Television Exposure and Academic Skills of Children: New … · Ashish Singh and Sarthak Gaurav / Journal of Communication Technology and Human Behaviors (2013) 1: 1-24 3 exposure

Journal of Communication Technology and Human Behaviors

(2013) 1: 1-24

doi:10.7726/jcthb.2013.1001

Research Article

______________________________________________________________________________________________________________________________

*Corresponding e-mail: [email protected]

Indira Gandhi Institute of Development Research, Mumbai, India

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Television Exposure and Academic Skills of Children:

New Findings from India

Ashish Singh* and Sarthak Gaurav

Received 10 September 2012; Published online 20 October 2012

© The author(s) 2012. Published with open access at uscip.org

Abstract The studies associating television viewing to performance are primarily based on developed countries. The

effect of television on children in developing countries, like India, might be different from that of the

developed countries, owing to cultural and socioeconomic differences. Additionally, in the Indian case, no

study has systematically analyzed the relationship between children’s academic skills and television viewing.

We examined the association between academic skills (Reading, Mathematics and Writing) of Indian children

and television viewing using a sample of children (aged 8-11 years) who were in school or had ever attended

school, from a universe of all the households included in a micro unit recorded nationally representative

survey (IHDS, 2004-05). Relevant socioeconomic, demographic, parent/household-level controls were

included in the multivariate analysis. The impact of content of the television programs was also controlled in

the analysis. The analysis was done at two levels: first, for the full sample; and second for subsamples, formed

first by sex and second by economic status. Findings suggested positive correlation between overall viewing

and the reading skills of boys and the mathematics skills of girls, but negative correlation with the writing

skills of both. The correlation of educational content with academic skills also differed by gender, with a

positive correlation with the three skills of girls but a positive correlation with only the writing skills of boys.

Moreover, educational content was positively correlated with the skills of children belonging to the lowest

wealth class but had no correlation with the skills of the children belonging to the highest wealth class.

Keywords: Television exposure; Academic abilities; Children; India

1. Introduction

The research on possible relationships between exposure to television and a child’s development

dates back to 1950s (Greenstein, 1954). The bulk of research on the topic points to the deleterious

effects of children’s television viewing on outcomes such as obesity, inactivity, attentional

problems, sleep disorders, aggression, and high-risk behavior (Liebert, 1986; MacBeth, 1996;

Robinson et al., 1998; Sargent et al., 2001; Villani, 2001; Earles et al., 2002; Dalton et al., 2003;

Christakis et al., 2004; Sargent et al., 2004). However, there are a few studies which found that

television viewing can be good for children. An extensive review of this body of literature can be

Ashish Singh and Sarthak Gaurav / Journal of Communication Technology and Human Behaviors (2013) 1: 1-24

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found in Kondo and Steemers (2010). These conflicting perspectives make it difficult to generalize

the influence of television viewing on child outcomes.

The generalization is even more difficult in the domain of cognitive ability where the evidence is

considerably more ambiguous; some studies have shown overall television viewing time and

viewing of non-educational programs to be harmful for children’s school readiness and cognitive

outcomes (Friedrich and Stein, 1973; Gadberry, 1980; Singer, 1990; Voort and Valkenburg, 1994;

MacBeth, 1996; Geist and Gibson, 2000; Wright et al., 2001; Hancox et al., 2005; Sharif and Sargent,

2005; Zimmerman and Christakis, 2005), but others have shown educational television to be

beneficial, with a number of experimental studies reporting that children who watched episodes of

educational television demonstrated improvements in educational domains immediately

afterwards (Bogatz and Ball, 1971; Singer and Singer, 1981; Davis, 1989; Hall et al., 1990; Rice et al.,

1990; Huston, 1992; MacBeth, 1996; Singer and Singer, 1998; Crawley, 1999; Anderson et al., 2001;

Naigles and Mayeux, 2001; Wright et al., 2001; Zill, 2001; Buckingham and Sefton-Green, 2004;

Fisch, 2005).

Further, there are few studies that found a positive influence of overall viewing time (including

non-educational programmes) on educational achievement: Schramm et al. (1961) reported that

heavy television viewing was associated with higher mental ability in young children; Johnson et al.

(1983) found higher math grades associated with a preference for sports, family, game and cartoon

shows; Gentzkow and Shapiro (2006) found that children who watch television perform marginally

better in reading and general knowledge at school. There are also studies which did not find any

relationship between time spent watching educational TV and educational domains, particularly

reading (Huston et al., 1999; Lyle and Hoffman, 1972; Schramm et al., 1961).

The ambiguity gets even more complicated by the results of studies that found different influences

in different settings or on different abilities. For example, Zimmerman and Christakis (2005) found

a detrimental effect of overall TV viewing on reading recognition, reading comprehension and

memory for digit scan for television viewing before age 3 but a beneficial effect of TV viewing on

reading recognition at ages 3 to 5 years. Schramm et al. (1961) reported that heavy television

viewing was associated with higher mental ability in young children and lower mental ability in

adolescents, but they found no relationship between viewing time and ability among older,

preadolescent children. Fetler (1984), Huston and Wright (1996) and Wright et al. (2001) found

“effect modification” of the effects of television viewing on educational outcomes by the

socioeconomic status of parents. Jordan (2004) proposed an ecological paradigm in which the

effects of television viewing might be different within distinct sociocultural niches and received

support from Joensson (1985) which reported that “high achievers” used television as a

complement to school learning whereas “low achievers” used television as a substitute for it. There

are also studies like Johnson et al. (1983), Lemish and Rice (1986), Singer and Singer (1998) and

Sharif and Sargent (2005), which reported positive influence of parental restriction and adult

involvement on academic achievement. Anderson et al. (2001), Wright et al. (2001), and Linebarger

and Walker (2005) argued that content is a stronger predictor of developmental outcomes than

total time spent watching television. Last but not least, Lablonde (1966), Strouse and Buerkel-

Rothfuss (1987) and Anderson et al. (2001) found that increased television screen time as well as

media content had different effects on girls’ and boys’ attitudes, behaviours and grades. If the

above review of literature is considered carefully, it indicates that the studies exploring the

relationship between television exposure and school performance have focused primarily on


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exposure during the preschool years (Huston et al., 2007) and have yielded conflicting results.

Given the plethora of contesting evidence in the literature it became imperative to ponder over the

value addition of our study over and above the existing ones.

1.1 Importance of Our Study

It can be observed that all the aforementioned studies are based on developed countries, primarily

the United States. Our literature search revealed a dearth of studies on relationship between

television viewing and academic performance of children in developing countries. We have reasons

to expect that the effect of exposure to television on children in developing countries might be

different for reasons mentioned below.

In developing countries (for example, India), children either do not have a room of their own or, if

they have a room, they do not have a separate television for themselves. Since the family sizes are

relatively larger (than developed countries) and the number of rooms is limited, most of the family

members, including children, watch television together (in the sample, the average number of

individuals per room per household was 3.3). So, the question of small children watching “R-rated”

programmes or adult programmes becomes irrelevant. To be specific, watching adult programmes

(together) is a taboo in India and the television is normally kept in a common room where

everybody can watch it. Therefore, it is highly improbable that children would be able to watch “R-

rated” programmes. Also, children in developed countries have multiple choices (other than

watching television, for example, piano lessons), some of which might be superior to watching

television, for spending their leisure time. Unfortunately, the same is not true for the majority of

children from developing countries. Therefore, the relationship between television exposure and

academic skills of children should be examined in proper context (Chernin and Linebarger, 2005, p.

