Hodijah
Wulandari1, Joko Sutarto2, Farid Ahmadi3
Universitas Negeri Semarang, Indonesia
[email protected]1,
[email protected]2,
[email protected]3
Abstrack:
This study examines the effect of
digital literacy of educators based on Artificial Intelligence (AI) on learning
effectiveness and educator performance in the Non-Formal Education Unit of the
Learning Activity Center (SKB) in Pekalongan
Prefecture. This research is quantitative causal research. With a population of
132 educators and a sample of 101 educators using a simple random sampling,
data were collected through questionnaires and analyzed descriptively and
simple linear regression. The findings indicated that the digital literacy of
AI-based educators positively and significantly influenced learning
effectiveness (59.1%) and educator performances (54%), with a significance
value of 0.000 <0.005. The research conclusion emphasizes the importance of
improving digital literacy through training and collaboration and the need for
support from agencies and the government in providing access to technology and
adequate infrastructure. Future investigations will examine additional
independent variables that could impact educational outcomes.
Keyword : Educator
Digital Literacy; Artificial Intelligence (AI); Learning Effectiveness;
Educator Performance
Corresponding:
Hodijah Wulandari
E-mail: [email protected]
Introduction
In the 21st century,
having literacy skills is very important in life. Rapid advances in science,
technology, and information require human literacy skills to continue
developing and adapting. Therefore, we must continue learning and improving
literacy
The condition of low
digital literacy is caused by various factors, such as the condition of access
and infrastructure, individual and social, to support and policies from the
government as well as support from units and leaders. Educators, as one of the
tools in every educational unit, are expected to have digital literacy skills
that are not only good but also adequate. The ability of educators to use
information and communication technology in the teaching and learning process
is what digital literacy means in this context. This skill is crucial for
overcoming various new challenges in the constantly changing field of
education. Educators have an essential role in optimizing the use of
information and communication technology, especially in accessing the Internet
to manage the educational process and quality learning materials to support the
development of students. Educators must creatively utilize technology to find
quality learning resources and manage more interactive learning.
One of the most
significant technological developments is the existence of Artificial
Intelligence (AI). AI is now an important part of teaching and learning
activities in schools and universities
However, this
technology has yet to be fully utilized in learning. There are still several
educational institutions that still need to adopt technology in the learning
process. Today's academic institutions need to use technological developments
to facilitate the tasks of educators and students. It is time for all schools
to start using technology in learning
However, it is still
critical to pursue digital literacy because it is the key to preparing for
future challenges. Only now have a few studies examined educators' digital
literacy, especially for educators in non-formal education units. So this research is essential to do in order provide a
deeper understanding of the extent to which the digital literacy of educators
based on Artificial Intelligence (AI) can affect the effectiveness of learning
and the performance of educators in the non-formal education unit Sanggar Kegiatan Belajar (SKB). In the future, this research can also be a
basis for developing policies and training programs to improve educators'
digital competence, which can improve the overall quality of education.
Research
Method
This
type of research is quantitative research. According to Sugiyono
[16], a causal quantitative approach is a research method used to identify
cause-and-effect relationships between two or more variables. This research is
included in causal quantitative research because it aims to determine the
effect of digital literacy on educators based on artificial intelligence (AI)
(X) on learning effectiveness (Y1) and educator performance (Y2).
The
population used in this study were educators (Teachers and tutors) in the
Non-formal Education Unit of the SKB in the Pekalongan
Prefecture of Central Java Province consisting of SKB Pekalongan
Regency, SKB Pekalongan City, SKB Tegal Regency, SKB
Tegal City, SKB Brebes Regency, SKB Pemalang Regency,
and SKB Batang Regency totaling 132 educators.
Sampling was carried out using the Simple Random Sampling technique, totaling
101 educators with the following calculations:
Table
1. Overview of the Study Population and Sample
|
NO |
REGION/SKB |
POPULATION |
CONSIDERATIONS |
SAMPLE |
|
1 |
SKB Pekalongan
Regency |
16 |
|
12 |
|
2 |
SKB Pekalongan
City |
18 |
�
|
14 |
|
3 |
SKB Tegal Regency |
23 |
���
|
18 |
|
4 |
SKB Tegal City |
25 |
���
|
19 |
|
5 |
SKB Pemalang
Regency |
21 |
���
|
16 |
|
6 |
SKB Brebes Regency |
13 |
�
|
10 |
|
7 |
SKB Batang Regency |
16 |
|
12 |
|
Total |
132 |
|
101 |
|
Source: Information from each SKB unit
A questionnaire was employed as part of the
data collection method and distributed via Google Forms. The questionnaire used in this study is a
type of closed questionnaire. The questionnaire used is a Likert scale using a
1-5 scale calculation, namely Strongly Agree (SS), scored 5; Agree (S), scored
(4); Undecided (RG), scored 3; Disagree (TS), scored 2: Strongly Disagree
(STS), score 1. Each score obtained has an ordinal measurement level (
Data testing
is done with validity tests, reliability tests, descriptive statistical
analysis, and classical assumption tests. Two classic assumption tests are the
normality test and the heteroscedasticity test. The analytical tools used are
Simple Regression Analysis and the coefficient of determination test.
