




































BANGLADESH JOURNAL OF MULTIDISCIPLINARY SCIENTIFIC RESEARCH 11(1) (2026), 43-54 

 

43 

        MULTIDISCIPLINARY SCIENTIFIC RESEARCH 
          BJMSR VOL 11 NO 1 (2026) P-ISSN 2687-850X E-ISSN 2687-8518 

         Available online at https://www.cribfb.com 

     Journal homepage: https://www.cribfb.com/journal/index.php/BJMSR 

                                                                                                                                                                                                    Published by CRIBFB, USA 

                                                                                                                              

FORMATION OF DIGITAL COMPETENCES OF STUDENTS IN THE 

SYSTEM OF HIGHER PEDAGOGICAL EDUCATION        

              
 Zabiyeva Kamshat Kazbekovna (a)   Zhiyembayev Zhomart Tumarbekovich (b)1  Seitova Sabyrkul (c)    

 Kalzhanova Gulmira Kenesovna (d)    Yesseikyzy Aiym  (e)    
 

(a) Lecturer, Zhetysu University named after I. Zhansugurov, Taldykorgan, Kazakhstan; E-mail: kamshatzabieva@gmail.com 
(b) Lecturer, Zhetysu University named after I. Zhansugurov, Taldykorgan, Kazakhstan; E-mail: zht.zhiembayev@gmail.com 
(c) Professor, Zhetysu University named after I. Zhansugurov, Taldykorgan, Kazakhstan, E-mail: s.m.seitova@gmail.com 
(d) Director of the Center for Competencies and Additional Education, Zhetysu University named after I. Zhansugurov, Taldykorgan,    Kazakhstan, E-

mail: kgk67@mail.ru 
(e)Lecturer, Zhetysu University named after I. Zhansugurov, Taldykorgan, Kazakhstan; E-mail: aiym.yesseykyzyy@gmail.com 

 

 
A R T I C L E I N F O 

 
 

Article History: 

 
Received: 28th August 2025 

Reviewed & Revised: 28th August 2025 

to 6th December 2025 

Accepted: 10th December 2025 

Published: 12th December 2025 

 
Keywords: 

 

Digital Competences, Higher Pedagogical 

Education, Digital Literacy, Professional 

Training, Innovative Teaching 

 
JEL Classification Codes: 

 

      I21, I23, I25, O33, M15 

 
      Peer-Review Model:  

 

      External peer review was done through  

      double-blind method.        

 
A B S T R A C T      
 

Given the ongoing digitalization in modern education worldwide, it is important to determine the 

features of the development of digital competence among future teachers. The research problem lies in 

the insufficient understanding of how innovative digital interventions affect the development of these 

competences in teacher education. The purpose of this study is to find out the impact of innovative 

(digital) intervention on the development of digital competence of future teachers. A mixed-method 

design was used, combining qualitative and quantitative approaches. A total of 186 students of 

pedagogical specializations participated in the study. Participants were divided into two groups: 
experimental (n = 93), who underwent an intervention program, and control (n = 93), who studied 

according to the traditional program. The primary data were collected using a digital competence 

questionnaire (28 items), performance tasks ("Micro-lesson" and "Mini-module in LMS"), LMS 

analytics, and semi-structured interviews. Moreover, descriptive statistics, paired t-tests, ANCOVA 

controlling for pre-test indicators, and effect size calculations were used for data analysis. The results 

confirmed that the experimental group recorded a significant increase in digital competences in all 

domains (Δ = +2.1–+3.6; p < 0.001; d = 0.63–0.88). In addition, the intervention was more effective 
among students with a lower initial level of competencies (F(1,182) = 8.47; p < 0.01), as well as among 

students in pedagogical and humanitarian specialties. The findings suggest that targeted digital 

interventions can substantially improve the development of digital competence in future teachers. 

 
 

© 2025 by the authors. Licensee CRIBFB, USA. This open-access article is distributed under the 
terms and conditions of the Creative Commons Attribution (CC BY) license 
(http://creativecommons.org/licenses/by/4.0).  

            

       

INTRODUCTION 

Active digitalization processes have influenced the transformation of the modern educational space and increased the 

requirements for the professional training of future teachers. Accordingly, a modern teacher must be proficient with ICT 

tools and incorporate them into educational strategies, ensure academic integrity, and promote inclusive teaching. In this 

context, developing digital competencies among students in higher education institutions is an important and even necessary 

condition for ensuring the quality of education in the coming years (Salas-Pilco & Yang, 2022). The relevance of this issue 

is heightened by the fact that the level of digital competence of future teachers has a “multiplicative” effect: it influences 

the digital literacy of hundreds of their future students and the overall use of technology in educational institutions.  

The main research challenge is the scientific justification and empirical validation of pedagogical interventions that 

enhance the digital competencies of future teachers in key areas and facilitate their sustainable integration into pedagogical 

practice. In the scientific field, much has already been established. In particular, the conceptual apparatus of "digital 

competence" and its structural components have been developed. The general trends of the digital transformation of 

education and the prominent examples of the use of digital tools in teaching have also been discussed. The proposed study 

is valuable. In particular, in theoretical terms, it aims to expand accepted ideas about the structure of digital competencies 

for a future teacher by integrating the DigCompEdu/TPACK/ISTE provisions into a holistic model. In a practical sense, the 

study will propose a quasi-experimental design with pre- and post-measures in the control and experimental groups during 

                                                 
1Corresponding author: ORCID ID: 0000-0003-2280-3210 

© 2025 by the authors. Hosting by CRIBFB. Peer review under responsibility of CRIBFB, USA.  

https://doi.org/10.46281/bjmsr.v11i1.2760 

 
To cite this article: Kazbekovna, Z. K., Tumarbek, Z. Z., Sabyrkul, S., Kenesovna, K. G., & Aiym, Y. (2025). FORMATION OF DIGITAL 

