Programme for International Student Assessment - Plus 2012-2013 (PISA Plus 2012-2013)

 

Table of contents

Project description

Blank data sets

Documentation

Notes on the use of the data

Literature

> Link to application form (Scientific Use Files)

> Link to application form (Campus Files)

Data Set Published on 22.08.2019
Version v3
Current Version Available Since 09.05.2023
Survey Period 2013
Sample 1st time of measurement: Students in grade 9 and 10 pursuing a Mittlerer Schulabschluss (general education school leaving certificate obtained on completion of grade 10) (N=9,998) from schools (n=222); 2nd time of measurement: Students in grade 9 and 10 pursuing a Mittlerer Schulabschluss (general education school leaving certificate obtained on completion of grade 10) (N=4,610) from schools (n=135); Teachers (N=593); Schools (N=118); Principals (N=118)
Survey Unit Principals
Students
Teachers
Measured Competencies Mathematics, Natural Sciences, Reading
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 Heine, Jörg-Henrik
Reiss, Prof. Dr. Kristina
Data Producers Reiss, Prof. Dr. Kristina
Funded by Standing Conference of the Ministers of Education and Cultural Affairs of the Länder in the Federal Republic of Germany, Organization for Economic Cooperation and Development (OECD)
Link https://www.zib.education/forschung/abgeschlossene-projekte/pisa-plus-2012-2013-kompetenzentwicklung-im-verlauf-eines-schuljahres/
Related Studies PISA 2000 (DOI: 10.5159/IQB_PISA_2000_v1), PISA 2003 (DOI: 10.5159/IQB_PISA_2003_v1), PISA 2006 (DOI: 10.5159/IQB_PISA_2006_v1), PISA 2009 (DOI: 10.5159/IQB_PISA_2009_v1), PISA 2012 (DOI: 10.5159/IQB_PISA_2012_v5), PISA 2015 (DOI: 10.5159/IQB_PISA_2015_v3), PISA-I-Plus 2003-4 (DOI: 10.5159/IQB_PISA_I_Plus_v1), PISA 2018 (DOI: 10.5159/IQB_PISA_2018_v1)
Suggested Citation Scientific Use File (SUF):

Reiss, K., Heine, J.-H., Klieme, E., Köller, O., & Stanat, P. (2019). Programme for International Student Assessment - Plus 2012-2013 (PISA Plus 2012-2013) (Version 3) [Data set]. Berlin: IQB – Institut zur Qualitätsentwicklung im Bildungswesen. http://doi.org/10.5159/IQB_PISA_Plus_2012-13_v3

Campus Use File (CUF):

Forschungsdatenzentrum am Institut zur Qualitätsentwicklung im Bildungswesen (FDZ am IQB) [Research Data Centre at the Institute for Educational Quality Improvement (FDZ at IQB)] (2020). Programme for International Student Assessment - Plus 2012, 2013 (PISA Plus 2012-2013) (Version 1) [Data set]. Data package: CUF Off-site. Berlin: IQB - Institut zur Qualitätsentwicklung im Bildungswesen. http://doi.org/10.5159/IQB_PISA_Plus_2012-13_CF_v1
Restriction Notice Cognitive abilities must not be used as a dependent variable in the analyses.

 

Project description

PISA-Plus 2012-2013 supplements the international PISA main survey in 2012 by a longitudinal component with a second measurement date. The same students were tested in the regular survey in 2012 and one year later in the tenth grade. Within the framework of the project it is possible to map changes over the course of a school year. In addition, this longitudinal dataset allows the analysis of conditions that influence the acquisition of competences. (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

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Notes on the use of the data

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

In principle, the tests from PISA and the IQB studies correlate highly, but the underlying competency 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 and thus more closely aligned with the schools´ curriculum than the 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 absolute trends on a common metric.

The data sets of PISA 2012 and IQB National Assessment Study 2012 studies can be linked with each other using the ID variable [idstud_FDZ]. This allows you to compare correlations between the scaled test values of both studies.

Please note additionally:

1.) In contrast to the PISA surveys, reading and mathematical literacy are only tested together in the IQB study in primary school: Reading literacy was recorded in the IQB National Assessment Study 2009 (lower secondary level) and in the IQB National Assessment Study 2011 (primary school) as well as in the IQB Trends in Student Achievement 2015 (lower secondary level) and in the IQB Trends in Student Achievement 2016 (primary school). Mathematics competencies can be found in the IQB National Assessment Study 2012 (secondary level) and IQB National Assessment Study 2011 (primary level) as well as in the IQB Trends in Student Achievement 2016 (primary level) and the IQB Trends in Student Achievement 2018 (secondary level).

