Media and Young Children’s Learning
VOL. 18 / NO. 1 / SPRING 2008 39
Media and Young Children’s Learning
Heather L. Kirkorian, Ellen A. Wartella, and Daniel R. Anderson
Summary
Electronic media, particularly television, have long been criticized for their potential impact on children. One area for concern is how early media exposure influences cognitive development and academic achievement. Heather Kirkorian, Ellen Wartella, and Daniel Anderson summarize the relevant research and provide suggestions for maximizing the positive effects of media and minimizing the negative effects.
One focus of the authors is the seemingly unique effect of television on children under age two. Although research clearly demonstrates that well-designed, age-appropriate, educational television can be beneficial to children of preschool age, studies on infants and toddlers suggest that these young children may better understand and learn from real-life experiences than they do from video. Moreover, some research suggests that exposure to television during the first few years of life may be associated with poorer cognitive development.
With respect to children over two, the authors emphasize the importance of content in mediating the effect of television on cognitive skills and academic achievement. Early exposure to age-appropriate programs designed around an educational curriculum is associated with cognitive and academic enhancement, whereas exposure to pure entertainment, and violent content in particular, is associated with poorer cognitive development and lower academic achievement.
The authors point out that producers and parents can take steps to maximize the positive effects of media and minimize the negative effects. They note that research on children’s television viewing can inform guidelines for producers of children’s media to enhance learning. Parents can select well-designed, age-appropriate programs and view the programs with their children to maximize the positive effects of educational media.
The authors’ aim is to inform policymakers, educators, parents, and others who work with young children about the impact of media, particularly television, on preschool children, and what society can do to maximize the benefits and minimize the costs. www.futureofchildren.org Heather Kirkorian is a postdoctoral research associate at the University of Massachusetts–Amherst. Ellen Wartella is a professor, executive vice chancellor, and provost at the University of California–Riverside. Daniel Anderson is a professor at the University of Massachusetts–Amherst.
Heather L. Kirkorian, Ellen A. Wartella, and Daniel R. Anderson
40 THE FUTURE OF CHILDREN
Since television first appeared in the nation’s living rooms in the middle of the twentieth century, observers have voiced recurrent concern over its impact on viewers, particularly children. In recent years, this concern has extended to other electronic screen media, including computers and video game consoles. Although researchers still have much to learn, they have provided information on the links between electronic media, especially television, and children’s learning and cognitive skills. The message is clear: most (if not all) media effects must be considered in light of media content. With respect to development, what children watch is at least as important as, and probably more important than, how much they watch.
In this article we review media research with an emphasis on cognitive skills and academic achievement in young children. We begin by arguing that by age three, children are active media users. We then discuss important aspects of child development that highlight the debate over whether children younger than two should be exposed to electronic media, emphasizing the apparent video deficit of infants and toddlers in which they learn better from real-life experiences than they do from video. Next we look at research on media effects in three areas: associations between media use and cognitive skills, particularly attention; experimental evidence for direct learning from educational media; and associations between early media use and subsequent academic achievement. We close with some suggestions for both media producers and parents for enhancing and extending the potentially beneficial effects of electronic media use in children, particularly those who are of preschool age.
Children as Active Media Users
Until the 1980s, social science researchers had only an implicit theory of how viewers watched television. Analysts regarded television viewing, particularly by young children, as being cognitively passive and under the control of salient attention-eliciting features of the medium such as fast movement and sound effects. Jerome Singer formalized this theory, proposing that the “busyness” of television leads to a sensory bombardment that produces a series of orienting responses that interferes with cognition and reflection. As a result, children cannot process television content and therefore cannot learn from it.1 Others proposed similar views, arguing that programs such as Sesame Street provided nothing that could be truly educational.2
Aletha Huston and John Wright proposed a somewhat different theory of attention to television, positing that the features of television that drive children’s attention may change as a child ages. Specifically, they claimed that in infancy, perceptually salient features of television such as movement and sound effects drive attention. With age and experience, however, children are less influenced by perceptual salience and are able to pay greater attention to informative features such as dialogue and narrative.3
Around the same time, Daniel Anderson and Elizabeth Lorch created a complementary model of children’s attention to television, drawing on evidence that television viewing is
Until the 1980s, social science researchers had only an implicit theory of how viewers watched television.Media and Young Children’s Learning VOL. 18 / NO. 1 / SPRING 2008 41 based on active cognition. They argued that attention in children at least as young as two is guided in large part by program content. For example, preschool children pay more attention to normal video clips than to those that have been edited to make them incomprehensible, for example by using foreign dubs of the video clips or randomizing the order of shots within the clips.4 Moreover, preschool-age children pay more attention to children’s programs than to commercials even though commercials are more densely packed with formal features.5 Children learn strategies for watching television by using their knowledge of formal features to guide attention.6 Finally, to understand typical programs that use standard video montage such as cuts, pans, and zooms, children engage in a variety of inferential activities while viewing.7
Developmental Considerations
Although children are active viewers of television by preschool age, research suggests that this may not be true of infants and toddlers. In this section we summarize research on attention to, comprehension of, and learning from video by children under two.
Attention to Electronic Media
Until recently, research on media effects
Table 1. Selected Popular Television Programs and DVD Series for Young Children TV programs | Description | Network | Barney & Friends | Evoking a preschool setting, Barney the dinosaur teaches songs and dances to young children. The show focuses heavily on pro-social themes of sharing, empathizing, helping others, and cooperating. | PBS | Blue’s Clues | A human host encourages viewers at home to help solve a mystery with his dog friend, Blue. The show is often repetitive and encourages interactivity by asking viewers to find clues and solve puzzles. | Nickelodeon | Bob the Builder | Bob the Builder and his construction crew face building, renovation, and repair challenges. The series often focuses on identifying a problem and making a plan to solve the problem. | PBS | Dora the Explorer | Featuring a bilingual Latina girl as the lead, Dora and her friends go on quests and help others, encouraging viewers to help out through their own actions or by telling her what she needs to know. In addition to highlighting traditional educational content such as color and shapes, Dora teaches language by repeating words and phrases in English and Spanish. | PBS | Sesame Street | Combining puppetry, live action, and animation, this long-running series focuses on a wide range of topics including the alphabet, numbers, emotion management, conflict resolution, music, dance, and healthy lifestyles. | PBS | Teletubbies | Centering on four colorful characters, the Teletubbies speak in a baby-like language and learn through play. The Teletubbies have televisions in their stomachs that show clips of real children from around the world. This program is targeted at toddlers. | PBS | Thomas & Friends | Based on a book series, Thomas the Tank Engine and his engine friends learn to work hard and be cooperative with each other. | PBS | The Wiggles | Featuring a four-man singing group for children, episodes of The Wiggles include songs and skits focused on solving a problem. The Wiggles encourages children to sing songs and move their bodies to music. | Disney | DVD series | Description | Producer | Baby Einstein | Series content covers wide range of topics including music, art, language, poetry, and science. Targeted at children starting at one month. | Disney | Brainy Baby | Educational series highlighting range of subjects including alphabet, art, music, shapes, foreign languages, and right and left brain development. Targeted at children starting at nine months. | Brainy Baby Company | Sesame Beginnings | Features baby versions of the Muppets from Sesame Street. The focus is on encouraging interactions between child and caregivers. Targeted at children starting at six months. | Sesame Workshop |

2nd research
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Child Abuse Prevention Issues Number 16 Winter 2002
The role of mass media in facilitating community education and child abuse prevention strategies
Bernadette J. Saunders1 and Chris Goddard2

Contact the Australian Institute of Family Studies for a copy of this newsletter. This report can also be downloaded in PDF (portable document) format (size=579k). You will need an Acrobat Reader which is free from the Adobe Systems Web site.