COMPETENCES OF STUDENTS IN THE SYSTEM OF HIGHER PEDAGOGICAL EDUCATION. Bangladesh Journal of Multidisciplinary Scientific 

Research, 11(1), 43-54. https://doi.org/10.46281/bjmsr.v11i1.2760 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://www.openaccess.nl/en
https://doi.org/10.46281/bjmsr.v11i1.2760
https://orcid.org/0000-0002-1459-6541
https://orcid.org/0000-0003-2280-3210
https://orcid.org/0000-0003-4352-6355
https://orcid.org/0000-0001-5043-9984
https://orcid.org/0000-0002-1216-5828


Kazbekovna et al., Bangladesh Journal of Multidisciplinary Scientific Research 11(1) (2026), 43-54

 

 
44 

one educational module. Such an approach will not only allow recording students' subjective perceptions of their own skills, 

but also evaluating real actions and didactic solutions. 

The study will aim to substantiate and empirically verify the effectiveness of targeted pedagogical intervention in 

the formation of digital competencies of students of higher pedagogical education institutions by identifying its general 

impact, the most progressive domains of competence, and the individual and contextual factors that modify this effect. Thus, 

this article will fill the gap between the declarative description of digital competencies and a proven model of their formation 

in future teachers.  

 

LITERATURE REVIEW 

The development of digital competencies among higher pedagogical education students is recognized in modern science as 

a key condition for preparing specialists who can act productively even amid the digital transformation of society. In 

international scientific literature, the term "digital competence" is often understood to refer to established international 

frameworks, such as DigCompEdu (Basantes-Andrade et al., 2022; Zhao et al., 2021a). In such conditions, it is an obvious 

integration of knowledge, skills, and attitudes that ensures future educators' ability to critically apply digital tools in teaching, 

educational content creation, assessment, and, especially, their own independent professional development. Researchers 

emphasize the multidimensional nature of this phenomenon: technical and methodological skills are closely intertwined, 

and individual communicative aspects are linked to ethical considerations (Zarubina et al., 2024; Kozhasheva et al., 2022). 

Current scholars have noted that the digital competencies of future educators should be closely linked to the 

development of professional autonomy and specific aspects of innovative culture (Pantani et al., 2025; Trujillo-Juárez et al., 

2025). It is considered that the more students use digital technologies, the more they will develop the ability to creatively 

adapt and independently solve available pedagogical problems in the future. Firstly, this is necessary for Kazakhstan's 

university system, as digital transformation has been declared a national priority (Dzhanegizova, 2024). Official programs 

and strategies emphasize the need to prepare competitive teachers who must possess modern information technologies, 

making them valuable employees in today's digital knowledge economy. 

In the context of studying the Kazakh case, the issue of acquiring digital competencies is extensive due to the 

implementation of state digitalization programs and strategic development programs in this field, which are aimed at 

integrating digital technologies and artificial intelligence into the education sector (Andekina & Anartayeva, 2022; 

Ergasheva et al., 2025). Official programs and their active support at the highest level indicate the need to change teacher 

training to equip teachers to process new material, integrate into digital environments, and actively use the latest 

technologies to implement the educational process. At the same time, Kazakhstan has implemented separate educational 

initiatives aimed at improving pedagogical education and transforming it in accordance with modern requirements (Gulmira 

et al., 2024). For example, such educational changes were based on the importance of developing digital platforms, using 

programs to upskill future teachers, and effectively designing educational courses focused on developing information, 

communication, and digital skills (Sultan et al., 2025). 

In some studies, the analysis of various competency frameworks (DigCompEdu, TPACK, and ISTE Standards for 

Educators) has also been emphasized. However, experimental tests of the effectiveness of targeted educational interventions 

specifically for students of pedagogical specialties remain insufficiently studied. 

Moreover, current empirical studies conducted at universities in Kazakhstan are noteworthy (Shaimukhanova et 

al., 2024; Buzaubakova & Nurmanaliyeva, 2021). Researchers have confirmed that educators in the future will be aware of 

the importance of acquiring digital competencies (including independently), but the level of competencies obtained and their 

development remain quite uneven (Jakubakynov et al., 2024; Babu et al., 2025; Pande et al., 2024; Al Hunaini et al., 2025; 

Zhou et al., 2025; Hasan & Surjamokhey, 2022). Kurakbayeva & Xembayeva, 2025). The greatest successes have been 

achieved through the application of basic tools and well-known online platforms. However, the following more complex 

skills related to pedagogical design, the use of artificial intelligence in teaching, online work, and critical thinking about 

digital content are still underdeveloped (Kapasheva et al., 2024). Methodologically, most studies rely on student surveys 

and self-assessments – these tools somewhat limit the possibility of in-depth analysis of the effectiveness of educational 

innovations. Kuratova et al. (2016) highlighted the importance of using modern technologies to organize the educational 

process. In addition, Partsei et al. (2025) proved the effectiveness of mobile learning applications. Bilyk et al. (2025) also 

identified the importance of using innovations for training specialists.   At the same time, existing scientific discussions 

have highlighted specific problems. Among them, the lack of a unified national model of digital competencies for 

pedagogical education should be highlighted first and foremost (Kolm et al., 2021). Another pressing challenge is the 

insufficient integration of digital technologies into educational programs, and the limited ability of university lecturers to 

use digital tools even as auxiliary mechanisms, let alone as full-fledged didactic resources (Neagu, 2022). An additional 

risk, as noted in a few studies, is the disparity in the levels of material and technical support for universities (Raza & Pate, 

2023; Mazur et al., 2025), which also indirectly affects the quality of future education for students. Despite numerous 

scientific publications on the digitalization of education, there remains a lack of empirically supported models for 

pedagogical specialties that synthesize the didactic, psychological, and instrumental aspects of developing digital 

competencies (Nurtayeva et al., 2024). Most research focuses either on describing platforms and tools (e.g., LMS, interactive 

services) or on general approaches to integrating ICT into teaching (Temirkhanova et al., 2024; Sillat et al., 2021).  

