Стратегии на образователната и научната политика

https://doi.org/10.53656/str2024-6s-1-def

2024/6s, стр. 11 - 24

DEFINING COGNITIVE, BEHAVIOURAL AND ENVIRONMENTAL FACTORS IN ENHANCING THE VALUE OF ARTIFICIAL INTELLIGENCE IN BUSINESS

Резюме: Artificial intelligence is one of the fastest-developing instruments of Industry 5.0. However, research on its impact has not been thoroughly discussed. Therefore, this paper focuses on developing an applicable methodology for measuring the added value of artificial intelligence in business practices, as well as understanding the fundamental factors that underpin the development of Industry 5.0 forces.This paper presents the results of testing a method for calculating the indirect value added by artificial intelligence (AI) to businesses. It is based on the premise that several factors significantly influence an organization's reputation and overall competitiveness when considering the indirect benefits of using AI. The validation of the model was conducted among 125 business organizations with experience in utilizing various AI-based systems and processes. The study's results indicate a strong statistical correlation between cognitive and motivational factors, as well as a strong correlation between these factors and the added value of AI. Additionally, there is a moderately low statistical correlation between environmental factors and the added value of AI when employing AI tools in practice.

Ключови думи: AI Added Value; cognitive factors for AI; motivational and environmental factors in business, business competitiveness and AIJEL: D01, D22, D91

Prof. Nikolay Sterev, DSc., Dr. Petya Biolcheva, Assoc. Prof. University of National and World Economy

Abstract. Artificial intelligence is one of the fastest-developing instruments of Industry 5.0. However, research on its impact has not been thoroughly discussed. Therefore, this paper focuses on developing an applicable methodology for measuring the added value of artificial intelligence in business practices, as well as understanding the fundamental factors that underpin the development of Industry 5.0 forces.

This paper presents the results of testing a method for calculating the indirect value added by artificial intelligence (AI) to businesses. It is based on the premise that several factors significantly influence an organization's reputation and overall competitiveness when considering the indirect benefits of using AI. The validation of the model was conducted among 125 business organizations with experience in utilizing various AI-based systems and processes. The study's results indicate a strong statistical correlation between cognitive and motivational factors, as well as a strong correlation between these factors and the added value of AI. Additionally, there is a moderately low statistical correlation between environmental factors and the added value of AI when employing AI tools in practice.

Keywords: AI Added Value; cognitive factors for AI; motivational and environmental factors in business, business competitiveness and AI

JEL: D01, D22, D91

Introduction

The widespread and rapid integration of artificial intelligence (AI) across all sectors of the economy has been recognized as a significant driver of economic development. With its assistance, businesses can manage information that was once restricted, predict customer behavior more accurately, stimulate innovation (Stoyanov 2024), and increase profitability.

AI technologies enable the automation of both routine and increasingly complex tasks, resulting in substantial productivity gains across various industries. Notable examples of AI's impact can be observed in the manufacturing sector, where business processes are optimized and costs are significantly reduced. A considerable portion of the manufacturing industry has already adopted AI solutions, while fintech companies are enhancing their financial services through improved data analytics, risk management, and the provision of customized financial products.

Technology companies are developing their own technology policies to address market demands and trends. Support mechanisms are emerging as a result of technological advancements rather than the reverse (Molhova & Biolcheva 2023). As we enter the age of artificial intelligence, businesses can more effectively differentiate between useful information and humanistic knowledge that fosters wisdom (manager.bg), thereby enhancing their overall value. However, the implementation of artificial intelligence in business necessitates substantial reorganizations and optimizations, which require significant financial investment.

There have been numerous unsuccessful attempts by companies due to incorrectly set goals, misunderstandings regarding the capabilities of artificial intelligence in specific applications, and a lack of quality data, among other factors. These challenges impose constraints on many managers when making decisions about introducing AI into their businesses. To facilitate the decision-making process, managers need to be aware of all potential threats, as well as the added value and returns that AI can provide. Several methods are documented in the economic literature to enhance the sustainability of development (Koleva et al. 2023; El Khatib et al. 2023) and to calculate the added value of AI for businesses (Wamba-Taguimdje et al. 2020). These methods primarily focus on direct returns, utilizing the relationship between changes in business processes that lead to reduced production costs or increased value for consumers (Kulińska 2014). In our previous research, we developed a model to calculate the indirect added value of AI for businesses (Biolcheva and Sterev 2024). This model is based on the premise that the estimation of AI's added value for businesses considers both changes in benefits and the preferences of those businesses.

The primary factors used to calculate indirect value added can be summarized as follows:

– Cognitive factors or factors influencing AI perception;

– Behavioral factors or behavior change factors related to the use of AI;

– Environmental factors or the impact of policies on the introduction or limitation of AI usage (Biolcheva and Sterev 2024).

With the current research, we aim to test this model and demonstrate its capability to calculate the indirect added value of artificial intelligence (AI) for businesses. To achieve this, the following chapters will sequentially present: a brief description of the model, the research methodology, the results, and the conclusion.

1. Added value model definition

There remains a lack of common understanding regarding how AI technologies create value within business organizations (Enholm et al. 2022). It is evident that technological advancements aim to identify solutions that foster positive change (Ivanov & Molhova 2023). Various researchers are exploring the added value of AI across different business sectors. For instance, Kim and his team (2011) assert that AI enhances both internal and external connections within organizations, thereby increasing their flexibility. According to Wamba-Taguimdje and colleagues (2020), the value added by AI is reflected in the improved eciency of company processes. We have identified certain gaps in this area, which motivates us to develop a model based on our perspectives on the subject.

The model for calculating the indirect added value of artificial intelligence (AI) for businesses is discussed in detail in our previous publication (Biolcheva and Sterev 2024). For the purposes of this study, we will briefly outline three main hypotheses: (H1) a higher degree of AI adoption, driven by more complex changes in business processes, (H2) increased trust and motivation resulting from the introduction of AI, leads to a greater economic impact of AI utilization in business. Additionally, environmental factors may indirectly influence the strength of this relationship (H3). In addition, the fundamental indicators are also calculated: the production costs of one product, the revenue from sales of a product, and the added value of a product, considering the changes in the aforementioned values before and after the implementation of AI.

The evaluation of the primary factors is conducted using a 5-point Likert scale (Joshi et al., 2015) to assess the strength of the statements ranked by the respondents. The summary score for each participant within the factor groups is calculated as a simple arithmetic mean. The final score for each of the three factors—cognitive, behavioural, and environmental—along with the overall value-added score, is determined by adjusting the mean scores using the Balassa method on a degree scale. After collecting the evaluations and making the necessary adjustments, the three hypotheses regarding their direct or indirect influences on one another are tested through correlation and regression analysis (Biolcheva and Sterev 2024).

2. Methodology

To evaluate the model for calculating the indirect added value of artificial intelligence in business, a survey was conducted involving 125 business organizations operating in Bulgaria. The respondents included both national and multinational companies. To ensure a diverse and knowledgeable respondent pool, assistance was sought from members of BACS (Bulgarian Association of Corporate Security), who hold positions of expertise in large technology firms, as well as from the Southeast Digital Innovation Hub and other experts. The respondents' fields of activity encompass companies in the high-tech sector and those in the service sector. The selection of these specific companies is driven by their higher degree of innovativeness and their inclination to adopt smart technologies based on artificial intelligence.

The decision to utilize an online survey for data collection is driven by the opportunity it affords respondents to express their opinions freely and anonymously. The study was conducted using an online survey that comprised 20 questions with closed-ended responses. The first section of the questions serves an introductory purpose, aiming to identify the type and size of the respondent's company. The second section seeks to clarify attitudes toward artificial intelligence (AI), the types of intelligent tools employed, and the extent of their usage by the respondents. The third section requires respondents to assign a score from 1 to 7 (in ascending order) regarding the contribution of AI in specific areas. The survey was conducted during the second quarter of 2024. Three of the monitored companies do not utilize AI tools, and the analysis is based on 122 accurately completed questionnaires. The survey data were processed using SPSS. To perform the necessary analyses, the selection of specific statistical methods focused on correlation and regression analysis.

3. Research and results analysis

Five main characteristics were used to classify the observations of the companies: the size of the company (i.e., micro, small, medium, or large); the international scope of the business (i.e., operating solely in Bulgaria or in Bulgaria and abroad); the company's experience with AI tools (measured in years of experience); the types and total number of AI tools implemented and utilized; and the anticipated expansion of AI tool usage in the future. The observations are based on interviews with Bulgarian companies conducted via the Internet. Although the sample is not statistically significant, the interviews include business development specialists to validate the methodology employed.

As a summary of the characteristics of the observed firms, we can derive the following results (Table 1).

Table 1. Characteristics of the observed firms

Q.1 What is the size ofthe companyQ.2 What is theinternationality of thecompanyQ.3 What is thecompany's experiencewith AI
Q.4.1What AItechnologies do youuseQ.4.2 How manyAItechnologies do youuseQ.7 Do you plan toexpand the use ofAIin the future

The data indicate that the distribution of responses is relatively balanced, both in terms of size and the respondents' internationalization and experience with AI tools. The tools themselves are also fairly evenly distributed, with the exception of neural networks, which demonstrate lower applicability. Furthermore, 20% of the firms observed do not utilize AI tools, and these firms typically do not intend to adopt AI tools in the future. Notably, nearly 50% of the firms surveyed restrict their use of AI to a single tool.

When examining the degree of dependence among the various qualification characteristics, three stand out as independent (see Table 2):

– Q.1 What is the size of the company;

– Q.6 What is your ethical position regarding the use of AI;

– Q.7 Do you plan to expand the use of AI.

It is these three independent variables that can be used to identify a cluster of firms associated with various patterns of AI usage behavior.