In the second part of their analysis of the role of mass media in child abuse prevention, the authors discuss the benefits of mass media programs as a tool to advocate for children's rights and more specifically, to promote awareness of, and to prevent, child abuse. The authors emphasise that campaign strategies may only be successful to the degree that they are backed by community education and direct support programs. Information gained from evaluations is highlighted, and recommendations for future media campaigns and initiatives are made.
INTRODUCTION
A previous Issues Paper focusing on the prevention of child maltreatment noted that 'the African proverb, "It takes a village to raise a child", epitomises the importance of the role of the wider community in raising children and young people' (Tomison and Wise 1999: 1). Increasingly, responsibility for children is not entrusted solely to parents or guardians but to whole communities (Cohen, Ooms and Hutchins 1995; Korbin and Coulton 1996). Strategies that aim to optimise the experiences of children and young people, and to prevent child abuse and neglect, are therefore required to ascertain, and perhaps confront, commonly held community attitudes and responses to all children and young people, and to increase community awareness of issues that may affect children and young people.
According to the National Child Protection Council (undated: 9, cited in Hawkins, McDonald, Davison and Coy 1994): 'Prevention of abuse involves changing those individual and community attitudes, beliefs and circumstances which allow the abuse to occur.'
The media play a significant role in forming and influencing people's attitudes and behaviour. Issues Paper 14, Child abuse and the media (Goddard and Saunders 2001), drew attention to the essential role of the media in increasing society's awareness of, and response to, child abuse and neglect. Of particular note was the part played by news and features that reported on specific child abuse cases, research and intervention strategies. Such media attention to child abuse has, at times, positively influenced public, professional and political responses to the circumstances in which children and young people find themselves. Understanding media influences, and how to use the media constructively, may thus be an essential tool for those who advocate for children, young people, and their families (see Brawley 1995).
In addition to news stories, feature articles, and investigative journalism, sporadic mass media education and prevention campaigns are launched. These campaigns usually endeavour to broaden community knowledge of child abuse and neglect, to influence people's attitudes towards children and young people, and to change behaviours that contribute to, or precipitate, the problem of child abuse and neglect in our communities.
For several reasons, however, the effectiveness of these campaigns remains contentious. Primarily, the effectiveness of mass media in the prevention of child abuse and neglect is debatable. For example, Rayner (1996) argues that 'media campaigns are bloody expensive' and their impact is difficult to determine. Expensive media campaigns may be hard to justify in a political climate where limited funds and resources are provided to address children's needs. Further, McDevitt (1996: 270) cites O'Keefe and Reed (1990: 215) to note that: 'At best, the media are "effective at building citizen awareness of an issue" but more complex attitudinal or behavioural change requires "more direct forms of citizen contact and intervention".'
Others argue, however, that mass media campaigns and media coverage of the abuse and neglect of children perform an important and significant role in placing issues such as child abuse on the public and political agenda. Lindsey (1994: 163) maintains that: 'Media has a central role in mediating information and forming public opinion. The media casts an eye on events that few of us directly experience and renders remote happenings observable and meaningful.'
As Wurtele and Miller-Perrin (1993) have observed, media coverage of child sexual assault has contributed to demystifying and reducing the secrecy that has characteristically surrounded its occurrence. Similarly, a review of the literature on mass media campaigns reveals many examples of campaigns impacting on public knowledge about issues such as work safety, drug and alcohol use, drink-driving, speeding, cigarette smoking, obesity, AIDS, and domestic violence. Attitudinal and/or behavioural change may also occur during campaigns, although this result may be short-lived, lapsing when campaigns end (Reger, Wootan and Booth-Butterfield 2000; Freimuth, Cole and Kirby 2001).
Mass media present the opportunity to communicate to large numbers of people and to target particular groups of people. As observed by Gamble and Gamble (1999: 478), mass communication is significantly different from other forms of communication. They note that mass communication has the capacity to reach 'simultaneously' many thousands of people who are not related to the sender. It depends on 'technical devices' or 'machines' to quickly distribute messages to diverse audiences often unknown to each other. It is accessible to many people, but may be avoided. It is orchestrated by specialists whose intent is to persuade potential audiences of the benefits of their attention. It is 'controlled by gatekeepers' who censor the content of messages. And finally, unlike one-to-one communication, it produces only minimal, delayed feedback to its senders.
However, mass communication simultaneously presents opportunities and limitations, both of which require consideration when planning mass media assisted eradication of social problems such as child abuse and neglect. According to Wellings and Macdowall (2000: 23), drawing on Tones et al. (1990): 'The strength of the mass media . . . lies in helping to put issues on the public agenda, in reinforcing local efforts, in raising consciousness about . . . issues and in conveying simple information . . . The limitations of the mass media are that they are less effective in conveying complex information, in teaching skills, in shifting attitudes and beliefs, and in changing behaviour in the absence of other enabling factors.'
Campaigns, and other forms of media education and entertainment (such as television programs, film and live productions), may be targeted at all families with a view to encouraging positive attitudes toward children and stopping abuse before it starts or is even considered (primary prevention). Groups of people identified as particularly susceptible to abusive behaviour may be targeted (secondary prevention). Further, a campaign or program may target families in which abuse has already occurred with the intention of preventing recurrence of the abuse (tertiary prevention).
Thus, a well-focused mass media campaign, educational program or live-theatre production has the potential to contribute successfully to community education and the prevention of child abuse and neglect. However, as will be emphasised throughout this Issues Paper, campaign strategies may only be successful to the degree that they are backed by community education and support programs:
'A media campaign can be effective, but it means nothing unless the campaign is integrated into an overall approach dealing with the various aspects of the problem being addressed.' (Peter White, then NSW Coordinator for the Drug Offensive, quoted in Burrows 1988: 16)
'Whatever happens at the mass level must be complemented and supported at a grass roots level for any long-term behavioural change to occur.' (Julie Urquhart, then campaign manager of the Drink-Drunk; the Difference is U NSW Youth Alcohol Strategy, quoted in Wood 1994: 18)
A report on a recent Western Australian mass mediabased campaign, 'Freedom from Fear', which targeted male perpetrators of domestic violence, identified 'five potential message strategies' for mass media prevention campaigns (Donovan et al. 2000: 80): * Criminal sanctions: a traditional emphasis on legal threats; * Community intervention: an approach encouraging friends and neighbours to report domestic violence or intervene with the perpetrator or victim; * Social disapproval: a theme emphasising shame and embarrassment (that is, 'real men don't hit women'); * Consequences: a theme based on the impact of the violence on their partner or children; and * Help is available: emphasising that help is available if the man desires to change.
These strategies grew out of a review of the literature and interviews with domestic violence workers. Each of these five strategies has strengths and weaknesses that warrant consideration in the formation of media messages for education and prevention campaigns.
This Issues Paper describes some recent and past mass media education and prevention campaigns, television programs, films, and live theatre productions. Their raison d'étre, their justification in the current economic and political environment, and their impact are discussed. Information gained from evaluations is highlighted and recommendations for future media campaigns and initiatives are made.
The primary focus of this paper is the media-assisted prevention of all forms of child abuse and neglect. However, examples of mass media-based prevention in other areas such as health and safety are drawn upon, and each of the message strategies noted above (Donovan et al. 2000) will become apparent in the context of current or past campaigns and media approaches to prevention.
WHY COMMUNITY EDUCATION AND PREVENTION CAMPAIGNS?
In the year 1990-1991 reports of child abuse and neglect to Australian child protection authorities numbered 49,721. According to the Australian Institute of Health and Welfare (AIHW 2002), in 2000-2001 reports had increased to 115,471; following investigation, 27,367 cases were confirmed or substantiated as involving child abuse and/or neglect.
The physical abuse, sexual abuse, emotional abuse, and neglect of children have a long recorded history. In the mid to late 1800s, Toulmouche, Tardieu, Bernard and Lacassagne reported that children were often sexually assaulted, that children reported honestly about their abuse, and that the perpetrators of abuse were often the children's fathers and brothers (Olafsen, Corwin and Summit 1993).
Corby (1993) notes that Kempe's 'discovery' of the battered child syndrome in 1962, and the 'discovery' of child sexual abuse in Britain in the 1980s were in fact 're-discoveries'. According to Corby (1993: 16): 'Child abuse is not a new phenomenon, nor is public or state concern about it. Nevertheless fresh attempts to tackle child mistreatment are usually accompanied by the declaration that it is a new and as yet undiscovered problem. This 'newness' is seen as an important part of the process of establishing it as an issue requiring resources to tackle it.'
Historically, children have been accorded little, if any, status in society. Deprived of rights and perceived as the property of their parents or guardians, children could be treated any way their 'owners' saw fit (see Cleverley and Phillips 1987; Archard 1993). In this context, community awareness and acceptance of the reality of child abuse, particularly child abuse perpetrated by family members, has been slow. 'Stranger danger', beliefs that children's stories are untrustworthy, and beliefs that parents always act in the best interests of their children, appear to be easier for communities to accept.
Such beliefs may present people with a means of turning a blind eye to the reality that child abuse is often perpetrated by adults well known to children, in children's own homes, and in other trusted environments. In relation to child sexual abuse, for example, Kitzinger and Skidmore (1995: 53) quote one interviewee from Kidscape in the United Kingdom: 'People don't want to be associated with child abuse as incest . . . it's a message we try to get across to the press but they're very wary . . . it's easier and safer to concentrate on strangers and bullying.'
Olafsen, Corwin and Summit (1993) have argued that cycles of awareness followed by suppression have typified society's response to child sexual abuse. Arguably, this has been society's response to all forms of child abuse and neglect of children. Mass media education and prevention campaigns present one means of breaking cycles of suppression and denial. The media have played a key role in periodically placing the issue of child abuse on the public agenda.
CONCEPTUALISATION OF CHILDHOOD AND ADOLESCENCE
This section discusses: images of children and young people in society and in the media; media influences on children and children's rights; and the impact of media campaigns on the victims of child abuse.
Images of children in society and the media
Journalists willing to advocate for children and young people face the challenge of counterbalancing negative images or 'demonisation' (Franklin and Horwath 1996) of children and, particularly, of adolescents, in print, television and film. Starkly contrasting with once popular views of childhood as a time of innocence, less than positive images of children and young people in the media may place obstacles in the path of attempts to prevent their abuse and neglect.
It is notable that child abuse media prevention campaigns rarely, if ever, focus on the maltreatment of adolescents (rather attention is given to societal problems, perhaps stemming from child abuse, such as drug use, youth suicide and chroming (see Goddard and Tucci 2002: 11)). Similarly, as observed by Mendes (2000: 50), drawing on Vinson (1987), Aldridge (1994) and Wilczynski and Sinclair (1999): 'Structural disadvantages contributing to child abuse and neglect such as poverty, unemployment, and gender or race-based discrimination are rendered invisible [in the media].'
A comparison of the media coverage of three child murder cases - two in the United Kingdom and one in Australia - highlights significantly different images of children created, or reinforced, by media comment.
Alder and Polk (2001) observe the language used and attitudes portrayed in the media coverage. In 1968, 11-yearold Mary Bell murdered two boys, aged three and four in the UK. Twenty-five years later, in1993, two ten-year-old boys murdered two-year-old Jamie Bulger in the UK, and in Australia in 1998, a ten-year-old boy was charged with drowning a six-year-old playmate.
According to Alder and Polk (2001), while media commentary in the Mary Bell case expressed 'concern for the offender' who was perceived by many as the 'surviving child of this tragedy', the latter two cases predominantly yielded media commentary that described the child offenders as 'evil', callous and reckless. Alder and Polk (2001: 134) contend that: 'What may have changed in the years since the Bell case is the gradual evolution of an internationalised media, capable of the instantaneous transfer of 'infotainment' around the globe . . . these outlets have a special appetite for the bizarre and unusual.'
Franklin and Horwath (1996) further observe a concerning change in society's perception of children which, as Tomison (1997) has noted, extends to adolescents. Less often perceived as 'innocent' and 'innately good', it seems a child or young person may now be portrayed as a 'powerful, destructive human being' (Franklin and Horwath 1996: 315).
The cases described above are distressing and uncommon. Negative images of children (perhaps stemming from such cases), and media reinforcement of feelings that children and young people are a burden on families and on society, do not assist in the prevention of child abuse and neglect. Further exploration of the lives experienced by young offenders, while not detracting from the horror of events that occur, almost invariably reveals their own victimisation as children or as adolescents.
Moreover, as Tomison (1997: 22) claims, perceiving children as 'powerful' and 'evil' beings may 'dehumanise' children and serve to justify child abuse. He further contends that the negative portrayal of children in the media may result in victims of abuse blaming themselves for their abuse. Victims may be led to believe that they deserved the assaults perpetrated against them, and thus accept their abuse as justified.
Further, Tomison (1997) cites Winn (1993) and Garbarino (1992) to note that these negative images of children may indeed be magnified once the child becomes an adolescent. Negative stereotypes of young people, he contends, may contribute to the incidence of adolescent maltreatment, exacerbating 'the problems of troubled youth in troubled families, providing a justification for unresponsive parenting and increasing the probability of serious family conflict' (Tomison 1997: 23).
By putting pressure on governments to increase community supports for children and families, and by presenting positive, empathetic images of children and young people, the media may have a powerful influence in preventing, rather than perhaps indirectly promoting, child maltreatment. As Walby (1996: 25) argues: 'Children and childhood need to be better appreciated; families with children need a more supportive environment; issues affecting children need more sophisticated debate; and services for children and the people who work for them need more support from the public.'
Media influences on children and children's rights
The impact of media advertising on children and adolescents is well documented, as is concern about some aspects of the media's powerful influence on children's attitudes and behaviours (see, for example, Macklin and Carlson 1999; Inquiry into the Effects of Television and Multimedia on Children and Families in Victoria 2000). Television may be 'a more powerful socialisation agent than peers and teachers' (Hutson, Watkins and Kunkel 1989 cited in Walsh, Laczniak, and Carlson 1999: 119).
As acknowledged in a major New Zealand newspaper, it is notable that: 'The media promote violence as an effective way of dealing with conflict through television, films, videos, and interactive video games' (The New Zealand Herald, 28/11/01).
In evidence given to the Victorian Government Inquiry into the Effects of Television and Multimedia on Children and Families in Victoria, Michael Carr-Gregg (2000: 68) further endorses this view: 'Contrary to some claims, many people in the medical, public health, and scientific communities are in agreement that the relationship between television violence and aggression and violence in young people does exist. Exhaustive reviews of the evidence accumulated over 40 years - and we are talking about 3000 different studies - have led researchers to conclude unequivocally that mass media significantly contributes to the aggressive behaviour and attitudes of many children, adolescents, and, of course, adults.'
However, this power of the media to negatively influence children's attitudes and behaviours may be used to impact positively on the lives of children and adolescents. According to the Inquiry into the Effects of Television and Multimedia on Children and Families in Victoria (2000: 35): 'Qualitative evidence suggests that quality children's television can enhance child development by providing positive role models of cooperation and collaboration as a responsible way of acting in the world.'
Indeed, the constructive use of mass media can assist in teaching children and young people socially desirable ways of dealing with conflict, knowledge of their rights to integrity and protection from harm, healthy eating habits and lifestyles, and ways to assert themselves and their rights in a positive, acceptable manner.
As noted in the Inquiry into the Effects of Television and Multimedia on Children and Families in Victoria (2000: 37), evaluations of educational television programs, designed either for pre-schoolers or for older children, have suggested their effectiveness in 'heightening a range of social behaviours' (Friedrich and Stein 1973), diminishing 'the effects of stereotyping' (Johnston and Ettema 1982), increasing 'preparedness for adolescence' (Singer and Singer 1994), and stimulating the discussion of 'solutions to general social issues' (Johnston, Bauman, Milne, and Urdan 1993). Research suggests that, at least in the short term, television viewing of such programs may increase children's and young people's knowledge and positively change attitudes and behaviours. Unfortunately, longitudinal studies exploring sustained effects are rare and thus inconclusive.
The Inquiry into the Effects of Television and Multimedia on Children and Families in Victoria (2000: 33) further notes that television 'is one of the most popular forms of mass communication and entertainment in Australia [and] has been under-utilised as an educative tool', and suggests that perhaps narrow vision has meant that the deliberate use of television simultaneously to entertain and educate has not been fully recognised. Despite this, Postman (1994) has argued that television is rapidly becoming 'the first curriculum', with educational institutions such as schools following behind.
According to the Inquiry into the Effects of Television and Multimedia on Children and Families in Victoria (2000: 1): 'The one thing on which the critics and the defenders of television agree is that it is a central and pervasive part of modern life. Children can spend more time watching television than any other activity except sleep . . . it is a major socialising force in children's lives.'
Mass media education and prevention campaigns may be designed to target children and young people, providing them with useful information and alerting them to avenues for further information, help and support. Campaigns can also use regular television programs for children. Drawing on the research of Baran, Chase and Courtright (1979) and Forge and Phemister (1987), the Inquiry into the Effects of Television and Multimedia on Children and Families in Victoria (2000: 15) states: 'Children . . . have shown cooperative behaviour following one observation of just one episode of positive social behaviour in a commercial television drama . . . and cartoons with a positive social message have produced positive behaviours in pre-schoolers . . . Discussions of complex issues and approaches to conflict resolution have also been successfully utilised in Australian drama.'
Campaign organisers can approach producers of popular children's television requesting that they incorporate messages, such as a child's right to physical integrity and to protection from harm, and depict desired protective behaviours, such as seeking help if a child feels threatened or unsafe.
Further, campaigns may be designed to give children and young people an opportunity to express their views on issues that affect them, specifically targeting adult audiences that habitually ignore the views and experiences of children and young people. Research on the physical punishment of children (Saunders, in progress) suggests, for example, that adults may be interested to hear children's views on the issue of physical discipline, and children interviewed in the research were keen for adults to hear their views. To date, however, the media rarely, if ever, consults children and takes their views into account before reporting on the physical punishment of children. Indeed, the media often trivialises the issue of physical punishment (Saunders and Goddard 1998, 1999 (a) and (b), 2000).
Tomison (1996: 77) has noted that The United Kingdom Commission of Inquiry into the Prevention of Child Abuse made a recommendation that the media 'take a more balanced and sympathetic view of children'. Tomison (1997: 25) highlights that: 'In line with a belief in the importance of 'listening to children', the Commission felt that the media should take the views of children into account when presenting on an issue in which children have some interest. The Commission (1996) recommended that the media should have an obligation to consider a child's best interest in stories in which children feature, and that the failure to do so would constitute grounds for a complaint to a relevant authority.'
As reported in Issues Paper 14 in this series, Child abuse and the media (Goddard and Saunders 2001), children can be encouraged to express their views through the media. The UK Children's Express is one example, as is Youth Forum in Melbourne's Herald Sun newspaper.

