Yelena Spirina
Nadezhda Gorbunova
Irina Samoilova
Dinara Kazimova
Saule Zhumagulova- Department of Applied Mathematics and Computer Science, E. A. Buketov Karaganda University, Karaganda, Kazakhstan
In accordance with the requirements of the IT sector, higher education is aimed at training IT specialists with relevant hard and soft skills competencies. This study examines the possibility of integrating Project-Based Learning (PBL) into training of IT students to develop programming, project and teamwork skills using professional cloud services and tools in IT project work. The selection of relevant cloud tools for project work was carried out by an expert group of teachers and IT specialists. The proposed approach was applied when studying programming courses at the Karaganda Buketov University. The students of the experimental group studied using PBL and professional cloud tools to work on the project, depending on the tasks and type of project. Pre- and post-testing were used for quantitative analysis, and surveys were conducted for qualitative analysis to assess students’ programming skills, project activities, and teamwork before and after the experiment. The experimental group showed positive results in statistical data analysis, which indicates the effectiveness of the methods used. Based on the obtained experimental data and analysis of existing scientific works, conclusions were made confirming the relevance and effectiveness of the implementation of PBL with cloud services in the educational process in IT disciplines in higher education.
1 Introduction
The digital transformation of education plays a key role in training high-demand IT professionals. Modern education is increasingly using digital technologies to meet the demands of the labor market. Future IT professionals need not only basic knowledge and standard skills, but also special thinking, deep knowledge of programming languages and the ability to make non-standard solutions (Yu et al., 2016).
Students’ professional competencies are formed as a result of a properly organized educational process, which will be aimed at developing communication skills, students’ abilities to carry out complex real IT projects, the ability to work in a team, manage projects, critical thinking, etc. (Wang, 2023). Students receive complex tasks that are close to the real tasks of the IT field mainly during the preparation of the final qualification project. However, one qualification project is not enough to master project skills (Kovalevskaia et al., 2021). Therefore, IT students should carry out real projects on the development of software applications already within the framework of specialized disciplines using appropriate pedagogical approaches.
PBL is widely used in engineering and science education, promoting collaboration, problem solving, critical thinking, and student engagement (Chen et al., 2021; Afanasiev et al., 2021; Rehman et al., 2024; Dai et al., 2025). In the context of digitalization, research highlights the importance of integrating digital tools with PBL. Research confirms the potential of GenAI chatbots to support project work (Perifanou and Economides, 2025), MOOCs to promote teamwork and responsibility (Spirina et al., 2024), and web-based tools to enhance creativity and learning outcomes (Marini et al., 2025). Cloud technologies are widely used in e-learning, distance and hybrid education, as well as to create LMS in higher education (Kovalevskaia et al., 2021; Dema and Choden, 2024; Rijal et al., 2024; Grover and Nandal, 2024). Combining PBL with cloud solutions shows positive results: Tang et al. (2023) reported improved software application and critical thinking skills when using cloud-based LMS, while Srikan et al. (2021) demonstrated increased creativity and digital media skills in PBL with cloud support.
The use of professional IT tools, including cloud services, used in the development, testing, deployment and management of IT projects as part of the study of specialized disciplines of the computer cycle, allows you to shift the focus in the learning process from purely educational activities to solving professional problems using tools used in professional communities, in software development teams (Rochev and Semyashkina, 2023). For students of the IT field, project work and cloud services, on the one hand, are the subject of study in order to master them at a professional level, on the other hand, they are a means or tool that allows them to solve related tasks in software development in their professional activities.
The purpose of this study is to evaluate the effectiveness of project-based IT training for students in teaching specialized disciplines in learning programming languages using professional cloud services.
To achieve this goal, the following Research Tasks were solved in the study:
1. To conduct a comparative analysis of the academic results of students who studied programming languages using the traditional methodology, and students who studied using the PBL approach using professional cloud tools;
2. To assess the impact of PBL on the formation of professional and personal competencies of IT students, such as motivation, project work skills and teamwork.
2 Literature review
Project-based learning (PBL) is a pedagogical strategy based on independent planning and solving complex practical tasks through the implementation of real projects (Thomas, 2000). The ideas of the project method were first substantiated by J. Dewey and W. Kilpatrick in the early twentieth century (Kilpatric, 1918).
