## http://unllib.unl.edu/LPP/
Library Philosophy and
Practice 2012ISSN 1522-0222 ## Does the Digital Environment Improve Modern Users' Internet Awareness?Dr. T. Saravanan M.M. Kalaivani Dr. V. Senthilkumar Department of Library & Information Science ## IntroductionMan invented many wonderful gadgets to the society. Now, those items are ruling the world and without which regular routines are unimaginable in the human beings life. Many studies reveal that people routines are heavily tied with those items. The Internet and its resources are playing a vital role in everyone life. Awareness of Information literacy concepts and skills are essential things to the modern users in order to improving their potential in research and other areas of academy. The associations between the users and their dependency of Internet have been traced in many studies. The global development of Internet features in digital libraries has generated changes in the pattern of library routines. Progressive development of Internet technology has affected the way of modern users in utilizing the electronic collections. The reasonable price of those electronic items enables the users to buy and access the electronic resources as and when they are interested. The massive impact of Internet and its electronic resources change the way of information seekers, who are seeking information in electronic environment. This is one kind of an attempt to investigate the modern users' Library visit and their awareness of Internet. ## ObjectivesThe objectives of this research were concerned with to measure the respondents' frequency of Library visit; their awareness levels of Internet, and the level of existing relationship between their Library Visit and Internet awareness. ## MethodologyThe respondents were selected from the disciplines of Commerce, Economics, English and History belonging to the Faculty of Arts, Annamalai University located in Tamilnadu. In our experimental design the population range for said disciplines was traced as 250. Selecting sample is an important task in any social sciences research. Hence the standard method was applied to measure the required sample size. The samples were selected for evaluation as calculated using the expected error rate, desired precision range and confidence level. Based on the said attributes the required sample size was traced as 111.95, but study included 120 samples for further investigation. To fulfill the structured problem objectives a well structured questionnaire was structured and distributed to 150 users on the basis of stratified random sampling. Of them 120 filled in questionnaires were taken into the account of analysis. The collected data were carefully sorted and analyzed with the statistical procedure namely Two-Way ANOVA. Also, the Post-Hoc Test (Tukey HSD) has been applied to go in depth to trace the positions of differences. ## ScopeRestrictions always exist to explore our presentations in any journals. Keeping this aspect in mind the present investigation comprises the respondents' frequency of Library visit and their Internet awareness levels only. ## HypothesesTo fulfill the said objectives a few null hypotheses have been structured in the present study. H H H H H H H ## AnalysisTable 1: Frequency of Library Visit: Table 1.1:Row Analysis: Table 1.2:Col. Analysis: Table 1.3:Total Analysis: The branch wise respondents' Library visit could be observed from the Table 1. 42.50% of the Commerce discipline users visit the library daily, followed by once in 2 days (27.50%) and rest of the levels have secured as 10% & 5% respectively. Economics discipline has secured 33.33% for the option 'Daily" followed by once in 2 days (30.00%), Bi-Month (13.33%), Monthly & Weekly (10.00%) and rest of the level 'Bi-Week' has got 3.33% only. 50.00% of the English branch users visit the library 'Daily', followed by once in 2 days (20.00%),Weekly (15.00%), Bi-Week(10.00%) and the remaining options have secured 2.50% each. 40.00% of History users visit the library 'Daily' while 25.00% of them visit the library 'once in 2 days'. The rest of the options have got their own in between the ranges of 5.00% and 11.67%. The columns and total analyses may explore more information about the dispersions of the observations. The observed points alone would never help any investigators to make the inferences about the population. Hence, a Two-Way ANOVA (Table 1.4) has been performed to trace the significance among the variables. From the ANOVA test results, it is inferred that with the weakened evidences (F=3.69(Fcrit =3.287), 8.38(Fcrit =2.901)) we fail to claim support to the formulated hypothesis one (H Table 1.4: Two Way Analysis of Variance: Variable analyzed: Score/Factor A (rows) variable: Branch/Factor B (columns) variable: Visit
