Presentación de la defensa de la tesis de Li Yang

1. Evaluation of Pre-service
and In-service Teachers ́
Digital Competence in Anhui
Province, China
Ph.D. Thesis
Candidate: Li Yang
Supervisors: Fernando Martínez Abad, Ph.D.
Alicia García Holgado, Ph.D.
22/May/2023

2. Thesis
Structure
1. Introduction
5. Discussion and
Conclusion
2. Literature Research:
Comparative study of
frameworks
Systematic Literature Reviews
of Chinese Teachers ́ Digital
Competence
4. Formulate an educational
proposal for improving
teachers ́ digital competence:
Theoretical Support for
Teacher Training
Educational Training Program
3. Assessment of teachers ́
digital competence:
Methodology
Results of Data Analysis

3. 1. Introduction
Media literacy & Digital literacy
Media literacy is defined as accessing, analyzing,
evaluating, and creating messages (Livingstone,
2004) across all forms of media.
Digital literacy is defined as the ability to
understand and use information in multiple formats
when it is presented via computers (Martin &
Grudziecki, 2006).
Both concepts emphasize the ability of critical
thinking or critical evaluation.
1.1. Constructs related
to digital technology

4. 1. Introduction
Digital competence
Digital competence (European Commission, 2018, p.
9) includes:
• Information and data literacy
• Communication and collaboration
• Media literacy
• Digital content creation (including programming)
• Safety (including digital well-being and
competences related to cybersecurity)
• Intellectual property-related questions
• Problem-solving
• Critical thinking.
1.1. Constrcuts related
to digital technology

5. 1. Introduction
The relation between the
concepts related to digital
technology
Digital literacy
Media
literacy
Information,
and date
literacy
Computer
literacy

6. 1. Introduction
1.2.1. Teachers ́ Digital Competence
Teachers' digital competence conceptions are related to
the teachers' professional development in the use of ICT
with pedagogical judgment (Krumsvik, 2008 & Spante
et al., 2018, p. 15).
1.2.2. Digital Competence in Chinese
Education
A series of educational policies regarding digitalization
in educational field have been launched from 2018 by
the China Ministry of Education.
1.2. Issues and justification

7. 1. Introduction
1.3. Objectives
General objectives:
1. Address the study of
digital
competence….
2. Determine the digital
competence level….
3. Formulate an
educational proposal
to improve the
digital competence
level…
for pre-and in- service
teachers in the Anhui
region (China).
Specific objectives:
1. Identify frameworks related to
digital competence and its key
components.
2. Design and validate a
questionnaire to evaluate pre-
and in-service teachers´ digital
competences.
3. Determine the perception of pre-
and in-service teachers´ digital
competence in Anhui region.
4. Design a training course for
teachers to improve their digital
competence level.

8. 2. Literature Research: Comparative Study of Frameworks
The objectives:
To analyze the contributions of
frameworks to understanding the
development of digital technology.
To determine the differences and
similarities between these
frameworks through SWOT
analysis.
The focus:
The evolutionary characteristics
of frameworks related to digital
competence.
The results of comparative
analyzes between these identified
frameworks.

9. 2. Literature Research: Comparative Study of Frameworks
1.
Identify
frameworks.
2.
Review the
indicators.
3.
Compare the
indicators.
4.
Integrate
SWOT
analysis
method.
5.
Comparative
analysis
between these
frameworks

10. 2. Literature Research: Comparative Study of Frameworks
Comparative analysis
results
---The connection of selected
frameworks
6 influential frameworks_ five similar elements:
(1) purpose of the framework;
(2) competence areas;
(3) competence, learning domains (such as knowledge, skills,
and attitudes);
(4) how to perform the tasks; and
(5) digital tools to be used.

11. 2. Literature Research: Comparative Study of Frameworks
Comparative analysis
results
---The connection of selected
frameworks

12. 2. Literature Research: Systematic Literature Reviews of Chinese
Teachers ́ Digital Competence
Objective 1
describe the current state of Chinese teachers´ digital
competences.
Objective 2
identify existing issues related to Chinese pre-and in-service
teachers.
Objective 3
map out a development framework for improving the Chinese
teachers´ digital competences level.