Table 2. Correlations between characteristics of observed firms

Q1.SizeQ.2InternationalizationQ.3Experiencewith AIQ.4 AItechnologiesQ.5 AIChallengesQ.6 AnEthicalPositionfor AIQ.7Expandinguseof AIQ11-,298**,405**,297**,193*,162,133Q2-,298**1-,172-,234*-,207*-,010-,281**Q3,405**-,1721,415**,265**,297**,285**Q4,297**-,234*,415**1,609**,212*,180Q5,193*-,207*,265**,609**1,065,102Q6,162-,010,297**,212*,0651,132Q7,133-,281**,285**,180,102,1321*. Correlation is significant at the 0.05 level (2-tailed).**. Correlation is significant at the 0.01 level (2-tailed).

When evaluating the application of AI tools in practice, the following average profile results can be derived. (Fig. 2).

3,33,53,73,94,14,34,5Q8. Increasing the degree of production automationand/or (decreasing) production timeQ9. Increasing process optimizationQ10. Economic optimization, including reducing thecost of raw materials, materials and labor andincreasing profitQ11. Improving the quality in the processes relatedto the realization ofthe products on the market?Q12. Increasing thelevel of convenience and speedwhen shoppingQ13. Increasing thelevel of personalization of thecustomer experienceQ14. Enhancing the consumer-brand connection,creating innovation in design, incl. throughelectronic virtual reality systemsQ15. Increasing quality of manufactured productsQ16. Assessingthe interaction between humans andAI in the manufacturing processcase profileaverageLegend:1 isthe lowest and 7the highest scorefor optimization / processimprovement

Figure 2. Profile of cognitive factors in using AI tools

From the analysis of the AI tools utilized, it is evident that their primary focus is on enhancing communication with consumers and increasing sales opportunities through artificial intelligence, rather than on improving or optimizing internal processes within the company. Despite the reported outcomes, the average profile score of 4.0 corresponds to the mean value regarding the level of process optimization and eciency.

An important aspect of this analysis is the degree of variation in the scores (Fig. 3).

Legend:1 isthe lowest and 7the highest scorefor optimization / processimprovement

Figure 3. Variation of cognitive factors when using AI tools

It is evident from the data that the estimates for the variation of cognitive factors closely resemble a normal distribution. Depending on the extent of utilization by the companies, the average in the distribution shifts either to the left (toward 3.00, indicating a deterioration of the effect) or to the right (toward 5.00, indicating an improvement of the effect).

Statistically, there is a correlation between individual cognitive factors (see

Table 3)

Table 3. Correlation dependences between the cognitive factors of AI for the observed companies

Q.8Q.9Q.10Q.11Q.12Q.13Q.14Q.15Q.16QcognQ.81,605**,585**,500**,439**,592**,498**,391**,390**,717**Q.9,605**1,571**,508**,723**,601**,452**,650**,727**,840**Q.10,585**,571**1,628**,574**,645**,489**,569**,440**,797**Q.11,500**,508**,628**1,377**,544**,429**,344**,374**,687**Q.12,439**,723**,574**,377**1,602**,373**,757**,649**,803**Q.13,592**,601**,645**,544**,602**1,657**,554**,561**,826**Q.14,498**,452**,489**,429**,373**,657**1,354**,445**,669**Q.15,391**,650**,569**,344**,757**,554**,354**1,762**,792**Q.16,390**,727**,440**,374**,649**,561**,445**,762**1,788**Qcogn,717**,840**,797**,687**,803**,826**,669**,792**,788**1*. Correlation is significant at the 0.05 level (2-tailed).**. Correlation is significant at the 0.01 level (2-tailed).

However, some variables are observed to be moderately highly correlated with others. These include:

• Q.14 Increasing the consumer-brand relationship by creating innovation in design, incl. by using virtual reality electronic systems

• Q.11 Quality improvement in the processes related to the realization of the products on the market

• Q.8 Increasing the degree of production automation and/or (decreasing) production time.

The assessment of behavioral factors is closely linked to the evaluation of motivating factors for the implementation and practical use of artificial intelligence (AI) (see Table 4). The primary motivating factors include:

Table 4. Characteristics of the observed companies

Curiosityof AIapplication
Increasing thee󰀩ciency ofproduction processesCompetitive or marketpressuresFullment of companygoals

From the data presented in Table 4, it is evident that the primary motivator for implementing AI tools in practice is the enhancement of production processes, cited by 64% of companies. Conversely, the least significant motivator is addressing competitive and market pressures, reported by only 30% of companies. These findings starkly contrast with the stated cognitive effects of process improvements within organizations, where the most pronounced effect is observed in enhancing communication with consumers, while the least significant effect pertains to the optimization of production processes.

In addition to the aforementioned points, trust in AI tools can be examined as a component of behavioral factors (see Fig. 4).

Legend:1 isthe lowest and 7the highest scorefor optimization / processimprovement

Figure 4. Profile of motivational factors when using AI tools

It is evident from the data that the variance scores of the motivating factors fall below the normal distribution. Specifically, intracompany motivation is significantly lower, scoring 3.10 out of 7.00, which negatively impacts trust. In contrast, the motivating score of the expected effect in the IS instruments exceeds the mean, with a score of 4.20 out of 7.00.

These findings are further supported by the lack of a correlational relationship among individual motivating factors (see Table 5).

Table 5. Correlation dependencies between the motivational factors of IM for the observed firms

Q17.1Q17.2Q17.3Q17.4Q17Q18QbehavQ17.11-,104,144-,166,464**-,018,275**Q17.2-,1041-,038-,067,410**,195*,385**Q17.3,144-,0381,126,617**,037,409**Q17.4-,166-,067,1261,455**,157,387**Q17,464**,410**,617**,455**1,189*,748**Q18-,018,195*,037,157,189*1,794**Qbehav,275**,385**,409**,387**,748**,794**1*. Correlation is significant at the 0.05 leQel (2-tailed).**. Correlationis significant at the0.01 leQel (2-tailed).

According to the results of the examination of the degree of dependence among the various motivational characteristics, three stand out as independent (see Table 5).

• Q.17.1 What motivates you to use AI in business: Curiosity;

• Q.17.2 What motivates you to use AI in business: Striving to increase the eciency of production processes;

• Q.17.3 What motivates you to use AI in business: Competitive or market pressures.

It is these three independent variables that can be used to identify a cluster of firms associated with various patterns of AI usage behavior.

The assessment of the value added by AI to the firm's activities is measured by three key effects: the firm's reputation, the transparency of its activities, and its fairness in the market.

However, the assessment of value added is lower than the anticipated level (at least an average of 4.00), as each of the evaluated value-added elements holds nearly equal significance (see Fig. 5).

Legend:1 is the lowest and 7 the highest score for optimization/process improvement

Figure 5. Value-added profile when using AI tools

In summary, one can assess the presence or absence of evidence to confirm the hypotheses derived from the model (see Fig. 5). When evaluating the presence or absence of a statistically significant correlation between individual variables, the following correlation matrix can be generated (see Table 6).

Table 6. Correlation relationships between variables: independent and dependent variables related to the use of AI for the observed firms

QcognQbehavQenviroQAValueQcogn1,632**,718**,760**Qbehav,632**1,393**,537**Qenviro,718**,393**1,727**QAValue,760**,537**,727**1*. Correlation is significant at the 0.05 leQel (2-tailed).**. Correlation is significant at the 0.01 leQel (2-tailed).

Based on this, the defined hypotheses are confirmed.

• H1: There is a strong statistical correlation between cognitive (H1.1) and behavioral (H1.2) factors that influence the independent outcome variable: the added value of AI in the practical use of AI tools.

• H2: There is a strong statistical correlation between cognitive and behavioral factors that determine the added value of AI.

• H3: There is a moderately low statistical correlation between environmental factors and the value added by AI when utilizing AI tools in practice.

Behavioral factors:CONFIDENCE,PERCEPTION andMOTIVATIONCognitivefactors:PRODUCTIVITYEnvironmentalfactors:STAKEHOLDERSAI Added ValueН1.1:0,760**Н1.2:0,537**Н2:0,632**Н30,760**

Figure 6. Verification of defined hypotheses using AI tools

In addition, a cluster analysis can be conducted to summarize the differences in firms' behaviors when utilizing AI tools in practice (Fig. 6).

Figure 7. Cluster defining by difference in using AI tools

– Cluster 1 primarily consists of medium and large national companies that possess significant experience in the practical application of AI tools. However, they utilize a limited range of AI tools, typically around one, and the challenges associated with the AI usage environment are relatively minimal. Their decisions regarding the further development of AI tools largely depend on changes in the environment.

– Cluster 2 comprises the smallest and some medium-sized national companies. While they have experience with AI tools, most of these companies do not utilize such tools in practice. The environmental impact assessment is relatively low; however, most of these representatives do not intend to adopt AI in the future.

– Cluster 3 comprises the largest and some medium-sized international companies that utilize AI tools to optimize one or more processes within the organization. On average, these companies employ 1 to 2 AI tools in practice. Recognizing the significant role of environmental challenges, they plan to introduce additional AI tools in the future.

– Cluster 4 comprises small and medium-sized international companies that possess considerable experience in implementing AI tools. Below are the representatives that utilize the highest number of AI tools in practice. For these companies, environmental challenges are of utmost importance, and they are primarily focused on expanding their use of AI tools.

Based on the primary differences in the key characteristics of the typical representatives of each cluster, the interaction of the individual variables in the application of AI can be summarized:

– Cluster 1 is situated in an optimal environment for evaluating the cognitive and behavioral factors associated with the use of AI in practice. However, the assessment of the environmental impact is minimal, and due to the limited use of AI tools, the added value of AI in their practice remains insucient.

– Cluster 2 representatives rate the importance of cognitive factors as mediocre and may feel demotivated to use AI tools in practice. For this group, the influence of the environment on the use of AI is minimal, as is their assessment of the added value of AI tools for their practice.

– For Cluster 3, the rating of cognitive factors was highest when combined with a high rating of behavioral factors. This combination also indicates the greatest influence of the environment on the use of AI, as these representatives derive the highest added value from the practical application of AI.

