Auto-Grader - Auto-Grading Free Text Answers

By Robin Richner

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.

• Format: Paperback
• Language: English
• ISBN: 3658392029
• ISBN13: 9783658392024
• Release Date: October 2022
• Publisher: Springer Gabler
• Length: 96 Pages
• Weight: 0.35 lbs.
• Dimensions: 0.3" x 5.7" x 8.2"