Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502 Vol. 3(8), 8-15, August (2014) Res.J.Recent Sci. International Science Congress Association 8 Relationship between Self-Regulated Learning Strategies and the Level of Internet Competency in Bachelor of Science Degree Students Eshaghali Azizi and K. Yeshodhara Department of Studies in Education, University of Mysore, Mysore, Karnataka, INDIAAvailable online at: www.isca.in , www.isca.me Received 17th September 2013, revised 30th November 2013, accepted 5th January 2014Abstract This paper is based to answering a question: Is there any relationship between Self-Regulated Learning Strategies (SRLS) and the level of Internet Competency (IC) in Bachelor of Science (B.Sc) Degree Students in various subjects include: PMCs, PCM and CBZ or not? This was a correlation study with prediction and analytical research. Among 254 Bachelor of Science Degree Students in final year who had taken out of 4 particular colleges which are stand for Mysore University Constituent College, Governmental College, Private Unaided and Private Aided College. Any one has chosen for convenience sampling method. The Motivational Strategies for Learning Questionnaire (MSLQ) have occupied to assess in Learning Strategies in total and scale wise. The Internet Competency tools prepared by researcher who had made to assess the level of Internet Competency in total and component wise. The data has analyzed using Pearson's correlation coefficient and Multiple Regression. As a matter of fact researcher has found that in his two variables include: Self-Regulated Learning Strategies and Internet competency among Bachelor of Science Degree Students in various subjects such as: PMCs, PCM and CBZ has a positive relationship in total. Keywords: Internet competency self-regulated learning strategies, computer general knowledge, ability, rehearsal, elaboration and critical thinking. IntroductionOne of the main elements of advance level education is the standard of teaching- learning procedure. The quality of this element depends on the attribute of learning and teaching performance. The oncoming vicissitude of acquire learning psychology of behaviorism to cognitivism and constructivism have furnished theoretical basis for teacher towards the choosing of exact appropriate methods of teaching and attain the required level of learning. But in fact, it is essential for students and teachers to be acquainted with teaching-learning methods and learning values. There by enormous progress the learning science and implementation of information and communication devices in advance education and application of active learning methods have facilitated both teachers and learners to outcome in efficient learning. Self Regulated learning (SRL) is an active constructive procedure, hence for learners set aims for their learning and monitor, policy, and controls their cognition, motivation, and behavior, directed and constrained by their ambitions and the contextual element of the environment. The current studies related to cognitive and Metacognitive Strategies have demonstrated that the person’s ability for learning depends on how much he/she uses these Strategies. More usage of these Strategies will be more useful for learning different subjects. The main point is that these are acquisitive and can teach them. Data has shown that when university or educational environment knows these relations, the learning environment will be designed for helping students more in learning. As higher education systems, especially computer science and other science subjects changed remarkably and increased their responsibilities for their activities, it seems that this process will grow increasingly; therefore, universities and teachers have important responsibility towards student’s better learning. The Internet has removed barriers of communication access from any corner in the world. It is quick, dependable and does not have confinement on content or format (except in particular countries). It also has an unlimited scope of facilities which aid users to obtain almost the infinite information in the Internet. The Internet expresses the opportunity to approach update research statement and knowledge throughout the world on topics as variant as science and technology, finance and business, arts and music. Thereby, it has become an essential constituent of electronic devices in academic Colleges and thus an invaluable instrument for learning and research. Hence Internet resources to be utilized effectively, students and scholars are required to evolve a sequence of new skills that comprise methods for searching appropriate tools, skills in evaluating the quality of documents setup, knowledge of web design, talents