Predicting Homework Distraction at the Secondary School Level: A Multilevel Analysis
by Jianzhong Xu - 2010
Background: Students continue to struggle with homework distraction well into the secondary school years. Recently, the concern over homework distraction has been growing, as new electronic media have offered diverse and nearly ubiquitous forms of diversion to students while they are doing homework. It is surprising to note, however, that a systematic examination of a broad spectrum of factors that contribute to homework distraction is noticeably absent from much contemporary literature. Thus, there is a critical need to examine a range of variables that may influence homework distraction and, consequently, what implications might be drawn from this line of research to help students better handle homework distraction.
Purpose: The aim of the present study is to propose and test empirical models of variables posited to predict homework distraction at the secondary school level, with the models informed by (a) relevant theoretical approaches (e.g., volitional control) and (b) findings from homework research that alluded to a number of factors that may influence homework distraction.
Research Design: The study reported here used cross-sectional survey data.
Participants: The participants were 1,800 students from 97 classes in the southeastern United States: 969 eighth graders from 52 classes, and 831 eleventh graders from 45 classes.
Results: Results from the multilevel analyses revealed that most of the variance in homework distraction occurred at the student level, with grade level as the only significant predictor at the class level. Findings further revealed that at the student level, the variation in homework distraction was influenced by gender, self-reported grades, the context of doing homework at home, and student attitudes toward homework.
Completing homework is a complicated, multifaceted process (Corno, 1996; Warton, 2001) influenced by more factors than any other instructional activities (H. Cooper, 2001). Not surprisingly, it has been a perennial topic of debate in education (Gill & Schlossman, 2000, 2004), and policy makers, educators, and interested observers have a tendency to make generalized, and often passionate and polemical, statements about what it is and what it should achieve (Gill & Schlossman, 2004; Warton). Recent heated debate about the case for and against homework is an example of this phenomenon (i.e., regarding the role of homework in childrens schooling; e.g., Bennett & Kalish, 2006; Kohn, 2006; Kralovec & Buell, 2000; Loveless, 2003; Marzano & Pickering, 2007; Public Agenda, 2000; Trautwein & Koller, 2003).
Although public attitudes toward homework have periodically shifted back and forth over the past 100 years (Gill & Schlossman, 2000, 2004), homework continues to be a widespread educational activity across cultures, ages, and ability levels (Warton, 2001); for most school-age children, it is an important part of their daily routine (H. Cooper, Robinson, & Patall, 2006; Corno, 2000). Typically defined as tasks assigned to students by school teachers that are meant to be carried out during non-school hours (H. Cooper, 1989, p. 7), homework brings learning to students daily lives, where it coexists with multiple competing activities. Not unexpectedly, students encounter an array of distractions associated with following through on homework. Indeed, they continue to struggle with homework distraction well into the secondary school years (e.g., Benson, 1988; Pool, Koolstra, & van der Voort, 2003a, 2003b; Wober, 1992; Xu, 2004, 2007; Xu & Corno, 2003). Recently, the concern over homework distraction has been growing, as new electronic media have offered diverse and nearly ubiquitous forms of diversion to students while they do homework (Foehr, 2006; Wallis, 2006; Warton; Xu, 2008b, 2008c; Xu & Corno, 2003).
It is surprising to note, however, that a systematic examination of a broad spectrum of factors that contribute to homework distraction is noticeably absent from much contemporary literature. Such an absence is surprising because (a) handling distraction is conceptualized as one important component of volitional control (Corno, 1994; Heckhausen, 1991; Kuhl & Fuhrmann, 1998), and (b) recent research on learning and memory suggests that distraction affects the way people learn, resulting in the acquisition of knowledge that is less flexibly applied in new situations (Foerde, Knowlton, & Poldrack, 2006; Schmid, 2006).
Thus, there is a critical need to examine a range of variables that may influence homework distraction and, consequently, what implications might be drawn from this line of research to help students better handle homework distraction. This line of research is particularly important at the secondary school level because homework has been found to be more strongly associated with academic achievement for secondary school students than elementary school students (H. Cooper, 1989; H. Cooper et al., 2006) and because secondary school students tend to have more autonomy and access to a wide array of media in their homes and bedrooms (e.g., televisions, computers, and video games) than elementary school students (Roberts, Foehr, & Rideout, 2005).
Distraction is known to occur frequently during goal-directed academic learning activities (Bembenutty & Karabenick, 2004; McCann & Turner, 2004; Schmitz & Wiese, 2006; Wolters, 2003). One theoretical approach that taps into distraction is self-regulated learning, particularly from the perspective of volitional control (Boekaerts & Corno, 2005; Corno, 1994, 2001, 2004; Heckhausen & Kuhl, 1985; Kuhl, 1984, 2000; Van Eerde, 2000; Winne, 2004; Wolters, 2003). Volitional control is concerned centrally with issues of implementation (i.e., an implementation mindset) that occur after the goal is set, to protect the intention to pursue that goal in the face of potential distraction or other obstacles (Boekaerts & Corno; Corno, 2001, 2004; Kuhl, 1985). Not surprisingly, handling distraction is viewed as a critical component of volitional control, along with other components, such as avoidance of procrastination, attention control, and self-motivation (Kuhl & Fuhrmann, 1998). Similarly, in Heckhausens (1991) categorization of three main volitional problems (i.e., problems with action initiation, overcoming obstacles to action implementation, and persistence over time), protecting goal pursuit from tempting distraction is considered an important component of action implementation.
Volitional control in general, with handing distraction in particular, is especially important to the task of doing homework because goals of homework assignments are regularly set by school teachers. The main charge for students, therefore, is to navigate the demands of doing homework (i.e., engaging purposively in maneuvers that effectively protect homework intention), which typically requires volitional control. In doing so, students are asked to maintain the needed focus and effort to complete assignments, with less structure, supervision, social pressures, and time constraints than exist in the classroom (H. Cooper et al., 2006; Trautwein & Koller, 2003; Wolters, 2003). They are asked to independently manage homeworkincluding, for example, implementing homework intention, staying focused, and keeping themselves on track (i.e., following through) in the face of an array of alluring distractions, enticing temptations, or competing personal strivings (Corno, 2004; Xu, 2008b, 2008c).
In their article on volition in the learning process, Garcia, McCann, Turner, and Roska (1998) linked expectancy-value theory (Eccles, 1983), particularly Eccless construct of task value, to intention formation, implementation, and protection. They argued that volitional control may be influenced by the pleasure one experiences when engaging in a task, and utility value as the instrumental benefit of engaging in a task. More specifically, based on Eccless theory, Warton (2001) discussed the important role of task value in following through on homework, including (a) task interest (i.e., the extent to which homework is rated as interesting), (b) task utility (i.e., childrens understanding of the purposes of homework), and (c) task cost (i.e., perceived opportunity costs associated with doing homework during after-school hours).
The present investigation was informed by the theoretical approaches on volitional control and expectancy value discussed above. It was further informed by two lines of related research: (a) research that examines a range of distractions while doing homework, and (b) research that alludes to a number of variables that may link to homework distraction.
HOMEWORK DISTRACTION CONTINUE INTO SECONDARY SCHOOL
The first line of literature finds that students continue to struggle with various distractions while doing homework well into the secondary school years (Beentjes, Koolstra, & van der Voort, 1996; Benson, 1988; J. E. Cooper, Horn, & Strahan, 2005; Corno & Xu, 2004; Patton, Stinard, & Routh, 1983; Pool, Koolstra, & van der Voort, 2003a, 2003b; Pool, van der Voort, Beentjes, & Koolstra, 2000; Leone & Richards, 1989; Wober, 1992; Xu, 2004, 2007, 2008b, 2008c; Xu & Corno, 2003). Patton et al. surveyed home study conditions of 387 students in Grades 59. Students described their conditions for studying at home and rated effects of television and radio or stereo on studying. Nearly half (49%) of the students reported that they often did homework with the television on, and nearly 6 out of 10 (58%) students played music while they worked. Listening to music allegedly enhanced the study experience, whereas television, students admitted, was somewhat bothersome.
Similarly, Wober (1992) reported one survey relating to students television experience in England. Among 551 students 1015 years old, more than 4 out of 10 said that they did homework with a television on even though they felt that this made their studying more difficult and less effective. In another study, Benson (1988) reported data from 93 students in Grade 6 from an upper-middle-class suburban community. Students were asked to list the five most prominent disturbances to studying in their homes and explain the reasons for their choices. All of the 93 middle school students reported finding homework distraction a problem at one time or another. Television airing and telephone calls were the two most troublesome homework distractions, mentioned by more than half of the students, and 36%40% of students listed additional distractions, which included feelings of restlessness and parents and siblings coming into the room asking questions or teasing them.