Even considering these results, despite the increased research activity, there are noticeable gaps in the current 

scientific field that require further investigation. Firstly, there is a lack of empirical research to assess the dynamics of digital 

competence development among students in pedagogical specialties throughout their studies. Also noteworthy is the lack 



Kazbekovna et al., Bangladesh Journal of Multidisciplinary Scientific Research 11(1) (2026), 43-54

 

 
45 

of comprehensive studies that combine quantitative results with existing theoretical data, thereby providing a deeper analysis 

of educational practices. Thirdly, the issues concerning the integration of artificial intelligence into the training of future 

teachers, including through the lens of determining the consequences of digital interventions on students' professional 

identity, have not been sufficiently researched. Therefore, current directions for further research include developing 

localized frameworks for digital competencies that account for the specifics of Kazakhstan's educational policy and 

sociocultural context. 

Accordingly, the purpose of the study is to substantiate and empirically verify the effectiveness of targeted 

pedagogical intervention in the formation of digital competencies of students of higher pedagogical education institutions 

in Kazakhstan. Taking into account the theoretical analysis and previous empirical results, the following hypotheses were 

formulated: 

 

 H1: Targeted pedagogical intervention provides a statistically significant increase in the overall level of digital 

competencies of students compared to traditional learning. 

 H2: The most significant growth is observed in the domains of digital competence related to content creation, 

communication, collaboration, and assessment using ICT. 

 

MATERIALS AND METHODS 
Research Design 

The problem of developing digital competencies is multidimensional, encompassing objective indicators (levels of task 

performance, changes in questionnaire indices) and subjective aspects (student perceptions, barriers, motivation). Therefore, 

it is advisable to use a mixed approach. Based on this type, quantitative data will allow us to highlight the scale and 

significance of changes. In contrast, qualitative data will influence the explanation of "why" and "how" these changes 

occurred. 

The study was designed as a quasi-experimental mixed design. This involved a combination of quantitative and 

qualitative methods. The quantitative part is based on a pre-post testing scheme with two groups: the experimental group 

(EG) - students undergoing a targeted pedagogical intervention to develop digital competencies; and the control group (CG) 

- students studying according to a traditional program without a specifically developed digital component. This design 

enabled assessment of the intervention's effectiveness by comparing changes in digital competence levels across groups. 

 

Participant Characteristics and Sampling Procedures 

Full-time students of pedagogical specialties of a higher education institution were involved in the study. The planned 

sample size is N = 186 people. 

The primary selection method is cluster selection based on already formed academic groups (intact classes), with 

subsequent unguided distribution of groups across the research conditions. To reduce systematic differences between 

conditions, comparative alignment is used; in particular, pairs of academic groups with similar characteristics (course, 

specialty, grade point average, previous ICT experience) were selected. 

 

Accordingly, the following students participated in the study 

Experimental group (EG): n=93 students (underwent a targeted intervention to develop digital competencies) 

Control group (CG): n=93 students (studied according to the usual program without a specially organized digital component. 

In the case of unequal clusters, a slight asymmetry (up to ±10%) was allowed and will be taken into account during 

analysis. 

The sample was formed according to the main criteria and was purposive. The main inclusion criteria were studying 

in the 2nd–4th year of a pedagogical specialty, participation in an educational module in which the intervention could be 

implemented, and written consent to participate. 

Exclusion criteria were incomplete completion of key stages (absence at pre- or post-measurement; >30% missed 

intervention classes) and refusal to process personal data/consent to participate. Table 1 presents basic data on the study 

participants. 

 

Table 1. Demographic characteristics of the student sample (N = 186) 

 
Indicator EG (n = 93) CG (n = 93) Total (N = 186) 

Gender 
   

– Women 68 (73.1 %) 70 (75.3 %) 138 (74.2 %) 

– Men 25 (26.9 %) 23 (24.7 %) 48 (25.8 %) 

Age (years) 
   

– 18–19 28 (30.1 %) 30 (32.3 %) 58 (31.2 %) 

– 20–21 45 (48.4 %) 43 (46.2 %) 88 (47.3 %) 

– 22 and over 20 (21.5 %) 20 (21.5 %) 40 (21.5 %) 

Course of study 
   

– 2nd year 32 (34.4 %) 30 (32.3 %) 62 (33.3 %) 

– 3rd year 34 (36.6 %) 36 (38.7 %) 70 (37.6 %) 

– 4th year 27 (29.0 %) 27 (29.0 %) 54 (29.0 %) 

Specialty 
   



Kazbekovna et al., Bangladesh Journal of Multidisciplinary Scientific Research 11(1) (2026), 43-54

 

 
46 

– Primary education 30 (32.3 %) 31 (33.3 %) 61 (32.8 %) 

– Preschool education 22 (23.7 %) 21 (22.6 %) 43 (23.1 %) 

– Secondary education (mathematics) 20 (21.5 %) 19 (20.4 %) 39 (21.0 %) 

– Secondary education (philology) 21 (22.6 %) 22 (23.7 %) 43 (23.1 %) 

Note. EG = Experimental Group; CG = Control Group. Percentages are calculated within each group. 

Source: Author’s development  
 

Experimental Manipulations or Interventions 

The intervention was carried out during one training module (12 weeks) within the framework of pedagogical disciplines. 

The lesson was conducted in the format of classroom meetings + online activities in the LMS. 