688) and the present study is an attempt in this direction.

Moreover, most of the studies discussed above suffer from some shortcoming or other. The

problems range from: (i) small sample sizes (for example, Clarke and Kurtz-Costes (1997) is based

on a sample size of 30 preschool children); (ii) nonrandom and non-representative samples (for

example, Sharif and Sargent (2005), which is one the most complete and methodologically sound

studies (based on a sample of 4508 students), has 95% white students in the sample with most of

the parents having completed high school); (iii) inadequate controls for content, personality and

parenting characteristics (Chernin and Linebarger 2005, p.688); (iv) self-reported or parental-

reported measure of school performance (Sharif and Sargent, 2005); and, (v) problems of

measuring television viewing accurately, where viewing measures sometimes consist of one or a

few questions with dubious validity asking individuals how much time they spend watching

television (Wright et al., 2001, p. 1350).

Our study (to the best of our knowledge) is the first study on India that systematically analyzed the

relationship between academic skills and exposure to television for children and does not suffer

from any of the aforementioned problems. Two studies that attempted to establish some relation

between television viewing and child behavioural/health outcomes in the Indian context need to be

mentioned. Gupta et al. (1994) studied a non-representative sample of 250 children (aged 3 to 10

years) in a hospital of an Indian city (Jaipur in the state of Rajasthan), and found an increase in

weight for 20% of children, a decrease in physical activity for 30% of cases, decreased interest in

study for 18% of children and a decrease in school performance for 10% of children. Since they

neither controlled for any background characteristics (demographic, socioeconomic, family, etc.)


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nor conducted any statistical tests or analysis, their results cannot be considered reliable. Arya

(2004) studied a sample (non-representative) of 150 children (aged 6 to 12 years) from two

government and two private schools in a block of Kangara (a city in the Indian state of Himachal

Pradesh) and examined the impact of television viewing on gender-based differences regarding

democratic, social, economic, hedonistic, health, religious, aesthetic and knowledge values of

children. The results were mixed with gender-based differences apparent in a few of the values and

not in others. These results were again doubtful because the analysis did not control for relevant

background characteristics and lacked methodologically sound statistical analysis.

In the present study, we used a nationally representative sample of more than 12,000 children to

analyze the association between television viewing time and observed reading, mathematics and

writing skills. The sample of children included all the children in the age group of 8 to 11 years who

were in school or ever attended school, from a universe of all the households included in a micro

unit recorded nationally representative survey conducted in 2004-05. Relevant socioeconomic,

demographic, parent/family-level and household-level controls were included in the multivariate

analysis. The impact of content of the television programs was also controlled in the analysis. For

the first time in this stream of literature, we controlled for other forms of media exposure, namely,

newspapers. The analysis was done at two levels using ordinal logistic regressions. The first level

involved analysis on the full sample. The second level of analysis involved the same examination at

two sub-levels: first, on subsamples formed by sex of children, and second, on subsamples formed

by economic status of the households to which children belonged. The results were mixed and

correlation of television on observed academic skills of children varied by gender, socioeconomic

status and by academic skill itself.

2. Data and Methods

2.1 Data

We used the publicly available data from the Indian Human Development Survey (IHDS), conducted

by the National Council of Applied Economic Research, New Delhi, India in collaboration with the

University of Maryland, in 2004-051. The survey is a micro unit recorded, nationally representative

survey based on a stratified multistage sampling procedure. The survey was spread over 33 states

and union territories of India and covers 26,734 households in rural and 14,820 households in

urban areas respectively. This survey was unique in the sense that it was designed to measure

different dimensions of human development with modules on education, health, employment,

income, gender empowerment and media exposure. This study made use of the modules on: (i)

media exposure which reports the extent and type of media exposure for men, women and children

of every household surveyed, and (ii) education which assesses reading, writing and mathematics

skills for children aged 8 to11 years.

2.2 Outcome Measures

The outcome measures are the results of tests conducted for measuring reading, mathematics and

writing skills of children. The tests were administered at home in order not to miss children who

are absent from school and were designed in a way to measure basic skills with relative ease of

administration and with low anxiety levels on the part of children. For this module IHDS worked

1 The data and the questionnaires are available at http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/22626.


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with PRATHAM, which has pretested similar tools on more than 250,000 children in India.

PRATHAM is a voluntary organization that has worked in the field of elementary education in India

for many years and has developed simple assessment tools to measure the effectiveness of their

training programs. The tests were simple and intuitive and were translated (with similar difficulty

levels) into 13 languages in addition to English and the children were asked to take the test in

whichever language they were most comfortable in (Desai et al., 2010, p.79). Interviewers were

trained by PRATHAM volunteers using specifically developed films to differentiate between things

like a child’s shyness and inability to read and to develop rapport with children.

The focus was on children aged 8 to 11 years because “all of these children should have acquired

the basic reading, writing, and arithmetic skills” (Desai et al., 2010, p.79). Children’s reading skills

were divided into five categories: (i) cannot read at all; (ii) can read letters but not form words; (iii)

can put letters together to read words but not read whole sentences; (iv) can read a short

paragraph for 2-3 sentences but not fluent enough to read a whole page; and (v) can read a one

page short story. The arithmetic skills were divided into four categories: (i) cannot read numbers

above 10; (ii) can read numbers between 10 and 99 but not able to do more complex number

manipulations; (iii) can subtract a two digit number from another; and (iv) can divide a number

between 100 and 999 by another number between 1 and 9. In terms of writing, the children were

tested for whether they were able to write a simple sentence, such as, “My mother’s name is

Madhuben”, with two or fewer mistakes (Desai et al., 2010). Though the module was administered

to 12,837 children, the information was consistent for 12,198 children (more than 95% of the total)

and these were the children who have been included in our study.

2.3 Explanatory Variables

The explanatory variable of primary interest is time spent by a child watching television. It was

measured as the number of hours per day (on an average day) a child watches television (0 = less

than 1/2 hour, 1 = 1/2 – 2 hours and 2 = more than 2 hours). The categories were formed for

meaningful interpretation and discussion. They were formed by taking into account the distribution

of television viewing time across children. Since, the survey reported less than or equal to half an

hour (per day) as zero, we had no choice but to take half an hour per day of viewing as the lowest

cutoff. Another explanatory variable of interest is how often a child watches educational content

(includes News, talk shows, educational or agricultural shows) and was categorized as “never”,

“sometimes” and “regularly” as reported in the survey. This variable for educational content was

included to separate the effect of educational television viewing from the effect of overall television

viewing. Of note is the fact that the survey itself provides the above categorization of the

educational content variable and we have used it as provided by the survey. Since the survey does

not provide any information on the number of hours of watching educational content, we do not

have any other option but to follow the survey’s categorization.