– Finally, the representatives of Cluster 4 demonstrate a greater awareness of the cognitive factors of AI and surpass the representatives of Cluster 3 in terms of motivation. However, their assessment of the added value of AI in their practice is moderate—significantly higher than that of representatives from Clusters 1 and 2, yet still notably lower than that of Cluster 3 regarding the added value of AI.

Conclusions

In summary, there is no doubt that realizing high added value from the use of AI is closely linked to a thorough assessment of the market and competitive factors that influence this impact. National companies, particularly small and medium-sized enterprises, urgently require additional training on the potential applications of AI tools to enhance processes and achieve improved economic and organizational outcomes across various functions—not just in user communication. Developing the necessary knowledge and skills to utilize different AI tools will also foster a greater willingness to adopt new technologies in the future.

Following the aforementioned points, it is essential to identify relevant information that can enhance the cognitive and motivational attitudes of these firms towards utilizing AI as a means to achieve greater added value from its implementation and practical use. This rationale supports the team's ongoing efforts to explore the indirect value that AI contributes to businesses. Future research should focus on complementing the relationships among the key drivers of AI adoption in business and measuring their added value.

The findings of this research could be highly beneficial for strategy developers, as the results may encourage small and medium-sized enterprises (SMEs) to adopt and implement more tools associated with Industry 5.0. Furthermore, the research indicates that SMEs encounter not only environmental challenges but also cognitive and behavioral limitations. These cognitive barriers can be addressed through various training programs offered at universities, while behavioral limitations can be mitigated through additional practical training sessions.

Nevertheless, the challenge of analyzing the effects of AI implementation in practice still remains. While this paper presents one possible model for defining the added value of AI, it requires further evidence from other regions, with an increasing number of respondents and business representatives.

Acknowledgements and Funding

This work financially supported by the UNWE Research Programme (Research Grand No 5/2023).

REFERENCES

BIOLCHEVA, P.; STEREV, N., 2024. A Model for Calculating the Indirect Added Value of AI for Business. Strategies for policy in science & education-Strategii na Obrazovatelnata i Nauchnata Politika, vol. 32, no. 3s, pp. 9 – 17. DOI: 10.53656/str2024-3s-1-mod.

ENHOLM, I. M.; PAPAGIANNIDIS, E.; MIKALEF, P. & KROGSTIE, J., 2022. Artificial intelligence and business Value: A literature review. Information Systems Frontiers, vol. 24, no. 5, pp. 1709 – 1734.

IVANOV I. & MOLHOVA, M., 2023. Bulgaria’s technological development through the prism of higher education policies. Strategies for policy in science & education-Strategii na Obrazovatelnata i Nauchnata Politika, vol. 31, no. 3s, pp. 154 – 17. DOI: 10.53656/str2023-3s-5-str.

JOSHI, A., KALE, S., CHANDEL, S., PAL, D., 2015. Likert scale: Explored and explained. British journal of applied science & technology, vol. 7, no. 4, pp. 396 – 403.

KIM, G.; SHIN, B.; KIM, K. K. & LEE, H. G., 2011. IT capabilities, process-oriented dynamic capabilities, and firm financial performance. Journal of the Association for Information Systems, vol.12, no. 7, DOI: 10.17705/1jais.00270.

KOLEVA, N.; ANGELOVA, Y., DIMOVA, D., 2023. A conceptual framework for integration of the concept of sustainable development in Bulgarian enterprises, Orlando, 27th World Multi-Conference on Systemics, Cybernetics and Informatics, Proceedings, DOI: 10.54808/ WMSCI2023.01.

KULIŃSKA, E., 2014. The significance of costs calculation in evaluation of the value added. China-USA Business Review, vol. 13, no. 4, pp. 1537 – 1514.

EL KHATIB, M.; ALI, S.; ALHARAM, I.; ALHAJERI, A.; PENEVA, G.; ANGELOVA, Y., & SHANAA, M., 2023. Drafting a digital transformation strategy for project management sector – Empirical Study on UAE. Strategies for policy in science & education-Strategii na Obrazovatelnata i Nauchnata Politika, vol. 31, no. 6s, DOI: 10.53656/str2023-6s-3-dra.

MOLHOVA, M. & BIOLCHEVA, P., 2023. Strategies and Policies to Support the Development of AI Technologies in Europe. Strategies for policy in science & education-Strategii na Obrazovatelnata i Nauchnata Politika, vol. 31, no. 3s, pp. 69 – 79, DOI: 10.53656/str2023-3s -5-str.

STOYANOV, I., 2024. Although slowly, artificial intelligence is entering business in our country, Available at: https://business.dir.bg/ikonomika/ makar-i-baQno-izkustQeniyat-intelekt-naQliza-Q-biznesa-u-nas (BG).

WAMBA-TAGUIMDJE, S.; WAMBA, L.; KAMDJOUG, S.; WANKO, J., 2020. Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business process management journal, vol. 26, no. 7, pp.1893 – 1924.

Prof. Nikolay Sterev, DSc.

ORCID iD: 0000-0001-8262-3241
Dr. Petya Biolcheva, Assoc. Prof.

ORCID iD: 0000-0001-9430-773X,
Department of Industrial Business
University of National and World Economy
Sofia, Bulgaria
E-mail: ind.business@unwe.bg
p.biolcheva@unwe.bg

2025 година
Книжка 4
ТРАНСФОРМАЦИИ НА ПАЗАРА НА ТРУДА И НУЖДАТА ОТ ОБРАЗОВАТЕЛНИ РЕФОРМИ

Ваня Иванова, Андрей Василев, Калоян Ганев, Ралица Симеонова-Ганева

Книжка 3
FORMING ENTREPRENEURIAL CULTURE THROUGH EDUCATION

Prof. Dr. Milena Filipova, Adriana Atanasova, PhD student

Книжка 2s
THE STATE OF INCLUSION IN ADAPTED BASKETBALL

Dr. Stefka Djobova, Assoc. Prof., Dr. Ivelina Kirilova, Assist. Prof.

THE IMPACT OF AGE ON ADULT’S PARTICIPATION IN PHYSICAL ACTIVITIES DURING LEISURE TIME

Dr. Despina Sivevska, Assoc. Prof. Dr. Biljana Popeska, Assoc. Prof.

Книжка 2
MODEL OF PROFESSIONALLY DIRECTED TRAINING OF FUTURE ENGINEER-TEACHERS

Prof. Ivan Beloev, Dr. Valentina Vasileva, Assoc. Prof. Dr. Іnna Savytska, Assoc. Prof., Dr. Oksana Bulgakova, Assoc. Prof. Dr. Lesia Zbaravska, Assoc. Prof., Dr. Olha Chaikovska, Assoc. Prof.

QUALITY OF HIGHER EDUCATION IN BULGARIA: COMMUNICATION AND COMPUTER TECHNOLOGY TRAINING

Prof. Rositsa Doneva, Dr. Silvia Gaftandzhieva, Assoc. Prof.

ВЛИЯНИЕ НА ОБРАЗОВАНИЕТО И ЧОВЕШКИЯ КАПИТАЛ ВЪРХУ ФОРМАЛНАТА И НЕФОРМАЛНАТА ИКОНОМИКА

Проф. д-р Стефан Петранов, доц. д-р Стела Ралева, доц. д-р Димитър Златинов

DETERMINANTS AFFECTING ACADEMIC STAFF SATISFACTION WITH ONLINE LEARNING IN HIGHER MEDICAL EDUCATION

Dr. Miglena Tarnovska, Assoc.Prof.; Dr. Rumyana Stoyanova, Assoc.Prof.; Dr. Angelina Kirkova-Bogdanova; Prof. Rositsa Dimova

Книжка 1s
CHALLENGES FACED BY THE BULGARIAN UNIVERSITIES IN THE CONTEXT OF SCIENCE – INDUSTRY RELATIONS

Dr. Svetla Boneva, Assoc. Prof., Dr. Nikolay Krushkov, Assoc. Prof.

INVENTING THE FUTURE: CAN BULGARIAN UNIVERSITIES FULFILL THEIR MISSION AS CATALYSTS FOR ECONOMIC GROWTH AND SUSTAINABILITY?

Dr. Ralitsa Zayakova-Krushkova, Assist. Prof., Dr. Alexander Mitov, Assoc. Prof.

AN INNOVATIVE MODEL FOR DEVELOPING DIGITAL COMPETENCES OF SOCIAL WORKERS

Prof Dr. Lyudmila Vekova, Dr. Tanya Vazova, Chief Assist. Prof., Dr. Penyo Georgiev, Chief Assist. Prof., Dr. Ekaterina Uzhikanova-Kovacheva

BUSINESS ASPECTS OF ACADEMIC PUBLISHING

Dr. Polina Stoyanova, Chief Assist. Prof.

THE ECONOMIC IMPACT OF MUSIC STREAMING

Dr. Dimiter Gantchev, Assist. Prof.

FILM INCENTIVE SCHEME IN THE REPUBLIC OF BULGARIA

Dr. Ivan Nachev, Assist. Prof.

PATENT PROTECTION OF DIGITAL TWINS

Dr. Vladislava Pаcheva, Chief Assist. Prof.

Книжка 1

МНОГОСТРАНЕН ПОДХОД ЗА ИЗСЛЕДВАНЕ РАВНИЩЕТО НА ДИГИТАЛИЗАЦИЯ В ПОДГОТОВКАТА НА БЪДЕЩИ УЧИТЕЛИ

Доц. д-р Бистра Мизова, проф. д-р Румяна Пейчева-Форсайт Проф. д-р Харви Мелър

2024 година
Книжка 6s
DISRUPTIVE TECHNOLOGIES RISK MANAGEMENT

Dr. Miglena Molhova-Vladova, Dr. Ivaylo B. Ivanov

THE DUAL IMPACT OF ARTIFICIAL INTELLIGENCE: CATALYST FOR INNOVATION OR THREAT TO STABILITY

Prof. Diana Antonova, Dr. Silvia Beloeva, Assist. Prof., Ana Todorova, PhD student

MARKETING IN TOURISM: PRACTICAL EVIDENCES

Dr. Fahri Idriz, Assoc. Prof.