in using discussion forums and chat rooms, and in addition based understanding of how to dispatch e-mail attachments. IC is the capacity of a personality to use the Internet accurately. It is a union of knowledge and skills to utilize the Internet for enhancing better academic performance. In addition to universal Research Journal of Recent Sciences ______________________________________________________________ ISSN 2277-2502Vol. 3(8), 8-15, August (2014) Res. J. Recent Sci. International Science Congress Association 9 Computer knowledge it comprises the capacities like General Webpage Using, Communication and Collaboration, Information Search and Information Management etc. Studies included that the Internet use and academic accomplishment were observed using the motives of Internet usege, students' attitude towards Internet usage, online time management, holdup tools for Self Regulatory talent in Web-based Learning Environment, the merits for Self Regulated students on the Internet, and Internet usage and technology. The outcome of these studies indicated that advanced computer skills, better time management, and more positive attitude towards Internet usage of enhanced academic progress, while Internet usage among students who are optimist influences scholastic learning10. Nowadays the Internet is penetrative in the lives of personals, colleges, and societies all over the globe, so in India. In the previous few decades have gone through a dramatic increment in the use of the Internet and an unparalleled proliferation of computer based technique. Computer technologies and the Internet bring up social advancement in modern society. Thereby computers have become a normal equipment of day to day living for an enormous proportion of our society; the Internet has a significant impact on quality of life11. Internet use provides many opportunities for education. Application of self regulation to internet usage can enhance the benefits offered by the Internet12. Self regulation helps student utilize the internet and computer to achieve academic goals. Self regulation plays the key role in the learning process and in regulating Internet use. Students achieve their own goal if they control and manage their tools with regulated learning13. Life is very rapid in this era of computer and technology. There is an immense requirement for knowledge up to date, which is a lot dependent on the usage of Internet. As such IC and SRL in nowadays world are necessary for people, particularly for students' generation. Hargis also viewed that understanding of the interaction between the students' learning Strategies, and motivation and technology can provide insight into helping students improve academic achievement. Consequently, Hargis examined the effect of SRL on Internet usage. He insisted that research about self regulation should be done to maximize the new educational tools, Internet use. LaRose, Mastro, and Eastin14 investigated the understanding of Internet usage in a correlational study with undergraduate students. There were positive correlations between Internet usage and the expected positive outcomes such as vigorous results (r= 0.48), pleasing connected results (r= 0.37), novel sensory results (r= 0.32), and social results (r= 0.39). There had been negative correlations between internet use and the expected negative constructs such as negative outcomes (r= -0.16), one's disparagement (r= -0.48) and one's detracting (r= -0.46). Internet addiction was positively correlated with Internet usage (r= 0.65). Internet one's efficacy was highly correlated to Internet usage (r= 0.65). Internet use was predicted, using multiple regression with the predictors, self efficacy of Internet (b= 0.65), perceived addiction (b= 0.41), activity results (b = 0.21), and one's-disparagement (b= -0.14) at a significant level of p 0.05. The results suggest that users with high self efficacy access the Internet confidently, and users with perceived addiction use the Internet more than others. They interpreted the results to mean that a person with Internet addiction is deficient in Internet self regulation. Another factor influencing Internet use is anxiety. La Rose, Lin, and Eastin15 showed a direct relationship between Internet usage and deficient Internet self regulation (r= 0.45) and Internet self efficacy (r= 0.38). They called it unregulated Internet usage when the users do not manage their Internet use time, or when they have a problem using the Internet productively. The studies of Internet usage suggest that if students are deficient in using self regulated policies, their use of the Internet can negatively affect academic achievement regardless whether they are novice or expert users. Unregulated