Conceptual
Framework
Visual
Representation (Conceptual Framework Diagram)
Digital Literacy of
Educators (central variable): This is the independent variable. It directly
influences both Learning Effectiveness and Educator Performance. Learning Effectiveness
(Mediating Variable): This variable acts as a mediator in enhancing educator
performance based on their ability to use digital tools effectively. Educator
Performance (Dependent Variable): The outcome variable is influenced by the
level of digital literacy and the resulting learning effectiveness.
Research
Implications
This framework can
be used to Assess Educator Needs, Identify gaps in digital literacy, and target
training programs. Policy Development can guide institutions in integrating
technology into teaching practices. Performance Evaluation can develop metrics to
evaluate the impact of digital literacy on learning outcomes and educator
performance.
RESULT
AND DISCUSSION
Descriptive
Analysis of AI-Based Educator Digital Literacy Variables
Table 2. Descriptive Statistics of Digital Literacy of AI-Based Educators
|
Descriptive Statistics |
|||||
|
|
N |
Min |
Max |
Mean |
Std. Deviation |
|
Digital
Literacy of AI-Based Educators |
101 |
36.00 |
100.00 |
76.4158 |
11.14295 |
|
Valid
N (listwise) |
101 |
|
|
|
|
Source: SPSS
27 output, research data processing 2024
Table 3. Frequency Distributions of AI-Based Educator
Digital Literacy Variables
|
No |
Scor Interval |
Total |
Percentage |
Category |
Average |
|
1 |
84 � 100 |
32 |
31,68% |
Very High |
76,4158 |
|
2 |
68 � 83 |
53 |
52,47% |
High |
|
|
3 |
52 � 67 |
15 |
14,86% |
High Enough |
|
|
4 |
36 � 51 |
1 |
0,99% |
Low |
|
|
5 |
20 � 35 |
0 |
0 |
Very Low |
|
|
Total |
101 |
100% |
|
High |
|
Source:
Research data processed in 2024
Table 4. Frequency Distribution of AI-based Educators�
Digital Literacy Indicators
|
No |
Indicator |
Average |
Category |
|
1 |
Access |
7,95 |
High |
|
2 |
Selecting |
8,01 |
High |
|
3 |
Understanding |
8,06 |
High |
|
4 |
Analyzing |
8,52 |
Very High |
|
5 |
Verifying |
7,14 |
High |
|
6 |
Evaluate |
7,45 |
High |
|
7 |
Distribute |
7,78 |
High |
|
8 |
Producing |
8,19 |
High |
|
9 |
Participate |
6,54 |
High Enough |
|
10 |
Collaborate |
6,72 |
High Enough |
Source:
Research data processed in 2024
These findings
indicate that, among the 101 respondents, the highest value of the AI-based
educator digital literacy variable is 100, and the lowest is 36 from the
questions given. The standard deviation is 11.14295, and the mean value
obtained on the variable is 76.4158. these descriptive statistics show that the
mean value is above the standard deviation, indicating a good representation of
the overall data. This means that educators at SKB in the Pekalongan
Prefecture already have digital literacy based on artificial intelligence (AI),
as indicated by the average result of AI-based educators, which is 76.4158 in
the high category.