DEVELOPMENT OF THE INFORMATION ECONOMY CONCEPT AND THE TRANSITION TO INDUSTRY 5.0

Dr. Dora Doncheva, Assist. Prof., Dr. Dimitrina Stoyancheva, Assoc. Prof.

THE GLOBAL MARKET AS A PROJECTION OF THE INFORMATION ECONOMY

Dr. Vanya Hadzhieva, Assist. Prof. Dr. Dora Doncheva, Assist. Prof.

ACADEMIC ENTREPRENEURSHIP: PRACTICAL RESULTS AND TRAINING

Prof. Nikolay Sterev, DSc., Dr. Daniel Yordanov, Assoc. Prof.

Книжка 6
AN INTEGRATIVE APPROACH TO ORGANIZING THE FORMATION OF STUDENTS’ COGNITIVE INDEPENDENCE IN CONDITIONS OF INTENSIFICATION OF LEARNING ACTIVITIES

Dr. Albina Volkotrubova, Assoc. Prof. Aidai Kasymova Prof. Zoriana Hbur, DSc. Assoc. Prof. Antonina Kichuk, DSc. Dr. Svitlana Koshova, Assoc. Prof. Dr. Svitlana Khodakivska, Assoc. Prof.

ИНОВАТИВЕН МОДЕЛ НА ПРОЕКТНО БАЗИРАНО ОБУЧЕНИЕ НА ГИМНАЗИАЛНИ УЧИТЕЛИ: ДОБРА ПРАКТИКА ОТ УниБИТ

Проф. д-р Жоржета Назърска, доц. д-р Александър Каракачанов, проф. д-р Магдалена Гарванова, доц. д-р Нина Дебрюне

Книжка 5s
КОНЦЕПТУАЛНА РАМКА ЗА ИЗПОЛЗВАНЕ НА ИЗКУСТВЕНИЯ ИНТЕЛЕКТ ВЪВ ВИСШЕТО ОБРАЗОВАНИЕ

Акад. д.н. Христо Белоев, проф. д.н. Валентина Войноховска, проф. д-р Ангел Смрикаров

ИЗКУСТВЕНИЯТ ИНТЕЛЕКТ В БИЗНЕСА – ФИНАНСОВИ, ИКОНОМИЧЕСКИ И МАРКЕТИНГОВИ АСПЕКТИ

Проф. д-р Андрей Захариев, доц. д-р Драгомир Илиев Гл. ас. д-р Даниела Илиева

RECENT TRENDS AND APPLICATIONS OF THE ARTIFICIAL INTELLIGENCE IN THE EDUCATION

Prof. Dr. Plamen Zahariev, Prof. Dr. Georgi Hristov, Prof. Dr. Ivan Beloev

COMPARATIVE ANALYSIS OF UTILIZING POPULAR INTELLIGENT COMPUTER SYSTEMS IN EDUCATION

Dr. Galina Ivanova, Assoc. Prof. Dr. Aleksandar Ivanov, Assoc. Prof.

CONCEPTUAL MODEL OF TRAINING IN REMOTE VIRTUAL SUPERVISION IN SOCIAL WORK

Dr. Silviya Beloeva, Assist. Prof. Dr. Nataliya Venelinova, Assist. Prof.

ИЗСЛЕДВАНЕ ПРИЛОЖИМОСТТА НА БЛОКОВИ ВЕРИГИ ОТ ПЪРВО НИВО (L1) В СИСТЕМА ЗА ЕЛЕКТРОННО ОБУЧЕНИЕ

Андриан Минчев, проф. Ваня Стойкова, гл. ас. д-р Галя Шивачева Доц д-р Анелия Иванова

DIGITAL DISCRIMINATION RISKS IN THE TRANSFORMATION OF HIGHER EDUCATION

Dr. Silviya Beloeva, Assist. Prof. Dr. Nataliya Venelinova, Assist. Prof.

OPPORTUNITIES, CHALLENGES AND SOLUTIONS FOR DIGITAL TRANSFORMATION OF THE EDUCATIONAL PROCESSES THROUGH 3D TECHNOLOGIES

Prof. Georgi Hristov, Prof. Plamen Zahariev, Dr. Diyana Kinaneva, Assist. Prof., Georgi Georgiev, Assist. Prof.

ДИГИТАЛНОТО ПОКОЛЕНИЕ VS. СЛЯТОТО, ПОЛУСЛЯТОТО И РАЗДЕЛНОТО ПИСАНЕ

Доц. д-р Владислав Маринов, ас. Анита Тодоранова

OPPORTUNITIES AND CHALLENGES FOR THE EDUCATION OF STUDENTS WITH SPECIAL EDUCATIONAL NEEDS IN THE DIGITAL ENVIRONMENT: THE NEW NORMAL

Prof. Julia Doncheva, DSc., Dr. Galina Ivanova, Assoc. Prof. Dilshod Tojievich Oblokulov

ИЗГРАЖДАНЕ НА КОМПЕТЕНЦИИ ЗА РАЗРАБОТВАНЕ НА STEM ОБУЧИТЕЛНИ РЕСУРСИ У БЪДЕЩИ УЧИТЕЛИ ПО ПРИРОДНИ НАУКИ

Доц. д-р Евгения Горанова, проф. д.н. Валентина Войноховска, проф. д-р Ангел Смрикаров

APPLICATION OF ZSPACE TECHNOLOGY IN THE DISCIPLINES OF THE STEM CYCLE

Boyana Ivanova, Assist. Prof. Dr. Kamelia Shoilekova, Assoc. Prof. Dr. Desislava Atanasova, Assoc. Prof. Dr. Rumen Rusev, Assoc. Prof.

TEACHERS' ADAPTATION TO CHANGES IN AN INCREASINGLY COMPLEX WORLD THROUGH THE USE OF AI

Prof. Zhanat Nurbekova, Kanagat Baigusheva, Kalima Tuenbaeva, Bakyt Nurbekov Prof. Tsvetomir Vassilev

АТОСЕКУНДНОТО ОБУЧЕНИЕ – МЕТАФОРА НА ДНЕШНОТО ОБРАЗОВАНИЕ

Проф. д.н. Юлия Дончева, Денис Асенов, проф. д-р Ангел Смрикаров проф. д-р Цветомир Василев

APPLICATION AND ASSESSMENT OF DIGITAL RESOURCES IN THE EDUCATION OF FUTURE PEDAGOGUES

Dr. Galina Ivanova, Assoc. Prof., Dr. Milena Velikova, Assist. Prof.

IDENTIFYING PLAYER TYPES IN THE CLASSROOM FOR EFFECTIVE GAMIFICATION

Dr. Desislava Atanasova, Assoc. Prof., Viliana Molnar

DEVELOPMENT AND INTEGRATION OF AUDIO AND VISUAL MICRO-RESOURCES IN THE LEARNING PROCESS THROUGH THE USE OF ARTIFICIAL INTELLIGENCE SYSTEMS

Dr. Petya Stefanova, Assist. Prof., Dr. Assist. Elitsa Ibryamova, Assist. Prof., Prof. Angel Smrikarov, Dr. Galina Ivanova, Assoc. Prof.

АНАЛИЗ НА ПРОГРАМНИТЕ МОДЕЛИ ЗА АВТОМАТИЗИРАНЕ НА КОГНИТИВНИ ПРОЦЕСИ

Доц. д-р Валентин Атанасов Доц. д-р Анелия Иванова

Книжка 5
MANAGING A POSITIVE AND LIFE-SKILLS DEVELOPMENT IN THE SCHOOL-BASED CURRICULA: A LITERATURE REVIEW ON THE SUSTAINABLE EDUCATION

Dr. Lindita Durmishi, Assoc. Prof., Dr. Ardian Durmishi Prof. Milena Filipova Dr. Silva Ibrahimi

APPLICATION OF THE COMPETENCY MODEL IN BUSINESS ADMINISTARATION HIGHER EDUCATION IN HORIZON 2030

Prof. Nadya Mironova, Dr. Tatyana Kicheva, Assoc. Prof., Dr. Miglena Angelova, Assoc. Prof.

Книжка 4s
THE EDUCATION AND RESEARCH IN THE QUADRUPLE HELIX AND THE REGIONAL INNOVATION PROSPECTS

Prof. Dr. Milen Baltov Dr. Stela Baltova, Assoc. Prof. Dr. Vilyana Ruseva, Assoc. Prof.

Книжка 4
ATTITUDES OF STUDENTS – FUTURE TEACHERS, FOR THE APPLICATION OF GENERATIVE ARTIFICIAL INTELLIGENCE

Assoc. Prof. Nikolay Tsankov, DSc. Dr. Ivo Damyanov, Assist. Prof.

EDUCATIONAL NEEDS OF THE JUDICIAL ADMINISTRATION IN THE CONTEXT OF DIGITALIZATION

Dr. Diana Dimitrova, Dr. Darina Dimitrova, Assoc. Prof., Dr. Velina Koleva

MANAGERIAL ASPECTS OF COOPERATION AMONG HIGHER EDUCATION INSTITUTIONS AND THEIR STAKEHOLDERS

Prof. Olha Prokopenko, DSc. Dr. Svitlana Perova, Assoc. Prof. Prof. Tokhir Rakhimov, DSc.

APPLICATION OF EDUCATIONAL STRATEGIES IN STUDYING THE DYNAMICS OF STATE POWER STRUCTURES: IMPLEMENTATION OF FORMAL AND INFORMAL MECHANISMS OF INFLUENCE

Prof. Stoyan Denchev, DSc. Dr. Miriyana Pavlova, Assist. Prof. Dr. Steliana Yordanova, Assist. Prof.

ДИАГНОСТИКА НА ФОРМИРАНАТА ПРОФЕСИОНАЛНА КОМПЕТЕНТНОСТ НА БЪДЕЩИ ИНЖЕНЕРИ ПО ЕНЕРГЕТИКА

Гл. ас. д-р Надя Илиева Доц. д-р Елена Бояджиева Ивалина Маринова

Книжка 3s
A MODEL FOR CALCULATING THE INDIRECT ADDED VALUE OF AI FOR BUSINESS

Dr. Petya Biolcheva, Assoc. Prof., Prof. Nikolay Sterev, DSc.