2.) We do not have a federal state identifier for the PISA surveys.

3.) If you wish to conduct analyses that include unpublished, novel comparisons between single federal states, our Rules of Procedure state that an extended application procedure with a review process applies.

Is it possible to record the age of students (to the day) in the IQB National Assessment Studies/IQB Trends in Student Achievement Studies and in PISA?

Information on the year and age of birth of students is collected as standard in the IQB National Assessment Studies and PISA studies and is available for re- and secondary analyses of the data. For reasons of data protection, however, the exact 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 (in PISA 2009 this information is available). Frequently, however, the data sets contain an age variable that was formed using the year and month of birth in relation to the test date (e.g. in the IQB National Assessment Studies 2011, 2012 and in PISA 2012, 2009, 2006).

Which PISA data can be linked to which IQB National Assessment Studies/IQB Trends in Student Achievement Studies?

The PISA 2012 data sets can be combined with the IQB National Assessment Study 2012. The students IDs have already been recoded in the data sets available at the FDZ at IQB in such a way that a linkage of both data sources is possible. Unfortunately, it is not possible to link the other PISA waves with the data from the IQB IQB National Assessment Studies /IQB Trends in Student Achievement Studies because the ID variables cannot be recoded uniformly.

At what levels was the Germany PISA data collected?

In the German PISA studies, information is only available at the federal state level. Please note that special conditions of use must be observed when analysing data from the federal states. You can read them here:

What is the number of classes drawn per school in PISA surveys?

Information on sampling in the studies can be found in the results reports or scale manuals.

Here is a brief summary of sampling in PISA:

PISA 2000:
random selection of 28 15-year-olds and 10 non-15-year-old ninth graders per school; thus, full classes were not drawn, analyses can only be done at the school level

PISA 2003:
random selection of 15-year-olds per school; in addition, two complete 9th graders were drawn per school for the national expansion; in the PISA-E data, however, no class-based sampling was realised.

PISA 2006:
school-based sampling, then random selection of 15-year-olds per school; at the schools in the international sample (PISA_I), students from two complete 9th grades were additionally tested

PISA 2009:
school-based sampling, additionally students from two complete 9th grades per school were tested

PISA 2012:
school-based sampling, additionally students from two complete 9th grades per school were tested

PISA 2015:
school-based sampling, additionally random selection of 15 ninth graders per school

PISA 2018:
school-based sampling, additionally random selection of 15 ninth graders per school

How many students in special and vocational schools are included in the PISA data?

Special needs and vocational students were covered separately in the above PISA surveys. The sample sizes for these subgroups are given below. They are based on the data in the German PISA Extended Samples (PISA-E) in the student and school management data sets. Where appropriate, there may be slight differences from the reported sample sizes in the results reports.

PISA 2000 E:
- 9th grade: n= 11 students in vocational schools, n= 22 students in special schools out of a total of n= 34,754 students
- 15-year-olds: n= 241 students at vocational schools, n= 799 students at special schools out of a total of n= 35,584 students
- School data set: n= 18 vocational schools, n= 4 special schools out of a total of n= 1,342 schools

PISA 2003 E (here no differentiation between data sets for 9th grade & 15-year-olds possible):
- 9th grade: n= 654 students at vocational schools, n= 1,712 students at special schools out of a total of n= 46,185 students
- School data set: n= 43 vocational schools, no special schools out of a total of n= 1,411 schools

PISA 2006 E:
- 9th grade: no students at vocational schools or special schools in the data set
- 15-year-olds: n= 625 students at vocational schools, n= 2,560 students at special schools out of a total of n= 39,573 students
- School data set: n= 42 vocational schools, no special schools out of a total of n= 1,496 schools

PISA 2009 E:
- 9th grade: no students at vocational schools or special schools in the data set out of a total of n= 9,461 students
- School data set: n= 9 vocational schools, n= 13 special schools out of a total of n= 226 schools

PISA 2012 E:
- 9th grade: no students at vocational schools, n= 153 at special schools out of a total of n= 9,998 students
- 15-year-olds: n= 99 students at vocational schools, n= 139 at special schools out of a total of n= 5,001 students
- School data set: n= 7 vocational schools, n= 12 special schools out of a total of n= 230 schools

PISA 2015 E:
- 9th grade:no students at vocational schools, n= 165 at special schools out of a total of n= 4,149 students
- 15-year-olds: n= 160 students at vocational schools, n= 134 at special schools out of a total of n= 6,504 students
- School data set: n= 8 vocational schools, n= 12special schools out of a total of n= 205 schools

PISA 2018 E:
- 9th grade: no students at vocational schools, n= 115 at special schools out of a total of n= 3,567 students
- 15-year-olds: n= 184 students at vocational schools, n= 98 at special schools out of a total of n= 5,451 students
- School data set: n= 10 vocational schools, n= 7 special schools out of a total of n= 191 schools

Can teacher and student data be linked in PISA?

