Keywords

Social Networking, Influence, Performance, Study Habits

Introduction

Internet technologies have, for the past few decades, significantly altered the way individuals both in and out of colleges work, play, and interact and even now, Internet communication is emergent; as the speed of the Internet increases, so too does the number of tools that utilize this still-growing technology [1] . Horrigan [2] noted that the Internet has become a primary vehicle for many individuals’ day-to-day activities, with the advent and historic growth of technologies such as electronic mail (e-mail), instant messaging, online newspapers, eBooks, research databases, Weblogs, eCommerce, and social networking sites and it is an increasing rarity for an individual in the US to go even a day without some sort of interaction using an Internet technology. Madden [3] explained that internet-based technology that holds promise for screening in this important population is social networking and more than 80% of adults aged 18 to 29 visit social networking sites such as Facebook. The utilization of Facebook has been found to increase users’ sense of personal belonging among college students and also, this sense of belonging has in and of itself been positively correlated with academic performance [4]. Social Networking Site (SNS) covers all about engagement creating relationships, communicating with one’s readers, building his following and connecting with his online audience. It has been observed as the practice of expanding the number of one’s business and/or social contacts by making connections through individuals. Livingstone [5] stated that affinity for self-presentation is often a mark of adolescence, and SNS use has made it possible for one’s own display of personality to reach a larger audience than previous generations. However, there are some overlap and integration with social media and social networking. Social media experts say that Facebook, Twitter and Pinterest are whole package platforms — and are considered both social media (tools) and social networking (a way to engage). You Tube, on the other hand, is a tool for video, so it’s social media. Chatting with other colleagues on LinkedIn? That’s social networking. Both work together for one’s overall social media strategy. Hughes [6] defines social media as a collection of Internet websites, services, and practices that support collaboration, community building, participation, and sharing, these technologies have attracted the interest of higher education faculty members looking for ways to engage and motivate their students to be more active learners. Similarly, there has been interest in integrating various social media tools (such as blogs, microblogs, videosharing sites, and social networking) into the learning process [7], especially by faculty members with a disposition towards the use of newer technology in education [8]. Junco, Merson and Salter [9] discusses the excessive use of social media tools by college students has led to debate over whether or not it has changed the very shape and structure of students’ social behavior and academic practices, and has thus caused leading educators to redefine their understanding of interpersonal communication and study dynamics. According to Wang, Chen and Liang [10] students use social media tools for many purposes such as access to information, group discussion, resource sharing and entertainment. On the contrary, Gross and Acquisti [11] argue that users may be putting themselves at risk both offline (e.g., stalking) and online (e.g., identify theft). In this study, social networking and social media are used interchangeably. Social networking has only one goal. It is to encourage new ways to communicate and share information. Observations showed, however, that many students have been blaming various social networking for it affects adversely their study habits and the steady decrease in their grade point averages. This emergent phenomenon has aroused the researcher to look into social networking and why it affects the study habits of students. The System’s theory input-output model developed by Ludwig Von Bertalanffy, according to Koontz and Weihrich [12], postulates that an organized enterprise does not exist in a vacuum; it is dependent on its environment in which it is established. They add that the inputs from the environment are received by the organization, which then transforms them into outputs. As adapted in this study, the students (Inputs) from different social economic backgrounds and are from various school backgrounds, and how the social networking affects the output which is the study habits and can be seen through their academic performance. Study habits, are learning tendencies that enable students to work privately. Azikiwe [13] describes that good study habits are good asset to learners because they assist students to attain mastery on areas of specialization for a consequent academic performance. However, Devine [14] asserted that researchers have not found any one study strategy or skill that is best for all students in all learning tasks. There are many useful strategies or skill, and the ones that a particular individual uses will depend on the individual and the learning situations. According to Hay [15], the more time spent on social networking sites, the less they may be good for students’ social lives, in the way that it may cause them to be more illiterate; short forms, and even the limited amount of characters one is allowed to type on certain statuses, don’t help expand the writing portion of a student’s mind resulting in lower grade averages and less time spent on studies. However, the positive is also that an ‚interactive world‛ full of ideas and insight and opinions can act as an aid for school work in the sense that students have a wide range of people’s information, knowledge, and experience to learn from and to report on. In this study, study habits is one of the variables upon which the researchers believed may have been affected by social networking, either good or bad. Academic performance, on the other hand, is not a concept that is new, many social scientists and researchers alike have defined academic performance in various ways. Tuckman [16] rightly put it that performance is the apparent demonstration of understanding, concepts, ideas and knowledge of a person and proposed that grades clearly depict the performance of a student. Thus, their academic performance must be managed efficiently keeping in mind all the factors that can positively or negatively affect their educational performance. Banquil [17] states that a student is generally judged on examination performance. Performance, therefore, is the application of a learning product that at the end of the process provides mastery. It is the acquisition of particular grades on examinations that indicates candidates’ ability, mastery of the content, skills in applying learned knowledge to particular situations. A student’s success is generally judged on examination performance. Success on examinations is a crucial indicator that a student has benefited from a course of study [18]. According to Vaughn [19], student users are affected by the internet and this impact is determined by the type of internet usage. They are positively or negatively affected by the informative use of internet while having drastic impact of recreational use of internet on them. Also, Flad [20] asserted that internet is advantageous to both students and teachers if used as a tool of knowledge creation and dissemination. As another variable for this study, the researchers also believed that there may be impact of social networking that can be put at forefront especially when respondents were classified as to age, sex, socio-economic status and educational attainment of parents. Social networking evidently has a lot of positive effects, but there are also some negative impacts. Interesting relevant information on the impact of social networking or social media on the study habits and academic performance of tertiary students at the West Visayas State University System would be put to fore. Credible evidences that would solidify the support on controlling the activities of social networking and reducing the risk of assimilating such addicting activities and damaging impacts would also be highlighted; hence, this study. This study aimed to describe how social networking influenced the study habits and academic performance of the Bachelor of Science in Information Technology graduating students of the West Visayas State University System. Specifically, it also sought answers to: Extent of utilization of social networking by the students as an entire group and as to their age, sex, socio economic status, and educational attainment of their parents; status of study habits of the students as an entire group and as to their age, sex, socio economic status, and educational attainment of their parents; level of academic performance of the students as an entire group and as to their age, sex, socio economic status, and educational attainment of their parents; if significant differences exist in the extent of utilization of social networking of students as an entire group and when classified as to age, sex, socio economic status, and educational attainment of their parents; if significant differences exist in the status of study habit of the students as to their age, sex, socio economic status, and educational attainment of their parents; if significant differences exist in the level of academic performance of the students as to their age, sex, socio economic status, and educational attainment of their parents; if significant relationship exists between the extent of influence of social networking and the status of study habit of students; if significant relationship exists between the extent of influence of social networking and the level of academic performance of students; and if significant relationship exists between the status of study habit and the level of academic performance of students.