Recently, new technologies have multiplied the challenges to doing homework at home (Foehr, 2006; Roberts et al., 2005; Warton, 2001; Xu, 2007, 2008b, 2008c; Xu & Corno, 2003). According to the Kaiser report (Foehr; Roberts et al.), which was based on a nationally representative sample of 2,032 students in Grades 312, many students use media while doing their homework, especially if they are doing homework on the computer. For example, 30% of students said that they either talk on the phone, instant message, watch television, listen to music, or surf the Web for fun most of the time when they are doing homework, and another 31% said they do this some of the time.
In the Kaiser report, students who completed the basic questionnaire were also asked to keep a 7-day media use diary. The latter request produced a self-selected sample of 694 respondents. The media diary data allowed a closer look at what happened when students did homework on the computer. The results revealed that although doing homework on the computer was students primary activity, they were usually doing something else as well (65% of the time). In fact, half (50%) of the time spent doing homework on the computer as students primary activity was also spent using another media, such as listening to music, instant messaging, watching television, looking at Web sites, using e-mail, and playing computer games and video games.
There is a growing concern that the emergence of this new media has greatly raised the distraction level for students doing homework (Ballard, 2003; Cook, 2000; Gaither, 2006; Lenhart, Rainie, & Lewis, 2001; McHale, 2005; Wallis, 2006). For example, two thirds of the parents in the Pew Internet Project (Lenhart et al., 2001), based on a nationally representative sample of 754 students aged 1217, along with their parents, expressed some or a lot of worry about the distracting power of the Internet. Many teens also acknowledged this distraction; one 17-year-old girl noted, Ive been doing my homework later than usual because I just seem to get carried away online and forget I have homework (p. 31).
In another study, Ballard (2003) interviewed 20 children between the ages of 8 and 14 on their media habits. Her interview data revealed that many students view new media as distractions to completing homework, in the sense that it makes schoolwork boring, takes [their] mind off of studying, and prevents them from getting [their home]work done (p. 5).
MULTIPLE FACTORS MAY INFLUENCE HOMEWORK DISTRACTION
Whereas the first line of research finds that secondary school students experience increased distractions while doing homework, the second line of research alludes to a number of factors that may influence homework distraction. These factors include student and family characteristics, homework environment, and student attitudes toward homework.
Homework environment. Because homework often takes place in the middle of other family activities during after-school hours, there is a need for students to arrange an environment that is conducive to home study and that minimizes homework distractions (Hong & Milgram, 1999; Pool et al., 2000; Xu, 2006; Xu & Corno, 2003, 2006). Xu and Corno (2003), based on survey data from 121 urban middle school students in Grades 68, examined the relationship between students efforts to arrange their environment (five-item scale, e.g., finding a quiet area and turning off the TV) and their perceived homework distraction (five-item scale, e.g., playing around with other things while doing my homework and stopping homework to watch my favorite TV show). All five items in the scale of homework distraction were reverse-scored. Alpha reliability coefficients for the scales related to arranging the environment and homework distraction were .66 and .79, respectively. The data suggested that arranging the homework environment was negatively associated with homework distraction (r = .28, p < .01), noting that the five items relating to homework distraction were reverse-scored.
In another related study, based on survey data from 412 rural high school students in Grades 912, Xu (2006) examined the relationship between students efforts to arrange their environment and their perceived homework distraction. The same two scales, relating to arranging environment and homework distraction, were used in this study; alpha reliability coefficients were .79 and .82, respectively. In line with the findings from another, urban middle school sample (Xu & Corno, 2003), arranging the environment was negatively associated with homework distraction in this rural high school sample (r = .24, p < .01). Taken together, these findings suggest that secondary school students who take more initiatives in arranging their environment are less likely to be distracted while doing homework.
Student attitudes toward homework. Other studies suggest a possible influence of student attitudes toward handling homework distraction. H. Cooper, Lindsay, Nye, and Greathouse (1998) linked student attitudes toward homework to the number of assignments that students completed. Five questions were posed to 424 students in Grades 612 (e.g., whether they liked their homework, and whether it helped them develop study skills and learn to mange their time). These five items were combined in a homework attitude scale (alpha reliability coefficient = .77). The data revealed that the amount of homework students completed was positively related to their attitudes toward homework, implying that those students who held more positive attitudes toward homework took more initiatives to follow through on it and to cope with homework distraction.
In another study, Xu and Yuan (2003) examined how homework was perceived by urban middle school students, based on open-ended interviews. This study revealed that while acknowledging that some assignments were interesting, many students complained that other assignments were frequently boring, too easy or too hard, or irrelevant to their lives.
The study further revealed that these students did not view doing homework as one of their favorite activities during after-school hours. About half of the students said that they would place homework somewhere in the middle of the list. As one student explained, Im not very excited about it, but Im not bragging about it. . . . As soon as I get home, Im just used to doing my homework and thats it. Its not that I like doing it; its just that Im used to doing it. The other half of the students said that they would place homework near or at the bottom of the list; they viewed doing homework as interfering with their pursuit of more attractive activities. One student said that his homework was the last thing he looked forward to doing because he wanted to go outside, play video games, and watch TV. The comparison between these two groups of students (i.e., those who placed homework in the middle vs. those who placed it near or at the bottom of the list of their favored after-school activities) implied that how favorably or unfavorably they viewed homework influenced the way they approached homework in general, and homework distraction in particular.
Student and family characteristics. Unlike homework environment and student attitudes toward homework, the linkage between student and family characteristics and homework distraction seems less certain. For example, based on survey data from 238 students in Grades 7 and 8, Xu and Corno (2006) linked gender and family help to homework distraction while controlling for parental level of education. The scale of homework distraction was the same scale discussed earlier in this section (Xu, 2006; Xu & Corno, 2003), and the alpha reliability coefficient for the scale was .82. The results revealed that homework distraction was unrelated to gender, parental education level, and family homework help.
On the other hand, the scale of homework distraction used in the preceding study did not include any specific items related to more recent electronic technology or high-tech distraction (Taylor, 2006), such as instant messaging, surfing the Web for fun, and playing computer games. Recently, some findings implied that there were possible gender differences in high-tech distraction at the secondary school level (Foehr, 2006; Gaither, 2006; Lenhart, Madden, & Hitlin, 2005). For example, in a study of 971 teens (aged 1217), Lenhart et al. (2005) found that boys were more likely to play online games than girls. On the other hand, girls were more likely to engage in online activities like sending e-mail, text messaging with a cell phone, and going to Web sites (e.g., related to music groups and health topics). In another study based on 1,204 teens in Grades 712, Foehr found that students engaged widely in multitasking while doing their homework and that girls were more likely to media-multitask than boys. Thus, there is a need to examine the role of gender in coping with various homework distractions, including high-tech distraction.
GAPS IN PREVIOUS RESEARCH AND PURPOSE OF THE PRESENT STUDY
Taken together, the first line of research finds that secondary school students continue to experience a variety of distractions while doing homework and that the emergence of new media technologies presents a new and formidable challenge relating to homework distraction, particularly for students at this developmental stage. Meanwhile, the second line of research alludes to a number of factors that may influence homework distraction (e.g., homework environment and student attitudes toward homework). However, much of what we know about these possible linkages (a) is based on zero-order correlations (i.e., without controlling other related variables); (b) is informed by insights from qualitative data (i.e., interviews with students); (c) is limited to conventional homework distraction (i.e., without tapping into high-tech distraction); and (d) has failed to incorporate a multilevel perspective (i.e., without differentiating between class- and student-level effects).
In addition, the second line of research has ignored other important variables surrounding homework task that may contribute to homework distraction. For example, the desires to engage in other after-school activities that often vary on a daily or weekly basis may present yet another source of distraction competing with homework (H. Cooper & Valentine, 2001; Warton, 2001; Xu, 1994; Xu & Corno, 1998).
Furthermore, there is a need to differentiate between different types of student attitudes toward homework (e.g., task interest and task utility), as informed by previous research on homework and theoretical approaches relating to volitional control and expectancy-value theory. Specifically, there is a need to differentiate homework interest (i.e., in the homework task in and of itself) from affective attitude toward homework (i.e., comparing homework with other after-school activities) because these two theoretically distinct constructs are found to be empirically distinguishable (Xu, 2008a). Such a differentiation makes sense in the context of doing homework because students efforts to protect homework intention are likely to be influenced by their perceived homework interest and the relative attractiveness of other competing activities available during after-school hours. This differentiation is further substantiated by interview data from Ballards (2003) study, in which students considered new media distractive because it made homework boring and made them less likely to focus on their work.