Internet use can be changed into regulated Internet use when students are guided by goals and objectives during Internet use. Students can be Self Regulated learners by using Learning Strategies. Students are able to be motivated the usages of SRLS by clear learning objectives and goals. Yangkim13 pointed out that there was less correlation between self regulation and academic levels and self regulation and Internet usage. There was no statistically significant correlation between Internet usage and academic achievement. Self regulation was remarkably correlated to self efficacy. Aggregate internet access was remarkably correlated to non academic related Internet browsing. Mean while not statistically significant, the consistent negative correlations between non academic Internet usage with both self regulation and achievement showed that the Internet may present an attractive distraction to achievement which may be occur to lack of self regulation. Bakay16 has indicated that there are significant differences among students IC grades and their individual distinctive, such as the kind of high school they are registered in, where these high schools are situated (center or suburb), and their Internet access situation such as, having computer at home or not, being subscribed to an Internet company or not, where they connect, how they have learned and how much time they spent to Internet weekly, the most preferred activities on the Internet, their stage of English and if they are attend Internet cafes or not. There are no significant differences between student's IC scores and their individual characteristics such as gender, grade, age and study area. Stromse and Bréten17 indicated that magnitude of internet specific epistemic ideas were found to explicate unparalleled variance in Internet based rummage, help seeking, self regulatory methods Research Journal of Recent Sciences ______________________________________________________________ ISSN 2277-2502Vol. 3(8), 8-15, August (2014) Res. J. Recent Sci. International Science Congress Association 10 respectively, specifically, students who emphasized that course related knowledge situated on the Internet consisted of particular truth and details perceived internet quest and valuation of search outcome to be less problematic and statement on more help Seeking and utilize of self regulatory methods during Internet based learning. Furthermore students thinking that internet based knowledge alleges need to be checked opposite other sources, evidence and prior knowledge were reportedly more likely to utilize self regulatory methods when using the Internet pending coursework. The outcomes are discussed as point of view of what characterizes the internet as knowledge originate. Lim18 exhibited that Internet information literacy correlated with Internet literacy (mechanical aspect) at a relatively remarkably coefficient of 0.71 and internet information literacy correlated with computer literacy at 0.67. Howsoever, it must be insisted that an Internet savvy student with advance computer literacy is not require further competent in information literacy. This is due to the outcomes that verify information literacy is also dependent on the student's academic ability and expert in the English language. Hence the mechanical IC level is not the only indicator impacting the competency stage of information literacy. However, it does indicate that students must hold a certain stage of computer, internet and information literacy in order to be able to make more effective use of the internet (as evidenced by the grade in information literacy; that is, advance the grade, the more effective the use of the internet) as a source of information and knowledge. In addition to computer and internet literacy, indicators influencing Internet information literacy are the English language in fluently and the innate academic ability of the volunteers. Furthermore, there was correlation between the frequency of the usage of the internet for schoolwork and the literacy level of the volunteers in computer, internet and information literacy, and also their inherent ability. McGhee19 indicated the statistically significant relationships between online technologies self efficacy with academic achievement and asynchronous interaction with academic achievement. Howbeit, there were less correlations between SRL and academic achievement. The outcome of this study ponders the constructivist tenets that the student is at the center of the learning experience. The current study is an attempt for the study of relationship between SRLS of B.Sc Degree students and their IC. It's hypothesized about the significant relationship between SRLS of B.Sc Degree students from different combination