The program provided for the active, consistent development of digital competencies across the key domains of 

the DigCompEdu and TPACK frameworks. In particular, in week 1, students were introduced to the program's purpose and 

objectives. At this stage, a diagnosis of the initial level of digital competencies (pre-test) was carried out, and the LMS was 

introduced. 

 

The Planning of Training Sessions Using ICT was also Carried Out 

At the next stage (week 4-5), interactive platforms (Padlet, Mentimeter, Google Docs) were actively used, and group work 

and peer-to-peer learning in an online environment were organized. 

At week 6-7, digital content was created. This stage involved developing interactive presentations, educational 

videos, and microcourses. Also at this stage, various tools for visualization and multimedia support were used. 

In weeks 8-9, online tests were designed, formative assessment was applied, and LMS analytics were used. 

Weeks 10-11 focused on ethics and security. In particular, familiarity with confidentiality and data protection was 

established. 

The final stage (week 12) involved completing a practical task: forming and presenting a mini-lesson using digital 

technologies. 

At this stage, post-testing was also provided, and focus groups were held to collect qualitative data (reflection, 

barriers, suggestions) (See Table 2). 

 

Table 2. Intervention plan for the formation of students' digital competencies 

 
Week Module content Tools and forms of work Competency domain 

(DigCompEdu/TPACK) 

Expected results 

1 Introduction. 

Diagnostics of the level 
of digital competencies 

Pre-test (online questionnaire Google 

Forms/SurveyMonkey); introductory lecture; 
LMS (Moodle/Google Classroom) 

instruction 

Professional engagement / 

Knowledge of context 

Awareness of goals; orientation 

in LMS; determination of 
starting level 

2–3 Information literacy and 
digital pedagogy 

Resource search workshop (Google Scholar, 
ERIC, ResearchGate); working with 

Zotero/Mendeley; LMS lesson planning 

Information & data literacy / 
Content knowledge + 

Pedagogical knowledge 

Ability to find, critically 
evaluate sources; integrate 

resources into curricula 

4–5 Communication and 

collaboration 

Using Padlet, Mentimeter, Google 

Docs/Slides, LMS online forums, and peer-
reviewed group assignments 

Digital communication & 

collaboration / PCK 

Online interaction skills, 

organization of teamwork, and 
development of critical thinking 

6–7 Digital content creation Canva, Powtoon, Genially, Loom, Edpuzzle; 

creating interactive presentations and 

educational videos 

Digital content creation / 

Technological pedagogical 

knowledge (TPK) 

Development of skills to 

develop multimedia materials 

and interactive courses 

8–9 Assessment and 

feedback 

Kahoot, Quizizz, Google Forms, LMS 

analytics; formative assessment; online 
rubrics 

Assessment & feedback / 

TPK + PCK 

Ability to use digital tools for 

assessment; skills to work with 
analytics 

10–

11 

Ethics, safety, inclusion Discussions; case analysis; Creative 

Commons search; introduction to GDPR/data 

protection; UDL (Universal Design for 
Learning) principles 

Digital responsibility / PK + 

CK 

Awareness of copyright issues, 

confidentiality, and the 

development of a culture of 
inclusion 

12 Summary: integrated 

mini-lesson 

Presentation of the developed lesson using 

digital technologies; post-test; focus groups 

Integrated digital 

competence / Technological 
pedagogical content 

knowledge (TPACK) 

Demonstration of 

comprehensive digital 
competencies; reflection and 

self-assessment 

Note. LMS – Learning Management System; PCK – Pedagogical Content Knowledge; TPK – Technological Pedagogical Knowledge; TPACK – 

Technological Pedagogical Content Knowledge; UDL – Universal Design for Learning; GDPR – General Data Protection Regulation. 
Source: Author’s development 

 

Instruments and Measures 

Data collection tools that combined quantitative and qualitative methods were used. In particular, a self-assessment 

questionnaire for digital competencies was used, based on the DigCompEdu and TPACK frameworks. It contained blocks 

of questions reflecting six key domains of digital competencies: information literacy, digital pedagogy, communication and 

collaboration, digital content creation, ethics and security, and assessment using ICT. The questionnaire also had a scaled 

structure (1-5), which made it possible to obtain an integral index of digital competencies (See Appendix A). To overcome 

the limitations of self-reported data, the study used a range of practical tasks. The first of them was a "Micro-lesson using 

digital technologies", within which students prepared and delivered short lessons integrating digital tools (See Appendix B). 

The next task involved the formation of a "Mini-module in the LMS" (See Appendix C). This consisted of creating a learning 



Kazbekovna et al., Bangladesh Journal of Multidisciplinary Scientific Research 11(1) (2026), 43-54

 

 
47 

segment using electronic resources, interactive tasks, and an assessment system. Both tasks were determined by developed 

rubrics with clear criteria (pedagogical expediency, interactivity, assessment and feedback, inclusiveness). This allowed us 

to record the real level of mastery of digital tools in pedagogical activity. 

An additional source of data was the consideration of logs and analytics of the learning management system (LMS). 

This made it possible to obtain objective indicators of engagement: the number of entries, task completion, participation in 

discussions, and the timeliness of work submissions. 

To expand understanding of the features of competency development, semi-structured interviews were conducted 

in focus groups with students in the experimental group (See Appendix D). 

 

Reliability and Validity 

The quality of the instruments was assessed against several parameters: the internal consistency of the questionnaire 

(Cronbach's α) and the inter-rater consistency in the assessment of practical tasks. The questionnaire (I1) demonstrated an 

acceptable level of internal consistency: Cronbach's α = 0.81 for the integral scale and 0.68-0.76 for the individual domains. 

For the "Micro-lesson" (I2) assessment rubric during the double assessment, the inter-rater consistency coefficient, 

Cohen's κ, was 0.72. 

