take extended periods of time to achieve and as emotions often arise due to externally or internally imposed deadlines. The authors gave an example of a girl who has been assigned to read a novel and write a paper on it for evening homework. As soon as she realizes that it is getting late and there are still too many pages to be read before she can start writing her paper, she may feel anxious or stressful. As a result, she may resort to time management strategies to alleviate her anxiety (e.g., quickening her reading or skipping some pages).


Taken together, research and theory on emotion regulation suggest that emotion regulation may be influenced by a number of variables, including background variables, adult monitoring, values and goals, arranging the environment, managing time, and monitoring motivation. Hence it is important to incorporate these variables in models of students’ management of homework emotion.


EMPIRICAL STUDIES ON HOMEWORK EMOTION


Several studies have found that children experience generally unpleasant emotional states while doing homework (Leone & Richards, 1989; Verma et al., 2002; Xu, 1994; Xu & Corno, 1998; Xu & Yuan, 2003). Xu and Corno (1998) conducted case studies of families doing third-grade homework. Data revealed that doing homework was an emotionally charged process. For example, one mother found that there were times when she and her daughter went to “the battlefield.” She explained:


It’s frustrating for her. She will pull her hair. She will get very angry at me. She will tell me things she should not say, like I’m not a very good mother; I don’t care about her; and I’m not comforting her. (p. 428)


In another qualitative study with middle school students, Xu and Yuan (2003) found that many students viewed homework negatively. Some students felt that it was “a pain in the neck.” One student noted, “I don’t like doing it. It makes me upset, and I don’t want to do it.” Similarly, another student complained that “homework is bothering because it takes away from the business of having fun [during the after-school hours]” (p. 35).


Following procedures of the experience sampling method (Csikszentmihalyi & Larson, 1987), Leone and Richards (1989) investigated students’ homework experiences as reported by 401 students in grades 5–9. Data revealed that students’ moods while doing homework were generally negative, regardless of age, sex, and academic performance. Students rated their levels of positive affect, motivation, and attention lower than they did for similar subjective experiences with other activities such as eating meals and doing chores.


Recently, Verma et al. (2002) used the experience sampling method to examine students’ homework experiences, as reported by 100 eighth graders in India. Data revealed that homework stood out as the least favorable context for doing schoolwork, in the sense that “the students felt significantly more unhappy, angry, irritable, weak, tired, stressed, and bored while doing homework as compared to classwork” (p. 505).


Meanwhile, some studies have alluded to a number of factors that may influence homework emotion management, including student and family characteristics, adult monitoring, and student attitudes toward homework. Xu and Corno (2006) linked gender, grade level, and family homework help to homework emotion management, as reported by 238 students in grades 7–8. Data revealed that students who received family help reported more frequently working to control potentially unpleasant emotions. In contrast to the boys, girls reported working more frequently to control such emotions.


A qualitative study by McCaslin and Murdock (1991) implied that children may learn from their parents about how to monitor their emotions, even when the parents had only limited formal education. In one family, the father encouraged his son, a sixth grader, to control unpleasant emotions that arose during homework. For example, when his son got a little upset with homework because it did not come right way, the father told the boy to calm down, cool off, and relax, so that he could get back on track, focus his mind, and get to the bottom of the problem. As a result, it appeared that the boy internalized some of his father’s suggested coping strategies. The son became aware of the potential consequences of frustrated coping (e.g., that refusing to ask for help could lead to a poor grade). Realizing the self-destructiveness of anger, the boy also began to learn to control his emotions, as illustrated in his statement: “I don’t feel like doing the work. But I keep doing it” (p. 229).


A recent study by Trautwein, Ludtke, Schnyder, and Niggli (2006) has also alluded to the role of teachers in the homework process. The study linked homework control to homework effort, as reported by 1,501 eighth graders from 93 classes in Switzerland. Data revealed that perceived teacher control (e.g., checking homework) was a statistically significant predictor of homework effort at the student level, implying that teacher monitoring may influence student behavior in general (Natriello & McDill, 1986), and in homework emotion management in particular.


Other studies have found that homework emotion management may be influenced by student attitude (Xu, 2005a, 2005b). Xu (2005a) linked student characteristics and homework reasons to homework emotion management, as reported by 205 students in grades 9–10. Data revealed that girls and students who received family help reported more frequently monitoring their emotions. In addition, reasons for doing homework as perceived by students were positively associated with more frequent use of homework emotion management strategies.


GAPS IN PREVIOUS RESEARCH AND PURPOSE OF THE PRESENT STUDY


Taken together, some empirical studies on homework emotion find that secondary students continue to experience unpleasant emotional states while doing homework. Other studies allude to several factors such as adult monitoring (McCaslin & Murdock, 1991; Trautwein et al., 2006; Xu & Corno, 2003) and student attitude (Xu, 2005a, 2005b) that were positively related to homework emotion management. Girls, compared with boys, reported more frequently controlling homework emotions (Xu, 2005a, 2006; Xu & Corno, 2006).


Yet much of what we know about homework emotion management (a) is informed by insights from qualitative data (e.g., McCaslin & Murdock, 1991; Xu & Corno, 1998) and (b) is inferred from studies that did not focus on homework emotion (e.g., Trautwein et al., 2006). In addition, in previous studies on homework emotion, individual student characteristics are confounded with those of classrooms. This clustering effect presents several major statistical issues (e.g., aggregation bias, misestimated standard errors, and heterogeneity of regression) due to the lack of independence between measurements at different levels. These studies fail to incorporate a multilevel perspective to differentiate between class- and student-level effects. Furthermore, the studies are not theoretically grounded in research and theory on emotion regulation.


