Sampling Criteria in International Comparative Education Research: A Scoping Review to Inform Health Professions Education

König, Franziska; Herinek, Doreen; Matthes, Franziska; Ewers, Michael

doi:10.3390/ime5010024

Abstract

Health Professions Education research is playing an increasing role in ensuring evidence-based practice in Health Professions Education (HPE). To this end, HPE research uses, among other approaches, comparisons as a method in the sense of Comparative Education Research (CER), which allows to compare programs at different levels of education. To obtain evidence-based results, it needs a methodologically sound approach with transparent and justifiable sampling strategies as well as defined sampling criteria. The aim of this research is to identify sampling criteria used in CER for program comparisons and to draw conclusions about what HPE research can probably learn from that. We conducted a scoping review following the Arksey and O’Malley framework, searching three databases and grey literature for international comparative education studies. Four reviewers selected and analyzed the studies using content analysis. A total of 68 studies were included, and six sampling criteria for international CER were identified: (1) culture, (2) education system, (3) curriculum of an education program, (4) ranking, achievement or performance, (5) state and relevance of research, and (6) opportunities and pragmatic reasons. All these criteria appear to be applicable to education research on HPE programs. The sampling criteria derived can serve as a guide for sample selection in international CER and HPE research, providing impetus to improve the quality of research methodology. This necessitates unrestricted access to data on educational programs and a more profound comprehension of the cultural, political and educational characteristics of the respective country.

Keywords:

sampling criteria; sampling strategy; scoping review; education programs; international comparative education research; health professions education

1. Introduction

The field of HPE continues to grow, driven by different education programs, such as disciplinary HPE programs (e.g., undergraduate and postgraduate medical, nursing, and allied health programs) as well as graduate-level programs in HPE, such as Master of Health Professions Education (MHPE) [1,2]. Correspondingly, research activities in HPE have expanded considerably, evolving from basic education studies to increasingly sophisticated and methodologically diverse investigations across multiple dimensions of HPE [3]. Research in the field of HPE aims not only to evaluate the effectiveness of education programs, but also to support their design, improve teaching methods, address curriculum-related challenges, and ensure these programs meet the evolving needs of educators and students [4,5,6,7]. HPE research covers diverse topics, including admissions, curriculum development, evaluation of content and teaching, and the transition to professional practice. This research ensures that HPE remains aligned with current developments in healthcare and education, contributing to global improvements in healthcare system [2,8,9].

One valuable approach to advancing HPE research is through systematically comparing education programs and systems across countries and contexts to identify similarities and differences in educational approaches, outcomes, and structures [10,11,12,13]. Comparisons allow to uncover best practices and provide evidence-based insights applicable to HPE and other educational contexts [14,15,16].

International comparative research activities in HPE require a theoretically and methodologically sound approach to be meaningful. In this context, it is worth considering general and higher education research, particularly the relatively new field of CER. There is an intense debate in this field about what constitutes appropriate CER methods and how to identify existing approaches suitable for the intended comparisons [17,18]. This debate includes discussions about the challenges of CER and the demand for greater plurality in the choice of methods [19,20] and the development of new methods [21,22]. The key challenge in CER is to strike a balance between the unique contexts of the phenomena being studied while maintaining sufficient common ground for comparability and analytical generalizations [23]. This applies to both variable-oriented quantitative research [24,25] and case-based qualitative research [23,26]. Thus, the debate revolves around competing expectations of methodological rigor as essential for meaningful comparisons. These range from calls for increased standardization to arguments that emphasize contextual sensitivity and methodological flexibility.

A transparent and justified sampling strategy that addresses general questions such as the population, sampling and recruitment methods, rationale for sample size and data collection duration is key [27]. Since education systems and programs can vary considerably, it is crucial to select cases that represent the diversity of educational practices and their impacts in order to ensure the quality of international CER [12,28,29]. While sampling alone cannot guarantee that research findings are valid, reliable and applicable beyond the specific study context, a clearly defined sample is essential.

Against this background, this paper addresses the challenges in sampling in international CER that focuses on comparing programs in general or higher education. The aims of our research are (1) to identify sampling criteria used in CER for program comparisons, and (2) to draw conclusions for sampling in comparative HPE research. With the results of this study, we hope to contribute to the discourse about stricter and more reliable sampling criteria in comparative HPE research and ultimately to provide impetus for improving the quality of research methodology in this emerging scientific field.

2. Materials and Methods

We conducted a scoping review using the Arksey and O’Malley framework [30] to compile a broad range of sampling criteria used in CER. This more exploratory review method allows the inclusion of studies with heterogeneous designs and methodologies. This review was prepared in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist guideline [31]. The study protocol has been registered on Open Science Frameworks “https://osf.io/x9uvd/overview” (accessed on 11 January 2026).

2.1. Identifying Relevant Studies

After identifying the research question, we conducted a comprehensive search of several databases, including Web of Science, ERIC, SocINDEX, grey literature sources www.greylit.org (accessed on 23 July 2024), and Google Scholar. Additionally, reference lists of identified articles were manually screened to locate further relevant studies.