Materials and Methods

Conducted among the 235 (100%) graduating students enrolled in the Bachelor of Science in Information Technology (BS InfoTech) program of West Visayas State University System for school year 2012 – 2013, this study aimed to ascertain the extent of influence of social networking on the respondents’ status of study habits and level of academic performance. This study utilized the descriptive-correlational type of research. According to Gay [21], the descriptive method of research involves collecting data to answer questions concerning the current status of the subject under study. Correlation studies, on the other hand, determine whether or not two variables are correlated. This means to study whether an increase or decrease in one variable corresponds to an increase or decrease in the other variable. This study involved collecting data to be used in determining whether, and to what degree relationship exists among the given variables. The independent variables were the respondents’ age, sex, socio economic status, and educational attainment of their parents. The moderator variable was the influence of social networking and the dependent variables were the status of study habits and the level of academic performance of the respondents. Employed statistics were means and standard deviations, ttest, ANOVA, and Pearson’s r Correlation. Statistical level for all inferential tests was set at .05 alpha. All statistical computations were processed through the Statistical Package for the Social Sciences (SPSS) software. The respondents were classified as to age, sex, socio economic status, and educational attainment of their parents. As to age, the respondents were classified as to young (20 years old below) and old (above 20 years old). As to sex, they were classified as to male and female. As to socio economic status, they were classified as to low, average, and high. As to educational attainment of their parents, they were classified as to elementary, high school, and college. To gather data from the respondents such as age, sex, socio economic status and educational attainment of their parents, a personal data sheet was attached to the questionnaire checklists. To determine the academic performance of the respondents, the Terminal Competencies Assessment (TCA) results were used. TCA is divided in to two parts: general competencies and the specialized knowledge. The general competencies include: Critical Thinking, Historical Perspective, Civic Responsibility, Technological Facility, Research Competence, Scientific Literacy, Information Literacy, and Effective Communications. The specialized knowledge covers disciplinary knowledge and skills in line with the respondents’ area of specialization. Study habit component skills included were homework and assignment, time allocation, reading and note-taking, study period procedure, concentration, written work, examination, teacher consultation.

