1,156
Views
26
CrossRef citations to date
0
Altmetric
Articles

Assessing scientific reasoning: a comprehensive evaluation of item features that affect item difficulty

, , , , , , & show all

References

  • AAAS (American Association for the Advancement of Science). 1993. Benchmarks for Science Literacy. New York: Oxford University Press.
  • AAAS (American Association for the Advancement of Science). 2009. Benchmarks for Science Literacy. New York: Oxford University Press.
  • AERA (American Educational Research Association), APA (American Psychological Association), and NCME (National Council on Measurement in Education). 2014. Standards for Educational and Psychological Testing. Washington, DC: American Educational Research Association.
  • Bates, D., M. Maechler, B. Bolker, and S. Walker. 2015. “Fitting Linear Mixed-effects Models Using lme4.” Journal of Statistical Software 67 (1): 1–48. doi:10.18637/jss.v067.i01.
  • Baxter, G. P., and R. Glaser. 1998. “Investigating the Cognitive Complexity of Science Assessments.” Educational Measurement: Issues and Practice 17 (3): 37–45. doi:10.1111/j.1745-3992.1998.tb00627.x.
  • Bramley, T., S. Hughes, H. Fisher-Hoch, and A. Pollitt. 1998. Sources of Difficulty in Examination Questions: Science. Cambridge: UCLES Internal Report.
  • Bybee, R. W. 2010. “What Is STEM Education?” Science 329: 996.10.1126/science.1194998
  • Crawford, B., and M. Cullin. 2005. “Dynamic Assessments of Preservice Teachers’ Knowledge of Models and Modelling.” In Research and the Quality of Science Education, edited by K. Boersma, M. Goedhart, O. de Jong, and H. Eijkelhof, 309–323. Dordrecht: Springer.10.1007/1-4020-3673-6
  • Day, A. 2013. The Structure of Scientific Examination Questions. Dordrecht: Springer.
  • De Boeck, P., M. Bakker, R. Zwitser, M. Nivard, A. Hofman, F. Tuerlinckx, and I. Partchev. 2011. “The Estimation of Item Response Models with the lmer Function from the lme4 Package in R.” Journal of Statistical Software 39 (12): 1–28. doi:10.18637/jss.v039.i12.
  • Dhillon, D. 2003. Predictive Models of Question Difficulty: A Critical Review of the Literature. Manchester: AQA. https://cerp.aqa.org.uk/sites/default/files/pdf_upload/CERP-RP-DD-01022003_0.pdf.
  • Duggan, S., P. Johnson, and R. Gott. 1996. “A Critical Point in Investigative Work: Defining Variables.” Journal of Research in Science Teaching 33 (5): 461–474.10.1002/(ISSN)1098-2736
  • Fischer, F., I. Kollar, S. Ufer, B. Sodian, H. Hussmann, R. Pekrun, B. Neuhaus, et al. 2014. “Scientific Reasoning and Argumentation: Advancing an Interdisciplinary Research Agenda in Education.” Frontline Learning Research 2 (3): 28–45.
  • Giere, R. N., J. Bickle, and R. F. Mauldin. 2006. Understanding Scientific Reasoning. 5th ed. Belmont, CA: Thomson/Wadsworth.
  • Glynn, S. M. 2012. “International Assessment: A Rasch Model and Teachers’ Evaluation of TIMSS Science Achievement Items.” Journal of Research in Science Teaching 49 (10): 1321–1344. doi:10.1002/Tea.21059.
  • Hartig, J., A. Frey, G. Nold, and E. Klieme. 2012. “An Application of Explanatory Item Response Modeling for Model-based Proficiency Scaling.” Educational and Psychological Measurement 72: 665–686.10.1177/0013164411430707
  • Hartmann, S. 2013. “Die Rolle von Leseverständnis und Lesegeschwindigkeit beim Zustandekommen der Leistungen in schriftlichen Tests zur Erfassung naturwissenschaftlicher Kompetenz.” [The Role of Reading Comprehension and Reading Speed in Text-based Assessments of Scientific Inquiry Skills]. Doctoral diss., University of Duisburg-Essen, Germany.
  • Hartmann, S., S. Mathesius, J. Stiller, P. Straube, D. Krüger, and A. Upmeier zu Belzen. 2015a. “Kompetenzen der naturwissenschaftlichen Erkenntnisgewinnung als Teil des Professionswissens zukünftiger Lehrkräfte: Das Projekt Ko-WADiS.” [Competencies in the Field of Scientific Inquiry as Part of Professional Knowledge of Prospective Teachers]. In Kompetenzerwerb an Hochschulen: Modellierung und Messung. Zur Professionalisierung angehender Lehrerinnen und Lehrer sowie frühpädagogischer Fachkräfte, edited by B. Koch-Priewe, A. Köker, J. Seifried, and E. Wuttke, 39–58. Bad Heilbrunn: Klinkhardt.