Omega squared for combined effects = 0.652 Table 1.5: Descriptive Statistics: Table 1.6: Comparisons among Branches The comparisons among rows (Branch) were analyzed and explored here to test the hypothesis three (H The Tukey HSD Test was adopted to measure the differences between means at alpha level 0.05 (Table 1.6 )and observed that there would be no significance statistically identified among rows and based on these enough evidences we can claim support to the formulated hypothesis three (H Table 1.7: Comparisons among Visits The comparisons among Columns (Visit) were analyzed and explored here to test the hypothesis four (H Table 1.7 depicts that there would be no significance statistically identified among columns at alpha level 0.05, and based on these enough evidences, we can claim support to the formulated hypothesis four (H Comparisons among Visit within Each Branch The comparisons among columns (visit) within each were analyzed and explored here to test the hypothesis five (H Table 1.8: Row 1 Comparisons (Commerce) Table 1.8 shows the test results that there would be no significance statistically identified among columns within row (Commerce) and based on these enough evidences we can claim support to the formulated hypothesis five (H Table 1.8a: Row 2 Comparisons (Economics) Table 1.8a shows the test results that there would be no significance statistically identified among columns within row (Economics) and based on these enough evidences we can claim support to the formulated hypothesis five (H Table 1.8b: Row 3 Comparisons (English) Table 1.8b shows the test results that there would be no significance statistically identified among columns within row (English) and based on these enough evidences we can claim support to the formulated hypothesis five (H Table 1.8c: Row 4 Comparisons (History) Table 1.8c shows the test results that there would be no significance statistically identified among columns within row (History) and based on these enough evidences we can claim support to the formulated hypothesis five (H Comparisons among Branch within Each Visit The comparisons among rows within each column (visit) were analyzed and explored here to test the hypothesis six (H Table 1.9: Column 1 Comparisons The above Tukey HSD Test among pairs of means at alpha level 0.05 clearly indicates that there would be no significance statistically identified among rows within each column(1) and based on these enough evidences we can claim support to the formulated hypothesis six (H Table 1.9a: Column 2 Comparisons Table 1.9a explores the Tukey HSD Test results at alpha level 0.05 that there would be no significance statistically identified among rows within each column(2) and based on these enough evidences we can claim support to the formulated hypothesis six (H Table 1.9b: Column 3 Comparisons Table 1.9c: Column 4 Comparisons Table 1.9d: Column 5 Comparisons Table 1.9e: Column 6 Comparisons From the tables 1.9a-1.9e if could be inferred that at alpha level 0.05 there would be no significance statistically identified among branches within each visit, and based on these enough evidences we can claim support to the formulated hypothesis six (H Table 2: Awareness of Internet Table 2.1: Row Analysis: Table 2.2: Col. Analysis: Table 2.3: Total Analysis: Respondents' awareness levels of Internet could be observed from the Table 2. In Commerce discipline 57.50% of the users have adequate awareness followed by 'Insufficient' (25.00%) and 'I can manage' (17.50%). In Economics 56.67% of the respondents have adequate awareness followed by 'Insufficient' (36.67%), and rest of the level has secured 6.67%. The respondents from the branch 'English' have received the scores 52.50% (adequate), 30.00% (I can manage) and 17.50% (Insufficient) respectively. History branch has secured 40.0% for the option 'adequate', and rests of the options have received 30.00% each. The columns and total analyses may explore more information about the dispersions of the observations. The observed points alone would never help the investigators to make the inferences about the population. Hence, a Two-Way ANOVA (Table 2.4) has been performed to trace the significance among the variables. From the ANOVA test results it is inferred that there would be no significance exist among the branch wise analysis (F=3.347(Fcrit =4.757)), which led us to claim support to the formulated hypothesis two (H Table 2.4: Two Way Analysis of Variance Variable analyzed: Score/ Factor A (rows) variable: Branch/ Factor B (col.) variable: Awareness
Omega squared for combined effects = 0.588 Table 2.5: Descriptive Statistics: Table 2.6: Comparisons among awareness The comparisons among columns (awareness) were analyzed and explored here to test the hypothesis four (H Table 2.6 depicts that there would be no significance statistically identified among columns at alpha level 0.05, and based on these enough evidences, we can claim support to the formulated hypothesis four (H Comparisons among Awareness within Each Branch Table 2.7: Row 1 Comparisons Table 2.7a: Row 2 Comparisons Table 2.7b: Row 3 Comparisons Table 2.7c: Row 4 Comparisons Tables 2.7-2.7c depict that there would be no significance statistically identified among the awareness within each row (Branch) at alpha level 0.05, and based on these enough evidences, we can claim support to the formulated hypothesis five (H Comparisons among branch within each awareness levels The comparisons among rows (Branch) within each column (awareness) were analyzed and explored here to test the hypothesis six (H Table 2.8: Column 1 Comparisons (Adequate) Table 2.8a: Column 2 Comparisons (I can manage) Table 2.8b: Column 3 Comparisons (Insufficient) Tables 2.8-2.8b depict that there would be no significance statistically identified among the branches within each column (awareness) at alpha level 0.05, and based on these enough evidences, we can claim support to the formulated hypothesis six (H Pearson Coefficient of Correlation Test: Table 3: Daily and Adequate