We restricted the search to the last 10 years to capture literature reflecting the current state of the field, including contemporary terminology, practices, and contextual conditions relevant to our review question. This time frame also provided a pragmatic and transparent boundary for the evidence-mapping process, consistent with scoping review methodology. Studies that employed all research methods were included; reviews were excluded. Search terms were comparative analysis, comparative education, international, program and/or study (Table 1).

Table 1. Search strategy for Web of Science, ERIC, SocINDEX and grey literature sources (* stands for truncation).

The search was conducted in English. The search strategy was developed in collaboration with an experienced health-based librarian (more detailed information in the acknowledgements). The identification of relevant studies was completed on 31 July 2024.

2.2. Study Selection

Titles and abstracts of all identified papers (n = 1148 after duplicates removal) were screened twice by independent reviewers considering the inclusion criteria (Table 2). The 1148 articles were divided among reviewers D.H., F.M., S.C.S., and F.S.. At the same time, the first author F.K. screened all articles (title and abstract). There was a high degree of agreement due to the jointly developed and adapted inclusion and exclusion criteria. Any discrepancies between the five reviewers were resolved by consensus. To manage references and eliminate duplicates, we used the Rayyan software tool [32]. After the title and abstract screening F.K. read the full texts (n = 100).

Table 2. Characteristics of included and excluded studies.

2.3. Charting the Data

The first author, F.K., extracted the basic study parameters from the included studies into a table and sorted them according to important characteristics, including comparison countries, study design, and education level (Table A1). D.H., F.M., S.C.S., and F.S. then independently checked the table based on a full-text review (n = 100) according to our defined criteria (Table 2). At the end of the selection process, we included n = 68 studies (Figure 1).

Figure 1. Flow diagram of search and study selection process.

2.4. Analysis of Selected Studies and Summary of Results

We conducted a qualitative content analysis [33,34] to identify sampling criteria employed in CER for program comparisons. We analyzed the introductions and methodologies of the literature to describe the study design, the sample size and the sampling procedure of the 68 included studies. The criteria for sampling were only described implicitly in the CER analyzed studies. For this reason, the first author (F.K.) developed inductive categories reflecting the sampling procedure. The sampling criteria were derived from these categories. Next, F.K. discussed the identified sampling criteria with the co-authors (D.H., F.M., S.C.S., and F.S.) during two team meetings. All reviewers agreed on the patterns and thematic concepts. The first author reviewed and recorded all the data and presented the final concepts to the co-authors, who reviewed and refined the sample criteria to ensure the analysis was trustworthy. Furthermore, a frequency count was conducted to determine the number of countries under comparison, the countries most frequently studied, the study designs employed, and the education level of the programs (see Section 3.1 and Table A1).

3. Results

3.1. Study Overview

The 68 eligible studies included research using quantitative (n = 21), qualitative (n = 12), and mixed methods designs (n = 7); document and course syllabus analyses (n = 10); and secondary analyses of international large-scale assessments and social surveys (n = 18). Across the 68 analyzed studies, a total of 79 countries were compared. Most frequently, research was focused on countries in North America and Europe. These countries include the United States (n = 18), Great Britain (n = 18) and Germany (n = 14). In contrast, only five countries from South America and six from Africa were included. The education levels included primary/secondary (n = 22), higher education (n = 41), and adult education (n = 5).

3.2. Sampling Criteria

From the analysis of the studies, we have inductively derived six criteria for sampling selection. Five criteria are based on content-related aspects: Culture (C1), Education system (C2), Curriculum of an education program (C3), Ranking, achievement or performance (C4), and State and relevance of research (C5). One criterion is based on technical considerations in sample selection: Opportunities and pragmatic reasons (C6).

(1): Culture (C1)

Cultural similarities or differences were used to select the sample. This also includes country-specific or regional characteristics. Comparisons have been made between studies examining differences among Asian and Western countries [35,36,37], Western and Eastern countries [38,39], Middle Eastern countries [40], Nordic countries [41], Western Europe and the United States [42] or variations among Arab countries with different political and social contexts [43]. In most cases, sampling decisions were justified by culture particularities. However, in some cases, the pragmatic for selecting specific regions, continents, or geographical areas was not provided [44], or was vaguely attributed to geographic proximity, shared EU membership, or presumed cultural, political, and economic convergence [45,46]. Factors such as academic achievement, social status, and religion in a country or the influence of its history were also considered [36,43,47,48].

(2): Education system (C2)

In some cases, sampling decisions were based on differences or similarities in education systems, which have developed historically and are closely linked to the respective political framework and developments. Differences in education systems are reflected in whether education is provided by state or private institutions [49,50], in the education level at which performance-based differentiation begins [51], and in existing social inequalities [52]. Countries can also be selected according to the expectations of the labor market, reflected in selection procedures, teaching methods, and internship programs [53], or according to the cooperation between educational institutions and the labor market during studies and internships [54].

