Legal LEGO: Model Based Computer Assisted Teaching in evidence courses

This paper describes the development of a new approach to the use of ICT for the teaching of courses in the interpretation and evaluation of evidence. It is based on ideas developed for the teaching of science to school children, in particular the importance of models and qualitative reasoning skills. In the first part, we make an analysis of the basis of current research into “evidence scholarship” and the demands such a system would have to meet. In the second part, we introduce the details of such a system that we developed initially to assist police in the interpretation of evidence.

[1]  Jeroen Keppens,et al.  Causality enabled compositional modelling of Bayesian networks , 2004 .

[2]  Jeroen Keppens,et al.  Knowledge based crime scenario modelling , 2006, Expert Syst. Appl..

[3]  N. Nersessian Should physicists preach what they practice? , 1995 .

[4]  Steven C Greer Miscarriages of Criminal Justice Reconsidered , 1994 .

[5]  Henry Prakken,et al.  Modelling reasoning about evidence in legal procedure , 2001, ICAIL '01.

[6]  D. Perkins The Many Faces of Constructivism. , 1999 .

[7]  Kenneth D. Forbus Why computer modeling should become a popular hobby , 1996 .

[8]  John Selbak Digital Litigation: The Prejudicial Effects of Computer-Generated Animation in the Courtroom , 1994 .

[9]  Johan de Kleer,et al.  An Assumption-Based TMS , 1987, Artif. Intell..

[10]  Brian Falkenhainer,et al.  Compositional Modeling: Finding the Right Model for the Job , 1991, Artif. Intell..

[11]  Seymour Papert,et al.  Mindstorms: Children, Computers, and Powerful Ideas , 1981 .

[12]  Douglas Walton,et al.  Critical questions in computational models of legal argument , 2005 .

[13]  D. Schum The Evidential Foundations of Probabilistic Reasoning , 1994 .

[14]  Kenneth D. Forbus Qualitative Process Theory , 1984, Artificial Intelligence.

[15]  Paul J. Feltovich,et al.  Smart machines in education: the coming revolution in educational technology , 2001 .

[16]  A. Caramazza,et al.  Naive beliefs in “sophisticated” subjects: misconceptions about trajectories of objects , 1981, Cognition.

[17]  Saul M. Kassin,et al.  Computer-Animated Displays and the Jury: Facilitative and Prejudicial Effects , 1997 .

[18]  Leo C. Ureel,et al.  Qualitative modeling for middle-school students , 2004 .

[19]  E. Bergslien Teaching To Avoid the "CSI Effect". Keeping the Science in Forensic Science , 2006 .

[20]  N. Duxbury Jerome Frank and the Legacy of Legal Realism , 1991 .

[21]  Jeroen Keppens,et al.  Probabilistic abductive computation of evidence collection strategies in crime investigation , 2005, ICAIL '05.

[22]  Douglas Walton,et al.  Appeal to Expert Opinion: Arguments from Authority , 1997 .

[23]  S. Turkle,et al.  Epistemological Pluralism and the Revaluation of the Concrete. , 1992 .

[24]  Jose P. Mestre Implications of research on learning for the education of prospective science and physics teachers , 2001 .

[25]  Seymour Papert,et al.  An exploration in the space of mathematics educations , 1996, Int. J. Comput. Math. Learn..

[26]  Johan de Kleer,et al.  Readings in qualitative reasoning about physical systems , 1990 .

[27]  Bart Verheij,et al.  Arguments and Defeat in Argument-Based Nonmonotonic Reasoning , 1995, EPIA.

[28]  Kenneth D. Forbus,et al.  Using Qualitative Physics to Build Articulate Software for Thermodynamics Education: A Preliminary Report , 1994, Interact. Learn. Environ..

[29]  W. Twining Taking facts seriously , 1997 .

[30]  T. Anderson,et al.  Analysis of evidence : how to do things with facts , 1997 .

[31]  Kenneth D. Forbus Articulate software for science and engineering education , 2001 .