13. 2. Literature Research:
Systematic Literature Reviews
Results _ The main terms used:

14. 2. Literature Research:
Systematic Literature Reviews
Results _ The 6 main research purposes:

15. 2. Literature Research: Systematic Literature Reviews of
Chinese Teachers ́ Digital Competence
The current status of the digital
competence level
The influencing factors
• The level of informatization in China
_unbalanced eastern, central, and western
regions
• Pre-and in-service teachers´ digital
competence level_ awareness high, but
lack high ability to use ICT tools
• TAM: Social influence, facilitating conditions,
perceived usefulness, perceived ease of use,
performance expectancy.
• Sex, years, years of teaching experience, educational
background, teachers' training experience,
technological environment, and self-efficacy etc.
Results _ The two main research outcomes

16. 2. Literature Research: Systematic Literature Reviews
Results:
The main methodological
characteristics _ Study
population & Sample size
Sample size 1-
200
201-
500
501-1000 1001-
2000
2001-
5000
> 5000 No
mention
No. of
articles
11 9 6 9 4 8 3

17. 2. Literature Research:
Systematic Literature Reviews
Results:
The main methodological
characteristics _
Type of the methodology
The design-validation
Validation of the instrument used

18. 2. Literature Research:
Systematic Literature Reviews
Results:
the main proposals presented:
Establishing a good
atmosphere for ICT.
Making good
pedagogical
strategies.
Conducting
teacher training.

19. 3. Assessment of Teachers ́ Digital Competence:
Methodology
4.1. Research design: An ex-post-facto methodology,
with non-experimental-cross-sectional design.
4.2. Sample and population
4.3. Variables and instrument
4.4. Procedures
4.5. Data Analysis

20. 3. Assessment of Teachers ́
Digital Competence:
Methodology
Sample of the research
Sex In-service teacher Pre-service teacher
Frequency Percentage Frequency Percentage
Female 136 55% 122 49%
Male 112 45% 128 51%
Total 248 100% 250 100%

21. 3. Assessment of Teachers ́ Digital Competence:
Methodology
4.3. Variables and instrument
4.3.2. Instrument
Digital
competences
construct
Yan et al. (2018).
FA_
Basic
Technology
Literacy
FB_
Technical
Support
Learning
FC_
Technical
Support
Teaching
• FA1_Consciousness and attitude;
• FA2_Technical Environment;
• FA3_Information Security
• FB1_Self-learning;
• FB2_Communication and Collaboration;
• FB3_Research and Innovation
• FC1_Resource preparation;
• FC2_Process Design;
• FC3_Practice Reserve
Factors Dimensions

22. 3. Assessment of Teachers ́
Digital Competence:
Methodology
Variables
• Criteria variables
• Other variables Name Type
Sociodemographi
variables
Sex Nominal
Age Ordinal
Educational background Ordinal
Profession Nominal
Explanatory ICT training courses
Nominal
The working school types Nominal
The available hardwires Nominal
The available research
Nominal

23. 3. Assessment of Teachers ́ Digital Competence:
Methodology
1. Implement
the online
questionnaire
in Qualtrics
(Dic/2020)
2. Send to
universities
Anhui for
reviewing
(Feb/2021)
3. Send the
questionnaire to
pre-service
teachers
(Feb/2021)
4. Send to in-
service
teachers in
Anhui
province
(Feb/2021)
5. Finally,
625
participants
(Jun/2021).
4.4. Procedures

24. 3. Assessment of Teachers ́ Digital Competence:
Results of Data Analysis
1). Scale validation (Cronbach's Alpha coefficient & CFA)
2). Descriptive analysis (frequency, means, standard deviations,
percentile, or coefficient of variation)
- items of each dimension
- dimensions and factors
3). Correlation analysis between dimensions or factors
4). Inferential analysis for exploring influencing factors
(criterion variables, sociodemographic and explanatory variables)
SPSS and JASP

25. 3. Results of Data
Analysis
1). Reliability and validity of
digital competence scale
Acceptable
Value
FA Consciousness
Consciousness
and attitude
FB
Technical
environment
FC Information
Information
Ethics and
Information
Security
chi2
78.876 26.184 113.693
df 116 116 296
p .997 <.999 <.999
Ratio (x2
/df) .668 .226 .384
Absolute fit
index
GFI .991 .998 .996
SRMR .047 .029 .036
Incremental fit
fit index
CFI <.999 <.999 <.999
NFI .986 .997 .995
RFI .984 .996 .994