Many authors agree that PBL is especially suitable for engineering students to prepare for their future professions. Thus, Teixeira et al. (2020) note that “PBL’s approach to teaching and learning increases students’ ability to acquire and apply knowledge in real professional situations, preparing them to master the necessary competencies that meet the modern requirements of both companies and academia.”
In the study by O’Connor et al. (2024), when exploring the possibility of using online PBL in engineering education, the factors that teachers should consider were identified, namely: communication, module planning, student relationships and team structure, flexibility of the online environment.
Based on a meta-analysis of 66 studies by Zhang and Ma (2023), they proved that project-based learning is significantly superior to traditional methods, especially in engineering and technology disciplines and in practical classes. The effectiveness of the method varies depending on the subject area, the type of course, the duration of the experiment, and the size of the study group.
PBL as a practical teaching method has positive application results in various fields: medicine (Kldiashvili et al., 2025), in the study of foreign languages (Ghosheh Wahbeh et al., 2021), in teaching physics (Gao and Yang, 2023), computer science (Almulla, 2020; Sindre et al., 2018). The results showed that the introduction of PBL increased student motivation and improved skills.
PBL is effectively applied in face-to-face, online, hybrid and hybrid/blended learning, often combined with digital technologies (Dahham and Fawareh, 2022). Studies highlight successful implementations in IT education use of PBL, for example, in a hybrid learning environment for software engineering (Ceh Varela et al., 2023), Mobile-PBL (Al-Qora’n et al., 2023), Blended Project Learning (BPBL) includes a mixture of face-to-face and online components (Adri et al., 2020; Barbosa, 2022).
Many studies confirm the high potential of PBL and digital technologies in teaching IT disciplines. PBL provides real-world problem solving experience, develops students’ practical, cognitive, and communication skills (Alves et al., 2018; Saad, 2022; Guo et al., 2020), and is successfully combined with other forms of learning and digital tools (Lescano and Yamao, 2023; Naik and Girase, 2021).
As noted by Bogdan et al. (2019), the relevance of cloud technologies in education is confirmed by their ability to provide a high degree of interactivity, accessibility of educational materials and the ability to work together on projects and assignments. Cloud technologies facilitate planning, collaboration and communication, as well as support individual learning in project activities (Çakiroğlu and Erdemir, 2018).
Some professional cloud services in the preparation of IT students were considered by Omelchenko and Omelchenko (2021), who presented the experience of using 1C cloud services; Rochev and Semyashkina (2023) considered the possibilities of using cloud-based software version control tools. Authors, Marnewick (2023), Bryzgalova (2021), Suswanto et al. (2017), note that professional cloud services have extensive capabilities and many of them can be used in various specialized disciplines of the computer cycle to solve IT tasks close to real projects.
At the same time, according to the recommendations for career growth in IT the relevance of using cloud services in the specialized training of IT students is justified by key factors of the IT industry (Rawat, 2024; Ohiri, 2023):
1. Technological progress. Preparing students to work with cloud services is becoming mandatory for a successful career in IT.
2. Labor market needs. Employers expect university graduates to be familiar and proficient with such technologies.
3. Flexibility and efficiency. Cloud services provide flexibility and scalability, allowing students easy access to resources and tools from anywhere in the world.
4. Collaborative opportunities. Many cloud platforms provide collaboration and team collaboration capabilities.
In general, the use of cloud services in the profile training of IT students not only corresponds to current trends in the IT industry, but also allows improving the quality of education, preparing students for real tasks and the needs of the labor market.
PBL has proven to be an effective approach to the formation of students’ competencies, and its integration with digital technologies enhances the educational effect. However, there is insufficient research examining the use of professional cloud services in project-based programming training, which determines the need for further study of their effectiveness in training IT specialists.
3 Research method
The study used theoretical methods (literature analysis, comparison of researchers’ opinions on the use of PBL, the use of cloud services in student education, generalization and systematization of theoretical material on the problem under study) and empirical research methods (student surveys, conversations with students and teachers, analysis of experimental research results). The main tools for obtaining quantitative data were the results pre- and post-testing, which was conducted to solve Research Task 1. The results were evaluated according to the scale of the European Credit Transfer and Accumulation System (ECTS). To obtain qualitative results, the survey data was compared before and after the experiment were compared to solve Research Task 2. The Likert scale was used to evaluate the questionnaire questions.