To address these gaps in previous research on homework distraction, the aim of the present study is to propose and test homework models that are tailored to the real-life homework distraction of present-day students at the secondary school level. I expected homework distraction to be associated with three categories of variables at the student level: (a) student and family characteristics (e.g., gender, parent education, family homework help); (b) the context of doing homework (e.g., arranging the homework environment, as well as time spent on organized sports, other extracurricular activities, and paid jobs); and (c) student attitudes toward homework, particularly relating to the role of task value (e.g., homework interest, affective attitude, and perceived purposes of doing homework).
I also expected homework distraction to be associated with two variables at the class level: (a) grade level and (b) teacher feedback. The reason to incorporate grade level as a variable here is that older teens (aged 1517), as compared with younger teens (aged 1214), reported more online activitiesfor example, reading and sending e-mails, using instant messaging, receiving text messages by cell phone, and shopping online (Lenhart et al., 2005). This difference in online activities implies that older teens are more likely to face online temptations while doing homework. In addition, it would be interesting to incorporate teacher feedback at the class level because teachers standards, control, and feedback for homework completion may influence the level of student efforts in doing homework (Natriello & McDill, 1986; Trautwein, Ludtke, Schnyder, & Niggli, 2006). For example, the study by Trautwein et al. (2006) revealed that perceived teacher control (e.g., the extent to which a teacher checks homework) was a statistically significant predictor of homework effort at the student level, implying that teacher feedback may influence student homework completion behaviors such as handling distraction.
PARTICIPANTS AND PROCEDURE
To address the concern that previous studies have tended to focus on middle-class Caucasian students (e.g., H. Cooper et al., 1998; Xu, 2005), the present study made an attempt to recruit districts with students from diverse cultural and socioeconomic backgrounds. The superintendents were contacted first to secure their permission to administer the homework instrument. The principals and teachers were then asked to send consent forms to students homes to seek parental approval. Finally, teachers in these schools administrated the homework instrument in the classroom between the middle of October and early November 2005.
Following the suggestion of Felson and Reed (1986) that class-average scores based on fewer than 10 students typically lack validity, I excluded those classes containing fewer than 10 students. As a result, data analyses were based on 1,800 students from 97 classes in the southeastern United States: 969 eighth graders from 52 classes, and 831 eleventh graders from 45 classes.
Of the participants in this sample, 46.7% were male and 53.3% were female. The sample was 56.0% Caucasian, 37.0% African American, 3.4% multiracial, 1.3% Latino, 1.2% Native American, and 1.1% Asian American. Among this sample, 34.5% received free meals. The survey response rate was 88.9%, and the racial/minority breakdown of the students who responded to this survey was comparable with that of these school districts.
The homework survey, which typically took about 40 minutes to administer, incorporated several variables relating to student and family characteristics. Students were asked to indicate the frequency of family homework help, ranging from 1 to 5: never (scored 1), rarely (scored 2), sometimes (scored 3), often (scored 4), and routinely (scored 5). Students were also asked about their level of academic achievement; they were instructed to select one choice that best described their grades across all their subjects during the previous 2 years: Below D (scored 1), mostly Ds (scored 2), (3) mostly Cs (scored 3), mostly Bs (scored 4), and mostly As (scored 5). This survey item was adapted from the National Education Longitudinal Study of 1988 (NELS:88). The only difference was that in NELS:88, the students reported their grades in specific subjects (e.g., English), whereas students in this survey reported their grades across all their school subjects.
The survey included two items on parents education. These two items asked, What is the highest level of education completed by your father/guardian? and What is the highest level of education completed by your mother/guardian? Possible responses for both items included less than high school (scored 6 years), some high school (scored 10 years), high school graduate (scored 12 years), some college or two-year college graduate (scored 14 years), four-year college graduate (scored 16 years), some graduate school (scored 17 years), and graduate degree (scored 19 years). A composite variable for parental level of education was then constructed by averaging the educational levels for the father and the mother.
In addition, the survey incorporated four items relating to the amount of time students spent on four after-school activities on a usual weekday, including organized sports activities, other extracurricular activities, watching television, and work at a paid job. Possible responses to these four items included: none (scored 1), half an hour or less (scored 2), more than half an hour to 1 hour (scored 3), more than 1 hour to 1.5 hours (scored 4), more than 1.5 to 2 hours (scored 5), more than 2 to 2.5 hours (scored 6), more than 2.5 to 3 hours (scored 7), and more than 3 hours (scored 8). Following the work of H. Cooper et al. (1998), an approximate measure of the amount of time spent on these activities was constructed by converting each students response to the midpoint of minutes associated with each scale value (1 = 0 minutes; 2 = 15 minutes; 3 = 45 minutes; 4 = 75 minutes; 5 = 105 minutes; 6 = 135 minutes; 7 = 165 minutes; and 8 = 195 minutes).
Several multi-item scales were used for the present study (see Table 1). These scales included affective attitude toward homework, motivational orientation toward homework, homework interest, teacher feedback, and homework distraction.
Table 1. Multi-Item Scales
Table 1. (Continued)
Note. aResponses were: 1 (strongly disagree), 2 (disagree), 3 (agree), and 4 (strongly agree). bResponses were: 1 (never), 2 (rarely), 3 (sometimes), 4 (often), and 5 (routinely). cResponses were: 1 (very boring), 2 (boring), 3 (neither boring nor interesting), 4 (interesting), and 5 (very interesting). dResponses were: 1 (dont like it at all), 2 (dont like it some), 3 (neither like it nor dislike it), 4 (like it some), and 5 (like it very much). eResponses were: 1 (decreases it a lot), 2 (decreases it some), 3 (does not make a difference), 4 (increases it some), and 5 (increases a lot). fResponses were: 1 (much lower than), 2 (lower than), 3 (about the same as), 4 (higher than), and 5 (much higher than). gResponses were: 1 (much worse than), 2 (worse than), 3 (about the same as), 4 (better than), and 5 (much better than). hResponses were: 1 (least favorite activity), 2 (less favorite activity), 3 (about the same as other activities), 4 (more favorite activity), and 5 (most favorite activity). iResponses were: 1 (none), 2 (some), 3 (about half), 4 (most), and 5 (all). jThe 95% percent confidence intervals (CIs) for coefficient alpha were calculated using a method employing the central F distribution (see Fan & Thompson, 2001).
Affective attitude toward homework. Informed by related literature (Leone & Richards, 1989; Verma, Sharma, & Larson, 2002; Warton, 2001; Xu, 2006, 2007), four items relating to students motivation, attention, and mood were used to assess the favorability of homework as compared with other after-school activities. Internal consistency (Cronbachs alpha) was .86.
Motivational orientation toward homework. Three subscales were developed to assess motivational orientation toward homework, based on the recently validated Homework Purpose Scale for secondary school students (Xu, 2010a, 2010b). Three items were used to measure peer-oriented reasons for doing homework (α = .79), relating to working with and seeking approval from peers. Three items were used to measure adult-oriented reasons for doing homework (α = .79), relating to seeking approval from significant others (e.g., parents and teachers). Nine items were used to measure learning-oriented reasons for doing homework (α = .90), relating to reinforcing school learning and developing a sense of responsibility.
Homework interest. Three items were used to assess the level of homework interest as perceived by students (α = .83), informed by literature on interest and intrinsic motivation in general (Deci, Vallerand, Pelletier, & Ryan, 1991; Isaac, Sansone, & Smith, 1999; Wigfield, 1994; Wigfield & Eccles, 2000), and homework interest in particular (H. Cooper et al., 1998; Xu, 2006, 2007). These items measure the extent to which students consider homework interesting and to what extent they like or dislike homework assignments.
Homework environment. Arranging the homework environment is one of the subscales in the recently validated Homework Management Scale for middle school students (Xu, 2008c) and high school students (Xu, 2008b). It consists of five items to assess students’ efforts to arrange their homework environment (α = .75), ranging from locating homework materials and finding a quiet place to creating a workspace that is conducive to study.
Teacher feedback. Five items were used to assess the extent to which teachers provide ongoing homework feedback (α = .79), informed by some related literature (Murphy et al., 1987; Trautwein, Koller, Schmitz, & Baumert, 2002; Trautwein et al., 2006; Walberg, Paschal, & Weinstein, 1985). These items measure how much of the assigned homework was monitored (e.g., discussed, collected, and checked).
Homework distraction. Ten items were used to assess various homework distractions that students encountered while doing homework (α = .87). These distractions range from conventional distraction (e.g., daydreaming, watching television, and initiating unrelated conversations; Xu, 2006; Xu & Corno, 2003) to high-tech distraction (e.g., stopping homework to play online games or to receive and send e-mail and other instant messages; Foehr, 2006; Wallis, 2006; Warton, 2001; Xu, 2008b, 2008c; Xu & Corno, 2003).