3rd research

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* Performing your original search, law on effectiveness of media exposure correlates academic performance, in PMC will retrieve _ records.
J Adolesc Health. Author manuscript; available in PMC 2011 January 1.
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J Adolesc Health. 2010 January; 46(1): 52.
Published online 2009 July 3. doi: 10.1016/j.jadohealth.2009.05.012
PMCID: PMC2818002
NIHMSID: NIHMS121631
Effect of Visual Media Use on School Performance: A Prospective Study1
Iman Sharif, MD, MPH, Thomas A. Wills, PhD, and James D. Sargent, MD
Iman Sharif, Associate Professor of Pediatrics, Nemours/A.I. DuPont Hospital for Children, Wilmington, DE, Thomas Jefferson University Medical School;
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Corresponding Author: Iman Sharif, MD, MPH, Nemours/A.I. DuPont Hospital for Children, 1600 Rockland Road, Wilmington, DE 19803, 302-651-6040 (Phone); 302-651-5948 (Fax), Email: isharif@nemours.org
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Abstract
Purpose
To identify mechanisms for the impact of visual media use on adolescents' school performance.
Methods
We conducted a 24-month, four-wave longitudinal telephone study of a national sample of 6,486 youth aged 10-14 years. Exposure Measures: Latent construct for screen exposure time (weekday time spent viewing television/playing videogames, presence of television in bedroom) and variables for movie content (proportion of PG13 and R movies viewed). Outcome Measure: Self and parent reports of grades in school. Effects of media exposures on change in school performance between baseline and 24 months were assessed using structural equation modeling. Information about hypothesized mediators (substance use, sensation-seeking, and school problem behavior) was obtained at baseline and at the16-month follow-up.
Results
Adjusted for baseline school performance, baseline levels of mediators, and a range of covariates, both screen exposure time and media content had adverse effects on change in school performance. Screen exposure had an indirect effect on poor school performance through increased sensation-seeking. Viewing more PG-13 and R-rated movies had indirect effects on poor school performance mediated through increases in substance use and sensation-seeking. R-rated viewing also had an indirect effect on poor school performance through increased school behavior problems. The effect sizes of exposure time and content on the intermediate variables and ultimately on school performance were similar to those for previously recognized determinants of these mediators – including household income, parenting style, and adolescents' self-control.
Conclusions
These aspects of visual media use adversely affect school performance by increasing sensation-seeking, substance use and school problem behavior.
Keywords: visual media, sensation-seeking, school performance, mediation, screen time, screen exposure, media content
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Introduction
To the extent that school performance predicts educational attainment, it has the potential to affect a host of economic and health outcomes. The relation between television and movie viewing and school performance has been a subject of debate. Studies on preteens and adolescents have suggested a detrimental effect of television viewing on school performance (1-3) relating it to lower homework completion, more learning problems, and worse academic achievement. However, little is known about what exactly it is about viewing television that affects school performance. For example, is it simply that time spent watching television displaces time doing homework, or does media use influence behavioral characteristics that are ultimately related to school performance? In a cross-sectional study, we found that hours of weekday television viewing and viewing of R-rated movie content were associated concurrently with poor school performance.(3) These observed effects for media exposure could involve intermediate processes and need to be tested in prospective research designs. In this paper we report results from a longitudinal analysis that tested several hypothesized pathways linking media variables to change in school performance.
Theoretical Model
We have developed a heuristic model, based on social-cognitive theory, that suggests several pathways through which visual media exposure can affect school performance (Figure 1). First, time spent on media use could simply displace time spent doing other activities that promote academic performance, such as doing homework or reading books. Second, viewing certain types of adult content could affect school performance by increasing adolescents' involvement in risky behaviors, such as smoking and alcohol use, resulting in decreased motivation at school. Indeed, exposure to such cues in television or movies increases involvement by adolescents in cigarette smoking(4-11), alcohol use(12-16), and sex(17-19). Third, there are certain dispositions that predict poor school performance, particularly a preference for intense and exciting sensations, which has been termed sensation-seeking.(20-25). Frequent viewing of movies that contain high levels of excitement and arousal (e.g., “action” movies) could increase the desire for these kinds of experiences, which is behaviorally incompatible with concentrated effort on reading and writing. There is also evidence to suggest that exposure to media violence promotes aggressive and uncontrolled behaviors.(26-30) When such behaviors occur in school (e.g., fighting with other students and arguing with teachers) they would be detrimental to the classroom environment and the student's relationship with teachers and other school personnel.(31) While we could not test all possible pathways shown in Figure 1, in the present research we explored three indirect pathways between visual media exposure and school performance and also tested for possible direct effects of media variables on school performance. We used a prospective analysis with structural equation modeling, including baseline measures of each of the three intermediate variables (substance use, school problem behavior, and sensation-seeking). Hence, we could test the effect of television and movie viewing on changes over time in these hypothesized intermediate variables, and subsequent effects of the intermediate variables on change in school performance. The model included baseline covariates, variables likely to be correlated with both media exposure and school performance, so as to address potential alternative explanations for the observed effects of media exposure on school performance.