There are factors other than television viewing, notably family/parental, demographic,

socioeconomic, and some other characteristics that influence the outcomes of interest. An immense

body of past research has demonstrated that all these variables exert significant influence on child’s

academic outcomes (LaBlonde, 1966; Fetler, 1984; Joensson, 1985; Dombusch et al., 1987; Huston

et al., 1990; Steinberg et al., 1992; Truglio et al., 1996; The Probe Team, 1999; Anderson et al., 2001;

Wright et al., 2001; Jordan, 2004; Govt. of India, 2006; Sharif and Sargent, 2006; Desai et al., 2008a;

Desai and Kulkarni, 2008). Control variables included in the multivariate models were:


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i. Highest educational attainment of adult female in the household – Highest standard

completed by female adult in the household (continuous variable)

ii. Highest educational attainment of adult male in the household – Highest standard

completed by male adult in the household (continuous variable)

iii. Age of the child – In years (continuous variable)

iv. Sex of the child – Male or female

v. Caste – Scheduled Castes/Scheduled Tribes (SC/ST), Other Backward Castes (OBC) and

other socioeconomically advanced castes (General/Upper castes). Individuals belonging to

SC/ST category are historically disadvantaged and have suffered severe social exclusion and

discrimination.

vi. Religion – Hindu (majority religious group in India), Muslim and Other religions

vii. Economic status – Measured by household “assets score” which is reported in the survey

and is measured on a scale of 30 household consumer goods and housing assets (continuous

variable).2

viii. Place of residence – Household classified as being in an urban or a rural area

ix. Newspaper reading by child – To capture exposure to other forms of media and is measured

by how often a child reads newspaper (never; sometimes; regularly).

It is important to point out that none of the studies covered in the literature survey controlled for

other forms of media exposure when analyzing the impact of television viewing on academic

performance of a child. We believed that it is important to control for other forms of media

exposure while evaluating the impact of one particular media on a child’s academic skills. Because

of the aforesaid rarity, as well as to capture the impact of watching educational content, we

estimated three sets of models for every outcome variable; (i) a basic model with the above

mentioned explanatory variables except educational content and newspaper reading habit of child,

(ii) a second model with the explanatory variables of the basic model and educational content

viewing by the child, and (iii) a final model with all of the explanatory variables.

2.4 Statistical Analysis

Since our outcome variables are ordinal, we used ordinal logistic regression analysis to calculate

odds ratios (ORs) for the relationship between observed academic skills and television use

variables while adjusting for family, demographic and socioeconomic characteristics. This model

gives cumulative ORs modeling the probability of being in any higher category on the academic

skills given a baseline category. With an ordered outcome variable, these models had the advantage

of retaining information that would be lost by combining the data into two arbitrary groups, as is

done using logistic regression.

Since for each dimension of academic skills of the N children, we had J achievement levels naturally

ordered in a meaningful way (ranked) for the ordinal outcome variable, the ordinal logistic model

can be specified as follows (Desai et al, 2008a):

iii xy εβ +=∗

)1(

kyi = if

∗

− ≤ ik y1δ kδ< for ,...,1=k J ;,...,1; Ni =

∞=−∞= ko δδ ; )2(

2 The assets score is based on 30 dichotomous items measuring household possessions and housing quality. The

details are available in Desai et al. (2008b, p.18). The measure of assets has a Cronbach’s reliability coefficient

alpha of 0.914.


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where the ordered outcomes are modeled to arise sequentially as a latent variable, y*, with lower y*

indicating lower level of achievement (Cameron and Trivedi, 2005). In our case, y* is an unobserved

measure of child’s academic skills as indicated by measured test scores in reading skills,

mathematics skills and writing skills.

Though the tests were administered by trained interviewers to specifically distinguish among

children at varying levels of reading, mathematics and writing ability, the same child may well be

classified, for example, by one interviewer as being able to read letters and not words and by

another interviewer as being able to put the letters together in words. So, the outcome variable in

this case was better classified as a propensity to read rather than a specific skill level (Desai et al.,

2008a). Observed reading levels (as coded in the survey responses) are only observed; yi are tied to

this latent variable (yi*) (which is not observed) by the measurement model where the underlying

events are cumulative logits:

( )readnotdoesyi 1= if

∗≤−∞= io yδ 1δ< )3(

( )lettery i 2= if

∗≤ iy1δ 2δ< )4(

( )wordyi 3= if

∗≤ iy2δ 3δ<

)5(

( )paragraphyi 4= if

∗≤ iy3δ4δ< )6(

( )storyyi 5= if

∗≤ iy4δ

∞=< 5δ )7(

For mathematics skills the observed levels were: yi =1 (does not recognize written numbers), yi = 2

(can read numbers), yi = 3 (can subtract a two digit number from another two digit number) and yi

= 4 (can divide a three digit number with a one digit number).

Since the outcome variable for writing ability was dichotomous, the model became a simple logistic

regression (logit) model with yi = 1 (cannot write a simple sentence with two or less mistakes) and

yi = 2 (can write a simple sentence with two or less mistakes).

As some existing studies on the impact of television viewing on children’s academic performance

documented differential impact by gender and socioeconomic status, we carried out the analysis at

two levels. At the first level, the estimation was done on the full sample of children. At the second

level, the full sample was divided into subsamples of male and female children with each subsample

analyzed separately, followed by division of the full sample into tertiles based on economic status

(as measured by household assets) and the analysis carried out separately for the poorest and

richest tertiles.

3. Results

3.1 Descriptive Statistics

Table 1 presents the distribution of television viewing, family, demographic, and socioeconomic as

well as newspaper reading characteristics of the children. It also reports the mean and standard

deviation of the observed reading, mathematics and writing skills by the aforesaid characteristics.

It can be observed that the majority (43%) of children fell into the category of half an hour to 2

hours per day of television watching, but when it came to watching of educational programmes,


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about 76% of children never watched educational content (news, talk shows and other educational

or agricultural programmes). Also, a little more than half of the children belonged to households

where there was no adult female who had completed even one year of schooling. The condition was

little better when it came to the education of male adults in the households, where more than 36%

of children belonged to households with at least one adult male with schooling between 6-10 years.

Another observation of interest was related to the newspaper reading habit of children. About 78%

children “never” read newspapers compared to only 6% who read newspapers “regularly”.

Table 1 Observed Academic Skills by Background Variables of Indian children, IHDS 2004-05

Reading Mathematics Writing N (%)

Mean Std. Dev. Mean Std. Dev. Mean Std. Dev.

