Informatics in Education

The choice of programming language for education is an intensely debated topic. On the one hand, the programming language is supposed to be relevant in that its organisation, structures, and paradigms adhere to current standards and best practices in industry and academia. On the other hand, the programming language is expected to be simple, that is, easy to use and, of course, easy to learn. This increasingly means that we need an introduction to concepts shaped by a long history without all the historic baggage.

Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student programming behavior can be modeled as a Markov process. The resulting transition matrix can then be used in machine learning algorithms to create clusters of similarly behaving students. We describe in detail the state machine used in the Markov process and how to compute the transition matrix. We compute the transition matrix for 665 students and cluster them using the k-means clustering algorithm. We choose the number of cluster to be three based on analysis of the dataset. We show that the created clusters have statistically different means for student prior knowledge in programming, when measured on a Likert scale of 1-5.

C++ is the most commonly used language in introductory and intermediate programming courses in Bulgarian universities. In recent years this language has developed greatly. Its abstractions are more flexible and affordable than ever before. Such great number of changes are related to the launch of the new standard (known as C++11) that we have grounds to consider it even a new language. It is inevitable to reflect all these changes in training courses and this prompted us to consider not only some updating of academic curricula but also a comprehensive reorganization of our programming courses. So, in this article we share our successes and difficulties in this direction.

This paper discusses some difficulties in teaching introductory courses to programming, paying particular attention to their mathematical nature. We consider some aspects, which have not been commented in detail in textbooks and often neglected by course outlines and schedules. Some of these are constructing complex conditions, exceeding array bound, calculating infinite series in conjunction with recursion, etc. We believe that those topics and accompanying notes along with appropriate teaching methodology could be and should be incorporated into introductory programming courses.

The goal of this literature study is to give some preliminary answers to the questions that aim to uncover the Pedagogical Content Knowledge (PCK) of Informatics Education, with focus on Programming. PCK has been defined as the knowledge that allows teachers to transform their knowledge of the subject into something accessible for their students. The core questions to uncover this knowledge are: what are the reasons to teach programming; what are the concepts we need to teach programming; what are the most common difficulties/misconceptions students encounter while learning to program; and how to teach this topic. Some of the answers found are, respectively: enhancing students' problem solving skills; programming knowledge and programming strategies; general problems of orientation; and possible ideal chains for learning computer programming. Because answers to the four questions are in a way not connected with each other, PCK being an unexplored field in Informatics Education, we need research based efforts to study this field.