IQB Trends in Student Achievement 2018 (IQB-BT 2018)

(formerly known as IQB National Assessment Study)

 

Table of contents

Project description

Blank data sets

Documentation

Notes on the use of the data

Literature

 

> Link to application form (Scientific Use Files)

Data Set Published on 30.06.2022
Version v2
Current Version Available Since 23.05.2024
Survey Period 2018
Sample Students in grade 9 (N=44,941); Teachers (N=5,026); Principals (N=1,264); Schools (N=1,471)
Survey Unit Parents
Principals
Students
Teachers
Measured Competencies Mathematics, Biology, Chemistry, Physics
Region Germany, Baden-Wuerttemberg, Bavaria, Berlin, Brandenburg, Bremen, Hamburg, Hesse, Mecklenburg-Western Pomerania, Lower Saxony, North Rhine-Westphalia, Rhineland-Palatinate, Saarland, Saxony, Saxony-Anhalt, Schleswig-Holstein, Thuringia
Principal Investigators Mahler, Dr. Nicole
Schipolowski, Dr. Stefan
Stanat, Prof. Dr. Petra
Data Producers Institut zur Qualitätsentwicklung im Bildungswesen (IQB)
Funded by Standing Conference of the Ministers of Education and Cultural Affairs of the Länder in the Federal Republic of Germany
Link https://www.iqb.hu-berlin.de/bt/BT2018/
Related Studies IQB-LV 2012 (DOI: 10.5159/IQB_LV_2012_v4)
Suggested Citation Stanat, P., Schipolowski, S., Mahler, N., Weirich, S., Henschel, S., Holtmann, M., Becker, B., & Kölm, J. (2022). IQB-Bildungstrend Mathematik und Naturwissenschaften 2018 (IQB-BT 2018) [IQB Trends in Student Achievement 2018 (IQB-BT 2018)] (Version 2) [Data set]. Berlin: IQB – Institut zur Qualitätsentwicklung im Bildungswesen. http://doi.org/10.5159/IQB_BT_2018_v2
Restriction Notice A restriction notice (Sperrvermerk) exists with regard to the data of this study, i.e., some topics and variables have been blocked by the data producer(s) in order to protect ongoing research and publication projects of members of their institution(s). If you wish to apply for access to these data and would like further information on the restriction, please do not hesitate to contact us.

Cognitive abilities must not be used as a dependent variable in the analyses.

Users of the data set should always cite the scale manual:

Becker, B., Busse, J., Holtmann, M., Weirich, S., Schipolowski, S., Mahler, N., & Stanat, P. (2022). IQB-Bildungstrend 2018. Skalenhandbuch zur Dokumentation der Erhebungsinstrumente in Mathematik und den naturwissenschaftlichen Fächern. [IQB Trends in Student Achievement 2018 scaling manual. Documentation of the survey instruments in the subjects Mathematics and Natural Sciences] Berlin: Humboldt-Universität zu Berlin, Institut zur Qualitätsentwicklung im Bildungswesen. https://doi.org/10.18452/25472

 

Project description

The IQB Trends in Student Achievement 2018 represents the second country comparison of the Institute for Educational Quality Improvement (IQB) in mathematics and in the science subjects biology, chemistry and physics at lower secondary level. In these subjects, the competences of students in the 9th grade were examined in 2018. This makes it possible for the first time to describe development trends at the population level with regard to the achievement of the educational standards in these subjects for the federal states in the Federal Republic of Germany. In addition to taking stock of the situation in 2018, the data, in conjunction with the The National Assessment Study in Mathematics and Science 2012, enable trend analyses to show the extent to which the level of competency achieved by ninth graders in the subjects studied has changed since 2012. The basis of the competence measurements are the educational standards of the Standing Conference of the Ministers of Education and Cultural Affairs of the Länder (Kultusministerkonferenz), which are binding for all Länder and define subject-specific competences that pupils should have developed by a certain point in their school career. In addition to the competencies achieved by ninth graders, the data can also be used to analyse gender-related, social and immigration-related disparities, for example, and to examine the extent to which these have changed since 2012. In addition, motivational characteristics of the students, aspects of teaching quality in mathematics and information on the training and further education of teachers in mathematics and the natural sciences were recorded. 44,941 9th grade students from a total of 1,462 schools in all federal states in the Federal Republic of Germany took part in the representative survey of the IQB Trends in Student Achievement 2018. In each of the schools drawn at random, one class (at grammar schools) or two classes (at non-grammar schools) were randomly selected to take part in the test (in contrast, a larger test group was formed in special schools, which usually comprised several learning groups). (IQB)

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Blank data sets

For a first overview of the data set and its variables, dummy data sets containing the variables used and the value labels relating to them are provided for download here.

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Documentation

Here you can find further documentation:

PDF Scaling Manual IQB Trends in Student Achievement 2018 (in German)

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Further information

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Notes on the use of the data

How are teacher data set and student data sets linked?

All data directly related to the students have already been merged into one data set. Thus, in addition to the information provided by the schools on the individual students, the results of the tests on competencies and basic cognitive skills and the survey of the students, this data set also contains the information from the parents' questionnaire. The only exception is the students' information on social networks, which is provided in a separate data set. The results of the teachers' survey and the survey of the school headmasters can also be found in separate data sets and can be merged with the students' data if necessary.

The data on social networks can be linked to the other data on the students via the student ID ("IDSTUD").