The researcher-made and duly validated questionnaire checklists were used to obtain the data on the influence of social networking and study habits of students. A five-point scale was used with the following weights and descriptions to the responses: 1—never, 2- seldom, 3- sometimes, 4- often, and 5- always. The instrument was validated by experts in research of the University. The instruments were pilot tested by the proponents. Split-half method was used to determine the reliability of the data gathering instruments. The data obtained from the study were subjected to descriptive and inferential statistical tools. Means and standard deviations were used to determine the influence of social networking, the status of study habits, and the level of students’ academic performance. To determine the extent of influence of social networking and the status of study habits, this scale and its descriptions were used: 4.21-5.00 – Very Highly Influenced; 3.41- 4.20 – Highly Influenced; 2.61-3.40 – Moderately Influenced; 1.81-2.60 – Fairly Influenced; 1.00-1.80 – Not Influenced. To determine the level of academic performance, this scale and its descriptions were used: 65-75 – Advanced; 54-64 – Very proficient; 43-53 – Proficient; 32-42 – Basic; 21-31 – Novice. To determine the socio-economic status, this scale and its descriptions were used: Php 8, 801.00–above – High; Php 4, 701.00-Php 18,000.00 – Average; Php 4, 700.00-below – Low. Table I shows the distribution of respondents when grouped as to age, sex, socio-economic status and educational attainment of parents. The total number of respondents was 235 or 100% of the total population. Out of 235 respondents, as to age, 140 (60%) were young and 95 (40%) were old; as to sex, 85 (36%) were males and 150 (64%) were females; as to socio-economic status, 130 (55%) were low, 68 (29%) were average and 37 (16%) were high; as to mother’s educational attainment, 46 (19%) finished elementary; 89 (38%), finished high school; and 100 (43%) finished college; and as to father’s educational attainment, 17 (7%) finished elementary; 108 (46%) finished high school; and 110 (47%) finished college.

Table 1

Distribution of Respondents

Category N %
Entire group 235 100
Age Young (20 years old and below) 140 60
Old (above 21 years old) 95 40
Sex Male 85 36
Female 64
Socio Economic Status Low 130 55
Average 68 29
High 37 16
Educational Attainment Mother Elementary 46 19
High School 89 38
College 100 43
Father Elementary 17 7
High School 108 4
College 110 47

Results and Discussions

As to the descriptive and inferential findings of this study, Table 2 shows that as an entire group, social networking highly influenced the respondents (M=3.43, SD=.64). The extent of influence of social networking among the students covered the use of social networks for their social life, entertainment and educational reasons.

