Auto-Grader - Auto-Grading Free Text Answers (Bestmasters)

Teachers spend a great amount of time grading free text answer type questions. To encounter this challenge an auto-grader system is proposed. The thesis illustrates that the auto-grader can be approached with simple, recurrent, and Transformer-based neural networks. Hereby, the Transformer-based models has the best performance. It is further demonstrated that geometric representation of question-answer pairs is a worthwhile strategy for an auto-grader. Finally, it is indicated that while the auto-grader could potentially assist teachers in saving time with grading, it is not yet on a level to fully replace teachers for this task.

• | Author: Robin Richner
• | Publisher: Springer Gabler
• | Publication Date: Oct 15, 2022
• | Number of Pages: 109 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 3658392029
• | ISBN-13: 9783658392024