TY - GEN
T1 - Optimization to Automated Phonetic Transcription Grading Tool (APTgt) – Automatic Exam Generator
AU - Liu, Jueting
AU - Speights, Marisha
AU - Bailey, Dallin
AU - Li, Sicheng
AU - Luan, Yaoxuan
AU - Mishra, Ishaan
AU - Cao, Yang
AU - Seals, Cheryl
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - The Automated Phonetic Transcription Grading Tool (APTgt) is an online exam system developed by Auburn University HCI group. This application aims to support faculty in communications disorders to improve their pedagogy and timely feedback for students. This article discusses an attempt to improve teacher’s experience by providing an automated method for exam generation, which can significantly save time while creating exams. The exam entry is created with the AU IPA (International Phonetic Alphabet) keyboard and system that grades the exams upon student completion of the exam. The exam is composed of several linguistics words with their pronunciation. Students need to answer the questions by inputting the correct phonetic spells during the exam. The core part in the auto-exam generator is the classification module, which can classify the input words into different difficulty levels. In this paper, we proposed two classification algorithms in the classification module: Rule-based algorithm and Classification and Regression Trees (CART).
AB - The Automated Phonetic Transcription Grading Tool (APTgt) is an online exam system developed by Auburn University HCI group. This application aims to support faculty in communications disorders to improve their pedagogy and timely feedback for students. This article discusses an attempt to improve teacher’s experience by providing an automated method for exam generation, which can significantly save time while creating exams. The exam entry is created with the AU IPA (International Phonetic Alphabet) keyboard and system that grades the exams upon student completion of the exam. The exam is composed of several linguistics words with their pronunciation. Students need to answer the questions by inputting the correct phonetic spells during the exam. The core part in the auto-exam generator is the classification module, which can classify the input words into different difficulty levels. In this paper, we proposed two classification algorithms in the classification module: Rule-based algorithm and Classification and Regression Trees (CART).
KW - Decision tree classifier
KW - E-learning
KW - International phonetic alphabet
KW - Linguistics words
KW - Multiclass classification
KW - Phonetic transcription
UR - http://www.scopus.com/inward/record.url?scp=85112195785&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85112195785&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-77889-7_6
DO - 10.1007/978-3-030-77889-7_6
M3 - Conference contribution
AN - SCOPUS:85112195785
SN - 9783030778880
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 80
EP - 91
BT - Learning and Collaboration Technologies
A2 - Zaphiris, Panayiotis
A2 - Ioannou, Andri
PB - Springer Science and Business Media Deutschland GmbH
T2 - 8th International Conference on Learning and Collaboration Technologies, LCT 2021, held as Part of the 23rd International Conference, HCI International 2021
Y2 - 24 July 2021 through 29 July 2021
ER -