(3): Curriculum of an education program (C3)

Furthermore, countries were selected based on anticipated differences and similarities in their curricula. A distinction is made between curricula that are less defined, informal, and minimally differentiated, which contribute to lower stratification, and more formalized curricula that explicitly sort students into different tracks [55]. Samples were selected based on the proportion of practical training in the study program, its evaluation, and on the learning methods employed, such as personal professional portfolios, student-led learning, blended learning, and clinical reasoning [56,57,58]. Additionally, the selection of countries was influenced by political demands on degree program content that have yet to be implemented [59]. Finally, the name of the degree program and its associated curricula are also aspects for selection [60,61,62].

(4): Ranking, achievement or performance (C4)

Results of large-scale assessments such as the Program for International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS) were also used to select international CER samples. Countries with the highest and lowest PISA or TIMSS performance levels were contrasted, for example, to demonstrate a correlation between teacher motivation and pupil performance [63]. Similarly, success rates in the performance ranking were also compared with a country’s economic development [64]. In addition to rankings that classified school performance, other ranking systems were used, such as those based on the individualism index [65], which could be utilized to distinguish between collectivist and individualist countries [66].

(5): State and relevance of research (C5)

Countries were selected based on the relevance of the phenomenon under investigation and the existence of previous studies on the programs in those countries. Furthermore, the countries were selected for comparison because the study programs under investigation had already been successfully developed and implemented in programs to address specific issues, such as bullying in schools [67] or stress in universities [68]. This provided other countries with an opportunity to learn from these experiences and adopt a similar best-practice approach [69,70,71,72].

(6): Opportunities and pragmatic reasons (C6)

The sampling criterion of ‘opportunities and pragmatic reasons’ is based on technical considerations in sample selection. This sampling criterion was used in the analyzed studies in conjunction with the convenience sampling strategy. Such convenience samples could be illustrated by students enrolled in the same degree program or attending the same conference [73,74,75,76,77] or studying at partner universities [78]. Another common reason was the researcher’s origin and geographical proximity to the surveyed group, such as when the researchers contributed to the analyzed program [79]. Sample selection was predicated on its accessibility, rather than on the theoretical framework or research question of the study.

3.3. Study Criteria Application

The six identified sampling criteria were applied individually or in combination in the analyzed studies. To highlight differences between countries, typically only one criterion was used, for example culture differences (C1). To justify the selection of countries and institutions, two criteria were commonly applied, such as differences between the curricula of education programs (C3) and pragmatic reasons, like the researcher`s geographical proximity to the surveyed group (C6). Criteria C1 to C5 were primarily used for country selection at the macro level. Educational institutions or individuals at the meso- or micro levels were often selected based on criterion C6 or without justification.

4. Discussion

The aim of this review was (1) to identify sampling criteria used in CER for program comparisons, and (2) to draw conclusions for sampling in comparative HPE research. We identified six sampling criteria used in the included literature: Five content-related criteria (C1-Culture, C2-Education system, C3-Curriculum of an education program, C4-Ranking, achievement or performance, and C5-State and relevance of research) and one criterion based on technical considerations (C6-Opportunities and pragmatic reasons).

As emphasized in the introduction with reference to Park et al. [18], transparent and well-defined sampling criteria are essential for ensuring research quality in CER and HPE. This perspective is shared by other authors in the field [26]. However, most CER studies analyzed rarely provided detailed justifications for their sampling decisions, making it difficult to understand the methodology and assess the validity of the comparisons. For this review, these criteria needed to be derived inductively from the analyzed studies because they were usually only mentioned implicitly rather than explicitly stated and justified in the methodology sections. This is all the more problematic given that both HPE and CER research often aim to compare education programs and measures within complex education systems [11,12,80]. HPE research has an additional layer of complexity because it operates at the intersection of education and health systems, each of which has its own regulatory, ethical, and structural conditions. Therefore, comparative research in this context is further complicated by the need to consider clinical realities, patient safety, professional regulations, and competency-based outcomes. Clear documentation of sampling decisions in HPE research allows other researchers to evaluate the selection of countries and programs, enabling them to draw appropriate insights and conclusions [8]. Creating and using reporting guidelines for this type of CER could improve the situation and encourage researchers to disclose their sampling criteria.

Our analysis reveals that sampling rationales in CER studies are often more transparent at the macro level than on the meso or micro levels. CER studies at the macro level often provide clear justifications for the selection of particular countries based on criteria such as cultural differences (C1) or education system characteristics (C2). However, explicit justifications are often lacking at the meso and micro levels (e.g., selection of specific institutions or programs, and selection of individual participants). This lack of transparency at the meso and micro levels poses a serious challenge, because these levels directly impact on the comparability of education programs and learners’ experiences. Without justification of institutional or participant-level choices, it becomes difficult to determine whether observed similarities or differences stem from the programs themselves or from selection bias introduced by unarticulated sampling decisions. This pattern suggests a critical gap in methodological transparency that HPE research should address [81].