of subjects-PMCs, PCM and CBZ and their level of IC. MethodologyThe population of this study comprises: final year students of the Yuvaraja College, Governmental First Grade College in Kuvempunagar, Maharani Science College For Women, Saradavilas College, Mahajana First Grade College, Governmental First Grade College for Women in Vijayanagara, Teresian College, NIE Science College, MMK and SDM College for Women, ST. Josephs First Grade College and Mallamma Marimallappa Science and BBM College that have B.Sc degree in different combinations as- PMCs, PCM and CBZ in Mysore city (Karnataka state- India). Only 2 colleges- ST. Josephs First Grade Colleges and BBM and Mallamma Marimallappa Science College have exempted from the population, due to they didn't have students of final year. The number of population was 745 students as following: PMCs -234 students, PCM 323- students and CBZ 188- students. Convenience sampling method has used to choose the Colleges in Mysore city and random sampling technique has used to draw final year students from different types of Colleges giving stand for different subjects- PMCs, PCM and CBZ. In total 254 students has chosen according to the table of Krejcie and Morgan20. Whole the colleges constituting the sample of the study are affiliated to University of Mysore. One college was chosen under any type of college: Governmental College, University of Mysore Constituent College, Private Unaided and Private Aided College. The details of the sample chosen for the study have given in the table 1. Table-1 Details of the sample for the study No. college Type Population and Sample Combination of field Totality CBZ PCM PMCs F M T F M T F M T F M T 1 Pvt. Unaided Population - - - 11 - 11 35 - 35 46 - 46 Sample - - - 5 - 5 14 - 14 19 - 19 2 Pvt. Aided Population 9 20 29 10 44 54 0 13 13 19 77 96 Sample 4 8 12 4 18 22 0 5 5 8 31 39 3 Governmental Population 82 - 82 97 - 97 34 - 34 213 - 213 Sample 33 - 33 39 - 39 14 - 14 86 - 86 4 UOM Constituent College Population 12 50 62 25 109 134 28 50 78 65 209 274 Sample 5 20 25 10 44 54 11 20 31 26 84 110 totality Population 103 70 173 143 153 296 97 63 160 343 286 629 Sample 42 28 70 58 62 120 39 25 64 139 115 254 Research Journal of Recent Sciences ______________________________________________________________ ISSN 2277-2502Vol. 3(8), 8-15, August (2014) Res. J. Recent Sci. International Science Congress Association 11 Motivational strategies for learning questionnaire (MSLQ) was applied in this study to assess the SRLS. This tool was designed at Research National Center of Michigan University (1986) to improve teaching and learning in high schools. Then it was extended to collegiate courses in order to measure the orientation of student's motivation and use them for learning. This tool consisted of 2 parts- i. Motivation and ii. Learning Strategies. In such study only Learning Strategies part has used. In this part, there are 2 components- i. Cognitive and Metacognitive Strategies ii. Resource Management Strategies- and it has 9 scales, each consisting of multiple items- elaboration, organization, rehearsal, metacognitive self regulation, critical thinking, effort regulation, time and study environment, help seeking and peer learning. In aggregate this part of questionnaire (Learning Strategies) consisted of 50 items. Each item has 7 levels of responses. If student thinks the declaration is very true of her/his, cross () box of 7, if a report is not at all true of student, cross () box of 1. If the report is more or less true of student, find the number between 1 and 7 that best depict student. This questionnaire was standardized by Pintrich, Smith, Garcia and Mckeachie21 using a sample of 380 students. In India Dangwal and Gope22 established its reliability with split half method and it was 0.98. In this study Cronbach's alpha reliability coefficient was found out and it was 0.93. Furtherthe IC questionnaire used in such study to assess the level of IC has made by the researcher. This questionnaire constituted of 6 main components, each consisting of multiple items. Each one item has 5 levels of responses like Nil, Poor, Average, Good, Very Good, which were given rating of 0 to the nil, 1 to the poor, 2 to the average, 3 to the good and 4 to the very good. It consisted of six components- General Webpage using, communication and collaboration, computer general ability, computer general knowledge, information search and information management. In whole this questionnaire included 72 items. Cronbach's alpha reliability coefficient have found out of 0.93. This paper is a correlation study with descriptive research. Further involves prediction of most contributing variables to the IC of B.Sc Degree students through regression