This document summarizes a study that examined the relationship between students' internet self-efficacy and their grades when using social media as a learning tool. The study hypothesized that students with high internet self-efficacy would earn higher overall grades. It involved surveying 40 undergraduate students about their internet self-efficacy and analyzing their course grades. Regression analysis found a positive correlation between self-efficacy scores and grades. Students with higher self-efficacy tended to earn higher grades, supporting the hypothesis.

1. INTERNET SELF-EFFICACY AND ITS
IMPACT ON STUDENT'S GRADES: AN
EXPLORATORY STUDY
Madani Alomar Alaa Kutbi
King Abdul Aziz University University of Windsor
Jeddah, Saudi Arabia Windsor, Canada
Maalomar@kau.edu.sa Kutbi@uwindsor.ca

2. HYPOTHESIS
Students with high internet self-efficacy will have
higher over all grades when they use social media as
a learning tool.

3. RESEARCH QUESTION
Does using social media as a learning tool affect the
overall grades of students who have high internet self-
efficacy?

4. LITERATURE REVIEW
This literature review looks at previous studies related
to the impact of the use of social media as a learning
tool on the educational process. It also focuses on the
relationship between computer/internet self-efficacy
and student performance.

5. SOCIAL MEDIA
According to Kaplan and Haenlein (2008), social media can be
defined as “a group of Internet-based applications ‘interactive
platforms’ that build on the ideological and technological
foundations of Web 2.0 that allow the creation and exchanges
of user-generated content” (as cited in Ralph & Ralph, 2013, p.
451)

6. SOCIAL MEDIA
• Supports collaborative learning.
• Engages individuals in critical thinking.
• Enhances communication and writing skills through
writing activity.
• Enables students to work in private environments.
• Supports information sharing, content creation, and
knowledge and information aggregation and
modification.

7. INTERNET SELF-EFFICACY AND
STUDENT PERFORMANCE
Bandura and Wood (1989) define self-efficacy as
“[the] beliefs in one’s capabilities to mobilize the
motivation, cognitive resources and courses of action
needed to meet situational demands” (p. 260).

8. INTERNET SELF-EFFICACY AND
STUDENT PERFORMANCE
Internet self-efficacy is one type of self-efficacy. It is defined as
“the beliefs in one’s capabilities to organize and execute courses
of Internet actions required to produce given attainments” (Hsu,
Chiu, 2004, p. 369
Self-efficacy might be more important than skills and knowledge
among technology users (Ertmer & Ottenbreit-Leftwich, 2010).

9. INTERNET SELF-EFFICACY AND
STUDENT PERFORMANCE
An individual’s beliefs about their efficacy can be influenced by four main
sources. According to Bandura (1994), these four main sources are:
1. mastery experiences,
2. seeing people similar to oneself manage task demands successfully,
3. social persuasion that one has the capabilities to succeed in given
activities,
4. inferences from somatic and emotional states indicative of personal
strengths and vulnerabilities.

10. METHODOLOGY
A quantitative approach was used for this study. The study
participants are undergraduate university students. Data
collection was based on the computer self-efficacy scale (CSE)
and course final exams. After the results of the CSE were
analyzed and key questions were identified, students’ test
scores were analyzed.

11. PARTICIPANTS
Because this study is focused on social media as a learning tool,
the participants were students who were taking an
undergraduate course that is taught using social media
platforms. Forty university students from the undergraduate
program were chosen to participate in this study.
The participants were non-native English students who were
taking an undergraduate course that is taught using social
media. Forty participants were chosen to participate in this
study. The course sessions take place twice a week, face-to-
face.

12. INSTRUMENTATION
A thirty-nine-item internet self-efficacy scale 2006
(ISE06) was developed to measure the perceptions of
capability regarding specific internet-related
knowledge and skills.

13. DATA ANALYSIS
To identify the influence of internet self-efficacy on students’ grades,
regression analysis that measures the strength of the association
between two quantitative variables was used. Simple regression
provides an equation for describing the relationship between one
input variable (X) and the output variable (Y). The t-test was used to
test the hypothesis and answer the research question.

14. RESULTS AND FINDINGS
FIGURE 1. DISTRIBUTION OF COURSE GRADE AND SELF-EFFICACY SCORES OF THE STUDENTS.
85
90 90
84
92
69
90
99
65
82
92
74
96 98
73
80
96
94
80
68 68
89
74
82
68
73
77
95
76
89
72 72
70
81
92
69
79
90
77 77
1
4 5
3 3
5
2 2 1
5
2 3
5 5
2 2
5 5 4
1 2
4
2 2 2 1 1
4
2
5
2 1 1 1
5
1 1 2 2 3
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
Course grade Self-Efficacy

15. RESULTS AND FINDINGS
Multiple R 0.58381437
R Square 0.34083922
Adjusted R Square 0.32349288
Standard Error 8.21527187
Observations 40
TABLE 1. REGRESSION STATISTICS

16. RESULTS AND FINDINGS
Table2. Values of a, b, t-test and Boundaries
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 71.213 2.694 26.435 0.000 65.760 76.667
1 3.839 0.866 4.433 0.000 2.086 5.592

17. RESULTS AND FINDINGS
Y X
75.05 1
78.90 2
82.73 3
86.57 4
90.41 5
Table 3. Y and X Values

18. RESULTS AND FINDINGS
Figure 2. Normal probability plots of the grades.
0
20
40
60
80
100
120
0 10 20 30 40 50 60 70 80 90 100
Y
Sample Percentile
Normal Probability Plot

19. DISCUSSION
The study findings suggest that there is a strong
positive correlation between students’ grades
and their internet self-efficacy. Thus, the null
hypothesis was rejected, and the alternative
hypothesis was accepted.

20. THANK YOU…