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

(vormals als Ländervergleich bezeichnet)

Inhaltsverzeichnis

Projektbeschreibung

Leerdatensätze

Dokumentation

Weiterführende Informationen

Hinweise zur Nutzung der Daten

Literatur

> Scientific Use Files beantragen

Projektbeschreibung

Der IQB-Bildungstrend 2018 stellt den zweiten Ländervergleich des Instituts zur Qualitätsentwicklung im Bildungswesen (IQB) im Fach Mathematik und in den naturwissenschaftlichen Fächern Biologie, Chemie und Physik in der Sekundarstufe I dar. In den genannten Fächern wurden die Kompetenzen von Schüler*innen der 9. Jahrgangsstufe im Jahr 2018 untersucht. Damit ist es erstmals möglich, in Bezug auf das Erreichen der Bildungsstandards in diesen Fächern für die Bundesländer in der Bundesrepublik Deutschland Entwicklungstrends auf Populationsebene zu beschreiben. Neben einer Bestandsaufnahme für das Jahr 2018 ermöglichen die Daten in Verbindung mit dem IQB-Ländervergleich 2012 Trendanalysen, die zeigen, inwieweit sich das von Neuntklässler*innen erreichte Kompetenzniveau in den untersuchten Fächern seit dem Jahr 2012 verändert hat. Die Grundlage der Kompetenzmessungen bilden die für alle Länder verbindlichen Bildungsstandards der Kultusministerkonferenz, die fächerspezifisch festlegen, welche Kompetenzen Schüler*innen bis zu einem bestimmten Punkt in ihrer Schullaufbahn entwickelt haben sollen.

Zusätzlich zu den von Neuntklässler*innen erreichten Kompetenzen können anhand der Daten beispielsweise auch geschlechtsbezogene, soziale und zuwanderungsbezogene Disparitäten analysiert und überprüft werden, inwieweit sich diese seit dem Jahr 2012 verändert haben. Zudem wurden motivationale Merkmale der Schüler*innen, Aspekte der Unterrichtsqualität im Fach Mathematik sowie Angaben zur Aus- und Fortbildung von Lehrkräften im Fach Mathematik und in den naturwissenschaftlichen Fächern erfasst.

An der repräsentativen Erhebung zum IQB-Bildungstrend 2018 nahmen 44.941 Schüler*innen der 9. Jahrgangsstufe aus insgesamt 1.462 Schulen in allen Bundesländern in der Bundesrepublik Deutschland teil. In jeder der nach einem Zufallsverfahren gezogenen Schulen wurden ebenfalls per Zufall eine Klasse (an Gymnasien) bzw. zwei Klassen (an nichtgymnasialen Schularten) bestimmt, die an der Testung teilnahmen (in Förderschulen wurde davon abweichend eine größere Testgruppe gebildet, die in der Regel mehrere Lerngruppen umfasste). (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.

• IQB-BT 2018: Teachers General blank data set (SPSS)
• IQB-BT 2018: Teachers Learing Group Specific blank data set (SPSS)
• IQB-BT 2018: Linking Error blank data set (SPSS)
• IQB-BT 2018: Matching Students Teachers blank data set (SPSS)
• IQB-BT 2018: Students Social Networks blank data set (SPSS)
• IQB-BT 2018: Students blank data set (SPSS)
• IQB-BT 2018: Principals blank data set (SPSS)
• IQB-LV 2012: Plausibles Values blank data set (SPSS)

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Documentation

Here you can find further documentation:

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

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Further information

• Further information on the study can be found here.
• Information about the data

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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

• an den Ham, Ann-Katrin; Ehmke, Timo; Hahn, Inga; Wagner, Helene; Schöps, Katrin (2016). Mathematische und naturwissenschaftliche Kompetenz in PISA, im IQB-Ländervergleich und in der National Educational Panel Study (NEPS) – Vergleich der Rahmenkonzepte und der dimensionalen Struktur der Testinstrumente. In: Bundesministerium für Bildung und Forschung [Hrsg.]: Forschungsvorhaben in Ankopplung an Large-Scale-Assessments. Berlin, Bundesministerium für Bildungund Forschung, S. 140-160.
• Jude, Nina,Klieme, Eckhard [Hrsg.](2013). PISA 2009 - Impulse für die Schul- und Unterrichtsforschung. Weinheim u.a.: Beltz. (Zeitschrift für Pädagogik, Beiheft 59)
• Hartig, Johannes, Frey, Andreas (2012).Validität des Tests zur Überprüfung des Erreichens der Bildungsstandards in Mathematik Zusammenhänge mit den bei PISA gemessenen Kompetenzen und Varianz zwischen Schulen und Schulformen. Diagnostica 58, S. 3-14.

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 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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