Figure 1
Theoretical relationships between media use, intermediate variables, and school performance
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Methods
Design/Setting/Participants
A national sample of U.S. youth aged 10-14 years was recruited between June and October 2003 through a random digit dial telephone survey. Details on the recruitment methods have been published previously.(7;9) Trained interviewers administered the survey. To ensure privacy, a Westat (Rockville, MD) computer-assisted telephone interview system was used so that adolescents could respond to sensitive questions by pressing numbers on the telephone keypad rather than speaking them out loud. Of 9,849 eligible households, parents in 7,492(77%) families consented, and in these families, 6,522(87%) adolescents assented to participation. After the baseline interview (Time 1), participants were interviewed again with follow-ups at 8 months (Time 2), 16 months (Time 3), and 24 months after baseline (Time 4). The study was approved by the institutional review boards of Dartmouth Medical School and Westat, and a Certificate of Confidentiality protecting the data was obtained from NIH.
Main Outcome Measure
We used a 3-item construct to measure school performance at Time 4 assessment. The youth were asked two questions, “How well do you usually do in school?” (Excellent, Good, Average, Below Average), and “What grades do you normally get?” (Mix of A's and B's, Mostly B's, Mix of B's and C's, Mostly C's, Mostly D's and F's). The parents were asked, “How well does your child usually do in school?” (Excellent, Good, Average, Below Average). A composite measure for Time 4 school performance had a Cronbach alpha of 0.84. The first question was also asked at Time 1, and this item was included in the analysis to provide a baseline measure for school performance. In both cases, a higher score indicates worse school performance.
Measures of Media Exposure
The baseline interview included questions to measure both the time spent using media and the content viewed (Table 1). A latent construct for screen exposure was based on two questions about television and videogame exposure on school days, plus a query about whether the adolescent had a TV in the bedroom. For this measure and other measures described subsequently, a higher score indicates more of the named construct.

Table 1
Description of questions used to measure media variables, parenting style variables, and adolescents' disposition & behavior variables
To measure content aspects, participants were presented with lists of 50 movie titles randomly drawn from a pool of 532 popular contemporary movies (each adolescent responded to a unique list of 50 titles). Movies in the individual lists were stratified by Motion Picture Association of America (MPAA) rating so that all lists had a similar MPAA rating distribution (20% G/PG, 40% PG-13, 40% R) reflecting the general availability of movies at the box office during the time of the study. For each participant we calculated the proportion of the movies he/she had viewed that were PG-13 rated and the proportion that were R-rated. Data on venue indicated that 8% of the participants viewed movies primarily in theaters, 51% viewed them primarily through videotape or DVD, and 41% primarily viewed movies through television including cable and pay per view, so television programming was an important venue for movie exposure but not the primary one.
Covariates and Mediators
Our heuristic model (Figure 1) lists a variety of factors that may be correlated with television viewing and school performance but are not assumed to be involved in transmitting the effect of media exposures (covariates). The model includes three constructs that are hypothesized to represent intermediate processes in the relation between media exposure and school performance (mediators), with paths hypothesized from these mediators to the outcome construct of poor school performance.
Covariates
The covariates constituted three general classes of variables: parenting style, adolescents' self-control characteristics and extracurricular activities, and demographics. The specific questions asked to measure these variables, their response categories, and reliability coefficients for the scores used are listed in Table 1. We used two validated measures of parenting style that assess authoritative parenting (maternal responsiveness and monitoring) (32). Self-control was measured by responses to four questions about whether the adolescent delays gratification versus being disinhibited and distractible. Engagement in extracurricular activities was measured with six questions about participation in organized and unorganized sports, clubs, and activities. Demographic variables were assessed by participant report for age, gender, race, and family structure, and by parent report for parental education and household income.
Mediators
The measures for the mediator variables are also listed in Table 1. For sensation-seeking disposition we used a 4-item scale, a subset of questions from the Zuckerman inventory. Problem behavior in school was assessed with four questions that measured the frequency of arguing, fighting, and disobedience. To measure substance use, we asked whether the participant had ever tried cigarettes or alcohol. All mediator variables were measured at both Time 1 and Time 3, so we could test for change in the intermediates as a function of media exposure variables at Time 1.
Statistical analysis
First we tested the association between each covariate and the Time 1 media use variables, and then we tested the association between each covariate and school performance at 24 months. Chi-square analysis was used for categorical variables, analysis of variance was used to compare means among groups, and Spearman correlations were used for ordinal variables.
Structural equation modeling analysis [SEM] tested whether media variables at Time 1 are related to school performance at Time 4 through influencing intermediate processes (mediators) between Time 1 and Time 3. The theoretical predictor variables at Time 1 were a latent construct for screen exposure (based on three indicators) and scores for the proportion of the movies a person had viewed that were PG13 rated and the proportion that were R rated. These predictors were specified as being correlated with demographic variables (age, gender, race, family structure, education, and household income), mother's responsiveness and monitoring, adolescent's self-control and engagement in extracurricular activities, and parental smoking [sum of mother's and father's smoking status]. Baseline values were included for adolescent's substance use [sum of ever used cigarettes and ever used alcohol], sensation-seeking, and school problem behavior. Time 1 school performance was included so as to index change in school performance between Time 1 and Time 4 as a function of the model variables.
The structural model was specified with Time 1 media measures, the covariates, and baseline measures of the mediators as exogenous (i.e., not predicted by any prior construct in the model); correlations among all the exogenous variables were included in the model. Hypothesized intermediates measured at Time 3 were specified as endogenous (i.e., could be predicted by prior constructs in the model) and correlations among the residual terms for these constructs were included. The outcome was a latent construct for poor school performance at Time 4, based on three indicators as described previously.
The model was analyzed in Mplus version 4(33) using maximum likelihood estimation with robust estimates of standard errors; the EM algorithm was employed to model missing data. From the baseline sample of 6,522, participants who reported zero movie exposure at Time 1 (n = 36) were excluded from the analysis because proportion scores for movie exposure could not be computed; hence, the analysis sample size was 6,486. The fit of the model to the data was indexed with the chi-square statistic, the Comparative Fit Index (CFI), and the Root Mean Square Error of Approximation (RMSEA). An initial model was estimated with all paths from Time 1 variables to Time 3 constructs, and all paths from Time 3 constructs to the Time 4 school performance outcome. Several non-significant paths were eliminated from the initial model and additional coefficients were included on the basis of modification indices, including two correlated error terms among indicators for the latent constructs. For the final model, we retained variables having path coefficients that were significant at p < 0.01 with robust estimates.
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Results
The interviewed sample was 6,486 at Time 1, 4,995 at Time 3, and 4533 at Time 4. At Time 1, the mean age of youth was 12 (range 10-14); 62% were White, 18% Hispanic, 11% Black, and 9% were Other race. Overall, 31% had a parent with a college degree, and household income ranged from $10,000 or less (8%) to over $75,000 (30%). Analyses of attrition showed that persons who dropped out of the study were somewhat more likely to be of nonwhite race and lower socioeconomic status, and to score higher on rebelliousness and sensation-seeking.(9) Detailed multivariate analyses of attrition effects showed that the set of study variables accounted for 3-5% of the variance in attrition, so overall the magnitude of attrition effects was moderate and the composition of the continuing sample was similar to that of the baseline sample.
Descriptive data showed that participants reported the following grades for baseline school performance: “excellent” (30%), “good” (42%), “average”/”below average “(28%). There were significant correlations at baseline between the covariates and the media use variables at Time 1 (Table 2). For example as compared to youth with better grades, participants with Average/Below average grades were more likely to have a television in the bedroom, to have more hours of television viewing and video game playing, and to watch a higher proportion of movies that were PG-13 or R-rated; and participants with greater screen exposure and more PG13/R movie viewing scored higher on sensation seeking and school problem behavior. For intermediate variables, the proportion of participants who had ever smoked (even a puff) increased from 10% at Time 1 to 18% at Time 3, and the proportion who had ever drunk alcohol increased from 10% to 19%. The mean score for sensation-seeking increased from 7.9 at Time 1 to 8.3 at Time 3, and the mean score for school problem behavior increased from 2.41 at Time 1 to 2.50 at Time 3. At Time 4, participants reported the following grades: “A's & B's” :61%; “Mostly B's” :12%; “B's & C's”: 20%; “Mostly C's” :6%; “Mostly D's & F's”:1%. Table 3 shows the relationship between baseline covariates and school performance at Time 4.

Table 2
Relationship between media use and other variables at baseline

Table 3
Relationship between baseline variables and poor school performance at 24 months.
The final structural model (Figure 2) had chi-square (127 df, N = 6,486) of 1021.50, CFI of 0.92, and RMSEA of 0.033, these parameters generally indicating reasonable fit of the model to the data. Extracurricular activities and parental smoking were nonsignificant and were dropped from the initial model. The residual correlations of Time 3 variables (excluded from the figure for graphical simplicity) were 0.09 between substance use and school problem behavior, 0.16 between school problem behavior and sensation-seeking, and 0.10 between sensation-seeking and substance use. Hypothesized paths from the Time 3 intermediates to Time 4 school performance were all significant (beta = .06 for substance use, beta = .14 for school problem behavior, and beta = .12 for sensation seeking), thus qualifying these as mediating variables. A direct effect from Time 1 screen exposure to poor school performance at Time 4 (beta = .07, t = 1.80, p < .10) was omitted from the figure because it did not meet the criterion for statistical significance; a path from poor school performance at Time 1 to substance use at Time 3 (beta = .05, t = 4.45, p < .0001) was omitted from the figure for graphical simplicity. The prior variables in the model accounted for 20% to 40% of the variance in the hypothesized mediators. Together the variables in the model, including direct effects, indirect pathways, and the stability coefficient for school performance, accounted for 48% of the variance in Time 4 school performance.

