ConQuest is a computer program developed at the Australian Council for Educational Research (ACER) for fitting item response and latent regression models. It provides a comprehensive and flexible range of item response models to analysts, allowing them to examine the properties of performance assessments, traditional assessments and rating scales. ConQuest also makes available, to the wider measurement and research community, the most up to date psychometric methods of multifaceted item response models, multidimensional item response models, latent regression models and drawing plausible values.

References in zbMATH (referenced in 37 articles )

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  1. LaMar, Michelle M.: Markov decision process measurement model (2018)
  2. Rose, Norman; von Davier, Matthias; Nagengast, Benjamin: Modeling omitted and not-reached items in IRT models (2017)
  3. Ip, Edward H.; Chen, Shyh-Huei; Quandt, Sara A.: Analysis of multiple partially ordered responses to belief items with don’t know option (2016)
  4. König, Johannes; Kramer, Charlotte: Teacher professional knowledge and classroom management: on the relation of general pedagogical knowledge (GPK) and classroom management expertise (CME) (2016) MathEduc
  5. Magis, David: Efficient standard error formulas of ability estimators with dichotomous item response models (2016)
  6. Zhang, Ying; Watermann, Rainer; Daniel, Annabell: Are multiple goals in elementary students beneficial for their school achievement? A latent class analysis (2016) MathEduc
  7. Bakker, Marjoke; van den Heuvel-Panhuizen, Marja; Robitzsch, Alexander: Effects of playing mathematics computer games on primary school students’ multiplicative reasoning ability (2015) MathEduc
  8. Friedrich, Alena; Flunger, Barbara; Nagengast, Benjamin; Jonkmann, Kathrin; Trautwein, Ulrich: Pygmalion effects in the classroom: teacher expectancy effects on students’ math achievement (2015) MathEduc
  9. König, Johannes; Blömeke, Sigrid; Kaiser, Gabriele: Early career mathematics teachers’ general pedagogical knowledge and skills: do teacher education, teaching experience, and working conditions make a difference? (2015) MathEduc
  10. Bakker, Marjoke; van den Heuvel-Panhuizen, Marja; Robitzsch, Alexander: First-graders’ knowledge of multiplicative reasoning before formal instruction in this domain (2014) MathEduc
  11. Gogol, Katarzyna; Brunner, Martin; Goetz, Thomas; Martin, Romain; Ugen, Sonja; Keller, Ulrich; Fischbach, Antoine; Preckel, Franzis: “My questionnaire is too long!” The assessments of motivational-affective constructs with three-item and single-item measures (2014) MathEduc
  12. König, Johannes; Blömeke, Sigrid; Klein, Patricia; Suhl, Ute; Busse, Andreas; Kaiser, Gabriele: Is teachers’ general pedagogical knowledge a premise for noticing and interpreting classroom situations? A video-based assessment approach (2014) MathEduc
  13. Lingel, K.; Neuenhaus, N.; Artelt, C.; Schneider, W.: The influence of metacognitive knowledge on the development of mathematics achievement at the beginning of secondary school (2014) MathEduc
  14. Penk, Christiane; Pöhlmann, Claudia; Roppelt, Alexander: The role of test-taking motivation for students’ performance in low-stakes assessments: an investigation of school-track-specific differences (2014) MathEduc
  15. Suárez-Álvarez, Javier; Fernández-Alonso, Rubén; Muñiz, José: Self-concept, motivation, expectations, and socioeconomic level as predictors of academic performance in mathematics (2014) MathEduc
  16. Baumert, Jürgen; Kunter, Mareike: The effect of content knowledge and pedagogical content knowledge on instructional quality and student achievement (2013) MathEduc
  17. Blömeke, Sigrid; Suhl, Ute; Döhrmann, Martina: Assessing strengths and weaknesses of teacher knowledge in Asia, Eastern Europe, and Western countries: differential item functioning in TEDS-M (2013) MathEduc
  18. Buchholtz, Nils; Kaiser, Gabriele: Improving mathematics teacher education in Germany: empirical results from a longitudinal evaluation of innovative programs (2013) MathEduc
  19. Christensen, Karl Bang: Conditional maximum likelihood estimation in polytomous Rasch models using SAS (2013)
  20. Frey, Andreas; Seitz, Nicki-Nils; Kröhne, Ulf: Reporting differentiated literacy results in PISA by using multidimensional adaptive testing (2013) MathEduc

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