A Study to Assess the Impact of Multimedia Usage on Behavioural Patterns of the Pre-University College Students in Selected Colleges at Mangalore

Mr. Liju James¹, Mr. Shivakumara J.²

¹2^nd Year M.Sc. Nursing, Department of Mental Health Nursing, Laxmi Memorial College of Nursing, Mangalore

²Associate Professor, Department of Mental Health Nursing, Laxmi Memorial College of Nursing, Mangalore

*Corresponding Author Email: vilayil555@gmail.com

ABSTRACT:

People use mass media in varying ways and for various purposes. But it is fact that not all the purposes of media are positive gratifications. Some are good and some are not. That is how the media works. However, we can see that media continue to give messages to us as we participate in them. Moreover, some messages or values are rubbed on to us, whether we like them or not. Media education is learning to dissect and identify them. The developing child in the modern society is typically introduced to the mass media at home and it is at home that he is most likely to use several varieties to print and broadcast media. By the time he reaches adolescence, he is plausible to assume that his patterns of media use have been shaped by social influence at home, particularly his parents. Entertainment is something everybody looks forward to. There are many ways to entertain those who need leisure and pleasure. Mass media is one of the most popular entertainments; one has the greatest invention of humankind. It has found place in every home in India. Excessive watching of television programmes has an unhealthy effect on children. Television has become quite popular among all ages. It provides variety for all tastes. On the other hand, television has an adverse effect on children. They get addicted to television. The scenes of sex, crime and violence in our films and programmes have adverse effects on children. Such scenes cause adverse effects on their thought life and work life. The aim of this study was to assess the impact of multimedia usage on behavioural patterns of the pre-university college students in selected colleges at Mangalore. The research approach used for the study was descriptive survey approach. The conceptual framework was based on David Kolb’s Experiential Learning Theory (learning styles) Model. The study was carried out in three pre- university colleges of Mangalore. The sample comprised of 120 students who were undergoing their pre- university course in science, arts and commerce as their main stream of study. Samples were selected by using multistage disproportionate stratified random sampling technique. Data was collected by administering tools like demographic proforma, survey questionnaire, and behavioural rating scale. Data were analyzed using descriptive and inferential statistics. The results of this study show that majority (62.5%) of the students are showed mild behaviour. About 30.8% of the students showed moderate behaviour and 6.7% of the students showed severe behavioural changes due to the influence of multimedia usage.

KEYWORDS: Impact, multimedia, behavioural pattern, college students, descriptive study.

INTRODUCTION:

Multimedia involves the integration of text, graphics, audio and/or video into a computer based environment. Multimedia is more than one concurrent presentation medium (for example, CD-ROM or a website).

Multimedia tends to imply sophistication (and relatively more expensive) in both production and presentation than simple text and images.¹ Multimedia today include many different forms. Multimedia includes everything that is now used on a device or computer: E-readers, smart phones, computers, laptops, CDs, DVDs, MP3 player etc. Multimedia technologies are further classified by their evolution in the digital world. Web 1.0 typically refers to the internet sites using earliest web based technologies, where as 2.0 sites refers to sites that are the newest and are using the most social tools, like Facebook, Orkut, YouTube etc. Facebook originated in 2004 as a Harvard University Website for students of that university to connect and communicate. It is also currently the most popular social network site among adolescents.²

Media represents one of the most powerful and underappreciated influences on adolescent development and health. More than 50 years of media research and thousand of media effects studies attest to the potential power of the media to influence virtually every concern that parents and clinicians have about young people: aggressive behaviour, sex, drugs, obesity, eating disorders, school performance, suicide, and depression. Clearly, much more research is needed, but clinicians, parents, school administrators , and government officials all need to aware of the research on the effects of modern media and act accordingly.³

Concern from the parents, professionals and the populace at large about the impact of the media on children and adolescents have grown steadily over recent years. The studies addressing this issue show a small but genuine association existing between media exposure and child behaviour. The recent growth of cable T.V and video movie rentals has increased the number of potential sources of positive and negative programming that may be viewed by the children. The groups of children who have little parental input and are ‘moral’ quick learners are eager to act out any new TV excitement. They are at high risk for viewing related violence because “Their teacher is television set.⁴

MATERIAL AND METHODS:

Conceptual frame work constructed by adopting David Kolb’s Experiential Learning Theory (learning styles) Model. Kolb’s learning theory sets out four distinct learning styles (or preferences) which are based on a four –stage learning cycle which affect the individual people differently. Ethical clearance was obtained prior to the study. The study was conducted in selected pre-university colleges at Mangalore. A written permission was obtained from the concerned authorities. For validity the criteria checklist, the tool along with blueprint, answer keys was submitted to 9 experts along with the objectives. The reliability for the Survey Questionnaire was established by using test –retest method. Karl Pearson’s Co-efficient Correlation Technique was used to calculate the reliability. The reliability was found to be r=0.90 and reliability of rating scale was established by Cronbach’s alpha and reliability was found to be r= 0.77 and it was found to be significant and reliable.