The aim of the present study was to propose and test empirical models of homework emotion management at the secondary school level. These models differ with respect to the specific predicator variables the models include and the level of these variables. Model 1 included three student-level variables (i.e., gender, parent education, and self-reported grade). Girls are found to expend more effort to regulate their emotion in literature on emotion regulation in general (e.g., McRae et al., 2008; Morris et al., 2007), and in previous studies on homework in particular (e.g., Xu, 2005a; Xu & Corno, 2006). Self-reported grade was used as a proxy variable for student ability as noted in the literature on emotion regulation and volitional control (e.g., Kuhl & Kraska, 1989; Pekrun, 2006). Parent education as a variable that may influence homework emotion management has been suggested by the literature on the role of familiar influences on emotion regulation (e.g., Morris et al., 2007; Raver, 2004). Although no predication is suggested in the literature regarding student ability and parent education, it was important to control for these variables in the present study.


Model 2 introduced two additional student-level variables relating to adult monitoring (i.e., family help and teacher feedback) in order to gain an impression of how much variance these two variables explain above and beyond the controlling variables in Model 1. The inclusion of family help and teacher feedback in Model 2 has been informed by theoretical frameworks on the positive influence of significant others in emotion regulation in general (e.g., Diamond & Aspinwall, 2003; Eisenberg et al., 2004; Larson & Brown, 2007), and in previous studies on homework in particular (e.g., Trautwein et al., 2006; Xu & Corno, 2006).


Model 3 incorporated six additional student-level variables relating to the role of students in the homework process (i.e., reasons for doing homework, arranging the environment, managing time, and monitoring motivation). In line with theoretical frameworks on the role of intentions in emotion regulation (e.g., Cole et al., 2004; Eisenberg & Spinrad, 2004) and previous studies on homework (e.g., Xu, 2005a), it was hypothesized that reasons for doing homework were positively associated with homework emotion management. Meanwhile, informed by Gross’s (1998) model on the role of situation selection and modification, as well as by dynamic, component systems theory regarding the importance of the time dimension in emotion regulation (Op ’t Eynde & Turner, 2006), it was hypothesized that arranging the environment and managing time were positively related to homework emotion management. It was further hypothesized that monitoring motivation is positively related to homework emotion management, as the theoretical framework on volitional control suggests that motivation control strategies may be positively associated with emotion control strategies (e.g., Corno, 1993; Husman et al., 2000; Kuhl, 1985).


Finally, Model 4 incorporated three variables at the class level: (a) grade level, (b) parent education (i.e., aggregation of parent education at the class level), and (c) teacher feedback (i.e., students’ shared assessment of teachers’ homework feedback). It is important to incorporate these three variables as class-level variables, since (a) individuals may increasingly learn to make greater use of emotion regulation strategies (e.g., Eisenberg & Spinrad, 2004; Morris et al., 2007) and (b) individuals’ use of these strategies may be influenced by social and academic contexts of doing homework (Corno & Mandinach, 2004), including peer, parent, and teacher influences at the class level (e.g., norm, expectation, and affective engagement in homework).


METHOD


PARTICIPANTS


To address the concern that homework studies have often focused on middle-class Caucasian students (e.g., Cooper, Lindsay, Nye, & Greathouse, 1998; Xu, 2005b), the present study made a conscious effort to recruit students from diverse cultural and socioeconomic backgrounds. Accordingly, school districts were chosen based on the criteria that these districts contained a diverse student body. The superintendents in these districts were contacted first to secure their permission to conduct this study. The principals and teachers were then asked to send parental consent forms home to seek parental approval. Following that, the teachers administered the survey in their classrooms during a normal school week.


The participants were 1,895 students from 111 classes in the southeastern United States, including 1,046 eighth graders from 63 classes and 849 11th graders from 48 classes. Of the participants in this sample, 46.4% were male, and 53.6% were female. The sample was 55.2% Caucasian, 37.7% African American, 3.5% multiracial, 1.3% Latino, 1.2% Native American, and 1.1% Asian American. Among this sample, 34.8% received free meals. The survey response rate was 88.9% (i.e., for all students who were present during the survey administration, and with parental consent and student assent). The racial/minority breakdown of the students who responded to this survey was comparable to that of these school districts.


HOMEWORK SURVEY

 

The participants were asked about their level of academic achievement, by selecting one choice that best described their grade average for all their subjects taken during the previous 2 years. This item was adapted from the National Education Longitudinal Study of 1988 (NELS: 88). Possible responses included the following: 1 (below D), 2 (mostly D’s), 3 (mostly C’s), 4 (mostly B’s), and 5 (mostly A’s). The only difference was that, in NELS: 88, the students reported their grades in specific subjects (e.g., English), whereas the students in this survey reported their average grades, including all their school subjects. Concerning the validity of students’ self-reported grades, a recent study (Dickhaeuser & Plenter, 2005) showed very strong correlations (r = .90) between self-reported and actual academic performance (regardless of gender or achievement level), using 866 students in grades 7 and 8.


Two items asked about parent education (one for the father/guardian, and another for the mother/guardian). Possible responses for both items included the following: less than high school (scored 6 years), some high school (scored 10 years), high school graduate (scored 12 years), some college or 2-year college graduate (scored 14 years), 4-year college graduate (scored 16 years), some graduate school (scored 17 years), and graduate degree (scored 19 years). A composite variable for parent education was then constructed by averaging the educational levels for the parents/guardians. In the case of single parent/guardian families, the responses to either the father/guardian or mother/guardian were used for parent education. In addition, students were asked to indicate the frequency of family homework help, ranging from 1 (never), 2 (rarely), 3 (sometimes), 4 (often) to 5 (routinely).


