Using Ontology-based Information Extraction for Subject-based Auto-grading

The procedure for the grading of students’ essays in subject-based examinations is quite challenging particularly when dealing with large number of students. Hence, several automatic essay-grading systems have been designed to alleviate the demands of manual subject grading. However, relatively few of the existing systems are able to give informative feedbacks that are based on elaborate domain knowledge to students, particularly in subject-based automatic grading where domain knowledge is a major factor. In this work, we discuss the vision of subject-based automatic essay scoring system that leverages on semiautomatic creation of subject ontology, uses ontology-based information extraction approach to enable automatic essay scoring, and gives informative feedback to students

Design and Assessment for Hybrid Courses: Insights and Overviews

Technology is influencing education, providing new delivery and assessment models. A combination between online and traditional course, the hybrid (blended) course, may present a solution with many benefits as it provides a gradual transition towards technology enabled education. This research work provides a set of definitions for several course delivery approaches, and evaluates five years of data from a course that has been converted from traditional face-to-face delivery, to hybrid delivery. The collected experimental data proves that the revised course, in the hybrid delivery mode, is at least as good, if not better, than it previously was and it provides some benefits in terms of student retention

Hybrid Course Delivery: Impact on Learning and Assessment

Technology is influencing education, blurring the boundaries of delivery modes. A combination between online and traditional teaching style, the hybrid/blended course, may present a solution with many benefits. This paper provides definitions of the different delivery approaches, and then evaluates four years of data from a course that has been converted from traditional face-to-face delivery, to a hybrid system. It is determined that the revised course, in hybrid delivery mode, is at least as good, if not better, than it previously was

Automatic Code Homework Grading Based on Concept Extraction

E-learning is taking more roles in the current methods of education. The automatic grading and assessment play a major role in both e-learning and traditional education as a method to reduce educational expenses and relief instructors from some of the lengthy tasks such as grading. In this paper, automatic grading for software code assignments or homework is described. A tool is developed to automatically grade students\u27 code assignments. Concepts or code from Students\u27 answers are first parsed. Key abstractions and keywords are extracted from students\u27 assignments and compared with typical or expected answers. Weights are given to code keywords by the instructor based on their value and importance in the overall answer. Relating this grading with code plagiarism, similarities are also measured between students\u27 assignments and an Euclidean distance method is developed and calculated between each assignment with all other assignments. Results showed that automatic grading for code assignments can be automated due to the nature of expected answers where grader can set and expect a fixed number of possible keywords in each answer. Such formality may not exist for several other types of essay questions

Automated essay grading: an evaluation of four conceptual models

Automated essay grading has been proposed for over thirty years. Only recently have practical implementations been constructed and tested. This paper describes the theoretical models for four implemented system described in the literature, and evaluates their strengths and weaknesses. All four models make use of comparisons with one or many model answer documents that have been previously assessed by human markers. One hybrid system that makes use of some linguistic features, combined with document characteristics, is shown to be a practical solution at present. Another system that makes use of primarily linguistics features is also shown to be effective. An implementation that ignores linguistic and document features, and operates on the ?bag of words? approach, is then discussed. Finally an approach using text categorisation techniques is considered

Service-oriented flexible and interoperable assessment: towards a standardised e-assessment system

Free-text answers assessment has been a field of interest during the last 50 years. Several free-text answers assessment tools underpinned by different techniques have been developed. In most cases, the complexity of the underpinned techniques has caused those tools to be designed and developed as stand-alone tools. The rationales behind using computers to assist learning assessment are mainly to save time and cost, as well as to reduce staff workload. However, utilising free-text answers assessment tools separately form the learning environment may increase the staff workload and increase the complexity of the assessment process. Therefore, free-text answers scorers have to have a flexible design to be integrated within the context of the e-assessment system architectures taking advantages of software-as-a-service architecture. Moreover, flexible and interoperable e-assessment architecture has to be utilised in order to facilitate this integration. This paper discusses the importance of flexible and interoperable e-assessment. Moreover, it proposes a service-oriented flexible and interoperable architecture for futuristic e-assessment systems. Nevertheless, it shows how such architecture can foster the e-assessment process in general and the free-text answers assessment in particular

A robust methodology for automated essay grading

None of the available automated essay grading systems can be used to grade essays according to the National Assessment Program – Literacy and Numeracy (NAPLAN) analytic scoring rubric used in Australia. This thesis is a humble effort to address this limitation. The objective of this thesis is to develop a robust methodology for automatically grading essays based on the NAPLAN rubric by using heuristics and rules based on English language and neural network modelling