Table 2

Extent of Influence of Social Networking among the Respondents

Category N Mean SD Description
Entire group 235 3.43 64 Highly Influenced
Young (20 years old and below) 140 3.43 64 Highly Influenced
Old (above 21 years old) 95 3.43 60 Highly Influenced
Sex Male 85 3.54 66 Highly Influenced
Female 150 3.37 65 Highly Influenced
Socio Economic Status Low 130 3.33 .57 Highly Influenced
Average 68 3.47 .67 Highly Influenced
High 37 3.71 .43 Highly Influenced
Educational Attainment Mother Elementary 46 3.44 62 Highly Influenced
High School 89 3.28 67 Highly Influenced
College 100 3.57 73 Highly Influenced
Father Elementary 17 3.32 62 Highly Influenced
High School 108 3.35 60 Highly Influenced
College 110 3.56 60 Highly Influenced

Legend: 4.21-5.00 – Very Highly Influenced; 3.41- 4.20 – Highly Influenced; 2.61-3.40 – Moderately Influenced; 1.81-2.60 – Fairly Influenced; 1.00-1.80 – Not InfluencedWhen they were classified as to age, social networking highly influenced the young (M=3.43, SD=.64) and the old (M=3.43, SD=.65). Likewise, as to sex, social networking highly influenced the male (M=3.54, SD=.60) and the female (M=3.37, SD=.66). When the respondents were grouped as to socio-economic status, social networking highly influenced those with low income (M=3.35, SD=.65), those with average income (M=3.47, SD=.57) and those with high income (M=3.71, SD=.67). When they were classified as to educational attainment of parents, social networking highly influenced those whose mothers finished elementary (M=3.44, SD=.43), high school (M=3.28, SD=.62) and college (M=3.57, SD=.67). Similarly, those whose fathers finished elementary (M=3.32, SD=.72), high school (M=3.35, SD=.62) and college (M=3.56, SD=.60). The SDs obtained showed the narrow dispersion of the means for each group, revealing the homogeneity of the respondents concerned in relation to the general influence of social networking on their study habits and academic performance. These results proved that the respondents’ study habits and academic performance were to a high extent influenced by social networking. Most likely that this high influence may have been result of easy access to and brought about by the availability of gadgets at hand like cell phones, desktops, laptops with mobile data and Wi-Fi connection. The affordability of these gadgets in the market may have been another reason. Table 3 reveals that as entire group, the respondents had high status of study habits (M=3.82, SD=.63). The study habit component skills upon which the researchers based the respondents’ status of study habits included homework and assignment, time allocation, reading and note-taking,

study period procedure, concentration, written work, examination, and teacher consultation.

Table 3

Status of Study Habit of the Respondents

Category N Mean SD Description
High
Entire group 235 3.82 .63
Age Young (20 years old and below) 140 3.73 .63 High
Old (above 21 years old) 95 3.96 .62 High
Sex Male 85 3.81 .65 High
Female 150 3.83 .62 High
Socio Economic Status Low 130 3.87 .60 High
Average 68 3.84 .56 High
High 37 3.61 .80 High
Educational Attainment Mother Elementary 46 3.43 .43 High
High School 89 3.28 62 High
College 100 3.57 67 High
Father Elementary 17 3.32 .73 High
High School 108 3.35 .62 High
College 110 3.56 .60

Legend: 4.21-5.00 – Very High; 3.41- 4.20 – High; 2.61-3.40 – Moderate; 1.81-2.60 – Fair; 1.00-1.80 – Poor

