Europe and the curriculum – A new approach to evaluate European education in curricula across subjects

Dr. Thomas Benz



In many school curricula in EU's public schools, European competency is perceived as a cross-sectional task ¹² (see Directorate-General for Education, Youth, Sport and Culture, 2020; “Curriculum Reform in Europe: The Impact of Learning Outcomes” 2012), but subjects outside of the social sciences struggle to fulfill these requirements. The German government organization Kultusministerkonferenz (KMK) has been working on defining European competency since the 1970s. In a recent publication (2020) they define a set of competencies at the core of educating for Europe. The competences in summary are 1) geopolitical knowledge of Europe 2) intercultural competence 3) participatory competence 4) multilingual competence. Beyond that, the source stresses the importance of building an individual European identity for every student, which co-exists with other regional modes of belonging like national, regional and local ones. This article relies on the theoretical input provided by above publication and in its course, applies the above competencies to deduce education for Europe in curricula of very different systems of schooling. I am further aided by Curriculum Studies (see for reference Pinar et Al., 2004, 2008; Varbelow, 2012). This American discipline is rarely represented as a discipline in its own rights with research institutes in Europe (see for reference Hopmann & Riquarts 2012; Pinar, 2011). A short look at vastly different understandings of curriculum within curricular documents points towards many definitory shortcomings in the field of practice. A similar issue persists with the definition of competence. I am specifically looking at competences which enable students to navigate the 5 political systems of the Greater Region, Saarland, Rhineland-Palantine, Luxembourg, Grande-Est, French Wallonia and through the results of my analysis, I will also aim to further contribute substance to the working definitions by the KMK above. The border region will be referenced here as Greater Region. The definition of Greater Region is marked on one hand by the geographical inclusion of Rhineland-Palantine, Wallonia in Southern Belgium, Luxembourg, the Saarland, and the French region of Grande-Est, on the other by efforts of cross-border cooperation (see Kooperationsraum-Großregion, n.d.). I am aiming to respond to the following: What (unused) potential for the inclusion of European competency is embedded within middle school curricula across different subjects in a cross-border metropolitan area? Which methodology can reveal these competencies across different curriculum designs?


Methods and Methodology:

Using methods of qualitative meta-synthesis (Bennett et al., 2017; Jones, 2004; Baumeister 2003) I am analyzing large bodies of text authored and published by the curricular authorities of 6 school districts from the French, Luxembourgish, German, and Belgian regions of our metropolitan area. The qualitative meta-synthesis is aided by corpus linguistic procedures to determine not just themes across texts but also their statistical importance. (see Jakubíček et. Al, 2015; Baker & LeTendre, 2014) Doing a qualitative meta review, I am borrowing methodology from Bennett, Driver and Trent’s (2017) theoretical approach to the method of narrative literature reviews. An important departure from the above approaches commonly termed narrative literature reviews, is that the nature of my text required me to deviate from some of the postulates. As the sampled texts are neither always scientific in nature nor far from homogenous in form, I here focus completely on what Leamy et al. (2011) outlined as a narrative synthesis. The latter can be considered a rather recent adaptation of qualitative meta-synthesis to work with qualitative research, as opposed to empirical, often quantitative ones.


As another departure from common qualitative meta-synthesis-approaches, I will establish a rationale for the inclusion of literature, which is a degree of relatedness. As I focus on texts which draw their relevance from the de-facto authority of their authors (curricula – curricular authorities), the validity of my data collection will not necessarily come from the data being scientific, but rather from the data being endorsed. I define endorsement of research, studies, and literature through its retraceable relation to the texts in question.The textual sample comes from middle school subjects, which for one exist in a similar form across all school districts, for second it is checked for selective bias by including solely public-school curricula of all levels of academic performance from ages 12-14 and the age respective grade levels in each school district. To further solidify the selection rationale, I made sure to include the school types, which include the largest populations of students at the above-mentioned age groups.  Lastly the sample manages to include ‘traditional’ candidates in a search for European competency i.e. social sciences, history, but it equally manages to include STEM subjects. Documents are included as long as they are published as curricular to the subject and grade in question by local authorities. The coding of my sample of texts from German and French language texts happened in two steps, one being inductive, and the other deductive coding. Both steps require a coding rationale which is provided through my research question, the question of competencies as connected to European Education.

Inductive Coding: Denzin & Lincoln (2002) mention the possibility of using so called keyword in context (KWIC) as linguistic tools used in the analysis of textual content. This logical formalism was enabled through the use of KWIC and linguistic statistics. Keyness can be described as the relative frequency of terms appearing in a selected textual corpus in relation to a generalized reference corpus for a specific language. Keyness refers to the higher/lower frequency of particular words (termed keywords) in one corpus when compared to their frequency in another corpus (Scott 1999). The significance level of this frequency difference is statistically calculated via log-likelihood tests. Keyword analysis was used to determine words which were significantly more frequent in broadsheets and tabloids (pp. 24-25). The math behind keyness is often associated with problems early corpus linguists faced when applying traditional statistics (for example parametric tests) to textual data. I used the tool SketchEngine (Kilgarriff, 2004) from the website SketchEngine is a fairly advanced statistical toolbox for corpus linguists, which offers functionality similar to WordSmith and beyond that of AntConc. Furthermore, SketchEngine offered accessibility and transparency.

Deductive Coding: I followed a similar analytic design here, but instead of solely relying on my reading to reveal inductive codes from the text sample, I also used an additional layer of logical formalism to guide my reading. The rationale behind that formalism is drawn from the European competency approach as outlined in chapter 1. The deductive coding of term combinations with the highest keyness across all sampled documents resulted in the expression of certain themes with each theme’s significance being underlined through the sum of keyness of all the term combinations it included.
Creation of subsamples:  The research question demands a form of comparison. Such comparison can be achieved through the structuring of the empirical data into subsamples. Curricular documents, depending on definitions, might include a wider or narrower range of genres of mediated production.  Leading to the analysis of the sampled information, I create a rationale of prioritization, to determine which documents were most closely related to the educational reality of the teachers and students. I categorize them as following:  1. Decrees; 2. Quasi-scientific literature; 3. Instruction manuals. As the research question pertains to different school systems and even to different national educational systems, it became imperative to further generate subsamples comparing the contents of curriculum across regions and lastly across subjects.



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