Descriptive
Analysis of Learning Effectiveness Variables
Table 5. Descriptive Statistics of Learning
Effectiveness
|
Descriptive Statistics |
||||||
|
|
N |
Min |
Max |
Mean |
Std. Deviation |
|
|
Learning
Effectiveness |
101 |
22.00 |
75.00 |
60.2178 |
8.79841 |
|
|
Valid
N (listwise) |
101 |
|
|
|
|
|
Source: SPSS
27 output, research data processing 2024
Table 6. Frequency Distribution of Learning
Effectiveness Variables
|
No |
Score Interval |
Total |
Percentage |
Category |
Average |
|
1 |
63 - 75 |
32 |
31,68% |
Highly
Effective |
60,2178 |
|
2 |
51 � 62 |
53 |
52,48% |
Effective |
|
|
3 |
39 � 50 |
15 |
14,85% |
Effective
Enough |
|
|
4 |
27 � 38 |
0 |
0% |
Less
Effective |
|
|
5 |
15 � 26 |
1 |
0,99% |
Very Less
Effective |
|
|
Total |
101 |
100% |
|
Effective |
|
Source:
Research data processed in 2024
Table 7. Frequency Distribution of Learning
Effectiveness Indicators
|
No |
Indicator |
Average |
Category |
|
1 |
Learning Implementation Management |
12,22 |
Effective |
|
2 |
Communicative Process |
12,15 |
Effective |
|
3 |
Learner Response |
12,02 |
Effective |
|
4 |
Learning Activity |
12,03 |
Effective |
|
5 |
Learning Outcomes |
11,78 |
Effective |
Source:
Research data processed in 2024
Based on the
results, it is known that out of 101 respondents, the highest value of the
learning effectiveness variable is 75, and the lowest value is 22 from the 15
questions given. The standard deviation is 8.79841, and the mean value obtained
on the variable is 60.2178. The results of the descriptive statistics show that
the mean value is greater than the standard deviation value, indicating a good
representation of the overall data. This means that, in general, the
effectiveness of learning at SKB in Pekalongan is at
a practical level, indicated by the average result of learning effectiveness of
60.2178 in the helpful category.
Descriptive
Analysis of Educator Performance Variables
Table 8. Descriptive Statistics of Educator
Performance
|
Descriptive
Statistics |
||||||
|
|
N |
Min |
Max |
Mean |
Std. Deviation |
|
|
Educator
Performance |
101 |
21.00 |
75.00 |
61.5446 |
8.79264 |
|
|
Valid
N (listwise) |
101 |
|
|
|
|
|
Source: SPSS
27 output, research data processing 2024
Table 9. Frequency
Distribution of Educator Performance Variables
|
No |
Scor Interval |
Total |
Percentage |
Category |
Average |
|
1 |
63 � 75 |
27 |
26,73% |
Very High |
61,5446 |
|
2 |
51 � 62 |
63 |
62,37% |
High |
|
|
3 |
39 � 50 |
10 |
9,91% |
High Enough |
|
|
4 |
27 � 38 |
0 |
0 |
Low |
|
|
5 |
15 � 26 |
1 |
0,99% |
Very Low |
|
|
Total |
101 |
100% |
|
High |
|
Source:
Research data processed in 2024
Table 10. Frequency Distribution of Educator
Performance Indicators
|
No |
Indicator |
Average |
Category |
|
1 |
Quality of Work |
12,22 |
High |
|
2 |
Speed or Accuracy of Work |
12,36 |
High |
|
3 |
Initiative in Work |
12,35 |
High |
|
4 |
Employability |
12,26 |
High |
|
5 |
Communication |
12,23 |
High |
Source:
Research data processed in 2024
Based on these results, out of 101 respondents, the highest value of the
learning effectiveness variable was 75, and the lowest value was 21 from the 15
questions given. The standard deviation is 8.79264, and the mean value obtained
on the variable is 61.5446. The results of the descriptive statistics of the
overall data. This means that, in general, the performance of educators at SKB
in Pekalongan is in the high category, indicated by
the average result of educator performance of 61.5445 in the high category.
Normality Test
Results
Table
11. Normality Test Results
|
Variables |
Sig. |
Decision |
|
X > Y1 |
0.080 |
Normal |
|
X > Y2 |
0.200 |
Normal |
Source:
Research data processed in 2024
According to the findings of the Kolmogrov-Smirnov normalcy test in the table above, the
probability value p or Asymp. Sig. (2-tailed) on X
against Y1 is 0.080 while on X against Y2 is 0.200. The normalcy assumption has
been met because the probability value is above the 0.05 significance level.
Heteroscedasticity
Test
Table 12. Heteroscedasticity Test Results
|
X > Y1 |
X > Y2 |
||
|
Variables |
Sig. |
Variables |
Sig. |
|
Digital Literacy of AI-based Educators |
0.405 |
Digital Literacy of AI-Based Educators |
0.886 |
Source:
Research data processed in 2024
Based on Table
12, the probability value (Sig) of the AI-based Educator Digital Literacy
variable on Learning Effectiveness is 0.405, while the AI-based Educator
Digital Literacy variable on Education Performance is 0.886. Since every
variable's probability value (Sig) is above the significance level of 0.05 or
5%, it can be inferred that there are no signs of heteroscedasticity as the
homoscedasticity assumption is met.
