An Exploratory Application of Rhetorical Structure Theory to Detect Coherence Errors in L2 English Writing: Possible Implications for Automated Writing Evaluation Software

This paper presents an initial attempt to examine whether Rhetorical Structure Theory (RST) (Mann & Thompson, 1988) can be fruitfully applied to the detection of the coherence errors made by Taiwanese low-intermediate learners of English. This investigation is considered warranted for three reasons. First, other methods for bottom-up coherence analysis have proved ineffective (e.g., Watson Todd et al., 2007). Second, this research provides a preliminary categorization of the coherence errors made by first language (L1) Chinese learners of English. Third, second language discourse errors in general have received little attention in applied linguistic research. The data are 45 written samples from the LTTC English Learner Corpus, a Taiwanese learner corpus of English currently under construction. The rationale of this study is that diagrams which violate some of the rules of RST diagram formation will point to coherence errors. No reliability test has been conducted since this work is at an initial stage. Therefore, this study is exploratory and results are preliminary. Results are discussed in terms of the practicality of using this method to detect coherence errors, their possible consequences about claims for a typical inductive content order in the writing of L1 Chinese learners of English, and their potential implications for Automated Writing Evaluation (AWE) software, since discourse organization is one of the essay characteristics assessed by this software. In particular, the extent to which the kinds of errors detected through the RST analysis match those located by Criterion (Burstein, Chodorow, & Leachock, 2004), a well-known AWE software by Educational Testing Service (ETS), is discussed

The Learning Grid and E-Assessment using Latent Semantic Analysis

E-assessment is an important component of e-learning and e-qualification. Formative and summative assessment serve different purposes and both types of evaluation are critical to the pedagogicalprocess. While students are studying, practicing, working, or revising, formative assessment provides direction, focus, and guidance. Summative assessment provides the means to evaluate a learner's achievement and communicate that achievement to interested parties. Latent Semantic Analysis (LSA) is a statistical method for inferring meaning from a text. Applications based on LSA exist that provide both summative and formative assessment of a learner's work. However, the huge computational needs are a major problem with this promising technique. This paper explains how LSA works, describes the breadth of existing applications using LSA, explains how LSA is particularly suited to e-assessment, and proposes research to exploit the potential computational power of the Grid to overcome one of LSA's drawbacks

Ethical Implementation of an Automated Essay Scoring (AES) System: A Case Study of Student and Instructor Use, Satisfaction, and Perceptions of AES in a Business Law Course

A pilot study of a vendor provided automated essay scoring system was conducted in a Business Law class of 27 students. Students answered a business law fact pattern question which was reviewed and graded by the textbook vendor utilizing artificial intelligence software. Students were surveyed on their use, satisfaction, perceptions and technical issues utilizing the Write Experience automated essay scoring (AES) software. The instructor also chronicles the adoption, set up and use of an AES. Also detailed are the advantages and disadvantages of utilizing such software in an undergraduate course environment where some students may not be technologically adept or may lack motivation to experiment with a new testing procedure