Does choice of programming language affect student understanding of programming concepts in a first year engineering course?

Most undergraduate engineering curricula include computer programming to some degree,introducing a structured language such as C, or a computational system such as MATLAB, or both. Many of these curricula include programming in first year engineering courses, integrating the solution of simple engineering problems with an introduction to programming concepts. In line with this practice, Roger Williams University has included an introduction to programming as a part of the first year engineering curriculum for many years. However, recent industry and pedagogical trends have motivated the switch from a structured language (VBA) to a computational system (MATLAB). As a part of the pilot run of this change,the course instructors felt that it would be worthwhile to verify that changing the programming language did not negatively affect students’ ability to understand key programming concepts. In particular it was appropriate to explore students’ ability to translate word problems into computer programs containing inputs, decision statements, computational processes, and outputs. To test the hypothesis that programming language does not affect students’ ability to understand programming concepts, students from consecutive years were given the same homework assignment, with the first cohort using VBA and the second using MATLAB to solve the assignment. A rubric was developed which allowed the investigators to rate assignments independent of programming language. Results from this study indicate that there is not a significant impact of the change in programming language. These results suggest that the choice of programming language likely does not matter for student understanding of programming concepts. Course instructors should feel free to select programming language based on other factors, such as market demand, cost, or the availability of pedagogical resources

Teaching methods are erroneous: approaches which lead to erroneous end-user computing

If spreadsheets are not erroneous then who, or what, is? Research has found that end-users are. If end-users are erroneous then why are they? Research has found that responsibility lies with human beings' fast and slow thinking modes and the inappropriate way they use them. If we are aware of this peculiarity of human thinking, then why do we not teach students how to train their brains? This is the main problem, this is the weakest link in the process: teaching. We have to make teachers realize that end-users are erroneous because of the erroneous teaching approaches to end-user computing. The proportion of fast and slow thinking modes is not constant, and teachers are mistaken when they apply the same proportion in both the teaching and end-user roles. Teachers should believe in the incremental nature of science and have high self-efficacy to make students understand and appreciate science. This is not currently the case in ICT and CS, and it is high time fundamental changes were introduced.Comment: 14 pages, 7 figures & table

Accounting Information Systems (AIS) Course Design: Current Practices and Future Trajectories

The accounting information systems (AIS) course is a core component of most accounting programs, but what it typically covers and how it’s typically taught is as varied as the number of instructors. As the AACSB Standard A7 indicates: “accounting degree programs include learning experiences that develop skills and knowledge related to the integration of information technology in accounting and business”. In this panel presentation, we looked at the approach of five experienced AIS instructors and compared and contrasted them. We highlight lessons learned and best practices

Punch Cards to Python: A Case Study of a CS0 Core Course

There is an immense interest in teaching computer science concepts - and programming specifically - to everyone. The United States Military Academy at West Point has required every student, regardless of major, to pass a computer science zero (CS0) course for the last 50 years: From punch cards to Python. We present a history of our CS0 course and the lessons learned from the most recent redesign of the course. We review the last decade of student assessments and how they influenced the latest iteration. We contrast the expectations of students in a CS0 course with those in a CS1 course. We discuss the national efforts to make CS accessible to all and explore the challenges unique to a CS0 course. We demonstrate similarities between our course and the Advance Placement CS Principles and show where differences are justified. We review the relevant pedagogical research for CS0 and present lessons learned over multiple iterations of the course. Based on our current course review and implementation, we believe that Computer Science for everyone is attainable and relevant to the needs of every student