Using intelligent feedback to improve sourcing and integration in students' essays

Anne Britt, Peter Wiemer-Hastings, Aaron Larson, and Chuck Perfetti. Using intelligent feedback to improve sourcing and integration in students' essays. International Journal of Artificial Intelligence in Education, 14:359–374, IAIED Society, Leeds, England, 2004.

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Abstract

Learning and reasoning from multiple documents requires students to employ the skills of sourcing (i.e., attending to and citing sources) and information integration (i.e., making connections among content from different sources). Sourcer's Apprentice Intelligent Feedback mechanism (SAIF) is a tool for providing students with automatic and immediate feedback on their use of these skills during the writing process. SAIF uses Latent Semantic Analysis (LSA), a string-matching technique and a pattern-matching algorithm to identify problems in students' essays. These problems include plagiarism, uncited quotation, lack of citations, and limited content integration. SAIF provides feedback and constructs examples to demonstrate explicit citations to help students improve their essays. In addition to describing SAIF, we also present the results of two experiments. In the first experiment, SAIF was found to detect source identification and integration problems in student essays at a comparable level to human raters. The second experiment tested the effectiveness of SAIF in helping students write better essays. Students given SAIF feedback included more explicit citations in their essays than students given sourcing-reminder instructions or a simple prompt to revise.

BibTeX

@ARTICLE{britt:ijaied04,
  author = 	 name:apac,
  title = 	 {Using intelligent feedback to improve sourcing and integration in students' essays},
  journal = 	 {International Journal of Artificial Intelligence in Education},
  year = 	 2004,
  publisher =    {IAIED Society},
  address =      {Leeds, England},
  volume =       14,
  pages =        {359--374},
  cvnote = {G-index = 132},
  abstract =     {Learning and reasoning from multiple documents requires students to employ the skills of sourcing (i.e., attending to and citing sources) and information integration (i.e., making connections among content from different sources). Sourcer's Apprentice Intelligent Feedback mechanism (SAIF) is a tool for providing students with automatic and immediate feedback on their use of these skills during the writing process. SAIF uses Latent Semantic Analysis (LSA), a string-matching technique and a pattern-matching algorithm to identify problems in students' essays. These problems include plagiarism, uncited quotation, lack of citations, and limited content integration. SAIF provides feedback and constructs examples to demonstrate explicit citations to help students improve their essays. In addition to describing SAIF, we also present the results of two experiments. In the first experiment, SAIF was found to detect source identification and integration problems in student essays at a comparable level to human raters. The second experiment tested the effectiveness of SAIF in helping students write better essays. Students given SAIF feedback included more explicit citations in their essays than students given sourcing-reminder instructions or a simple prompt to revise.}
}