Similarly, for the task "Mini-module in the LMS" (I3), the consistency coefficient of expert assessments was ICC 

= 0.79. These indicators indicated reliability. 

The definition of LMS analytics (I5) did not require a traditional reliability assessment; however, the technical 

stability of the logs, which ensures the reproducibility of the indicators, was checked. 

 

Data Analysis  

Data analysis was carried out using both quantitative and qualitative methods. However, at the initial stage, the data set was 

checked for completeness and correctness. Multiple imputation was used to handle missing values (less than 10%). This, in 

turn, enabled the sample to remain representative. The distribution of variables was previously checked, and possible outliers 

were identified. 

Descriptive statistics were used to assess the intervention's effectiveness. In particular, mean values, standard 

deviations, medians, quartiles, and confidence intervals were calculated for the leading indicators (digital competence 

indices, performance task results, LMS data). 

Within the groups (experimental/control), paired t-tests (or the nonparametric equivalent, the Wilcoxon Signed 

Rank Test) were performed to compare pre- and post-results. 

Intergroup differences were analyzed using ANCOVA, with the post-indicator as the dependent variable and the 

pre-level as the covariate. Cohen's d was also calculated for pairwise comparisons. A correlation analysis was performed, 

including a validity check of the questionnaire results and performance task scores (Pearson's r and Spearman's r). The focus 

group interviews were analyzed using thematic analysis. This included transcribing the recordings, initial familiarization 

with the data, and open coding of participants' statements. The next stage was grouping codes into categories corresponding 

to barriers and facilitators of digital competence development. 

To ensure the reliability of the qualitative analysis, two independent researchers coded 20% of the corpus, and 

consistency was checked using Cohen's κ (≥ 0.70). 

 

RESULTS 

The targeted intervention led to higher student performance than traditional teaching. At the pre-test stage, no statistically 

significant differences (p > 0.05) were found between the control (M = 45.3; 95% CI [43.9–46.7]) and experimental groups 

(M = 46.1; 95% CI [44.6–47.6]). This indicated their initial equivalence. 

After the intervention, the mean score in the experimental group increased significantly (M = 62.9; 95% CI [61.5–

64.3]), while the increase in the control group was minimal (M = 50.4; 95% CI [48.9–51.9]). Between-group analysis using 

ANCOVA confirmed a statistically significant difference in favor of the experimental group, F(1,183) = 27.60, p < 0.001, 

partial η² = 0.18. The effect size was large (Cohen’s d = 0.82), indicating a substantial practical impact of the intervention 

 

Table 3. Integral level of digital competencies (EG and CG) 

 
Group 

 

Pre-test (M ± SD, 95% 

CI) 

Post-test (M ± SD, 95% 

CI) 

Δ F 

(ANCOVA) 

p partial η² 

(effect) 

Cohen’s 

d 

CG (n = 93) 45.3 ± 6.9 (43.9–46.7) 50.4 ± 7.0 (48.9–51.9) +5.1 1.82 > 0.05 0.02 (small) 0.22 

EG (n = 93) 46.1 ± 7.1 (44.6–47.6) 62.9 ± 6.4 (61.5–64.3) +16.8 27.60 < 

0.001 

0.18 (large) 0.82 

Note. CG – Control Group; EG – Experimental Group; M – Mean; SD – Standard Deviation; CI - Confidence Interval; Δ – Mean difference between pre- 
and post-test; F(df) – ANCOVA test statistic with degrees of freedom; η² – Partial eta squared (effect size); Cohen's d - standardized mean difference. 

Source. The author's calculations are based on the results of the experimental study.  

 

The intervention had a differentiated impact. The most significant increase was recorded in the areas of digital 

content creation (Δ = +3.6; t(92) = 10.03; p < 0.001; η² = 0.21), assessment using ICT (Δ = +3.4; t(92) = 9.77; p < 0.001; η² 

= 0.20) and digital pedagogy (Δ = +3.2; t(92) = 9.21; p < 0.001; η² = 0.19). This determined that the practical tasks that 

required active integration of digital technologies into the pedagogical process affected students' skill development. 



Kazbekovna et al., Bangladesh Journal of Multidisciplinary Scientific Research 11(1) (2026), 43-54

 

 
48 

Moderate growth was recorded in the domains of communication and collaboration (Δ = +2.9; t(92) = 8.88; p < 

0.001; η² = 0.17) and information literacy (Δ = +2.7; t(92) = 8.45; p < 0.001; η² = 0.16). The smallest, although statistically 

significant, increase occurred in the area of ethics and safety (Δ = +2.1; t(92) = 6.12; p < 0.01; η² = 0.12). This can be 

explained by the relatively high starting level of students in this area. 

 

Table 4. Dynamics of digital competencies by domain (EG) 

 
Domain Pre-test (M ± 

SD) 

Post-test (M ± 

SD) 

Δ t(df) / F(df) p η² (effect) Cohen’s d 

Information Literacy 3.1 ± 0.7 5.8 ± 0.6 +2.7 t(92)=8.45 <0.001 0.16 0.74 

Digital Pedagogy 2.9 ± 0.8 6.1 ± 0.7 +3.2 t(92)=9.21 <0.001 0.19 0.81 

Communication and Collaboration 3.2 ± 0.6 6.1 ± 0.7 +2.9 t(92)=8.88 <0.001 0.17 0.78 

Content Creation 2.8 ± 0.9 6.4 ± 0.6 +3.6 t(92)=10.03 <0.001 0.21 0.88 

Ethics and Security 3.7 ± 0.7 5.8 ± 0.6 +2.1 t(92)=6.12 <0.01 0.12 0.63 

ICT Assessment 2.9 ± 0.8 6.3 ± 0.7 +3.4 t(92)=9.77 <0.001 0.20 0.85 

Note. M – Mean; SD – Standard Deviation; Δ – mean difference between pre-test and post-test; t(df) – Student’s t-test statistic with degrees of freedom; p 

– significance level; η² – partial eta squared (effect size); Cohen’s d – standardized mean difference. 
Source. The author's calculations are based on the results of the experimental study. 