Researchers in education are often confronted with data that follow multilevel or nested structures (e.g., students within classrooms). In the case of the present study, individual student characteristics are confounded with those of classrooms because individuals are not assigned randomly to groups. This clustering effect presents several major statistical issuesaggregation bias, misestimated standard errors, and heterogeneity of regressionthat are due to lack of independence between measurements at different levels. These issues cannot be appropriately handled with traditional regression and analysis of variance. Multilevel modeling allows for the inclusion of variables at two levels (i.e., the student and class levels) and takes into account the nonindependence of observations by addressing the variability associated with each level of nesting (i.e., decomposing any observed relationship between variables into separate within-class and between-class components). A detailed presentation of multilevel modeling (also referred to as hierarchical linear modeling [HLM]) is beyond the scope of the present study and is available elsewhere (e.g., Goldstein, 1995; Hofmann, 1997; Hox & Kreft, 1994; Lee, 2000; Raudenbush & Bryk, 2002; Snijders & Bosker, 1999).
Multilevel analyses were conducted using the HLM 6 (Raudenbush, Bryk, Cheong, Congdon, & Toit, 2004) computer program. Because the HLM 6 output does not report standardized regression coefficients, I standardized all continuous variables (M = 1, SD = 1) to enhance the interpretability of the resulting regression coefficients. Consequently, the regression weights for all variables (except the dummy-coded variables, including gender, lunch status, and grade level) are approximately comparable with the standardized weights that result from multiple-regression procedures (Trautwein et al., 2006).
Model 1 included five student-level variables relating to student and family characteristics: gender, lunch status, parent education, self-reported grades, and family homework help. Model 2 introduced five student-level variables relating to the context of doing homework, including arranging the environment, and time spent on television, organized sports, other extracurricular activities, and paid jobs. Model 3 incorporated five additional student variables relating to student attitudes toward homework, including homework interest, affective attitude toward homework, and peer-oriented, adult-oriented, and learning-oriented reasons.
In educational psychology, 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 (Ludtke, Koller, Marsh, & Trautwein, 2005; Ryan, Gheen, & Midgley, 1998; Trautwein et al., 2006). In the present study, homework feedback was aggregated at the class level to form an index of students shared assessment of teachers feedback (and was not restandardized). This variable, along with grade level, were introduced as two class-level variables in Model 4.
All models reported are random-intercept models. The random part of the intercept was freely estimated to reflect between-classroom differences in homework distraction. Because 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 relatively few missing values, ranging from 0.00% to 6.72% (with a mean of 2.05%). These missing values were imputed using the expectation-maximization (EM) in SPSS 13.0. The EM algorithm is an iterative computation technique of maximum likelihood estimates for incomplete data, which yields more reliable and unbiased estimates compared with other imputation techniques such as simple regression techniques, mean substitution, and the last-observation carried forward (Koszycki, Benger, Shlik, & Bradwejn, 2007; Schafer & Graham, 2002).
Relating to student and family characteristics, the mean educational level for the parents was 13.60 years (SD = 2.72), and 34.5% of the students received free meals. The frequency of family homework help was never (38.2%), rarely (11.3%), sometimes (27.4%), often (16.5%), and routinely (6.6%). Student self-reported grades over the last 2 years were below D (1.2%), mostly Ds (5.7%), (3) mostly Cs (27.0%), mostly Bs (43.1%), and mostly As (23.0%).
In addition, the amount of time students reported spending on organized sports, other extracurricular activities, television, and paid jobs was 78 minutes (SD = 74), 39 minutes (SD = 59), 120 minutes (SD = 72), and 46 minutes (SD = 74), respectively. The mean score for working to arrange a suitable homework environment was 3.15 (SD = .87), indicating that students tended to arrange their homework environment (e.g., to find a quiet place and to turn off television) slightly more often than sometimes (scored 3).
The mean score for peer-oriented reasons was 2.31 (SD = .73), indicating that students tended to disagree (scored 2) that they did homework to work with and seek approval from classmates. The mean scores for adult-oriented reasons and learning-oriented reasons were 2.70 (SD = .73) and 2.82 (SD = .61), respectively, indicating that students tended to agree (scored 3) that they did homework to seek adult approval or to reinforce school learning and develop a sense of responsibility.
The mean score for homework interest was 2.37 (SD = .95), indicating that students tended to think of their homework as boring or as adversely affecting their other school interests (scored 2). The mean score for affective attitude toward homework was 2.14 (SD = .84), indicating that students motivation, attention, and moods while doing homework were lower or worse than (scored 2) those experienced with other after-school activities.
Meanwhile, the mean score for aggregated teacher feedback at the class level was 3.6 (SD = .34), indicating that teachers provided feedback for between half (scored 3) and most (scored 4) of their assigned homework. Finally, the mean score for the dependent variable (i.e., homework distraction) was 2.61 (SD = .87), falling between rarely (scored 2) and sometimes (scored 3) on the 10 items that related to various homework distractions, which ranged from daydreaming to stopping homework to play online games.
Table 2 presents zero-order correlations among the various independent variables and homework distraction. Homework distraction was found to correlate significantly with all the independent variables except gender and parent education.
Table 2. Pearson Correlations
Note. N varies from 1,691 to 1,800. * p < . 05. ** p < .01.
The fully unconditional model was conducted to partition the variance in homework distraction into between-class and within-class components. When this model was run, the within-class variance was .942, whereas the between-classes variance was .061. The results indicated that homework distraction varied across classes (p < .001). The results also indicated that most of the variance occurred at the student level, with 6.1% of the variance in homework distraction located at the class level.
Model 1 included five student-level variables relating to student and family characteristicsgender, lunch status, parent education, self-reported grades, and family homework help. Together, these variables explained 2.2% of the variance in homework distraction at the student level, along with 17.9% of the variance in homework distraction at the class level (see Table 3).
Table 3. Predicting Homework Distraction: Results from Hierarchical Linear Modeling
N = 1,691 from 97 classes. b = unstandardized regression coefficient. SE = standard error of b. R2 = amount of explained variance.
* p < .05. ** p < .01.
Model 2 incorporated an additional five student-level variables relating to the context of doing homework: arranging the homework environment, time spent on television, organized sports, other extracurricular activities, and paid jobs. These variables explained an additional 15.6% of the variance in homework distraction at the student level, as well as an additional 25.6% of the variance in homework distraction at the class level.
Model 3 incorporated five additional student-level variables relating to student attitude toward homework (i.e., homework interest, affective attitude, and peer-oriented, adult-oriented, and learning-oriented reasons). These variables explained an additional 7.4% of the variance in homework distraction at the student level, and an additional 23.4% of the variance in homework distraction at the class level.
In Model 4, two class-level variablesgrade level and aggregated teacher feedbackwere entered. These variables accounted for 10.8% of the variance in homework distraction at the class level, above and beyond the previous variables included in Model 3.
Overall, the final model (i.e., Model 4) explained 25.2% of the variance in homework distraction at the student level, 77.7% of the variance in homework distraction at the class level, and 28.3% of the total variance in homework distraction. As documented in Table 3, 12 student-level variables were found to have a statistically significant effect on homework distraction. Among them, seven variables had a negative effect on homework distraction. Those students with higher scores in affective attitude (b = -.22, p < .01), self-reported grades (b = -.08, p < .01), learning-oriented reasons (b = -.08, p < .05), homework interest (b = -.07, p < .05), and adult-oriented reasons (b = -.06, p < .05) reported that they were less likely to be distracted while doing homework. Those students who took more initiatives in arranging the environment reported that they were less likely to be distracted during homework sessions (b = -.20, p < .01). Interestingly, males reported statistically significant lower levels of homework distraction after controlling other variables (b = -.30, p < .01).
Meanwhile, five student-level variables were found to have a positive effect on homework distraction. Those students who spent more time on television watching (b = .15, p < .01), other extracurricular activities (b = .10, p < .01), sports (b = .06, p < .01), and paid jobs (b = .05, p < .05) reported that they were more likely to be distracted while doing homework. In addition, higher scores in peer-oriented reasons were associated with higher homework distraction scores (b = .10, p < .01).
At the class level, grade level and teacher feedback served as predictors. Grade level was found to have a positive effect on homework distraction (b = .13, p < .05). Eleventh graders, as compared with eighth graders, were more likely to be distracted while doing homework. On the other hand, the negative effect of teacher feedback aggregated at the class level did not reach the significance level (b = -.11, p = .12).
