Teaching How to Think Like a Programmer

This chapter aims to provide a general description of the preferred pedagogical approaches for the delivery and practice of computer science education based on a review of the literature. Pedagogical approaches mainly used in the teaching of computer science are unplugged activities, robotics programming, block-based or initial programming environments and cross-curricular activities. The preference of these pedagogical approaches varies according to the learners' age and level. Whilst all of these approaches can be used for all ages, some are aimed more at the beginner level than others. The benefits of using each of these approaches will be discussed in this chapter by way of considering educational tips.

Novice Programming Environments

In 2011, the author published an article that looked at the state of the art in novice programming environments. At the time, there had been an increase in the number of programming environments that were freely available for use by novice programmers, particularly children and young people. What was interesting was that they offered a relatively sophisticated set of development and support features within motivating and engaging environments, where programming could be seen as a means to a creative end, rather than an end in itself. Furthermore, these environments incorporated support for the social and collaborative aspects of learning. The article considered five environments—Scratch, Alice, Looking Glass, Greenfoot, and Flip—examining their characteristics and investigating the opportunities they might offer to educators and learners alike. It also considered the broader implications of such environments for both teaching and research. In this chapter, the author revisits the same five environments, looking at how they have changed in the intervening years. She considers their evolution in relation to changes in the field more broadly (e.g., an increased focus on “programming for all”) and reflects on the implications for teaching, as well as research and further development.

Fostering Computational Thinking and Creativity in Early Childhood Education

This chapter focuses on the design and implementation of coding, programming, and robotics activities in real-world classroom conditions in early childhood education that foster computational thinking and creativity. The study extends the author's experience in designing learning environments through experimentation, exploration, expression, construction, meaning negotiation, and collaboration. The author tries to gain further insight into the potential of implementing unplugged activities, robotics systems, and programming environments in the context of multi-disciplinary, hands-on activities. Using a variety of tools, strategies, and methods as well as qualitative approaches employed in case studies of classroom practice during Afternoon Robotics Club courses, the findings highlight the overall process indicating some special features that contribute to or cause difficulty in the formation of an effective learning experience. Special issues of interest, key aspects, solutions, and recommendations, as well as future research directions, are discussed.

Developing mobile software for foreign language learning

Problem. The subject of the study is an interactive mobile application in Java. To perform this work, the following tasks were set: analysis of programming environments and languages of development; analysis of methods for developing the logic and interface of the mobile application; development of an interactive mobile application in Java. Goal. The aim of the work is to develop a mobile application for learning a foreign language for the Android operating system, whose interface and logic will be modern, user-friendly and accessible to users. Methodology. The general concept of a mobile application for learning a foreign language is as follows: learning a foreign language offline, versatile learning (words, grammar), the presence of a motivational unit, simple design. The object of research is the process of building an interactive mobile application in Java for the Android operating system. In the course of the work, a study of programming languages and environments for the development of mobile applications was conducted. Programming languages such as: Java, C ++, C # were considered. Programming environments such as Android Studio, NetBeans and Eclipse were also analyzed. As a result, the Java programming language and Android Studio programming environment were chosen for the development of the mobile application. Two types of markup were selected: LinearLayout; ConstraintLayout. Results. The mobile application for learning a foreign language for the Android operating system was developed in Android Studio in two programming languages: Java (logic) and XML (interface). The aim to provide the application with modern interface and logic, to make it user-friendly and accessible to users was completed. Originality. Contribution has been made to the field of using smartphones for learning foreign languages. The sphere of using smartphones has been expanded with the use of all modern trends to the creation of mobile applications for learning foreign languages. Practicalvalue. Considering that the number of potential users will only increase in the nearest future, the developed mobile application for learning a foreign language is an ideal platform for educating those who want to develop and learn foreign languages for themselves, as well as for work, communication and travel.

A Detailed Item Response Theory Analysis of Algorithms and Programming Concepts in App Inventor Projects

Teaching computing in K-12 is often introduced focusing on algorithms and programming concepts using block-based programming environments, such as App Inventor. Yet, learning programming is a complex process and novices struggle with several difficulties. Thus, to be effective, instructional units need to be designed regarding not only the content but also its sequencing taking into consideration difficulties related to the concepts and the idiosyncrasies of programming environments. Such systematic sequencing can be based on large-scale project analyses by regarding the volition, incentive, and opportunity of students to apply the relevant program constructs as latent psychometric constructs using Item Response Theory to obtain quantitative ‘difficulty’ estimates for each concept. Therefore, this article presents the results of a large-scale data-driven analysis of the demonstrated use in practice of algorithms and programming concepts in App Inventor. Based on a dataset of more than 88,000 App Inventor projects assessed automatically with the CodeMaster rubric, we perform an analysis using Item Response Theory. The results demonstrate that the easiness of some concepts can be explained by their inherent characteristics, but also due to the characteristics of App Inventor as a programming environment. These results can help teachers, instructional and curriculum designers in the sequencing, scaffolding, and assessment design of programming education in K-12.

Visualization of Control Processes a nd Code Validation

The article contains an overview of articles related to the description of control process visualization. It provides short information on how to visualize the production line based on two programming environments: Factory IO and Inventor together with Matlab/Simulink. The analysis of these two environments concerns control of a virtual 3D object from a real PLC. Both virtual production line projects are based on control from the S7-1214 DC/DC/DC controller. Currently, there is a need to validate the program code or control process which has been done using several commercially available programs.

Learning From Errors: Exploring the Effectiveness of Enhanced Error Messages in Learning to Program

Error messages provided by the programming environments are often cryptic and confusing to learners. This study explored the effectiveness of enhanced programming error messages (EPEMs) in a Python-based introductory programming course. Participants were two groups of middle school students. The control group only received raw programming error messages (RPEMs) and had 35 students. The treatment group received EPEMs and had 33 students. During the class, students used an automated assessment tool called Mulberry to practice their programming skill. Mulberry automatically collected all the solutions students submitted when solving programming problems. Data analysis was based on 6339 student solutions collected by Mulberry. Our results showed that EPEMs did not help to reduce student errors or improve students’ performance in debugging. The ineffectiveness of EPEMs may result from reasons such as the inaccuracy of the interpreter’s error messages or students not reading the EPEMs. However, the viewpoint of productive failure may provide a better explanation of the ineffectiveness of EPEMs. The failures in coding and difficulties in debugging can be resources for learning. We recommend that researchers reconsider the role of errors in code and investigate whether and how failures and debugging contribute to the learning of programming.

Crowdsourced Evaluation of Robot Programming Environments: Methodology and Application

Industrial robot programming tools increasingly rely on graphical interfaces, which aim at rendering the programming task more accessible to a wide variety of users. The usability of such tools is currently being evaluated in controlled environments, such as laboratories or companies, in which a group of participants is asked to carry out several tasks using the tool and then fill out a standardized questionnaire. In this context, this paper proposes and evaluates an alternative evaluation methodology, which leverages online crowdsourcing platforms to produce the same results as face-to-face evaluations. We applied the proposed framework in the evaluation of a web-based industrial robot programming tool called Assembly. Our results suggest that crowdsourcing facilitates a cost-effective, result-oriented, and reusable methodology for performing user studies anonymously and online.