Several multi-item scales were used for the present study (see Table 1). Some items were adapted from standard instruments (e.g., Cooper et al., 1998) or based on related literature (e.g., Warton, 2001), whereas others were derived from previously validated measures (Xu, 2008b, 2008c, 2010).


Table 1.  Alpha Reliability of Multi-Item Scales


Scales

Items

α (CI)

Teacher feedbacka

How much of your assigned homework is discussed in class?

.79 (.77, .80)

How much of your assigned homework is collected by teachers?

How much of your assigned homework is checked by teachers?

How much of your assigned homework is graded by teachers?

How much of your assigned homework is counted in your overall grade?

Peer-oriented   reasonsb

Doing homework brings you approval from classmates

.78 (.77, .80)

Doing homework gives you opportunities to work with classmates

Doing homework gives you opportunities to learn from classmates

Adult-oriented reasonsb

Doing homework brings you teacher approval

.79 (.77, .80)

Doing homework brings you family approval

Doing homework makes your family more aware of your learning at school

Learning-oriented reasonsb

Doing homework helps you understand what’s going on in class

.89 (.89, .90)

Doing homework helps you learn how to manage your time

Doing homework gives you opportunities to practice skills from class lessons

Doing homework helps you develop a sense of responsibility

Doing homework helps you learn to work independently

Doing homework helps you develop good discipline

Doing homework helps you learn study skills

Doing homework helps you get a good grade

Doing homework helps you prepare for the next lesson


Scales

Items

α (CI)

Arranging the environmentc

Locate the materials I need for my homework

.75 (.73, .76)

Find a quiet area

Remove things from the table

Make enough space for me to work

Turn off the TV

Managing timec

Set priority and plan ahead

.73 (.71, .75)

Keep track of what remains to be done

Remind myself of the available remaining time

Tell myself to work more quickly when I lag behind

Monitoring motivationc

Find ways to make homework more interesting

.83 (.82, .84)

Praise myself for good effort

Praise myself for good work

Reassure myself that I am able to do homework when I feel it is too hard

Emotion managementc

Tell myself not to be bothered with previous mistakes

.71 (.68, .73)

Tell myself to calm down

Cheer myself up by telling myself that I can do it

Homework  

   completion

How much of your assigned homework do you usually completea?

.71 (.68, .74)

How often do you come to class without your homeworkcd?

Note. The 95% confidence intervals (CIs) for the coefficient alpha were calculated using a method employing the central F distribution (see Fan & Thompson, 2001).

aResponses were 1 (none), 2 (some), 3 (about half), 4 (most), and 5 (all). bResponses were 1 (strongly disagree), 2 (disagree), 3 (agree), and 4 (strongly agree). cResponses were 1 (never), 2 (rarely), 3 (sometimes), 4 (often), and 5 (routinely). dThe item was reverse scored.


Teacher Feedback


Five items were used to assess the extent to which teachers provide homework feedback (α = .79), informed by related literature (Murphy et al., 1987; Trautwein, Koller, Schmitz, & Baumert, 2002; Trautwein et al., 2006). These items measured how much of the assigned homework was monitored (e.g., discussed, collected, and checked).


Reasons for Doing Homework


Three subscales were employed to assess reasons for doing homework, based on the recently validated homework purpose scale through the use of confirmatory factor analysis (Xu, 2010). Three items were used to measure peer-oriented reasons (α = .78), relating to working with and seeking approval from peers. Three items were used to measure adult-oriented reasons (α = .79), relating to seeking approval from parents and teachers. Nine items were used to measure learning-oriented reasons (α = .89), relating to reinforcing school learning and developing a sense of responsibility.


Arranging the Environment


Arranging the environment included five items to assess student initiative in arranging the work environment (Xu, 2008b, 2008c). These items ranged from finding a quiet space to locating the materials that are needed to do homework (α = .75).


Managing Time  


Managing time included four items to assess student initiative in budgeting time to meet deadlines (Xu, 2008b, 2008c). These items ranged from setting priorities and planning ahead to keeping track of the available remaining time (α = .73).


Monitoring Motivation


Monitoring motivation refers to generating thought that “increases the strength of the current intention by selectively processing information that supports it” (Kuhl, 1985, p. 107), something that “individuals purposefully act to initiate, maintain, or supplement their willingness to start, to provide work toward, or to complete a particular activity or goal” (Wolters, 2003, p. 190). Monitoring motivation included four items to assess student initiative in maintaining or enhancing homework intentions (Xu, 2008b, 2008c), ranging from making homework more interesting to reassuring themselves that they can complete their homework successfully (α = .83).


Managing Homework Emotion  


As homework typically elicits unpleasant emotional responses, regardless of age, gender, and academic performance (e.g., Leone & Richards, 1989; Verma et al., 2002), homework emotion management focuses on strategies that students use to regulate their emotional states while doing homework. The development of this scale was informed by empirical studies in homework (e.g., Corno & Xu, 2004; Xu & Corno, 1998) and in emotional development in adolescence (e.g., Larson & Brown, 2007), as well as a theoretical framework on volitional control (e.g., Corno, 1986, 1993; Kuhl, 1985, 1987). This scale consisted of three items (α = .71), ranging from down-regulating unpleasant emotions (e.g., “Tell myself not to be bothered with previous mistakes”) to up-regulating positive emotions (e.g., “Cheer myself up by telling myself that I can do it”).