AI EFFECTIVENESS AND RISK ASSESSMENT OF INVESTMENTS IN HIGH-RISK START-UPS

Sotir Ivanov, PhD Student, Dr. Petya Biolcheva, Assoc. Prof.

COMPETITIVENESS OF TEXTILE PRODUCERS IN DIGITAL BUSINESS ERA

Prof. Nikolay Sterev, DSc., Dr. Vyara Milusheva, Assoc. Prof.

CHALLANGES OF USING ARTIFICIAL INTELLIGENCE IN MANAGEMENT DECISION MAKING

Dr. Bozhana Stoycheva, Assist. Prof. Dr. Pavel Vitliemov, Assoc. Prof.

THE SIGNIFICANCE OF ERASMUS+ MOBILITY IN BUSINESS EDUCATION: AN EXAMINATION OF A SUCCESSFUL BULGARIAN-MEXICAN COLLABORATION

Dr. Lyudmila Mihaylova, Assoc. Prof. Dr. Emil Papazov, Assoc. Prof. Dr. Diana E. Woolfolk Ruiz

Книжка 3
ИГРОВИ ПОДХОДИ В ОБУЧЕНИЕТО: УНИВЕРСИТЕТСКИ КОНТЕКСТ

Проф. д.н. Цветан Давидков Силвия Тонева, докторант

Книжка 2
FORMATION OF PROFESSIONAL SKILLS OF AGRICULTURAL ENGINEERS DURING LABORATORY PRACTICE WHEN STUDYING FUNDAMENTAL SCIENCE

Dr. Ivan Beloev, Assoc. Prof. Dr. Oksana Bulgakova, Assoc. Prof., Dr. Oksana Zakhutska, Assoc. Prof., Dr. Maria Bondar, Assoc. Prof. Dr. Lesia Zbaravska, Assoc. Prof.

ИМИДЖ НА УНИВЕРСИТЕТА

Проф. д.п.н. Галя Христозова

Книжка 1s
COMPETITIVENESS AS A RESULT OF CREATIVITY AND INNOVATION

Dr. Nikolay Krushkov, Assoc. Prof. Dr. Ralitza Zayakova-Krushkova

INNOVATION, TECHNICAL PROGRESS AND ECONOMIC DEVELOPMENT

Dr. Aleksandar Aleksandrov, Assist. Prof.

ENHANCING ECONOMIC SECURITY THROUGH INTELLECTUAL PROPERTY

Dr. Dimiter Gantchev, Assist. Prof.

INTELLECTUAL PROPERTY AND SECURITY IN THE INTEGRATED CIRCUITS INDUSTRY

Dr. Ivan Nachev, Dr. Yuliana Tomova, Iskren Konstantinov, PhD student, Marina Spasova, student

GREEN TRADEMARKS AND SUSTAINABILITY

Dr. Silviya Todorova, Assist. Prof.

ARTIFICIAL INTELLIGENCE AND ITS PROTECTION AS AN INVENTION

Dr. Vladislava Pаcheva, Assist. Prof.

Книжка 1
PROBLEMS AND PERSPECTIVES FOR SOCIAL ENTREPRENEURSHIP IN HIGHER EDUCATION

Prof. Dr. Milena Filipova Prof. Dr. Olha Prokopenko Prof. Dr. Igor Matyushenko, Dr. Olena Khanova, Assoc. Prof. Dr. Olga Shirobokova, Assoc. Prof. Dr. Ardian Durmishi

RESEARCH OF USING THE SYSTEM APPROACH TO INCREASE PROFESSIONAL COMPETENCE OF STUDENTS IN THE PROCESS OF STUDYING NATURAL SCIENCES

Dr. Ivan Beloev, Assoc. Prof. Dr. Іnna Savytska, Assoc. Prof., Dr. Oksana Bulgakova, Assoc. Prof. Prof. Iryna Yasinetska, Dr. Lesia Zbaravska, Assoc. Prof.

2023 година
Книжка 6s
TRANSFORMING MARITIME EDUCATION FOR A DIGITAL INDUSTRY

Dr. Christiana Atanasova, Assist. Prof.

DEVELOPMENT OF A COMMON INFORMATION SYSTEM TO CREATE A DIGITAL CAREER CENTER TOGETHER WITH PARTNER HIGHER SCHOOLS

Prof. Dr. Yordanka Angelova, Dr. Rossen Radonov, Assoc. Prof. Vasil Kuzmov, Assist. Prof. Stela Zhorzh Derelieva-Konstantinova

DRAFTING A DIGITAL TRANSFORMATION STRATEGY FOR PROJECT MANAGEMENT SECTOR – EMPIRICAL STUDY ON UAE

Mounir el Khatib, Shikha al Ali, Ibrahim Alharam, Ali Alhajeri Dr. Gabriela Peneva, Assist. Prof., Prof. Jordanka Angelova, Mahmoud Shanaa

VOYAGE OF LEARNING: CRUISE SHIPS WEATHER ROUTING AND MARITIME EDUCATION

Prof. Svetlana Dimitrakieva, Dr. Dobrin Milev, Assist. Prof., Dr. Christiana Atanasova, Assist. Prof.

RESEARCH ON THE SUSTAINABLE DEVELOPMENT COMPETENCES OF THE LANDSCAPE ARCHITECT IN PRACTICE

Land. arch. Elena Dragozova, Assoc. Prof., Dr. Stanislava Kovacheva, Assoc. Prof.

STUDY OF THE KEY FACTORS INFLUENCING THE EFFECTIVE PLANNING AND UTILIZATION OF PRODUCTION FACILITIES IN THE INDUSTRIAL ENTERPRISE

Dr. Tanya Panayotova, Assoc. Prof., Dr. Krasimira Dimitrova, Assoc. Prof., Neli Veleva, PhD student

SIMULATOR TRAINING – UNIQUE POWERFUL INSTRUMENT FOR EDUCATING, SKILLS CREATING, MITIGATING SKILLS AND RESILIENCE CREATING

Prof. Dimitar Dimitrakiev, Vencislav Stankov, Assist. Prof., Dr. Christiana Atanasova, Assist. Prof.

СТРУКТУРНИ ПРОМЕНИ В ОБУЧЕНИЕТО НА МЕНИДЖЪРИ ЗА ИНДУСТРИЯ 5.0

Доц. д-р Недко Минчев, доц. д-р Венета Христова, гл. ас. д-р Иван Стоянов

RESEARCH OF THE INNOVATION CAPACITY OF AGRICULTURAL PRODUCERS

Dr. Siya Veleva, Assoc. Prof.; Prof. Dr. Eng. Margarita Mondeshka Dr. Anka Tsvetanova, Assoc. Prof.,

Книжка 6
Книжка 5s
ПРЕСЕЧНАТА ТОЧКА НА СПОРТА, СИГУРНОСТТА И КРИПТО ФЕН ТОКЕНИТЕ

Полк. доц. Георги Маринов Доц. Милена Кулева

ВИДОВЕ ТРАВМИ В ПАРАШУТИЗМА И ПРЕВЕНЦИЯТА ИМ

Капитан III ранг Георги Калинов

ОБУЧЕНИЕ В ХОДЕНЕ С ПОМОЩНИ СРЕДСТВА – РИСКОВЕ И СИГУРНОСТ ЗА ПАЦИЕНТА

Атанас Друмев Доц. д-р Данелина Вачева, доц. д-р Искра Петкова

Книжка 5
ПОДХОДИ ЗА ПСИХОСОЦИАЛНА ПОДКРЕПА НА УНИВЕРСИТЕТСКИ ПРЕПОДАВАТЕЛИ В УСЛОВИЯ НА КРИЗА

Доц. д.н. Цветелина Търпоманова, доц. д.н. Веселина Славова

Книжка 4s
DETERMINING THE DEGREE OF DIGITALIZATION OF A HIGHER EDUCATION INSTITUTION

Acad. DSc. Hristo Beloev, Prof. Dr. Angel Smrikarov, Assoc. Prof. DSc. Valentina Voinohovska, Assoc. Prof. Dr. Galina Ivanova

A STUDY ON THE POSSIBILITIES TO INTEGRATE THE MODERN 3D TECHNOLOGIES IN THE SCIENTIFIC ACTIVITIES OF THE HIGHER EDUCATION INSTITUTIONS

Prof. Dr. Georgi Hristov, Assoc. Prof. Dr. Ivan Beloev, Assoc. Prof. Dr. Plamen Zahariev, Assist. Prof. Dr. Diyana Kinaneva, Assist. Prof. Georgi Georgiev

THE ROLE OF THE UNIVERSITIES AS ACCELERATORS FOR THE INTEGRATION OF THE STEM LEARNING METHODS IN THE PRIMARY AND SECONDARY SCHOOLS

Prof. Dr. Georgi Hristov, Assoc. Prof. Dr. Ivan Beloev, Assoc. Prof. Dr. Plamen Zahariev, Assist. Prof. Georgi Georgiev

ОТ STEM КЪМ BEST: ДВА СТАНДАРТА, ЕДНА ЦЕЛ

Проф. д-р Андрей Захариев, проф. д-р Стефан Симеонов, гл. ас. д-р Таня Тодорова

ВЪЗМОЖНОСТИ ЗА ПРИЛОЖЕНИЕ НА БЛОКЧЕЙН ТЕХНОЛОГИЯТА В ОБРАЗОВАНИЕТО

Докторант Андриан Минчев, доц. д-р Ваня Стойкова

ПРЕДИЗВИКАТЕЛСТВА НА ДИГИТАЛНАТА ТРАНСФОРМАЦИЯ В ОБРАЗОВАНИЕТО – СРАВНИТЕЛЕН АНАЛИЗ НА СТУДЕНТСКОТО МНЕНИЕ

Гл. ас. д-р Мирослава Бонева, доц. д-р Антон Недялков, проф. д.н. Милена Кирова

CHALLENGES, REQUIREMENTS, OPPORTUNITIES AND SOLUTIONS FOR THE DIGITAL TRANSFORMATION OF THE TRANSPORT EDUCATION

Prof. Dr. Georgi Hristov, Assoc. Prof. Dr. Ivan Beloev, Assoc. Prof. Dr. Plamen Zahariev

Книжка 4
EFFECT OF RESILIENCE ON BURNOUT IN ONLINE LEARNING ENVIRONMENT

Dr. Radina Stoyanova, Prof. Sonya Karabeliova, Petya Pandurova, Dr. Nadezhda Zheckova Dr. Kaloyan Mitev

STATE AND PROSPECTS OF DEVELOPMENT OF ACADEMIC MOBILITY IN THE SYSTEM OF TRAINING A SPECIAL EDUCATION SPECIALIST

Dr. Tetiana Dokuchyna, Assoc. Prof., Prof. Dr. Svitlana Myronova, Dr. Tetiana Franchuk, Assoc. Prof.