26. 3. Results of Data
Analysis
2). Descriptive analysis
- items in each dimension
- dimensions and factors
Medium level
3,60
3,70
3,80
3,90
4,00
4,10
4,20
FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3
3,78
3,80
3,82
3,84
3,86
3,88
3,90
3,92
3,94
3,96
3,98
Basic Technology Literacy Technical Support Learning Technical Support Teaching

27. 3. Results of Data
Analysis
3). Correlation analysis
between dimensions or
factors
Direct and high significant
correlations
Factor Dimension Rxy Sig.
F1 Basic
Literacy FA1– FA2 .791 <.00
FA1– FA3 .706 <.00
FA2– FA3 .725 <.00
F2 Technical
Learning FB1– FB2 .817 <.00
FB1 – FB3 .826 <.00
FB2– FB3 .810 <.00
F3 Technical
Teaching FC1– FC2 .874 <.00
FC1– FC3 .816 <.00
FC2– FC3 .873 <.00
F1 Basic Technology Literacy – F2
Support Learning .747 <.00
F1 Basic Technology Literacy – F3
Support Teaching .627 <.00
F2 Technical Support Learning – F3
Support Teaching .804 <.00

28. 3. Results of Data Analysis
3,65
3,70
3,75
3,80
3,85
3,90
3,95
4,00
4,05
Basic Technology Literacy Technical Support Learning Technical Support Teaching
In-service Pre-service
3,50
3,60
3,70
3,80
3,90
4,00
4,10
4,20
FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3
In-service Pre-service
4). The inferential analysis between in-
service and pre-service teachers
In-service
(n=248)
Pre-service
(n=250)
W Sig. r
Mean SD Mean SD
FA1 4.027 0.724 3.891 0.774 52457.50 .029 0.101
FA2 3.905 0.707 3.782 0.747 51782.00 .045 0.093

29. 3. Results of Data Analysis
4). Influencing factors_ Sex
-For pre-service teachers
Mann-Whitney U test _ no significant
differences
3,5
3,6
3,7
3,8
3,9
4
4,1
4,2
FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3
Female Male
3,74
3,76
3,78
3,80
3,82
3,84
3,86
3,88
3,90
3,92
3,94
Basic Technology Literacy Technical Support Learning Technical Support Teaching
Female Male

30. 3. Results of Data Analysis
4). Influencing factors_ Sex
- For in-service teachers
Mann-Whitney U test _ no significant
differences
3,60
3,70
3,80
3,90
4,00
4,10
4,20
4,30
FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3
Female Male
3,70
3,75
3,80
3,85
3,90
3,95
4,00
4,05
4,10
Basic Technology Literacy Technical Support Learning Technical Support Teaching
Female Male

31. 3. Results of Data Analysis
4). Influencing factors_ Educational
degree
- For pre-service teachers
Kruskal-Wallis H test_ no significant
differences
2,50
3,00
3,50
4,00
4,50
5,00
FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3
College Bachelor Master/PhD
3,70
3,75
3,80
3,85
3,90
3,95
4,00
4,05
4,10
Basic Technology Literacy Technical Support Learning Technical Support Teaching
College Bachelor Master/PhD

32. 3. Results of Data Analysis
4). Influencing factors_ Educational
degree
- For in-service teachers
Kruskal-Wallis H test _ FB3, FC1
and FC2
Technical Support Learning &
Teaching.
3,40
3,60
3,80
4,00
4,20
4,40
4,60
FA1 FA2 FA3 FB1 FB2 FB3 FC1 FC2 FC3
College Bachelor Master/PhD
3,65
3,70
3,75
3,80
3,85
3,90
3,95
4,00
4,05
4,10
4,15
Basic Technology Literacy Technical Support Learning Technical Support Teaching
College Bachelor Master/PhD

33. 3. Results of Data
Analysis
4). Influencing factors_ Age
- For pre-service teachers
The linear correlation
coefficient_ Positive
Pre-service Rxy Sig.
Age – FA1 Consciousness and attitude .168 .003
Age – FA2 Technical environment .088 .116
Age – FA3 Information Ethics and Information
Security
.062 .273
Age – FB1 Self-learning .092 .099
Age – FB2 Communication and collaboration .135 .016
Age – FB3 Research and innovation .094 .094
Age -- FC1 Resource preparation .113 .044
Age -- FC2 Process design .114 .043
Age -- FC3 Practice reserve .133 .019
Age – FA Basic Technology Literacy .124 .027
Age – FB Technical Support Learning .115 .039
Age – FC Technical Support Teaching .112 .046