The above four scales relating to student initiative (i.e., arranging the environment, managing time, monitoring motivation, and managing homework emotion) were derived from previously validated measures (Xu, 2008b, 2008c). The scales were found to be empirically distinguishable (i.e., factorially distinct) for high school students (Xu, 2008a) and middle school students (Xu, 2008c).


Recently, domain specificity (content, task, activity, or context specific) and domain generality have been discussed relating to a number of psychological constructs (e.g., interest, metacognitive skills, and self-concept). Some studies support domain specificity (e.g., Dow & Mayer, 2004), whereas others support domain generality (e.g., Veenman, Wilhelm, Beishuizen, 2004). Relating to academic emotions, two studies by Goetz and his colleagues (Goetz, Frenzel, Pekrun, & Hall, 2006; Goetz, Frenzel, Pekrun, Hall, & Ludtke, 2007) suggested that certain academic emotions may be organized along domain-specific lines. Yet, as the studies stated, one limitation of existing research on domain specificity (including their studies) concerns the definition of what constitutes a domain (e.g., subject matter or classroom context). Indeed, in research on interest, the term of domain is broadly defined as particular classes of objects, events, or ideas (Hidi & Renninger, 2006). Consequently, Krapp (2005) proposed that “in empirical studies, an interest can be conceptualized at different levels of specification” (p. 382).


In addition, there is a theoretical distinction between emotion and emotion regulation (Campos et al., 2004), mirroring the distinction between individuals’ cognitive processing and their regulation of cognition (Pintrich, Wolters, & Baxter, 2000) and between individuals’ motivation and their regulation of motivation (Wolters, 2003). The distinction between emotion and emotion regulation was to some extent illustrated in one recent study (Tamir, John, Srivastava, & Gross, 2007), which showed that “the associations between implicit emotion theories and all emotion regulation variables remained unchanged even after controlling for emotional intensity” (p. 741). Thus, individuals with very strong emotions are not necessarily more or less likely to regulate their emotions. The findings that academic emotions may be organized along domain-specific lines (Goetz et al., 2006; Goetz et al., 2007) also do not necessarily imply a difference in emotion regulation by domain. On the contrary, relating to emotion regulation, one emerging consensus is that there may be domain-general aspects of executive control (e.g., set shifting, updating and monitoring, and response inhibition) (e.g., Gross & Thompson, 2007; Miyake, Friedman, Emerson, Witzki, & Howerter, 2000).


Consequently, there is merit in conceptualizing homework as one of the important activities in students’ life contexts, particularly as we have no empirical evidence from previous studies implying a difference in homework emotion management relating to homework assignments in different school subjects. From a sociocultural perspective, activity (e.g., homework) is a fundamental concept reflecting the way tasks are interpreted by students and the engagement (e.g., affective and cognitive) that surrounds task completion (Corno & Mandinach, 2004; Wenger, 1998). This perspective is also in line with the view that an activity setting provides the context of affordances and tools for adolescents to learn through conscious observation how to manage emotional episodes (Larson & Brown, 2007).


STATISTICAL ANALYSES


Hierarchical linear modeling (HLM) allows for the inclusion of variables at multiple levels while taking into account the nonindependence of observations by addressing the variability associated with each level of nesting (Raudenbush & Bryk, 2002; Snijders & Bosker, 1999). Multilevel analyses were conducted using HLM 6 (Raudenbush, Bryk, Cheong, Congdon, & Toit, 2004). As the HLM 6 output does not report standardized regression coefficients, I standardized all continuous variables to enhance the interpretability of the resulting regression coefficients. Thus, the regression weights for all variables (except the dummy-coded variables, including gender and grade level) are approximately comparable with the standardized weights that result from multiple-regression procedures (Trautwein et al., 2006).


Model 1 included three student-level variables relating to student and family characteristics (i.e., gender, parent education, and self-reported grade). Model 2 introduced two student-level variables relating to adult monitoring (i.e., family help and teacher feedback). Model 3 incorporated six additional student-level variables relating to student attitude (i.e., peer-, adult-, and learning-oriented reasons) and student initiative (i.e., arranging the environment, managing time, and monitoring motivation).


In educational psychology, the aggregation of student-level variables to form an indicator of the classroom environment is a standard procedure for obtaining general information about the learning environment (Ryan, Gheen, & Midgley, 1998; Trautwein et al., 2006; Xu, 2008a). Scores aggregated to the classroom level reflect shared perception of the classroom environment (e.g., social and academic contexts of doing homework). In the present study, teacher feedback was aggregated at the class level to form an index of students’ shared assessment of teacher feedback. Similarly, parent education was aggregated at the class level to form an index of parent education at the class level. These two variables (not restandardized), along with grade level, were introduced as three class-level variables in Model 4. The justification for incorporating teacher feedback as a student-level variable and a class-level variable is that students’ shared assessment of their teachers’ feedback in a given class might have an effect on homework emotion management above and beyond the effect of teacher feedback at the student level. Likewise, the reason for incorporating parent education as a student-level variable and a class-level variable is that parent education in a given class might have an effect on homework emotion management above and beyond the effect of parent education at the student level.


All models reported are random-intercept models. The random part of the intercept was freely estimated to reflect between-classroom differences in homework emotion management. As I had no a priori hypotheses concerning between-classroom differences in the predictive power of the predictor variables, I did not estimate the random parts of the slopes. Restricted maximum likelihood estimation was used in all models, and all predictor variables were introduced as uncentered variables. There were a few missing values for variables included in the present study, ranging from 0.00% to 7.23% (with a mean of 2.58%). These missing values were imputed using the expectation-maximization (EM) in SPSS 13.0.