The study took place in several stages:
Stage 1—pre-test to identify the initial level of students and conduct an introductory survey to identify students’ attitudes to PBL when learning programming, as well as identifying professional cloud platforms and services for learning programming languages, developing methodological recommendations on the use of cloud tools when performing an IT project within the discipline;
Stage 2—experiment with the use of PBL methods and the implementation of project work with cloud tools by students;
Stage 3 is a post–test to determine the level of students after completing the experiment and conducting a post-survey to identify students’ attitudes towards PBL with cloud tools when learning programming;
Stage 4—processing and analysis of experimental results.
The Expert Group was established to develop project-based training, identify relevant IT professional cloud services, and prepare test assignments for pre- and post-testing. The Expert Group included 5 graduates of the department working in IT companies and 12 teachers.
The study involved third-year students of the educational program “Information Systems” of the E. A. Buketov Karaganda University of the Republic of Kazakhstan. The participants have a basic knowledge of programming technology, which allowed them to freely participate in the study. To assess the effectiveness of the PBL methodology on learning outcomes, students (43 students in total) were randomly divided into control (N = 21) and experimental groups (N = 22). The sample was gender diverse, including 29 male and 14 female students. The experiment was conducted during one semester.
The content of the academic disciplines “Programming in Python” and “Programming in Java,” covered by both groups, was the same in terms of volume and sequence of academic topics, however, the way classes were conducted and the level of active student involvement differed significantly. The control group (CG) studied using a traditional approach: they studied theoretical material, reviewed and programmed training examples, discussed various approaches to solving problems under the guidance of a teacher, and could optionally use cloud services as a tool for solving learning tasks, but did not complete the final project work.
In contrast, the students of the experimental group (EG) gained knowledge through the application of PBL, namely, they completed the final IT project during the last 6 weeks of the semester. Moreover, they used cloud services recommended by the teachers, depending on the tasks and the type of project. The implementation of an IT project consists in creating a unique software application or system that is as close as possible to the real one, fulfills a number of functional requirements and meets the specific needs of users.
Pre- and post-tests were conducted to conduct a comparative analysis of the academic results of CG students who studied programming languages using the traditional methodology, and EG students who studied using the PBL approach using professional cloud tools (Research Task 1). The test tasks were developed taking into account Bloom’s taxonomy in order to cover several cognitive levels from basic memorization to analytical thinking. According to the recommendations of Gosen and Washbush (2004), assessment tools should be consistent with the results of experimental training to ensure validity and reliability.
The developed tests consisted of 25 multiple-choice questions in accordance with Bloom’s cognitive complexity matrix and are aimed at assessing the developed skills of application and analysis of program code. In addition, questions at the “assessment” level are included, allowing you to evaluate the proposed code fragments, find an error, or select the correct code instructions, which allows you to develop critical thinking skills. Cognitive processes for the “creation” level of goals are implemented by students during the application of the project-oriented learning approach, especially actively when students independently or in a team work on an IT project. Academic results were assessed using the ECTS. The assessment of the reliability of measurement instruments was verified using the Cronbach’s alpha coefficient with similar student groups, the result is α = 0.82, which confirms good internal consistency. The obtained correlation coefficient r = 0.73 confirms the ability of grades to reflect a positive change in students’ results.
To assess the impact of PBL on the development of soft skills competencies of IT students (Research Task 2), a survey was conducted CG and EG using a questionnaire developed by an expert group in the Google Forms format.
During the study, the students of the CG and EG passed the same preliminary test and an online survey to determine the initial level of knowledge and assess confidence in the implementation of the IT project, then at the end of the semester after the experiment, they passed the same post-test to measure differences in the acquisition of knowledge, understanding and practical skills in software development, as well as a post-survey to assess the impact of PBL on the development of students’ personal professional competencies, in particular motivation, project work skills and teamwork skills. These measurements allowed for a comparative analysis of experimental learning for knowledge gain. To analyze the quantitative data, the Student’s t-test was used to compare the deviations of the average values of the pre- and post-test results in the control and experimental groups.
4 Results and discussion
At the first stage of the study, the expert group identified IT professional cloud services that are used by professional programmers. The choice of a specific platform depends on the specifics of the discipline, the goals of the IT project, the specifics of the tasks and preferences. The survey results are presented in Table 1.
Table 1. Professional cloud services for software development.