The present study examined empirical models of variables posited to predict homework distraction at the secondary school level. The results from the multilevel analyses revealed that most of the variance in homework distraction occurred at the student level. The results further revealed that most of the student-level variables in the final model (i.e., Model 4) contributed to the explanation of the variation in homework distraction, except the three variables relating to student and family characteristics (i.e., lunch status, parental education, and homework help).
INTERPRETATION OF FINDINGS
The finding that girls, compared with boys, were more likely to be distracted while doing homework was not unanticipated because girls were found to be more likely to engage in online activities (Lenhart et al., 2005) and media multitasking (Foehr, 2006). On the surface, this finding is intriguing, given that theoretical claims (e.g., Covington, 1992, 1998; Deslandes & Cloutier, 2002; Harris, Nixon, & Rudduck, 1993; Jackson, 2002, 2003) and previous empirical studies (e.g., Harris et al., 1993; Hong & Milgram, 1999) implied that girls tend to hold more positive attitudes toward homework and to expend greater effort on following through on homework. Yet, a more detailed examination suggests that data from the present study were in line with these theoretical claims and empirical studies in the sense that (a) the regression weight of gender increased from b = -.11 to b = -.23 after five student-level variables relating to the context of doing homework were included in Model 2, and (b) the regression weight further increased from b = -.23 to b = -.30 after five student-level variables relating to student attitudes toward homework were entered in Model 3. Indeed, zero-order correlations in Table 2 further suggest that, for example, boys were less likely to take initiatives to arrange their homework environment and more likely to have lower scores in homework interest and affective attitude toward homework.
For exploratory reasons, I repeated Model 4 to test a gender interaction with other relevant student-level variables, including self-reported grades; family homework help; arranging the environment; time spent on sports, other extracurricular activities, television, and paid jobs; homework interest; affective attitude toward homework; and peer-oriented, adult-oriented, and learning-oriented reasons. None of the interaction terms between gender and each of the above variables yielded statistically significant results.
How is one to explain the finding that those students with higher self-reported grades reported that they were less likely to be distracted while doing homework? Although the present study is the first to link student achievement to homework distraction after controlling other relevant variables, this finding is in line with the hypothesis that students who have been continually performing poorly in schoolwork may show less of an inclination to work on homework tasks (McCann & Turner, 2004) and therefore may be less likely to maintain homework intention in the face of temptations and distractions.
It is interesting to note that lunch status was not associated with homework distraction. One possible explanation is that technology access becomes less an issue for students from low socioeconomic backgrounds. This explanation is, to some extent, substantiated by the finding that in 9 out of 10 districts of low socioeconomic status (94%), some teachers have already implemented the practice of assigning Internet-based homework (National School Boards Association, 2007).
As to the finding that family help was unrelated to homework distraction after controlling other variables relating to the context of doing homework at home (i.e., arranging the environment and time spent on other after-school activities), there are at least two possible explanations. One is that high-tech distraction (e.g., instant messaging while doing homework), compared with conventional distraction (e.g., television), is difficult for parents to monitor and police (Cook, 2000). High-tech distraction, in general, tends to be less visible to parents (e.g., switching from one computer window containing a homework project to another in which instant messages from friends appear; Xu & Corno, 2003). In addition, some parents shy away from monitoring such potential distractions because they do not have enough knowledge about the new media technology to be involved (Dahl, 2006). Taken together, these two explanations suggest that, compared with family help, students own initiatives (e.g., arranging the environment) play a more important role in handling homework distraction.
Relating to the context of doing homework, the associational evidence from the present study lends empirical support to the claim that desires to engage in other after-school activities (e.g., television, sports, and other extracurricular activities) may interfere with following through on homework (H. Cooper & Valentine, 2001; Warton, 2001; Xu & Corno, 1998). The finding that students who took more initiatives in arranging homework environment were less likely to be distracted is consistent with the volitional literature on the importance of environmental control in reducing the probability of encountering distraction (Corno, 1993; Wolters, 2003). The finding also meshes well with the type of strategy referred to as environmental structuring in self-regulated learning (Zimmerman, 1994; Zimmerman & Martinez-Pons, 1986, 1990). In addition, although in line with previous findings that arranging the environment is significantly related to traditional homework distraction (Xu, 2006; Xu & Corno, 2003), the present study takes a step further, suggesting the important role of arranging the environment in coping with homework distraction, including both the conventional and high-tech kinds.
The present study further suggests that student attitudes toward homework influence homework distraction, above and beyond other student-level variables (i.e., student and family characteristics and the context of doing homework). Specifically, it provides additional empirical support to the observation that there is a need to differentiate between homework interest and affective attitude toward homework (Ballard, 2003; Xu, 2006, 2007, 2008a; Xu & Yuan, 2003). Although both variables were found to be negatively associated with homework distraction, the regression coefficient for affective attitude toward homework (b = -.22, p < .01) was about three times larger than the regression coefficient for homework interest (b = -.07, p < .05), recalling that all continuous variables were standardized before the multilevel analyses, and their regression coefficients are approximately comparable with the standardized weights resulting from multiple-regression procedures. These results suggest that there is a need to reconceptualize the construct of task value in future investigation on homework distraction, in the sense that affective attitude toward homework (i.e., the relative attractiveness of the homework task as compared with other competing activities) needs to be considered as an important facet of the value construct. This reconceptualization may also have implications for investigating volitional control in general, because (a) handling distraction is considered an important component of volitional control (Corno, 1994; Heckhausen, 1991; Kuhl & Fuhrmann, 1998), and (b) the implementation of an intention is influenced by the relative strength, attractiveness, or pleasantness of a competing action tendency (Garcia et al., 1998; Van Eerde, 2000).
In addition, the present study suggests that the important role of motivational orientation toward homework may play in homework distraction; results revealed that homework distraction was positively associated with peer-oriented reasons and negatively associated with adult-oriented and learning-oriented reasons. One possible explanation is that cooperative learning activities are likely to contain peer distraction (Corno, 2004; Rogers & Swan, 2004), and those students with higher scores in peer-oriented reasons are more likely to contact peers about their homework assignments, which may often lead them to engage in other social activities unrelated to the homework task at hand. On the other hand, those students with higher scores in adult-oriented and learning-oriented reasons are more likely to take their own initiatives to overcome homework distraction. However, this explanation needs to be treated with caution. Although previous research suggests that students attitudes toward homework play an important role in their homework completion behavior (H. Cooper et al., 1998; Xu, 2005), the present study did not include a measure of frequency of engaging in peer-oriented homework versus adult-oriented or learning-oriented homework.
Although the present study is the first to examine homework distraction simultaneously in relation to the student-level and class-level variables, the finding of small class-level differences (6.1%) in homework distraction is not surprising. Looking at the way homework distraction was defined (Table 1), it makes sense that most of the variance in homework distraction (e.g., watching television and instant messaging) occurred at the student level (i.e., at home) rather than at the class level.
What do we make of the finding that grade level as a class-level variable was positively associated with homework distraction? Although there is no empirical study that explicitly links homework distraction to grade level, a number of researchers (e.g., Bempechat, 2004; H. Cooper et al., 2006; H. Cooper & Valentine, 2001; Patton et al., 1983) hypothesize that younger children are less able to focus and avoid distractions than older children. Thus, the finding from the present study raises an important question about this hypothesis.
One possible explanation is that the nature of homework distraction is evolving over time, in the sense that homework distraction examined in the present study has incorporated specific items relating to high-tech distraction, which was far less a concern even 510 years ago. This explanation is substantiated to some extent by recent findings that older children tend to have more autonomy and access to a wide array of media in their homes and bedrooms (Roberts et al., 2005) and tend to engage in more online activities (e.g., exchanging instant and text messages, as well as buying online; Lenhart et al., 2005); these tendencies may lead to more homework distractions for older children.
Finally, how do we explain the significant low correlations between homework distraction and a number of student-level variables, particularly those relating to time spent on other after-school activities such as paid jobs (b = .05, p < .05), sports (b = .06, p < .01), other extracurricular activities (b = .10, p < .01), and television (b = .15, p < .01)? One possible explanation is that, in addition to the amount of time spent on these after-school activities, the scheduling of these after-school activities (e.g., in the middle or near the end of homework assignments) may play an important role in homework distraction. This explanation is, to some extent, supported by one recent experimental study on college students (Botvinick & Bylsma, 2005), which showed that mid-subtask distraction leads to an increased number of errors (as compared with end-subtask distraction).
LIMITATIONS OF THE DATA
Although students in the present study came from diverse cultural backgrounds, the racial compositions of this sample (e.g., 56.0% Caucasian, 37.0% African American, and 1.3% Latino) were somewhat different from those of the national average (e.g., 56.5% Caucasian, 17.1% African American, and 19.6% Latino; Common Core of Data, 20052006). Nevertheless, the percentage of the students who received free meals (34.5%) was very close to the national average (32.3%; Common Core of Data).