RESULTS


MULTILEVEL ANALYSES


Table 2 presents the descriptive statistics relating to the study variables. It also includes zero-order correlations among independent variables and homework emotion management. Homework emotion management was found to correlate significantly with all of the independent variables, except grade level, parent education at the student level, and parent education at the class level.



Table 2. Descriptive Statistics and Pearson Correlations


Variables

M

SD

1

2

3

4

5

6

7

8

9

10

11

12

13

14

 1. Grade level (class) (8 = 0, 11= 1)

    .43

 .50

----

             

 2. Gender (girl = 0, boy = 1)

    .46

 .50

 .00

----

            

 3. Parent education

13.72

 2.63

-.11**

 .04

----

           

 4. Parent education (class)

13.64

 1.00

-.29**

-.01

.38**

----

          

 5. Self-reported grade

 3.80

.88

-.01

 .15**

 .15**

 .13**

----

         

 6. Family homework help

 2.42

 1.32

-.29**

-.02

 .13**

 .09**

-.07**

----

        

 7. Teacher feedback

 3.57

.84

-.15**

-.03

 .04

-.02

-.02

.19**

----

       

 8. Teacher feedback (class)

 3.60

.35

-.37**

 .01

-.02

-.05*

-.12**

.20**

.40**

----

      

 9. Peer-oriented reasons

 2.32

.73

 .04

-.10**

 .00

-.06*

 .01

.20**

.20**

.09**

----

     

10. Adult-oriented reasons

 2.72

.73

-.04

-.12**

 .05*

-.04

 .05*

.21**

.30**

.16**

.56**

----

    

11. Learning-oriented reasons

2.83

.60

 .06**

-.18**

 .03

-.06**

 .10**

.16**

.32**

.13**

.59**

.66**

----

   

12. Arranging environment

 3.16

.88

-.07**

-.14**

 .05*

 .02

 .15**

.22**

.25**

.12**

.22**

.32**

.42**

----

  

13. Managing time

 2.94

.88

-.06*

-.10**

 .08**

 .07**

 .21**

.18**

.21**

.10**

.24**

.32**

.38**

.59**

----

 

14. Monitoring motivation

 2.71

.97

-.08**

-.13**

 .09**

 .07**

 .07**

.25**

.22**

.14**

.33**

.36**

.42**

.47**

.55**

----

15. Emotion management

 2.60

.93

-.01

-.17**

 .04

 .02

 .11**

.19**

.22**

.09**

.30**

.32**

.38**

.42**

.48**

.61**


Note. N varies from 1,884 to 1,895.  

* p < . 05.  ** p < .01.




The fully unconditional model was conducted to partition the variance in homework emotion management into between-class and within-class components. The results indicated that most of the variance occurred at the student level, with 2.3% of the variance in homework emotion management located at the class level.


As using multilevel modeling to control for cluster effects is justified even when intraclass correlations are as low as .02 (Kreft & de Leeuw, 1998; von Secker, 2002), three student-level variables relating to student and family characteristics—gender, parent education, and self-reported grade—were included in Model 1. Together, these variables explained 4.4% of the variance in homework emotion management at the student level (see Table 3).


Table 3. Predicting Homework Emotion Management: Findings of Multilevel Analyses



Model predictor

Model 1

Model 2

Model 3

Model 4

b

SE

b

SE

b

SE

b

SE

Student level

        
 

Gender (girl = 0, boy = 1)

 -.33**

.05

 -.30**

.05

 -.15**

.04

 -.15**

.04

 

Parent education

  .04

.02

   .01

.02

 -.02

.02

 -.01

.02

 

Self-reported grade

  .10**

.02

  .11**

.02

  .02

.02

  .02

.02

 

Family homework help

  

  .17**

.03

  .01

.02

  .02

.02

 

Teacher feedback

  

  .18**

.02

  .04*

.02

  .05*

.02

 

Peer-oriented reasons

    

  .06*

.02

  .05*

.03

 

Adult-oriented reasons

    

  .02

.03

  .02

.03

 

Learning-oriented reasons

    

  .03

.03

  .02

.03

 

Arranging the environment

    

  .07**

.03

  .08**

.03

 

Managing time

    

  .15**

.03

  .15**

.03

 

Monitoring motivation

    

  .44**

.02

  .44**

.02

Class level

        
 

Parent education

      

 -.01

.05

 

Teacher feedback

      

 -.03

.05

 

Grade level (8 = 0, 11= 1)

      

  .09*

.04

R2 individual level

.044

.109

.418

.418

R2 class level

.000

.000

.835

.880

R2 total

.032

.099

.428

.429

Note. N = 1,884 from 111 classes. b = unstandardized regression coefficient. SE = standard error of b. R2 = amount of explained variance.

* p < .05. ** p < .01.


Model 2 incorporated two additional student-level variables relating to homework monitoring by adults (i.e., family help and teacher feedback). These two variables explained an additional 6.5% of the variance in homework emotion management at the student level.


Model 3 incorporated six additional student-level variables relating to student attitude (i.e., peer-, adult-, and learning-oriented reasons) and student initiative (i.e., arranging the environment, managing time, and monitoring motivation). These variables explained an additional 30.9% of the variance in homework emotion management at the student level, as well as 83.5% of the variance in homework emotion management at the class level, above and beyond the previous variables included in Model 2.