Television viewing by children

(hours/day)

<= 1/2 2.3 1.4 1.3 1.0 0.6 0.5 40.9

1/2 – 2 2.8 1.3 1.7 1.0 0.8 0.4 43.3

> 2 3.0 1.2 1.8 1.0 0.7 0.4 15.8

Educational content viewing by

children

Never 2.5 1.4 1.5 1.0 0.7 0.5 76.1

Sometimes 3.0 1.2 1.9 1.0 0.8 0.4 18.5

Regularly 3.1 1.1 2.0 1.0 0.8 0.4 5.4

Highest schooling of female

adult in household (years)

No formal schooling 2.2 1.4 1.3 1.0 0.6 0.5 50.5

1 – 5 2.7 1.3 1.6 1.0 0.7 0.5 15.8

6 – 10 3.1 1.1 2.0 0.9 0.8 0.4 24.7

> 10 3.4 0.9 2.2 0.8 0.9 0.3 9.0

Highest Schooling of Male

Adult in Household (years)

No formal schooling 2.1 1.4 1.2 1.0 0.6 0.5 28.0

1 – 5 2.4 1.4 1.4 1.0 0.6 0.5 16.7

6 – 10 2.8 1.2 1.7 1.0 0.7 0.4 36.4

> 10 3.2 1.1 2.1 0.9 0.8 0.4 18.9

Age of Child (years)

8 2.1 1.3 1.2 0.9 0.6 0.5 25.1

9 2.6 1.3 1.5 1.0 0.7 0.5 22.2

10 2.8 1.3 1.7 1.0 0.7 0.4 33.5

11 3.0 1.2 1.9 1.0 0.8 0.4 19.2

Sex of Child

Male 2.7 1.3 1.6 1.0 0.7 0.5 52.9

Female 2.6 1.4 1.5 1.0 0.7 0.5 47.1


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Caste

General 2.9 1.2 1.9 1.0 0.8 0.4 30.8

OBC 2.6 1.4 1.5 1.0 0.7 0.5 40.0

SC/ST 2.4 1.3 1.3 1.0 0.6 0.5 29.2

Religion

Hindu 2.7 1.3 1.6 1.0 0.7 0.5 79.1

Muslim 2.3 1.4 1.4 1.0 0.6 0.5 13.8

Others 2.8 1.3 1.8 1.0 0.7 0.4 7.1

Economic Status of Household

(Asset Quantiles)

1 2.1 1.4 1.2 1.0 0.6 0.5 36.7

2 2.6 1.3 1.6 1.0 0.7 0.5 32.6

3 3.2 1.0 2.1 0.9 0.8 0.4 30.7

Place of Residence

Rural 2.5 1.4 1.5 1.0 0.7 0.5 69.9

Urban 2.9 1.2 1.9 1.0 0.8 0.4 30.1

Newspaper Reading (child)

Never 2.5 1.3 1.5 1.0 0.7 0.5 78.1

Sometimes 3.0 1.1 1.9 1.0 0.8 0.4 15.7

Regularly 3.3 1.1 2.1 0.9 0.9 0.3 6.2

Overall 2.6 1.3 1.6 1.0 0.7 0.5 100

Notes: (1) Total number of observations = 12,198; (2) Reading Skills: cannot read at all = 0; can read

letters but not form words = 1; can put letters together to read words but not read whole sentences =

2; can read a short paragraph but not fluent enough to read whole page = 3; and can read a one page

short story = 4; (3) Mathematics Skills: cannot read numbers above 10 = 0; can read numbers between

10 and 99 but not able to do more complex number manipulation = 1; Can subtract a two digit number

from another = 2; Can divide a three digit number by another number between 1 and 9 = 3; (4)

Writing Skills: Cannot write a simple sentence with 2 or less mistakes = 0, writes with 2 or less

mistakes = 1; and (5) Educational content includes News, talk shows and other educational and

agricultural shows.

The pattern of academic skills by television viewing shows that all the observed academic skills

improved with both overall television watching time and watching of educational content. The

observed reading, mathematics and writing skills also improved with the increase in the level of

formal schooling of adult females and adult males in the household. However, the correlation with

educated adult females seems more than the correlation with educated adult males in the

household. It can be observed that the mean scores (in any academic skill) for a child was higher for

any highest level of schooling completed by adult females in the household compared to the same

level of schooling completed by adult males in the household.

The observed academic skills also improved with the age of the children. This was not surprising

since older children were more likely to have higher academic skills compared to their younger


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counterparts for the same set of tests being administered. The male children performed relatively

better than their female counterparts but the difference was very small. Further, the performance

of children in all the academic dimensions by social and economic status of the household was as

expected. Region of residence had a bearing on the test scores as well, with the urban children

having higher average scores in the three skills than their counterparts. It can also be seen that the

observed reading, mathematics and writing skills systematically increased with the increase in time

spent reading newspapers.

While the descriptive statistics presented above are of interest and give an idea of the general

pattern of distribution of academic skills by background characteristics, they do not control for

other independent (explanatory) variables while investigating the role of a particular independent

variable in explaining variations in a child’s academic performance. It therefore becomes important

to pay more attention to the multivariate results that control for other factors while examining the

effect of a particular independent variable on an outcome variable.

3.2 Multivariate Results – Full Sample

The main multivariate results for the full sample are documented in Table 2, which reports the

cumulative odds of being in any higher level on the academic skills given a baseline level.

3.2.1 Reading Skills

The first estimated model (Model 1r) showed a positive correlation between total television

watching time and the observed reading skills of children. It did not include the controls for

television content and other forms of media exposure. It can be observed that the odds of achieving

any higher level of reading skills for children who watched half an hour to two hours of television

daily was 18% (significant at p < 0.01) more than that of the children who never watched or

watched less than half an hour of television per day. Similarly, children who watched more than

two hours of television daily had 15% (significant at p < 0.05) higher odds of achieving any higher

level compared to those who never watched or watched less than half an hour of television per day.

It can be noted that the correlation between reading skills and watching half an hour to two hours

of television daily was stronger (both in terms of magnitude and significance) than that with

watching more than two hours daily.

When we introduced the viewing of educational content in the model (Model 2r), the influence of

overall television watching was suppressed, but it still remained positive and significance levels did

not change. Watching of educational content “sometimes” also had a positive correlation

(significant at p < 0.05) with a child’s reading skills. Children who watched educational contents

“sometimes” had 11% higher odds of achieving any higher reading level compared to those who

“never” watched educational content. However, watching educational content “regularly” did not

have a significant correlation (though the nature was positive) with the reading skills of children. It

should be kept in mind that educational content here included news, talk shows and agricultural

shows in addition to educational shows. If another control in terms of exposure to other forms of

media (reading newspapers) is introduced (Model 3r), the positive correlation between overall

television watching and the reading skills diminishes further. Also, the significance level of positive

correlation between watching more than two hours of television daily and reading skills fell and

was significant at p < 0.1. With the introduction of newspaper reading habit of children, the effect of

watching educational content became insignificant (though the nature remained positive), while

reading newspapers “sometimes” had a strong positive correlation (significant at p < 0.01) with the


11

reading skills of children. However, reading newspapers “regularly” did not explain reading skills of

children significantly.

3.2.2 Mathematics Skills

As per the basic model (Model 1m), watching half an hour to two hours of television daily was

positively correlated (significant at p < 0.01) with the mathematics skills of children. The children

who watched this duration of television had 13% higher odds of achieving any higher mathematics

level than those who never watched or watched less than half an hour of television per day.

Conversely, watching more than two hours of television per day had a negative (but insignificant)

correlation with the mathematics skills.