34. 3. Results of Data
Analysis
4). Influencing factors_ Age
- For in-service teachers
The linear correlation
coefficient_ Negative
In-service Rxy Sig.
Age – FA1 Consciousness and attitude -.005 .927
Age – FA2 Technical environment -.117 .044
Age – FA3 Information Ethics and Information
Security .029 .615
Age – FB1 Self-learning -.051 .385
Age – FB2 Communication and collaboration -.175 .003
Age – FB3 Research and innovation -.116 .046
Age – FC1 Resource preparation -.111 .058
Age – FC2 Process design -.102 .081
Age – FC3 Practice reserve -.073 .213
Age – FA Basic Technology Literacy -.029 .624
Age – FB Technical Support Learning -.128 .028
Age – FC Technical Support Teaching -.099 .091

35. 3. Assessment of Teachers ́ Digital Competence:
Results of Data Analysis
4). Influencing factors_
teaching experience
- For in-service teachers
The linear correlation
coefficient_ Negative
In-service teachers Rxy Sig.
FA1 Consciousness and attitude -.088 .173
FA2 Technical environment -.173 .007
FA3 Information Ethics and Information
Security
-.040 .537
FB1 Self-learning -.151 .019
FB2 Communication and collaboration -.223 <.001
FB3 Research and innovation -.224 <.001
FC1 Resource preparation -.232 <.001
FC2 Process design -.234 <.001
FC3 Practice reserve -.193 0.003
F1 Basic Technology Literacy -.108 .096
F2 Technical Support Learning -.222 <.001
F3 Technical Support Teaching -.236 <.001

36. 3. Results of Data
Analysis
4). Influencing factors _
school type, available
hardwires, available project.
- For in-service teachers
Available
laptop / tablet
Yes
(n=205)
No (n=18) W Sig. r
Mean SD Mean SD
FB3 3.856 0.71 3.460 0.78 2422.5 .026 .313
Available
smartboard
interactive
Yes
(n=200)
No
(n=22)
W Sig. r
Mean SD Mean SD
FC2 3.882 0.671 3.659 0.542 2764.50 .048 .257
Available
project
Yes
(n=205)
No
(n=20)
W Sig. r
Mean SD Mean SD
FA2 3.910 0.738 3.500 0.541 2911.50 .002 .420
FB3 3.860 0.715 3.500 0.827 2648.50 .030 .292
FC1 3.934 0.607 3.656 0.583 2691.50 .020 .313
FB 3.910 0.627 3.631 0.593 2681.50 .023 .308

37. 4. Educational Training Program:
Justification
Teacher
educators
as a role
models
Learning
instructional
design with
technology
The training
modality
The
reflection on
the role of
technology
in education
Authentic
technology
experiences
Five main clear strategies
for Chinese teacher training:

38. 4. Educational Training Program:
Program Design
• Target population:
Pre-and in-service teachers in Anhui Province.
• The used framework for training program:
The 3rd edition of UNESCO ICT Competency Framework for Teachers.
• Competences:
Transversal competences & General teacher digital competences
• Resources required:
Human resources: tutors, content experts, and technologists.

39. 4. Program Design
• Description of each training
modules
• Training duration
5 Modules
27 (lessons)
Target
Group
7 Months
M1 M2 M3 M4 M5 M6 M7
1º (2 lessons) In-service
2º (7 lessons) Both
3º (5 lessons) Both
4º (7 lessons) In-service
5º (6 lessons) In-service
Module 1 _ Understanding ICT in Education Policy
Module 2 _ Application of Digital Skills
Module 3 _ Curriculum and Assessment
Module 4 _ Design ICT-supported project- based learning activities
Module 5_ Organization and Administration

40. 4. Program Design
• Assessment of training program
1. Formative assessment
• Media for assessment
• Assessment techniques
• Assessment instrument/s
• Evaluation standards
2. Summative assessment
With the development of the program, the teacher will
obtain a numerical grade [0- 100 points] in the final course,
which is formatted by three parts of grade:
• the attendance rate (20 %)
• the classroom performance (20 %)
• the classwork and homework (60 %).