In Model 4, three class-level variables—grade level, aggregated teacher feedback, and parent education—were entered. These variables accounted for additional 4.5% of the variance in homework emotion management at the class level.


Overall, the final model (Model 4) explained 41.8% of the variance in homework emotion management at the student level, 88.0% of the variance in homework emotion management at the class level, and 42.9% of the total variance in homework emotion management. As shown in Table 3, six student-level variables were found to have a statistically significant effect on homework emotion management. Homework emotion management was positively associated with monitoring motivation (b = .44, p < .01), managing time (b = .15, p < .01), arranging the environment (b = .08, p < .01), peer-oriented reasons (b = .05, p < .01), and teacher feedback (b = .05, p < .05). In addition, boys reported statistically significant lower scores in homework emotion management than did girls (b = -.15, p < .01).


At the class level, three variables served as predictors (i.e., grade level, aggregated teacher feedback, and parent education). Grade level was found to have a positive effect on homework emotion management (b = .09, p < .01), after all the other variables were controlled. Specifically, compared with eighth graders, 11th graders were more likely to take initiative in managing their emotion while doing homework.


FOLLOW-UP ANALYSES


As managing one’s unpleasant emotional states is crucial for successful academic performance (e.g., Corno & Kanfer, 1993; Pekrun, 2006), the main objective in the present study was to examine a range of variables that may influence homework emotion management. On the other hand, as research on the regulation of unpleasant emotion has hypothesized that more regulation is better regulation (Bridges, Denham, & Ganiban, 2004), it is important to examine whether this hypothesis can be empirically tested in the case of homework.


For this purpose, the students were asked two additional questions, adapted from NELS: 88 and studies by Cooper and his colleagues (e.g., Cooper et al., 1998). Students were asked to indicate the amount of homework completion and the frequency of coming to class without homework (see Table 1). These two items were then combined in the homework completion scale (with the second item reverse scored). The alpha reliability for the scale was .71.


Given the relatively small intraclass correlation (.02), I conducted structural equation modeling (SEM) analyses to test the hypothesized causal model: (a) Five latent variables (i.e., arranging the environment, managing time, monitoring motivation, peer-oriented reasons, and teacher feedback) were assumed to predict homework emotion management, as informed by the multilevel analyses, and (b) homework emotion management was further assumed to predict homework completion. Model fit was evaluated with EQS version 6.1 (Bentler, 2006) based on several criteria, including comparative fit index (CFI), root mean square error of approximation (RMSEA), and standardized root mean square residual (SRMR). In terms of CFI, a value of .90 or greater was suggested as evidence of adequate fit, which was later changed to .95 (Hu & Bentler, 1999). Recently, the value of .95 has been considered too restrictive (e.g., Marsh, Hau, & Wen, 2004). Byrne (2008) suggested that CFI values in the range of .92 through .94 may be reasonable indicators of a good model fit. RMSEA values less than .05 indicate a good fit, with values as high as .08 representing reasonable errors of approximation in the population (Byrne, 2008). SRMR values less than .08 indicate a well-fitting model (Hu & Bentler, 1999).


Results of the SEM showed that the model provided an adequate fit to the data (CFI = .92; SRMR = .060; RMSEA = .049; 90% C.I. = .047, .052). As was hypothesized, homework emotion management was positively related to monitoring motivation (β = .43), managing time (β = .34), peer-oriented reasons (β = .12), and teacher feedback (β = .07). However, the path from arranging the environment to homework emotion management did not reach significance in this model (β = .09, effect/standard error of effect = 1.44).


Figure 1.  Standardized path coefficients for five latent variables (i.e., arranging the environment, managing time, monitoring motivation, peer-oriented reasons, and teacher feedback) on homework emotion management and homework completion


[39_16062.htm_g/00002.jpg]

* p < .05.


Of primary interest is the path from homework emotion management to homework completion. As was hypothesized, this path was statistically significant (β = .43), indicating that each standard deviation change in homework emotion management will result in .43 of a standard deviation change in homework completion. This finding suggests that homework emotion management can have a powerful effect on homework completion.


In addition, I conducted SEM analyses to test for the invariance across gender (boys vs. girls). All factor loadings and all structural paths were constrained equally across gender. Given the rigor of the constraints, the findings revealed an adequate fitting multigroup model (CFI = .92; SRMR = .065; RMSEA = .049; 90% C.I. = .047, .052). The Lagrange multiplier (LM) test of equality constraints indicated that four factor loadings were noninvariant across gender (i.e., four items relating to arranging the environment, monitoring motivation, teacher feedback, and homework emotion management). With this exception, all paths in the hypothesized causal model were found to be equivalent across gender.


DISCUSSION


The present study examined models of homework emotion management at the secondary school level. Results from the multilevel analyses revealed that most of the variance in homework emotion management occurred at the student level, with grade level as the only significant predictor at the class level. Results further revealed that six student-level variables in the final model (Model 4) contributed to the explanation of the variation in homework emotion management, including gender, teacher feedback, peer-oriented reasons, arranging the environment, managing time, and monitoring motivation.


What do we make of the finding that grade level was positively associated with homework emotion management? This finding is in line with research and theory on emotion regulation that hold that emotion regulation increases with age (e.g., Eisenberg & Morris, 2002; Eisenberg & Spinrad, 2004). On the other hand, this finding is inconsistent with previous findings that there was no statistically significant difference across grade levels (Xu, 2005a; Xu & Corno, 2006). Possible explanations are that (a) the grade level used for comparison in these studies is over a smaller grade span—Grade 7 vs. Grade 8 in one study (Xu & Corno, 2006) and Grade 9 vs. Grade 10 in another study (Xu, 2005a), (b) these studies fail to control other variables that may influence homework emotion management, and (c) they may not have sufficient statistical power to be able to show a significant effect by grade level. Thus, by examining homework emotion management at the eighth- and 11th-grade levels while controlling other important variables at the student and class level, the present study provides a clearer picture of homework emotion management and grade level.