Introducing the viewing of educational content (Model 2m) suppressed the positive correlation

between watching half an hour to two hours of television daily and mathematics skills (both in

terms of magnitude as well as significance). Also, the detrimental effect of watching more than two

hours of television increased minutely (the odds ratio changed from 0.97 to 0.94) but remained

insignificant. As in the case of reading skills, watching educational content “sometimes” had a

strong positive correlation (significant at p < 0.01) with the mathematics skills of children. Once

again, watching educational content “regularly” did not come out to be significant (though the odds

ratio was greater than 1), as was the case in reading skills. When newspaper reading habit was also

controlled for (Model 3m), the positive correlation between watching half an hour to two hours of

television daily and mathematics skills plummeted further (now significant at p < 0.1). The negative

correlation between watching more than two hours of television and mathematics skills increased

even more, but still remained insignificant. Unlike the case of reading skills, the inclusion of

newspaper reading habit of children did not affect the significance of watching educational content

“sometimes”, but it decreased the odds of achieving a higher level from 19% to 14%. Reading

newspapers “sometimes” had a strong positive correlation (significant at p < 0.01) with the

mathematics skills of children, a case similar to that of reading skills. However, reading newspapers

“regularly” did not have any significant effect on the mathematics skills of children.


12

Table 2: Odds ratios from the ordinal logistic regression: academic skills (full sample)

Reading Mathematics Writing

Model 1r Model 2r Model 3r Model 1m Model 2m Model 3m Model 1w Model 2w Model 3w

TV watching, 1/2 – 2 hrs/day 1.181*** 1.151*** 1.149*** 1.128*** 1.089** 1.085* 1.126** 1.059 1.062

(0.049) (0.049) (0.049) (0.047) (0.047) (0.047) (0.056) (0.054) (0.055)

TV watching, > 2 hrs/day 1.149** 1.121** 1.112* 0.971 0.939 0.929 0.837** 0.787*** 0.783***

(0.065) (0.065) (0.064) (0.055) (0.054) (0.053) (0.061) (0.058) (0.058)

Highest schooling of female 1.067*** 1.067*** 1.067*** 1.064*** 1.063*** 1.063*** 1.106*** 1.104*** 1.103***

adult in household (yrs.) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.007) (0.007) (0.007)

Highest schooling of male 1.030*** 1.030*** 1.029*** 1.035*** 1.035*** 1.034*** 1.024*** 1.024*** 1.023***

adult in household (yrs.) (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) (0.005) (0.005) (0.005)

Age (yrs.) 1.597*** 1.595*** 1.593*** 1.598*** 1.597*** 1.594*** 1.415*** 1.413*** 1.409***

(0.026) (0.026) (0.026) (0.026) (0.026) (0.026) (0.029) (0.029) (0.029)

Female 0.850*** 0.851*** 0.851*** 0.747*** 0.748*** 0.749*** 0.844*** 0.844*** 0.847***

(0.029) (0.029) (0.029) (0.025) (0.025) (0.025) (0.035) (0.035) (0.036)

OBC 0.847*** 0.850*** 0.853*** 0.797*** 0.802*** 0.806*** 0.831*** 0.839*** 0.843***

(0.036) (0.036) (0.036) (0.034) (0.034) (0.034) (0.046) (0.047) (0.047)

SC/ST 0.738*** 0.740*** 0.741*** 0.668*** 0.671*** 0.674*** 0.769*** 0.774*** 0.778***

(0.036) (0.036) (0.036) (0.032) (0.032) (0.033) (0.048) (0.048) (0.049)

Muslim 0.589*** 0.592*** 0.591*** 0.645*** 0.649*** 0.648*** 0.717*** 0.723*** 0.723***

(0.030) (0.030) (0.030) (0.034) (0.034) (0.034) (0.046) (0.046) (0.046)

Other Religions 0.929 0.924 0.919 1.044 1.040 1.032 0.976 0.966 0.958

(0.062) (0.062) (0.062) (0.066) (0.065) (0.065) (0.088) (0.087) (0.087)

Household assets score 1.073*** 1.072*** 1.071*** 1.079*** 1.078*** 1.077*** 1.053*** 1.050*** 1.047***

(0.005) (0.005) (0.005) (0.005) (0.005) (0.005) (0.006) (0.006) (0.006)

Urban 0.968 0.966 0.969 1.075* 1.072* 1.077* 1.078 1.071 1.078

(0.041) (0.041) (0.041) (0.045) (0.045) (0.045) (0.059) (0.059) (0.059)

Watching educational 1.112** 1.073 1.189*** 1.138*** 1.310*** 1.220***

contents sometimes (0.053) (0.052) (0.054) (0.054) (0.085) (0.081)

Watching educational 1.105 1.097 1.009 1.014 1.420*** 1.344**

contents regular (0.089) (0.088) (0.076) (0.078) (0.167) (0.161)

Newspaper reading 1.193*** 1.251*** 1.371***

Sometimes (0.059) (0.062) (0.095)

Newspaper reading 0.982 0.934 1.147

Regular (0.085) (0.077) (0.145)


13

Notes: (1) Figures in parenthesis are robust standard errors; (2) ***p < 0.01, **p < 0.05, *p < 0.10; (3) The

reference categories for the independent variables are: For overall television watching – watching <

1/2 hours (hrs.)/day; Sex of child – male; Caste – general (upper castes); Religion – Hindu; Place of

residence – rural; Watching educational content – never; Reading newspapers – never; and

(4) We conducted a Wald test for joint significance of the coefficients in the models and a Brant test

for proportional odds assumption. For each of the three models (in each of the skills), the Wald test

provided sufficient evidence for rejecting the null, which is joint insignificance of the coefficients in

the model, thus justifying the inclusion of the independent variables in the model. One of the

assumptions underlying ordinal logistic regression is that the relationship between each pair of

levels of outcome variable is the same, that is, odds being the same across adjacent categories. This

proportional odds assumption or the parallel regression assumption was tested using the Brant test

(omnibus likelihood ratio test). Though the models (reading ability and mathematics) could not

reject the proportional odds assumption for specific coefficients of interest, the assumption was

rejected for all the coefficients together. Therefore, we conducted generalized ordinal logistic

estimation, which does not assume the proportional odds assumption, for reading ability and

mathematics ability. The results showed that for all the independent variables, the odds ratios for the

lowest level of outcome variable (for all outcome variables) to the higher ones, next lowest to the

remaining higher ones and so on, were very close to each other and also very close to the odds ratios

of the ordinal logistic estimation for both the reading ability as well as mathematics ability.

Moreover, the significance of coefficients remained the same (the results can be provided upon

request). Therefore, we keep the estimates of ordinal logistic regressions for a simple but meaningful

interpretation and discussion. Since there are only two levels of outcome for writing ability, the

proportional odds assumption does not apply.

3.2.3Writing Skills

The results of writing skills were more interesting and quite different from those of reading and

mathematics skills. In the absence of controls for educational content and newspaper reading

(Model 1w), watching half an hour to two hours of television daily had a positive and significant

correlation (at p < 0.05) with a child’s writing skills. But watching more than two hours of television

per day had a significant (at p < 0.05) detrimental correlation with the same skills.

