The development of a user classification model for a multi-cultural society

Abstract

During the last ten years, a number of computerised testing systems have been developed without considering the users' level of computer proficiency. Students at the University of Port Elizabeth come from a diverse background, both in home language and population group. The level of computer expertise of these students is diverse, and this may influence the test scores they obtain in computerised tests. In this study, various factors were found to be significant indicators of performance on computer-based tasks. These factors include previous computer and software experience, attitude towards computers, self-perceived ability to work with computers, contact with technology, gender, and home language. This paper discusses the development of a user classification model to classify students into three user groups, namely novice, intermediate and expert. Two methods were used for classification. The first followed a quantitative approach to user modeling and required users to perform simple computer-based tasks. The second method was qualitative in nature and used a questionnaire to assess the factors that were found to be significant indicators of performance in human-computer interaction. The hypothesis is that a user classification model can be developed for the first year student population at the University of Port Elizabeth. During the last ten years, a number of computerised testing systems have been developed without considering the users' level of computer proficiency. Students at the University of Port Elizabeth come from a diverse background, both in home language and population group. The level of computer expertise of these students is diverse, and this may influence the test scores they obtain in computerised tests. In this study, various factors were found to be significant indicators of performance on computer-based tasks. These factors include previous computer and software experience, attitude towards computers, self-perceived ability to work with computers, contact with technology, gender, and home language. This paper discusses the development of a user classification model to classify students into three user groups, namely novice, intermediate and expert. Two methods were used for classification. The first followed a quantitative approach to user modeling and required users to perform simple computer-based tasks. The second method was qualitative in nature and used a questionnaire to assess the factors that were found to be significant indicators of performance in human-computer interaction. The hypothesis is that a user classification model can be developed for the first year student population at the University of Port Elizabeth.