Skip to main content
SpringerLink
Log in

Computerisiertes adaptives Testen

  • Chapter
  • First Online:
Testtheorie und Fragebogenkonstruktion

Zusammenfassung

Computerisiertes adaptives Testen ist ein spezielles Vorgehen zur computerbasierten Messung individueller Merkmalsausprägungen, bei dem sich die Auswahl der zur Bearbeitung vorgelegten Items am vorherigen Antwortverhalten der Testperson orientiert. Der Grundgedanke besteht darin, keine starre Abfolge von Items vorzugeben, sondern nur solche Items, die möglichst viel diagnostische Information über die individuelle Ausprägung des zu messenden Merkmals liefern. Dieses Anliegen wird durch die Spezifikation von sechs elementaren Bausteinen umgesetzt. Es handelt sich dabei um den Itempool, die Art den Test zu beginnen, die Schätzung der individuellen Merkmalsausprägung, die Itemauswahl, die Berücksichtigung nicht statistischer Einschränkungen (z. B. die Kontrolle relativer Anteile vorgegebener Items je Inhaltsfacette des gemessenen Merkmals) und die Art, den Test zu beenden. Für alle Bausteine liegen mehrere Optionen vor, die je nach Anforderung der Testsituation in bestmöglicher Weise miteinander kombiniert werden können. Der Hauptvorteil des computerisierten adaptiven Testens im Vergleich zum nicht adaptiven Testen besteht in einer Messeffizienzsteigerung, die in den meisten Fällen beträchtlich ausfällt. Darüber hinaus sind positive Auswirkungen auf die Validität der adaptiv erhobenen Testergebnisse zu verzeichnen. Um unerwünschte Effekte beim computerisierten adaptiven Testen zu vermeiden, sollte die Funktionsweise eines adaptiven Tests im Rahmen der Instruktion transparent erläutert werden. Die Konstruktion eines computerisierten adaptiven Tests ist aufwendig. Neben der Erstellung und Kalibrierung eines geeigneten Itempools, sind präoperationale Simulationsstudien durchzuführen, sodass ein dem Gegenstand und Einsatzbereich angemessener adaptiver Algorithmus spezifiziert werden kann.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 69.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Literatur

  • American Educational Research Association (AERA), American Psychological Association (APA) & National Council on Measurement in Education (NCME). (2014). Standards for educational and psychological testing. Washington, DC: American Psychological Association

    Google Scholar 

  • Asseburg, R. (2011). Leistungsbereitschaft in Testsituationen. Motivation zur Bearbeitung adaptiver und nicht-adaptiver Leistungstests. Marburg: Tectum.

    Google Scholar 

  • de Ayala, R. J. (2009). The theory and practice of item response theory. New York: Guilford.

    Google Scholar 

  • Babcock, B. & Weiss, D. J. (2012). Termination criteria in computerized adaptive tests: Do variable-length CATs provide efficient and effective measurement? Journal of Computerized Adaptive Testing, 1, 1–18.

    Google Scholar 

  • Bergstrom, B. A., Lunz, M. E. & Gershon, R. C. (1992). Altering the level of difficulty in computer adaptive testing. Applied Measurement in Education, 5, 137–149.

    Google Scholar 

  • Betz, N. E. (1975). New types of information and psychological implications. In D. J. Weiss (Ed.), Computerized adaptive trait measurement: Problems and Prospects (Research Report 75-5) (pp. 32–43). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.

    Google Scholar 

  • Betz, N. E. & Weiss, D. J. (1976a). Effects of immediate knowledge of results and adaptive testing on ability test performance (Research Report 76-3). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.

    Google Scholar 

  • Betz, N. E. & Weiss, D. J. (1976b). Psychological effect of immediate knowledge of results and adaptive ability testing (Research Report 76-4). Minneapolis: University of Minnesota, Department of Psychology, Psychometric Methods Program.

    Google Scholar 

  • Bock, R. D. & Mislevy, R. J. (1982). Adaptive EAP estimation of ability in a microcomputer environment. Applied Psychological Measurement, 6, 431–444.

    Google Scholar 

  • Born, S. & Frey, A. (2017). Heuristic constraint management methods in multidimensional adaptive testing. Educational and Psychological Measurement, 77, 241–262.

    PubMed  Google Scholar 

  • Chalmers, R. P. (2016). Generating adaptive and non-adaptive test interfaces for multidimensional item response theory applications. Journal of Statistical Software, 71, 1–38. https://doi.org/10.18637/jss.v071.i05

    Article  Google Scholar 

  • Chalmers, P. (2017). mirtCAT: Computerized adaptive testing with multidimensional item response theory. R package. Version 1.3. Retrieved from https://CRAN.R-project.org/package=mirtCAT [29.12.2019]

  • Chang, H. H. (2015). Psychometrics behind computerized adaptive testing. Psychometrika, 80, 1–20.

    PubMed  Google Scholar 

  • Chang, W. (2017). shiny: web aplication framework for R. R package. Version 1.0.0. Retrieved from https://cran.r-project.org/web/packages/shiny/index.html [29.12.2019]

  • Cheng, P. E. & Liou, M. (2000). Estimation of trait level in computerized adaptive testing. Applied Psychological Measurement, 24, 257–265.

    Google Scholar 

  • Cheng, Y. & Chang, H. H. (2009). The maximum priority index method for severely constrained item selection in computerized adaptive testing. British Journal of Mathematical and Statistical Psychology, 62, 369–383.

    PubMed  Google Scholar 

  • Cheng, Y., Chang, H. H., Douglas, J. & Guo, F. (2009). Constraint-weighted α-stratification for computerized adaptive testing with nonstatistical constraints balancing measurement efficiency and exposure control. Educational and Psychological Measurement, 69, 35–49.

    Google Scholar 

  • Choi, S. W. & King, D. (2014). MAT: Multidimensional adaptive testing. R package. Version 2.2. Retrieved from https://rdrr.io/cran/MAT/ [29.12.2019]

  • Diao, Q. (2010). Comparison of ability estimation and item selection methods in multidimensional computerized adaptive testing. Ann Arbor, MI: UMI Research Press.

    Google Scholar 

  • Eggen, T. J. H. M. (2004). Contributions to the theory and practice of computerized adaptive testing. Enschede: Print Partners Ipskamp.

    Google Scholar 

  • Fink, A., Born, S., Frey, A. & Spoden, C. (2018). A continuous calibration strategy for computerized adaptive testing. Psychological Test and Assessment Modeling, 60, 327–346.

    Google Scholar 

  • Fink, A., Spoden, C., Kroll, P. & Frey, A. (2019). KAT-HS-App Benutzerhandbuch. Frankfurt am Main: Johann-Wolfgang Goethe-Universität Frankfurt.

    Google Scholar 

  • Frey, A. (2006). Validitätssteigerungen durch adaptives Testen. Frankfurt am Main: Peter Lang.

    Google Scholar 

  • Frey, A. & Ehmke, T. (2007). Hypothetischer Einsatz adaptiven Testens bei der Überprüfung von Bildungsstandards. Zeitschrift für Erziehungswissenschaft, Sonderheft 8, 169–184.

    Google Scholar 

  • Frey, A. & Hartig, J. (2013). Wann sollten computerbasierte Verfahren zur Messung von Kompetenzen Anstelle von Papier- und Bleistift-basierten Verfahren eingesetzt werden? Zeitschrift für Erziehungswissenschaft, 16, 53–57.

    Google Scholar 

  • Frey, A. & Seitz, N. N. (2009). Multidimensional adaptive testing in educational and psychological measurement: Current state and future challenges. Studies in Educational Evaluation, 35, 89–94.

    Google Scholar 

  • Frey, A. & Seitz, N. N. (2010). Multidimensionale adaptive Kompetenzdiagnostik: Ergebnisse zur Messeffizienz. Zeitschrift für Pädagogik, Beiheft 56, 40–51.

    Google Scholar 

  • Frey, A. & Seitz, N. N. (2011). Hypothetical use of multidimensional adaptive testing for the assessment of student achievement in PISA. Educational and Psychological Measurement, 71, 503–522.

    Google Scholar 

  • Frey, A., Hartig, J. & Moosbrugger, H. (2009). Effekte des adaptiven Testens auf die Motivation zur Testbearbeitung. Diagnostica, 55, 20–28.

    Google Scholar 

  • Frey, A., Hartig, J. & Rupp, A. (2009). Booklet designs in large-scale assessments of student achievement: Theory and practice. Educational Measurement: Issues and Practice, 28, 39–53.

    Google Scholar 

  • Frey, A., Seitz, N. N. & Kroehne, U. (2013). Reporting differentiated literacy results in PISA by using multidimensional adaptive testing. In M. Prenzel, M. Kobarg, K. Schöps & S. Rönnebeck (Eds.), Research on PISA (pp. 103–120). Dordrecht: Springer.

    Google Scholar 

  • Frey, A., Seitz, N. N. & Brandt, S. (2016). Testlet-based multidimensional adaptive testing. Frontiers in Psychology, 7, 1–14.

    Google Scholar 

  • Frey, A., Kröhne, U., Seitz, N. N. & Born, S. (2017). Multidimensional adaptive measurement of competences. In D. Leutner, J. Fleischer, J. Grünkorn & E. Klieme (Eds.), Competence assessment in education. Research, models, and instruments. Cham: Springer.