analysis. The data has collected using MSLQ and IC questionnaire. During administration of the questionnaire, clarifications have given for certain items on demand. The data has analyzed using Pearson's correlation coefficient and multiple regression on SPSS.Table-2 Results of Pearson's correlation coefficient for SRLS and IC in total and Scales and components wise with reference to B.Sc Degree Students in the combinations of PMCs, PCM and CBZ Total IC Information search Information Management General Webpage Using Communication collaboration Computer General Ability Computer General Knowledge R value and P value Component of IC Strategies of SRL .099 .093 .070 .084 .061 .103 .108 R V Organization .117 .138 .269 .182 .337 .101 .086 P V .145* .119 .120 .129* .092 .150* .157* R V Metacognative self-regulated .020 .058 .056 .040 .146 .017 .012 P V .043 .028 .020 .025 .017 .050 .065 R V Peer Learning .500 .660 .751 .690 .793 .425 .305 P V -.018 -.014 -.020 -.012 -.010 -.036 -.003 R V Time and Study Environment .776 .830 .747 .851 .880 .566 .966 P V -.043 -.042 .003 -.064 -.017 -.056 -.046 R V Effort Regulation .499 .505 .964 .311 .788 .378 .464 P V .223** .200** .209** .235** .170** .203** .205** R V Critical Thinking .000 .001 .001 .000 .006 .001 .001 P V .151* .113 .133* .115 .099 .156* .168** R V Rehearsal .016 .072 .034 .066 .116 .013 .007 P V .071 .080 .133* .085 .087 .030 .029 R V Help Seeking .258 .202 .034 .178 .166 .633 .642 P V .176** .180** .177** .158* .129* .156* .167** R V Elaboration .005 .004 .005 .012 .040 .013 .008 P V .141* .126* .135* .127* .102 .129* .143* R V Total SRLS .025 .045 .032 .042 .106 .040 .022 P V **p0.01 *p0.05 Research Journal of Recent Sciences ______________________________________________________________ ISSN 2277-2502Vol. 3(8), 8-15, August (2014) Res. J. Recent Sci. International Science Congress Association 12 Results and Discussion Table No. 2 shows that the finding of Pearson's correlation coefficient and it presents that: In total there is significant positive relationship between SRLS with IC (r=0.141, p0.05) of B.Sc Degree students in the different combination of subjects (PMCs, PCM and CBZ). There is significant positive relationship between Metacognative self-regulated with computer general knowledge (r=0.157, p0.05), metacognative self-regulated with computer general ability (r=0.150, p0.05), metacognative self-regulated with general webpage using (r=0.129, p0.05), metacognative self-regulated with total IC (r=0.145, p0.05) in the B.Sc Degree Students in the different combination of subjects: PMCs, PCM and CBZ. There is significant positive relationship between critical Thinking with Computer General Knowledge(r=0.205, p0.01), Critical Thinking with Computer General Ability(r=0.203, p0.01), Critical Thinking with Communication and Collaboration (r=0.170, p0.01), Critical Thinking with General Webpage Using (r=0.235, p0.01), Critical Thinking with Information Management (r=0.209, p0.01), Critical Thinking with Information Search (r=0.200, p0.01), Critical Thinking with total IC (r=0.223, p0.01) of B.Sc Degree Students in the different combination of subjects-PMCs, PCM and CBZ. There is significant positive relationship between Rehearsal with Computer General Knowledge (r=0.168, p0.01), Rehearsal with Computer General Ability (r=0.156, p0.05), Rehearsal with Information Search (r=0.133, p0.05), Rehearsal with total IC(r=0.151, p0.05). There is significant positive relationship between Help Seeking with Information Management(r=0.133, p0.05) of B.Sc Degree Students in the different combination of subjects- PMCs, PCM and CBZ. There is significant positive relationship between Elaboration with computer general knowledge(r=0.167, p0.01), elaboration with computer general ability(r=0.156, p0.05), elaboration with communication collaboration(r=0.129, p0.05), elaboration with general webpage using(r=0.158, p0.05), elaboration with information management(r=0.177, p0.01), elaboration with information search(r=0.180, p0.01), elaboration with total IC(r=0.176, p0.01) of B.Sc Degree Students in the different combination of subjects- PMCs, PCM and CBZ. There is significant positive relationship between SRLS in total with computer general knowledge(r=0.143, p0.05), SRLS in total with computer general ability (r=0.129, p0.05), SRLS in total with general webpage using(r=0.127, p0.05), SRLS in total with information management(r=0.135, p0.05), SRLS in total with information search (r=0.126, p0.05) of B.Sc Degree Students in the different combination of subjects- PMCs, PCM and CBZ. The multiple regression has used to assess the multiple coefficient of correlation between srls and ic of students. so the variables such as metacognitive self regulation, organization, peer