Книжка 3s
STRATEGIES AND POLICIES TO SUPPORT THE DEVELOPMENT OF AI TECHNOLOGIES IN EUROPE

Assoc. Prof. Miglena Molhova, Assoc. Prof. Petya Biolcheva

BULGARIA'S TECHNOLOGICAL DEVELOPMENT THROUGH THE PRISM OF HIGHER EDUCATION POLICIES

Assoc. Prof. Ivaylo B. Ivanov, Assoc. Prof. Miglena Molhova

INTELLIGENT ANIMAL HUSBANDRY: FARMER ATTITUDES AND A ROADMAP FOR IMPLEMENTATION

Prof. Dr. Dimitrios Petropoulos, Koutroubis Fotios Assoc. Prof. Petya Biolcheva Evgeni Valchev

EFFECTIVE MANAGEMENT OF HUMAN RESOURCES IN TOURISM THROUGH MOTIVATION

Assoc. Prof. Fahri Idriz Assoc. Prof. Marin Geshkov

Книжка 3
САМООЦЕНКА НА ОБЩООБРАЗОВАТЕЛНИТЕ И РЕСУРСНИТЕ УЧИТЕЛИ ЗА РАБОТА В ПАРАДИГМАТА НА ПРИОБЩАВАЩОТО ОБРАЗОВАНИЕ

Проф. д.н. Милен Замфиров, проф. Емилия Евгениева, проф. Маргарита Бакрачева

STUDY OF THE DEVELOPMENT OF THE USE OF COMMUNICATIVE TECHNOLOGIES IN THE EDUCATIONAL PROCESS OF ENGINEERS TRAINING

Assoc. Prof. Ivan Beloev, Assoc. Prof. Valentina Vasileva Assoc. Prof. Sergii Bilan, Assoc. Prof. Maria Bondar, Assoc. Prof. Oksana Bulgakova, Assoc. Prof. Lyubov Shymko

SAFETY THROUGH ARTIFICIAL INTELLIGENCE IN THE MARITIME INDUSTRY

Assoc. Prof. Petya Biolcheva Evgeni Valchev, PhD student

Книжка 2
РАЗПОЛОЖЕНИЕ НА ВИСШИТЕ УЧИЛИЩА В БЪЛГАРИЯ В КОНТЕКСТА НА ФОРМИРАНЕ НА ПАЗАРА НА ТРУДА

Гл. ас. д-р Цветелина Берберова-Вълчева, доц. д-р Камен Петров, доц. д-р Николай Цонков

CHARACTERISTICS AND COMPONENTS OF THE CYBER HYGIENE AS A SUBCLASS OF CYBER SECURITY IN MILITARY ENVIRONMENT AND EDUCATIONAL ISSUES

Prof. Boyan Mednikarov, DSc. Prof. Yuliyan Tsonev Dr. Borislav Nikolov, Prof. Andon Lazarov, DSc.

Книжка 1
MODERNIZATION OF THE CONTENT OF THE LECTURE COURSE IN PHYSICS FOR TRAINING FUTURE AGRICULTURAL ENGINEERS

Dr. Ivan Beloev, Assoc. Prof., Dr. Valentina Vasileva, Assoc. Prof. Prof. Vasyl Shynkaruk, DSc., Assoc. Prof. Oksana Bulgakova, Assoc. Prof. Maria Bondar Assoc. Prof. Lesia Zbaravska, Assoc. Prof. Sergii Slobodian

THE NEW PANDEMIC NORMAL THROUGH THE EYES OF BULGARIAN STUDENTS

Prof. Vyara Stoilova, Assoc. Prof. Todorka Kineva

2022 година
Книжка 6
ORGANIZATION OF AN INCLUSIVE EDUCATIONAL ENVIRONMENT FOR THE STUDENTS WITH SPECIAL NEEDS

Prof. Halyna Bilavych Prof. Nataliia Bakhmat Prof. Tetyana Pantiuk, Prof. Mykola Pantiuk Prof. Borys Savchuk

ДИГИТАЛИЗАЦИЯ НА ОБРАЗОВАНИЕТО В БЪЛГАРИЯ: СЪСТОЯНИЕ И ОБЩИ ТЕНДЕНЦИИ

Д-р Теодора Върбанова, проф. д-р Албена Вуцова, доц. д-р Николай Нетов

СКРИНИНГ НА ЗРЕНИЕТО – ПРОФИЛАКТИКА И ЕЛЕМЕНТ ОТ ПРАКТИКАТА НА СТУДЕНТИ И ОБУЧЕНИЕТО НА УЧЕНИЦИ

Руска Драганова-Христова, д-р Славена Стойкова, доц. д-р Снежана Йорданова

Книжка 5
ПРАВОТО НА ИЗБОР В ЖИВОТА НА ДЕЦАТА В РЕПУБЛИКА БЪЛГАРИЯ

Проф. д.п.н. Сийка Чавдарова-Костова, гл. ас. д-р Даниела Рачева, ас. Екатерина Томова, доц. д-р Росица Симеонова

SUSTAINABLE PROFESSIONAL DEVELOPMENT THROUGH COACHING: BENEFITS FOR TEACHERS AND LEARNERS

Assoc. Prof. Irina Ivanova, Assoc. Prof. Penka Kozhuharova, Prof. Rumyana Todorova

SELF-ASSESSMENT – A COMPONENT OF THE COMPETENCE-BASED TRAINING IN THE PROFESSION “APPLIED PROGRAMMER”

Assoc. Prof. Ivaylo Staribratov, Muharem Mollov, Rosen Valchev Petar Petrov

Книжка 4
BENCHMARKING FOR DEVELOPMENT OF SPEED AND POWER CHARACTERISTICS

Assist. Prof. Dr. Darinka Ignatova Assoc. Prof. Dr. Alexander Iliev

DIAGNOSIS AS A TOOL FOR MONITORING THE EFFECTIVENESS OF ADDICTION PREVENTION IN ADOLESCENTS

Prof. O.A. Selivanova Assoc. Prof. N.V. Bystrova, Assoc. Prof. I.I. Derecha, Assoc. Prof. T.S. Mamontova, Assoc. Prof. O.V. Panfilova

Книжка 3
ПУБЛИЧНОТО РАЗБИРАНЕ НА НАУКАТА В МРЕЖОВИЯ СВЯТ

Д-р Светломир Здравков, д-р Мартин Й. Иванов, д-р Петя Климентова

ОБРАЗОВАНИЕ ЗА УСТОЙЧИВО РАЗВИТИЕ – ПРАКТИКО-ПРИЛОЖНИ АСПЕКТИ

Гл. ас. д-р Златка Ваклева Проф. д-р Тоня Георгиева

Книжка 2
PREPARATION OF PRIMARY SCHOOL TEACHERS FOR COMMUNICATIVE AND RHETORICAL ACTIVITY IN SCHOOL IN THE CONTEXT OF THEIR PRACTICAL TRAINING

Prof. Halyna Bilavych Prof. Nataliia Bakhmat Prof. Tetyana Pantyuk, Prof. Mykola Pantyuk Prof. Borys Savchuk

ПРОЛЕТНА КОНФЕРЕНЦИЯ НА СЪЮЗА НА МАТЕМАТИЦИТЕ В БЪЛГАРИЯ

(Трявна, 5 – 9 април 2022) Гл. ас. д-р Албена Симова

Книжка 1
ДИГИТАЛНАТА ИНТЕРАКЦИЯ ПРЕПОДАВАТЕЛ – СТУДЕНТ В ОНЛАЙН ОБУЧЕНИЕТО В МЕДИЦИНСКИТЕ УНИВЕРСИТЕТИ

Д-р Миглена Търновска, д-р Румяна Стоянова Доц. Боряна Парашкевова, проф. Юлияна Маринова

2021 година
Книжка 6
Книжка 5
ЕДНА РЕКАПИТУЛАЦИЯ НА ИЗСЛЕДВАНИЯ ВЪРХУ ИНТЕРКУЛТУРНИТЕ ОТНОШЕНИЯ. КАКВО СЛЕДВА ОТ ТОВА ЗА ОБРАЗОВАНИЕТО?

Давидков, Ц., 2019. Изследвания върху културите. Културни ориентири на управлението. София: СУ „Св. Климент Охридски“, ISBN 978-954-9399-52-3 Проф. Пламен Макариев

Книжка 4s
RECOGNITION OF FAKE NEWS IN SPORTS

Colonel Assoc. Prof. Petko Dimov

SIGNAL FOR HELP

Ina Vladova, Milena Kuleva

Книжка 4
PREMISES FOR A MULTICULTURAL APPROACH TO EDUCATION

Dr. Anzhelina Koriakina, Assoc. Prof., Prof. Lyudmila Amanbaeva, DSc.