As most of the variance in homework emotion management occurred at the student level rather than at the class level, homework emotion management was largely a function of individual student characteristics and experiences (i.e., background variables, adult monitoring, and student attitude and initiative). With respect to student-level variables, the finding from multilevel analyses that girls were more likely to monitor their emotion while doing homework is in line with findings from previous studies (Xu, 2005a; Xu & Corno, 2006). This finding is also in line with the literature on emotion regulation that holds that girls, compared with boys, typically better regulate their emotion (e.g., Morris et al., 2007) and use more volitional strategies (e.g., Husman et al., 2000).


In terms of adult monitoring, the effect of homework help was no longer statistically significant when variables on student attitude and initiative were included. Meanwhile, the effect of teacher feedback decreased from Models 2 to 3, but remained statistically significant. In line with the finding that student attitudes play an increasingly important role in students’ homework behavior (Cooper et al., 1998), these findings suggest that the effects of adult monitoring are partly mediated by the role of students in the homework process.


There has been a tacit understanding regarding the role of adult monitoring of homework in general, with homework emotion management in particular. Yet adult monitoring has rarely been empirically tested. In a recent review of parental involvement in children’s academic lives, Pomerantz, Moorman, and Litwack (2007) hypothesized that parents’ involvement may become less necessary as children progress through the school system. Similarly, the standard developmental view on emotion regulation hypothesizes that children initially rely on interactions with adults to regulate emotions, and children progressively internalize these abilities as the children mature (Diamond & Aspinwall, 2003). Yet very little empirical evidence is available about adults’ role in socializing emotion regulation during adolescence (Morris et al., 2007). Thus, this finding regarding the mediating role of adult monitoring is highly important, particularly as this effect has been demonstrated in a relatively large sample of students from diverse backgrounds at different grade levels, through the use of hierarchical analyses.


In line with previous findings (Xu, 2005a, 2005b), the results from Model 3 provided empirical support for the theoretical claims of the importance of goals and intentions in emotion regulation (e.g., Cole et al., 2004; Op ’t Eynde & Turner, 2006). Specifically, these results revealed that homework emotion management was positively associated with peer-oriented reasons (unlike adult- and learning-oriented reasons). One possible explanation is that students with higher scores in peer-oriented reasons are more likely to do homework with their peers. Completing homework with peers, compared with completing homework by themselves or with family members, may result in relatively more positive subjective experiences such as arousal and affect (Leone & Richards, 1989; Warton, 2001). Consequently, students with higher scores in peer-oriented reasons may take more initiative to manage homework emotion.


Another important contribution of the present study concerns the important role of student initiative on homework emotion management. Although the present study is the first to link student initiative to homework emotion management, these findings are in line with the literature on emotion regulation. For example, the finding that managing time was positively related to homework emotion management provides empirical support to the hypothesis that time management strategies play a vital role in emotion regulation (Op ’t Eynde & Turner, 2006).


The finding that monitoring homework motivation was positively associated with homework emotion management is in line with (a) recent discussion that motivation may influence affective experiences (e.g., Linnenbrink, 2006; Pekrun, 2006) and (b) the literature on volitional control that motivation control strategies may be positively associated with emotion control strategies (e.g., Corno, 1993; Husman et al., 2000; Kuhl, 1985). The present study moves one step forward, suggesting that monitoring motivation and managing time play a key role in homework emotion management (compared with other variables included in the present study), as evident from both multilevel analyses and follow-up SEM analyses. Taken together, these findings suggest that there is a need to conceptualize these two variables (i.e., monitoring motivation and managing time) in the process of emotion regulation in general (e.g., Cross’s model), and in homework emotion management in particular.


The present study further examined the hypothesis that homework emotion management may predict homework completion, one of the important outcome variables in the homework process (e.g., Cooper et al., 1998; Xu, 2005b). Results suggest that homework emotion management can have a powerful effect on homework completion. Consequently, it would be important to conceptualize homework emotion management as one of the important variables in Cooper’s (1989) model of the homework process. Specifically, it would be important to conceptualize homework emotion management as a variable that may be influenced by other variables (e.g., peer-oriented reasons, managing time, monitoring motivation, and teacher feedback), as well as a variable that may, in turn, influence other important outcome variables in the homework process such as homework completion.


LIMITATIONS AND FUTURE RESEARCH


It is important to note that the findings of the present investigation were based on a relatively large sample of students from diverse backgrounds. The percentage of the students who received free meals (34.8%), for example, was close to the national average (32.3%) (Common Core of Data, 2005–2006). In addition, self-report is a valuable and often irreplaceable source of information about emotions (Kouzma & Kennedy, 2002; Youngstrom & Green, 2003). This is particularly so in the case of homework, as direct observations of homework emotion management at home (e.g., at the kitchen table or in children’s bedrooms) by trained observers or their parents are intrusive and time-consuming, thereby restricting the duration of homework observation and the number of students whose homework practices can be examined. Moreover, compared with observers or parents, children have certain advantages as observers of their own homework emotions, as some aspects of children’s emotional responses while doing homework are not easily observable. Thus, children’s reports of their responses are often more veridical than those made by observers or the children’s parents.