learning, effort regulation, time and study environment, critical thinking, help seeking, rehearsal and elaboration as predictors and IC as a criterion variable were entered into the regression equation with the Enter method. The multiple coefficients of correlation among the variables were 0.30 which explains 9% of variance of average marks (R=0.09). Further table 3 shows that the model is significant (F=2.72, P0.01).Table-3 Regression of academic achievement on IC (model summary and ANOVA) Model r r square Adjusted r square df f value p value One .30 .09 .06 9, 244 2.72 .005** Table-4 Regression coefficient of IC among the students Predictors Standardized Coefficients T P value Beta (Constant) 6.17 .000 Organization -.03 .37 .708 Metacognative self-regulation .03 .33 .743 Peer learning -.18 2.16 .032* Time study environment -.11 1.58 .116 Effort Regulation -.10 1.57 .119 Critical Thinking .22 2.41 .017* Rehearsal .12 1.33 .183 Help Seeking -.02 .21 .836 Elaboration .14 1.33 .185 Research Journal of Recent Sciences ______________________________________________________________ ISSN 2277-2502Vol. 3(8), 8-15, August (2014) Res. J. Recent Sci. International Science Congress Association 13 Table 4 shows that among the scales of learning strategy, peer learning (Beta= -0.18, t=2.16, p0.05) and critical thinking (Beta= 0.22, t=2.41, p0.05) were the best predictor of IC for students. Further among the organization (Beta= -0.03, t=0.37, p&#x-3.3;ĺ ¦0.05), meta-cognitive self-regulation (Beta= 0.03, t=0.33, p&#x-3.3;ĺ ¦0.05), time and study environment (Beta= -0.11, t=1.58, p&#x-3.3;ĺ ¦0.05), effort regulation (Beta= -0.10, t=1.57, p&#x-3.3;ĺ ¦0.05), Rehearsal (Beta= 0.12, t=1.33, p&#x-3.3;ĺ ¦0.05), help seeking (Beta= -0.02, t=0.21, p&#x-3.3;ĺ ¦0.05) and elaboration (Beta= 0.14, t=1.33, p&#x-3.3;ĺ ¦0.05) were not the predictor of IC for students. Discussion: In this study results showed: i. SRLS and the levelof IC of B.Sc Degree students in the different combination of subjects- PMCs, PCM and CBZ are positively related to each other. ii. Metacognative self-regulation strategy is positively related to general webpage using, computer general ability, computer general knowledge, and total IC of B.Sc Degree students in the different combination of subjects- PMCs, PCM and CBZ. iii. There is significant positive relationship between Critical Thinking and all the components of IC (general webpage using, computer general ability, computer general knowledge, information management, communication and collaboration, information search) and total IC of B.Sc Degree Students in the different combination of subjects- PMCs, PCM and CBZ. iv. There is significant positive relationship between Rehearsal Strategy and Information search, computer general ability, computer general knowledge and total IC of B.Sc Degree Students in the different combination of subjects- PMCs, PCM and CBZ. v. Help seeking strategy is positively related to information management of B.Sc degree students in the different combination of subjects PMCs, PCM and CBZ. vi. There is significant positive relationship between Elaboration Strategy and whole the components of IC- computer general ability, computer general knowledge, general webpage using, information search, communication and collaboration, information management and total IC of B.Sc Degree students in the different combination of subjects- PMCs, PCM and CBZ. vii. There is significant positive relationship between SRLS in total and all the components of IC (except Communication and Collaboration), Information search, computer general ability, computer general knowledge, information management, general webpage using and total IC of B.Sc Degree students in the different combination of subjects- PMCs, PCM and CBZ. viii. There is no relationship between other scales of SRLS and components of IC of B.Sc Degree students in the different combination of subjects- PMCs, PCM and CBZ. ix. Further result shows that between the scales of learning strategy (Peer learning and critical thinking) was the best predictor of IC for students. However between the other variables of learning Strategies were not the predictor of IC for students. Few studies exist are available in the subject, only three findings gained in the current study are partially in accordance with studies done prior. Yangkim13 revealed that there were fewer correlations between self regulation and academic achievement and Self Regulation and Internet usage. Total Internet access was highly correlated to non academic related Internet browsing. Stromse and Bréten17 indicated that Self regulatory Strategies, especially students that have emphasized that course-related knowledge situated on the Internet consisted