In order to make meaningful and methodologically sound comparisons, the sampling criteria must be clearly defined and applied consistently at all three levels. From the perspective of CER, sampling decisions are not neutral; rather, they reflect assumptions about which structural, institutional, or cultural dimensions are analytically relevant. The Framework for Comparative Education Analyses developed by Bray et al. can be used to justify and describe sample selection in more detail, taking into account the micro, macro, and meso levels [22]. In this framework the three levels are further differentiated: Level 1: Individual (micro); Levels 2 and 3: Classroom and school (meso) and Levels 4, 5, and 6: District, states/provinces, countries, world regions/continents (macro) [22]. It is particularly important to systematically formulate and apply sampling criteria at all these different levels, as clinical training structures and access to practice environments vary considerably between institutions and countries. Careful consideration should therefore be given to how sampling criteria are applied at all three levels to ensure that comparisons are meaningful and methodologically sound. This could be included in reporting guidelines for comparative HPE research. In addition to the criteria derived inductively in this study, established comparative education approaches—such as system-based criteria that focus on similarities and differences in education [22] or health systems and culturally informed perspectives [65]—can further support an analytically grounded selection of cases.

A convenience sample (C6) is commonly used in CER and HPE when access to education programs or research participants is limited. HPE research faces specific access barriers, including the limited availability of clinical learning environments, regulatory restrictions on international collaborations, ethical considerations in healthcare, and the heterogeneity of professional roles across different healthcare systems [8,20]. These challenges require flexible sampling procedures that take practical constraints into account while maintaining theoretical rigor [27]. However, the methodological literature in CER also points to problems due to methodological limitations and reflects practical constraints when using convenience samples [81]. Strengthening methodological reflection requires a clearer discussion of the potential consequences of using convenience sampling. These consequences include limited representativeness, excessive dependence on existing partners, and the selection of institutions that are easily accessible, making it easy to collect samples. Our findings suggest that the strategic use of C6 in combination with other criteria allows for methodologically sound adaptations to real-world research conditions, e.g., selection based on convenience and due to different curricula [78,82]. Furthermore, geographical proximity, linguistic compatibility, and existing institutional partnerships can be strategic responses to subject-specific constraints if they are transparently justified and combined with substantive selection criteria [79,83].

To meet the challenges of HPE, the application of the above sampling criteria requires subject-specific adjustments that reflect the particular characteristics of HPE. For instance, when applying the criterion “curriculum of an education program” (C3), sample selection in HPE research should focus on differences in educational content, teaching methods, program structures, educational policy frameworks, different professional legal frameworks, professional competency requirements and different models of clinical training integration [84]. Similarly, the “ranking and performance criterion” (C4) must be expanded to include health-specific metrics, such as patient outcomes, success rates in obtaining professional licenses, and integration into health systems. The status and relevance of the “research criterion” (C5) are particularly important in HPE research because the implementation of educational innovations has the potential to impact on professional practice and patient care. When applying this criterion, countries with comparable or different healthcare challenges, workforce structures or professional development needs could be considered. In addition to adapting the sampling criteria to the specificities of the HPE context, additional sampling criteria could be developed to reflect the unique characteristics of HPE. These criteria could include health system integration, professional regulatory frameworks, clinical practice settings, and patient safety considerations [3,85].

This review has strengths as well as limitations. For the first time, this review systematically compiled and analyzed studies in international CER to determine which sampling criteria are used to examine education programs, and to provide impetus for the future design of HPE. Sampling criteria were identified to contribute to the development of more rigorous and reliable research in the field of international CER and HPE, and ultimately to improve the quality of research methodology in these areas. However, there are several limitations to be considered. The review is limited to three databases focusing on education articles published in English. To obtain results reflecting the current methodological approach in CER, the search period was limited to ten years. The search could have distinguished between different levels of CER research or focused on articles about higher education. However, this was not done to gain a general understanding of the sampling criteria used in CER.

5. Conclusions

The sampling criteria derived from studies on education programs in CER can serve as an orientation for sample selection in international CER and HPE research, or at least provide impetus for improving the quality of methodology in these fields of research. Beyond providing a descriptive overview of existing criteria, this study highlights the central importance of sample selection in comparative CER and HPE research, which determines not only what is compared, but also what forms of comparison are possible. A key implication of this review is that sample selection decisions in comparative HPE research should be understood as theoretically grounded and multi-stage processes rather than purely technical or pragmatic decisions. To enable a transparent and analytically sound selection process, selection criteria should be systematically developed and explicitly justified for all three levels: macro (e.g., selection of countries or regions), meso (e.g., selection of specific institutions or programs), and micro (e.g., selection of individual participants). Future studies should therefore consciously integrate the three levels and reflect on their interrelationships when combining different sampling criteria.

The present study focused on sampling in CER. Further studies are needed that specifically address and analyze the sampling procedure in HPE. Additionally, quantitative and qualitative studies should evaluate the sampling criteria for different research designs. Qualitative studies could explore how the proposed criteria are understood and applied in different institutional and national contexts. This would help to identify context-specific challenges and unintended effects. Conversely, quantitative studies could examine the robustness and comparability of the criteria across larger samples and assess their implications for the validity and generalizability of comparative findings.