 

However, the intervention's effectiveness depended on several individual and contextual factors. In particular, the 

initial level of digital skills significantly influenced the intervention's effect. Students with lower basic competencies 

demonstrated a greater increase in the integral index (Δ = +19.2) compared to those with a higher starting level (Δ = +12.4). 

The interaction "group × pre-test" was significant (F(1,182) = 8.47, p < 0.01, partial η² = 0.07). Thus, this indicated that the 

lower the initial level, the greater the intervention's impact. 

Secondly, the specialty of training had a specific modifying effect. The most significant increase was observed 

among students of pedagogical and humanitarian specialties (Δ = +17.8; Cohen's d = 0.85), while the increase was more 

moderate among students of technical specialties (Δ = +13.1; Cohen's d = 0.64). This is because the level of digital skills in 

technical subjects was already relatively high, and the potential for improvement was limited. 

Third, the course characteristics also mattered. In those groups where the instructor actively integrated digital tools 

into practical tasks (e.g., working with the LMS, digital assessment, collaborative projects), the intervention effect was 

significantly more potent (p < 0.001; η² = 0.09) (See Table 5). 

 

Table 5. Modification of the intervention effect by individual and contextual factors 

 
Factor Category Pre-test (M 

± SD) 

Post-test (M 

± SD) 

Δ F 

(ANCOVA) 

p partial η² 

(effect) 

Cohen’s 

d 

Baseline Level Low (bottom 50%) 42.1 ± 5.8 61.3 ± 6.1 +19.2 8.47 < 0.01 0.07 0.91  
High (top 50%) 49.7 ± 6.4 62.1 ± 6.7 +12.4 

   
0.66 

Specialty Education/Humanities 45.0 ± 6.7 62.8 ± 6.2 +17.8 6.92 < 0.01 0.06 0.85  
Technical 47.2 ± 7.1 60.3 ± 6.5 +13.1 

   
0.64 

Course features High digital integration 45.7 ± 6.9 64.0 ± 6.0 +18.3 11.24 < 0.001 0.09 0.89  
Low digital integration 46.0 ± 6.8 58.9 ± 6.6 +12.9 

   
0.61 

Note. M = mean; SD = standard deviation; Δ = mean gain (post-test − pre-test). F values are from ANCOVA models controlling for pre-test scores. Degrees 

of freedom were F(1,182) for baseline level, F(1,181) for specialty, and F(1,180) for course features. Partial η² indicates effect size. 

 

The diagram in Figure 1 illustrates the average increase (Δ) in students’ digital competences, considering both 

individual and contextual factors. The most significant changes were recorded among students with lower initial levels, 

those studying in pedagogical and humanitarian specialties. 

 

 
Figure 1. Intervention gains by moderators  

 

Figure 2 shows the standardized effect sizes (Cohen's d) for different moderator categories. Moderate effects were 

observed among students with a higher initial level, among representatives of technical specialties, and in courses with a 

smaller digital component. Thus, the effectiveness of the intervention depends mainly on individual and contextual factors. 

Baseline skills:
Low (bottom

50%)

Baseline skills:
High (top 50%)

Specialty:
Pedagogy/Huma

nities

Specialty:
Technical

Course features:
High digital
integration

Course features:
Low digital
integration

Gain (Δ) 19.2 12.4 17.8 13.1 18.3 12.9

0

5
10

15
20

25

G
A

IN
 (

Δ
)

Intervention Gains by Moderators



Kazbekovna et al., Bangladesh Journal of Multidisciplinary Scientific Research 11(1) (2026), 43-54

 

 
49 

 
Figure 2. Standardized effect sizes (Cohen’s d) for different categories of moderators 

 

The interviews conducted covered several individual and organizational-contextual factors that influenced the 

targeted intervention and explained the observed variability in results. The identified factors were interpreted in two 

dimensions: implementation barriers and facilitators (facilitating factors). Accordingly, the main barriers were technical 

issues (an unstable Internet connection, insufficient equipment, and software). An important drawback was students' low 

digital confidence and minimal prior experience. This, in turn, affected the difficulty of completing practical tasks at the 

initial stages. Cognitive overload was also noticeable, arising from the intensive introduction of new digital tools. This factor 

partially explained the intra-group variability in results, especially in the experimental group. At the same time, the key 

facilitators focus on pedagogical support and feedback. Collaborative learning strategies, including working together on 

"mini-modules in the LMS," were instrumental in facilitating peer learning and reducing the impact of individual barriers. 

The practical relevance of the tasks, which were directly related to future professional activities, also had a noticeable effect. 
 

DISCUSSIONS 

The results empirically confirmed both hypotheses. The first hypothesis (H1), that the targeted pedagogical intervention led 

to a statistically significant increase in students' overall digital competence compared to traditional learning, was fully 

confirmed. After completing the program, the experimental group showed an increase in average indicators of digital 

competence, indicating the effectiveness of the implemented modules and the integration of digital practices into the 

educational process. The results of this study showed the importance of creating a high-quality, innovative environment for 

the formation of digital competence of future teachers. Moreover, the results obtained demonstrated that the integrated 

intervention had a significant effect: the increase in the experimental group (Δ = +16.8) was significantly higher than in the 

control group (Δ = +5.1), with ANCOVA confirming a statistically significant difference (F(1,183) = 27.6; p < 0.001; η² = 

0.18). The effect size (Cohen’s d = 0.82) falls within the extensive range, indicating the practical significance of the 

intervention. 

