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Students' Complex Problem Solving Profiles.

Michela Gnaldi1, Silvia Bacci2, Thiemo Kunze3

  • 1Department of Political Sciences, University of Perugia, Via Pascoli 20, 06123, Perugia, Italy.

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|June 22, 2020
PubMed
Summary
This summary is machine-generated.

This study identifies ten distinct student profiles for complex problem solving (CPS) using item response theory. Higher-performing students exhibit better cognitive and non-cognitive skills, with learning-by-doing impacting different groups uniquely.

Keywords:
complex problem solvingdiscrete two-tier item response theory (IRT) modellog dataprofiles of students

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Area of Science:

  • Educational Psychology
  • Cognitive Science
  • Psychometrics

Background:

  • Complex problem solving (CPS) is a critical 21st-century skill assessed via computer-based tests.
  • Log data from these tests offer behavioral insights but pose statistical challenges.
  • Identifying homogeneous student profiles is crucial for understanding CPS abilities.

Purpose of the Study:

  • To decode complex problem solving (CPS) log data for identifying homogeneous student profiles.
  • To analyze the multidimensional nature of CPS and its relationship with individual characteristics.
  • To profile students based on their performance in dynamic, computer-based problem-solving tasks.

Main Methods:

  • Utilized a discrete two-tier item response theory model.
  • Analyzed log data from computer-based complex problem solving (CPS) tests.
  • Incorporated individual characteristics (cognitive, non-cognitive, gender, age) into the model.

Main Results:

  • Complex problem solving (CPS) was modeled as a three-dimensional latent variable.
  • Ten distinct latent classes of students with homogeneous CPS profiles were identified.
  • Higher latent classes correlated with superior cognitive and non-cognitive performances.
  • Learning-by-doing effects varied across student profiles.
  • Cognitive skills, non-cognitive skills, gender, and age differentiated latent classes.

Conclusions:

  • Student profiles in complex problem solving (CPS) are multidimensional and influenced by individual characteristics.
  • Distinct learning patterns emerge across different student profiles.
  • The developed model effectively profiles students in complex problem solving (CPS) tasks.