@inproceedings{be1c5682afec474b80ed815cb85cf54f,
title = "Semantic feedback for paper-based programming exams",
abstract = "We design and study ExamParser, an innovative intelligent semantic automatic indexing method, for orchestrating today's programming classes. ExamParser automatically processes paper-based exams by associating sets of concepts to the exam questions, which provide graders semantic grading guidelines and leave personalized semantic feedback. Results showed that the ExamPraser significantly extract more and diverse concepts from exams. It also achieves high coherence within exam, indicating the automatic concept extraction from exams is promising and could be a potential technological solution to provide personalized feedback for large-size programming classes.",
keywords = "Computing education, Personalized learning, Programming, Semantic feedback, Visual analytics",
author = "Ihan Hsiao and Govindarajan, {Sesha Kumar Pandhalkudi}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 16th IEEE International Conference on Advanced Learning Technologies, ICALT 2016 ; Conference date: 25-07-2016 Through 28-07-2016",
year = "2016",
month = nov,
day = "28",
doi = "10.1109/ICALT.2016.111",
language = "English (US)",
series = "Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "65--69",
editor = "Spector, {J. Michael} and Chin-Chung Tsai and Ronghuai Huang and Paul Resta and Sampson, {Demetrios G} and Kinshuk and Nian-Shing Chen",
booktitle = "Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016",
}