THE IMPACT OF INTERNET ON SOCIAL ANXIETY

AND LEARNING ADAPTABILITY FOR YOUNG ADULT

INTERNET USERS

Hui-Jen Yang

, Yun-Long Lay

, Wen-Yu Tsao

and Justin S. Lay

Department of Information Management, National Chin-Yi University of Technology, Taiping City, Taiwan

Department of Electronic Engineering, National Chin-Yi University of Technology, Taiping City, Taiwan

Department of Computer Science and Information Engineering, Tunghai University, Taiwan

Keywords: Social anxiety; Self-efficacy; Achievement expectancy, Career awareness, Learning adaptability.

Abstract: This research is to explore the factors affecting the social anxiety and learning adaptability for young adult

Internet users. Results found that achievement expectancy, network self-efficacy, network usage rate and

career awareness have significantly affected social anxiety. This result also displayed that achievement

expectancy, network usage rate and career awareness have significantly influenced learning adaptability.

Social anxiety has a negative effect on learning adaptability. The implications for the academic and

educational bureau are also discussed within this paper’s closing.

1 INTRODUCTION

Is Internet bringing people more convenient

communication or bringing them more anxiety in

their daily lives? The network technology has

changed the way of people’s lives. Individuals

probably obsess with net activities, thereby

impacting adolescents lifestyle or changes their

interpersonal interaction among groups, and then

causes social interaction anxiety or learning

adaptability problems. However, little evidence has

yet come forth in this field. It is worthy of

investigation within current college students’ social

anxiety and learning adaptability.

Several studies have shown that people with

people with high social anxiety have poor social

capability (Zou, 2007). Faludi (1991) also found

people with high social anxiety usually hesitate to

communicate with other people Thus, what factors

affect college students’ social anxiety and learning

adaptability are the main issues being examined in

this research.

2 THEORETICAL

AND HYPOTHESES

2.1 Related Constructs

Clark et al. (1995) argued that fear of negative

evaluation and social avoidance is the hallmarks of

social anxiety. In this study, social anxiety is defined

as the young Internet users’ worrying about negative

evaluation by other people and fear of interaction

with other people. Several studies have shown the

factors affecting the social anxiety. The higher the

self-focused attention is, the higher the social

anxiety is (Kashdan et al., 2004). Expectation and

self-awareness have a significant impact on social

anxiety, respectively (Bogels et al., 2002). Previous

study has also shown that high social anxiety leads

to poor social adaptability (Haemmerlie et al., 1988).

Learning adaptability generally includes learning

method, learning habit, learning attitude, learning

environment and physical adaptability (Li, 1996).

Ashforth et al. (2007) presented that the

socialization process affects learning adaptability.

Career achievement expectation also affects learning

adaptability (Kenny et al., 2005). Gong (2003) found

that achievement affect learning adaptability. Palthe

(2004) noted that self-efficacy affect adaptability.

116

Yang H., Lay Y., Tsao W. and S. Lay J. (2010).

THE IMPACT OF INTERNET ON SOCIAL ANXIETY AND LEARNING ADAPTABILITY FOR YOUNG ADULT INTERNET USERS .

In Proceedings of the International Conference on e-Business, pages 116-119

DOI: 10.5220/0002935901160119

 SciTePress

Bandura (1977) suggested three outcomes of

self-efficacy that can predict the changes in people’s

behavior: choice behavior, effort expenditure and

thought patterns and emotional reactions. Thus, in

this study Internet self-efficacy focuses on what

individuals believe they can accomplish surfing

online. Griffin et al. (1998) found that self-efficacy

affected the test anxiety. Self-efficacy has a positive

effect on achievement and negative impact on test

anxiety (Griffin et al., 1998).

Expectancy’s theory suggests that the individual

will consider the outcomes associated with various

levels of performance. Rapee et al. (1997) displayed

that social anxiety have an external negative

psychological effect on performance. An individual's

self-evaluation affects social anxiety. They also

presented that task-focused attention would affect

social anxiety Rapee et al. (1996) found that

self-evaluation had affected social anxiety. Griffin et

al. (1998) found that achievement affected text

anxiety. Previous evidence also found that

achievement affected learning adaptability and

social anxiety (McEwan et al., 1999).

Our definition of career awareness is the

students’ consideration of future job-orientation and

its social value. Fadale (1973) developed a Career

Awareness Inventory to measure students’ career

awareness. Career awareness affects life adaptability

(Super, 1990). Clark & Wells (1995) wrote that

individuals have social anxiety because of their overt

self-awareness. Bogels et al. (2002) found social

anxiety was affected by self-awareness.

Usage rate is generally classified into light users,

middle users and heavy users in the marketing field.

In this study, the network usage rate is based on the

time that users use the Internet. We classify Internet

users into light users, middle users and heavy users.

Some evidence has been found to support the impact

of network usage rate on anxiety and adaptability.

Kaltiala-Heino et al. (2000) found the frequency of

involvement in bullying has a significant effect on

anxiety.. Ybarra et al. (2007) found that network

harassment behavior has a positive influence on

psychosocial behavior.

2.2 Hypotheses

Based on the previous empirical research, nine

hypotheses are developed and shown below.

H1: network self-efficacy has a negative influence

on social anxiety;

H2: network self-efficacy has a positive influence on

learning adaptability;

H3: network usage rate has a positive influence on

social anxiety;

H4: network usage rate has a negative impact on

learning adaptability;

H5: achievement expectation has a negative impact

on social anxiety;

H6: achievement expectation has a positive affect on

learning adaptability;

H7: career awareness has a positive affect on social

anxiety;

H8: career awareness has a positive affect on

learning adaptability;

H9: social anxiety has a negative influence on

learning adaptability.