Furthermore, the findings underscore the importance of embedding sampling strategies in a broader understanding of cultural, political, and educational contexts. Deeper engagement with these contextual dimensions is essential for assessing the comparability of cases and for interpreting similarities and differences meaningfully. Future research should explicitly state the contextual assumptions underlying sampling decisions and explain how these assumptions influence comparative interpretations. To improve transparency and cumulative knowledge building in this area, we strongly recommend developing reporting guidelines for comparative educational research in HPE.

In terms of methodological development, two concrete recommendations emerge from this study. First, future research could evaluate the proposed sampling criteria through both qualitative and quantitative studies to assess their applicability, robustness, and limitations in different comparative designs. Second, unrestricted access to data on education programs could be considered a prerequisite for high-quality comparative HPE research, requiring the commitment of both research and educational institutions.

Author Contributions

Conceptualization, F.K.; methodology, F.K., D.H. and F.M.; software, F.K. and D.H.; validation, F.K., D.H. and F.M.; formal analysis, F.K.; investigation, F.K.; resources, M.E.; data curation, F.K.; writing—original draft preparation, F.K.; writing—review and editing, F.K., D.H., F.M. and M.E.; visualization, F.K.; supervision, M.E.; project administration, M.E. All authors have read and agreed to the published version of the manuscript.

Funding

The authors declare that they have not received a grant from funding agencies in the public, commercial, or not-for-profit sectors (institutional funding).

Data Availability Statement

The original contributions presented in this study are included in the article (Appendix A: Table A1).

Acknowledgments

The authors would like to thank Simone Campos Silva (S.C.S.) and Fabio Schnepf (F.S.), for their contribution to the study selection. Many thanks also to Joshua Paul, for his careful proofreading and helpful suggestions for linguistic improvement. Finally, the authors would like to say thank to Corinna Dressler, and Meghan R. Forrest for their professional support in compiling the review [86].

Conflicts of Interest

The manuscript has been read and approved by all the authors. Language editing assistance was provided by DeepL. The tool was used solely for grammar correction and stylistic improvement. The authors are responsible for all ideas and conclusions presented. The authors declare no conflicts of interest.

Appendix A

Table A1. Data extraction table.