On the other hand, findings based on self-reported data may be subject to social desirability bias (e.g., Fowler, 1995). Students may want to present themselves in a more favorable light (e.g., underreporting family help). Although it is difficult to determine the exact effects of self-reported data on these findings, some evidence suggests that social desirability bias is unlikely to be a major concern for the present study. For example, the percentage of eighth graders who reported that they received family help in the present study (73%) was close to that found in a nationally representative sample of eighth graders (71%) in the National Education Longitudinal Study of 1988 (Horn & West, 1992).


The items in the homework emotion management scale focus on self-instruction in down-regulating unpleasant emotions and up-regulating positive emotions. It would be interesting to incorporate additional items relating to other strategies that students may use to regulate their emotions—such as cognitive reappraisal (Gross, 2002; McRae et al., 2008)—in future studies on homework emotion management.


Future research would benefit from incorporating other data sources (e.g., a diary study, think-aloud protocols, stimulated video recall, and trace logs in computer-assisted environments) to better capture ongoing dynamic processes of homework emotion management. It would be informative to conduct qualitative studies to better understand the nature of homework emotion management in cross-cultural settings, as achievement-related emotional experiences (e.g., anxiety, anger, and pride) may be influenced by cultural values (Frenzel, Thrash, Pekrun, & Goetz, 2007; Op ’t Eynde & Turner, 2006; Pekrun, 2006).


Although the present study is the first to link homework emotion management to a broad spectrum of variables at the student level and class level, and these findings are in line with research and theory on emotion regulation, they are based on a cross-sectional survey (rather than repeated measures at different time points). Consequently, there is a need to conduct longitudinal studies that follow cohorts of students to examine how they manage homework emotion over time. Meanwhile, although the follow-up analyses revealed that homework emotion management was positively related to homework completion, there is a need to link homework emotion management to major homework outcome variables in Cooper’s (1989) model, including homework performance and academic achievement in a longitudinal design.


Finally, although much care was taken to control for possible confounding variables (i.e., informed by research and theory on emotion regulation), other predictor variables might have had an effect on homework emotion management had they been included. This is particularly the case for homework, as it is influenced by more factors than most other instructional activities (Cooper, 2001). Although there are multiple barriers to random assignments in applied settings in general (Shadish, Cook, & Campbell, 2002) and with homework intervention in particular (Cooper, Robinson, & Patall, 2006), controlled experiments are needed to better address the issue of causation (Pekrun, 2006; Tamir et al., 2007). For example, there is a need to test the causal hypotheses more directly by experimentally manipulating student initiative (e.g., managing time or monitoring motivation) and by testing the effects of such manipulations on subsequent homework emotion management.


EDUCATIONAL IMPLICATIONS


The findings that the effects of adult monitoring (teacher feedback and family help) were partly mediated by the role of students suggest that teachers and parents can exert their influence indirectly on homework emotion management at the secondary school level. This is an important message for families from diverse backgrounds, as the present study implies that the kind of direction parents give to children matters even if parents do not have a higher education, an observation that is in line with previous qualitative findings (e.g., McCaslin & Murdock, 1991) and quantitative findings (e.g., Xu, 2005a). Meanwhile, the gender difference relating to homework emotion management suggests that teachers and parents need to pay more attention to boys doing homework during the secondary school years, as families of secondary school students tend to be more involved in girls’ homework than that of boys (Cooper, Lindsay, & Nye, 2000; Xu, 2005b).


In the context of studies with young adults, Gross, Richards, and John (2006) found that, for many younger adults, thinking explicitly about regulating their own emotion regulation was a novel experience. Thus, it may be time, the authors argued, to use contemporary research on emotion regulation to inform and enrich curricula in high school and college that typically do not include information on emotion and emotion regulation. This argument is quite relevant in the case of homework, as the present findings suggest that students’ own initiative (e.g., monitoring motivation and managing time) plays a vital role in homework emotion management.


Thus, there is a critical need for secondary schools to strategically engage students in the homework process. One way to do this would be to listen to students’ own voices as to how the students’ emotional sequences unfold while doing homework and how these sequences are influenced by other factors in students’ lives. Specifically, it would be important to listen to students talk about their coping strategies or worked examples in managing homework emotion (e.g., positive self-talk), as well as suggestions about what the students’ schools or families might do to help the students to cope with unpleasant homework emotion. These voices, along with recent work on emotion regulation, such as those mentioned in the present study, would provide an important basis for school counselors to use in discussion with students about how to better handle homework emotion. Equipped with such information, parents and teachers can provide more meaningful and relevant support for efforts at homework emotion management. This, in turn, will encourage students to play a more constructive role in managing homework emotion (e.g., developing and experimenting with their implicit theories about beneficial conditions for dealing with homework emotion), as homework provides recurring opportunities for students to experience and observe a range of emotional episodes and their contingencies. Finally, as schooling is an emotionally laden process for students, teachers, and parents (Larson & Brown, 2007; Schutz et al., 2006), a better understanding of how students learn to manage homework emotion can provide a springboard for new ideas about emotion management in other important aspects of students’ lives (e.g., test taking, emotional events within the classroom, peer relationships, and youth sports).


Acknowledgments


I would like to thank Editor Lyn Corno and TCR reviewers for their insightful and constructive comments.


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Cite This Article as: Teachers College Record Volume 113 Number 3, 2011, p. 529-560
https://www.tcrecord.org ID Number: 16062, Date Accessed: 10/26/2021 5:51:24 AM

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