  • Hartmann, S., and A. Upmeier zu Belzen, D. Krüger, and H. A. Pant. 2015b. “Scientific Reasoning in Higher Education.” Zeitschrift für Psychologie 223: 47–53. doi:10.1027/2151-2604/a000199.
  • Hoang, Viet-Ngu, Lynette A. May, and T. Tang. 2012. The Effects of Linguistic Factors on Student Performance on Economics Multiple Choice Questions. Brisbane: Social Science Research Network. doi:10.2139/ssrn.2121816.
  • KMK (The Standing Conference of the Ministers of Education and Cultural Affairs of the Länder in the Federal Republic of Germany), ed. 2005a. Bildungsstandards im Fach Biologie für den Mittleren Schulabschluss (Jahrgangsstufe 10) [Standards for Secondary Education in Biology]. Beschlüsse der Kultusministerkonferenz. München: Wolter Kluwer.
  • KMK (The Standing Conference of the Ministers of Education and Cultural Affairs of the Länder in the Federal Republic of Germany), ed. 2005b. Bildungsstandards im Fach Chemie für den Mittleren Schulabschluss (Jahrgangsstufe 10) [Standards for Secondary Education in Chemistry]. Beschlüsse der Kultusministerkonferenz. München: Wolter Kluwer.
  • KMK (The Standing Conference of the Ministers of Education and Cultural Affairs of the Länder in the Federal Republic of Germany), ed. 2005c. Bildungsstandards im Fach Physik für den Mittleren Schulabschluss (Jahrgangsstufe 10) [Standards for Secondary Education in Physics]. Beschlüsse der Kultusministerkonferenz. München: Wolter Kluwer.
  • Koeppen, K., J. Hartig, E. Klieme, and D. Leutner. 2008. “Current Issues in Competence Modeling and Assessment.” Zeitschrift für Psychologie/Journal of Psychology 216: 61–73.10.1027/0044-3409.216.2.61
  • Krell, M., and A. Upmeier zu Belzen, and D. Krüger. 2014. “Students’ Levels of Understanding Models and Modelling in Biology: Global or Aspect-dependent?” Research in Science Education 44: 109–132.10.1007/s11165-013-9365-y
  • Le Hebel, F., A. Tiberghien, and P. Montpied. 2013. “Sources of difficulties in Pisa science items.” Proceedings of the European Science Education Research Association Conference 2013. Nicosia: ESERA.
  • Leong, S. C. 2006. “OnVarying the Difficulty of Test Items.” Paper presented at the 32nd Annual Conference of the International Association for Educational Assessment, Singapore, May 21–26.
  • Lincoln, D., and M. L. Kearney. 2015. “Competence Assessment in Higher Education.” Studies in Higher Education 40 (3): 391–392. doi:10.1080/03075079.2015.1005334.
  • Martiniello, M. 2009. “Linguistic Complexity, Schematic Representations, and Differential Item Functioning for English Language Learners in Math Tests.” Educational Assessment 14: 160–179. doi:10.1080/10627190903422906.
  • Mathesius, S., A. Upmeier zu Belzen, and D. Krüger. 2014. “Kompetenzen von Biologiestudierenden im Bereich der naturwissenschaftlichen Erkenntnisgewinnung. Entwicklung eines Testinstruments.” [Biology Students’ Scientific Inquiry Competencies: Developing a Measurement Instrument] Erkenntnisweg Biologiedidaktik 13: 73–88.
  • Mayer, R. E. 2005. “Principles for Reducing Extraneous Processing in Multimedia Learning: Coherence, Signaling, Redundancy, Spatial Contiguity, and Temporal Contiguity Principles.” In The Cambridge Handbook of Multimedia Learning, edited by R. E. Mayer, 183–200. Cambridge: Cambridge University Press.10.1017/CBO9780511816819
  • Mayer, J. 2007. “Erkenntnisgewinnung als wissenschaftliches Problemlösen.” [Scientific Inquiry as Scientific Problem Solving] In Theorien in der biologiedidaktischen Forschung. Ein Handbuch für Lehramtsstudenten und Doktorande, edited by D. Krüger and H. Vogt, 177–184. Berlin: Springer.
  • Miller, G. A. 1999. “On Knowing a Word.” Annual Review of Psychology 50: 1–19.10.1146/annurev.psych.50.1.1
  • Mitzel, H. C., D. M. Lewis, R. J. Patz, and D. R. Green. 2001. “The Bookmark Procedure: Psychological Perspectives.” In Setting Performance Standards: Concepts, Methods and Perspectives, edited by G. Cizek, 249–281. Mahwah, NJ: Erlbaum.
  • Mullis, I. V. S., M. O. Martin, and P. Foy. 2013. “The Impact of Reading Ability on TIMSS Mathematics and Science Achievement at the Fourth Grade: An Analysis by Item Reading Demands.” In TIMSS and PIRLS 2011: Relationships among Reading, Mathematics, and Science Achievement at the Fourth Grade – Implications For Early Learning, edited by M. O. Martin and I. V. S. Mullis, 67–110. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Lynch School of Education, Boston College.