Information from the teacher survey is found in two separate data sets. On the one hand, there is a "general teacher data set", which contains information about the teachers themselves (e.g. their training). Each teacher who participated in the survey corresponds to one line in this data set. On the other hand, a "learning group-specific teacher data set" is provided, which contains information of the teachers on individual learning groups (e.g. on characteristics of their teaching in the respective learning group). In this data set, one row corresponds to one learning group, so that information in several rows can come from the same teacher. Both data sets can be linked with the help of the teacher ID (variable "IDTEACH"). The linking of teachers and students is done using the matching data set and the learning group specific data set based on the matching ID ("IDMATCHING"). This variable represents a unique identifier of a learning group at general schools and special schools.

The linking of the student data with the data of the principals can be done for both the general schools and the special schools via the school ID (variable "IDSCH").

Are the competence estimators of the PISA, IGLU and IQB studies comparable with each other?

In principle, the achievement tests used in German large scale assessment studies (PISA, IGLU and IQB studies) correlate highly, but the underlying competence models differ. The IQB tests are based on the educational standards of the The Standing Conference of the Ministers of Education and Cultural Affairs of the Länder in the Federal Republic of Germany (Kultusministerkonferenz, KMK) and as a result more closely aligned with the German school curriculum than PISA tests.

Comparability can be tested using IRT methods based on studies in which both PISA and IQB items were used. Some studies for comparison are, for example

The extent of comparability must be considered separately for reading and mathematical literacy and for secondary and primary education. Although it can be assumed that federal state differences can be well mapped using both measures, it is unfortunately not possible to analyse trends on a common metric.

How many classes per school are included in the sample in the IQB studies?

In the IQB studies, one class per school is usually included in the sample. Exceptions are made for some federal states and for some types of schools (e.g. special education schools). Information on sampling in the studies can be found in the results reports or scale manuals.

Here is a brief summary of the sampling procedure:

  • National Assessment Study 2008/2009: One 9th grade class per school; the entire class took part in the test; special education schools were not part of the sample.
  • National Assessment Study 2011: in regular schools: One 4th grade class per school; the entire class took part in the test; at special schools, all students in 4th grade with a special need in the area of learning, language, or emotional and social development participated across all classes.
  • National Assessment Study 2012: In grammar schools ("Gymnasium"), one 9th grade class was included in the study, in other school types (with the exception of special education schools), two classes per school (if available) were included. The entire classes took part in the test. At special schools, all students in 4th grade with a special need in the area of learning, language, or emotional and social development participated across all classes.
  • IQB Trends in Student Achievement 2015: In regular schools, one ninth grade class per school was included in the sample; the entire class took part in the test. In special education schools, all ninth grade adolescents with special needs in the area of learning, language, or emotional and social development participated in the study.
  • IQB Trends in Student Achievement 2016: in regular schools: one 4th grade class per school; the entire class took part in the test; at special schools, all students in 4th grade with a special need in the area of learning, language, or emotional and social development participated across all classes.
  • IQB Trends in Student Achievement 2018: In grammar schools ("Gymnasium"), one 9th grade class was included in the study, in other school types (with the exception of special education schools), two classes per school (if available) were included. The entire classes took part in the test. At special schools, all students in 4th grade with a special need in the area of learning, language, or emotional and social development participated across all classes.

Is it possible to record the age of students (to the day) in the IQB studies?

Information on the year and age of birth of students is collected as standard in the IQB studies and is available for re- and secondary analyses of the data. However, for reasons of data protection, exact information on the date of birth was not recorded and is not available in the data sets. The exact test date is also not included in most data sets. Often, however, the data sets contain an age variable that was calculated using the year and month of birth in relation to the test.

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Literature

Selected literature is listed PDF here (as of February 2023).

2022

Becker, B., Busse, J., Holtmann, M., Weirich, S., Schipolowski, S., Mahler, N., & Stanat, P. (2022). IQB-Bildungstrend 2018: Skalenhandbuch zur Dokumentation der Erhebungsinstrumente in Mathematik und den naturwissenschaftlichen Fächern (Schriftenreihe des Institutes zur Qualitätsentwicklung im Bildungswesen No. Band 11). Berlin: Institut zur Qualitätsentwicklung im Bildungswesen (IQB). https://doi.org/10.18452/25472

Busse, J., Becker, B., Weirich, S., & Schipolowski, S. (2022). IQB Trends in Student Achievement 2018: A Large-Scale Educational Assessment Study in Germany. Journal of Open Psychology Data, 10(1). https://doi.org/10.5334/jopd.71

Neuendorf, C., & Jansen, M. (2022). Comparing different facets of the social integration of high-achieving students in their classroom: No gender stereotyping, but some nonlinear relationships. Journal of Educational Psychology. Advance online publication. https://doi.org/10.1037/edu0000778

Stanat, P., Schipolowski, S., Mahler, N., Weirich, S., Henschel, S., Holtmann, M., Becker, B., & Kölm, J. (2022). IQB-Bildungstrend Mathematik und Naturwissenschaften 2018 (IQB-BT 2018) (Version 1) [Data set]. Berlin: IQB - Institut zur Qualitätsentwicklung im Bildungswesen. https://doi.org/10.5159/IQB_BT_2018_v1

2021

Schipolowski, S., Edele, A., Mahler, N., & Stanat, P. (2021). Mathematics and science proficiency of young refugees in secondary schools in Germany. Journal for Educational Research Online / Journal Für Bildungsforschung Online, 2021(1), 78–104. https://doi.org/10.31244/jero.2021.01.03 

2019

Stanat, P., Schipolowski, S., Mahler, N., Weirich, S., & Henschel, S. (Eds.). (2019). IQB-Bildungstrend 2018: Mathematische und naturwissenschaftliche Kompetenzen am Ende der Sekundarstufe I im zweiten Ländervergleich. Münster, New York: Waxmann.  

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