When watching of educational content was introduced in the model (Model 2w), the positive

correlation between watching half an hour to two hours of television daily and the writing skills

became insignificant. The negative relationship between watching more than two hours of

television per day and the writing skill increased, both in terms of magnitude as well as level of

significance. The odds of writing a simple sentence with two or less mistakes decreased from 0.84

to 0.79 and were now significant at p < 0.01. In a manner different from the case of reading skills

and mathematics skills, watching educational content “sometimes” as well as watching educational

content “regularly” had a positive and significant correlation (at p < 0.01) with a child’s writing

skills.

With the introduction of newspaper reading habit of the children in the model (Model 3w), the

negative effect of watching more than two hours of television daily increased even further and

remained significant at p < 0.01. Also, unlike reading and mathematics skills, watching educational

content “sometimes” or “regularly” had a positive correlation with a child’s writing skills at p <0.01

and p < 0.05, respectively. It is also evident that the effect of reading newspapers was similar to the

case of reading and mathematics skills.


14

3.3 Multivariate Results – Boys vs. Girls

For the analysis by the sex of children, we divided the full sample of children into two subsamples

based on the sex of children. Since we already showed the importance of including educational

content as well as newspaper reading habit of children in the estimation, we have presented the

results (Table 3) of only the full models for reading, mathematics, and writing skills.


The analysis by sex of children showed a very contrasting picture as far as the correlation between

television viewing and a child’s observed academic skills was concerned. If reading skills were

considered (Model 1m and Model1f), watching half an hour to two hours of television daily had a

positive and significant correlation (at p < 0.01) with the reading skills of boys, whereas it did not

affect the reading skills of girls significantly. When watching more than two hours of television daily

was taken into account, it affected the reading skills of boys positively and significantly (at p < 0.1)

but had an insignificant effect on the reading skills of girls.

Watching educational content did not have any significant correlation with the reading skills of

boys, but was significantly correlated with the reading skills of girls. Watching educational content

“sometimes” increased the odds of achieving any higher level of reading skills in girls by 26%

(significant at p < 0.01), whereas watching educational content “regularly” increased the odds of

achieving any higher level of reading skills by 23% (significant at p < 0.1). In both cases, the

reference category was of those girls who “never” watched educational content.


The results on mathematics skills (Model 2m and Model 2f) also differed by sex of children. While

watching television was not correlated with the mathematics skills of boys, watching half an hour to

two hours of television daily had a positive and significant correlation (at p < 0.1) with the

mathematics skills of girls.

In a manner similar to that of reading skills, watching educational content was not significantly

correlated with the mathematics skills of boys, but watching it “sometimes” was positively and

significantly correlated with the mathematics skills of girls. Watching educational content

“sometimes” increased the odds of achieving any higher level of mathematics skills in girls by 18%

(significant at p < 0.01). For both boys and girls, watching educational content “regularly” was not

correlated significantly with mathematics skills.

3.3.3 Writing Skills

The results for male and female children (Model 3m and Model 3f) were somewhat similar as far as

writing skills were concerned. Watching half an hour to two hours of television daily neither

affected the writing skills of boys nor the writing skills of girls significantly, whereas watching more

than two hours of television daily was negatively and significantly correlated with the writing skills

of both boys and girls. However, the detrimental correlation was relatively higher for boys

compared to girls, where the boys who watched more than two hours of television daily were only

0.74 times (significant at p < 0.01) as likely to write a simple sentence with two or fewer mistakes

as the boys who did not watch or watched less than half an hour of television daily. The

corresponding figure was 0.82 (significant at p < 0.1) for female children.

Considering the effect of watching educational content, we found that watching educational content

“sometimes” was positively and significantly correlated with the writing skills of both boys as well


15

as girls. However, the positive correlation was relatively higher for girls compared to boys. The girls

who watched educational content “sometimes” had 26% (significant at p < 0.05) higher odds of

writing a simple sentence with two or fewer mistakes compared to the girls who “never” watched

educational content. The corresponding figure was 17% (significant at p < 0.1) for boys. Also, it was

noteworthy that watching educational content “regularly” did not have any significant correlation

with the writing skills of boys, while it had a positive and significant correlation (at p < 0.01) with

the writing skills of girls.

Table 3 Odds ratios from the ordinal logistic regression: academic skills by sex of child

Male Children Female Children

Reading

Model1m

Mathematics

Model2m

Writing

Model3m

Reading

Model1f

Mathematics

Model2f

Writing

Model3f

TV watching, 1/2–2 hrs/day 1.198*** 1.050 1.109 1.087 1.117* 1.009

(0.071) (0.062) (0.079) (0.067) (0.070) (0.076)

TV watching, > 2 hrs/day 1.147* 0.925 0.744*** 1.060 0.925 0.823*

(0.092) (0.073) (0.075) (0.089) (0.079) (0.089)

Highest schooling of female 1.057*** 1.046*** 1.100*** 1.077*** 1.081*** 1.106***

adult in household (yrs.) (0.007) (0.007) (0.010) (0.008) (0.008) (0.011)

Highest schooling of male 1.039*** 1.046*** 1.023*** 1.017*** 1.022*** 1.023***


Age (yrs.) 1.629*** 1.666*** 1.432*** 1.556*** 1.521*** 1.386***

(0.037) (0.038) (0.040) (0.037) (0.036) (0.041)

OBC 0.910 0.830*** 0.899 0.784*** 0.773*** 0.786***

(0.053) (0.049) (0.069) (0.048) (0.048) (0.063)

SC/ST 0.713*** 0.660*** 0.778*** 0.771*** 0.686*** 0.775***

(0.047) (0.044) (0.069) (0.055) (0.049) (0.071)

Muslim 0.592*** 0.634*** 0.709*** 0.588*** 0.663*** 0.742***

(0.042) (0.046) (0.067) (0.044) (0.050) (0.069)

Other Religions 0.894 0.998 1.024 0.958 1.086 0.892

(0.079) (0.082) (0.128) (0.098) (0.105) (0.118)

Household assets score 1.057*** 1.072*** 1.045*** 1.089*** 1.084*** 1.049***

(0.007) (0.007) (0.008) (0.008) (0.007) (0.009)

Urban 0.870** 0.954 1.002 1.089 1.226*** 1.162*

(0.050) (0.056) (0.076) (0.067) (0.075) (0.093)

Watching educational 0.941 1.098 1.177* 1.255*** 1.183** 1.266**


Watching educational 0.980 0.988 1.261 1.232* 1.040 1.422*


Newspaper reading 1.258*** 1.278*** 1.516*** 1.127 1.230*** 1.231**

sometimes (0.085) (0.084) (0.146) (0.082) (0.091) (0.124)

Newspaper reading regular 1.116 1.111 1.161 0.875 0.788* 1.143

(0.128) (0.123) (0.199) (0.116) (0.097) (0.216)


16

Notes: (1) Figures in parenthesis are robust standard errors; (2) ***p < 0.01, **p < 0.05, *p < 0.10; (3)

The reference categories for the independent variables are: For overall television watching – watching

< 1/2 hours (hrs.)/day; Sex of child – male; Caste – general (upper castes); Religion – Hindu; Place of

residence – rural; Watching educational content – never; Reading newspapers – never.