Figure 2
Structural model for relation of Time 1 predictors and Time 3 mediators to Time 4 school performance. Analytic N=6,486. Ovals indicate latent constructs, rectangles indicate manifest variables. Values are standardized coefficients; all coefficients are ...
The coefficients in Figure 2 are standardized to make them comparable; they indicate the change in school performance expected for a 1 standard deviation increase in the predictor, adjusted for all other covariates. Regarding hypothesized pathways, there was a significant indirect effect from more Time 1 screen exposure to worsened school performance at Time 4 through an increase in sensation-seeking at Time 3. Also, Time 1 PG-13 movie viewing had indirect effects for worsened school performance at Time 4 through two mediating variables, increased substance use and increased sensation-seeking at Time 3. The Time 1 measure for R movie viewing had indirect effects on worsened school performance through changes in all three mediators from Time 1 to Time 3: increases in substance use, sensation-seeking, and school problem behavior.
With regard to the effects of other Time 1 variables on school performance, maternal responsiveness and monitoring resulted in better school performance because they decreased school problem behavior and substance use, respectively. In addition to a direct effect for (better) school performance, good self-control also improved school performance because it was related to a decrease in sensation-seeking. Sensation-seeking itself was a key predictor variable aside from the role as an intermediate variable for media effects: initial sensation-seeking led to worsened school performance through effects on higher levels of substance use and school problem behavior at Time 3. In addition to the stability coefficient for school performance from Time 1 to Time 4, poor school performance at Time 1 affected subsequent school performance through its links to increases over time in school problem behavior, sensation-seeking, and substance use.
Effects for Time 1 demographic variables, included in the model but excluded from the figure for graphical simplicity, were as follows. Positive relations to change in substance use were noted for older age (beta = 0.14, p < 0.0001), female gender (beta = 0.05, p < 0.001) and White race (beta = 0.06, p < 0.001). Inverse relations to change in school problem behavior from Time 1 to Time 3 were noted for female gender (beta = -0.04, p < 0.01) and household income (beta = -0.07, p < 0.0001). Change in sensation-seeking was positively associated with White race (beta = 0.07, p < 0.0001) and was inversely associated with household income (beta = -0.04, p < 0.01). Female gender (beta = -0.09, p < 0.0001), White race (beta = -0.06, p <0 .01), higher household income (beta = -0.06, p < 0.01), and higher parental education (beta = -0.08, p < 0.0001) were all inversely related to worse school performance.
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Discussion
Using a longitudinal study design, we found a detrimental effect of visual media use on school performance. We tested three mechanisms for the relation between media use and worsened school performance, through effects of media variables on adolescents' substance use, school problem behavior, and disposition for sensation-seeking. Each of these variables showed change over the study period, and a structural equation modeling analysis showed that both time spent with television/videogames and specific content in movies viewed (PG13 and R ratings) influenced change in school performance through affecting the hypothesized mediators.
After controlling for associations with covariates, the coefficients for the effects of media variables on intermediate processes and ultimately on school performance are similar to those for parenting style (maternal responsiveness and monitoring) and adolescent's self-control. The latter finding is noteworthy because self-control has been shown to have an effect on academic performance similar to that observed for IQ (22). The effect sizes for media variables in the present study suggest that the environmental influence of media exposure may have an effect comparable to that of variables recognized as important determinants of school performance, including demographics (e.g., parental education and income), parenting styles, and self-control characteristics.
The paths shown in Figure 2 are consistent with the concept that both quantity of screen exposure and characteristics of media content affect school performance Amount of screen exposure had an indirect effect through increased sensation-seeking and possibly through a direct effect on school performance consistent with the displacement hypothesis, though the latter effect was only marginally significant. Supporting predictions from our heuristic model, the content variables (PG-13 movie viewing and R-movie viewing) acted on school performance through indirect effects; results showed R-rated movie viewing had the most diverse effects, having paths to all three mediators, but PG13 viewing also had indirect effects through two of the mediators. Thus the results provide more support for media effects operating through behavioral processes, as evidenced by the changes over time in the intermediate variables (sensation-seeking, substance use, and school problem behavior). However, variables germane to alternative hypotheses, such as measures of homework completion or motivation for academics, were not included in the present study and could be assessed in more detail in further research. The results also showed that some of the study variables (e.g., self-control, sensation seeking) had direct or indirect effects on school performance themselves, and these should be considered for inclusion in further studies of academic performance.
While the study had a longitudinal design, control for baseline school performance, and adjustment for other important predictors of school performance, it has some limitations. The measures were brief ones, some of relatively low reliability; more extensive scales and multiple indicators for all constructs would enhance measurement reliability in further research. A possible mediator, time spent sleeping, has been shown in other studies to be an inverse correlate of time spent viewing television and playing videogames (34;35), but was not measured here. Assessment of academic performance through different sources and methods (e.g., school grades, standardized tests) would be desirable where this is feasible. Finally, we did not specifically identify the type of PG-13 or R-rated content in television and movies (violence, sexual behavior, language, etc) that influenced adolescent problem behavior. Including specific content and mediator variables would help clarify how media effects on adolescent behavior occur.
In summary, the present findings are consistent with related research on the deleterious effects of media use on school performance. The new information about the mechanisms through which these effects occur can aid in educational interventions targeting parents. This work provides specific counseling points as to the risks of both quantity and content of media use and their relations to adolescent behaviors and dispositions that can lead to worsening school performance. The results may also be useful through delineating multiple pathways from media exposure to academic outcomes, which can be addressed in media literacy programs.(36;37) Overall, the findings offer strong evidence for parental monitoring of children's television viewing time and, especially, restricting exposure to adult movie content during early adolescence.
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Footnotes
1Presented in part at the annual meetings of the Eastern Society for Pediatric Research in Philadelphia, March 2007 & the Pediatric Academic Societies, May 2007. Supported by CA-77026--National Institutes of Health
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Contributor Information
Iman Sharif, Associate Professor of Pediatrics, Nemours/A.I. DuPont Hospital for Children, Wilmington, DE, Thomas Jefferson University Medical School.
Thomas A. Wills, Professor, Prevention and Control Program, Cancer Research Center of Hawaii, University of Hawaii at Manoa.
James D. Sargent, Professor of Pediatrics, Children's Hospital at Dartmouth, Dartmouth Medical School, Lebanon, NH.
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High school students' academic performance and internet usage.
Abstract:
Considerable controversy surrounds the effects technologies such as the Internet have on human capital accumulation. As with most media, the Internet and related services are capable of delivering enriched learning experiences. However, there are large potential costs to using the Internet and its concomitant services, which may result in degradation of high school students' scholastic performance. In this study, we explore two related questions. First, does Internet usage harm the grades of high school students? Second, to what degree does the intensity of Internet usage affect grades? We utilize data from the 2005 National Survey on Drug Use and Health (NSDUH), which measures educational outcomes, internet use and a host of other correlates. Probit results indicate that excessive Internet use lowers the probability of earning top grades while more moderate use has a positive impact on the probability.

Subject:
Internet (Usage)
High school students (Technology application)
Authors:
Austin, Wesley
Totaro, Michael W.
Pub Date:
01/01/2011
Publication:
Name: Journal of Economics and Economic Education Research Publisher: The DreamCatchers Group, LLC Audience: Academic Format: Magazine/Journal Subject: Business, general Copyright: COPYRIGHT 2011 The DreamCatchers Group, LLC ISSN: 1533-3604
Issue:
Date: Jan, 2011 Source Volume: 12 Source Issue: 1
Topic:
Computer Subject: Internet; Technology application
Product:
Product Code: E197400 Students, Senior High
Geographic:
Geographic Scope: United States Geographic Code: 1USA United States
Accession Number:
256863841
Full Text:
INTRODUCTION

Several reasons might lead technology to assist or impair human capital attainment by students. Youths may employ the Internet in educational matters such as writing papers, searches for answers to questions and communicating with classmates on homework. However, time spent in activities where "surfing the net" occurs could substitute away from time allocated to reading, studying and completing homework. This may hurt academic performance in the short term, which might also diminish the ability or incentive to continue schooling over the longer term.

Within the past decade, the Internet and WWW use have increased substantially--for example, according to Pew Internet & American Life Project Surveys, the percentage of U. S. online users has increased from 40-45% in March 2000 to nearly 80% in April 2009 (Pew Internet & American Life Project Surveys, 2009). Recent expansion of adolescent use of the Internet is the result of an ongoing shift in adolescents' daily behavior patterns. The majority of adolescents from a sample in one study compared their online behaviors to the phenomenon of placing telephone calls, which are typically mundane, the purposes for which are both social and nonsocial (Gross, 2004). Hence, adolescents' Internet use occurs without much thought or consideration--it has become, in effect, just a normal daily activity.

Why is the potential impact of Internet use on educational outcomes relevant for the discipline of economics? Human capital accumulation bears directly and heavily on earning potential (see Grossman, 1972 and Mincer, 1974) and it is widely accepted that strong and statistically significant relationships link individual health and human capital formation. Moreover, the impact of educational policies and factors that affect learning continues to generate widespread public policy concern. Thus, for economists and policy makers, gauging the relationship that technology use has on educational outcomes is worthy of study.

MOTIVATION
Computer access and use among adolescents and other ages have grown considerably over the past decade (Louge, 2006). In fact, more than 80% of U.S. adolescents between the ages of 12 and 17 use the Internet, with roughly half going online daily (Lenhart et al., 2005). The significance of Internet use by children and adolescents has even spawned a new field of inquiry in developmental psychology (Greenfield and Yan, 2006). With the likelihood that Internet usage by adolescents will continue to increase over time, concerns about the impact on high school students' academic performance should be researched. Stakeholders--parents, teachers, administrators, and the students themselves--would benefit from knowing more about the digital environment within which learning occurs. Regardless of whether academic performance is positively or negatively impacted by Internet use, a better understanding and greater awareness about such issues might facilitate changes in pedagogy by educators, as well as learning on the part of students and the support they receive from their parents.

In a conceptual context, we tacitly assume that students utilize the Internet for both academic and non-academic purposes, with the most intense users (which is described in the Data section) spending the most time in non-academic pursuits (e.g. Facebook, downloading music). And our general modeling framework is one of optimization, where there are both educational benefits and costs to the Internet, and where the primary benefit of Internet use is increased human capital accumulation as evidenced by higher grades. At a basic level, Internet use denotes a certain amount of technical savvy which emanates from a student actually learning a new skill--this alone can translate into higher grades. Benefits derived from Internet use usually come about at significant costs, including deployment of the required infrastructure for providing Internet access to students (which this study does not directly address) as well as monetary and time costs devoted to the Internet that detract from educational achievement (see Angrist and Lavy, 2002).

The central issue is to determine what, if any, level of Internet use raises or lowers grades. This entails a quintessential marginal benefit/ marginal cost analysis. This article begins the process by examining quasi-defined levels of Internet utilization (where more venues of use in a defined time period is assumed to equate to more money and time devoted to use) and the resulting impact on student grades.

LITERATURE OVERVIEW

The controversy over whether technology actually improves student learning is one that stirs debate and motivates research. The articles reported in the economics literature have been limited both in quantity and scope with methods and results varying across studies. The literature has focused primarily on the impact of technologies in general on student learning; few studies have examined the direct link between educational outcomes such as GPA and Internet use.

Gratton-Lavoie and Stanley (2009) compare undergraduate students who opted to enroll in online microeconomics classes against those who opted for the traditional in-class course. Results show a higher average score on exams for students enrolled in online classes. However, after accounting for selection bias, results indicate that age positively affects students' average exam scores, with the online teaching mode having a very small effect on average exam scores. Kubey et al. (2001) uses a small survey of 572 students at a public university and finds that heavy Internet use is highly correlated with poor academic performance.

