Enhancing Simulation-based Training Adversary Tactics via Evolution (ESTATE)
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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 15, 2010
- Accession Number
- ADA523231
Entities
People
- Brad R Rosenberg