Unfortunately, linking is only possible for the partial data sets of 9th graders (the data sets of 15-year-olds include cross-school samples). In most PISA waves, two 9th graders were drawn, but the partial data sets often lack a unique class ID.

Here is an overview in bullet points of the individual PISA waves:

- PISA 2000: no teacher questionnaire was used here.

- PISA 2003: partial data set "PISA-I-9th grade": teacher questionnaires contain questions at school level, not at class level; a link via the variable [idclass_FDZ] is possible, but in the teacher data set there is a high proportion of missing values on this variable (presumably because many teachers were surveyed per school); partial data set "PISA-E": no teacher questionnaires available

- PISA Plus 2003-2004: a linkage is possible in principle, but teacher data would have to be imported from PISA 2003 data and are only available at the first measurement point.

- PISA 2006: partial data set "PISA-E": no teacher data set for 9th grades available, linkage only possible at school level; partial data set "PISA-I": no clear linkage possible, as the teacher data set does not contain a class ID.

- PISA 2009: also no class ID in the teacher data set, but linking via idsch and variable [LF39M01] (German taught in PISA class: yes vs. no) partially possible; however, two 9th grades were drawn from each school.

- PISA 2012: Linking is possible in principle via class name variables (teacher data set: class_FDZ; student data set: ClassName_FDZ) but difficult to achieve in practice, as the metric of the school ID does not correspond between the two sub-data sets and there is a high proportion of missing values on class name variables (I interpret reports from PISA staff that linking is not successful in the majority of cases).

- PISA 2015: Linkage is not directly possible, as all teachers in the drawn schools were surveyed.

- PISA 2018: A link between teachers and students via the variable "TEACHCLASS_ID" is not possible until the end of 2022 due to a blocking notice. However, this variable also only contains the information whether the teacher has taught a ninth grade or not. This is because almost all teachers in the drawn school were surveyed. Alternatively, the variable "TEACHERID" can be used, but this variable also does not allow a clear assignment between students and the corresponding teacher.

For which PISA data is a repeated measures data set available?

A repeated measures data set is available for PISA-2003 (PISA-Plus 2003, 2004) and PISA-2012 (PISA-Plus 2012, 2013).

How were the science literacy tests developed in PISA?

In contrast to the IQB National Assessment Studies, the science tests in PISA are not curricularly anchored or subject-specifically designed. Therefore, there are no subtests for biology, physics and chemistry in PISA. Instead, PISA tests scientific literacy (see e.g. OECD, 2006). This involves skills that are significant in situations in which one is confronted with science and technology. These situations relate to physical systems, living systems, earth and space systems and technological systems. Specifically, the following competencies are tested:

(a) recognise scientific issues

b) describe, explain and predict scientific phenomena

c) use scientific evidence to make decisions.

More information on the concept and the test (including sample items) can be found here:

In PISA Plus 2012-13, is it possible to link not only students but also principals and teachers longitudinally?

Unfortunately, the teacher IDs cannot be recoded uniformly between the two measurement points, so that it cannot be ensured whether the same teacher completed the questionnaire at both measurement points. This also applies to the principals, but at least the school IDs can be linked between the two measurement points. Thus, information about the participating schools can be linked longitudinally. However, the number of items used in both surveys is relatively small.

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Literature

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

2021

Becker, M., Kocaj, A., Jansen, M., Dumont, H. & Lüdtke, O. (2021). Class-average achievement and individual achievement development: Testing achievement composition and peer spillover effects using five German longitudinal studies. Journal of Educational Psychology. https://doi.org/10.1037/edu0000519

2020

Forschungsdatenzentrum am Institut zur Qualitätsentwicklung im Bildungswesen. (2020). Code Book for the PISA-Plus 2012-2013 Campus Files. Berlin. https://doi.org/10.5159/IQB_PISA_Plus_2012-13_CF_Skalendokumentation_v1

Forschungsdatenzentrum am Institut zur Qualitätsentwicklung im Bildungswesen. (2020). Programme for International Student Assessment - Plus 2012, 2013 (PISA-Plus 2012, 2013) - Campus File (Version 1) [Datensatz]. Berlin: IQB - Institut zur Qualitätsentwicklung im Bildungswesen. https://doi.org/10.5159/IQB_PISA_Plus_2012-13_CF_v1