Angrist and Lavy (2002) argue that most studies covering enhancements of learning through technology focus on qualitative factors, such as participant perceptions. Thus, an empirical approach is undertaken which compares outcomes between students who supplement learning with computer aides against those students who do not. Their results show that increased educational use of computers seems to have little or no effect on students' test scores. Ordinary least squares regression estimates demonstrate no relationship between computer-aided instruction and academic achievement, with the exception of a negative effect on eight-grade mathematics scores.

Ball et al. (2006) examine the effect of employing wireless handheld technology by students on academic performance in undergraduate principles of economics courses by way of a controlled experiment. One group of students (experimental group) were equipped with wireless handheld devices that allows interactive participation with standard economics games, multiple choice tests, and communication with the instructor during class time. The second group (control group) was not given the devices. Course content, assignments, exams, and so on, were identical between both groups. Results show that students in the experimental group earned final grades that were an average of 3.2 points higher than did the students in the control group.

Anstine and Skidmore (2005) assess whether MBA students in online economics classes learn as much of the material (measured by average exam scores) as did their counterparts in the traditional economics classes. Specifically, a small sample of MBA students was given the option to enroll in either an online or traditional class. Accounting for sample selection bias, regression analysis proffers that students in the online classes did not learn as much, suggesting that the online learning environment is less effective than the traditional classroom environment.

Jackson et al. (2006) studies the impact of home Internet use on academic performance of 140 low-income children between December 2000 and June 2002. The degree of Internet use is calculated using four measures: minutes per day spent online, logins per day, number of domains visited per day, and number of emails sent per day. Academic performance of participants was measured by GPA and standardized test scores on the Michigan Educational Assessment Program (MEAP). Results suggest that children with greater Internet use had higher GPAs and higher MEAP scores. However, the higher MEAP scores were only in the reading portion, with Internet use having no effect on the mathematics portion of the MEAP test.

It is worth noting that at least one study examined adolescents' activities while online (Hunley, Evans, Delgado-Hachey, Krise, Rich, Schell, 2005). Employing a logbook approach whereby students documented their time for a seven-day period, Hunley et al. (2005) found that at least 50% of the students (N = 101) logged the following activities while online (hours per week indicated in parenthesis): visiting web sites (1.27), playing games (4.43), reading the news (0.73), researching information (1.22), and emailing (1.13). Fewer than 50% of the students spent time chatting (2.12), word processing (2.13), shopping (1.60), and "other" (2.00).

Many studies have limited sample sizes and education-related variables. In contrast, our analysis employs a much larger sample size of students for which there is substantially greater information on demographics and household characteristics. Moreover, the number of variables available in our dataset is large and generally exceeds the number of variables found in the datasets in the above studies.

DATA

Since its inception in 1979, the National Survey on Drug Use and Health (NSDUH), sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA), is administered annually to approximately 55,000 civilian, non-institutionalized individuals age 12 and over, chosen so that the application of sample weights produces a nationally representative sample with approximately equal numbers of respondents from the 12-17, 18-25, and 26 and over age groups.

Variables on Internet use are collected and compiled by SAMHSA administrators only for the 2005 survey; hence these are the data we analyze. Our sample consists of 12,184 enrolled high school students. Data from the NSDUH allow for both breadth and depth of coverage on the topic. Breadth comes from the ability to study aspects of educational outcomes using data from an elaborate questionnaire administered to 12-17 year olds on a wide array of youth experiences. An assortment of variables are observed, therefore, that have the potential to serve as predictors for grades in the proposed model. Depth is provided by variables on race, gender, family income, family composition, religion and health.

A potentially problematic attribute of the data is non-random measurement error emanating from the self-reported nature of responses. However, studies on the quality of self-reported academic variables data suggest that such reporting bias should be minimal. Cassady (2001) finds that self-reported GPA values are "remarkably similar to official records" and therefore are "highly reliable" and "sufficiently adequate for research use." Hunley et al. (2005) address concerns about self-reported survey data by way of demonstration of the reliability of survey data as "appropriate" for measuring accurately adolescents' Internet use. Specifically, students provided estimates of their Internet use, and then logged their actual daily Internet use for a one week period. Comparisons between estimated Internet use and actual use showed reliability of the self-reported estimates. Their conclusion is that researchers should feel confident about self-reported survey data pertaining to Internet use.

RESEARCH METHOD AND EMPIRICAL SPECIFICATION

Consider the following equation, in which Grades is a function of exogenous factors with Internet usage of prime importance,

Grades = [[beta].sub.0] + [[beta].sub.1]IU + X[[beta].sub.2] + [epsilon]

In the above equation, which applies to individual NSDUH respondents (with the corresponding observation-level subscript suppressed), IU represents venues of Internet usage in the past 30 days. Vector X represents a set of other exogenous variables that conceivably affect grades. The [beta]'s are parameters to be estimated and s is the error term.

Grades

We investigate effects on grades by analyzing the probability the student receives an 'A' or 'B' average or an average of 'D' or below. Grades is measured using a 1-4 scale with '4' representing A+, A, A- ; '3' representing B+, B, B-; '2' representing C+, C, C- and '1' representing D or below.

Internet Usage

When the survey is administered, respondents are queried on venues of Internet utilization in the past 30 days. We categorize Internet users in three forms: Level 1; Level 2; and Level 3. For individuals in Level 1, the Internet was utilized at home, at school, at a friend's house, at a cafe with Internet access, over a cell phone and some other place--this variable is "open" and does not have specific options. For those in Level 2, the Internet was utilized at home and at school. For those in Level 3, the Internet was utilized only at school. We term those in Level 1 as intense Internet users; those in Level 2 as moderate users; and those in Level 3 as light users. For light usage, Internet access is subject to time constraints (i.e. hours of operation for schools), whereas for intense and moderate usage, there is virtual 24 hour access. To avoid the "dummy variable trap" in the regressions, those that did not use the Internet (no use) in the past 30 days is the omitted category and is used as the category of comparison.

Explanatory Variables

Several variables from the NSDUH data are considered explanatory in equation (1): age indicators are included for whether the student is 14, 15, 16 or 17 years old with age 13 as the omitted category to avoid the "dummy variable trap." Binary indicators are included for whether the mother or father resides in the household, for whether parents assisted the student with homework always or sometimes in the past 12 months, with "never" as the omitted category, and for whether the student is currently classified as a sophomore or junior/ senior, with "freshman" as the omitted category. We also include a binary variable for school type (public or private). Potential endogeneity (stemming from students' "self-selecting" into certain learning environments by choosing to attend certain schools) should be mitigated in that location of high school attendance is largely determined by parental preferences in occupation, living conditions, as well as other correlates.

To control for the possibility that a student subscribes to a "work hard-play hard" ethos and therefore heavily utilizes the Internet yet maintains high grades, a binary indicator is incorporated for a student that heavily uses the Internet and also states that school work is important/ meaningful, and is thus more likely to have good grades. We term this a "high motivation" student.

Family income is measured in four categories: $10,000-$19,999; $20,000-$49,999; $50,000-$74,999; and $75,000 or greater, with $10,000-$19,999 as the omitted category. A measure for the number of times the student moved in the past year is incorporated as is a binary indicator for gender. For race, indicators are specified for Caucasians, African Americans and Asians, with non-white Hispanics as the omitted category. Further, student physical health is measured as follows: great health, good health and fair health with "poor health" as the omitted category. A factor for religiosity is also included given that this may proxy for increased academic discipline. For this factor, a binary variable is created and coded as '0' if religion does not influence decisions and '1' if it does. Religiosity has been linked to educational outcomes (Wolaver, 2002).

EMPIRICAL FINDINGS

Table 1 presents select summary statistics. Intense Internet use is 0.047 and moderate Internet use is 0.491 while light use is lower with a mean of 0.350--all indicating abundant exposure to the Internet. Approximately eight percent of students attend private schools. Fathers are less likely to be present in the household than are mothers and the proportion of parents that always help with homework is also quite high (0.54). Caucasians comprise approximately 63 percent of the sample, African Americans about 14 percent, while non-white Hispanics and Asians account for about 15 percent and three percent, respectively. About one third of students report being in excellent health, with 41 percent reporting good health, and a large proportion (0.651) state that religion influences decision making.

The Effects of Internet Use on the Probability of Obtaining an 'A' or 'B'

As shown in Table 2, intense Internet use is significant and lowers the probability of earning an 'A' or 'B' versus lower grades; light Internet use also lowers the probability while moderate use elevates the probability of an 'A'/ 'B'. The Log Pseudolikelihood is -6707.84. Intense Internet use reduces the probability of achieving an 'A'/ 'B' by 0.03--for students that are intense Internet users, the probability of having an 'A'/ 'B' average is undercut by approximately 5 percent compared to students who did not use the Internet at all in the past 30 days (to which, for parsimony, we refer to as 'no use' for the remainder of the section). If a student reports moderate usage, the probability of having an 'A'/ 'B' increases by 0.08 compared to no use--moderate users have a roughly 12 percent increased probability of earning this average compared to no use. Light internet users have about a 6 percent lower probability of earning an 'A'/ 'B' versus no use.

The negative effects associated with intense Internet utilization may indicate that this level of usage actually impairs the learning process (perhaps by lowering attention span) which, in turn, reduces the capability of the student to earn top grades. Also, students using the Internet at a friend's house or cafe may be distracted by non-academic conversations even when using the Internet for academic purposes. In addition, intense use may translate into less time spent on and homework and studying, compared to no use; hence, grades are lower for those in the intense use category versus no use.

Interestingly, light users have a diminished probability of an 'A'/ 'B' versus no use. This may provide evidence that when students have Internet access only at school, that time is utilized "surfing the net" for recreational purposes (e.g. Facebook), which is time subtracted from studying; therefore, grades are actually lower for those in the light use category compared to no use. Overall, moderate use (which includes home use as a major component) has the most positive impact on grades, which could indicate that home Internet use by students is more focused on academic pursuits compared to other venues.

As stated in our Motivation section, there is an opportunity cost involved in using the Internet, which includes reduced study time and possibly increased devotion of the students' monetary resources to Internet services that detracts from the prospect of receiving an 'A'/ 'B' average. These results imply that those costs are salient. This is an interesting contrast to the study done by Jackson et al. (2006), which (as discussed earlier) found that adolescents who used the Internet more had higher grade point averages. An additional contrast to our results and the results of the Jackson et al. (2006) study are the results of Hunley et al. (2005), which did not show a significant relationship between time spent on the computer at home and grades.