Simple Linear
Regression Analysis
Table
13. Hasil Analisis Regresi Linear Sederhana
|
X > Y1 |
X > Y2 |
||
|
Variable |
B |
Variable |
B |
|
Constant |
13.852 |
Constant |
17.226 |
|
Digital
Literacy of AI-Based Educators |
0.607 |
Digital
Literacy of AI-Based Educators |
0.580 |
Source:
Research data processed in 2024
According to the
findings of the above table's basic linear regression analysis, the regression
model for the effect of AI-based Educators� Digital Literacy on Learning
Effectiveness is obtained as follows:
Where:
Y
= Learning Effectiveness
X
= Digital Literacy of AI-Based Educators
The following information is obtained
based on the simple linear regression model above.
1.
The
constant is 13.852, which means that if the value of the independent variable
(Digital Literacy of AI-Based Educators) does not change, then the value of the
dependent variable (Learning Effectiveness) is also 13.852.
2.
The
regression coefficient on the AI-based Educator Digital Literacy variable is
0.607. It is positive, meaning that if the AI-based educator Digital Literacy
variable increases by 1 point significantly, the AI-based Educator Digital
Literacy variable will increase the value of the Learning Effectiveness
variable by 0.607.
Meanwhile, the
results of the regression model for the effect of AI-based Educator Digital
Literacy on Educator Performance are as follows:
Where:
Y
= Educator Performance
X
= Digital Literacy of AI-Based Educators
The following information is obtained
based on the simple linear regression model above.
1. The constant is 17.226, which means
that if the value of the independent variable (Digital Literacy of AI-Based
Educators) does not change, then the value of the dependent variable (Educator
Performance) is 17.226.
2. The regression coefficient on the
AI-Based Educator Digital Literacy variable is 0.580 and positive, meaning that
if the AI-Based Educator Digital Literacy variable increases by 1 point
significantly, the AI-Based Educator Digital Literacy variable will increase
the value of the Educator Performance variable by 0.580.
Coefficient of
Determination
Table
14. Coefficient of Determination Results
|
Variables |
R Square |
|
Digital
Literacy of AI-Based Educators on Learning Effectiveness |
0.591 |
|
Digital
Literacy of AI-Based Educators on Educator Performance |
0.540 |
Source:
Research data processed in 2024
Considering the outcomes of the
previously mentioned coefficient of determination test, The
regression model's R2 (R Square) value is used to calculate how well the
independent variable (independent) can explain the dependent variable
(dependent). Considering Table 14, it is known that the R value2 on the effect
of AI-Based Educator Digital Literacy on Learning Effectiveness is 0.591, 59.1%
of the variance in the dependent variable; according to this, Learning
Effectiveness can be explained by variations in the independent variable, specifically
AI-Based Educator Digital Literacy. While the remaining amount (100%-59.1% =
40.1%) is affected by factors not included in this study.
The effect of AI-Based Educator
Digital Literacy on Educator Performance is 0.540. This means that 54% of the
variation in the dependent variable, Educator Performance, can be explained by
the variation in the independent variable, namely AI-Based Educator Digital
Literacy. The remaining amount (100%-54% = 46%) is affected by factors not
included in this study.
Research Hypothesis Test
T Test (Partial)
Table 15. Partial
Test Result
|
X > Y1 |
X > Y2 |
|||
|
T Statistic |
Sig. |
T Statistic |
Sig. |
|
|
11.948 |
0.000 |
10.785 |
0.000 |
|
Source:
Research data processed in 2024
Considering the findings of the
t-test, presented in Table 15, it is obtained that the significant value of the
AI-based Educator Digital Literacy variable is 0.000, which is less than 0.05.
As for the t count, the value is 11.948> t table (1.983), so the AI-Based
Educator Digital Literacy variable affects the Learning Effectiveness variable.
So, the first hypothesis, H1: Digital Literacy of AI-Based Educators, has a
positive and significant effect on the learning effectiveness variable, which
is "accepted."