These IT professional cloud services were recommended to students when doing project work. The teacher issues the assignment for the project and the allocation of students to projects (i.e., the formation of a project subgroup) in the first weeks of the semester. The project involves the creation of software (applications, software products) close to the real tasks of the IT sector. Then students assign roles in the project, divide the project into tasks and modules, determine the deadlines for the implementation of modules, a prototype, a project, deadlines for the presentation and protection of the project. As noted by Çakiroğlu and Erdemir (2018), the teacher, organizing project training, acquires special powers, he acts as a facilitator or coach, provides assistance in difficult situations and guides in choosing the best solutions and cloud services for this project. As part of the study, it turned out that psychological problems may arise when communicating with students, which can negatively affect the results of the project, which was noted by Bryzgalova (2021) and Rijal et al. (2024).
Table 2 shows the contents of a questionnaire for students’ self-assessment of programming skills, project activities, and teamwork, which was used before and after the experiment. The questionnaire includes questions to determine students’ interest in PBL using cloud services when studying specialized programming disciplines, as well as questions to identify students’ self-esteem for joint IT projects and willingness to work in a team. The Likert scale was used to evaluate the questionnaire questions (1—very low, 5—very high).
Table 2. Questionnaire for assessing programming, project work, and teamwork skills of students.
Table 3 shows the results of responses to a questionnaire to identify students’ self-esteem in the form of average scores on the Likert scale, standard deviation (SD) for the CG and EG groups for each question of the survey conducted before the experiment (pre-survey) and after the experiment (post-survey).
Table 3. Pre- and post-survey results (means, standard deviations).
An analysis of the results of the pre-survey allows us to conclude that students in the control and experimental groups rate their programming skills rather low and have little understanding of the specifics of creating a real IT project (questions Q1, Q2).
Questions Q3–Q4 assessed students’ confidence in developing an IT project. Before the experiment, most people believed that project work only applies existing knowledge. However, the post-survey showed an increase in self-assessment of programming skills in EG (from 2.76 to 3.73 points) and a high assessment of the ability to create a project (m = 4.01; SD = 0.17), which indicates formed teamwork skills and the belief that projects develop programming skills.
The Q5 question allowed us to evaluate students’ knowledge of IT cloud services for project work. Prior to the experiment, CG and EG had little experience with specialized services, limited to IDE and Microsoft Teams. After the experiment, EG’s knowledge expanded significantly (the average score increased from 2.36 to 3.72).
Questions Q6–Q7 revealed the positive attitude of EG students towards project-based learning as a means to gain practical experience close to real conditions. Teamwork skills in EG increased from 2.04 to 3.4 (in CG—from 2.0 to 2.14). Analyzing the results of the answers to question Q8, EG’s self-assessment of the use of project and team skills in professional activities also increased (from 2.22 to 3.41).
The survey results demonstrate that the integration of PBL using professional cloud tools enhances both the technical and professional-personal competencies of IT students. The EG showed a significant increase in self-assessment of programming skills, confidence in creating IT projects, and teamwork skills. Knowledge about professional cloud tools and how they can be used for collaborative development has significantly expanded. In addition, the students noted that PBL provides an opportunity to acquire practical experience that is as close as possible to the conditions of the real industry.
A quantitative analysis of the results of pre- and post-testing during the experiment to compare the academic results of students is presented in Table 4. The results of pre-testing indicate a comparable initial level of knowledge in the CG and EG, which is an important condition for ensuring the reliability of experimental results.
Table 4. Pre- and post-testing results.
Before applying the t-test, the basic statistical assumptions were verified: (1) the normality of the distribution was evaluated (to test the H0 hypothesis), the feature distributions did not have significant asymmetries or outliers; (2) the uniformity of variances was verified by comparing standard deviations using the Fisher test. For the Pre-test, the variances in CG and EG are similar (≈1.2 < 2), for the Post-test, the variances are also similar. This allowed us to conclude that the conditions for using the t-test have been met. Cohen’s d effect size was applied, in addition to p-values, to determine the practical relevance of the results.
In accordance with the experimental plan, the homogeneity of the CG and EG groups was checked, and the significance of the differences in the pre- and post-test data was assessed using a t-test to compare the values of the two groups. A comparative analysis of the Pre-test data showed no statistically significant differences between the control and experimental groups (t = −0.74, p = 0.46, Cohen’s d = 0.21). This confirms the homogeneity of the groups before the start of the experiment.