The second hypothesis (H2), which predicted the most significant growth in the domains of digital competence 

related to content creation, communication, collaboration, and assessment using ICT, was also confirmed. The highest 

increases in indicators were observed precisely in areas focused on practical activities and interaction, which can be 

explained by the combination of blended learning tools (LMS, interactive services, video presentations) and elements of 

joint project work. Such data are consistent with studies confirming the effectiveness of practice-oriented methods of 

forming digital skills (integration of micro-lessons with digital tools, creation of training modules in LMS) (Timotheou et 

al., 2022; Suleimenova et al., 2023). Such approaches allow moving from declarative knowledge to functional mastery of 

digital resources. Within DigComp, the results indicate a transition of students from the "basic" to the "intermediate" and 

partially "higher" level of mastery. In particular, the European Digital Competence Framework has systematically identified 

five areas of digital skills: information and data work, communication and collaboration, digital content creation, security, 

and problem solving (Egusquiza et al., 2023; Inamorato dos Santos et al., 2023). It included 21 competence descriptors and 

four levels of mastery: from basic to expert. The specified framework has become the basis for national strategies and 

educational standards in many EU countries and is used by international organizations and leading technology companies 

(Microsoft, Intel) (Gallego Joya et al., 2025; Zhao et al., 2021b). In this sense, the study's results need to be interpreted in 

the context of local and international training tasks for future teachers. 

The analysis showed that the most potent effects were observed in digital content creation (Δ = +3.6; d = 0.88), 

ICT-based assessment (Δ = +3.4; d = 0.85), and digital pedagogy (Δ = +3.2; d = 0.81). This is consistent with the 

intervention's methodological design, which involved students completing tasks directly related to these domains: 

developing a "micro-lesson" and creating a "mini-module" in the LMS. More minor, but still significant, increases were 

recorded in the domains of information literacy (+2.7) and communication and collaboration (+2.9). The smallest increase 

was observed in  ethics and safety (+2.1), which is explained by the relatively high starting level of students. This picture is 

consistent with other studies, which indicate that ethical and safety aspects are more stable and form earlier (Ospanova et 

al., 2025; Sitaridis & Kitsios, 2023). Other works suggest that technologies offer new opportunities to improve the quality 

of teaching, learning, research, and organizational management (Spante et al., 2018; Kurmanov et al., 2024). Investing in 

the digital skills of teachers and students brings individual and organizational benefits (González-Pérez, & Ramírez-

Baseline skills:
Low (bottom

50%)

Baseline skills:
High (top 50%)

Specialty:
Pedagogy/Human

ities

Specialty:
Technical

Course features:
High digital
integration

Course features:
Low digital
integration

Cohen's d 0.91 0.66 0.85 0.64 0.89 0.61

0

0.2

0.4

0.6

0.8

1



Kazbekovna et al., Bangladesh Journal of Multidisciplinary Scientific Research 11(1) (2026), 43-54

 

 
50 

Montoya, 2022), in particular, the formation of quality education in innovative forms that meet the expectations and needs 

of students, and improved employability (Medeshova et al., 2025; Seitaliyeva et al., 2025). 

In particular, it is worth considering the initial level. Students with lower basic digital skills showed greater gains 

(Δ = +19.2; d = 0.91) than those with higher starting scores (Δ = +12.4; d = 0.66). This is consistent with the results of other 

authors, who indicated that the intervention is particularly effective for those who experience initial deficits—the fourth 

question concerned barriers and facilitators to implementing digital practices. Qualitative analysis revealed several key 

barriers: technical limitations (unstable internet, insufficient material and technical base), low digital confidence of students, 

as well as cognitive overload. This is also consistent with other scholars (Mo'minova, 2024; Jedrinović et al., 2024). In 

particular, the scientific literature indicates that the implementation of the processes of training students in digital 

competencies is based on the following principles: devices and conditions, goals and possibilities of their use in the 

educational process, the availability of educational materials, the availability of teachers capable of radically changing 

teaching methods and technologies in order to provide students with the appropriate digital competencies (Fernández-

Batanero et al., 2022). It is worth agreeing with the view that only the availability of digital technologies will create new 

opportunities for the development of human capital and the emergence of innovative "digital" industries across all areas of 

the economy and business (López-Nuñez et al., 2024). This means that after receiving higher education, future teachers 

must be able to use the digital competencies they have acquired to search for, access, analyze, and use information, as well 

as exchange data to fulfill their professional duties. Taking into account the data obtained and the results of other authors, 

the following criteria can be distinguished for determining the best service: 1. Multifunctionality. The presence of several 

functions in a digital tool. 2. Unification. A clear set of tools and rules, accessible and straightforward navigation. 3. Locality 

and confidentiality (Aubakirova et al., 2023; González Calleros et al., 2022). Team collaboration should be in a local 

network, and it does not mean that all information is generally available. 

It is also worth considering the study's scope. In particular, the key source of information was the self-assessment 

questionnaire for digital competencies, developed based on the DigCompEdu and TPACK frameworks. Despite a 

satisfactory level of reliability (Cronbach's α = 0.81), self-assessment always carries the risk of subjectivity and social 

desirability bias. This effect should be taken into account when reviewing the results. The duration of the intervention should 

also be considered. The intervention was carried out over a single academic semester, which does not allow for conclusions 

about the long-term stability of the acquired competencies. Further studies should involve a diverse sample and conduct 

long-term interventions. 

 

CONCLUSIONS 

The paper demonstrated the effectiveness of a targeted pedagogical intervention to develop students' digital competencies. 