The Effects of Internet Use on the Probability of a 'D' or Lower Average

Table 3 presents the regression estimates for the probability the respondent has a 'D' or lower grade versus other grades. The Log Pseudolikelihood is -6707.84. Intense Internet use elevates the probability of achieving a 'D' or lower grade by almost 0.02. If a student reports moderate usage, the probability of having a 'D' or lower average falls by 0.03 compared to no use, but rises by 0.01 for light use (compared to no use). Intense users have a higher probability of a 'D' or lower grade (about 25 percent), while moderate users have a decreased probability (approximately 28 percent) of having this average, compared to students who report no use. Light users have a roughly 13 percent increased probability of a 'D' or lower average compared to no use.

The estimated effect for intense use is rather large, even accounting for the fact that the outcome incorporates grades of 'D' and 'F'. Again, there may be large opportunity costs associated with such rigorous Internet use which undermines academic achievement. Thus, grades are lower and higher failure rates may account for some of the largeness. Moreover, moderate users fare better academically compared to no use: moderate users have a decreased probability of earning a 'D' or less versus those students' that report no Internet use. For light users, the probability of earning 'D' or lower is higher compared to no use, again potentially indicating that students who only have Internet access at school spend this time in recreational use and hence suffer lower grades as study time falls.

The Effects of Other Explanatory Variables on Grade Probabilities

Many of the other explanatory variables have a significant impact on grades. Interestingly, "High Motivation" students have a greater probability (0.12) of earning an 'A'/ 'B' average but the probability of earning a 'D' or lower is reduced by 0.06. The presence of mothers in the households generally has a favorable impact on 'A'/ 'B' grades, while the presence of fathers is not significant. However, parental involvement does have profound effects as assisting with homework raises student grades. For example, if a parent always helps with homework, the probability of an 'A'/ 'B' rises by approximately 0.06; the probability of 'D' or lower falls by 0.02.

Those that attend private schools have a 12 percent greater probability of earning an 'A'/'B' and a 27 percent lower probability of having a 'D' or lower average. In addition, Caucasians and Asians have higher probabilities of achieving an 'A'/ 'B' average versus African Americans, while females enjoy a higher probability of 'A'/ 'B' and versus males. Higher levels of income are also significant in some instances. Students in families earning $20,000-$49,999 and $50,000-$74,000 a year have a greater probability of obtaining an 'A'/ 'B' average (0.037 and 0.197 respectively) and lower probability of having a 'D' or less (-0.008 and -0.017 respectively), compared to families earning $10,000-$19,999.

As students advance in age, the probability of having an 'A'/ 'B' mildly decreases and the probability of a 'D' or lower increases. Of course, this may indicate an increasing opportunity cost involved in studying and in other educational activities as students learn to drive, enjoy more personal freedom and possibly rebel against parents. The effects are opposite for class standing where students that are juniors/ seniors have enhanced probabilities of earning an 'A'/ 'B' and lower probabilities of earning a 'D' or less. This could imply that at least some students study more in an effort to "drive-up" GPA's for approaching college entrance.

In keeping with broader literatures on human capital, students that are in better health also earn higher grades (higher probability of 'A'/ 'B'; lower probability of 'D' or less), while those that relocate more often have lower 'A'/ 'B' probabilities and higher 'D' and below probabilities. In addition, religiosity impacts grades: students who state religious beliefs influence decisions have a 0.064 greater probability of having an average 'A'/ 'B' average and a 0.025 diminished probability of having a 'D' or less than 'D' average. For the most part, our results demonstrate that the number of venues of Internet use have an impact on the academic achievement of high school students even after controlling for a host of other factors.

CONCLUDING REMARKS

For this study, there is evidence that the grades of high school students are lowered when additional venues of Internet access are utilized. Specifically, when all venues of Internet use are exhausted, which we refer to as intense use, grades are lower when compared to students that report no Internet use. Moreover, students that only use the Internet at school, which we term light use, also suffer from lower grades compared to those that did not utilize the Internet. Conversely, students that used the Internet at school and at home, which we term moderate use, enjoy higher grades versus those that did not use the Internet. Our model supports a hypothesis of "optimal" Internet use. Results indicate that grades are higher when students undertake moderate Internet use; however, grades decline when students are below or surpass a certain threshold (i.e. optimum). Potentially large opportunity costs of Internet use (in the possible form of detractions from time spend studying and engaging in other activities that enhance grades) may be present for intense and light Internet users.

The results provide useful information to high school administrators, teachers, counselors, parents, and students, when they consider implications for use of the Internet in an educational setting. Moreover, university administrators and faculty will find the results helpful, since many high school graduates continue their education by way of college and university studies. From a policy perspective, high school administrators may wish to consider guidelines that curtail non-academic Internet use in schools.

Our data did not explicitly outline whether students' Internet use was for academic or social purposes; therefore, future research that incorporates this data would provide more information. In addition, the costs of deploying the required infrastructure needed to provide Internet access to students would prove useful in continued analyses of the benefits and costs of the Internet.

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Wesley Austin, University of Louisiana at Lafayette

Michael W. Totaro, University of Louisiana at Lafayette
Table 1. Descriptive Statistics
(n=12,184)
Standard
Variable Mean Deviation

Probability of an 'A' or 'B' grade 0.684 0.465
Probability of a 'D' or lower grade 0.070 0.256
Intense Internet Use (past 30 days) 0.047 0.213
Moderate Internet Use (past 30 days) 0.491 0.499
Light Internet Use (past 30 days) 0.350 0.407
No Internet Use (past 30 days) 0.112 0.315
High Motivation Student: heavy internet use/ positive school attitude 0.713 0.452
Mother in household 0.918 0.275
Father in household 0.732 0.443
Respondent is female 0.501 0.500
Attending private school 0.082 0.274
Age of student (13 years old) 0.134 0.340
Age of student (14 years old) 0.215 0.410
Age of student (15 years old) 0.228 0.420
Age of student (16 years old) 0.222 0.415
Age of student (17 years old) 0.192 0.394
Race (Caucasion) 0.631 0.483
Race (African American) 0.136 0.342
Race (Asian) 0.030 0.170
Race (non-white Hispanic) 0.152 0.359
Sophomore 0.220 0.414
Junior or Senior 0.324 0.468
Family income (less than $20,000) 0.180 0.344
Family income ($20,000-$49,999) 0.345 0.475
Family income ($50,000-$74,999) 0.202 0.402
Family income ($75,000 or more) 0.286 0.452 number of times moved (past year) 0.322 0.696
Parents help with homework (always) 0.547 0.498
Parents help with homework (sometimes) 0.230 0.421
Student health status (great) 0.331 0.471
Student health status (good) 0.418 0.493
Student health status (fair) 0.213 0.410
Religion influences decisions 0.651 0.477

Table 2. Probit estimates for the probability of an 'A' or 'B'

(n = 12,184)

Log Pseudolikelihood = -6707.84

Robust Standard
Explanatory variables Coefficient Error

Intense Internet use -0.034 *** (0.021)
Moderate Internet use 0.082 * (0.014)
Light Internet use -0.039 * (0.014)
High Motivation Student 0.116 * (0.011)
Mother in household 0.057 * (0.016)
Father in household 0.012 (0.011)
Respondent is female 0.145 * (0.008) school type (private) 0.082 * (0.015)
Age of student (14 years old) -0.047 * (0.016)
Age of student (15 years old) -0.127 * (0.019)
Age of student (16 years old) -0.193 * (0.024)
Age of student (17 years old) -0.191 * (0.028)
Race (Caucasian) 0.089 * (0.020)
Race (African American) -0.011 (0.022)
Race (Asian) 0.198 * (0.018)
Sophomore 0.073 * (0.014)
Junior or Senior 0.137 * (0.018)
Family income ($20,000-$49,999) 0.006 (0.013)
Family income ($50,000-$74,999) 0.037 ** (0.015)
Family income ($74,999 and over) 0.097 * (0.014) number of times moved (past year) -0.035 * (0.006)
Parents help with homework (sometimes) 0.021 ** (0.006)
Parents help with homework (always) 0.057 * (0.008)
Student health status (great) 0.217 * (0.019)
Student health status (good) 0.164 * (0.021)
Student health status (fair) 0.062 * (0.022)
Religion influences decisions 0.064 * (0.009)

* statistically significant at 1%

** statistically significant at 5%

*** statistically significant at 10%

Table 3. Probit estimates for the probability of a 'D' or lower

(n = 12,184)

Log Pseudolikelihood = -2697.80 Robust Standard
Explanatory variables Coefficient Error

Intense Internet use 0.018 ** (0.010)
Moderate Internet use -0.021 * (0.005)
Light Internet use 0.009 *** (0.005)
High Motivation Student -0.053 * (0.006)
Mother in household -0.007 (0.007)
Father in household 0.001 (0.004)
Respondent is female -0.025 * (0.003) school type (private) -0.019 * (0.006)
Age of student (14 years old) 0.011 (0.007)
Age of student (15 years old) 0.033 * (0.009)
Age of student (16 years old) 0.065 * (0.014)
Age of student (17 years old) 0.053 * (0.016)
Race (Caucasian) -0.012 -0.008
Race (African American) -0.013 *** (0.007)
Race (Asian) -0.037 * (0.006)
Sophomore -0.002 * (0.005)
Junior or Senior -0.048 * (0.006)
Family income ($20 ,000-$49,99 9) 0.005 (0.005)
Family income ($50,000-$74,999) -0.008 (0.006)
Family income ($74,999 and over) -0.017 * (0.006) number of times moved (past year) 0.011 * (0.002)
Parents help with homework (sometimes) -0.001 * (0.002)
Parents help with homework (always) -0.020 * (0.003)
Student health status (great) -0.057 * (0.006)
Student health status (good) -0.051 * (0.007)
Student health status (fair) -0.021 * (0.006)
Religion influences decisions -0.025 * (0.004)

* statistically significant at 1%

** statistically significant at 5%

*** statistically significant at 10%
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Journal of Media and Communication Studies Vol. 3(5), pp. 198-202, May 2011
Available online http://www.academicjournals.org/jmcs
ISSN 2141 – 2545 ©2011 Academic Journals
Full Length Research Paper
Mass media as correlates of children’s behavioural problems in Kwara State, Nigeria
K. K. Kadiri1 and A. Y. Muhammed2*
1Department of Mass Communication, University of Ilorin, Ilorin, Nigeria.
2Department of Sociology, University of Ilorin, Ilorin Nigeria.
Accepted 28 April, 2011
In the last 70 years, mass media such as radio, motion pictures, recorded music and television have become important agents of socialization. Television in particular is a critical force in the socialization of children. Many parents in essence allow the television set to become a child’s favourite “playmate”. It is generally agreed that children are exposed to a great deal of violence in the process. Mass media are important in socialization because they provide models of behaviour particularly among children. These models can have powerful effects on their behaviour, leading to behavioural problems. It is against this background that this study examines the relationship between mass media and children’s behavioural problem in Kwara State of Nigeria in 2010. To achieve this, survey design was employed among 816 children exposed to mass media. The major research hypothesis tested revolved around the relationship between mass media and children’s behavioural problems. The data were analysed using chi-square and Pearson product moment correlation co-efficient to indicate that the two factors were related. Based on this, it was recommended that public policy on media should focus on eliminating violent scenes in the mass media.
Key words: Mass media, behavioural problems, children, communication, technology.
INTRODUCTION

