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• Removing the burden of syntax: developing computational thinking and algorithmic skills of STEM students

  29-49

  Ádám Gulácsi

  Maria Csernoch

  Views:

  15

  In higher education, solving programming exercises using a high-level programming language is a standard approach for developing computational thinking and algorithmic skills. However, this method has its limitations: learning the syntax of a high-level programming language puts an extra cognitive load on students, preventing them from focusing on problem-solving. Furthermore, computational thinking is not limited to programming: STEM students can benefit more from solving problems within their own discipline, in different environments. This practical article proposes a collection of unplugged, semi-unplugged and plugged-in alternatives that can be used to develop the computational thinking and algorithmic skills of students.

  Subject Classification: 97P99

• A computational thinking problem-thread for grade 7 students and above from the Pósa method

  101-110

  Eszter Bóra

  Views:

  322

  Lajos Pósa has been developing his “learning through discovery” (Győri & Juhász, 2018) method since 1988. His weekend math camps are focused on fostering problem-solving skills and high-level mathematical-thinking skills in gifted students from grades 7 to 11. One of the core aspects of the method is the structure of the problems, all problems are part of a complex, intertwined, and rich network. In this article we analyze a computational thinking problem-thread and its role in the camps’s network of problems (Gosztonyi, 2019), and show some aspects of the method. The insights gained using this method can be useful in other contexts. The possible adaptation of the method to secondary and high schools is briefly discussed as well.

  Subject Classification: 97D40

• Teaching puzzle-based learning: development of transferable skills

  245-268

  Nickolas Falkner

  Raja Sooriamurthi

  Zbigniew Michalewicz

  Views:

  408

  While computer science and engineering students are trained to recognise familiar problems with known solutions, they may not be sufficiently prepared to address novel real-world problems. A successful computer science graduate does far more than just program and we must train our students to reach the required levels of analytical and computational thinking, rather than hoping that it will just 'develop'. As a step in this direction, we have created and experimented with a new first-year level course, Puzzle-based Learning (PBL), that is aimed at getting students to think about how to frame and solve unstructured problems. The pedagogical goal is increase students' mathematical awareness and general problem solving skills by employing puzzles, which are educational, engaging, and thought provoking. In this paper we continue sharing our experiences in teaching such a course. Whereas a brief discussion on our pedagogical objectives were covered in the first paper together with the material of the first of two lectures on pattern recognition, this follow-up paper presents the material of the second of two lectures, in which additional exercises are discussed to reinforce the lesson. Along the way we provide a glimpse of some foundational ideas of computer science such as incomputability and general system development strategies such as incremental and iterative reasoning. This paper discusses the outcomes of PBL courses, which include expected improvement in the overall results achieved by students who have undertaken PBL courses, compared to those students who have not.

• Teaching puzzle-based learning: development of basic concepts

  183-204

  Nickolas Falkner

  Raja Sooriamurthi

  Zbigniew Michalewicz

  Views:

  489

  While computer science and engineering students are trained to recognise familiar problems with known solutions, they may not be sufficiently prepared to address novel real-world problems. A successful computer science graduate does far more than just program and we must train our students to reach the required levels of analytical and computational thinking, rather than hoping that it will just 'develop'. As a step in this direction, we have created and experimented with a new first-year level course, Puzzle-based Learning (PBL), that is aimed at getting students to think about how to frame and solve unstructured problems. The pedagogical goal is increase students' mathematical awareness and general problem solving skills by employing puzzles, which are educational, engaging, and thought provoking. We share our experiences in teaching such a course – apart from a brief discussion on our pedagogical objectives, we concentrate on discussing the presented material which covers (in two lectures) just one selected topic (pattern recognition). In this paper we present the ideas behind foundations for PBL and the material of the first of two lectures on pattern recognition, in which we address core concepts and provide students with sufficient exemplars to illustrate the main points.

• Gamification in Higher Education

  87-106

  Kinga Kovácsné Pusztai

  Views:

  965

  The way of thinking and the way of life of the today's children and teenagers have changed radically. Some of the well-established pedagogical methods that were used for decades have become obsolete. Therefore, we need to look for a new method to approach Generations Z and Alpha. Gamification, which has been known since 2010 and means the use of game elements in other areas of life, offers an opportunity to do so.
  In addition to a brief description of gamification, my article shows some possibilities for using it at the university. Furthermore, I investigate the impact of gamification on the student in "Algorithms and Data Structures" university course.

  Subject Classification: 97P30