41. 5. Discussion:
Level of Chinese teachers´ digital competence
Good perception of digital competence
 Chen et al. (2019), Galindo- Domínguez and Bezanilla (2021) and Valtonen et al. (2021).
Good consciousness and attitude
 The earlier studies (Chen, Zhou, & Wu, 2020; Li et al., 2019; Ma et al., 2019) in the
 Chen, et al. (2020), which was concentrated in a different eastern province of China.
Technical support practice is not strong
 The earlier studies in other countries (Charbonneau-Gowdy, 2015; Munyengabe et al., 2017; Ogodo et al., 2021; Valtonen
et al., 2015; Wikan & Molster, 2011).

42. 5. Discussion:
Influencing factors
Age (in-service teachers )
younger teachers have higher level.
 Barahona et al. (2020) and Li, Liao, et al. (2016).
 Nieto-Isidro et al. (2022) indicated, older teachers have similar levels of technical proficiency and higher levels of teaching
use ICT skills.
Teaching experience (in-service teachers )
with less teaching experience have higher level.
 HIinojo-Lucana et al. (2019) and Pozo Sánchez et al. (2020), and Lucas et al. (2021)
o analysis methods is different: the multiple linear regression approach.
o the specific characteristics of the population sample (Spanish teachers VS Chinese teachers).

43. 5. Discussion:
influencing factors
Sex
No impact
 The studies of Cabero Almenara, 2017 and Tondeur et al., 2018.
 Guillén-Gámez et al. (2021), which following the order established in the various steps of the regression models
Educational background (in-service teachers)
 Zhao et al. (2021)
 studies from different countries: Portillo et al. (2020)
ICT training courses
No impact
 Li, Wu, et al. (2016)

44. 6. Conclusion
The objectives were achieved in the study :
• Identify frameworks related to digital competence and its key
components for teachers in China.
• Design and validate a questionnaire to evaluate pre-and in-
service teachers´ digital competences.
• Determine teachers ´s digital competence in Anhui province.
• Design a training course for Chinese pre-service and in-service
teachers.

45. Limitations and further research directions
• Sample size
• Self-report data
• Research design
• Formulation of objectives
• Aims of the research.

46. The publications derived
from this doctoral thesis
• Yang, L., García-Holgado, A., & Martínez-Abad, F. (2020).
A Study to Analyze the Digital Competence of Pre-service
Teachers and In-service Teachers in China [Conference
paper]. ACM International Conference Proceeding Series,
Salamanca (Spain).
https://www.scopus.com/inward/record.uri?eid=2-s2.0-
85100581757&doi=10.1145%2f3434780.3436642&partnerI
D=40&md5=b93 ad74390101ec12e5ed434e3a35925
• Yang, L., García-Holgado, A., & Martínez-Abad, F. (2021).
A Review and Comparative Study of Teacher's Digital
Competence Frameworks: Lessons Learned. In F. J. García-
Peñalvo (Ed.), Information Technology Trends for a Global
and Interdisciplinary Research Community (pp. 51-71). IGI
Global. https://doi.org/10.4018/978-1-7998-4156-2.ch003
(36 of 96 in SPI– Q2 – ICEE 79).

47. The publications derived
from this doctoral thesis
• Yang, L., Martinez-Abad, F., & Garcia-Holgado, A. (2022).
Exploring factors influencing pre-service and in-service
teachers ' perception of digital competence in the Chinese
region of Anhui. Education and Information Technologies.
https://doi.org/10.1007/s10639-022-11085-6 (JCR SSCI -
EDUCATION & EDUCATIONAL RESEARCH– Q1 (62 de
270) - JIF 3.666).
• Yang, L., García-Holgado, A., & Martínez-Abad, F. (2023).
Digital Competence of K-12 Pre-service and In-Service
Teachers in China: A Systematic Literature Review. Asia
Pacific Education Review (JCR SSCI - EDUCATION &
EDUCATIONAL RESEARCH– Q3 (184 de 270) - JIF 1.823).
(Under review)

48. Evaluation of Pre-service and In-
service Teachers ́ Digital
Competence in Anhui Province,
China
Ph.D. Thesis
Candidate: Li Yang
Supervisors:
Dr. Fernando Martínez-Abad, Ph.D.
Dra. Alicia García- Holgado, Ph.D.
Thanks!