Findings from the present study are based on student self-report and therefore may be subject to social desirability bias (Fowler, 1995). Students, for example, may want to present themselves in a more favorable light (e.g., underreporting family help or overreporting homework interest). Two steps were taken to minimize this potential bias: (a) the students answered the survey in a self-administered form instead of giving answers to an interviewer, and (b) they were assured that their responses would be anonymous and kept confidential.
Although it is difficult to determine what the exact effects of self-reported data are on findings, one line of evidence suggests that social desirability bias is unlikely to be a major concern in the present study. For example, the percentage of eighth graders who reported that they received family homework help in the present study (74%) 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). It also seems that the students, as a group, did not deliberately try to make themselves look good by asserting that they considered homework interesting and viewed it as a favorite after-school activity, given that they viewed both of these aspects quite negatively.
In addition, although the item on student self-reported grades was adapted from NELS:88, it is a crude estimate of student academic achievement. Another limitation relates to the issue of causation, a limitation facing virtually all nonexperimental research. Although much care was taken to control for possible confounding variables and alternative explanations, other predictor variables might have had an effect on homework distraction had I included them. Unfortunately, it is difficult to address the issue of causality in nonexperimental research in general (Winship & Sobel, 2004), and with homework research in particular, because homework is influenced by more factors than any other instructional activity (H. Cooper, 2001).
Because the present study is the first to link homework distraction to a broad range of variables, further research is needed to validate the homework survey instrument used in this study in other settings. There is a need, for example, to incorporate items relating to the scheduling of other after-school activities, in addition to the amount of time spent on these activities. In addition, there is a need to examine homework distraction across ability levels based on standardized test scores, because results from the present study revealed that homework distraction was influenced by student self-reported grades.
There is also a need to continue this line of research to examine a combination of influences on homework distraction with populations of students in upper elementary and early middle school levels because (a) younger children tend to have less access to a range of media in their homes and bedrooms (Roberts et al., 2005) and are less likely engage in online activities (Lenhart et al., 2005), and (b) results from the present study raise a question about the hypothesis that younger children are less able to focus and avoid distraction than older children (e.g., Bempechat, 2004; H. Cooper & Valentine, 2001; Hoover-Dempsey et al., 2001). Similarly, there is a need to examine possible gender difference in handling homework distraction, because results from the present study imply that girls are vulnerable to homework distraction when high-tech avenues are taken into account.
In addition to the outlined confirmatory investigations, exploratory investigations are equally needed in this area for in-depth examination of the ever-changing reality of doing homework at home, including: (a) the nature and types of distractions that secondary school students encounter in their life context, and (b) the evolving approaches or strategies that they may develop to deal with these distractions. It would be informative to conduct qualitative case studies that focus on the microlevel processes that go on in homes while homework is being carried out (H. Cooper, Lindsay, & Nye, 2000, p. 484) in order to examine more closely what homework distraction means to students and how student attitudes toward homework and their approaches in handling homework distraction develop over the secondary school years.
More specifically, it would be important to examine how (not just whether or to what magnitude) certain attitudes toward homework (e.g., affective attitude) play a role in coping with homework distraction. It would also be important, in the face of more readily accessible communication tools, to study conditions for engaging collaborative aspects of doing homework while minimizing homework distraction; Leone and Richards (1989) reported that students (a) displayed higher levels of affect and arousal when doing homework with friends and lower levels when doing homework alone, and (b) were more attentive to homework when completing it alone than when doing so with friends.
The finding that family help was unrelated to homework distraction does not mean that parents do not play an important role in helping their children cope with homework distraction at the secondary school level. For example, parents may exert their influence strategically by structuring and prioritizing other after-school activities, given that the present study revealed that time spent on other after-school activities (i.e., television viewing, sports participation, other extracurricular activities, and paid jobs) was negatively associated with homework distraction. In addition, because student attitudes toward homework were positively associated with parent attitudes (H. Cooper et al., 1998), parents can play an indirect, yet important, role in helping students cope with homework distraction through influencing their attitudes toward homework (e.g., both adult-oriented and learning-oriented reasons for doing homework). In particular, parents may play an indirect yet strategic and important role with older teens regarding to their attitudes toward homework; the results from the present study implied that 11th graders were more likely distracted while doing homework than younger students.
Whereas Epstein and Van Voorhis (2001) focused on the important role that teachers play in designing homework to promote specific academic outcomes across the grades, the present study further suggests the important role of teachers in designing homework to increase homework interest and counter homework distraction. Particularly, there is a need to reexamine homework practices and to find ways to design homework assignments that are more interesting and engaging (Leone & Richards, 1989; Warton, 2001; Xu, 2004, 2008a), given that the present study revealed that homework distraction was negatively related to homework interest at the student level.
In addition, teachers may want to be more mindful about the collaborative aspect of doing homework, given that new media offer more readily accessible communication tools (e.g., chatting, text messaging, blogging, and visiting online communities) that allow students to contact peers about their homework assignments (Lenhart et al., 2001; National School Boards Association, 2007). Homework collaboration changes the traditional solitary nature of the homework task and the separation of homework from social learning (Coutts, 2004; Leone & Richards, 1989). On the other hand, it may introduce additional sources of homework distraction that interfere with homework completion. One way to address this issue would be to expand homework hotlines (Reach & Cooper, 2004) to incorporate characteristics of social networking (i.e., live exchanges and instant access). If educators can show adolescents how to stay focused in online learning activities (while providing timely homework assistance in these activities that appeal to them), adolescents are more likely to use appropriate strategies to inhibit distraction while working with peers on homework tasks.
Previous studies suggest that adolescents are aware of the influences of study conditions on homework completion (Benson, 1988; Patton et al., 1983; Xu & Corno, 2003) and that their own views about homework influence their homework behavior (Bryan, Nelson, & Mathur, 1995; H. Cooper et al., 1998; Warton, 2001). The present study moves one important step forward, suggesting the important role that student initiative can play in dealing with homework distraction. Thus, one of the most important implications of the present study is to encourage secondary students themselves to get more actively involved in managing homework distractions. They can, for example, minimize distractions by arranging a conducive homework environment. They can also use self-regulatory strategies (e.g., monitoring motivation) to make homework more engaging for themselves and thus make themselves more likely to persist in the face of distractions. In addition, if they can be helped to see the value of injecting meaning into their daily homeworkviewing homework tasks as closing critical gaps in their academic experiences (i.e., learning-oriented reasons) or fulfilling expectations of their significant others (i.e., adult-oriented reasons)they are more likely to take more initiatives to protect their attention against potential homework distraction.
Finally, students need to prioritize and structure their other after-school activities on a weekly basis so that they are less likely to be sidetracked by thoughts of competing activities while doing daily homework (Xu, 2008a). These efforts on the part of students are particularly important, given that the present study suggests that simply moving up from middle school to high school by and in itself does not mean that students are more ready to display a greater initiative in handling homework distraction. Indeed, if left alone, as alluded to by the present study, high school students become more vulnerable to the new generation of homework distraction.
I would like to thank Editor Gary Natriello and three anonymous reviewers for their constructive comments and helpful suggestions.
Ballard, K. D. (2003, June). Media habits and academic performance: Elementary and middle school students perceptions. Paper presented at the National Media Education Conference, Baltimore, MD.
Beentjes, J. W. J., Koolstra, C. M., & van der Voort, T. H. A. (1996). Combining background media with doing homework: Incidence of background media use and perceived effects. Communication Education, 45, 5972.
Bembenutty, H., & Karabenick, S. A. (2004). Inherent association between academic delay of gratification, future time perspective, and self-regulated learning. Educational Psychology Review, 16, 3557.
Bempechat, J. (2004). The motivational benefits of homework: A social-cognitive perspective. Theory Into Practice, 43, 189196.
Bennett, S., & Kalish, N. (2006). The case against homework: How homework is hurting our children and what we can do about it. New York: Crown.
Benson, R. (1988). Helping pupils overcome homework distractions. Clearing House, 61, 370372.
Boekaerts, M., & Corno, L. (2005). Self-regulation in the classroom: A perspective on assessment and intervention. Applied Psychology: An International Review, 54, 199231.
Botvinick, M. M., & Bylsma, L. M. (2005). Distraction and action slips in an everyday task: Evidence for a dynamic representation of task context. Psychonomic Bulletin and Review, 12, 10111017.
Bryan, T., Nelson, C., & Mathur, S. (1995). Homework: A survey of primary students in regular, resource, and self-contained special education classrooms. Learning Disabilities Research and Practice, 10, 8590.
