Cell phone as appropriate information technology english language essay

19. Last Mayo, in an article ‘ the digital divide: scarcity, inequality and conflict’ in the book entitled ‘ Digital Cultures’ edited by Glen Creeber and Royston Martin mentioned about digital divide and other concomitant divides like geographical divide, social divide and democratic divide. According to the researchers, inequality in access to ownership of new media can significantly affect the access to information from the new media or Internet by the disadvantaged communities and at the same time creating or reinforcing the socio-economic disparities based on the digital marginalization of the of the poorer classes, races and regions of the world. The researcher cited the words of Lisa Servon who argues that ownership and access do not necessarily amount to use in all cases where they have the skill. They may not find relevant content online for becoming active and consistent users. According to the investigator, physical access to computer and Internet is definitely a major variable for the better understanding and defining the digital divide. Also there is a urgent need by looking at other variables like literacy, technological literacy content, language, network and the most important one is cost which is correlated with new media access. Moreover, the researcher defined technological literacy as the skills and ability of the individuals and communities to use the digital technologies and Internet for their socio-economic and political needs. Nevertheless he introduced the concept from Andy Carvin where they talked about basic literacy, informational literacy and adaptive literacy are all vital ingredients in understanding the complex nature of digital divide. He also explained the geographic divide as lack of access to new media and the Internet due to geographic location. It is multidimensional and can refer to national, regional and global inequalities in access to Internet. Further he told that availability of digital opportunities is based on where an individual lives in terms of their proximity and access to the digital information networks. He said that global divide is about disparities in access between people living in the highly developed economies of the north and those living in the less developed south. And regarding social divide the investigator opined that differences in access between various social groups due to socio-demographic barriers such as class, income, education, gender, age and race. The general trend in both the developed and developing countries is that the richer classes are the first to own and use these media technologies while the poorer people only get them as a result of the ‘ trickle down’ effect when prices of computers and Internet connection become affordable. Also Internet is a capital-intensive; therefore, poor people are away from computers, modems, and software and Internet service providers monthly subscriptions may not be affordable them. And ‘ democratic divide’ as mentioned by Last Mayo that there are people who can use the digital media and the Internet as tools and resources for participation in political activism and those who cannot participate. 20. Ellen Johanna Helpster in an article ‘ Gendered Internet Use across Generations and Life Stages’ in the journal entitled ‘ Communication Research’ assumes and tests that generation is the determining factor for level of Internet use and life stage, establishes gender variations in Internet use. The researcher have taken a representative sample of 1578 Internet users by applying random selection method. There are four types of variables that the researcher has incorporated in his article, viz. gender, generation, life stage and Internet use. And also research questions were formulated and tested by statistical methods like factor analysis. The researcher considered three types for detailed analysis like sexual material question i. e., ‘ how often people looked for ” sites with adult stuff” (M= 1. 25; SD= 1. 05), health related questions asked how often people looked for information on medical care on the Internet (M= 203; SD= 1. 05) and shopping like how often people said they ‘ get information about goods and services’ and likewise. Not only that scores achieved were averaged (M= 2. 54; SD=. 78. α =. 78). The researcher also chooses to implement Likert Scale (5pt. scale) from (0to 4) which calculated regarding posting of messages on discussion boards, creating a slog or website, whether they had any social networking profile last year (M=. 65; SD= 1. 06, α =. 78). Also, online personal communication calculated how often Internet users took part in the activities like Instant messaging, e-mailing, chatting; M= 2. 69; SD=. 98, α =. 62). The detailed finding summarized as that gendered nature of health (female) and sexual material (male) actions and also showed that men were more frequent users of Internet for shopping than women in Britain. The seven factors areFactor 1: Interpersonal utility with Eigenvalue = 10. 5 and 34. 98 per cent of variance. Factor 2: Information Seeking with Eigenvalue= 2. 81 and 9. 35 per cent of variance. Factor 3: Surveillance with Eigen value = 1. 89 and 6. 29 per cent of variance. Factor 4: Self-developmemnt with Eigenvalue = 1. 36 and 4. 53 per cent of variance. Factor 5; Exploration with Eigenvalue = 1. 15 and 3. 84 per cent of variance. Factor 6: Diversion with Eigenvalue= 1. 12 and 3. 72 per cent of variance. Factor 7: Career Opportunities with Eigenvalue= 1. 