2019

Reiss, K., Heine, J.-H., Klieme, E., Köller, O., & Stanat, P. (2019). Programme for International Student Assessment - Plus 2012, 2013 (PISA-Plus 2012, 2013) (Version 3) [Datensatz]. Berlin: IQB - Institut zur Qualitätsentwicklung im Bildungswesen. https://doi.org/10.5159/IQB_PISA_Plus_2012-13_v3

2017

Ehmke, T., Köller, O. & Stanat, P. (2017). Äquivalenz der Erfassung mathematischer Kompetenzen in PISA 2012 und im IQB-Ländervergleich 2012. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 37–59). Springer VS. https://doi.org/10.1007/s11618-017-0751-5

Ehmke, T., Sälzer, C., Pietsch, M., Drechsel, B. & Müller, K. (2017). Kompetenzentwicklung im Schuljahr nach PISA 2012: Effekte von Klassenwiederholungen. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 99–124). Springer VS. https://doi.org/10.1007/s11618-017-0752-4

Hahnel, C., Goldhammer, F., Kröhne, U., Schiepe-Tiska, A., Lüdtke, O. & Nagy, G. (2017). Der Einfluss kognitiver Basisfertigkeiten auf die Änderung der in PISA gemessenen Lesekompetenz. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 205–228). Springer VS. https://doi.org/10.1007/s11618-017-0748-0

Heine, J.-H., Nagy, G., Meinck, S., Zühlke, O. & Mang, J. (2017). Empirische Grundlage, Stichprobenausfall und Adjustierung im PISA-Längsschnitt 2012–2013. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 287–306). Springer VS. https://doi.org/10.1007/s11618-017-0756-0

Kiemer, K., Haag, N., Müller, K. & Ehmke, T. (2017). Einfluss sozialer und zuwanderungsbezogener Disparitäten, sowie der Klassenkomposition auf die Veränderung der mathematischen Kompetenz von der neunten zur zehnten Klassenstufe. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 125–149). Springer VS. https://doi.org/10.1007/s11618-017-0753-3

Kuger, S., Klieme, E., Lüdtke, O., Schiepe-Tiska, A. & Reiss, K. (2017). Mathematikunterricht und Schülerleistung in der Sekundarstufe: Zur Validität von Schülerbefragungen in Schulleistungsstudien. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 61–98). Springer VS. https://doi.org/10.1007/s11618-017-0750-6

Lehner, M. C., Heine, J.-H., Sälzer, C., Reiss, K., Haag, N. & Heinze, A. (2017). Veränderung der mathematischen Kompetenz von der neunten zur zehnten Klassenstufe. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 7–36). Springer VS. https://doi.org/10.1007/s11618-017-0746-2

Nagy, G., Haag, N., Oliver, L. & Köller, O. (2017). Längsschnittskalierung der Tests zur Überprüfung des Erreichens der Bildungsstandards der Sekundarstufe I im PISA-Längsschnitt 2012/2013. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 259–286). Springer VS. https://doi.org/10.1007/s11618-017-0755-1

Nagy, G., Lüdtke, O., Köller, O. & Heine, J.-H. (2017). IRT-Skalierung der Tests im PISA-Längsschnitt 2012/2013: Auswirkungen von Testkontexteffekten auf die Zuwachsschätzung. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 229–258). Springer VS. https://doi.org/10.1007/s11618-017-0749-z

Nagy, G., Retelsdorf, J., Goldhammer, F., Schiepe-Tiska, A. & Lüdtke, O. (2017). Veränderungen der Lesekompetenz von der 9. zur 10. Klasse: Differenzielle Entwicklungen in Abhängigkeit der Schulform, des Geschlechts und des soziodemografischen Hintergrunds? In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 177–203). Springer VS. https://doi.org/10.1007/s11618-017-0747-1

Reiss, K., Klieme, E., Köller, O. & Stanat, P. (Hrsg.). (2017). PISA Plus 2012 – 2013: Springer VS. https://doi.org/10.1007/s11618-017-0754-2

Schiepe-Tiska, A., Rönnebeck, S., Heitmann, P., Schöps, K., Prenzel, M. & Nagy, G. (2017). Die Veränderung der naturwissenschaftlichen Kompetenz von der 9. zur 10. Klasse bei PISA und den Bildungsstandards unter Berücksichtigung geschlechts- und schulartspezifischer Unterschiede sowie der Zusammensetzung der Schülerschaft. In K. Reiss, E. Klieme, O. Köller & P. Stanat (Hrsg.), PISA Plus 2012 – 2013 (Bd. 20, S. 151–176). Springer VS. https://doi.org/10.1007/s11618-017-0754-2

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