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Automatic grading is not a new approach but the need to adapt the latest technology to automatic grading has become very important. As the technology has rapidly became more powerful on scoring exams and essays, especially from the 1990s onwards, partially or wholly automated grading systems using computational methods have evolved and have become a major area of research. In particular, the demand of scoring of natural language responses has created a need for tools that can be applied to automatically grade these responses. In this paper, we focus on the concept of automatic grading of short answer questions such as are typical in the UK GCSE system, and providing useful feedback on their answers to students. We present experimental results on a dataset provided from the introductory computer science class in the University of North Texas. We first apply standard data mining techniques to the corpus of student answers for the purpose of measuring similarity between the student answers and the model answer. This is based on the number of common words. We then evaluate the relation between these similarities and marks awarded by scorers. We consider an approach that groups student answers into clusters. Each cluster would be awarded the same mark, and the same feedback given to each answer in a cluster. In this manner, we demonstrate that clusters indicate the groups of students who are awarded the same or the similar scores. Words in each cluster are compared to show that clusters are constructed based on how many and which words of the model answer have been used. The main novelty in this paper is that we design a model to predict marks based on the similarities between the student answers and the model answer. We argue that computational methods be used to enhance the reliability of human scoring, and not replace it. Humans are required to calibrate the system, and to deal with situations that are challenging. Computational methods can provide insight into which student answers will be found challenging and thus be a place human judgement is required. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we discuss the redesign of a support management system deployed in a small and medium sized enterprise (SME) in the UK. The original system was not fulfilling its needs as it had not captured work practices in a way that was recognizable to the users. The advantages of the redesign included: improved usefulness; improved efficiency and productivity; reduced learning time; improved usability; and increased acceptance among users. The system is used to support complex and distributed cooperative activities taking place in an SME. We evaluated the current system and analysed work practices using a user-centred design and evaluation philosophy. In this paper we discuss how user needs are incorporated into the enhanced design of the support management system. The user-centred design techniques used in this research include interviews, questionnaires, observations and user tests. We present comparative evaluation results that show significant improvement in performance of user tasks using the redesigned support management system. The contribution of this paper is the presentation of a case study to show how a user-centred design and evaluation philosophy can lead to better requirements capture resulting in systems that more accurately capture the users’ conceptual models. [ABSTRACT FROM AUTHOR]