01 and 3. 35 per of variance. Finally findings reveal that magazine usage provided superior on ore dimension of gratifications factors than Internet usage. 22. Robert Larose et al, in their article ‘ Understanding Internet Usage- A Social Cognitive Approach to Uses and Gratification’ have identified new set of variables from social-cognitive theory which were very much likely explain Internet usage. The researchers have developed self-efficacy and self-disparagement for the field of Internet behavior. They also defined that Internet addiction was the result of crisis or deficient self-regulation within domain of social-cognitive theory. Moreover, they analyzed negative consequences of online behavior and its impact on Internet usage pattern. Survey method was incorporated distributing Likert-type questionnaire to 171 subjects. And for the measurement of hypothesis the researchers have applied statistical method Pearson product moment correlation and multiple regression. The researcher hypotheses are a) expected activity, pleasing sensory, novel sensory and social outcome expectations are positively associated with Internet usage and after performing correlation matrix there is a significant relationship between variables expected outcomes (r=. 48, p <. 001), pleasing sensory outcomes (r=. 37. p <. 001), novel sensory outcomes (r=. 32, p <. 001) and social outcomes (r=. 37, p <. 001) are all positively related to Internet usage. Further findings supported the second hypotheses that ‘ expectations of negative Internet outcomes will be negatively related to Internet usage’ i. e, negative Internet outcomes were contrary to Internet usage (r= -. 16, p <. 05) and hence supporting the second hypothesis. Similarly, other results revealed that self-efficacy (r=. 65, p <. 001), self-disparagement (r= -. 48, p <. 001), self-slighting (r=-. 46, p < . 001) and self-perceptions of Internet addiction (r=. 65, p <. 001) were all related to Internet usage the way researcher hypothesized. 23. Ting Yang et al, in their article named " A comparative Study on the College Students’ Internet uses and Gratification between Korea and China." Have tried to find out Internet usage pattern and gratification of college students in two countries China and Korea and made comparative study between these two countries. Findings revealed that Korean students have higher Internet gratification level than Chinese students. The researchers have applied Uses and Gratification approach as a strong theoretical framework and found that there is a positive correlation between Internet gratification level and addiction level. Moreover, research results indicated that Gratification Obtained (GO) is higher than Gratification Sought (GS). For the above findings the researchers formulated research questions likeIs there any Internet usage motivation differences between two groups? Is there any Internet gratifications differences between two groups? What is the relationship between gratification level and Internet addiction level? To establish associations between variables the researchers have applied survey method composed of demographic variables, Internet usage situation, gratification level measurement, Internet addiction level measurement. Likert-type scale was formulated with 1 being strongly disagree and 5 being strongly agree. Moreover, they measured difference between two groups through Chi-square test and found that there were no significant difference between two groups Internet usage motivation but information seeking (p <. 01) and online shopping (p <. 01) were significantly different. In another segment like to test the gratification level in two countries the researchers have applied t-test and findings revealed that Internet usage gratification difference between these two countries is significant i. e., (p <. 01) and Chinese group is less satisfied (M= 2. 76, SD=. 60) than Korean group (M= 3. 16, SD=. 54). When measuring the relationship between gratification and addiction Pearson’s correlation was utilized and found that in Korean groups, there is a positive correlation between Internet addiction and Internet gratification (Pearson’s r=. 61, p <. 01) and when it was examined in Chinese students, likewise both Internet addiction and Internet gratification is positively associated (Pearson’s r=. 26, p <. 01). 24. Anabel Queen-Haase et. al, in an article ‘ Uses and Gratifications of Social Media: A Comparison of Facebook and Instant Messaging’ tried to explore comparison between these two media and how these two social media satisfy needs of the users. The researchers have employed both survey and interview method for the data collection. They have applied Likert scale starting from 1= never to 8= several times a day and also identified 25 items or gratifications for measurements but after performing factor analysis with principal component method and also with varimax rotation only 24 items had been included since one item did not satisfy the suggested factor loading. Equally t-tests were employed to examine gender differences in the factors. Finally they applied OLS (Ordinary Least Squares) regression to examine the association between gratification obtained and use of Facebook. Factor analysis revealed six gratification items like pastime, sociability and social information. Also research findings conclude that Facebook is mainly used for fun and know about various social activities in user’s own network while instant messaging is predominantly for maintaining social relationship and social development.

