Robin Richner

Auto-Grader - Auto-Grading Free Text Answers (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

About the author

Robin Richner was working as a Machine Learning Engineer in the edtech industry exploring ways to help teachers in their daily life. He now moved on to the web3 industry.

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Produktdetails

• Verlag: Springer Fachmedien Wiesbaden
• Seitenzahl: 96
• Erscheinungstermin: 14. Oktober 2022
• Englisch
• ISBN-13: 9783658392031
• Artikelnr.: 66108887

Autorenporträt

Robin Richner was working as a Machine Learning Engineer in the edtech industry exploring ways to help teachers in their daily life. He now moved on to the web3 industry.

Inhaltsangabe

Introduction.- Research design.- Research background.- Data.- Model development.- Evaluation.- Discussion, limitations and further research.- Conclusion.

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