ПОЗИТИВНА ПСИХОЛОГИЯ: ПРОБЛЕМНИ ОБЛАСТИ И ФОРМИРАНЕ НА ЛИЧНОСТТА

Доц. д-р Стоил Мавродиев, Любомира Димитрова

КНИГА ЗА ИСТОРИЯТА НА БЪЛГАРСКОТО ВИСШЕ ИНЖЕНЕРНО ОБРАЗОВАНИЕ

Сгурев, В., Гергов, С., Иванов, Г., 2019. Положителните науки с приложение към индустрията. История на висшето техническо образование в България. София: Изд. на БАН „Проф. Марин Дринов“, Изд. „Захарий Стоянов“. ISBN 978-619-245-004-5, ISBN 978-954-09-1387-2.

Книжка 3
ENTREPRENEURSHIP AND INTERDISCIPLINARY EDUCATION – SEMIOTIC ASPECTS

Prof. Dr. Christo Kaftandjiev Dr. Diana Kotova

THE PRACTICAL IMPORTANCE OF ACCOUNTING EDUCATION FOR FUTURE MANAGERS

Nataliia Radionova, DSc. Dr. Radostina Stoyanova, Assist. Prof.

ЗА ОБРАЗОВАТЕЛНАТА ИНТЕГРАЦИЯ И ЗАЛОЗИТЕ НА НАСТОЯЩЕТО

Нунев, Й., 2020. Мониторинг на процесите на приобщаване и образователна интеграция и модели за десегрегация на ромското образование. Пловдив: Астарта, ISBN 978-954-350-283-7

Книжка 2
Книжка 1
METHODOLOGY OF SAFETY AND QUALITY OF LIFE ON THE BASIS OF NOOSPHERIC EDUCATION SYSTEM FORMATION

Nataliia Bakhmat Nataliia Ridei, Nataliia Tytova, Vladyslava Liubarets, Oksana Katsero

ОБРАЗОВАНИЕ В УСТОЙЧИВО РАЗВИТИЕ И ВЗАИМОДЕЙСТВИЕ „ДЕТЕ – СРЕДА“

Стоянова, М. (2020). Образование в устойчиво развитие и взаимодействие „дете – среда“ София: Авангард принт. ISBN 978-954-337-408-3

2020 година
Книжка 6
HIGHER EDUCATION AS A PUBLIC GOOD

Yulia Nedelcheva, Miroslav Nedelchev

Книжка 5
НАСЪРЧАВАНЕ НА СЪТРУДНИЧЕСТВОТО МЕЖДУ ВИСШИТЕ УЧИЛИЩА И БИЗНЕСА

Добринка Стоянова, Блага Маджурова, Гергана Димитрова, Стефан Райчев

Книжка 4
THE STRATEGY OF HUMAN RIGHTS STUDY IN EDUCATION

Anush Balian Nataliya Seysebayeva Natalia Efremova Liliia Danylchenko

Книжка 3
ПОМОЩНИ СРЕДСТВА И ТЕХНОЛОГИИ В ПРИОБЩАВАЩОТО ОБРАЗОВАНИЕ

Янкова, Ж. (2020). Помощни средства и технологии за деца и ученици със специални образователни потребности в приобщаващото образование.

Книжка 2
МИГРАЦИЯ И МИГРАЦИОННИ ПРОЦЕСИ

Веселина Р. Иванова

SOCIAL STATUS OF DISABLED PEOPLE IN RUSSIA

Elena G. Pankova, Tatiana V. Soloveva, Dinara A. Bistyaykina, Olga M. Lizina

Книжка 1
ETHNIC UPBRINGING AS A PART OF THE ETHNIC CULTURE

Sholpankulova Gulnar Kenesbekovna

ЗА СВЕТЛИНАТА, КОЯТО ИЗЛЪЧВА… В ПАМЕТ НА ПРОФ. Д.П.Н. АСЕМГУЛ МАЛДАЖАНОВА

Нашата редколегия загуби един все- отдаен и неповторим колега и приятел – проф. д.п.н. Асемгул Малдажанова. Пе- дагог по призвание и филолог по мисия! Отиде си от нас нашият приятел, коле- га и член на редколегията на списанието – професор д.п.н. Асемгул Малдажанова – първи заместник-ректор на Евразийския

2019 година
Книжка 6
EMOTIONAL COMPETENCE OF THE SOCIAL TEACHER

Kadisha K. Shalgynbayeva Ulbosin Zh.Tuyakova

Книжка 5
„ОБРАЗОВАТЕЛНИ КИНОХОРИЗОНТИ“ В ПОЛЕТО НА МЕДИА ОБРАЗОВАНИЕТО

(2018). Образователни кинохоризонти. Международен сборник с научни публи- кации по проект „Естетически и образователни проекции на кинодидактиката“. Бургас: Проф. д-р Асен Златаров. Съставител: Маргарита Терзиева. ISBN 978-954-471-496-3

Книжка 4
ВИСШЕТО МОРСКО ОБРАЗОВАНИЕ В КОНКУРЕНТНА СРЕДА

Бакалов, Я. (2019). Висше морско образование. Лидиране в конкурентна среда. Варна: Стено. ISBN 978-619-241-029-2

Книжка 3
УЧИЛИЩЕТО НА БЪДЕЩЕТО

Наталия Витанова

Книжка 2
КНИГА ЗА УСПЕШНИТЕ НАУЧНИ ПУБЛИКАЦИИ

Кожухаров, А. (2018). Успешните научни публикации. Варна: Тера Балканика. ISBN 978-619-90844-1-0

Книжка 1
POST-GRADUATE QUALIFICATION OF TEACHERS IN INTERCULTURAL EDUCATIONAL ENVIRONMENT

Irina Koleva, Veselin Tepavicharov, Violeta Kotseva, Kremena Yordanova

ДЕЦАТА В КОНСТИТУЦИОННИТЕ НОРМИ НА БЪЛГАРИЯ

Румен Василев, Весела Марева

СЪСТОЯНИЕ НА БЪЛГАРСКОТО ОБРАЗОВАНИЕ

Анелия Любенова Любомир Любенов

ИНТЕРКУЛТУРНИЯТ ТРЕНИНГ КАТО ЧАСТ ОТ СТРАТЕГИЯТА ЗА ГЛОБАЛИЗАЦИОННА ИНТЕГРАЦИЯ

Хубенова, М. (2018). Значение на междукултурната комуникация за направления: политически науки, право, икономика и бизнес. София: Издателски комплекс УНСС. ISBN 978-619-232-072-0

ЕДИН НОВ УЧЕБНИК

Дончева, Ю. (2018). Теоретични и методически основи на запознаване с околния свят в детската градина. Русе: Лени Ан

2018 година
Книжка 6
СТРАТЕГИИ НА ОБРАЗОВАТЕЛНАТА И НАУЧНАТА ПОЛИТИКА НАУЧНО СПИСАНИЕ STRATEGIES FOR POLICY IN SCIENCE AND EDUCATION EDUCATIONAL JOURNAL ГОДИНА XXVI / VOLUME 26, 2018 ANNUAL CONTENTS / ГОДИШНО СЪДЪРЖАНИЕ СТРАНИЦИ / PAGES КНИЖКА 1 / NUMBER 1: 1 – 120 КНИЖКА 2 / NUMBER 2: 121 – 224 КНИЖКА 3 / NUMBER 3: 225 – 336 КНИЖКА 4 / NUMBER 4: 337 – 448 КНИЖКА 5 / NUMBER 5: 449 – 560 КНИЖКА 6 / NUMBER 6: 561 – 664

ДИСКУСИОННО / DISCUSSION 211 – 216: Процедурата за назначаване на ръководител на катедра като причина за вло- шаващото се качество на обучението и микроклимата във висшите учи лища у нас [The Procedure for Appointing a Head of Department as a Reason for the Deteriorating Quality of Education and the Microclimate in the Higher School] / Александър Димит- ров / Alexander Dimitrov

Книжка 5
A NEW AWARD FOR PROFESSOR MAIRA KABAKOVA

The staff of the Editorial board of the journal “Strategies for Policy in Science and Education” warmly and sincerely congratulates their Kazakhstan colleague -

ПРОДЪЛЖАВАЩАТА КВАЛИФИКАЦИЯ НА УЧИТЕЛИТЕ – НОРМАТИВЕН И ИЗСЛЕДОВАТЕЛСКИ ОБЗОР

(научно-теоретично обобщение върху проведени обучения на учители)

ЕТНОЦЕНТРИЗМЪТ И ИНЕРЦИИТЕ ОТ МИНАЛОТО – СЕРИОЗНИ ПРОБЛЕМИ В БЪЛГАРСКАТА ОБРАЗОВАТЕЛНА СИСТЕМА

(Eтнопедагогически аспекти на основното и средното образование) Веселин Тепавичаров

Книжка 4
ХРИСТО БОТЕВ И ПОЗНАВАТЕЛНИЯТ КРЪГОЗОР НА СЪВРЕМЕННИТЕ СТУДЕНТИ ЗА ЕВРОПА

Изследователски разказ за един познавателен подвиг и за една познавателна недостатъчност

Книжка 3
BLENDED EDUCATION IN HIGHER SCHOOLS: NEW NETWORKS AND MEDIATORS

Nikolay Tsankov Veska Gyuviyska Milena Levunlieva

ВЗАИМОВРЪЗКАТА МЕЖДУ СПОРТА И ПРАВОТО

Ивайло Прокопов, Елица Стоянова

НАДНАЦИОНАЛНИ И МЕЖДУПРАВИТЕЛСТВЕНИ МЕТОДИ НА ИНТЕГРАЦИЯ В ОБЛАСТТА НА ПРАВОСЪДИЕТО И СИГУРНОСТТА

(Формиране на обща миграционна политика: парадигми и образователни аспекти) Лора Махлелиева-Кларксън

Книжка 2
Книжка 1
ВЪЗПРИЯТИЯ И НАГЛАСИ НА УЧЕНИЦИТЕ ПО ВАЖНИ ОБЩЕСТВЕНИ ВЪПРОСИ

(Данни от Международното изследване на гражданското образование – ICCS 2016)