While the effect of AI-Based Educator
Digital Literacy on Educator Performance has a significance value of 0.000,
this value is smaller than 0.05. As for the t count, the value is 10.785>t
table (1.983), so the AI-Based Educator Digital Literacy variable affects the
Educator Performance variable. Thus, the second hypothesis, H2: Digital
Literacy of AI-Based Educators has a positive and significant effect on the
Educator Performance variable "accepted."
Discussion
The Influence of
Digital Literacy of Educators Based on Artificial Intelligence (AI) on Learning
Effectiveness
�� The
study's first hypothesis is that teachers' digital literacy, which is based on
artificial intelligence (AI), significantly improves the efficacy of learning.
Considering the findings of the conducted research, the hypothesis is proven.
The results of this study indicate that the digital literacy of educators based
on Artificial Intelligence (AI) has a positive effect with a regression coefficient
of 0.607, t count obtained a value of 11.948> t table (1.983) and
significance with a significance value of 0.000 smaller than 0.005 on learning
effectiveness. In light of these findings, the first hypothesis in this study
is accepted. The accepted hypothesis means that the higher the digital literacy
of educators based on Artificial Intelligence (AI), the more effective learning
effectiveness SKB in the Pekalongan Prefecture of
Central Java Province.
�� Descriptive statistical analysis of digital
literacy of AI-based educators proves that the average value is included in the
high category, namely 76.4158. High digital literacy of AI-based educators will
also impact effective learning effectiveness because the digital literacy of
AI-based educators affects learning effectiveness. The AI-based educator
digital literacy variable is measured using ten indicators: accessing,
selecting, understanding, analyzing, verifying, evaluating, distributing,
producing, participating, and collaborating. Based on the outcomes of
descriptive statistics, the indicator of analyzing is included in the very high
category, the indicators of accessing, selecting, understanding, verifying,
evaluating, distributing, and producing are included in the high category, and
the indicators of participating and collaborating are included in the moderate
category.
Considering the
explanation, it is likely that the digital literacy of educators based on
artificial intelligence (AI) impacts the effectiveness of learning. Educators
with high AI-based digital literacy can use their ability to process data,
analyze information, create more personalized and relevant learning content,
and network to gain a more comprehensive experience. Therefore, the higher
digital literacy of AI-based educators will encourage educators to continue to
innovate in learning, increase the expectations of education, and increase
student learning outcomes to face challenges in the digital era.
The findings of
this study are consistent with
Earlier research
that supports the findings of this study on the effect of digital literacy on
learning effectiveness is research from
The Influence of
Digital Literacy of Educators Based on Artificial Intelligence (AI) on Educator
Performance
�� The
study's second hypothesis is that teachers' digital literacy, based on
artificial intelligence (AI), significantly and favorably affects their
performance. Based on the results of the research that has been done, this
hypothesis is proven. The results of this study indicate that the digital
literacy of educators based on Artificial Intelligence (AI) has a positive
effect with a regression coefficient of 0.508, the calculated t value obtained
a value of 10,785> t table (1,983) and significance with a significance
value of 0.000 smaller than 0.005 on educator performance.
�� Based on these results, the second hypothesis
in this study can be accepted. The accepted hypothesis means that the higher
the digital literacy of educators based on Artificial Intelligence (AI), the
higher the performance of educators at SKB in the Pekalongan
Prefecture of Central Java Province.
�� Therefore, the digital literacy of educators
based on Artificial Intelligence (AI) impacts educator performance. Educators
with high AI-based digital literacy can utilize AI technology to improve the
quality of learning, such as developing more innovative learning materials,
providing more personalized and immediate feedback to learners, and initiating
the use of various AI tools in the learning process. This is reflected in
improved quality of work, speed in responding to technological developments, and
higher initiative in implementing innovations in learning. The higher the
digital literacy of AI-based educators, the higher their performance.
The results of
this study are those stated by
Previous research
on the effect of digital literacy on educator performance, based on the results
of this study, is from
CONCLUSION
From the study results, the digital literacy
of AI-based educators has a positive and significant effect on learning
effectiveness, and the digital literacy of AI-based educators has a positive
and significant impact on educator performance. The suggestions that can be
given are: (1) educators can improve digital literacy, primarily based on
Artificial Intelligence (AI), by proactively participating in training and
applying it in daily learning; (2) educators can also always collaborate with
colleagues for various knowledge and experiences, (3) institutions need to
provide easy access to technological devices and digital resources that support
the use of AI and need to create an innovative learning culture and encourage
educators to continue to develop themselves, (4) the government needs to
facilitate the development of educator's digital literacy and provide adequate
infrastructure as well as making policies that support the use of AI in
education. (5) future research is expected to develop other independent
variables that may affect learning effectiveness and educator performance.
