Accession Number:

ADA523231

Title:

Enhancing Simulation-based Training Adversary Tactics via Evolution (ESTATE)

Descriptive Note:

Quarterly status rept. 15 Mar 2009-15 Jun 2010

Corporate Author:

CHARLES RIVER ANALYTICS INC CAMBRIDGE MA

Personal Author(s):

Report Date:

2010-06-15

Pagination or Media Count:

8.0

Abstract:

The goal of this task is to discover a method to measure student learning and to determine if students are gaining proficiency in this pre-algebra activity. This method will augment our student assessment and challenge adaptation techniques by providing a better estimate of student ability and Zone of Proximal Development ZPD. Earlier exploration of the MoneyBee Dataset indicated that the students score better as they attempt more problems, but because of student selection of problems, it was unclear whether the students were improving or simply choosing easier problems to attempt Rosenberg, 2009. Also, we discovered that our heuristic estimate of problem difficulty correlates with the time to complete a problem Rosenberg, 2010. The results of the current analysis below show that as the number of problems attempted by a student increases, 1 the mean and median difficulty increases and 2 the mean and median time to complete decreases. This provides strong evidence for learning on the MoneyBee task.

Subject Categories:

  • Sociology and Law
  • Numerical Mathematics
  • Computer Programming and Software
  • Human Factors Engineering and Man Machine Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE