• ETRI Journal
• /
• v.46 no.1
• /
• pp.82-95
• /
• 2024

As automated essay scoring (AES) has progressed from handcrafted techniques to deep learning, holistic scoring capabilities have merged. However, specific trait assessment remains a challenge because of the limited depth of earlier methods in modeling dual assessments for holistic and multi-trait tasks. To overcome this challenge, we explore providing comprehensive feedback while modeling the interconnections between holistic and trait representations. We introduce the DualBERT-Trans-CNN model, which combines transformer-based representations with a novel dual-scale bidirectional encoder representations from transformers (BERT) encoding approach at the document-level. By explicitly leveraging multi-trait representations in a multi-task learning (MTL) framework, our DualBERT-Trans-CNN emphasizes the interrelation between holistic and trait-based score predictions, aiming for improved accuracy. For validation, we conducted extensive tests on the ASAP++ and TOEFL11 datasets. Against models of the same MTL setting, ours showed a 2.0% increase in its holistic score. Additionally, compared with single-task learning (STL) models, ours demonstrated a 3.6% enhancement in average multi-trait performance on the ASAP++ dataset.

• Quality Improvement in Health Care
• /
• v.1 no.1
• /
• pp.124-131
• /
• 1994

Polysomnography is an essential methodology for diagnosing and following up sleep disorders and doing researches on human sleep. Sleep medicine, mainly with the utilization of polysomnographic techniques, has developed itself as one of the promising fields in the 21st century medicine. Korea is not an exception in importing and developing sleep medicine into the conventional medicine. However, it still remains to be clarified what polysomnography is for and how it should be done, considering the relatively recent introduction of sleep medicine into Korea. The author, being a board-certified sleep medicine specailist, having experienced spreading out sleep medicine within Korea for the past four years, and having recently set up a major sleep study facility in Korea at Seoul National University Hospital, attempts in this introductory critical article to review the essential issues related to quality assurance in polysomnographic study of human sleep. Also, unconditional introduction of "automated" sleep scoring system, which has been found to have significantly reduced reliability in various studies including the author's own, is critically reviewed. The author suggests that quality assurance and training program should be initiated and established by a responsible sleep medicine-related organization such as the Korean Association of Sleep Medicine and Psychophysiology.

• Journal of Biomedical Engineering Research
• /
• v.28 no.5
• /
• pp.585-589
• /
• 2007

This study proposes an automated pegboard utilizing the RFID system with multiple reader antennas for the rehabilitation services and the occupational therapy. The system automates the scoring by detecting the plugging correctness as well as the plugging status. It also aims to increase the patient's interest and the functional intelligence. The system was prototyped and tested for the automatic capability of the scoring the session time and success rate. The proposed system will be served as the typical example for the ubiquitous rehabilitation devices.

• Educational Technology International
• /
• v.12 no.2
• /
• pp.71-94
• /
• 2011

How can an automated essay scoring (AES) program, which provides feedback for essays, be a formative tool for improving ESL writing? In spite of the increasing demands for English writing proficiency, English writing instruction has not been effective for teaching and learning because of a lack of timely and accurate feedback. In this context, AES as a possible solution has been gaining the attention of educators and scholars in ESL/EFL writing education because it can provide consistent and prompt feedback for student writers. This experimental study examined the impact of different types of feedback for a college ESL writing program using the Criterion AES system. The results reveal the positive impact of AES in a college-level ESL course and differences between the teacher's feedback and the AES feedback. The findings suggest that AES can be effectively integrated into ESL writing instruction as a formative assessment tool.

• Journal of The Korean Association For Science Education
• /
• v.40 no.3
• /
• pp.321-336
• /
• 2020

We explore automated scoring models of scientific argumentation. We consider how a new analytical approach using a machine learning technique may enhance the understanding of spoken argumentation in the classroom. We sampled 2,605 utterances that occurred during a high school student's science class on molecular structure and classified the utterances into five argumentative elements. Next, we performed Text Preprocessing for the classified utterances. As machine learning techniques, we applied support vector machines, decision tree, random forest, and artificial neural network. For enhancing the identification of rebuttal elements, we used a heuristic feature-engineering method that applies experts' classification of morphemes of scientific argumentation.

• The Journal of the Korea Contents Association
• /
• v.7 no.5
• /
• pp.36-46
• /
• 2007

This paper presents an automated English scoring system designed to help non-native speakers of English, Korean-speaking learners in particular. The system is developed to help the 3rd grade students in junior high school improve their English grammar skills. Without human's efforts, the system identifies grammar errors in English sentences, provides feedback on the detected errors, and scores the sentences. Detecting grammar errors in the system requires implementing a special type of rules in addition to the rules to parse grammatical sentences. Error production rules are implemented to analyze ungrammatical sentences and recognize syntactic errors. The rules are collected from the junior high school textbooks and real student test data. By firing those rules, the errors are detected followed by setting corresponding error flags, and the system continues the parsing process without a failure. As the final step of the process, the system scores the student sentences based on the errors detected. The system is evaluated with real English test data produced by the students and the answers provided by human teachers.

• The KIPS Transactions:PartB
• /
• v.14B no.3 s.113
• /
• pp.223-230
• /
• 2007

The purpose of developing an automated scoring system for English composition is to score the tests for writing English sentences and to give feedback on them without human's efforts. This paper presents an automated system to score English composition, whose input is a single sentence, not an essay. Dealing with a single sentence as an input has some advantages on comparing the input with the given answers by human teachers and giving detailed feedback to the test takers. The system has been developed and tested with the real test data collected through English tests given to the third grade students in junior high school. Two steps of the process are required to score a single sentence. The first process is analyzing the input sentence in order to detect possible errors, such as spelling errors, syntactic errors and so on. The second process is comparing the input sentence with the given answer to identify the differences as errors. The results produced by the system were then compared with those provided by human raters.

• The KIPS Transactions:PartB
• /
• v.16B no.2
• /
• pp.173-180
• /
• 2009

The purpose of developing an automated scoring system for English composition is to score English writing tests and to give diagnostic feedback to the test-takers without human's efforts. The system developed through our research detects grammatical errors of a single sentence on morphological, syntactic and semantic stages, respectively, and those errors are calculated into the final score. The error detecting stages are independent from one another, which causes duplicating the identical errors with different labels at different stages. These duplicated errors become a hindering factor to calculating an accurate score. This paper presents a solution to detecting the duplicated errors and improving an accuracy in calculating the final score by eliminating one of the errors.

• Bulletin of the Korean Chemical Society
• /
• v.29 no.5
• /
• pp.921-927
• /
• 2008

Discovery of $\alpha$-glucosidase inhibitors has been actively pursued with the aim to develop therapeutics for the treatment of diabetes and the other carbohydrate mediated diseases. As a method for the discovery of new novel inhibitors of $\alpha$-glucosidase, we have addressed the performance of the computer-aided drug design protocol involving the homology modeling of $\alpha$-glucosidase and the structure-based virtual screening with the two docking tools: FlexX and the automated and improved AutoDock implementing the effects of ligand solvation in the scoring function. The homology modeling of $\alpha$-glucosidase from baker’s yeast provides a high-quality 3-D structure enabling the structure-based inhibitor design. Of the two docking programs under consideration, AutoDock is found to be more accurate than FlexX in terms of scoring putative ligands to the extent of 5-fold enhancement of hit rate in database screening when 1% of database coverage is used as a cutoff. A detailed binding mode analysis of the known inhibitors shows that they can be stabilized in the active site of $\alpha$- glucosidase through the simultaneous establishment of the multiple hydrogen bond and hydrophobic interactions. The present study demonstrates the usefulness of the automated AutoDock program with the improved scoring function as a docking tool for virtual screening of new $\alpha$-glucosidase inhibitors as well as for binding mode analysis to elucidate the activities of known inhibitors.

• International Journal of Aeronautical and Space Sciences
• /
• v.17 no.2
• /
• pp.204-213
• /
• 2016

A differential game theory based approach is used to develop an automated maneuver generation algorithm for Within Visual Range (WVR) air-to-air combat of unmanned combat aerial vehicles (UCAVs). The algorithm follows hierarchical decisionmaking structure and performs scoring function matrix calculation based on differential game theory to find the optimal maneuvers against dynamic and challenging combat situation. The score, implying how much air superiority the UCAV has, is computed from the predicted relative geometry, relative distance and velocity of two aircrafts. Security strategy is applied at the decision-making step. Additionally, a barrier function is implemented to keep the airplanes above the altitude lower bound. To shorten the simulation time to make the algorithm more real-time, a moving horizon method is implemented. An F-16 pseudo 6-DOF model is used for realistic simulation. The combat maneuver generation algorithm is verified through three dimensional simulations.