Because of the coefficient of determination analysis results in this study, the
independent variables were able to explain the dependent variable by 59.1% and
54%. This means that other factors still affect the effectiveness of learning
and educator performance by 40.1% and 46%.
REFERENCES
Ahyani, Nur, Fitria,
Happy, Lian, Bukman, & Nugroho, Hery S. (2024).
The Effect of Digital Literacy on Teacher Performance. EDUSAINSEK: Journal
of Education, Science, and Technology, 11(3).
https://doi.org/10.47668/edusaintek.v11i3.1283
Aini, Dian F, & Nuro, Falistya
Roisatul Mar'atin. (2023).
Analysis of Teachers' Digital Literacy Competencies as a Skill Support for
Elementary School Teachers. Journal of Basicedu,
7(1), 840�851. https://doi.org/10.31004/basicedu.v7i1.4744
Faizah, U. (2019). Evaluation of the Performance of
Educators and Education Personnel and the Learning Process of Islamic
Education in Indonesia. Al-Fikri: Journal of Islamic Education Studies and
Research, 2(2), 44. https://doi.org/10.30659/jspi.v2i2.5151
Judge, L. (2022). The Role of Artificial Intelligence in
Education.
Hardiyanti, Waode E, & Alwi,
Nurul M. (2022). Analysis of Digital Literacy Skills of Early Childhood
Education Teachers during the COVID-19 Pandemic. Journal of Obsession:
Journal of Early Childhood Education, 6(4), 3759�3770.
https://doi.org/10.31004/obsesi.v6i4.1657
Kumalasari, Fatmawati, Riyadi, Riyadi, & Hadiyah. (2023). The effect of digital
literacy on teachers' ability to operate the elementary school digital report
card application. JPI (Indonesian Education Journal): Scientific Journal of Education, 9(3).
https://doi.org/10.20961/jpiuns.v9i3.76529
Luh P, Putu S, Made S. (2022). The Role of Artificial
Intelligence (AI) to Support Learning During the Covid-19 Pandemic. Journal
of Computer and Science Technology (KOMTEKS), 1(2), 15�21.
Mukaromah, Lu'luul, &
Wardoyo, Cipto. (2022). Online Learning
Effectiveness: Through Digital Literacy And Teacher's
Professional Competence. Assets: Journal of Accounting and Education, 11(1),
10. https://doi.org/10.25273/jap.v11i1.10810
Mulianingsih, Ferani, Anwar, Khoirul, Shintasiwi, Fitri A, &
Rahma, Anggi J. (2020). Artificial Intelligence with
the Formation of Values and Character in the Field of Education. IJTIMAIYA:
Journal of Social Science Teaching, 4(2), 148.
https://doi.org/10.21043/ji.v4i2.8625
Sappaile, Baso I. (2007).
The Concept of Educational Research Instruments. Journal of Education and
Culture, 13(66), 379�391. https://doi.org/10.24832/jpnk.v13i66.356
Sri Purwati, & Sukiman.
(2024). The Influence of Teachers' Digital Literacy and Media Literacy on The
Quality of Learning at Raudhatul Athfal.
Journal of Scientific Research, Education, and Technology (JSRET), 3(2),
600�612. https://doi.org/10.58526/jsret.v3i2.389
Soheila Mohammadyari., &
Harminder Singh. (2015). Understanding the effect of e-learning on individual
performance: The role of digital literacy. Computers & Education, Vol. 82,
11�25. https://doi.org/10.1016/j.compedu.2014.10.025.
Sukardi et al. (2023).
The Role of Teacher Competence, Digital Literacy, and the Availability of
Technological Facilities in Improving the Quality of Learning (Study on
Elementary School Teachers in Kandeman District, Batang Regency). Aditya Fiber, 12(1),
01- 10. https://doi.org/10.56444/sa.v12i1.552
Sulistyarini, Winda, & Fatonah, Siti. (2022). The Influence of Digital Literacy
Understanding and the Utilization of Learning Media on Teachers' Pedagogic
Competence in the Digital Learning Era. Journal of Educational Learning and Innovation (ELIa), 2(1), 42�72.
https://doi.org/10.46229/elia.v2i1.383
Ulandari, Riska. S, A.
(2023). The Role of AI in the World of Education. Bengkulu: CV. Brimedia Global.