    Google Scholar 

  • Hambleton, R. K., Zaal, J. N. & Pieters, J. P. M. (1991). Computerized adaptive testing: Theory, applications, and standards. In R. K. Hambleton & J. N. Zaal (Eds.), Advances in educational and psychological testing: Theory and applications (pp. 341–366). New York, NY, US: Kluwer Academic/Plenum Publishers.

    Google Scholar 

  • He, W. & Reckase, M. D. (2014). Item pool design for an operational variable-length computerized adaptive test. Educational and Psychological Measurement, 74, 473–494.

    Google Scholar 

  • He, W., Diao, Q. & Hauser, C. (2014). A comparison of four item-selection methods for severely constrained CATs. Educational and Psychological Measurement, 74, 677–696.

    Google Scholar 

  • Keng, L. (2011). A Comparison of the performance of testlet-based computer adaptive tests and multistage tests. Ann Arbor, MI: Proquest.

    Google Scholar 

  • Khorramdel, L. & von Davier, M. (2016). Item response theory as a framework for test construction. In K. Schweizer & C. DiStefano (Eds.), Principles and methods of test construction. Göttingen: Hogrefe.

    Google Scholar 

  • Kubinger, K. D. (2009). Adaptives Intelligenz Diagnostikum – Version 2.2 (AID 2) samt AID 2-Türkisch. Göttingen: Beltz.

    Google Scholar 

  • Leroux, A. J., Lopez, M., Hembry, I. & Dodd, B. G. (2013). A comparison of exposure control procedures in CATs using the 3PL model. Educational and Psychological Measurement, 73, 857–874.

    Google Scholar 

  • Linacre, J. M. (2000). Computer-Adaptive Testing: A methodology whose time has come. In C. Sunhee, K. Unson, J. Eunhwa and J. M. Linacre (Eds.), Development of computerized middle school achievement test. Seoul, South Korea: Komesa Press.

    Google Scholar 

  • Lord, F. M. (1971). The self-scoring flexilevel test. Educational and Psychological Measurement, 8, 147–151.

    Google Scholar 

  • Lord, F. M. (1980). Applications of item response theory to practical testing problems. Hillsdale: Lawrence Erlbaum Associates.

    Google Scholar 

  • Luecht, R. M. (1996). Multidimensional computerized adaptive testing in a certification or licensure context. Applied Psychological Measurement, 20, 389–404.

    Google Scholar 

  • Magis, D., Raiche, G. & Barrada, J. R. (2016). catR: Generation of IRT response patterns under computerized adaptive testing. R package. Version 3.11. Retrieved from https://rdrr.io/cran/catR/ [29.12.2019]

  • Mikolajetz, A. & Frey, A. (2016). Differentiated assessment of mathematical competence with multidimensional adaptive testing. Psychological Test and Assessment Modeling, 58, 617–639.

    Google Scholar 

  • Mislevy, R. J. (1986). Bayes modal estimation in item response models. Psychometrika, 51, 177–195.

    Google Scholar 

  • Moosbrugger, H. & Goldhammer, F. (2007). FAKT-II. Frankfurter Adaptiver Konzentrationsleistungs-Test. Bern: Huber.

    Google Scholar 

  • Moosbrugger, H. & Heyden, M. (1997). Frankfurter Adaptiver Konzentrationsleistungs-Test. Bern: Huber.

    Google Scholar 

  • Ortner, T. M. & Caspers, J. (2011). Consequences of test anxiety on adaptive versus fixed item testing. European Journal of Psychological Assessment, 27, 157–163.

    Google Scholar 

  • Ponsoda, V., Olea, J., Rodriguez, M. S. & Revuelta, J. (1999). The effects of test difficulty manipulation in computerized adaptive testing and self-adapted testing. Applied Measurement in Education, 12, 167–184.

    Google Scholar 

  • Reckase, M. D. (2009). Multidimensional item response theory. Dordrecht: Springer.

    Google Scholar 

  • Revuelta, J. & Ponsoda, V. (1998). A comparison of item exposure control methods in computerized adaptive testing. Journal of Educational Measurement, 35, 311–327.

    Google Scholar 

  • Sands, W. A., Waters, B. K. & McBride, J. R. (Eds.). (1997). Computerized adaptive testing: From inquiry to operation. Washington, DC: American Psychological Association.

    Google Scholar 

  • Segall, D. O. (1996). Multidimensional adaptive testing. Psychometrika, 61, 331–354.

    Google Scholar 

  • Segall, D. O. (2005). Computerized adaptive testing. In K. Kempf-Leonard (Ed.), Encyclopedia of social measurement. Amsterdam: Elsevier.

    Google Scholar 

  • Shin, C. D., Chien, Y., Way, W. D. & Swanson, L. (2009). Weighted penalty model for content balancing in CATs. San Antonio, TX: Pearson.

