Using Automated Indices of Cohesion to Evaluate an Intelligent Tutoring System and an Automated Writing Evaluation System
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Abstract
We present an evaluation of the Writing Pal (W-Pal) intelligent tutoring system (ITS) and the W-Pal automated writing evaluation (AWE) system through the use ofcomputational indices related to text cohesion. Sixty-four students participated in this study. Each student was assigned to either the W-Pal ITS condition or the W-Pal AWE condition. The W-Pal ITS includes strategy instruction, game-based practice, and essay-based practice with automated feedback. In the ITS condition, students received strategy training and wrote and revised one essay in each of the 8 training sessions. In the AWE condition, students only interacted with the essay writing and feedback tools. These students wrote and revised two essays in each of the 8 sessions. Indices of local and global cohesion reported by the computational tools Coh-Metrix and the Writing Assessment Tool (WAT) were used to investigate pretest and posttest writing gains. For both the ITS and the AWE systems, training led to the increased use of global cohesion features in essay writing. This study demonstrates that automated indices of text cohesion can be used to evaluate the effects of ITSs and AWE systems and further demonstrates how text cohesion develops as a result of instruction, writing, and automated feedback.
Keywords
Cohesion Intelligent Tutoring Systems Natural Language Processing Corpus Linguistics Computational Linguistics Writing PedagogyPreview
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