Nr.	Reference (First Author, Publication Year, Origin Country of First Author)	Compared Countries	Instrument for Comparison	Sample Strategy	Sample Criteria	Education Level
1	Abazaoğlu & Aztekin 2016, Turkey [63]	Singapore, Japan, Finland, Turkey	Program for International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS)	Comparison of the best and worst performing countries in the PISA and TIMSS large-scale assessments	Ranking, achievement or performance	Primary/secondary education
2	Abdullah & Hassanpour 2021, Turkey [40]	Turkey (North Cyprus), Iraq	Mixed methods study analyzing curricula, documents and qualitative Interviews with educators	Comparison of universities in middle East with a digital design course in architectural education	Culture	Higher education
3	Altun & Kalkan 2021, Turkey [87]	Singapore, Turkey and Italy	PISA	Comparison of the best, average and worst performing countries in the PISA large-scale assessment	Ranking, achievement or performance	Primary/secondary education
4	Baikady et al. 2023, South Africa [37]	India and China	Qualitative interviews using self-developed online questionnaire	Comparison of Asian countries with universities offering the analyzed program in social work	Culture	Higher education
5	Barnes 2021, Hungary [70]	Australia and USA	Qualitative Interviews using self-developed questionnaire	Comparison between a university where the program in question has already been implemented and a university where the program is yet to be implemented	State and relevance of research	Higher education
6	Berková et al. 2023, Czech Republic [73]	Czech Republic, Belgium, Germany, Greece, the Netherlands, and Poland.	Cross-sectional study using self-developed questionnaire	Convenience sample of partner universities and members of the same program in engineering	Opportunities and rational reasons	Higher education
7	Bernardi & Valdés 2021, Italy [51]	Australia, Chile, Denmark, Estonia, Finland, Iceland, Ireland, Latvia, Lithuania, Poland, Norway, Spain, Sweden, UK (OECD countries)	PISA	The comparison countries are OECD countries with similar education systems	Education system	Primary/secondary education
8	Bodovski et al. 2017, USA [39]	Czech Republic, Hungary, Russian, Poland, France, Germany	PISA	Comparison between Western benchmark countries and Eastern benchmark countries. All countries have gone through post-socialist transformations during the last two decades.	Culture	Primary/secondary education
9	Carnoy et al. 2015, USA [38]	Czech Republic, Hungary, Poland, Estonia, Latvia, Lithuania, Sweden, Finland and Germany	Mixed method: PISA and Interviews with educators	Comparison between neighboring former-communist countries and some Western European countries with social democratic traditions	Culture	Primary/secondary education
10	Chen et al. 2023, China [67]	United States, UK, China, Japan, South Korea	PISA	Comparison between universities in Western countries, where the study program in question has already been successfully introduced and universities in East Asian Countries where the program is yet to be implemented	State and relevance of research	Primary/secondary education
11	Cheung 2017, China [88]	China, Singapore, Taiwan and Korea	PISA	Comparison of the top five high performing Asian countries in the PISA large-scale assessment	Ranking, achievement or performance	Primary/secondary education
12	Chitsamatanga et al. 2018, South Africa [52]	South African and Zimbabwean	face to face using self-developed online questionnaire	Comparison of non-industrial countries with different academic and educational backgrounds	Education system	Adult education
13	Clivaz & Miyakawa 2020, Switzerland [75]	Switzerland, Japan	Face-to-face meetings (Analysis of mathematics lessons in different countries)	Convenience sample with members of the same education program	Opportunities and rational reasons	Higher education
14	Coffey et al. 2014, UK [68]	India and UK	Cross-sectional study using questionnaire originally developed for the compared study	Comparison of region with high suicide rate among students in India with an existing study in UK, using existing instrument from the comparative study	State and relevance of research	Higher education
15	Crisp 2017, Australia [82]	Australien, Danmark, Hungary, Sweden, UK	Curricula analyses	Convenience sample of partner universities with the same problems in developing a new curriculum for the program under study	Opportunities and rational reasons	Higher education
16	Cummins et.al. 2022, USA [89]	France, Canada, the United Kingdom, USA	PIAAC	Countries compared had participated in the large-scale Adult Skills Assessment Survey PIAAC and established funding systems for adult education	Ranking, achievement or performance	Adult education
17	De La Fuente Robles & Cano 2020, Spain [90]	Spain, Cyprus, Czech Republic, Germany, Italy, Portugal, United Kingdom, Netherlands, Poland, Slovak Republic	Curricula and document analyses	Comparison of universities with a high level of international mobility and a long tradition of Erasmus programs (Convenience sampling).	Opportunities and rational reasons	Higher education
18	Dearden & Macaro 2016, UK [76]	Italy, Germany, Austria, Poland	Qualitative interviews using self-developed online questionnaire	Convenience sample with members of the same conference.	Opportunities and rational reasons	Higher education
19	Devos et al. 2021, France [61]	15 countries	Cross-sectional study using self-developed online questionnaire for nursing educator	All compared universities providing undergraduate nursing programs (worldwide full survey).	Curriculum of an educational program	Higher education
20	El Islami et al. 2022, Indonesia [57]	Indonesia, Vietnam, Thailand	Curriculum analysis	Comparison of countries with a renewed curriculum and belonging to an alliance and region (Association of Southeast Asian Nations and countries of the Global South)	Curriculum of an educational program	Primary/secondary education
21	Fernández Espinosa & López Gonzále 2024, Spain [48]	17 countries	Cross-sectional study using self-developed questionnaire for school managers and teachers	Comparison of Spanish speaking countries from a region with a Christian tradition, a cooperation already exists between the schools	Culture	Primary/secondary education
22	Flem et al. 2017, Norway [72]	Denmark, Norway and Sweden	Curriculum analysis	Scandinavian countries were compared in which the curriculum studied was introduced for the first time and in which cooperation between schools already exists	State and relevance of research	Higher education
