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ERIC Number: ED599205
Record Type: Non-Journal
Publication Date: 2019-Jul
Pages: 6
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Grading Emails and Generating Feedback
Unnam, Abhishek; Takhar, Rohit; Aggarwal, Varun
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (12th, Montreal, Canada, Jul 2-5, 2019)
Email has become the most preferred form of business communication. Writing "good" email has become an essential skill required in the industry. "Good" email writing not only facilitates clear communication, but also makes a positive impression on the recipient, whether it be one's colleague or a customer. The aim of this paper is to demystify the components of a "good" email and to define a set of parameters by which to grade the quality of an email and provide detailed feedback. This can help candidates improve their email writing skills and also guide tutors. The email grading parameters encompass traditional attributes of written English (i.e. coherent and relevant content and correct grammar) but also include a unique set of characteristics that we may objectively identify as email etiquette. These characterstics comprise the metrics we use to evaluate the quality of the various constituent parts of an email. We grade the email using artificial intelligence, acting on semi-structured text. We use a mix of machine learning and rule-based systems to effectively grade an email on the specified parameters. Our system automatically grades email with accuracy comparable to human graders. [For the full proceedings, see ED599096.]
International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Publication Type: Speeches/Meeting Papers; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A