Literature DB >> 2011052

Solving the problem of how medical students solve problems.

R H Stevens1, J M McCoy, A R Kwak.   

Abstract

Although gathering and processing information are essential to medical problem solving, little is known about what strategies students use to gather information or how they use their cognitive skills to solve problems. We have developed computer-based problem-solving exercises in immunology to determine how students gather and process information. Graphic representations of students' search paths through different problems were developed to visualize how organized and focused their knowledge was, how well their organization related to critical concepts in immunology, where serious misconceptions (confusion or erroneous models) occurred, and whether proper knowledge links between conceptual domains existed. With rapid generation and interpretation of information on patterns and difficulties in problem solving, it should become possible to develop a specific and personal approach to each student's educational needs.

Mesh:

Year:  1991        PMID: 2011052

Source DB:  PubMed          Journal:  MD Comput        ISSN: 0724-6811


  9 in total

1.  Design and performance frameworks for constructing problem-solving simulations.

Authors:  Ron Stevens; Joycelin Palacio-Cayetano
Journal:  Cell Biol Educ       Date:  2003

2.  Can artificial neural networks provide an "expert's" view of medical students performances on computer based simulations?

Authors:  R H Stevens; K Najafi
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1992

3.  Preliminary evaluation of learning via the AI/LEARN/Rheumatology interactive videodisc system.

Authors:  J A Mitchell; A J Bridges; J C Reid; J H Cutts; S Hazelwood; G C Sharp
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1992

4.  Composing user models through logic analysis.

Authors:  B P Bergeron; R N Shiffman; R L Rouse; R A Greenes
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1991

5.  Artificial neural networks can distinguish novice and expert strategies during complex problem solving.

Authors:  R H Stevens; A C Lopo; P Wang
Journal:  J Am Med Inform Assoc       Date:  1996 Mar-Apr       Impact factor: 4.497

6.  Problem-solving skills among precollege students in clinical immunology and microbiology: classifying strategies with a rubric and artificial neural network technology.

Authors:  S Kanowith-Klein; M Stave; R Stevens; A M Casillas
Journal:  Microbiol Educ       Date:  2001-05

7.  Conceptual change and computer-assisted instruction.

Authors:  M Pradham; P Dev
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1993

8.  Artificial neural network comparison of expert and novice problem-solving strategies.

Authors:  R H Stevens; A C Lopo
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1994

9.  Metacognition and Peer Learning Strategies as Predictors in Problem-Solving Performance in Microbiology.

Authors:  Josephine Itota Ebomoyi
Journal:  J Microbiol Biol Educ       Date:  2020-02-28
  9 in total

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