Common Core of Data. (20052006). Common Core of Data, 20052006 (Version 1a). Retrieved November 19, 2007, from http://nces.ed.gov/ccd/pubschuniv.asp
Cook, S. (2000, October 24). One eye on homeworkthe other on e-mail, TV, games . . . Christian Science Monitor, 92(233), 16.
Cooper, H. (1989). Homework. White Plains, NY: Longman.
Cooper, H. (2001). The battle over homework: Common ground for administrators, teachers, and parents (2nd ed.). Thousand Oaks, CA: Corwin Press.
Cooper, H., Lindsay, J. J., & Nye, B. (2000). Homework in the home: How student, family and parenting-style differences relate to the homework process. Contemporary Educational Psychology, 25, 464487.
Cooper, H., Lindsay, J. J., Nye, B., & Greathouse, S. (1998). Relationships among attitudes about homework, amount of homework assigned and completed, and student achievement. Journal of Educational Psychology, 90, 7083.
Cooper, H., Robinson, J. C., Patall, E. A. (2006). Does homework improve academic achievement? A synthesis of research, 19872003. Review of Educational Research, 76, 162.
Cooper, H., & Valentine, J. C. (2001). Using research to answer practical questions about homework. Educational Psychologist, 36, 143153.
Cooper, J. E., Horn, S., & Strahan, D. B. (2005). If only they would do their homework: Promoting self-regulation in high school English classes. High School Journal, 88(3), 1026.
Corno, L. (1993). The best-laid plans: Modern conceptions of volition and educational research. Educational Researcher, 22(2), 1422.
Corno, L. (1994). Student volition and education: Outcomes, influences, and practices. In D. H. Schunk & B. J. Zimmerman (Eds.), Self-regulation of learning and performance (pp. 229255). Hillsdale, NJ: Erlbaum.
Corno, L. (1996). Homework is a complicated thing. Educational Researcher, 25(8), 2730.
Corno, L. (2000). Looking at homework differently. Elementary School Journal, 100, 529548.
Corno, L. (2001). Self-regulated learning: A volitional analysis. In B. Zimmerman & D. Schunk (Eds.), Self-regulated learning and academic achievement: Theory, research, and practice (Vol. 2, pp. 111142). Mahwah, NJ: Erlbaum.
Corno, L. (2004). Introduction to the special issue work habits and work styles: Volition in education. Teachers College Record, 106, 16691694.
Corno, L., & Xu, J. (2004). Doing homework as the job of childhood. Theory Into Practice, 43, 227233.
Coutts, P. M. (2004). Meanings of homework and implications for practice. Theory Into Practice, 43, 182188.
Covington, M. V. (1992). Making the grade: A self-worth perspective on motivation and school reform. Cambridge, England: Cambridge University Press.
Covington, M. V. (1998). The will to learn: A guide for motivating young people. Cambridge, England: Cambridge University Press.
Dahl, M. (2006, November 10). Really, Im listening; Digital-savvy teens say parents shouldnt stress about all their electronic multitasking. The Sacramento Bee, p. J1.
Deci, E. L., Vallerand, R. J., Pelletier, L. G., & Ryan, R. M. (1991). Motivation and education: The self-determination perspective. Educational Psychologist, 26, 325346.
Deslandes, R., & Cloutier, R. (2002). Adolescents perception of parental involvement in schooling. School Psychology International, 23, 220232.
Eccles, J. S. (1983). Expectancies, values, and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motives (pp. 75146). San Francisco: Freeman.
Epstein, J. L., & Van Voorhis, F. L. (2001). More than minutes: Teachers roles in designing homework. Educational Psychologist, 36, 181193.
Fan, X., & Thompson, B. (2001). Confidence intervals about score reliability coefficients, please: An EPM guidelines editorial. Educational and Psychological Measurement, 61, 517531.
Felson, R. B., & Reed, M. D. (1986). Reference groups and self-appraisals of academic ability and performance. Social Psychology Quarterly, 49, 103109.
Fowler, F. J. (1995). Improving survey questions: Design and evaluation. Thousand Oaks, CA: Sage.
Foehr, U. G. (2006). Media multitasking among American youth: Prevalence, predictors, and pairings. Menlo Park, CA: Kaiser Family Foundation.
Foerde, K., Knowlton, B. J., & Poldrack R. A. (2006). Modulation of competing memory systems by distraction. Proceedings of the National Academy of Sciences of the United States of America, 103, 1177811783.
Gaither, C. (2006, August 11). They do it all while studying: At homework time, many students also playing games, e-mailing friends and watching TV. The Los Angeles Times, p. A28.
Garcia, T., McCann, E. J., Turner, J. E., & Roska, L. (1998). Modeling the mediating role of volition in the learning process. Contemporary Educational Psychology, 23, 392418.
Gill, B. P., & Schlossman, S. L. (2000). The lost cause of homework reform. American Journal of Education, 109, 2762.
Gill, B. P., & Schlossman, S. L. (2004). Villain or savior? The American discourse on homework, 18502003. Theory Into Practice, 43, 174-181.
Goldstein, H. (1995). Multilevel statistical models. London: Edward Arnold.
Harris, S., Nixon, J., & Rudduck, J. (1993). School work, homework and gender. Gender and Education, 5, 314.
Heckhausen, H. (1991). Motivation and action. New York: Springer-Verlag.
Heckhausen, H., & Kuhl, J. (1985). From wishes to action: The dead-ends and shortcuts on the long way to action. In M. Frese & J. Sabini (Eds.), Goal-directed behavior: The concept of action in psychology (pp. 134160). Hillsdale, NJ: Erlbaum.
Hofmann, D. A. (1997). An overview of the logic and rationale of hierarchical linear models. Journal of Management, 23, 723744.
Hong, E., & Milgram, R. M. (1999). Preferred and actual homework style: A cross-cultural examination. Educational Research, 41, 251265.
Hoover-Dempsey, K. V., Battiato, A. C., Walker, J. M., Reed, R. P., DeLong, J. M., & Jones, K. P. (2001). Parental involvement in homework. Educational Psychologist, 36, 195204.
Horn, L., & West, J. (1992). National Education Longitudinal Study of 1988: A profile of parents of eighth graders. Washington, DC: U.S. Department of Education, Office of Educational Research and Improvement.
Hox, J. J., & Kreft, I. G. G. (1994). Multilevel analysis methods. Sociological Methods and Research, 22, 283299.
Isaac, J. D., Sansone, C., & Smith, J. L. (1999). Other people as a source of interest in an activity. Journal of Experimental Social Psychology, 35, 239265.
Jackson, C. (2002). Laddishness as a self-worth protection strategy. Gender and Education, 14, 3751.
Jackson, C. (2003). Motives for laddishness at school: Fear of failure and fear of the feminine. British Educational Research Journal, 29, 583598.
Kohn, A. (2006). The homework myth: Why our kids get too much of a bad thing. Cambridge, MA: Da Capo Press.
Koszycki, D., Benger, M., Shlik, J., & Bradwejn, J. (2007). Randomized trial of a meditation-based stress reduction program and cognitive behavior therapy in generalized social anxiety disorder. Behaviour Research and Therapy, 45, 25182526.
Kralovec, E., & Buell, J. (2000). The end of homework: How homework disrupts families, overburdens children, and limits learning. Boston: Beacon Press.
Kuhl, J. (1984). Volitional aspects of achievement motivation and learned helplessness: Toward a comprehensive theory of action-control. In B. A. Maher (Ed.), Progress in experimental personality research (Vol. 13, pp. 99171). New York: Academic Press.
Kuhl, J. (1985). Volitional mediators of cognition-behavior consistency: Self-regulatory processes and action versus state orientation. In J. Kuhl & J. Beckman (Eds.), Action control: From cognition to behavior (pp.101128). New York: Springer-Verlag.
Kuhl, J. (2000). The volitional basis of personality systems interaction theory: Applications in learning and treatment contexts. International Journal of Educational Research, 33, 665704.
Kuhl, J., & Fuhrmann, A. (1998). Decomposing self-regulation and self-control: The volitional component inventory. In J. Heckhausen & C. S. Dweck (Eds.), Motivation and self-regulation across the life span (pp. 1549). New York: Cambridge University Press.
Lee, V. E. (2000). Using hierarchical linear modeling to study social contexts: The case of school effects. Educational Psychologist, 35, 125141.
Lenhart, A., Madden M., & Hitlin, P. (2005). Teens and technology: Youth are leading the transition to a fully wired and mobile nation. Washington, DC: Pew Internet and American Life Project.
Lenhart, A., Rainie, L., & Lewis, O. (2001). Teenage life online: The rise of the instant-message generation and the Internets impact on friendships and family relationships. Washington, DC: Pew Internet and American Life Project.
Leone, C. M., & Richards, M. H. (1989). Classwork and homework in early adolescence: The ecology of achievement. Journal of Youth and Adolescence, 18, 531548.
Loveless, T. (2003). The 2003 Brown Center Report on American education: How well are American students learning? Washington, DC: Brookings Institution Press.
Ludtke, O., Koller, O., Marsh, H. W., & Trautwein, U. (2005). Teacher frame of reference and the big-fish-little pond effect. Contemporary Educational Psychology, 30, 263285.
Marzano, R. J., & Pickering, D. J. (2007). The case for and against homework. Educational Leadership, 64(6), 7479.
McCann, E. J., & Turner, J. E. (2004). Increasing student learning through volitional control. Teachers College Record, 106, 16951714.
McHale, T. (2005). Portrait of a digital native: Are digital-age students fundamentally different from the rest of us? Technology and Learning, 26(2), 33.
Murphy, J., Decker, K., Chaplin, C., Dagenais, R., Heller, J., Jones, R., et al. (1987). An exploratory analysis of the structure of homework assignments in high schools. Research in Rural Education, 4, 6171.
National School Boards Association. (2007). Creating and connecting: Research and guidelines on online socialand educationalnetworking. Alexandria, VA: Author.
Natriello, G., & McDill, E. L. (1986). Performance standards, student effort on homework, and academic achievement. Sociology of Education, 59, 1831.
Patton, J. E., Stinard, T. A., & Routh, D. K. (1983). Where do children study? Journal of Educational Research, 76, 280286.
Pool, M. M., Koolstra, C. M., & van der Voort, T. H. A. (2003a). Distraction effects of background soap operas on homework performance: An experimental study enriched with observational data. Educational Psychology, 23, 361380.
Pool, M. M., Koolstra, C. M., & van der Voort, T. H. A. (2003b). The impact of background radio and television on high school students homework performance. Journal of Communication, 53, 7487.
Pool, M. M., van der Voort, T. H. A., Beentjes, J. W. J., & Koolstra, C. M. (2000). Background television as an inhibitor of performance on easy and difficult homework assignments. Communication Research, 27, 293326.
Public Agenda. (2000). Survey finds little sign of backlash against academic standards or standardized tests. New York: Author.
Raudenbush, S., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis (2nd ed.). Thousand Oaks, CA: Sage.
Raudenbush, S., Bryk, A., Cheong Y. F., Congdon, R., & Toit, M. (2004). HLM 6: Hierarchical linear and nonlinear modeling. Lincolnwood, IL: Scientific Software International.
Reach, K., & Cooper, H. (2004). Homework hotlines: Recommendations for successful practice. Theory Into Practice, 43, 234241.
Roberts, D. F., Foehr, U. G., & Rideout, V. (2005). Generation M: Media in the lives of 818 year-olds. Menlo Park, CA: Kaiser Family Foundation.
Rogers, D., & Swan, K. (2004). Self-regulated learning and internet searching. Teachers College Record, 106, 18041824.
Ryan, A. M., Gheen, M. H., & Midgley, C. (1998). Why do some students avoid asking for help? An examination of the interplay among students academic efficacy, teachers social-emotional role, and the classroom goal structure. Journal of Educational Psychology, 90, 528535.
Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147177.
Schmid, R. (2006). Listen to mom and dad: Distractions make learning less efficient. Retrieved December 18, 2006, from http://www.usatoday.com/tech/science/discoveries/2006-07-24-distractions-learning_x.htm?csp=34
Schmitz, B., & Wiese, B. S. (2006). New perspectives for the evaluation of training sessions in self-regulated learning: Time-series analyses of diary data. Contempary Educational Psychology, 31, 6496.
Snijders, T. A. B., & Bosker, R. J. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London: Sage.
Taylor, C. L. (2006, December 17). Teens balancing act: New study shows young people are spending more time multitasking, with mixed results. Newsday, p. 37.
Trautwein, U., & Koller, O. (2003). The relationship between homework and achievementstill much of a mystery. Educational Psychology Review, 15, 115145.
Trautwein, U., Koller, O., Schmitz, B., & Baumert, J. (2002). Do homework assignments enhance achievement? A multilevel analysis of 7th grade mathematics. Comtemporary Educational Psychology, 27, 2650.
Trautwein, U., Ludtke, O., Schnyder, I., & Niggli, A. (2006). Predicting homework effort: Support for a domain-specific, multilevel homework model. Journal of Educational Psychology, 98, 438456.
van Eerde, W. (2000). Procrastination: Self-regulation in initiating aversive goals. Applied Psychology: An Internatinal Review, 49, 372389.
Verma, S., Sharma, D., & Larson, R. W. (2002). School stress in India: Effects on time and daily emotions. International Journal of Behavior Development, 26, 500508.
Walberg, H. J., Paschal, R. A., & Weinstein, T. (1985). Homeworks powerful effects on learning. Educational Leadership, 42, 7679.
Wallis, C. (2006, March 27). The multitasking generation: Theyre e-mailing, IMing and downloading while writing the history essay. What is all that digital juggling doing to kids brains and their family life? Time, pp. 4855.
Warton, P. M. (2001). The forgotten voices in homework: Views of students. Educational Psychologist, 36, 155165.
Wigfield, A. (1994). Expectancy-value theory of achievement motivation: A developmental perspective. Educational Psychology Review, 6, 4978.
Wigfield, A., & Eccles, J. S. (2000). Expectancy-value theory of achievement motivation. Contemporary Educational Psychology, 25, 6881.
Winne, P. H. (2004). Putting volition to work in education. Teachers College Record, 106, 18791887.
Winship, C., & Sobel, M. E. (2004). Causal inferences in sociological studies. In M. Hardy & A. Bryman (Eds.), Handbook of data analysis (pp. 481503). Thousand Oaks, CA: Sage.
Wober, J. M. (1992). Text in a texture of television: Childrens homework experience. Journal of Educational Television, 18, 2334.
Wolters, C. A. (2003). Regulation of motivation: Evaluating an underemphasized aspect of self-regulated learning. Educational Psychologist, 38, 189205.
Xu, J. (1994). Doing homework: A study of possibilities. Unpublished doctoral dissertation, Teachers College, Columbia University, New York.
Xu, J. (2004). Family help and homework management in urban and rural secondary schools. Teachers College Record, 106, 17861803.
Xu, J. (2005). Purposes for doing homework reported by middle and high school students. Journal of Educational Research, 99, 4655.
Xu, J. (2006). Gender and homework management reported by high school students. Educational Psychology, 26, 7391.
Xu, J. (2007). Middle-school homework management: More than just gender and family involvement. Educational Psychology, 27, 173189.
Xu, J. (2008a). Models of secondary students' interest in homework: A multilevel analysis. American Educational Research Journal, 45, 1180-1205.
Xu, J. (2008b). Validation of scores on the homework management scale for high school students. Educational and Psychological Measurement, 68, 304324.
Xu, J. (2008c). Validation of scores on the homework management scale for middle school students. Elementary School Journal, 109, 8295.
Xu, J. (2010a). Homework purpose scale for high school students: A validation study. Educational and Psychological Measurement, 70. doi:10.1177/0013164409344517
Xu, J. (2010b). Homework purposes reported by secondary school students: A multilevel analysis. Journal of Educational Research, 103, 171182.
Xu, J., & Corno, L. (1998). Case studies of families doing third-grade homework. Teachers College Record, 100, 402436.
Xu, J., & Corno, L. (2003). Family help and homework management reported by middle school students. Elementary School Journal, 103, 503518
Xu, J., & Corno, L. (2006). Gender, family help, and homework management reported by rural middle school students. Journal of Research in Rural Education, 21(2). Retrieved May 15, 2008, from http://jrre.psu.edu/articles/21-2.pdf
Xu, J., & Yuan, R. (2003). Doing homework: Listening to students, parents, and teachers voices in one urban middle school community. School Community Journal, 13(2), 2544.
Zimmerman, B. J. (1994). Dimensions of academic self-regulation: A conceptual framework for education. In D. H. Schunk & B. J. Zimmerman (Eds.), Self-regulation of learning and performance: Issues and educational applications (pp. 321). Hillsdale, NJ: Erlbaum.
Zimmerman, B. J., & Martinez-Pons, M. (1986). Development of a structured interview for assessing student use of self-regulated learning strategies. American Educational Research Journal, 23, 614628.
Zimmerman, B. J., & Martinez-Pons, M. (1990). Student differences in self-regulated learning: Relating grade, sex, and giftedness to self-efficacy and strategy use. Journal of Educational Psychology, 82, 5159.