The results showed that the EG achieved a significant, practically important increase in the integral index of digital 

competencies compared with the control group. The most significant growth was observed in areas related to practical 

pedagogical activities - digital content creation, digital pedagogy, and assessment using ICT. The study also identified 

several individual and contextual factors (initial skill level, specialty, and course features) that influenced the development 

of this competency. The results obtained are of great importance for educational practice and policy. First, the development 

of students' digital competencies requires the systematic integration of digital technologies into the educational process, 

rather than their use as an auxiliary tool. Second, teachers play a key role in overcoming barriers: their methodological 

support and feedback significantly enhance the effectiveness of digital interventions. Third, the most significant effect is 

achieved among students with a lower starting level, so educational programs should take into account individual learning 

trajectories. Despite the significant results, the study has several limitations. In particular, the use of a self-assessment 

questionnaire did not eliminate the risk of subjectivity. The intervention lasted only one semester, which does not allow for 

assessing the long-term stability of the results. Further research should focus on expanding the sample and extending the 

experiment duration. It is also worth monitoring the impact of digital interventions over time (1–2 years) to assess their 

stability and the transfer of results into professional activities. 
 

 

Author Contributions: Conceptualization, Z.K.K. and Z.Z.T.; Methodology, Z.K.K. and S.S.; Software, Z.K.K. and K.G.K.; Validation, Z.K.K., Z.Z.T. 

and Y.A.; Formal Analysis, Z.K.K, Y.A. and S.S.; Investigation, Z.K.K, Y.A.; Resources, .K.K., Z.Z.T. and Y.A; Data Curation, Z.K.K. and K.G.K.; 
Writing – Original Draft Preparation, Z.K.K. and K.G.K.; Writing – Review & Editing, K.K., Z.Z.T. and Y.A.; Visualization, Z.K.K. and S.S.; Supervision, 

Z.Z.T; Project Administration, Z.Z.T.; Funding Acquisition, Y.A. Authors have read and agreed to the published version of the manuscript. 

Institutional Review Board Statement: Ethical review and approval were waived for this study because the research does not involve vulnerable groups 
or sensitive issues. 

Funding: The authors received no direct funding for this research. 

Acknowledgments: Not applicable.  

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 

due to restrictions. 
Conflicts of Interest: The authors declare no conflict of interest. 

 

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APPENDICES 

Appendix A: Student Digital Competence Questionnaire (self-assessment from 1 to 5). 

Block 1. Information Literacy 

I can find reliable sources for educational activities through specialized search engines. 

I can evaluate the reliability and relevance of the information found. 

I organize and systematize digital materials using bibliography managers or cloud services. 

I teach students to check information and critically evaluate it. 

Block 2. Digital Pedagogy 

I plan lessons so that students work with shared online documents 

I use LMS (Moodle, Google Classroom) to organize the learning process. 

I combine digital and traditional teaching methods depending on the didactic goals. 

I can integrate interactive online tools (Kahoot, Mentimeter) into lessons to activate students. 

Block 3. Communication and Collaboration 

I organize student group work in a digital environment. 

I use digital tools to communicate with students outside of class. 

I can create an online environment for peer-to-peer learning and peer assessment. 

I maintain academic integrity in digital interaction. 

Block 4. Digital Content Creation 

I create my own multimedia materials (videos, interactive presentations). 

I adapt digital materials to the needs of different students. 

I use tools for data visualization (infographics, charts). 

I can integrate the created resources into LMS learning modules. 

Block 5. Assessment and Feedback 

I can configure automatic assessment criteria in the LMS. 

I use digital tools for formative assessment. 

I use different digital methods for individual feedback. 

Block 6. Ethics, safety, and inclusion 

I check licenses (Creative Commons, open) before using media in the course. 

I take confidentiality and the protection of personal data into account when working in an online environment. 

I ensure the inclusivity of digital resources 

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https://doi.org/10.3390/su132112184


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Block 7. Integrated competencies 

I can combine subject knowledge with digital technologies to create educational content. 

I integrate digital tools to meet the lesson's methodological objectives. 

I know how to select ICT qualitatively 

I evaluate the effectiveness of applied digital technologies 

 

Appendix B: Evaluation rubric for Micro-lesson using digital technologies 
 

Criterion 0 points (none) 1 point (low level) 2 points (average level) 3 points (high level) 

Pedagogical 

Appropriateness 

Does not meet 

objectives 

Partially compliant Compliant, but superficial Fully compliant, integrated into 

the lesson 

Interactivity and 

Collaboration 

None Minimal elements A few interactive elements Thoughtful interactivity, 
effective collaboration 

Assessment and 

Feedback 

None Insufficiently structured Partially organized Clear formative assessment, 

timely feedback 

Inclusion and UDL Not taken into 
account 

Partially considered Accepted, but with 
limitations 

Fully integrated (subtitles, 
alternative formats) 

Ethics and Safety Ignored Only partially complied 

with 

Generally met Fully compliant (CC licenses, 

data protection) 

Maximum score: 15 

Appendix C: Evaluation Rubric for the Mini-Module in the LMS 

Criterion 0 points 1 point 2 points 3 points 

Structure and navigation None Insufficient Satisfactory Clear, logical 

Coherence of goals and objectives None Partial Mainly agreed Fully consistent 

Content quality Very low Basic Sufficient High, professional 

Interactivity None Minimal A few elements Systematically organized 

Evaluation and analytics None Very limited Basic tools used Fully evaluated with analytics 

Inclusivity (UDL) None Partial Generally considered Fully integrated 

Ethics and copyright Violated Partially taken into account Mostly considered Fully complied with 

Maximum score: 15 

 

Appendix D:  Guide for focus groups and interviews  

Questions: 

What was most useful for you in the program? 

What digital tools did you start using most often? 

What difficulties did you encounter when working with digital technologies? 

Did you have any technical difficulties? 

What factors do you consider important for the development of digital competence? 

How do you assess the changes in your readiness to use ICT in future pedagogical practice? 
 

 
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