(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 5, No. 4, 2014 180 | Page www.ijacsa.thesai.org Investigating Students’ Achievements in Computing Science Using Human Metric Ezekiel U. Okike Department of Computer Science University of Botswana Gaborone, Botswana Abstract—This study investigates the role of personality traits, motivation for career choice and study habits in students’ academic achievements in the computing sciences. A quantitative research method was employed. Data was collected from 60 computing science students using the Myer Briggs Type indicator (MBTI) with additional questionnaires. A model of the form                        was used, where   represents a dependent variable,                       the independent variables. Data analysis was performed on the data using the Statistical Package for the social sciences (SPSS). Linear regression was done in order to fit the model and justify its significance or none significance at the 0.05 level of significance. Result of regression model was also used to determine the impact of the independent variable on students ’ performance. Results from this study suggest that the strongest motivator for a choice of career in the computing sciences is the desire to become a computing professional. Students’ achievements especially in the computing sciences do not depend only on students temperamental ability or personality traits, motivations for choice of course of study and reading habit, but also on the use of Internet based sources more than going to the university library to read book materials available in all areas Keywords—academic achievement; personality traits; computing science; study habits I. INTRODUCTION Achievements in educational terms refer to academic achievement. It is the performance of a student in his studies at school. Student’s achievement in school subjects such as Mathematics, Physics, and Computer Science is a measure of the overall academic ability and knowledge of a subject of study. Although there exists a number of achievement studies in the subject areas like Mathematics, Physics, Chemistry and Biology, this is not the case in Computer Science especially at the university level. The need to measure students achievement in computing science among other things include the following: to ensure that students meet their set academic goals, to ensure students meet graduation requirements, to serve as a means to validate teaching effectiveness, and to serve as a means to identify outstanding students for recognition. Every university takes as priority the learning standards and outcomes of her students. Hence universities adopt different approaches to measuring students academic achievement. A common approach used by many universities to measure academic achievement of students is by means of Continuous Assessment (CA), and final examination. In this regard, the CA mark could be between 30%-40% while the final examination score could be 60%-70%. Furthermore, universities have tools that help in ascertaining how well a subject has been taught by a lecturer and how well the students understood and mastered the course content. An example of this tool at the University of Botswana is the Students Evaluation of Courses and Teaching (SECAT) tool. Using this tool, the course, the student and the course lecturer are evaluated by the students through an automated questionnaire which reports its analysis as soon as students complete the SECAT questionnaires. Although the use of this tool is a good way to measure how well a course has been taught by a lecturer, and how well the students have mastered the course content, there remains a gap to be investigated between the students inherent personality trait and students achievement in each course of study. This paper investigates students achievement in Computing Science using 60 third year students of Computer Science (CS), Information Technology (IT), Computing with Finance, and Information System (IS) at the University of Botswana, Gaborone. This study is motivated by the interest to contribute to the empirical body of knowledge about using a human metric tool such as the Myers Briggs Type Indicator (MBTI) as a predictor of students’ achievement especially in the Computing Sciences. The term Computing Science encompasses Computer Science (CS), Computer Engineering (CE), Software Engineering (SE), Information Technology (IT), and Information Systems (IS). For the purpose of this study, courses offered by students in the Department of Computer Science leading to the award of Bachelor of Computer Science (BSC 280), Bachelor of Information Technology (BSC 204), and Bachelor of Computing with Finance (BSC 205) and Bachelor of Information Systems (BIS 230) are considered. All courses offered in these programmers cover hardware and software courses representing the four subdivisions of Computing Science as defined by the educational curriculum committee of the professional body in charge of computing education worldwide [1]. A. Problem Statement The use of a human metric tool such as the Myers Brigg Type Indicator (MBTI) to predict academic achievement in the computing sciences has not been widely reported. In effect,