When they were classified as to age, the respondents yielded high status for both the young (M=3.73, SD=.63) and the old (M=3.96, SD=.62). Likewise, as to sex, they showed high status for both male (M=3.81, SD=.65) and female (M=3.83, SD=.62). When the respondents were grouped as to socio-economic status, they showed high status for all those with low income (M=3.87, SD=.60), those with average income (M=3.84, SD=.56) and those with high income (M=3.61, SD=.80). When they were classified as to educational attainment of parents, the respondents yielded high status for all those whose mothers finished elementary (M=3.44, SD=.43), high school (M=3.28, SD=.62) and college (M=3.57, SD=.67). Also, those whose fathers who finished elementary (M=3.32, SD=.72), high school (M=3.35, SD=.62) and college (M=3.56, SD=.60). The SDs obtained showed the narrow dispersion of the means for each group, revealing the homogeneity of the respondents concerned in relation to the status of their study habits. The overall results disclosed a high status among respondents’ study habits. The revealed high status may have been brought about by their academic struggles, perseverance to pass their subjects with high grades, ability to adapt to academic demands and pressures, systematic study schedules, and the like. Most likely that they have relevant study practices as well as influences of peer groups and others as regards how to balance and focus on their studies. Table 4 shows that as entire group, the respondents had basic level of academic performance (M=35.17, SD=6.09). When they were classified as to age, the respondents yielded basic level of academic performance for both the young (M=36.55, SD=6.55) and the old (M=33.04, SD=4.60). Likewise, as to sex, they showed basic level of academic performance for both male (M=36.15, SD=6.55) and female (M=34.59, SD=5.75). When the respondents were grouped as to socio-economic status, they showed basic level of academic performance for all those with low income (M=34.36, SD=5.73), those with average income (M=35.04, SD=.5.30) and those with high income (M=38.13, SD=7.67). When they were classified as to educational attainment of parents, the respondents yielded basic level of academic performance for all those whose mothers finished elementary (M=34.00, SD=5.22), high school (M=33.69, SD=5.15) and college (M=36.74, SD=6.66). Also, those whose fathers who finished elementary (M=34.64, SD=7.30),

high school (M=33.89, SD=5.33) and college (M=36.54, SD=5.89). The SDs obtained showed the narrow dispersion of the means for each group, revealing the homogeneity of the respondents concerned in relation to the level of their academic performance. The general competencies covered in the terminal assessment test administered to the respondents like critical thinking, historical perspective, civic responsibility, technological facility, research competence, scientific literacy, information literacy, and effective communications yielded overall results of a basic level of academic performance among the respondents, showing a very modest accomplishment. These turn out may have been brought about by personal factors, lack of review or to the extent, weak teaching-learning procedures. Most likely, though it’s a specialized learning that covered disciplinary knowledge and skills in line with the respondents’ area of specialization, there may be lack of experiential learning, practice and more practice.

Table 4

level of academic performance of the respondents

Category N Mean SD Description
Entire group 235 35.17 6.09 Basic
Age Young (20 years old and below) 140 36.55 6.55 Basic
Old (above 21 years old) 95 33.04 4.60 Basic
Sex Male 85 36.15 6.55 Basic
Female 150 34.59 5.75 Basic
Socio Economic Status Low 130 34.36 5.73 Basic
Average 68 35.04 5.30 Basic
High 37 38.13 7.67 Basic
Educational Attainment Mother Elementary 46 34.00 5.22 Basic
High School 89 33.69 5.15 Basic
College 100 36.74 6.66 Basic
Father Elementary 17 34.64 7.30 Basic
High School 108 33.89 5.33 Basic
College 110 36.54 5.89 Basic

Legend: 65-75 – Advanced; 54-64 – Very proficient; 43-53 – Proficient; 32-42 – Basic; 21-31 – Novice

t-test and ANOVA results on Table 5 revealed that there were no significant differences on the extent of influence of social networking on the respondents as to their age (t = .02, p = .98), sex (t = 1.94; p = .05) and educational attainment of father (F=.40, p = .26). Social networking has been and will be a worldwide trend, and the clientele regardless of age, young or old, are captive users. Sex, represented by male and female, may be an interesting and important variable, yet in this study may not be significant at all. This may be due to the mental and emotional interests of both sexes on using social networking. Both have been observed to be sociable people living in a sociable society. As to their everyday activities and decisions, they may resort to such occupational hobby or serious business of social networking and no sex is an exception. Most likely that they’re both strongly exposed to social media as their springboard for social networking. Regardless of their father’s educational attainment, the respondents took personally their interests and perhaps developed attachment on social networking through the use of available gadgets at hand. On the other hand, ANOVA results showed significant differences existed when the respondents were classified as to socio economic status (F=.40, p=.01) and educational attainment of mother (F=.40, p=.003). It is well noted that the higher the socio economic status, the better opportunity for anyone to avail gadgets like cell phones,

laptops and the like and can change them with more hightech ones at one’s disposal. Social networking may have a better impact to those who can afford the technology. Likewise, the respondents, when classified as to educational attainment of mother, also showed a significant difference as to social networking’s influence. This may be due to the closeness and the impact of mothers to their kids. The higher the education of the mother, the higher the possibility that she has influenced how her kids would prefer to be socially active and be adept with social networking.