Research approach used for the study was Descriptive survey approach. The study was conducted in the selected pre university colleges at Mangalore on 120 students were selected by multi stage stratified Random Sampling technique.. The data was collected by using Demographic Proforma, survey questionnaire, and behavioural rating scale. The data collected was analyzed to achieve the objectives of the study and to test the research hypotheses using descriptive and inferential statistics.

RESULTS:

Section I: Description of sample characteristics:

This section deals with background information of students such as age, gender, course of study, stream of study, place of stay, part time job, monthly pocket money, monthly income, media used frequently and reasons for using multimedia. A sample of 120 students of Pre-university College was drawn from the selected pre-university colleges based on the specific criteria. The data are analyzed using the descriptive statistics and presented in terms of frequency, percentage.

Table 1: Frequency and percentage distribution of the sample according to the baseline characteristics N = 120

Sl. No.	Demographic Variables	Frequency (f)	Percentage (%)
1	Age in years
	16-17	76	63.3
	18-19	44	36.7
	20 and above	0	0.0
2	Gender
	Male	60	50.0
	Female	60	50.0
3	Course of study
	1^st year PUC	60	50.0
	2^nd year PUC	60	50.0
4	Stream of study
	Science	40	33.3
	Arts	40	33.3
	Commerce	40	33.4
5	Place of stay
	Home	96	80.0
	Hostel	19	15.8
	Relatives home	5	4.2
6	Do you have a part time job?
	Yes	29	24.2
	No	91	75.8
7	Monthly pocket money you received
	<200	57	47.5
	201-400	34	28.3
	401-600	14	11.7
	601-1000	10	8.3
	1001-2000	5	4.2
8	Income of family(in rupees)
	<5000	34	28.3
	5001-10000	38	31.7
	10001-15000	28	23.3
	>15000	20	16.7
9	Frequently used media
	Cell phone	39	32.5
	Internet	38	31.7
	Television	33	27.5
	Video games	10	8.3
10	Reasons for using multimedia
	Chatting	20	16.7
	Spending time	52	43.3
	Recreation	25	20.8
	Social networking	23	19.2

Table 3: Chi-Square test showing association between the impact of multimedia usage by the students and selected demographic variables N=120

Sl. No.	Demographic Variables	χ² value	df	P value	Significance
1	Age	2.163	2	0.339	Not significant
2	Gender	3.343	2	0.188	Not significant
3	Course	4.884	2	0.087	Not significant
4	Stream	3.817	4	0.431	Not significant
5	Place	1.246	4	0.876	Not significant
6	Do you have part time job	3.406	2	0.492	Not significant
7	Monthly pocket money	6.064	8	0.64	Not significant
8	Income of family	8.804	8	0.359	Not significant
9	Frequently used media	0.396	6	0.99	Not significant
10	Reasons for using multimedia	1.354	6	0.969	Not significant

Section III: Association between the impact of multimedia usage by the students and selected demographic variables

This section deals with findings of the association between the impact of multimedia usage by the students and selected demographic variables. To test the association the following null hypothesis was formulated: H₀₁:There is no a significant association between the impact of multimedia usage by the students and selected demographic variables at 0.05 level of significance.

The data presented in Table 3 shows that there is no significant association between the impact of multimedia usage by the students and selected demographic variables. So the research hypothesis H₁isrejected and null hypothesis H₀₁is accepted.

DISCUSSION:

Major findings of the study:

I. Sample characteristics

· Majority (63.3%) of the samples were in the age group of 16-17 years. Only 36.7% were in the age group of 18-19 years.

· The sample consisted of equal number of males and females (50%).

· The sample consisted of equal number of students from first year and second year PUC.

· The sample consisted of equal number of students from Arts, Science, and Commerce group (33.3%).

· Majority (80%) of samples were staying at home. About (15.6%) were stayed at hostel. Only (4.2%) of them were stayed in the relatives home.

· Majority (75.8%) of the students did not have any part time job. Only (24.2%) were having part time job.

· Majority (47.5%) of the students were getting below Rs.200 as pocket money. About (28.3%) were got Rs.201-400, (11.7%) were getting Rs.401-600 and (8.3%) were getting Rs.1001-2000 as pocket money.

· Majority (31.7%) of the students has income of family ranges from Rs. 5001-10,000.Only (16.7%) were having the income more than Rs.15, 000.

· The majority of the students (32.5%) were used cell phone, 31.7% were used internet, and 27.5% were used television and only (8.3%) of the students used video games.

· Majority (43.3%) of the students used multimedia for spending time. Only (16.7%) of the students used for chatting purpose.

