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• A first course in computer science: languages and goals

  137-152

  Dennis C. Smolarski

  Views:

  119

  The College Board Advanced Placement exam in computer science will use the language Java starting in fall 2003. The language chosen for this exam is based on the language commonly taught in introductory computer science courses at the university level. This article reviews the purpose of an introductory course and the various suggestions for the curriculum of introductory courses published by the Association for Computing Machinery. It then proposes that such a course stress foundational concepts over specific language syntax, and then provides a list of such foundational concepts and related topics. Based on this fundamental curriculum, the article recommends C++ as the most appropriate language. An appendix provides a sample syllabus.

• General key concepts in informatics: data

  135-148

  Péter Szlávi

  László Zsakó

  Views:

  236

  "The system of key concepts contains the most important key concepts related to the development tasks of knowledge areas and their vertical hierarchy as well as the links of basic key concepts of different knowledge areas. When you try to identify the key concepts of a field of knowledge, you should ask the following questions: Which are the concepts that are the nodes of the concept net and can be related to many other concepts? Which are the concepts that necessarily keep re-appearing in different contexts when interpreting what you have learnt before? Which are the concepts that arrange specific facts in structures, which contribute to interpreting and apprehending new information and experience? Which are the concepts that – if you are unfamiliar with and unaware of – inhibits you in systematizing various items of knowledge or sensibly utilizing them?" [9] One of the most important of these concepts is the data.

• Methods of teaching programming

  247-257

  Péter Szlávi

  László Zsakó

  Views:

  153

  Programming methodology is one of the oldest fields of IS education, and thus various methods have evolved for its teaching. While some of them could be used effectively in primary or secondary education, others are more suited for students in higher education. The methods themselves determine the structure and curricula of courses such as Programming methodology, Data types and algorithms, Programming technology.

• Discovery as culture, not template: lessons from Hungary

  77-102

  Keren Dror

  Views:

  77

  In this study, I investigate the structural adaptations necessary to implement Hungarian-style guided discovery in mainstream secondary school classrooms. During a six-week residency in Budapest, I observed classrooms, interviewed five Hungarian educators, and collected survey and interview data from students. My findings suggest that guided discovery in Hungary is less a fixed method and more a pedagogical culture, shaped by shared values, historical influences, and professional communities. While Hungarian educators praised its ability to foster deep thinking, student agency, and creativity, they also described challenges around pacing, assessment, and curriculum alignment. Structural supports such as flexible curriculum frameworks, professional networks, and differentiated assessment practices emerged as critical enablers of the method’s success. Student responses revealed both the promise of discovery-based instruction and the pressures it can create without sufficient scaffolding. I conclude that Hungarian-style guided discovery is not best understood as a replicable model, but as a set of values that evolve through professional dialogue and trial-and-error. Its meaningful implementation depends not on uniform procedures, but on the presence of cultural, institutional, and community structures that allow teachers to make it their own.

  Subject Classification: 97D40, 97D50, 97C30

• Better understanding mathematics by algorithmic thinking and computer programming

  295-305

  Katalin Fried

  István Fekete

  Péter Princz

  Views:

  349

  Tamás Varga’s mathematics education experiment covered not just mathematics, but also other related topics. In many of his works he clearly stated that computer science can support the understanding of mathematics as much as mathematics supports informatics. On the other hand, not much later than the introduction of the new curriculum in 1978, personal computers started to spread, making it possible to teach informatics in classes and in extracurricular activities. Varga’s guided discovery approach has a didactic value for other age groups as well, not only in primary school. Its long-lasting effect can be observed even in present times. Having reviewed several educational results in the spirit of Tamás Varga, we have decided to present an extracurricular course. It is an open study group for age 12-18. Students solve problems by developing Python programs and, according to our experiences, this results in a deeper understanding of mathematical concepts.

  Subject Classification: 97B10, 97B20, 97D50, 97N80, 97P20, 97P30, 97P40, 97P50, 97U70

• Gamification in Higher Education

  87-106

  Kinga Kovácsné Pusztai

  Views:

  987

  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