3.4 Multivariate Results – by Economic Status

For analyzing the differential effect of television viewing on children by the economic status of the

households they belong to, we divided the full sample into three quantiles (tertiles) based on

household assets and compared the correlation between television watching and skills of the

children falling into the first tertile (henceforth referred as “poor”) to the correlation between

television watching and skills of children who fell into the third tertile (henceforth referred as

“rich”). Table 4 reports the results (odds ratios) of this comparison.


Results of Model 1p and Model 1r need to be compared for observing the contrasts in reading skills

between the poor children and the rich children. Though the total television watching time was not

significantly correlated with the reading skills of children of either group, it can be observed that

watching educational content “sometimes” had a very significant positive correlation with the

reading skills of poor children, while it did not have any significant correlation with the reading

skills of rich children. Among the poor children, the odds of achieving any higher level in reading

skills for the children who watched educational content “sometimes” were 42% higher (significant

at p < 0.01) than the children who “never” watched educational content. Another finding worth

noticing here is that sex of children did not have any significant bearing on the reading skills of

children in the set of rich children but it had a significant correlation with the reading skills of

children falling into the poor category. Female children in the group of poor children were only 0.63

times (significant at p < 0.01) as likely to achieve any higher level of reading skills compared to

their male counterparts.


Model 2p and Model 2r report the estimates for mathematics skills for the aforesaid two groups of

children. In mathematics skills, similar to the case of reading skills, the total television watching

time was not correlated significantly with the children of either group. Again, as in the case of

reading skills, it can be observed that watching educational content “sometimes” had a significant

and positive correlation with the mathematics skills of the poor children but failed to have any

significant correlation with the mathematics skills of rich children. Among the poor children, the

odds of achieving any higher level in mathematics skills for the children who watched educational

content “sometimes” were 39% higher (significant at p < 0.01) than the children who “never”

watched educational content.

3.4.3 Writing Skills

Unlike reading and mathematics skills, watching more than two hours of television daily was

negatively and significantly correlated with the writing skills of the children of both groups (Model

3p and Model 3r). Again, watching educational content “sometimes” had a very significant and

positive correlation with the writing skills of poor children but failed to have any significant effect

on the writing skills of rich children. Among the poor children, the odds of writing a simple

sentence with two or fewer mistakes for the children who watched educational content

“sometimes” were 73% higher (significant at p < 0.01) than the children who “never” watched


17

educational content. Compared to reading and mathematics skills, this positive correlation was

much higher.

Though the effect of newspaper reading had not been discussed in the analysis based on

subsamples, it is worthwhile to mention that reading newspapers “sometimes” had a significant and

positive correlation with the reading, mathematics and writing skills of children of all the

subgroups discussed so far, except for the reading skills of girls and rich children. For these two

subgroups, the correlation was positive but nonetheless not significant.

Table 4 Odds ratios from the ordinal logistic regression: academic skills by assets quantiles

Bottom one-third Top one-third

Reading

Model1p

Mathematics

Model2p

Writing

Model3p

Reading

Model1r

Mathematics

Model2r

Writing

Model3r

TV watching, 1/2 – 2 hrs/day 1.105 1.080 1.089 1.031 0.988 0.825

(0.073) (0.075) (0.085) (0.116) (0.104) (0.136)

TV watching, > 2 hrs/day 1.072 0.920 0.485*** 1.010 0.841 0.660**

(0.159) (0.136) (0.081) (0.121) (0.095) (0.116)

Highest schooling of female 1.103*** 1.103*** 1.127*** 1.049*** 1.040*** 1.079***


Highest schooling of male 1.028*** 1.025*** 1.019** 1.025*** 1.051*** 1.025**


Age (yrs.) 1.501*** 1.479*** 1.365*** 1.680*** 1.776*** 1.465***

(0.039) (0.039) (0.041) (0.054) (0.056) (0.068)

Female 0.694*** 0.633*** 0.776*** 1.100 0.890** 0.871

(0.037) (0.035) (0.049) (0.071) (0.055) (0.081)

OBC 0.786*** 0.734*** 0.803** 0.896 0.840** 0.879

(0.064) (0.063) (0.081) (0.065) (0.059) (0.093)

SC/ST 0.759*** 0.666*** 0.843** 0.641*** 0.724*** 0.638***

(0.066) (0.061) (0.081) (0.060) (0.065) (0.081)

Muslim 0.545*** 0.689*** 0.759*** 0.672*** 0.574*** 0.688***

(0.049) (0.064) (0.081) (0.068) (0.058) (0.093)

Other Religions 0.897 1.143 1.094 1.147 0.959 1.116

(0.109) (0.154) (0.182) (0.123) (0.088) (0.174)

Household assets score 1.111*** 1.114*** 1.078*** 1.043*** 1.057*** 1.030

(0.017) (0.017) (0.019) (0.013) (0.012) (0.019)

Urban 1.153 1.169 1.103 1.038 1.156** 1.243**

(0.112) (0.115) (0.124) (0.071) (0.078) (0.120)

Watching educational 1.427*** 1.385*** 1.732*** 1.009 1.093 1.055


Watching educational 0.758 0.775 1.013 1.093 0.996 1.327


Newspaper reading 1.575*** 1.500*** 1.593*** 1.127 1.258*** 1.266**


18

sometimes (0.156) (0.163) (0.217) (0.089) (0.094) (0.146)

Newspaper reading regular 1.892 0.921 1.472 0.941 1.017 1.219

(0.733) (0.339) (0.543) (0.097) (0.102) (0.193)

Notes: (1) Figures in parenthesis are robust standard errors; (2) ***p < 0.01, **p < 0.05, *p < 0.10; and

(3) the reference categories for the independent variables are: For overall television watching –

watching < 1/2 hours (hrs.)/day; Sex of child – male; Caste – general (upper castes); Religion –

Hindu; Place of residence – rural; Watching educational content – never; Reading newspapers –

never.

Further discussion on these results has been provided in the subsequent section which also

concludes this paper.

4. Discussion and Conclusion

As far as India is concerned, this paper provides the first systematic and reliable evidence on the

association between watching television and a child’s observed academic skills. The age group of

the children in the study varied from 8 - 11 years, which is a deviation from most of the previous

studies, which were based on preschool children. This age group was important from the

perspective of the different stages of cognitive development that are related to television watching

and that a child experiences (Piaget, 1969; Lemish, 2007). Among the different stages of cognitive

development experienced by children, the “concrete operational stage” is associated with the age

group of 7 to 12 years. This is the stage when children begin to engage in abstract thoughts that

allow them to understand the medium’s codes and conventions sufficiently to follow story lines.

They develop levels of perception (televisual literacy) that allow them to understand the chunks

and segments that constitute a television programme and how they are linked (Signorielli 1991,

p.28). From the age of 12, children are assumed to understand television in a similar way to adults

(Hodge and Tripp, 1986, p. 80-81; Lemish, 2007, p. 39). Since this is a stage where the attraction for

television is very high among children as they start to comprehend the programmes, it became

imperative to study the effect of watching television on this specific age group.