II. Assessment of impact of multimedia usage on behavioural patterns of the students

· Majority (62.5%) of the students showed mild behaviour, (30.8%) were showed moderate behaviour. Only (6.7%) of the students showed severe behaviour while using multimedia.

III. Association between impact of multimedia usage on behavioural patterns of students and selected demographic variables

· There is no significant association between multimedia usage by the students and selected demographic variables.

Discussion of study findings with other studies:

I. Sample characteristics.

In this study

· Majority (63.3%) of the samples were in the age group of 16-17 years.

· Equal number of male and female students (50%).

· Equal number of male and female students from first and second year PUC (50%).

· Equal numbers of students were drawn from Arts, Science and commerce group (33.3%).

· Most (80%) of the samples were staying at home.

· Majority (75.8%) of the students did not have any part time job.

· Maximum (47.5%) were getting below Rs.200

· Highest percentage (31.7%) of the students has the family income ranging from Rs.5001-10,000.

· Maximum (32.5%) of the students were using cell phone and (31.7%) were used internet.

· Majority (43.3%) of the students used multimedia for spending time mainly. These study findings are consistent with the findings of the other study conducted to assess the relationship between watching professional wrestling on television and engaging in the date fighting among high school students.

Section 2: Assessment of the impact of multimedia usage on behavioural patterns of pre-university college students:

In this study, majority (62.5%) of the students showed mild behaviour and 30.8% of the students showed moderate behaviour. Only (6.7%) of students showed severe behaviour while using multimedia. These study findings are consistent with other studies conducted among students. A cross-sectional study was conducted on the impact of mobile phone use on various dimensions of students in Mangalore. The samples were 500 students studying for various courses (MBBS, BPT, MLT, B. Sc. Nursing and GNM). The samples were selected using proportionate stratified random sampling method. A self administered impact scale was used for data collection. The findings of the study showed that students have more negative impacts (52.22%) than positive impacts (47.78%).⁵

A descriptive study was conducted to assess the influence of mass media on behavioural changes among adolescents as perceived by their parents in a selected school at Mangalore .The sample comprised of 150 parents were selected randomly. The data was collected by using modified behaviour change rating scale. The study results shows that majority of adolescents (25%) who are addicted to TV they had behavioural changes moderately and others mobile phones 7%, internet use 2% were had mild behaviour changes. The study concludes that the mass media as a great influence on behavioural changes of adolescents.⁶

Section 3: Discussion of studies related to association between the impact of multimedia usage by the students and selected demographic variables

The present study revealed that there is no significant association between the impact of multimedia usage by the students and selected demographic variables. A telephone survey study was conducted on “Television, video, and computer game usage in children under 11 years of age”. Researchers conducted Telephone survey on1454 parents of children <11 years old derived from a diverse clinic population. The objectives of the study was to conduct a population-based survey of television and other media usage in young children to determine (1) total media usage; (2) the proportion of children who have televisions in their bedrooms and who eat breakfast or dinner in front of the television; and (3) predictors of parental concern about the amount of television their child watches. The mean age of the index child was 5.05 years. Mean daily reported child media use was as follows: television (1.45 hours; SD, 1.5); videos (1.1 hours; SD, 1.30); and computer games (0.54 hours; SD, 0.96). Thirty percent of parents reported that their child ate breakfast or dinner in front of the television in the past week, and 22% were concerned about the amount of television that their child watched. In multivariate linear regression, eating breakfast or dinner in front of the television in the past week was associated with increased hours of television viewing (0.38 hours [0.21, 0.54]) and video (0.19 hours [0.04, 0.34]). Having a television in a child's bedroom was associated with increased hours of television (0.25 hours [0.07, 0.43]), video viewing (0.31 hours [0.16, 0.47]), and computer games (0.21 hours [0.10, 0.32]). In general, higher parental education was associated with decreased hours of television and video but not computer games. Older children were 2 to 3 times more likely than younger children to have a television in their bedroom and to have eaten a meal in front of it in the past week. More parents that are educated were less likely to report that their child had a television in their bedroom and more likely to be concerned about the amount of television their child viewed. Combined video and computer game usage exceeded television usage. Both children of low- and high-income parents are at risk behaviours associated with television usage.⁷

A study was conducted on “cross-sectional and longitudinal connections between exposure to mass media viewing and aggressive behaviour” on 220 Finnish children. The results confirmed that aggressive behaviour in early adulthood is predicted by childhood TV-violence viewing. Violence viewing in adulthood could not be predicted by early aggressive behaviour.⁸

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Received on 02.03.2015 Modified on 18.03.2015

Asian J. Nur. Edu. and Research 5(2): April-June 2015; Page180-184

DOI: 10.5958/2349-2996.2015.00037.3

Group	Behavioural Pattern	Frequency (f)	Percentage (%)
Pre-university college students	Mild	75	62.5
	Moderate	37	30.8
	Severe	8	6.7