An intelligent information access system assisting a case based learning methodology evaluated in higher education with medical students

  • Authors:
  • Fernando Aparicio;Manuel De Buenaga;Margarita Rubio;Asunción Hernando

  • Affiliations:
  • Computer Science Department, Universidad Europea de Madrid, C/Tajo, s/n, 28670 Villaviciosa de Odón, Madrid, Spain;Computer Science Department, Universidad Europea de Madrid, C/Tajo, s/n, 28670 Villaviciosa de Odón, Madrid, Spain;Medical Specialties Department, Universidad Europea de Madrid, C/Tajo, s/n, 28670 Villaviciosa de Odón, Madrid, Spain;Medical Specialties Department, Universidad Europea de Madrid, C/Tajo, s/n, 28670 Villaviciosa de Odón, Madrid, Spain

  • Venue:
  • Computers & Education
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

In recent years there has been a shift in educational methodologies toward a student-centered approach, one which increasingly emphasizes the integration of computer tools and intelligent systems adopting different roles. In this paper we describe in detail the development of an Intelligent Information Access system used as the basis for producing and assessing a constructivist learning methodology with undergraduate students. The system automatically detects significant concepts available within a given clinical case and facilitates an objective examination, following a proper selection process of the case in which is taken into account the students' knowledge level. The learning methodology implemented is intimately related to concept-based, case-based and internet-based learning. In spite of growing theoretical research on the use of information technology in higher education, it is rare to find applications that measure learning and students' perceptions and compare objective results with a free Internet search. Our work enables students to gain understanding of the concepts in a case through Web browser interaction with our computer system identifying these concepts and providing direct access to enriched related information from Medlineplus, Freebase and PubMed. In order to evaluate the learning activity outcomes, we have done a trial run with volunteer students from a 2nd year undergraduate Medicine course, dividing the volunteers into two groups. During the activity all students were provided with a clinical case history and a multiple choice test with medical questions relevant to the case. This test could be done in two different ways: learners in one group were allowed to freely seek information on the Internet, while the other group could only search for information using the newly developed computer tool. In the latter group, we measured how students perceived the tool's support for solving the activity and the Web interface usability, supplying them with a Likert questionnaire for anonymous completion. The particular case selected was a female with a medical history of heart pathology, from which the system derived medical terms closely associated with her condition description, her clinical evolution and treatment.