23	Forbes et al. 2020, USA [91]	Netherlands, Japan, Korea, Denmark, Germany, USA, France, Czech Republic, Indonesia, Mexico, Hungary, Bulgaria, Romania	PISA	Comparison of the best and worst performing countries in the PISA large-scale assessment	Ranking, achievement or performance	Primary/Secondary education
24	Frick & Pyhältö 2022, South Africa [79]	South Africa, Finland	Cross-sectional study using questionnaire for students	Countries were selected based on the regional and content-related proximity of the researchers and the socio-economic differences between the countries	Opportunities and rational reasons	Higher education
25	Gard & Dagis 2016, Sweden [50]	Sweden, India	Cross-sectional study using self-developed questionnaire for students	Countries were selected on the basis of different educational systems and differences in the curriculum of the program analyzed	Education system	Higher education
26	Guraya et al. 2021, United Arab Emirates [58]	United Arab Emirates, the Kingdom of Saudi Arabia, Malaysia	Cross-sectional study using self-developed questionnaire for students	Chosen universities have a similar curriculum with some elements of medical professionalism in their curricula	Curriculum of an educational program	Higher education
27	Hagenauer et al. 2016, Switzerland [66]	Australian, German	Qualitative study using semi-structured face-to-face interviews	Comparison of the countries that score highest on the Individualism Index; comparison of countries also represents the personal cultural background of the authors	Ranking, achievement or performance	Adult education
28	Hammerness et al. 2020, USA [56]	Chile, Cuba, Finland, Norway, USA	Mixed methods study using data from surveys of program candidates, observations of methods courses, and interviews with program faculty and students	Comparison of countries based on the differences in the implementation and organization of the internship during the study	Curriculum of an educational program	Higher education
29	Huang & Oga-Baldwin, 2015, Taiwan [92]	Japan, Taiwan	Cross-sectional study using questionnaire for graduates (Survey instruments were taken from previous research assessing teacher education programs).	Selection of countries based on similarities in the expectations of graduates in the teaching profession	Education system	Higher education
30	Hutchinson & Korazim-Kőrösy 2017, Norway [41]	Denmark, Norway, Sweden, Finland and Greenland, USA, Canada, Israel and Hungary	Cross-sectional study using online self-developed questionnaire	Nordic countries which follow either the social democratic welfare model or the liberal welfare model; countries are members of the Nordic Association of Schools of Social Work (NASSW).	Culture	Higher education
31	Ibrahim et al. 2021, Palestine [93]	Palestine, Qatar, Tunisia	Cross-sectional study using self-developed questionnaire for students	Arabic countries with different higher education systems	Education system	Higher education
32	Ibrahim 2017, Palestine [43]	22 Arab countries	Cross-sectional study using questionnaire for educator	Arabic countries with different political and social systems	Culture	Higher education
33	Johnson & Činčera 2015, USA [74]	US, Czech	Mixed methods study using a qualitative questionnaire and qualitative interviews with children	Participants from the same education program	Opportunities and rational reasons	Primary/secondary education
34	Karakoç Alatli 2020, Turkey [94]	Turkey, Singapore	PISA	Comparison of the best and worst performing countries in the PISA large-scale assessment	Ranking, achievement or performance	Primary/Secondary education
35	Kaya 2022, Turkey [64]	Singapore, Turkey, UK	TIMSS	Comparison of the best and worst performing countries in the TIMSS large-scale assessment; comparison of countries with different economic development	Ranking, achievement or performance	Primary/secondary education
36	Kılıc Depren & Depren 2022, Turkey [95]	Turkey, China	PISA	Comparison of the best and worst performing countries in the PSA large-scale assessment	Ranking, achievement or performance	Primary/secondary education
37	Kim & Celis 2016, USA [96]	Brazil, Peru, Argentinian, Chile and Singapore, Australian, South Korea, Hong Kong, Philippines, Venezuela, Japan, Thailand, Indian, Mexico	Quantitative social network analysis	Comparison of programs in Latin America, Asia and Oceania based on their high ranking in the evaluation	Ranking, achievement or performance	Higher education
38	Kobernyk et al. 2022, Ukraine [42]	UK, Denmark, France, Germany, Austria, US	Curricula analysis and document analysis	Comparison of countries in Western Europe and USA with the same education program	Culture	Higher education
39	Kwarteng & Servoh 2023, Ghana [44]	Africa: Ghana, South Africa, Kenya, Egypt; Europe: England, Belgium, Lithuania, Cyprus; Asia: Hong Kong, Singapore; North Amerika: USA	Curricula analysis	Comparison of universities in Africa (one from each of the East, West, North, and Southern regions) and universities from Europe, Asia, and America.	Culture	Higher education
40	Labra et al. 2023, Canada [62]	Belgium, Canada, Chile, Switzerland	Cross-sectional study using self-developed questionnaire for students	Comparison of countries with the same education program	Curriculum of an educational program	Higher education
41	Lake et al. 2017, USA [78]	Nicaragua, USA	Curriculum analysis	There is a partnership between the selected schools	Opportunities and rational reasons	Higher education
42	Leung et al. 2018, USA [97]	USA, UK, Australia	Curriculum analysis	Comparison of programs based on their high ranking in the evaluation and their focus on the field of study	Ranking, achievement or performance	Higher education
43	Levy et al. 2022, UK [98]	UK, Nigeria	Cross-sectional study using self-developed online questionnaire for students	Partnership between the selected schools	Opportunities and rational reasons	Higher education
44	Meng et al. 2017, China [99]	China, USA	PISA	Countries with good and poor results in the PISA large-scale assessment were compared	Ranking, achievement or performance	Primary/Secondary education
45	Mulero et al. 2022, Spain [100]	Spain, Greece, Lithuania, Poland, Portugal	Cross-sectional study using self-developed questionnaire for students	Partnership between universities and geographical proximity of the researchers; participating in the same project	Opportunities and rational reasons	Primary/secondary education
46	Ní Fhloinn & Fitzmaurice 2022, Ireland [60]	29 countries	Cross-sectional study using online questionnaire for students	Comparison of all universities with a mathematic institute in Europe (full survey)	Curriculum of an educational program	Higher education
