Investigating Students ’ Achievements in Computing Science Using Human Metric

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


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, www.ijacsa.thesai.orgthere is not enough empirical evidence as to the role of personality traits in students' academic achievements especially at the tertiary level.This study is a contribution to bridge the gap in literature regarding academic achievements in computing sciences using the MBTI tool.

B. Study Ovjectives
The main objective of this study is to investigate if personality traits do affect academic achievements in computing science.The study also investigates the motivating factors affecting the choice of a career in Computing Science and the reading habits which influence academic achievements in computing science

C. Research Questions
The following research questions are investigated in this study.
 What are the factors that influence students choice of course of study in Computing Science at the University of Botswana?
 Which study habits influence students academic success in the Computing Science at the University of Botswana?
 Which personality traits are high achievers in Computing Science at the University of Botswana?

D. Research Hypotheses
The following hypotheses are tested in this study: H0: Introverts will have higher academic achievements than extroverts H1: Introverts will not have higher academic achievements than extroverts H0: Sensors will have higher academic achievements than intuitives H1: Sensors will not have higher academic achievements than intuitives H0: Thinkers will have higher academic achievements than feelers H1: Thinkers will not have higher academic achievements than feelers H0: Judges will have higher academic achievements than Perceivers H1: Judges will not have higheracademic achievements than perceivers H0: There is significant correlation between personality traits and academic achievements H1: There is no correlation between personality traits and academic achievements.
The rest of this paper is divided into 6 sections.Section 2 is a review of relevant literature.Section 3 explains the research methodology.Section 4 presents the result of this study with appropriate discussion.Section 5 is the conclusion while section 6 is the list of references II.LITERATURE REVIEW Okike [2] investigated the major personality indicators of students Systems Analysts and Designers at the University of Botswana and their performances at System Analysis and Design practical and theoretical examinations.The study suggests that the best achievers in Systems Analysis and Design are students who possess the personality types of Extrovertism ( E ), iNtuition (N), Feeling (F), Judging (J), Thinking (T), Introversion (I), and Sensing (S).The highest passes in the overall Systems Analysis and Design examination are students with the combined personality traits of Introversion iNtuition Feeling Judging (INFJ), Introversion iNtuition Thinking Judging (INTJ), Extroversion iNtuition Thinking Judging (ENTJ), ExtroversioniNtuition Feeling Judging (ENFJ), and Introversion Sensing Thinking Judging (ISTJ).
Capretz and Ahmed [3] studied the connections between personality traits and the process of software development.The authors mapped soft skills and personality traits to the main stages of the software life cycle.They claim that assigning people with personality types best suited to particular stages of the software life cycle increases the chances of project's successful outcome Omar and Syed-Abdullah [4] applied rough setsin identifying effective personality type in software engineering teams.It was suggested that a balance of personality types Sensing (S), iNtuition (N), Thinking and Feeling (F) assisted teams in achieving higher software quality.Extroverts ( E) in the team also had impacts on team performance.Da Cunha and Greathead [5] investigated if a specific personality type is correlated with performance on code review task.In their investigation, the researchers measured personality with the Myers Briggs Type indicator(MBTI) while the reviewed code was a Java based 282 lines of code.The subjects of study were 64 second year undergraduate student at New Castle University, UK.To examine the possible links with MBTI type and code review ability, the researchers computed some correlations between task score and each bipolar factor Extrovert-Introvert (EI), Sensing-iNtuition(SN), Thinking-Feeling(TF) and Judging-Perceiving(JP).The result of this study indicated that only a single bipolar within the SN bipolar significantly correlated with code review task, suggesting that people more intuitively inclined performed better than others on code review.
Bishop-Clark and Wheeler [6] investigated the Myers-Briggs personality type and its relationship to computer programming.Specifically, the study sought to know if college students with certain personality types performed better than others in an introductory programming course.The researchers first did a pilot study with 24 students and a follow up study with 114 students.The result of this study showed that sensing students performed significantly better than intuition students in programming assignments while judging students performed better than perception students on computer programs although the results were not significant statistically.In addition, they also noted that although personality may not be an important factor in a student's decision to drop a course, it may influence a student's www.ijacsa.thesai.orgevaluation of a class.The researchers concluded that the act of programming (creating and debugging programs) is a feat on its own and should be distinct from scores on written programs.
Similarly, Irani, Telg, Scherler, and Harrington [7] studied the relationship between personality type and distance education students course perception and performance using 39 graduate students of distance education.Perceptions of instructional technique used by the distance instructor were strongly correlated to the students' course grade and overall grade point average for the following personality types: extravert, introvert, intuitive, sensing, feeling, and judging.Of the MBTI type preferences, only thinking and perceiving types showed no significant correlations between course perceptions and performance indicators.Findings from this study indicate that performance outcomes for distance education students may be closely related to course perceptions as a function of personality type preference.Perceptions of instructional technique used by the distance instructor were strongly correlated to the students' course grade and overall grade point average for the following personality types: extravert, introvert, intuitive, sensing, feeling, and judging.
Turley and Bieman [8] studied the attributes of individual software developers in order to identify their professional competencies using biography data and Myers-Briggs Type Indicator (MBTI) and concluded that there was no simple predictor of performance.Although experience variables in their study were related to performance, it could only predict classification of exceptional and non exceptional of 63% of the subjects.
Chung [9] studied the cognitive abilities in computer programming using 523 Form Four secondary school students in Hong Kong.Test administered to the students included mathematics, space, symbols, hidden figures and programming ability.Results of the study suggest that performance in mathematics and spatial tests were significant predictors in programming ability.Thinking Judging (ENTJ).The MBTI tool classified the 60 students according to their individual personality traits.Furthermore, additional questionnaires were designed in order to gather information from the students concerning what motivated their choice of programme of study at the University of Botswana (UB): BSC 204, BSC 205, BSC 280, BIS 230 and BED 240; as well as how they study in order to understand the various courses they take at the university.In order to measure achievement in the various courses taken by a student, a model was used as follows:

III. STUDY METHODOLOGY
Where represents a dependent variable, and the independent variables are represented as . The dependent variable in this study is the achievement (performance or score) in each course taken by a student; the independent variables are the various personality traits exhibited by a student in terms of the level (in percentages) of Extroversion, Introversion, Thinking, Feeling, Sensing, iNtuition, Judging and Perceiving.
The variables which influenced students choice of programme of study: parental influence, personal desire to be in the computing profession, students ability in science and mathematics, students ability in science without mathematics, other reasons; and the variables which indicate student study habit : reading of text books, reading only class notes, reading from online lecture notes (module), use of internet materials, use of university library to read text books and other relevant materials, none use of university library, going to university library to read personal materials; reading class notes, text books and online lecture notes; reading class notes and online lecture materials only because student don't have enough money to purchase recommended text; any other reasons were also considered as independent variable.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.

A. Model Fitting
The model was tested for fitness using regression statistic.The result is shown in Table 1 and Table 2.In Table 1, the R square value of 0.431implies that about 43.1% of the predictors explain the variations in the dependent variable.This means that the personality traits contribute to academic achievements of computing science students.www.ijacsa.thesai.org  1, it is clear that 43.1% of the independent variables (predictors) explains the variation in the dependent variable (average score or achievement).This suggests that more information on some other variables are needed to predict achievement in the model

B. Analysis of Students by Personality types
Table 3 below shows the frequency distribution of students by personality types.

C. Factors Influencing Students choice of Coputing career
Table 4 shows the frequency distribution of students' response to their motivations for choice of course of studyin computing science.4, the desire to be in the computing profession is the highest motivating factor (76.6%) in choosing a career in computing science followed by students' ability in science and Mathematics (33.3%).Factors such as parental influence (3.3%), being good in science but not in Mathematics (3.3%) do not have a strong influence on students choice of course of study in Computing science.This suggests that ability in Mathematics is a significant predictor of a students probability of choosing a career in the Computing Sciences.Chung [9] also suggested that ability in Mathematics and spartial tests were significant predictors of programming ability and hence programming as a career.Hence, achievements in Mathematics could enhance achievements in Computing Science.

D. Students Study Habits in Computing Science
Table 5 presents students' study habit and understanding their course lectures in computing science at the University of Botswana.
From Table 5, reading class notes, text books and materials posted by lecturers on Moodle (76.6%) and use of Internet related sources (58.3%) are the main study habits of computing science students at the University of Botswana.In terms of students' use of the University library, 33.3 % of computing science students use the library in order to study their personal materials, 23.3% use library book materials while 6.7% of computing science students do not use the library.Furthermore, it is interesting to note that students' use of Internet based sources (58.3%) is higher than students use of the University library to study personal materials (33.3%), and to use library book materials (23.3%).This suggests that Computing Science students spend more time using Internet based sources than using the University library.This implies that computing science students use the laboratories more than the library.Capretz and Ahmed [3] on the other hand identified thesoft skills requirements of Systems Analysts, Software Designers, Programmers, Testers and Maintenance engineers and subsequently mapped the skills unto personality types.Some of the identified soft skills include communication skills, interpersonal skills, ability to work independently, being an active listener, having strong analytical and problem solving skills, being open and adaptable to changes, innovative skills, organizational skills, acute attention to details, fast listening skills and team playing skills:

G. Discussion
A careful comparison of Tables 3 and 6

H. Conclusion
In conclusion, the desire to be in the Computing profession is the essential motivating factor in choosing a career in the Computing Sciences (research question 1).
The main study habits which influence students achievement in Computing Science are reading class notes, text books, materials posted on Moodle by lecturers and use of Internet related sources (research question 2).The use of Internet related sources imply that Computing Science students spend more time in laboratories with computers on Internet facilities than in than library reading book sources.Distinctive personality types may enhance academic achievement as well as performance in certain tasks.It is suggested that the best achievers from this study are students who possess the combine personality types ENFJ, INFJ, ENTJ, INTJ (research question 3).Therefore, study concludes that personality traits do affect achievement in Computing Science and especially the traits of Extroversion, Introversion, iNtuition, Feeling, Thinking, Judging, and probably Sensing and Perceiving.

F
. Comparisons Between Personality characteristics and Computing Characteristics a) Characteristics of various types From [2], the following characteristics of the various personality types were identified:  Extraversion (E): Focus on the outer world  Introversion (I): Focus own inner world  Feeling (F): When making decisions, they look at the people and special circumstances  iNtuition (N) : Interpret and add meaning to information they taken in  Judging (J): In dealing with outside, they get things decided  Thinking (T): When making decisions they first look at the logic and consistency www.ijacsa.thesai.orgb) Essential skills of Computing Scientists Grimson [10] identified four skill set required to study Computer Science namely:  Computational thinking skill  Understanding Code  Understand abilities and limits  Map Problem into computation.

TABLE VI .
ACHIEVEMENT SUMMARY OF NUMBER OF PASSES BY PERSONALITY TRAITS