An evaluation was made of the linear relationship between the selected variables using Correlation. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Daily and Adequate as r(2)=0.9145, p = 0.086. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-3: Scatter Plot Distribution Table 3.1: Daily and I can manage
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Daily and I Can Manage as r(2)=0.8678, p= 0.132. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-3.1: Scatter Plot Distribution Table 3.2: Daily and Insufficient
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Daily and Insufficient as r(2)=0.4746, p = 0.525. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-3.2: Scatter Plot Distribution Table 4: Once in 2 Days and Adequate
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables and also statistically significant linear relationship between Once in 2 Days and Adequate as r(2)=0.9525, p = 0.0476. Hence, we do not have enough statistical evidences to claim support to the formulated hypothesis seven (H Figure-4: Scatter Plot Distribution Table 4.1: Once in 2 Days and I can manage
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Daily and I can manage as r(2)=0.3218, p = 0.6782. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-4.1: Scatter Plot Distribution Table 4.2: Once in 2 Days and Insufficient
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Daily and Insufficient as r(2)=0.922, p = 0.078. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-4.2: Scatter Plot Distribution Table 5: Week and Adequate
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Week and Adequate as r(2)=0.8532, p = 0.1468. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-5: Scatter Plot Distribution Table 5.1: Week and I can manage
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Week and I can manage as r(2)=0.8806, p = 0.1194. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-5.1: Scatter Plot Distribution Table 5.2: Week and Insufficient
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Week and I can manage as r(2)=0.8806, p = 0.1194. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-5.2: Scatter Plot Distribution Table 6: Bi-Week and Adequate
An evaluation was made of the linear relationship between the selected variables using Correlation analysis. Test result indicates the negative and weak relationship between the variables Bi-Week and Adequate as r(2)=-0.1058, p = 0.8942. With the help of enough statistical evidences it is inferred that there would not be a possible significance statistically identified to claim support to the alternative against the formulated hypothesis seven (H Figure-6: Scatter Plot Distribution Table 6.1: Bi- Week and I can manage
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Bi-Week and I can manage as r(2)=0.7384, p = 0.2616. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-6.1: Scatter Plot Distribution Table 6.2: Bi-Week and Insufficient
An evaluation was made of the linear relationship between the selected variables using Correlation analysis. Test result indicates the negative and weak relationship between the variables Bi-Week and Insufficient as r(2)=-0.6825, p = 0.3174. With the help of enough statistical evidences it is inferred that there would not be a possible significance statistically identified to claim support to the alternative against the formulated hypothesis seven (H Figure-6.2: Scatter Plot Distribution Table 7: Monthly and Adequate
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Monthly and Adequate as r(2)=0.6199, p = 0.3802. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-7: Scatter Plot Distribution Table 7.1: Monthly and I can manage
An evaluation was made of the linear relationship between the selected variables using Correlation analysis. Test result indicates the negative and weak relationship between the variables Monthly and I can manage as r(2)=-0.2272, p = 0.7728. With the help of enough statistical evidences it is inferred that there would not be a possible significance statistically identified to claim support to the alternative against the formulated hypothesis seven (H Figure-7.1: Scatter Plot Distribution Table 7.2: Monthly and Insufficient
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. Also, there would be a statistically significant linear relationship between Monthly and Insufficient as r(2)=0.969, p = 0.03. Hence, we do not have enough statistical evidences to claim support to the formulated hypothesis seven (H Figure-7.2: Scatter Plot Distribution Table 8: Bi-Month and Adequate
An evaluation was made of the linear relationship between the selected variables using Correlation Analysis. Test result indicates positive relationship between the variables. However, no statistically significant linear relationship between Bi-Month and Adequate as r(2)=0.658, p = 0.342. Hence, we do not have enough statistical evidences to claim support to the alternative against the formulated hypothesis seven (H Figure-8: Scatter Plot Distribution Table 8.1: Bi-Month and I can manage