2017 година
Книжка 6
ЗНАЧИМОСТТА НА УЧЕНЕТО: АНАЛИЗ НА ВРЪЗКИТЕ МЕЖДУ ГЛЕДНИТЕ ТОЧКИ НА УЧЕНИЦИ, РОДИТЕЛИ И УЧИТЕЛИ

Илиана Мирчева, Елена Джамбазова, Снежана Радева, Деян Велковски

ВЪЗПРИЯТИЯ И НАГЛАСИ НА УЧЕНИЦИТЕ ПО ВАЖНИ ОБЩЕСТВЕНИ ВЪПРОСИ

(Данни от Международното изследване на гражданското образование – ICCS 2016)

СТРАТЕГИИ НА ОБРАЗОВАТЕЛНАТА И НАУЧНАТА ПОЛИТИКА НАУЧНО СПИСАНИЕ STRATEGIES FOR POLICY IN SCIENCE AND EDUCATION EDUCATIONAL JOURNAL ГОДИНА XXV / VOLUME 25, 2017 ANNUAL CONTENTS / ГОДИШНО СЪДЪРЖАНИЕ

СТРАНИЦИ / PAGES КНИЖКА 1 / NUMBER 1: 1 – 112 КНИЖКА 2 / NUMBER 2: 113 – 224 КНИЖКА 3 / NUMBER 3: 225 – 336 КНИЖКА 4 / NUMBER 4: 337 – 448 КНИЖКА 5 / NUMBER 5: 449 – 552 КНИЖКА 6 / NUMBER 6: 553 – 672

Книжка 5
ОРГАНИЗАЦИОННА КУЛТУРА В УЧИЛИЩЕ

Ивайло Старибратов, Лилия Бабакова

Книжка 4
КОУЧИНГ. ОБРАЗОВАТЕЛЕН КОУЧИНГ

Наталия Витанова, Нели Митева

Книжка 3
ТЕХНОХУМАНИЗМЪТ И ДЕЙТЪИЗМЪТ – НОВИТЕ РЕЛИГИИ НА БЪДЕЩЕТО

Harari, Y. N. (2016). Homo Deus. A Brief History of Tomorrow. Harvill Secker. ISBN-10: 1910701874

Книжка 2
Книжка 1
РЕФОРМИТЕ В ОБРАЗОВАНИЕТО – ПЕРСПЕКТИВИ И ПРЕДИЗВИКАТЕЛСТВА

Интервю с Габриела Миткова, началник на Регионалното управление на образованието – Силистра

ЕМПАТИЯ И РЕФЛЕКСИЯ

Нели Кънева, Кристиана Булдеева

2016 година
Книжка 6
СТРАТЕГИИ НА ОБРАЗОВАТЕЛНАТА И НАУЧНАТА ПОЛИТИКА НАУЧНО СПИСАНИЕ STRATEGIES FOR POLICY IN SCIENCE AND EDUCATION EDUCATIONAL JOURNAL ГОДИНА XXIV / VOLUME 24, 2016 ANNUAL CONTENT / ГОДИШНО СЪДЪРЖАНИЕ

СТРАНИЦИ / PAGES КНИЖКА 1 / NUMBER 1: 1 – 120 КНИЖКА 2 / NUMBER 2: 121 – 232 КНИЖКА 3 / NUMBER 3: 233 – 344 КНИЖКА 4 / NUMBER 4: 345 – 456 КНИЖКА 5 / NUMBER 5: 457 – 568 КНИЖКА 6 / NUMBER 6: 569 – 672

Книжка 5
Книжка 4
Книжка 3
Книжка 2
Книжка 1
2014 година
Книжка 6
Книжка 5
КОХЕРЕНТНОСТ НА ПОЛИТИКИ

Албена Вуцова, Лиляна Павлова

Книжка 4
ОБРАЗОВАНИЕТО ПО ПРАВАТА НА ЧОВЕКА ПРЕЗ ПОГЛЕДА НА ДОЦ. ЦЕЦКА КОЛАРОВА

Цецка Коларова. (2013). Образование по правата на човека. София: Авангард Прима. ISBN 978-619-160-234-6

USING THE RESULTS OF A NATIONAL ASSESSMENT OF EDUCATIONAL ACHIEVEMENT

Thomas Kellaghan Vincent Greaney T. Scott Murray Chapter 4 Translating Assessment Findings Into Policy And Action Although the primary purpose of a system of national assessment is to describe students’ learning, its role is not limited to description. To justify the effort and expenditure involved, the information that an assessment provides about the achievements of students, their strengths and weaknesses, and how they are distributed in the population (for example, by gender or location

Книжка 3
Книжка 2
PROFESSIONAL DEVELOPMENT OF UNIVERSITY FACULTY: А SOCIOLOGICAL ANALYSIS

Gulnar Toltaevna Balakayeva Alken Shugaybekovich Tokmagambetov Sapar Imangalievich Ospanov

ЗА ПО-ХУМАНИСТИЧНА ТРАДИЦИОННО- ИНОВАЦИОННА ОБРАЗОВАТЕЛНО-ВЪЗПИТАТЕЛНА СТРАТЕГИЯ У НАС

(КОНЦЕПТУАЛНА РАЗРАБОТКА В ПОМОЩ НА ПОДГОТОВКАТА НА НОВ ЗАКОН ЗА ОБРАЗОВАНИЕТО)

Книжка 1
РЕФЛЕКСИЯТА В ИНТЕГРАТИВНОТО ПОЛЕ НА МЕТОДИКАТА НА ОБУЧЕНИЕТО ПО БИОЛОГИЯ

Иса Хаджиали, Наташа Цанова, Надежда Райчева, Снежана Томова

USING THE RESULTS OF A NATIONAL ASSESSMENT OF EDUCATIONAL ACHIEVEMENT

Thomas Kellaghan Vincent Greaney T. Scott Murray Chapter 1 Factors affecting the use and nonuse of national assessment fi ndings The main objectives of a national assessment, as set out in volume 1 of this series, Assessing National Achievement Levels in Education, are to determine (a) how well students are learning in the education system (with reference to general expectations, aims of the curriculum, and preparation for further learning and for life); (b) whether there is evidence of par

2013 година
Книжка 6
Книжка 5
Книжка 4
QUESTIONNAIRE DEVELOPMENT

ÎÖÅÍßÂÀÍÅÒÎ

РОССИЙСКАЯ СИСТЕМА ОЦЕНКИ КАЧЕСТВА ОБРАЗОВАНИЯ: ГЛАВНЫЕ УРОКИ

В. Болотов / И. Вальдман / Г. Ковалёва / М. Пинская

Книжка 3
MASS MEDIA CULTURE IN KAZAKHSTAN

Aktolkyn Kulsariyeva Yerkin Massanov Indira Alibayeva

РОССИЙСКАЯ СИСТЕМА ОЦЕНКИ КАЧЕСТВА ОБРАЗОВАНИЯ: ГЛАВНЫЕ УРОКИ

В. Болотов / И. Вальдман / Г. Ковалёва / М. Пинская

Книжка 2
ОЦЕНЯВАНЕ НА ГРАЖДАНСКИТЕ КОМПЕТЕНТНОСТИ НА УЧЕНИЦИТЕ: ПРЕДИЗВИКАТЕЛСТВА И ВЪЗМОЖНОСТИ

Светла Петрова Център за контрол и оценка на качеството на училищното образование

Книжка 1
Уважаеми читатели,

вет, както и от международния борд за предоставените статии и студии, за да могат да бъдат идентифицирани в полето на образованието пред широката аудитория от педа- гогически специалисти във всички степени на образователната ни система. Благодаря за техния всеотдаен и безвъзмезден труд да създават и популяризират мрежа от научни съобщества по профила на списанието и да насърчават научните изследвания. Благодаря на рецензентите от национално представените висши училища, на- учни институции и

METHODS FOR SETTING CUT SCORES IN CRITERION – REFERENCED ACHIEVEMENT TESTS

ÎÖÅÍßÂÀÍÅÒÎ COMPARATIVE ANALYSIS OF THE QUALITY OF THE SEPARATE METHODS

ПУБЛИКАЦИИ ПРЕЗ 2012 Г.

СПИСАНИЕ „БЪЛГАРСКИ ЕЗИК И ЛИТЕРАТУРА“

2012 година
Книжка 6
DEVELOPMENT OF SCIENCE IN KAZAKHSTAN IN THE PERIOD OF INDEPENDENCE

Aigerim Mynbayeva Maira Kabakova Aliya Massalimova

Книжка 5
Книжка 4
Книжка 3
СИСТЕМАТА ЗА РАЗВИТИЕ НА АКАДЕМИЧНИЯ СЪСТАВ НА РУСЕНСКИЯ УНИВЕРСИТЕТ „АНГЕЛ КЪНЧЕВ“

Христо Белоев, Ангел Смрикаров, Орлин Петров, Анелия Иванова, Галина Иванова

Книжка 2
ПРОУЧВАНЕ НА РОДИТЕЛСКОТО УЧАСТИЕ В УЧИЛИЩНИЯ ЖИВОТ В БЪЛГАРИЯ

* Този материал е изготвен въз основа на резултатите от изследването „Parental Involvement in Life of School Matters“, проведено в България в рамките на проек- та „Advancing Educational Inclusion and Quality in South East Europe“, изпълняван

ВТОРИ ФОРУМ ЗА СТРАТЕГИИ В НАУКАТА

Тошка Борисова В края на 2011 г. в София се проведе второто издание на Форум за страте- гии в науката. Основната тема бе повишаване на международната видимост и разпознаваемост на българската наука. Форумът се организира от „Elsevier“ – водеща компания за разработване и предоставяне на научни, технически и медицински информационни продукти и услуги , с подкрепата на Министер- ството на образованието, младежта и науката. След успеха на първото издание на Форума за стратегии в науката през

Книжка 1
РЕЙТИНГИ, ИНДЕКСИ, ПАРИ

Боян Захариев