  • NGSS (Next Generation Science Standards) Lead States. 2013. Next Generation Science Standards: For States, By States. Washington, DC: The National Academies Press.
  • Nissan, S., F. DeVincenzi, and K. L. Tang. 1996. An Analysis of Factors Affecting the Difficulty of Dialogue Items in TOEFL Listening Comprehension. Princeton, NJ: ETS.
  • Nitz, S., H. Prechtl, and C. Nerdel. 2014. “Survey of Classroom Use of Representations: Development, Field Test and Multilevel Analysis.” Learning Environments Research 17 (3): 401–422.10.1007/s10984-014-9166-x
  • Nowak, K., A. Nehring, R. Tiemann, and A. Upmeier zu Belzen. 2013. “Assessing Students′ Abilities in Processes of Scientific Inquiry in Biology Using a Paper–Pencil-test.” Journal of Biological Education 47 (3): 182–188.10.1080/00219266.2013.822747
  • NRC (National Research Council). 1996. National Science Education Standards. Washington, DC: National Academic Press.
  • Oh, Phil S., and Sung J. Oh. 2011. “What Teachers of Science Need to Know about Models: An Overview.” International Journal of Science Education 33 (8): 1109–1130. doi:10.1080/09500693.2010.502191.
  • Pollitt, A., N. Entwistle, C. Hutchinson, and C. de Luca. 1985. What Makes Exam Questions Difficult? Edinburgh: Scottish Academic Press.
  • Prenzel, M., P. Häußler, J. Rost, and M. Senkbeil. 2002. “Der PISA-Naturwissenschaftstest: Lassen sich die Aufgabenschwierigkeiten vorhersagen?” [The PISA Science Test: Can Item Difficulties Be Predicted?]. Unterrichtswissenschaft 30: 120–135.
  • QCA (Qualifications and Curriculum Authority). 2007. Science: Programme of Study for Key Stage 3 and Attainment Targets. London: QCA.
  • R Core Team. 2015. R: A Language and Environment for Statistical Computing. Vienna, Austria: The R Foundation for Statistical Computing. https://www.r-project.org/
  • Schnotz, W. 2005. “An Integrated Model of Text and Picture Comprehension.” In The Cambridge Handbook of Multimedia Learning, edited by R. E. Mayer, 49–70. Cambridge: Cambridge University Press.10.1017/CBO9780511816819
  • Schwartz, R. S., N. G. Lederman, and B. A. Crawford. 2004. “Developing Views of Nature of Science in an Authentic Context: An Explicit Approach to Bridging the Gap Between Nature of Science and Scientific Inquiry.” Science Education 88: 610–645. doi:10.1002/sce.10128.
  • Spearritt, D. 1980. The Improvement of Measurement in Education and Psychology: Contributions of Latent Trait Theories. Melbourne: The Australian Council for Educational Research.
  • Stiller, J., P. Straube, S. Hartmann, V. Nordmeier, and R. Tiemann. 2015. “Erkenntnisgewinnungskompetenz Chemie- und Physik-Lehramtsstudierender. Untersuchungen zu Domänenspezifität.” [Pre-service Chemistry and Physics Teachers’ Scientific Inquiry Competencies : Investigating Domain Specificity]. In Berlin-Brandenburger Beiträge zur Bildungsforschung 2015. Herausforderungen, Befunde und Perspektiven interdisziplinärer Bildungsforschung, edited by Jurik Stiller and Christin Laschke, 179–202. Frankfurt am Main: Peter Lang.10.3726/978-3-653-04961-9
  • Taskin, V., S. Bernholt, and I. Parchmann. 2015. “An Inventory for Measuring Student Teachers’ Knowledge of Chemical Representations: Design, Validation, and Psychometric Analysis.” Chemistry Education Research and Practice 16: 460–477. doi: 10.1039/c4rp00214.
  • Upmeier zu Belzen, A., and D. Krüger. 2010. “Modellkompetenz im Biologieunterricht.” [Model Competence in Biology Teaching]. Zeitschrift für Didaktik der Naturwissenschaften 16: 59–75.
  • Wellnitz, N., S. Hartmann, and J. Mayer. 2010. “Developing a Paper-and-Pencil-test to Assess Students’ Skills in Scientific Inquiry.” In Contemporary Science Education Research: Learning and Assessment, edited by G. Çakmaki and F. Taar, 289–294. Ankara: ESERA.
  • Wong, T. F. 2003. “A Case Study of Test Design in an Engineering Programme Using Item Aanalysis.” INTI Journal 1 (3): 223–232.
  • Zlatkin-Troitschanskaia, O., R. J. Shavelson, and C. Kuhn. 2015. “The International State of Research on Measurement of Competency in Higher Education.” Studies in Higher Education 40 (3): 393–411. doi:10.1080/03075079.2015.1004241.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.