of specific facts and details perceived Internet Search and valuation of search outcomes to be less problematic and statement on more Help Seeking and usage of Self Regulatory Strategies during Internet based learning. Hargis also viewed that understanding the interaction between the students' learning Strategies, and motivation and technology can provide insight into helping students improve academic achievement. There is a need to extend coaches related to database search skills such as searching specific interfaces, navigating the database and so on, and Internet skills such as communication on the Internet, web browser navigation, web search methods, web search instrument, valuation of web resources, gateways and using subject based portals and so on. Students might not meet their academic goals if Internet browsing is not focused and efficient. One's regulation in learning can also apply to Internet use in order for students to be successful in academic fields. Unfocused Internet browsing might be unregulated Internet use which comes from deficiency of one's regulation. Students who use the Internet efficiently and properly are self regulated Internet users. Self regulation should be taught in conjunction with an academic matter and not individually. Students benefit from seeing how they can use what they learn. Many self regulation methods are general and can be applied to various content but their implementation usually will vary depending on the content area. Thus one's monitoring is a general Strategy but what students one's monitor will vary depending whether they are reading means of access in text, writing compositions or solving difficulties in geometry. When general Strategies are taught it is important also to show students how the method can be adapted for use with other content. The colleges should have an individual and more financial support and the other measurable support for an information literacy agenda. Teachers in different combination of subject- PMCs, PCM and CBZ should emphasize and encourage students to use various techniques and methods of SRLS for betterment of their academic performance. Also different types of colleges have taken initiative to prepared facilities for students and encourage them to extend IC for the betterment of their academic performance. Conclusion To educate and prepare the new generation to work in the 21stcentury and to be able to face the challenges of the future, we require undertaking research into the scheming of classroom activities making use of Internet information skills to learn discipline specific knowledge. This matter and one's- directed, Research Journal of Recent Sciences ______________________________________________________________ ISSN 2277-2502Vol. 3(8), 8-15, August (2014) Res. J. Recent Sci. International Science Congress Association 14 occupied learning using the Internet will be the focus for research in differentiated education and Internet information literacy. The Internet is used for instruction and learning in classrooms. Although, there are problems with use Internet such as Internet addiction or unregulated Internet use14. When students use the Internet academically or non academically, both can influence their learning positively or negatively. School learning usually is based on academic content. SRL skills do not develop automatically, but these skills will fruitful students for lifelong learning. Hence, it behooves teachers and parents to help students develop their one's regulatory competencies and encourage them to practice using them whole facets of their lives. Students should be taught how to examine their learning progress and have given opportunities to do so. Usually in school, learners have their learning valuated for them by teachers. But self regulation is a cyclical procedure in which learners one's regulate, check their progress, and adjust their approach as needed. Students need opportunities for one's valuation due to they may not do it automatically and it affects their motivation and SRL. According to the findings of this study it can be concluded that students with higher Self-Regulated Learning Strategies, tend to be more Internet Competency. Consequently students with lower Self-Regulated Learning Strategies will be equipped with less Internet Competencies. One can also say Critical thinking and peer learning strategies are good predictors of Internet competencies. The results of present study can be used for lecture, educators, teachers and managers in Universities and Educational Institutions, particularly Open Universities, Distance Education and Virtual Education in prediction and curriculum and instructional planning. 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