An evaluation was made of the linear relationship between the selected variables using Correlation analysis. Test result indicates the negative and weak relationship between the variables Bi-Month and I can manage as r(2)=-0.2134, p = 0.7866. With the help of enough statistical evidences it is inferred that there would not be a possible significance statistically identified to claim support to the alternative against the formulated hypothesis seven (H Figure-8.1: Scatter Plot Distribution Table 8.2: Bi-Month and Insufficient
An evaluation was made of the linear relationship between the selected variables using Correlation analysis. Test result indicates the strong relationship between the variables Bi-Month and Insufficient as r(2)=-0.956, p = 0.044. With the help of enough statistical evidences it is inferred that there would not be a possible significance statistically identified to claim support to the alternative against the formulated hypothesis seven (H Figure-8.2: Scatter Plot Distribution Determinations: The present study encompasses the sample size up to 120 comprising the disciplines of Commerce, Economics, English and History. The study reveals that the respondents' daily visit to the library to utilize the IT infrastructures has secured the first slot as the mean value is traced as 12.75 with Std.Dev. 7.182. Respondents' 2 days once visit received the mean 7.5, and Std.Dev. 3.873. The Week wise visit to the library has secured the mean and Std.Dev. 3.5, 2.082 followed by Bi-Week (2.5, 1.291), Bi-Month (2.25, 2.062) and rest of the attribute month have the least values (1.5, 1.291). It could be inferred from the analysis that the majority of respondents would like to visit the library daily in order to access the electronic features that are offered in the library. Two-Way Anova was applied to fulfill the research question; do the modern users' Library visits differ? , and the results (F=3.69, 8.38) made us to conclude that there would be a possible significance exist between the users visit to the library. The calculated w The analysis for the attributes 'Internet awareness' reveal that majority of respondents have got adequate awareness (mean=16.25, Std.Dev.=8.539) of Internet whereas the rest of the users felt that they have insufficient knowledge of the Internet (mean=7.75, Std.Dev.=3.594) followed by the level 'I can manage', which has received the mean 6 with the Std.Dev.4.546. Two-Way Anova was again applied to test the research question, do the users' Internet awareness levels differ? , and the results for rows (F=3.347, 6.038) made us to conclude that there would not be a possible significance exist between the users' awareness levels. In contrary the results for columns (F=6.038) would not led us to conclude the same. To trace the significance for the pairs, we once again used the Post-Hoc Test (Tukey HSD). The awareness wise comparison test results indicates possible significance for the groups 1-2 (Table 2.6) rather than other pairs. The statistical tool namely Pearson's correlation coefficient has been adopted to test the research question, do the users' Library visits influence them to upgrade their awareness of Internet? , and the outcomes were explored towards the Tables 3-8.2. Correlation Test result indicates positive as well as statistically significant linear relationship between the variables (Table 4) Once in 2 Days and Adequate as r(2)=0.9525, p = 0.0476 ; (Table 7.2) Monthly and Insufficient as r(2)=0.969, p = 0.03, and (Table 8.2) Bi-Month and Insufficient as r(2)=-0.956, p = 0.044. Though some of the strong/weak and positive/negative relationships were identified between the variables thorough out the study the possible significance was not captured in between the levels of the variables except a few levels. It would be interesting to observe the above results that the frequent visits to the library enable one to be aware of the Internet, when compared to the Bi-Month and Month wise visits. Hence, it could be concluded that there would be linear relationship exist between the users' library visits and their awareness of Internet. Of course, the electronic environment setups inside the library upgrade the modern users' Internet awareness. ## AcknowledgementsI sincerely express my thanks to Professor Emeritus William G. Miller, Lowa State University. ## References1. Ricco RAKOTOMALALA.(2005). Tanagra: Un logiciel gratuit pour l'enseignement et la recherche. in Actes de EGC'2005, RNTI-E-3.vol-2. Pp.697-702. 2. Saravanan, T. (2010). Google Use and Users: A Survey. 3. Saravanan T and Gopalakrishnan, S.(2011). Higher education user's awareness of Google: Searching for Structure. 4. TexaSoft. (2007) WINKS SDA, 6 5. William G. Miller.(2009). ## Appendix 1
Figure 1: Branch wise 3D Distribution Figure 2: Library Visit-3D Distribution Figure 3: Branch Vs Visit 3D Distribution ## Appendix 2Figure 4: Branch Mean Distribution Figure 5: Awareness Mean Distribution
Figure 6: Branch Vs Awareness Mean Distribution |