Table 5

Differences in the Extent of Influence of Social Networking on the Respondents

Category Mean df t-value 2-tailed Probability Statistical Decision
Age Young (20 years old and below) 36.55 233 .02 .98 Not Significant
Old (above 21 years old) 33.04
Sex Male 36.15 232 1.94 .05 Not Significant
Female 34.59
Category Mean df mean-Square 2-tailed Probability Statistical Decision
Socio Economic Status Low 34.36 Significant
Average 35.04 232 .40 .01
High 38.13
Educational Attainment Mother Elementary 34.00 232 .40 .003 Significant
High School 33.69
College 36.74
Father Elementary 34.64 232 .40
High School 33.89 .26 Not Significant
College 36.54

P, <.05

t-test and ANOVA results on Table 6 revealed that there was a significant difference on the status of study habits of the respondents when classified as to their age (t =-2.66, p = .01). It may be posited that age is a factor on how one prioritizes his studies. Getting aged perhaps creates a better perspective and system on how one can manage his time schedule and activities, be it in the classroom or in personal life; most likely, with the respondents of this study. When they were classified as to sex (t=-.16, p = .87), socio economic status (F=.39, p = .08) and educational attainment of parents: mother (F=.40; p= .18), father (F=.40, p=.07), there were no significant differences on the status of study habits of the respondents. Irrespective of these variables, the students’ study habits may have been a result of the stringent instructional activities afforded by their teachers and their institution; that their academic demand and pressure may have drove them to study, set time schedules and religiously follow these schedules.

Table 6

Differences in the Status of Study Habits of the Respondents

Category Mean df t-value 2-tailed Probability Statistical Decision
Age Young (20 years old and below) 36.55 233 -2.66 .01 Significant
Old (above 21 years old) 33.04
Sex Male 36.15 232 -.16 .87 Not Significant
Female 34.59
Category Mean df mean-Square 2-tailed Probability Statistical Decision
Socio Economic Status Low 34.36
Average 35.04 232 39 08 Not Significant
Educational Attainment Mother Elementary 34.00 232 .40 .18 Not Significant
High School 33.69
College 36.74
Father Elementary 34.64 232 .40 .07 Not Significant
High School 33.89
College 36.54

P, <.05

respondents’ imbibing both as part of their system, where one exists so with the other. While it was found out that no significant relationship existed between the status of the study habits and level of academic performance of the respondents as revealed by Pearson’s r of -117 and two-tailed probability of .07 which was greater than the set of 0.05 level of significance. No significant correlation was noted because both variables may not have much of impact to the respondents’ daily instructional activities. They may have become vital components in their studies of information technology but not much relationship significance has been identified. JSSHR 22|Volume 1|Issue 1|2015 11 Table 8: Relationship between the Extent of Influence of Social Networking and Status of CONCLUSIONS The extent of influence of social networking on students as an entire group and regardless of age, sex, socio economic status, and educational attainment of their parents was high. It also proved that the respondents’ study habits and academic performance were to a high extent influenced by social networking. Most likely that this high influence may have been result of easy access to and brought about by the accessibility of gadgets like cell phones with mobile data and Wi-Fi connection. The affordability and availability of these gadgets in the market may have been another reason. Likewise, this implies that students may have not realized that spending more time in social networking could be a hindrance to a good academic performance. In fact they have more important things to do like school works and studying their lessons. The status of study habits of students as an entire group and regardless of age, sex, socio economic status, and educational attainment of their parents was high. This means that students may have established certain habits in accordance to their needs and have their aspirations and purpose of utilizing social networking in improving their academic performance. The level of academic performance of students as an entire group and regardless of age, sex, socio economic status, and educational attainment of their parents was basic. The findings mean that being active in social networking could affect students socially, emotionally and academically. This may mean that social networking could highly influence study habits and academic performance of students negatively. Being involved in social networking can influence the students not to give importance to their academic subjects. Students should utilize certain time for researching or advance study aside from social networking. Students would have certain restrictions on how will they use and view the pages of social networking sites. For example, if they have spare time or they are on the time of net researching they could visit their educational social networking sites. Students should evaluate themselves; assess their aspirations in looking for friends. They should not always seek attention, instead try to confide themselves with those people who appreciate them. It is suggested that parents should get appropriate guidance and counselling about dealing on how to develop good study habits for the educational development of their children. Healthy and sympathetic teacher-student relationship should be initiated to upgrade the level of academic self-esteem of students. Self-study should be encouraged and emphasized. The teachers should ask the Category Pearson’s r 2-tailed Probability Statistical Decision Social Networking Study Habit .36 .00 Significant Social Networking Academic Perform

