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You will hand in a four-page paper as outlined above. It must be clear that you have incorporated the changes requested from the planning stage. Failure to do so will result in a fail grade for your work. This paper can be submitted on or before the 5th January 2019 for three-line feedback (which will be with you by the 10th January) with the final submission being the 15th January 2019.


The instructions within the ACM template noted above must be followed. You should include an abstract of between 100 and 200 words – this should not include any references. This should clearly explain what you did, how you did
it, what you found. Not following the formatting rules will result in a penalty (as high as 20%) being applied to your work. Do NOT include any supplementary material (e.g. videos – these are not part of our work You should aim to reference between 5 and 10 works – the appropriateness is more important than the numberJ Books, journals and conference papers should be referenced in the appropriate way – marks may be lost for sloppy referencing of these three items. Each reference in the list MUST BE referred to in the text.

Data analysis

he mobile phone was initially made to be used by adults basically for business purposes and it has become a powerful device used across all scales of economy. A mobile phone is a device used for wireless communication, entertainment and research (K. 2013), and it has become a basic device used across the globe for communication through its use continues to advance due to technological development and revolution (Mikael Gajecki 2014). Research study on mobile gaming revealed that women are major users of mobile phones for mobile gaming (Aoki 2011) and mobile games are integrated majorly to behavioral addiction (Kritika M. 2013).

Further studies (Takao 2009) say that the addictive mobile gaming is becoming problematic on the phone usage and it is impacting negatively to family relationships while (San Francisco 2012) Argue that however many mobile games have addiction effect, it was designed with strategies of training and education where through mobile gaming, children are introduced to the world of technology. Researchers have over time been tirelessly trying to base their studies on how mobile gaming has impacted positively or negatively to behavioral change.  (Böhmer 2011) Reveal that, along with the positive effects, there are negative aspects to the users which include addiction and increase of fraud cases among others.

The study reveals that there is a relationship between psychological characteristics and mobile gaming addiction (Hong 2012).

Data analysis

Data were coded in IBM SPSS. Frequency statistics and descriptive statistics were used to analyze the effect of the use of mobile gaming on behavioral change and as well analyze the attitude of the respondents across the gender on the effect of mobile gaming on their health. The correlation coefficient was used to determine the relationship between the use of mobile and the addiction effect.

Results and discussion

Table I: Shows Percentage of respondents who own mobile phone

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

YES

32

100.0

100.0

100.0

All the 32 respondents have the mobile phone as shown in table I below.

This is a clear indication that a mobile phone is an access device to a larger percentage of the population across the globe.

Correlation analysis was conducted between the two variables, the behavioral change and in, particular, addiction and the use of the mobile.

Table II below shows that the correlation within the two variables is 1 and .0426 with one another. This is a significant correlation at 5% and at 1%. Therefore, behavioral change and addiction are dependent on the use of mobile phone.

Table II: Relationship between Mobile gaming and addiction

Mobile

User   Addiction

Phone         usage

Pearson correlation

Significant(2-tailed test)

Size (N)

1

34                                  

.0426*** 

.003

 34

Current       grade

Pearson correlation

Significant(2-tailed test)

Size (N)

.0426*** 

.003

 34

1

34                                  

***Correlation is significant at 0.01 level (2-tailed)

Hypothesis test: Is there a significant relationship between mobile gaming and addiction?

H0: There is no significant relationship between mobile gaming and addiction.

H1: There is a significant relationship between mobile gaming and addiction.

Table III: Statistical test computation

Responses

A

B

A-B

(A-B)^2

(A-B)^2/B

Yes

22

10.67

11.33

128.37

12.3

No

8

10.67

-2.67

7.13

0.67

No Idea

2

10.67

-8.67

75.17

7.4

Total

32

32

-0.01

20.07

B stands for expected value and A is the observed value

A=32/3=10.67     X2 =    =20.55 hence H1 

X2 = Table value =(r-1) =3-1=2      2 at 0.05=5.991 (H0)

Conclusion: our calculated value is 20.07 which is greater than table value 5.991. We, therefore, reject the null hypothesis (H0) and accept alternative hypothesis (H1). We, therefore, conclude that there is a significant relationship between mobile gaming and addiction

Results and discussion

32 respondents were surveyed, of which 16(50%) and 16(50%) were male and female respectively.