    Google Scholar 

  • Spoden, C., Frey, A. & Bernhardt, R. (2018). Implementing three CATs within eighteen months. Journal of Computerized Adaptive Testing, 60, 38–55.

    Google Scholar 

  • Stocking, M. L. & Swanson, L. (1993). A method for severely constrained item selection in adaptive testing. Applied Psychological Measurement, 17, 277–292.

    Google Scholar 

  • Sympson, J. B. & Hetter, R. D. (1985). Controlling item-exposure rates in computerized adaptive testing. In Navy Personnel Research and Development Center (Ed.), Proceedings of the 27th annual meeting of the Military Testing Association (pp. 973–977). San Diego: Navy Personnel Research and Development Center.

    Google Scholar 

  • van der Linden, W. J. (1998). Bayesian item-selection criteria for adaptive testing. Psychometrika, 63, 201–216.

    Google Scholar 

  • van der Linden, W. J. (1999a). A procedure for empirical initialization of the trait estimator on ability estimates. Applied Psychological Measurement, 23, 21–29.

    Google Scholar 

  • van der Linden, W. J. (1999b). Multidimensional adaptive testing with a minimum error-variance criterion. Journal of Educational and Behavioral Statistics, 28, 398–412.

    Google Scholar 

  • van der Linden, W. J. (Ed.). (2016a). Handbook of item response theory. Volume 1: Models. Boca Raton: Chapman & Hall/CRC.

    Google Scholar 

  • van der Linden, W. J. (Ed.). (2016b). Handbook of item response theory. Volume 2: Statistical tools. Boca Raton: Chapman & Hall/CRC.

    Google Scholar 

  • van der Linden, W. J. & Pashley, P. J. (2010). Item selection and ability estimation in adaptive testing. In van der Linden, W. J. & Glas, C. A. W. (Eds.), Elements of adaptive testing (pp. 3–30). New York, NY: Springer.

    Google Scholar 

  • van der Linden, W. J. & Reese, L. M. (1998). A model for optimal constrained adaptive testing. Applied Psychological Measurement, 22, 259–270.

    Google Scholar 

  • Warm, T. A. (1989). Weighted likelihood estimation of ability in item response models. Psychometrika, 54, 427–450.

    Google Scholar 

  • Weiss, D. J. (1983). New horizons in testing: Latent trait test theory and computerized adaptive testing. New York: Academic Press.

    Google Scholar 

  • Weiss, D. J. (2004). Computerized adaptive testing for effective and efficient measurement in counseling and education. Measurement and Evaluation in Counseling and Development, 37, 70–84.

    Google Scholar 

  • Weiss, D. J. (2011). Better data from better measurements using computerized adaptive testing. Journal of Methods and Measurement in the Social Sciences, 2, 1–27.

    Google Scholar 

  • Yan, D., Lewis, C. & von Davier, A. A. (2014a). Overview of computerized multistage tests. In D. Yan, A. A. von Davier & C. Lewis, C. (Eds.). Computerized multistage testing: Theory and applications (pp. 3–20). Boca Raton: Chapman & Hall/CRC.

    Google Scholar 

  • Yan, D., von Davier, A. A. & Lewis, C. (Eds.). (2014b). Computerized multistage testing: Theory and applications. Boca Raton: Chapman & Hall/CRC.

    Google Scholar 

  • Ziegler, B., Frey. A., Seeber, S., Balkenhol, A. & Bernhardt, R. (2016). Adaptive Messung allgemeiner Kompetenzen (MaK-adapt). In K. Beck, M. Landenberger & F. Oser (Hrsg.), Technologiebasierte Kompetenzmessung in der beruflichen Bildung. Ergebnisse aus der BMBF-Förderinitiative ASCOT (S. 33–54). Bielefeld: wbv.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institut für Psychologie – Arbeitsbereich Pädagogische Psychologie, Goethe Universität Frankfurt am Main, Theodor-W.-Adorno-Platz 6, 60323, Frankfurt am Main, Deutschland

    Prof. Dr. Andreas Frey

Authors
  1. Prof. Dr. Andreas Frey
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Andreas Frey .

Editor information

Editors and Affiliations

  1. Institut für Psychologie, Goethe-Universität Frankfurt am Main, Frankfurt am Main, Hessen, Germany

    Helfried Moosbrugger

  2. Methodenzentrum, Eberhard Karls Universität Tübingen, Tübingen, Baden-Württemberg, Germany

    Augustin Kelava

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Frey, A. (2020). Computerisiertes adaptives Testen. In: Moosbrugger, H., Kelava, A. (eds) Testtheorie und Fragebogenkonstruktion. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-61532-4_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-61532-4_20

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-61531-7

  • Online ISBN: 978-3-662-61532-4

  • eBook Packages: Psychology (German Language)

Publish with us

Policies and ethics

Search

Navigation