Table 7

Differences in the Level of Academic Performance of the Respondents

Category Mean df t-value 2-tailed Probability Statistical Decision
Age Young (20 years old and below) 36.55 233 4.50 .00 Significant
Old (above 21 years old) 33.04
Sex Male 36.15 232 1.84 .07 Not Significant
Female 34.59
Category Mean df mean-Square 2-tailed Probability Statistical Decision
Socio Economic Status Low 34.36 232 Significant
Average 35.04 35.61 .003
High 38.13
Educational Attainment Mother Elementary 34.00 232 35.12 .001 Significant
High School 33.69
College 36.74
Father Elementary 34.64 232 35.93 .009 Significant
College 36.54

Table 8

Relationship between the Extent of Influence of Social Networking and Status of

Category Pearson’s r 2-tailed Probability Statistical Decision
Social Networking Study Habit .36 00 Significant
Social Networking Academic Performance .13 .04 Significant
Study Habit Academic Performance -117 .07 Not Significant

Conclusions

The extent of influence of social networking on students as an entire group and regardless of age, sex, socio economic status, and educational attainment of their parents was high. It also proved that the respondents’ study habits and academic performance were to a high extent influenced by social networking. Most likely that this high influence may have been result of easy access to and brought about by the accessibility of gadgets like cell phones with mobile data and Wi-Fi connection. The affordability and availability of these gadgets in the market may have been another reason. Likewise, this implies that students may have not realized that spending more time in social networking could be a hindrance to a good academic performance. In fact they have more important things to do like school works and studying their lessons. The status of study habits of students as an entire group and regardless of age, sex, socio economic status, and educational attainment of their parents was high. This means that students may have established certain habits in accordance to their needs and have their aspirations and purpose of utilizing social networking in improving their academic performance. The level of academic performance of students as an entire group and regardless of age, sex, socio economic status, and educational attainment of their parents was basic. The findings mean that being active in social networking could affect students socially, emotionally and academically. This may mean that social networking could highly influence study habits and academic performance of students negatively. Being involved in social networking can influence the students not to give importance to their academic subjects. Students should utilize certain time for researching or advance study aside from social networking. Students would have certain restrictions on how will they use and view the pages of social networking sites. For example, if they have spare time or they are on the time of net researching they could visit their educational social networking sites. Students should evaluate themselves; assess their aspirations in looking for friends. They should not always seek attention, instead try to confide themselves with those people who appreciate them. It is suggested that parents should get appropriate guidance and counselling about dealing on how to develop good study habits for the educational development of their children. Healthy and sympathetic teacher-student relationship should be initiated to upgrade the level of academic self-esteem of students. Self-study should be encouraged and emphasized. The teachers should ask the students to keep the record of their progress towards their set goals. Academic heads must enforce academic advising among their teachers. Provisions on compulsory academic counselling for underachievers must be imposed and may consider giving more remedial actions to improve student’s learning. In closure, the present study may be replicated to further investigate how this learning environment that integrates the proposed framework for confluent academic interventions affects students’ study habits and learning behavior and enhances students’ educational development.