Research Questions:

RQ1: What is the relationship level between motivational factors and the usage of new media by college students? RQ2: What is the relationship pattern between personal gratification dimensions and the usage of new media? RQ3: What is the correlation between influences of social factors and the new media use? RQ4: What is the level of association between academic gratification sought by the students and the new media? RQ6: How far are the use of new media and the use of conventional media interrelated? RQ7: What is the relationship between access to new media and parental income of the college students? RQ8: What is the correlation between parental education and usage of new media by the students? RQ9: What are, in any, negative influences of Internet use on students? RQ10: What are the problems associated with content generation and protection on the web in terms of Internet security?

Social Significance:

The advent of new medium and inroads it has already made in the psyche of the average Indian student make it’s abundantly clear that higher education is virtually impossible to be transacted in the absence of Internet mediation even in the remotest parts of the country. While the Internet has been able to alter the pattern of consuming media texts by opting for digital platform through convergence, it has been able to change the practice accessing superior knowledge sources for the students of higher education sector. India, like other developing nations faces the specter of a digital divide due to its different level of inadequacies. Illiteracy, gender disempowerment, financial incapability and inadequate distribution of material resources in different parts of the country are some of the factors responsible for keeping India in the throes of digital disempowerment. While the transaction of academics has become a completely digitally mediated practice for the students in some parts of the nation and thereby becoming digital natives, most of the students in the country are still very much digital immigrants and busy in overcoming the bottlenecks thrown in by the new digital culture. So, the study would be able to shed light on the factors affecting access and uses of new media and the consequent bottlenecks the students in the colleges in Silchar face and how it can be overcome in future.

Methodology:

This research is basically based on uses and gratification theory. The theory is to examine why under graduate college students are using Internet and what is their level of satisfaction after using Internet and whether they are able to gratify their various tastes, preferences and needs. Hence this U&G approach is the right one for all these answers. One of the methods of research is survey appropriate for the current thesis. Survey is purely a quantitative research and it is under positivist paradigm, i. e., it is frequently used by positivist researchers in social sciences. Positivist research is concerned with many quantitative research techniques like experiment, survey etc. Unlike others survey is the most popular research method in Mass Communication. Survey is being conducted by asking questions through questionnaire regarding quantitative information. Therefore, this method is reflective of the fact that it represents the social nomenclatures and its various tastes and preferences among the universe.

Merits:

Surveys can be employed to investigate the problems in natural settings. For example, newspaper reading or television viewing can be investigated, as they happen, not in the artificial settings of the laboratory. No geographical limitation exists and surveys can be conducted anywhere. A large amount of data can be collected easily from different sections of the society.

Demerits:

Wrong wordings or wrong questions may get wrong responses. Often wrong respondents may be accommodated in survey research. The questions must be worded and organized unambiguously to collect the desired information.

Justification and Limitation of Sampling Procedure:

The researcher has taken into account non-probability sampling, especially in the form of available samples that is samples from volunteer respondents. Available sample is known as convenience sampling (Wimmer & Domminick, 2006) which is readily available for the study such as group of under-graduate students from different colleges in this case. In many instances convenience sampling may be helpful and produce useful results in collecting exploratory information (ibid). But the researcher should aware of the fact that available sample has both positive and negative attributes as it may contain unknown quantities of error (ibid). Application of convenience sampling is a matter of intense debate in many research area as it has no external validity irrespective of what results it generate as many scholars argue. But it is useful in pretesting questionnaire and often help in eliminating problems in research methods before the final research is attempted as argued by the supporters of available sample.

Justification in Respondents’ selection:

From prior research it has been found that Internet gratification and usage pattern specially designed, focused and targeted to college-going students being a first generation and high incidence of users (Robert La Rose et al, 2002). They are the most emblematic population of users as felt by the earlier researchers. Hence, the researcher has identified college students as potential subjects.

The Profile of Area:

Silchar is situated in the southern part of the Indian state of Assam. It is the headquarters of the Cachar district. The city of Silchar is the second largest city in the state of Assam and an important commercial centre and consequently witnesses the settlement of a sizable population of traders from distant parts of India. The main city of the Barak valley is Silchar. The researcher has chosen all the four colleges from Silchar. Selected colleges are Guru Charan College, Cachar College, Radhamadhab College and Women’s College. The research questions formulated and tested with the statistical technique of factor analysis, correlation, multiple regression and ANOVA. Sample Size: The sample size is 405. It is a well-known fact according to Wimmer and Dominick that multivariate analysis always demands a large number of samples than univariate studies for the simple reason that multivariate analysis involves analyzing multiple response data, that is, several measurements measuring the same subject. Guidelines followed for choosing sample size for multivariate statistics is as follows: Sample size (S. S) 50= Very poor(Comrey & Lee, 1992)S. S 100= PoorS. S 200= FairS. S 300= GoodS. S 500= Very goodS. S 1000= Excellent.

List of independent variables-

‘ Motivation factor’ which are ‘ access advantage’ and ‘ peer compatibility and capacity building’.‘ Personal gratification factor’ which are ‘ information seeking’ and ‘ allied aggregation’.‘ Social factor’ which are ‘ friendship factor, and ‘ socialization’.‘ Academic gratification factor’ which are ‘ capacity enhancement’ and ‘ academic gratifications’ and ‘ role of teachers’‘ Demographic factor’ which are ‘ family income, ‘ course factor’, ‘ mother’s education’ and ‘ father’s education’.

