An IS Student’s Worst Nightmare: Programming Courses

IS students continue to struggle to complete the programming courses often required in their course of study. In this research-in-progress, we describe how IS educators can learn about the predictors of success in programming courses and translate that knowledge into better advising for their IS students. We plan to administer an open-ended survey to IS educators, asking them what factors they believe predict success in programming principles courses. Based on their responses, we will determine if IS educator perceptions of variables predicting success in programming courses match the realities discussed in previous research. Then we plan to develop a set of guidelines so that IS educators can translate that knowledge into better advising for IS students

Correlated Factors of Success in Information Systems: Personality, Creativity, and Academic Achievement

This paper describes a research project that explores the factors that contribute to success in the undergraduate information systems major. Personality factors, creativity factors, demographic factors, and cognitive ability factors are included in the analyses. Several hundred current students, grouped as new majors and as graduating seniors, are included in the study. This paper describes the justification for the study and the research design. Some preliminary results are presented showing the personality factors of the sample. More complete results will be presented at the conference

Predicting Student Failure in an Introductory Programming Course with Multiple Back-Propagation

One of the most challenging tasks in computer science and similar courses consists of both teaching and learning computer programming. Usually this requires a great deal of work, dedication, and motivation from both teachers and students. Accordingly, ever since the first programming languages emerged, the problems inherent to programming teaching and learning have been studied and investigated. The theme is very serious, not only for the important concepts underlying computer science courses but also for reducing the lack of motivation, failure, and abandonment that result from students frustration. Therefore, early identification of potential problems and immediate response is a fundamental aspect to avoid student’s failure and reduce dropout rates. In this paper, we propose a machine-learning (neural network) predictive model of student failure based on the student profile, which is built throughout programming classes by continuously monitoring and evaluating student activities. The resulting model allows teachers to early identify students that are more likely to fail, allowing them to devote more time to those students and try novel strategies to improve their programming skills

Correlated Factors of Success: Personality, Creativity and Academic Achievement Among IS Students

Escalating demand for emerging IS personnel and a rapidly changing technological environment currently challenge many academic institutions attempting to attract, retain, and properly prepare the next generation of IS professionals. While in some instances attractive salaries and increased recruiting have attracted more students to the major, many academic programs still struggle with retaining and properly educating tomorrow’s IS employees. With that in mind, this study is designed to take a fresh look at today’s IS student in an attempt to identify some of the more significant factors related to success in the field. Specifically, factors related to personality, creativity, and other student attributes are studied to determine their relationship to a student’s success in the IS major. Results of the effort indicate that while personality type does play a role in the success of students, the aspects of creativity studied here are not significantly related to achievement. Additional analyses provide insight into other characteristics that are related to academic achievement or success in the study of information systems

Factors Affecting Student Performance in Intermediate Programming Courses: A Mixed Method Study

There is increasing demand for computing professionals in the United States and too few college graduates to fill the projected need. While extant research has explored a wide variety of student and course attributes to predict student success in introductory programming courses, similar studies focused on intermediate and advanced courses is lacking. Our study aims to explore and identify student and course attributes impacting student performance in intermediate programming courses. Using mixed methods, we provide insights for instructors and instructional designers in developing courses to facilitate the successful completion of course learning objectives for more students, leading to more students who graduate and are able to fill IT-related roles in the future

Faculty and Industry Conceptions of Successful Computer Programmers

Identifying success criteria for computer programmers can help improve training and development programs in academic and industrial settings. In the present research, we interviewed college faculty members and obtained a list of success criteria for both individual and group programming settings. Then, faculty and industry members rated the importance of these characteristics in each setting. The two settings showed both common and unique success criteria. Shared criteria included being creative and conscientious and enjoying problem solving. Important characteristics found for programming alone included cognitive and technical skills and being introverted. Important characteristics for programming in a group included interpersonal cooperation skills and personal maturity. Faculty and industry agreed on what constituted importance characteristics in both settings. Implications for programmer training and selection are discussed

Computer Programming Aptitude Test as a Tool for Reducing Student Attrition

Submitted to the VTR conference to be held in Rezekne, June 2015The stable trend to lose from one-third to half of students in the first study year of computing studies motivated us to explore, which methods are used to determine in advance such applicants, who have no change to overcome the first study year. Initially, a research about the factors influencing the attrition in Faculty of Computing at the University of Latvia was conducted. The research revealed that the trend of non-beginning studies might indicate the wrong choice of the study field and possible lack of understanding of what is programming by enrolled students (applicants as well as pupils). The study provides the review of the situation with programming aptitude tests in the world, which could serve as one of the solutions to the dropout reduction. An action plan is proposed, which is based on the exploration of students and evaluation of activities already conducted at the Faculty of Computing of the University of Latvia to reduce dropout (School of Young Programmers, Compensative Course in High School Mathematics, Mentoring programs). Moreover, the supplementation of these activities by one of the existing programming attitude tests (or a combination of several tests) or a necessity to develop a new similar test is considered

Computer Programming Aptitude Test as a Tool for Reducing Student Attrition

The stable trend to lose from one-third to half of students in the first study year of computing studies motivated us to explore, which methods are used to determine in advance such applicants, who have no change to overcome the first study year. Initially, a research about the factors influencing the attrition in Faculty of Computing at the University of Latvia was conducted. The research revealed that the trend of non-beginning studies might indicate the wrong choice of the study field and possible lack of understanding of what is programming by enrolled students (applicants as well as pupils).The study provides the review of the situation with programming aptitude tests in the world, which could serve as one of the solutions to the dropout reduction. An action plan is proposed, which is based on the exploration of students and evaluation of activities already conducted at the Faculty of Computing of the University of Latvia to reduce dropout (School of Young Programmers, Compensative Course in High School Mathematics, Mentoring programs). Moreover, the supplementation of these activities by one of the existing programming attitude tests (or a combination of several tests) or a necessity to develop a new similar test is considered

Gender, Computer Access and Use as Predictors of Nigerian Undergraduates’ Computer Proficiency

This study X-rayed the contributions of gender, access to computer andcomputer use to the Nigerian undergraduates’ computer proficiency. Threehundred and fifteen (315) undergraduates from the Faculty of Education ofOlabisi Onabanjo University, Nigeria served as the sample for this study.The instruments used for the data collection were Computer Access andUsage Scale (CAUS) and Computer Proficiency Scale (CPS). The datacollected were analysed using simple percentages, standard deviation,Analysis of Variance and Multiple regression statistics. Meanwhile, thefindings revealed that gender, access to computer and computer usage jointly predicted the student’s computer proficiency. However, gender had the least predictive power of the criterion variable. Recommendations based on the outcome of this study were highlighted in this paper.Keywords: Gender, Computer-access, Computer Use, Undergraduates,Computer Proficienc