In Hungary, K-12 informatics/computer science education focuses on mostly surface-based methods. This approach can be observed in the teaching of several topics in the subject, of which we focus on spreadsheet management. This is further emphasized by regulatory documents – the Hungarian National Core Curriculum and Hungarian Curriculum Frameworks –, where handling algorithms, calling schemata, and problem-solving in general are only assigned to the programming topic. In the process of fulfilling the requirements of the school curricula and the various tool-centered exams, students become familiar with the software interfaces and how to navigate them, instead of developing computational thinking skills and learning how to approach and solve real-world problems.

Our educational system is based on a spiral teaching approach; therefore, spreadsheet management is taught throughout several grades in a small number of lessons. Prior research shows that students learning spreadsheet management with surface-approach methods do not build up a reliable knowledge structure. These students cannot solve problems in contexts differing to the ones in which they learned the topic and cannot use their surface navigation abilities in different software environments.

Our research group focuses on spreadsheeting with an algorithm-building and problem-solving method at the center of the teaching-learning process. For this purpose, we have developed and introduced the Sprego (Spreadsheet Lego) methodology. Sprego is based on Pólya’s four-step concept-based problem-solving approach, and its efficiency has already been proved compared to traditional low-mathability surface-approach methods. In the comparison of the low- and high-mathability approaches, several further questions arise, and amongst them one crucial aspect is how the different methods support the schema-construction and knowledge built up in long-term memory. In this paper we discuss this question using a delayed post-test that was carried out one year after the treatment period. We focused on the students’ achievement both in the experimental (Sprego) and control (traditional surface-approaches) groups based on the methods used one year prior to the administration of the delayed post-test. The results show that students who learned the spreadsheet management topic with Sprego achieved significantly better scores on the delayed tests than those students who used low-mathability approaches.

在匈牙利，K-12信息学/计算机科学教育主要集中在基于表面的方法上。可以在该主题的多个主题的教学中观察到这种方法，我们将重点放在电子表格管理上。监管文件（《匈牙利国家核心课程》和《匈牙利课程框架》）进一步强调了这一点，在这些文件中，处理算法，调用模式和一般的问题解决通常只分配给编程主题。在满足学校课程和各种以工具为中心的考试的要求的过程中，学生逐渐熟悉软件界面以及如何进行导航，而不是发展计算思维技巧和学习如何解决和解决实际问题。

我们的教育系统基于螺旋式教学方法；因此，在少数几个课程中，将电子表格管理贯穿多个年级。先前的研究表明，使用表面方法学习电子表格管理的学生无法建立可靠的知识结构。这些学生无法在不同于他们学习主题的环境中解决问题，也无法在不同的软件环境中使用其表面导航功能。

我们的研究小组专注于电子表格，在教学过程中以算法构建和问题解决方法为中心。为此，我们开发并介绍了Sprego（电子表格Lego）方法。Sprego基于Pólya基于概念的四步问题解决方法，并且与传统的低数学曲面方法相比，它的效率已经得到证明。在比较低数学能力和高数学能力的方法时，还会出现其他问题，其中一个关键方面是不同的方法如何支持在长期记忆中建立的架构和知识。在本文中，我们使用治疗期后一年进行的延迟后测试来讨论这个问题。我们根据延后的测试后一年使用的方法，着重于实验组（Sprego）和对照组（传统表面方法）的学生成绩。结果表明，与使用低数学方法的学生相比，使用Sprego学习电子表格管理主题的学生在延迟测试中的得分明显更高。