And dependent variables are

1. ‘ Benefits of Internet’ and2. ‘ Companionship’Variables selected after extensive literature review:

Questionnaire Construction:

The structured questionnaire with factors and its sub-factors with a scale of 1 to 3 points. The researcher has distributed the questionnaire directly to the respondents for maximum responses. The questionnaire consists of three parts, viz., part-A, part-B. Part-A deals with demographic data, and part-B dealing with statement wise questions. There are 16 statement type questions. Out 16 questions, a total of 80 variables are enlisted. The researcher has used 3-point Likert scale method e. g., The extent of current practice is: I can’t say Disagree Agree1 2 3The students were asked to give their responses as per the above structure.

Factor Analysis: The Brief of Sophisticated Statistical Application.

Factor analysis is a multivariate technique. It is an extremely potent, powerful and functional analytic approach to explore or define psychological variables as well as behavioral, financial and other types of variables. It is a sophisticated statistical technique for determining the underlying factors or latent factors among a large number of interdependent variables. Moreover, it is a useful method for designing multiple-item scales, where each scale represents a dimension of a highly abstract construct. The researcher has designed taking ‘ Internet Gratification’ as major item. Many items or sub-items can be used to define gratification like motivational gratification, personal gratification dimension, social gratification and academic gratification and so forth. Under these gratification items, many sub-items can be developed and interpreted through factor analysis. However, the researcher can simplify the measurement of Internet gratification by identifying a couple of underlying dimensions of Internet gratification. The researcher further separated Internet gratification into many sub-concepts like a) access to cyber world (b) updating knowledge (c) to be equal with friends or peer group compatibility (d) borderless communication (e) increases the ability to compete with others or enhances competitiveness. All the sub-items are under motivational gratification dimension. The relationship between the sub-items and Internet motivational gratification could then be transformed or expressed as follows: Internet motivational gratification = G (Access to virtual world) + G (Upgrading knowledge) + G (Peer group compatibility) + G (Borderless communication) + G (Enhances competitiveness) ; where G= Gratification. In this formulation, Internet motivation gratification is a construct represented by a few basic factors. The research actually starts by identifying a good number of items to define each of the factors. These are some of the items administered to the subjects via questionnaire during the course of the study. Likewise the other factors personal gratification, social gratification and academic gratification can be expressed and formulated. Hence, factor analysis is an appropriate technique for cases where the items or factors or variables have a high degree of inter-correlation. There are many underlying or latent variables which have been defined rightly according to their factors loadings. Nonetheless there are many concepts which need to define here to discuss factor analysis and not only that all those concepts have used in further analysis and interpretation of the data. Factor: it is an underlying dimension of numerous interrelated variables. Factor loadings: it is nothing but some numerical values which explain how closely the variables are related each one of the factors discovered. They are factor-variable correlations. It is the absolute size of the loadings that is important in the interpretation of the data. There should be a minimum standard or cut-off for factor loadings for indentifying the latent variables. The selection of latent variables is fully dependent on minimum factor loading for each variable. Factor loading varies depending upon the nature of the study. Many researchers argue and claim that factor loading should be decided on the basis of sample size being selected in the study, i. e., factor loading should 10 per cent from the total sample size. If the sample size is 300 then factor loading for the corresponding each variable will be 0. 30. Communality (h2) = it shows how much of each variable is accounted for by the underlying factors taken together. It is computed as under: h2 of a variable = [its factor loading of factor A]2 + [ its factor loading of B] + ………….. Eigen value (or latent root): it is the sum of squared values of factor loadings relating to a factor. It indicates the relative importance of each factor in accounting for the particular set of variables under study. Total sum of squares: when Eigen values of all factors are totaled, the resulting value is called the total sum of squares.

Purpose of Using Factor Analysis:

The main purpose of applying factor analysis or data reduction method is to remove highly correlated variables or redundant variables from the original data set with a smaller number of uncorrelated variables. The factor analysis method has several procedures to construct a solution. Firstly one has to go for extraction methods. The principal component method of extraction has been enacted and starts by finding a linear combination of variables or component that accounts for as much variation as possible. It then finds another component that accounts for as much of the remaining variation as possible and is uncorrelated with the previous component, continuing in this way until there are as many components as original variables. Usually, a few components will account for most of the variation, and these components can be used to replace the original variables. This method is most often used to reduce the number of variables in the data file.

Applications of Factor Analysis:

A. Identification of Latent or Unobtrusive Factors:–clusters variables into homogeneous sets.–generates new variables (i. e. factors).–approves one to gain insight into categories. B. Screening of Variables:–identifies groupings or renaming to allow one to select one variable to represent many.–useful in regression. C. Eigen Values• Selecting how many components or factors to use, consider Eigen values from a principal components method.• Rules to go by:-Scree plot-% of variance explained.