Table IV: shows the relationship between age against gender

Age

Total

15-19

19-24

25-29

30-34

Gender

Male

Count

5

7

3

1

16

% within Gender

31.3%

43.8%

18.8%

6.3%

100.0%

% within Age

55.6%

46.7%

50.0%

50.0%

50.0%

Female

Count

4

8

3

1

16

% within Gender

25.0%

50.0%

18.8%

6.3%

100.0%

% within Age

44.4%

53.3%

50.0%

50.0%

50.0%

Total

Count

9

15

6

2

32

% within Gender

28.1%

46.9%

18.8%

6.3%

100.0%

% within Age

100.0%

100.0%

100.0%

100.0%

100.0%

9(28.1%) of total population aged (15-19) of which 5(31.3%) and 4(25.0%) were female. 15(46.9%) aged (19-24) of which 7(43.8%) and 8(50.0%) were female. Similarly, 6(18.8%) aged (25-29) of which 3(18.8%) were male and 3(18.8%) were female and finally 2(6.3%) aged (30 -34) years.

The results also indicate that in both male and female, most of the respondents were aged between 19 to 24 years

Analysis to identify the device that respondents use to play games across the gender was conducted as indicated in the bar chart below.

Pie chart I: Shows type of device that respondents use to play games across

The device I use to play games

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Mobile Phone

18

56.3

56.3

56.3

Computer

8

25.0

25.0

81.3

PlayStation

3

9.4

9.4

90.6

Xbox

3

9.4

9.4

100.0

Total

32

100.0

100.0

It shows that the highest number 18(56.3%)  respondents use the mobile phone to play games followed by 8(25.0%)  who use a computer. 3(9.4%) use Xbox and go to PlayStation respectively to play computer games. The analysis indicates with clarity that mobile phones are the major device used by respondents to play computer games. This could be attributed to its accessibility based on mobility, portability and the cost associated with buying the mobile phone.

The mobile phone also is advantageous in a way that one can easily install or uninstall the mobile games application at once choice with no limitation. The cost of buying computer is high and are not portable making it an unfavorable choice of device to use. PlayStation could be equipped with more sophisticated tools for better gaming but it has a time limit for playing and cannot allow one to customize the usage to fit personal standards as compared to the mobile phone.

Analysis of the type of games that respondents liked most was conducted as shown in the bar chart I below

Bar chart I: Shows the game that most respondents play

The results reveal that the highest respondents 12(37.5%) play candy crush saga as their favorite game followed by the angry birds with 9(28.1%) respondents. Mortal kombat5 and modern combat were being used by 4(12.5%) respondents respectively. Low percentage 3(9.4%) respondents play PUBG (playerRunknown’sBattleGrunds).

Further analysis was done to examine the time that respondents spent playing games and the relationship to gender.

The bar chart II: Shows the time that respondents spent across the gender

It reveals that female spent a lot of time playing games with high percentage playing game (61-80+) hours a week. Male spent considerable little time (21-40) hours a week. This reveals that men know how to control the time they spent on gaming, unlike women who spent their time uncontrollably. It also reveals that men play several mobile games and spending less time in each game as compared to women who play less mobile games and put more concentration on one game consuming considerably more time

The Bar chart below shows the attitude of the respondents on whether they feel lonely in the event they don’t play games.

Bar chart III: The attitude of respondents on loneliness in the event they don’t play games

It shows that highest percentage of respondents 25 (78.1%) feel loneliness in the event they don’t play games whereas lowest percentage 7(21.9%) disagree on the feeling of loneliness when they don’t play games.

Highest percentage 24(75.0%) respondents say that gaming does not have a positive effect on their health whereas the lowest percentage 8(25.0%) say that gaming has a positive effect on their health. The bar chart below shows the distribution of the respondent’s attitude on the effect of gaming on their health

Pie chart II: The attitude of respondents on the effect of gaming on their health

It, therefore, tells much about the awareness of the respondents on the effect of the gaming on their health.

Discussion

The study was carried out to investigate the relationship between mobile gaming and addiction. The focus was on time that people spent on gaming, the most played game, the attitude of the people on the effect of gaming on their health, and the gender that are prone to gaming. It also investigated the device that most people use for gaming. There is positive a correlation between Mobile gaming and addiction.

The finding was clear that all the respondents that were surveyed had mobile phones and that most of them play games on their mobile phone. The analysis reveals that women are the major population who spent most of their time gaming and this could be attributed to the fact that women have chores that entails remaining indoors, taking care of siblings and in the process of making their kids happy, they like the gaming too. Furthermore, respondents say that they feel loneliness in the event they don’t play games. This partial indication of the addiction effect that users face prompting to continuous usage of mobile phones for gaming. Most importantly, respondents are aware of the negative effect that mobile gaming has on their health.

Conclusion

A mobile phone is a device accessible to many people. Its use has taken a different direction as more invention continue to advance. Several mobile gaming is accessible on the mobile phone mostly on Android smartphones. Some of the mobile games available and accessible to mobile phones include angry birds, candy crush saga, mortal combats5, and mortal combat. Results of the analysis show that Candy Crush is the most played game implying that the game has features that are favorable for use by many users. However, all the mobile games have an addictive effect with a negative effect on the users since it consumes most of the time of the user. On the other hand, mobile gaming has a positive effect on the feeling of loneliness.

Due to the innovation of many mobile games that are accessible to the mobile phone, many people especially women who play mobile gaming will rise tremendously especially those aged 18 to 25 years of age.

References

Aoki Kumiko, and Downes Edward. “Cell phone usage.” An analysis of young people's Use of and Attitudes Toward cell phone. 5th ed. Oxford; New York, 2011.

Böhmer, Schöning, Johannes, Krüger, Antonio, Cheverst, Keith, Rohs, Michael, Löchtefeld, Markus, Taher, and Faisal Markus. “A large-scale study on mobile application usage”. Proceedings of the 13th international conference on human-computer interaction with mobile devices and services 56, no. 2(2011): 23-28.

Hong, Fu-Yuan, Chiu, Shao, and Huang Der-Hsiang. "A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students." Journal of Computers in Human 8, no. 9(2012): 33-38. doi: 10.1145/1613858.1613876.

Dmitrieva, Natalia. “Mobility development.” Experimental results on academic mobility development in university students in process of foreign language acquisition.7th ed. London, Macmillan, 2013.

Kritika, Vasanta. “The Mobile Phone Usage among Teens and Young Adults Impact Of Invading Technology.” .International Journal of Innovative Research in Science, Engineering and Technology 5, no. 13(2013): 43-47.

Magnus, Ligi, and Karmen Trasberg. “University students’ reasons for Committing academic fraud and knowledge about regulations: a qualitative interview study.” Mass Communication Research. 7th ed. Basingstoke, Macmillan, 2014.

Mikael Gajecki, Anne H Berma. “Mobile phone brief intervention applications for risky alcohol use among university students: a randomized controlled study.” Addiction Science & Clinical. 6th ed. Germany, Frank Cass 2014.

San Francisco, CA: Pfeiffer. "The gamification of learning and instruction." Game-based methods and strategies for training and education. 7th ed. Hawker Brownlow Education,2012.

Sung Youl Park, Min-Woo Nam, Seung-Bong Cha. "University students' behavioral intention to use mobile learning: Evaluating the technology acceptance model." 4th ed. Basingstoke: Macmillan, 2012.

Takao, M., Takahashi, S., & Kitamura, M. "Addictive Personality and Problematic Mobile." Journal of Cyberpsychology & Behaviour. 4th ed. London, Oxford Press, 2009.

Vivaracho-Pascual, and Pascual-Gaspar, J. "On the Use of Mobile Phones and Biometrics for Accessing Restricted Web Services." 3rd ed. Oxford; New York, 2012.

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