Automated writing evaluation (AWE) has been frequently used to provide feedback on student writing. Many empirical studies have examined the effectiveness of AWE on writing quality, but the results were inconclusive. Thus, the magnitude of AWE's overall effect and factors influencing its effectiveness across studies remained unclear. This study…

This study investigates the potential of a software tool based on Latent Semantic Analysis (LSA; Landauer, McNamara, Dennis, & Kintsch, 2007) to automatically evaluate complex German texts. A sample of N = 94 German university students provided written answers to questions that involved a high amount of analytical reasoning and evaluation.…

Analyzed 17 personal attributes of 160 undergraduate students who wrote reports on a computer or by hand, and compared differences in the quality of computer and handwritten reports with each student's personal attributes. Concludes that some attributes do relate to computer writing quality. (JMV)

Powers, Burstein, Chodorow, Fowles, and Kukich (2002) suggested that automated essay scoring (AES) may benefit from the use of "general" scoring models designed to score essays irrespective of the prompt for which an essay was written. They reasoned that such models may enhance score credibility by signifying that an AES system measures the same…

Latent semantic analysis (LSA) is an automated, statistical technique for comparing the semantic similarity of words or documents. In this article, I examine the application of LSA to automated essay scoring. I compare LSA methods to earlier statistical methods for assessing essay quality, and critically review contemporary essay-scoring systems…