5.3 One-sample T-Test results The following hypothesis (one-tail test) was tested using a one-sample t-test to confirm
whether the proposed framework was beneficial in enhancing students’ m-learning ex-
periences:
•
H 0
Overall mean score of m-learning = 3.40.
•
H α Overall mean score of m-learning
> 3.40.
A one-sided significant difference (
P < 0.05) was found in the one-sample t-test re-
sults, suggesting that the null hypothesis H0 was rejected and that the overall mean score
of m-learning
> 3.40 denotes a high level of agreement. Additionally, Cohen’s d [35]
was used to determine the size of the effect of the framework. The effect size is de-
scribed by Cohen [35] as small at d = 0.2, medium at d = 0.5 and large at d = 0.8 or
more (see Table 5).
Table 5. One-sample t-test results
Test Value = 3.40 t Df Significance Mean Differ- ence 95% Confidence Interval of the Difference One- Sided p Two- Sided p Lower Upper Cohen’s d 1. M-learning in computer
programming eases the pro-
cess of quizzes.
3.888 20
<.001
<.001
.60000 .2781
.9219
.70711
(
medium
)
2. M-learning in computer
programming encourages me
to learn more.
2.008 20
.029
.058
.31429 -.0122 .6407
.71714
(
medium
)
3. My results in M-learning
in computer programming
were better compared to
those I received in traditional
learning.
4.347 20
<.001
<.001
.60000 .3121
.8879
.63246
(
medium
)
4. M-learning in computer
programming met my needs. 2.368 20
.014
.028
.36190 .0431
.6807
.70034
(
medium
)
5. M-learning in computer
programming met my expec-
tations.
2.238 20
.018
.037
.31429 .0213
.6073
.64365
(
medium
)
6. M-learning in computer
programming has increased
my confidence.
2.238 20
.018
.037
.31429 .0213
.6073
.64365
(
medium
)
7. I want to take other
courses using M-learning.
4.832 20
<.001
<.001
.79048 .4493 1.1317
.74960
(
medium
)
Overall
4.052 20
<.001
<.001
.47075 .2284
.7131
.53243
(
medium
)
iJIM
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Vol. 17, No. 13, 2023
51
Paper —Effects on Saudi Female Student Learning Experiences in a Programming Subject Using Mobile…
