Modelling the Complexity of Measurement Estimation Situations - A Theoretical Framework for the Estimation of Lengths

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Standard

Modelling the Complexity of Measurement Estimation Situations - A Theoretical Framework for the Estimation of Lengths. / Weiher, Dana Farina; Ruwisch, Silke; Huang, Hsin-Mei E. et al.
in: mathematica didactica, Jahrgang 45, 25.08.2022.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Harvard

APA

Vancouver

Bibtex

@article{783314b3eaa14fea99dc837ddcb3e3f3,
title = "Modelling the Complexity of Measurement Estimation Situations - A Theoretical Framework for the Estimation of Lengths",
abstract = "Abilities in estimation are important for everyday life, and investigated with different research interests. Although quite different estimation situations were used, studies usually did not address the question of task characteristics systematically. This paper presents a theoretical model that may serve as a basis for the task design in length estimation. First, key featuresof length estimation tasks were extracted by analyzing the literature. Second, these elements are varied systematically. Third, they are combined, reanalyzed, and reduced. This procedure results in a model of 228 meaningful situations for length estimation. The model may also serve as an analytical tool for comparison of studies. ",
keywords = "Didactics of Mathematics",
author = "Weiher, {Dana Farina} and Silke Ruwisch and Huang, {Hsin-Mei E.} and Jessica Hoth and Aiso Heinze",
year = "2022",
month = aug,
day = "25",
doi = "10.18716/ojs/md/2022.1593",
language = "English",
volume = "45",
journal = "mathematica didactica",
issn = "0172-8407",
publisher = "Verlag Franzbecker",

}

RIS

TY - JOUR

T1 - Modelling the Complexity of Measurement Estimation Situations - A Theoretical Framework for the Estimation of Lengths

AU - Weiher, Dana Farina

AU - Ruwisch, Silke

AU - Huang, Hsin-Mei E.

AU - Hoth, Jessica

AU - Heinze, Aiso

PY - 2022/8/25

Y1 - 2022/8/25

N2 - Abilities in estimation are important for everyday life, and investigated with different research interests. Although quite different estimation situations were used, studies usually did not address the question of task characteristics systematically. This paper presents a theoretical model that may serve as a basis for the task design in length estimation. First, key featuresof length estimation tasks were extracted by analyzing the literature. Second, these elements are varied systematically. Third, they are combined, reanalyzed, and reduced. This procedure results in a model of 228 meaningful situations for length estimation. The model may also serve as an analytical tool for comparison of studies.

AB - Abilities in estimation are important for everyday life, and investigated with different research interests. Although quite different estimation situations were used, studies usually did not address the question of task characteristics systematically. This paper presents a theoretical model that may serve as a basis for the task design in length estimation. First, key featuresof length estimation tasks were extracted by analyzing the literature. Second, these elements are varied systematically. Third, they are combined, reanalyzed, and reduced. This procedure results in a model of 228 meaningful situations for length estimation. The model may also serve as an analytical tool for comparison of studies.

KW - Didactics of Mathematics

U2 - 10.18716/ojs/md/2022.1593

DO - 10.18716/ojs/md/2022.1593

M3 - Journal articles

VL - 45

JO - mathematica didactica

JF - mathematica didactica

SN - 0172-8407

ER -

DOI

Zuletzt angesehen

Publikationen

  1. A sensor fault detection scheme as a functional safety feature for DC-DC converters
  2. Evaluating structural and compositional canopy characteristics to predict the light-demand signature of the forest understorey in mixed, semi-natural temperate forests
  3. lp-Norm Multiple Kernel Learning
  4. Design optimization of spiral coils for textile applications by genetic algorithm
  5. Exact and approximate inference for annotating graphs with structural SVMs
  6. Fast, Fully Automated Analysis of Voriconazole from Serum by LC-LC-ESI-MS-MS with Parallel Column-Switching Technique
  7. Recurrence Quantification Analysis of Processes and Products of Discourse
  8. Lessons learned for spatial modelling of ecosystem services in support of ecosystem accounting
  9. Construct Objectification and De-Objectification in Organization Theory
  10. Computational modeling of amorphous polymers
  11. Modeling and numerical simulation of multiscale behavior in polycrystals via extended crystal plasticity
  12. Influence of Process Parameters and Die Design on the Microstructure and Texture Development of Direct Extruded Magnesium Flat Products
  13. Simple saturated PID control for fast transient of motion systems
  14. Dynamic Lot Size Optimization with Reinforcement Learning
  15. The delay vector variance method and the recurrence quantification analysis of energy markets
  16. Introducing parametric uncertainty into a nonlinear friction model
  17. Faulty Process Detection Using Machine Learning Techniques
  18. TextGraphs 2024 Shared Task on Text-Graph Representations for Knowledge Graph Question Answering
  19. Clause identification using entropy guided transformation learning
  20. Mathematical Modeling for Robot 3D Laser Scanning in Complete Darkness Environments to Advance Pipeline Inspection
  21. Dispatching rule selection with Gaussian processes
  22. Constraints are the solution, not the problem
  23. Dynamic priority based dispatching of AGVs in flexible job shops
  24. Mining positional data streams
  25. Understanding the properties of isospectral points and pairs in graphs
  26. Improving students’ science text comprehension through metacognitive self-regulation when applying learning strategies
  27. Comments on "Tracking Control of Robotic Manipulators With Uncertain Kinematics and Dynamics"
  28. Computing regression statistics from grouped data
  29. From Knowledge to Application
  30. Gaussian processes for dispatching rule selection in production scheduling