@article{3418,
  keywords = {Automated Short Answer Scoring, Hybrid Transfer Learning, Student Answer Dataset, Trustworthy System},
  author = {Martinus Maslim and Hei-Chia Wang and Cendra Devayana Putra and Yulius Denny Prabowo},
  title = {A Trustworthy Automated Short-Answer Scoring System Using a New Dataset and Hybrid Transfer Learning Method},
  abstract = {To measure the quality of student learning, teachers must conduct evaluations. One of the most efficient modes of evaluation is the short answer question. However, there can be inconsistencies in teacher-performed manual evaluations due to an excessive number of students, time demands, fatigue, etc. Consequently, teachers require a trustworthy system capable of autonomously and accurately evaluating student answers. Using hybrid transfer learning and student answer dataset, we aim to create a reliable automated short answer scoring system called Hybrid Transfer Learning for Automated Short Answer Scoring (HTL-ASAS). HTL-ASAS combines multiple tokenizers from a pretrained model with the bidirectional encoder representations from transformers. Based on our evaluation of the training model, we determined that HTL-ASAS has a higher evaluation accuracy than models used in previous studies. The accuracy of HTL-ASAS for datasets containing responses to questions pertaining to introductory information technology courses reaches 99.6%. With an accuracy close to one hundred percent, the developed model can undoubtedly serve as the foundation for a trustworthy ASAS system.},
  year = {2024},
  journal = {International Journal of Interactive Multimedia and Artificial Intelligence},
  volume = {8},
  chapter = {37},
  number = {5},
  pages = {37-45},
  month = {03/2024},
  issn = {1989-1660},
  url = {https://www.ijimai.org/journal/bibcite/reference/3418},
  doi = {10.9781/ijimai.2024.02.003},
}