2.3 Instrument Development

Responses are provided using a 7-point Likert scale

for all constructs, rated from 1 (not at all) to 7

(extremely). The scales of social anxiety, learning

adaptability, career awareness, Internet self-efficacy,

achievement expectation and network usage rate is

adapted and modify from Mattick & Clarke’s (1998),

Li’s (1996), Fadale’s (1973), Yang et al.’s (2008),

and Ybarra et al.’s (2007) usage scale.

3 RESULTS

3.1 Characteristics of Samples

The mean Internet experience of the young adult

respondents was 6.73 years (N=516). The

distribution of hours spent on the Internet per week

(19.5% under five hours; 22.1% six to ten; 10.6%

eleven to fifteen; others are over sixteen hours) and

length of Internet usage (continuous use is 30.6%

and 43.4% is at least once a day) among respondents

indicated that the Internet has become pivotal

communication tool for young adult Internet users.

3.2 Reliability and Validity

The alpha value of each construct exceeds the

minimum value of 0.7, providing satisfactory

reliability as proposed by Nunnally (1978). In this

study, the reliability coefficients were 0.88 for

achievement expectation, 0.91 for network

self-efficacy, 0.78 for network usage rate, and 0.87

THE IMPACT OF INTERNET ON SOCIAL ANXIETY AND LEARNING ADAPTABILITY FOR YOUNG ADULT

INTERNET USERS

117

for career awareness. All constructs display

excellent psychometric properties. Confirmatory

factor analysis (CFA) was testing the validity. The

CFA is using the EQS software to determine whether

the measurement model fitted to our collected data

(Bentler, 1995). CFA is conducted using the

maximum likelihood method. The measurement

model should find

to be nonsignificant; the

goodness-of-fit-index (GFI) should be above 0.90;

and root mean square error of approximation

(RMSEA) should be below 0.05 (Bentler, 1995).

The CFA yields

/df < 3, p<.0001, NFI=.886,

NNFI=.904, IFI=.921, CFI=.920, GFI=.898, and

RMSE=0.037 (<0.05). Although the NFI and GFI

were slightly below 0.9, these results indicate that

the measurement model does fit the data and

validate the model proposed by this research.

3.3 Results and Discussions

Structural Equation Modelling (SEM) was used to

test hypotheses. The chi-square, RMSEA and a

number of goodness-of-fit indices should fit the

theoretical requirements (Bentler, 1995). The

measures indicate that the model provided a good fit

for the data (CFI=.963; NFI=.915; NNFI=.946;

GFI=.927; AGFI=.894; RMSEA=.008). Among the

nine hypotheses, eight of the nine hypotheses are

significant at levels between 0.05, and 0.001, shown

in Figure 1. There are four hypotheses involving

factors to predict social anxiety. Network

self-efficacy and career awareness have a significant

impact on social anxiety (β=-.120, P<0.05; β

=.524, P<0.001) as the hypotheses predicted. This

result indicated that if users have high network

self-efficacy, they would have more confidence

surfing the Internet. They would thus have no

problem in social interaction occasions perceiving

the feelings of anxiety. Stronger career awareness

would result in higher social anxiety on the part of

individuals because young adult will worry about

their future and be anxious that they can not survive

in society. Clark & Wells (1995) thought individuals

have social anxiety because of over self-awareness.

Network usage rate and achievement expectation

have a direct negative effect on social anxiety (β

=-.116, P<0.01; β =-.159, P<0.05) as the

hypotheses predicted. These results indicated that

young adult Internet users spent too much time on

the Internet and may cause social anxiety. The

current study also supported the relationship

between achievement expectation which conjunction

with past research (Rapee et al., 1997). This result

shows that young adult with high achievement

expectation will try to solve the problems they face,

so they will have low social anxiety.

Figure 1 Results of hypotheses.

In turn, five hypotheses involved to predict

learning adaptability and all were supported.

Network usage rate, achievement expectation, career

awareness and social anxiety have a significant

effect on learning adaptability (β=-.105, P<0.001;

β =.825, P<0.001; β =.079, P<0.05; β =-.323,

P<0.01) as hypothesized (H6, H7, H8 & H9). The

results indicated that if young adults spend too much

time on the Internet, and could cause a learning

adaptability problem. Internet users with high

achievement expectation more easily adapt to

different environments, so they have better learning

adaptability. Young adults with higher career

awareness would take precautions against the

problems they may face planning before they act and

simulate the problems they may need to overcome.

They will thus have better learning adaptability.

Finally, this research also found that social anxiety

and learning adaptability have a negative

relationship. This means that if young adults have

higher social anxiety, they would have less learning

adaptability in their daily lives. This result is also

consistent with previous research (Zou et al., 2007).

However, the influence of network self-efficacy on

learning adaptability is not significant (β=.039,

P>0.05) unlike as hypothesized (H5) (Griffin et al.,

1998; Palthe, 2004). The possible argument is the

measurement problem of learning adaptability

causing the result.

4 CONCLUSIONS

This study represents an initial effort in mapping

some attributes of young adult networking users to

social anxiety and learning adaptability. This study

ICE-B 2010 - International Conference on e-Business

118

is noteworthy to academic researchers and educators

alike. From an academic researcher’s perspective,

the majority of social anxiety research comes from a

medical perspective in studying patients. Little prior

research is from the young adult networking users’

view to investigate the factors affecting social

anxiety. The research results can serve as a reference

for advanced study. From the educational

perspective, schools have more chance to understand

college students’ social anxiety and learning

adaptability after using Internet in networking

society to reduce and prevent the percentage of

students from quitting school and enhance their

studying adaptablilty.

ACKNOWLEDGEMENTS

This work was supported by the National Science

Council of Taiwan- No: NSC-97-2410- H-167-009.

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INTERNET USERS

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