The results of the Post-test t-test showed statistically significant differences between the control and experimental groups and are accompanied by a very large effect size (t = 9.41, p < 0.0001, Cohen’s d = 2.92). In the EG, there is a significant increase in the proportion of students who scored “excellent” (on a scale of 90–100). The grades “unsatisfactory” (scores 0–49) and “satisfactory” (scores 50–55) disappear completely or are significantly reduced, which indicates the effectiveness of the proposed pedagogical impact.
EG students showed a high increase in knowledge in the field of software development: the average test score changed from 67.0% (SD = 5.7) to 82.3% (SD = 3.2). At the same time, KG students showed minor improvements: the average test score changed from 65.8% (SD = 5.7) to 71.6% (SD = 3.9). Thus, there is a 15.3% increase in learning outcomes in EG, and only 5.8% in KG. These results prove the effectiveness of PBL using professional cloud-based tools in teaching IT students programming.
The results of the study show that the use of cloud-based tools enhances the effectiveness of PBL in IT education compared to traditional approaches. Cloud technologies simplify project training and collaboration by providing round-the-clock access to resources and the ability to continue projects outside the classroom, including mixed and remote formats. However, their successful application requires a well-developed digital infrastructure and optimization of university resources (Rijal et al., 2024; Eljak et al., 2024; Qasem et al., 2020). Cloud technologies increase the efficiency of interaction between students and teachers, provide access to materials through LMS and contribute to the growth of academic performance. Their use in PBL enhances collaborative discussion and practical work on projects, which improves learning outcomes compared to traditional lecture methods (Grover and Nandal, 2024; Chueh and Kao, 2024).
Professional software platforms and tools play a key role in the training of IT students. Cloud services make it possible to reproduce the standards of the IT industry and increase students’ willingness to work. Research shows that the use of industrial tools accelerates adaptation in practice and improves results (Hazrat et al., 2023). Therefore, the use of PBL with cloud services is advisable not only in programming, but also in other disciplines, provided that the integration is pedagogically sound and the planned learning outcomes are achievable.
5 Conclusion
PBL plays a key role in shaping the competencies of IT specialists. The study confirmed the effectiveness of PBL in teaching programming and showed the potential for integrating professional cloud-based tools, which enhances the educational effect through flexibility, collaboration, bringing tasks closer to real conditions and optimizing costs.
However, despite the evident potential of PBL and the advantages of using cloud services, the study revealed a number of limitations and challenges:
• In the process of planning training, the expediency of using PBL and the selection of adequate cloud technologies for a particular discipline should be taken into account;
• Dependence on a stable Internet connection;
• Financial constraints: significant subscription and license costs may be required to make the advanced functionality of cloud platforms and services available;
• The organization and control of project work using cloud technologies requires high digital competence from teachers, time to learn new tools, which increases the workload and requires additional training.
The results confirm the pedagogical value of PBL with cloud services, allowing students to combine theoretical knowledge with practical skills. At the same time, the issues of integrating cloud technologies into education and teacher training remain relevant, which opens up prospects for further research.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by Ethical Committee of E. A. Buketov Karaganda University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
YS: Writing – review & editing, Supervision, Methodology, Conceptualization. NG: Writing – original draft, Formal analysis, Data curation. IS: Formal analysis, Data curation, Writing – review & editing. DK: Supervision, Writing – original draft, Conceptualization, Validation. SZ: Resources, Formal analysis, Writing – original draft, Supervision.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The authors declare that no Gen AI was used in the creation of this manuscript.
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Keywords: project-based learning (PBL), cloud services, IT education, professional competencies, soft skills, competency-based approach
Citation: Spirina Y, Gorbunova N, Samoilova I, Kazimova D and Zhumagulova S (2025) Effectiveness of project-based learning with cloud tools for developing professional competencies in IT education. Front. Educ. 10:1668913. doi: 10.3389/feduc.2025.1668913
Edited by:
Odiel Estrada-Molina, University of Valladolid, SpainReviewed by:
Krittawaya Thongkoo, Chiang Mai University, ThailandEdgar Ceh Varela, Eastern New Mexico University, United States
Copyright © 2025 Spirina, Gorbunova, Samoilova, Kazimova and Zhumagulova. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yelena Spirina, c2VhLnNwaXJpbmFAZ21haWwuY29t