Behavioural problems can occur in children of all ages. Very often they start in early life. Toddlers and young children may refuse to do as they are asked by adults, in spite of being asked many times. They can be rude, swear and have tantrums, or an outburst of aggressive or disruptive behaviour (Carr, 2000). Some children may even have serious behavioural problems such as physical fights, drug abuse, arson etc. Rutter and Taylor (2002) admit that there are behavioural problems when the child continues to behave badly for several months or longer or if the behaviour is not of the ordinary and it seriously breaks the rules accepted in his family and community, these behavioural problems may be disruptive, delinquent and deviant. They opined that these sorts of behavioural problems can affect a child‟s development and also interfere with his ability to live a
*Corresponding author. E-mail: aymuhammeduil@yahoo.com. Tel: +234-8034290060. normal life. In reference to the aforementioned, Reza and Mercy (2001) report that violence by young persons is one of the most visible forms of behavioural problems in human society. According to them, world newspapers and broadcast media report daily on violence by gangs in schools or young people on the streets. Young people‟s violence deeply harms not only its victims but also their families, friends and communities. Its effects are seen not only in death, illness and disability, but also in terms of the quality of life. Behavioural problems by young ones add greatly to the cost of health and welfare services, reduce productivity, decrease the value of property, disrupt a range of essential services and generally undermined the fabric of the society.
The issue of mass media and children has become very important not only because of its communicability but as a result of its effects on children‟s behaviour. Children are exposed to different social environments and hence they react differently to mass media. A typical African child has different social environments from that
Of a child in a developed country, like Britain or

American (Gbadeyan, 2008).
In Nigeria, children are not exposed to those hobbies their counterparts in developed countries are exposed to. There are few recreational facilities in most of these developing countries. For instance, in Nigeria, children have recreational centres in Ibadan, Lagos and a few other cities. This consequently makes them rely on viewing television as a past-time and hobby. They watch television and home videos for long hours immediately after closing from schools about 2.00 pm till late hours in the night. In the process, they are exposed to so many hours of television commercials and programmes which eventually have consequential effects on their behaviour.
Children are surrounded by mass media. They are an ideal target, simply because they are avid viewers. Most big name brands and advertising agencies use television for example to try and influence children as consumers. Their behavior is a reflect of such influence: they choose what they consume, insist on their favourite brands and influence their families‟ choice (The Courier UNESCO 2001; Children Now, 1998; Gbadeyan, 2008).
Television and other broadcast media have been in existence over a century. However, there have been serious concerns about the impact of mass media on children‟s behaviour since inception. Since early 1950s, there has been growing pressure mounted by parents, teachers and social scientists on their legislators and governments “to do something” about the amount of violence within the mass media, particularly television. In addition to this initial worry about violence and other obnoxious issues around mass media, many professionals and parents are now questioning the quality of programmes designed by mass media for children, the amount of advertising directed at young viewers, and the way mass media portrayed men, women and ethnic minorities, and the effects of time that children are exposed to mass media (Murray and Lonnborg, 1995).
The perceived effects of the media on children are manifold. The media have been blamed for alienation, copy-cat killings, producing apathy amongst the popula-tion, reinforcing prejudices and trivializing important issues. Of course, the extent to which we blame the media for negative effects depends upon how active or passive an audience is. This study is an attempt to assess the effects of mass media on children‟s behavioural problems.
The media (traditional and new)
In the twenty-first century, communication technology is such that information can be shared instantaneously by millions of people simultaneously, almost anywhere around the world. Communication, which is the transfer of information from one individual or group to another, whether in speech or through the mass media of modern times is crucial to any society. One influential early
Kadiri and Muhammed 199 theorist of communication media was the Canadian author Marshall McLuhan. According to Giddens (2006), the medium is the message, that is to say, society is influenced much more by the type of the media than by the content or the messages, which the media convey (Giddens, 2006).
A society in which satellite television plays an important part is obviously different from the one that relies on the printed word carried aboard on ocean liner. We live today in an interconnected world in which people experience the same events from many different places. Thanks to globalization and the power of communications techno-logy, people from Caracas to Cairo are able to receive the same popular music, news films and television programmes, twenty- four-hours news channels report on stories as they occur, and broadcast coverage of the unfolding events for the rest of the world to see. Films made in Hollywood or Hong Kong reach audiences around the world, while celebrities such as David Beckham and Tiger Woods have become household names on every continent (Giddens, 2006).
It is important to note that we have been witnessing a process of convergence in the production, distribution and consumption of information. Whereas at one time ways of communicating, such as print, television and films, were relatively self contained spheres, they have now become intertwined to a remarkable degree. The divisions between forms of communication are no longer as dramatic as they once were; television, radio, newspapers and telephones are undergoing profound transformation as a result of advances in technology and the rapid spread of the Internet. While newspaper remains central to human lives, the ways they are organized and deliver their services are changing as newspaper can be read online. Mobile telephone use is exploding, and digital television and satellite broadcasting services allow an unprecedented diversity of choice for viewing audiences.
Opening the global space of communication again is the Internet. The internet is at the heart of this com-munication revolution. With the expansion of technologies such as voice recognition, broadband transmission, web casting and cable links, the internet threatens to erase the distinction between traditional forms of media and to become the conduit for the delivery of information, entertainment, advertising and commerce to media.
Common behavioural problems in children
Gottfredson (2001) classifies behavioural problems in children into psychosocial disorders, habit disorders, anxiety disorders, disruptive behaviour and sleeping problems. The specific behaviours used to produce a diagnosis of behavioural problem fall into four groups: aggressive conduct that causes or threatens physical harm to other people or animals, non-aggressive
200 J. Media Commun. Stud. behaviour that causes property loss or damage, deceitfulness or theft, and serious violations of rules. Aggression and threats to do physical harm to people or animal is a very common behaviour for those with behavioural problem. Often, harm and torture of animals are displayed early in these children, even as early as 5 to 6 years old. Aggression is also showed towards other persons (children and adults) and include bullying, physical assault (body or with weapons), and even forced sexual abuse. Furthermore, behavioural problem does not have to be physically violence towards others. Physical violence can include aggression towards non-human targets, exam-ples include destruction of property (school vandalism, destruction of uninhabited homes) or fire starting. Fire starting is a very popular activity among those with behavioural problems. Destruction of property has little to do with revenge or making any form of statement, it is a thrill seeking behaviour (Ishola, 2009). In a similar manner, the thrill factor of stealing is far greater for the child with behavioural problem than the attainment of these items. Some stealing may be to attain substances of abuse or to use the items to impress someone, but again, it is the thrill, not the attainment of wealth that is the reason for the theft (Banmrind, 1991). Lying is part of a game, a way out of a problem or a way to manipulate. Those with behavioural problems know how to manipulate situation very difficult to diagnose because they can change their tactics to fit the situation. If they get into trouble in school, they can change their story to make themselves the victims and the actual victim the perpetrator. It is very difficult to read them and know when they are telling the truth and manipulating the situation (Ishola, 2009). Furthermore, behaviours that can be the most destructive to family and friends of children with behavioural problems are deceitfulness, manipulation, and theft. This stage is characterized by lack of conscience by the children. There are no boundaries for these children. All that is important to them is that their needs are met, even if they cause great harm to their supposed loved ones. The children with behavioural problems are only interested in their own needs, meaning that they have no problem with breaking rules they do not agree with, which include most rules that will impede their current impulsive need. Intervention strategies Many societies consider delinquency, violence, drug and alcohol abuse, smoking, and early patterns of sexual behaviour that risk sexually transmitted diseases and pregnancy among unmarried teenagers to be serious problems. These can ruin adolescents‟ lives by making them to be put in jail, by limiting their education and vocational training opportunities. Risk factors for behavioural problems occur throughout children‟s development, and children face new risks as they mature and encounter new challenges. Children‟s environments also become more complex as they grow older, making intervention more difficult. Negative events and conditions that are stressful create difficulties for both parents and children (Briere, 1992). The entertainment media, including cinema, television and music, also affect young people‟s perceptions of norms of behaviour. Evidence suggests that seeing aggressive behaviour on television may make some children more aggressive. Some movies, television and music produced in the United States in particular may over emphasize undesirable behaviour. Parents can reduce the harmful effects of international and local media by keeping children from viewing or listening to programmes that present aggressive behaviour and other problem behaviour in positive light (Jason and Hanaway, 1997). School can also reduce the harmful effects of aggressive media by teaching children that these shows are not accurate on the extent or result of violence and substance use. The school programmes and mass media messages used to emphasize positive things that young people are doing and to show that most young people are opposed to substance use and violent behaviour. Schools can reduce the amount of time children spend viewing or listening to programmes that present aggressive behaviour and other problem behaviour in positive ways. Theoretical anchorage (cultivation theory) The cultivation theory looks at the mass media as a socializing agent and investigates whether television viewers come to believe the television version of reality the more they watch it. The theory contends that television drama has a small but significant influence on the attitudes, beliefs and judgments of viewers concerning the social world. The focus is on “heavy viewers”. People who watch a lot of television are likely to be more influenced by the ways in which the world is framed by television programmes than individuals who watch less, especially regarding topics of which the viewers have little first-hand experience.
Evra (1990) argues that by virtue of inexperience, young viewers may depend on television for information more than other viewers do. Mass media are seen as dominating “symbolic environment”. Cultivation theory presents the mass media not as windows on or reflection of the world, but a world in itself (McQuail and Windahl, 1993). The theory argues that the over-representation of violence on mass media constitutes a symbolic message about law and order rather than a simple cause of more aggressive behaviour by viewers. Cultivation theorists argue that heavy viewing leads viewers to have more
Kadiri and Muhammed 201 Table 1. Relation between mass media and children‟s behavioural problems. Variables | N | Degrees of freedom (df) | Observed X2 | Critical x2 0.05 (a = 0.05) | Decision | Mass media and behavioural problems | 816 | 225 | 12,240.000 | 124.342 | Reject H0 |

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Review of Educational Researchrer.sagepub.com 1. doi: 10.3102/00346543044001001 REVIEW OF EDUCATIONAL RESEARCH Winter 1974 vol. 44 no. 1 1-67
The Effectiveness of Alternative Instructional Media: A Survey
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