47	Nonte et al. 2018, Germany [46]	France, Germany, Italy, Netherlands	PIRLS	Neighboring countries commonly share a major intersection of cultural, political, social, and economic factors	Culture	Primary/secondary education
48	Novotná et al. 2021, Czech Republic [101]	Czech Republic, Hungary	Document analyzes	Comparison of countries with similar historical development of the education systems	Education system	Higher education
49	Prendergast & Hongning 2016, Ireland [36]	Ireland, China	Cross-sectional study using self-developed questionnaire for students	Historical differences in the emphasis of learning and the importance of the analyzed school subject; authors are math teachers in the selected countries	Culture	Primary/secondary education
50	Rasmussen & Bayer 2014, Denmark [102]	Canada, Denmark, Finland, Singapore	Document analysis	Comparing the curricula of teacher education programs in the best and worst performing countries in the PISA large-scale assessment	Ranking, achievement or performance	Higher education
51	Salajan et al. 2017, USA [103]	USA, Romania	Mixed methodology using content analysis of documents containing program descriptions/curricula and qualitative interviews with students.	Convenience sample of the same education program	Opportunities and rational reasons	Higher education
52	Sanders et al. 2023, Australia [104]	30 countries	Two cross-sectional study using self-developed questionnaire quantitative study	Convenience sample with members of the same training course	Opportunities and rational reasons	Adult education
53	Sa-Nguanmanasak & Khampirat 2019, Thailand [105]	Thailand, Malaysia	Cross-sectional study using self-developed questionnaire for students	Comparison of countries with different rankings in terms of the quality of graduates’ qualifications	Ranking, achievement or performance	Higher education
54	Sin et al. 2017, UK [69]	UK, China, Malaysia	Mixed methods study using semi-structured interviews, focus group, a written interview and an audio interview for students and graduates	Comparison of two studies on a program implemented in two different countries; the program was developed by a third country and is to be improved	State and relevance of research	Higher Education
55	Soto-Sanfiel et al. 2018, Spain [45]	Croatia, France, Germany, Italy, Spain, UK	Cross-sectional study using a questionnaire for students	Comparison of countries of the European Union	Culture	Higher education
56	Sulosaari et al. 2023, Finland [106]	Denmark, Finland, Estonia, Iceland, Lithuania and Norway	Curriculum analysis	Comparison between Nordic and Baltic countries, as the program in question has only recently been introduced in this region	Curriculum of an educational program	Higher education
57	Tan & Liu 2018, China [35]	Singapore, Hong Kong, Taipei, Korea, Macau, and Japan, Switzerland, Netherlands, Estonia, Finland, Canada, Poland, Belgium, Germany, Australia	PISA	Comparison of Confucian heritage cultures and non-Confucian heritage cultures with different educational and economic development	Culture	Primary/secondary education
58	Tannehill et al. 2021, Ireland [83]	Austria, Belgium, Bulgaria, Czech Republic, Croatia, France, Germany, Greece, Ireland, Italy, Latvia, Lithuania, Luxembourg, Macedonia, Malta, the Netherlands, Norway, Poland, Portugal, Slovakia, Spain, Sweden, Turkey, UK	Expert survey	Experts for the analyzed education program were selected among Erasmus-program countries	Opportunities and rational reasons	Higher education
59	Tham et al. 2023, Sweden [53]	Australia, England, Finland, Northern Ireland, Sweden, USA	Mixed methods: document analyses and qualitative interviews with experts	Countries compared have different professional systems in which social workers practice; experts were chosen based on their significant professional and research experience	Education system	Higher education
60	Tiede & Grafe 2016, Germany [59]	Germany, USA	Mixed methods: qualitative semi-structured interviews and a quantitative questionnaire	Comparison countries support the integration of media education in teacher on the basis of political demands, but without a binding national (legal) obligation	Curriculum of an educational program	Higher education
61	Tsai et al. 2017, Taiwan [107]	Taiwan, Japan, South Korea, USA, Germany, Czech Republic	PISA	Comparison of countries from East Asia, Europe and the USA; education systems differ, e.g., in their cultural expectations of student achievement and in their traditions of promoting vocational training	Education system	Primary/secondary education
62	Urick et al. 2022, USA [55]	USA, Belgium	TIMSS	Comparison of countries with less-identified/informal tracking/differential curricula which produces stratification versus formalized system which explicitly sorts students into distinct tracks	Curriculum of an educational program	Primary/secondary education
63	van der Klink et al. 2017, Netherlands [77]	Netherlands, Israel, Japan, Australia, Czech Republic, Belgium	Qualitative Interviews	Convenience sample of participants in a conference	Opportunities and rational reasons	Adult education
64	van der Merwe et al. 2014, South Africa [49]	South Africa, UK	Mixed methods: analysis of curricula/documents and focus groups with semi-structure questionnaire	Comparison of countries with similar education systems and similar foci and quality criteria of the analyzed program	Education system	Higher education
65	Van Noord et al. 2019, Netherlands [47]	31 countries	Data from the International Social Survey Program (cross-national collaboration on nationally surveys)	Comparison of Western countries with cultural differences	Culture	Higher education
66	Widyaningrum et al. 2019, USA [71]	India, Indonesia, USA	Mixed methods: qualitative interviews with experts and analysis of curricula	Comparison of countries with a long and a short history of the occupational field under investigation	State and relevance of research	Higher education
67	Yalçın 2017, Turkey [108]	Netherlands, Turkey	PISA	Comparison of the best and worst performing countries in the PSA large-scale assessment	Ranking, achievement or performance	Primary/secondary education
68	Haanwinckel et al. 2018, Brazil [54]	Brazil, England	Semi-structured interviews with experts from the field under investigation	Comparison of countries based on the differences in the implementation and organization of the internship during the study	Education system	Higher education

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