We studied the correlation between watching television and the reading, mathematics and writing

skills of children and found substantial variation in level and nature of correlation with the three

skills. In case of reading skills, watching television had a positive correlation irrespective of

controlling for educational content or other forms of media exposure. Results in the case of

mathematics skills were a little different, where watching television for small durations (1/2 – 2

hours daily) had a positive correlation, whereas watching more than two hours of television daily

had a detrimental but insignificant correlation. In contrast to reading and mathematics skills,

watching more than 2 hours of television had a strong and significant positive correlation with the

writing skills of children. These differential effects have also been documented in earlier studies:

Zimmerman and Christakis (2005) reported a beneficial effect (at age 3-5 years) of television for

reading recognition scores, but found modest adverse effects on other scores; Johnson et al. (1983)

associated lower grade (and I.Q.s) with more television watching but higher math grades with a

preference for family, game and cartoon shows (fifth to eighth grade children); Schramm et al.

(1961) correlated higher mental ability with heavy television viewing in young children but no

relationship between viewing time and ability among older, preadolescent children.


19

Watching of educational content did not have any significant correlation with the reading skills of

the children in the presence of effective controls, while watching educational content “sometimes”

was positively correlated with mathematics skills as well as writing skills. In the case of writing

skills, even watching educational content “regularly” had a positive correlation. The insignificant

correlation of watching educational content “regularly” with the reading and mathematics skills

should be seen in the light that “educational content” included news, talk shows and agricultural

shows in addition to the direct education programmes. If a child watched this content too much it

might have resulted in the neglect of regular studies, which may have led to insignificant difference

in the skills of children who did not watch educational content and the children who watched too

much of it. Since the exact contribution of the different components of educational content is

unknown, no further insightful analysis can be done. It must be mentioned here that there is ample

evidence in support of the positive correlation between educational content and a child’s academic

performance, as has already been discussed; we do not repeat it here.

The findings related to the differential impact of television on the academic skills of children

belonging to different sexes were more interesting. While overall television viewing was positively

correlated with the reading skills of boys, it did not have any significant correlation with the

reading skills of girls. Conversely, the overall television viewing time did not have any significant

correlation with the mathematics skills of boys, but watching 1/2 - 2 hours of television daily was

positively correlated with the mathematics skills of girls. The influence of watching educational

content on reading and mathematics skills also differed across boys and girls, where it did not have

any significant effect on boys, but watching “sometimes” was positively correlated with both the

reading as well as mathematics skills of girls. These contrasts are not surprising if seen in the light

of LaBlonde (1966), which found a significant negative relationship between television viewing and

I.Q. for girls but not for boys, Anderson et al. (2001), which related increased television screen time

to higher grades for boys but lower grades for girls and Sharif and Sargent (2006), who found that

girls were more vulnerable if there were more cable movie channels in the home, whereas boys

were more vulnerable if “R-rated” movie viewing was restricted (p. e1068-69). The difference in

media use patterns by gender (Huston et al., 1999) and the development of gender identities by the

age of 6-7 years with categorization of programmes by own distinctive tastes (Davis et al., 2000)

have been attributed as possible reasons for the differential impact of television viewing on the

academic skills of boys and girls. Only in the case of writing skills, the influence of watching

television was similar for both boys and girls, and watching more than 2 hours of television daily

had a strong detrimental correlation with writing skills, but watching educational content

“sometimes” had a significant positive association with writing skills.

We also deviated from most of the extant studies by analyzing the differential influence of watching

television on the academic skills of children belonging to different wealth classes. The separate

analysis stands justified if we note the results that watching educational content “sometimes” had a

significant positive correlation with the reading, mathematics and writing skills of children

belonging to the lowest wealth class but failed to have any significant correlation with any of the

three academic skills of the children belonging to the highest wealth class. These differences in the

influence of television on children with different socioeconomic status are in accordance to the

studies by Fetler (1984), Anderson et al. (2001) and Wright et al. (2001), who suggested that

television use by children of lower socioeconomic status may be particularly beneficial to their

school performance. In the study by Fetler (1984) among children in lower socioeconomic class

homes, those who watched little or no television had worse academic performance than those who


20

watched moderate amounts of television. Conversely, among children from higher socioeconomic

class homes, children who watched little or no television had better academic performance than

those who watched moderate amounts (Anderson et al., 2001; Jordan, 2004). It is worthwhile to

mention here that watching too much television (more than two hours daily) had a significant

negative correlation with the writing skills of both sets of children.

Though the effect of newspaper reading on children’s academic skills is not the focus of this study, it

is important to note that reading newspapers “sometimes” had a positive correlation with the

academic skills of children irrespective of their gender or socioeconomic status. It is also important

to note that heavy exposure of either educational content or reading newspapers failed to

significantly affect the academic skills of children, for which the possible reason of interference with

regular studies has already been discussed.

This study has several strengths, including systematic measure of television exposure, large sample

size, adequate and appropriate controls for a number of family, demographic and socioeconomic

characteristics and no geographic area limitation. Moreover, departure from self-reported

measures of academic performance as the main outcome is an added advantage of this study. At the

same time, our study is also subject to a few limitations. Correlations of television viewing and

achievement may be a function of other factors. Though we controlled for a host of demographic

and family characteristics (e.g., education, caste, religion and wealth) and the controls are informed

by earlier literature on this subject as well as the relevance of factors in Indian context, it is always

possible that unmeasured variables account for part of the associations. Another limitation comes

from the cross-sectional and non-experimental nature of our study. In the absence of longitudinal

evidence and appropriate counterfactuals, it becomes difficult to establish significant causality

between the variables concerned. Clearly, a major way to take this research agenda (the effect of

television viewing on academic skills of Indian children) forward will be to evaluate the effects of

television viewing on the academic skills of children in India under an experimental setup (e.g.,

randomized control trials). This will help in establishing the causal relationship between watching

of television and academic skills and will help in providing additional evidence on how television

viewing can impact the academic skills of Indian children. Although the study is subjected to the

above limitations, grounding of the analysis in appropriate theory, methodological soundness,

robustness of results and support for the results in existing literature justifies its contribution.

On a concluding note we will like to mention that demonizing television on the basis of incomplete

studies with inadequate controls seems unjustified. Watching television in an uncontrolled manner

might be detrimental to the academic skills of children, but watching educational content in a

regulated manner seems to have a positive correlation with children’s academic skills. As a final

remark, we quote:

“Television can be of general benefit to children. It can bring them into contact with aspects of

life they would not otherwise become aware of. It can provide a valuable tool in the home and at

school not simply to keep children occupied but also, if used appropriately, as a constructive way to

use their time… Television is not a ‘one-eyed monster’ lurking impishly in the corner of the living

room, kitchen or bedroom waiting to exert an evil influence over young members of the household.

It is a channel through which a range of entertainment, drama and learning can be obtained and

experienced and increasingly these days it is under the control of the viewer.”

-Gunter and McAleer [1997, p. xii-xiii]

.


21

Acknowledgement

The authors thank the referee and the editorial team for helpful comments.

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