Utilizing Sprego and Sprego contents

Csernoch, Mária; Biró, Piroska

doi:10.1145/2978249.2978267

Cited by 2 publications

(5 citation statements)

References 3 publications

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“…• Instead of the three functions for the three inputs, an array formula can be used [50] [51] [52], [53] [54] [55] (with the array formula the copying and the absolute and relative references can be avoided which are the major sources of erroneous documents [1]). …”

Section: What Teachers Do Mattersmentioning

confidence: 99%

“…However, at present it is completely isolated for various reasons: (1) the Hungarian language, (2) teachers' reluctance to switch from low to high mathability approaches, (3) the fact that it takes several years to prove its effectiveness 100%. Both Hubwieser [57] and Csernoch [50] [51] [52] focus on real world problems with high mathability approaches. Sprego is similar to…”

Section: Examples Of High Mathability Materialsmentioning

confidence: 99%

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Thinking Fast and Slow in Computer Problem Solving

Csernoch¹

2017

JSEA

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Research in spreadsheet management proved that the overuse of slow thinking, rather than fast thinking, is the primary source of erroneous end-user computing. However, we found that the reality is not that simple. To view end-user computing in its full complexity, we launched a project to investigate end-user education, training, support, activities, and computer problem solving. In this project we also set up the base and mathability-extended typology of computer problem solving approaches, where quantitative values are assigned to the different problem solving methods and activities. In this paper we present the results of our analyses of teaching materials collected in different languages from all over the world and our findings considering the different problem solving approaches, set in the frame of different thinking modes, the characteristics of expert teachers, and the meaning system model of teaching approaches. Based on our research, we argue that the proportions of fast and slow thinking and most importantly their manifestation are responsible for erroneous end-user activities. Applying the five-point mathability scale of computer problem solving, we recognized slow thinking activities on both tails and one fast thinking approach between them. The low mathability slow thinking activities, where surface navigation and language details are focused on, are widely accepted in end-user computing. The high mathability slow thinking problem solving activities, where the utilization of concept based approaches and schema construction take place, is hardly detectable in end-user activities. Instead of building up knowledge which requires slow thinking and then using the tools with fast thinking, end-users use up their slow thinking in aimless wandering in huge programs, making wrong decisions based on their untrained, clueless intuition, and distributing erroneous end-user documents. We also found that the dominance of low mathability slow thinking activities has its roots in the education system and through this we point out that we are in great need of expert teachers and institutions and their widely accepted approaches and methods.

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Section: What Teachers Do Mattersmentioning

confidence: 99%

Section: Examples Of High Mathability Materialsmentioning

confidence: 99%

Thinking Fast and Slow in Computer Problem Solving

Csernoch¹

2017

JSEA

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“…One must also note that-contrary to Prensky's unproven claims considering digital generations [52,53]-even digital children are in great need of educational support. To provide this support, we must have expert teachers [26,40,45] who can break away from the widely accepted tool-centered, lowmathability teaching and testing approaches, and switch to high-mathability problemsolving approaches [29,30,57,58,75,76]. Institutional Review Board Statement: Ethical review and approval were waived for this study, due to structure of the test, where only the schools are recorded strictly and occasionally the grades.…”

Section: Discussionmentioning

confidence: 99%

“…Back then, in 1993, these statements were based on the researchers' experiment; however, these findings have been proven multiple times since then [23][24][25][26][27][28][29][30]. The focus should be on the development of computational thinking [19,[31][32][33][34][35][36][37], including the development of algorithmic and computational problem-solving skills [38][39][40][41][42], extended to end-user computing.…”

Section: Gradesmentioning

confidence: 99%

“…However, this is not so, because browsing the interfaces and looking for ideas requires slow thinking [64], whose processes are proved erroneous, leading to serious spreadsheet errors [39,80,84,85]. Instead, with a reasonable cognitive load [29,30,76], the names, the arguments, and the semantics of the functions must be memorized to allow end-users to activate fast thinking, which would lessen spreadsheet errors. Schema construction and applying the built schemata in solving novel problems is widely accepted and applied in teaching mathematics [86].…”

Section: Spreadsheet Functionsmentioning

confidence: 99%

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The Comparison of Students’ Self-Assessment, Gender, and Programming-Oriented Spreadsheet Skills

2021

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Previous research proved that teaching spreadsheeting from a programming perspective is much more effective than the widely accepted tool-centered surface approach methods. Spreadsheeting as an introductory programming approach allows students to build up schemata leading to contextualized, concept-based problem-solving. Furthermore, it provides tools for real-world problem-solving in other disciplines, and supports knowledge-transfer to database management and “serious” programming. The present study provides the details of a nationwide testing of Grades 7–10 students on how they evaluate their spreadsheet knowledge, which classroom activities form their self-assessment values, and the results of three spreadsheet tasks evaluated by the SOLO categories of understanding. The comparison reveals that most students’ spreadsheet knowledge is pre-structural. On the other hand, they assess themselves much higher, which is primarily based on the number of activities carried out in classes. Traces of conscious problem-solving and knowledge-transfer within the scope of spreadsheeting are hardly detectable, while knowledge brought from mathematics is recognizable. In general, we found proof that the pieces of knowledge remain unconnected, not allowing students to reach the relational level of understanding and build up long-lasting knowledge.

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Utilizing Sprego and Sprego contents

Cited by 2 publications

References 3 publications

Thinking Fast and Slow in Computer Problem Solving

Thinking Fast and Slow in Computer Problem Solving

The Comparison of Students’ Self-Assessment, Gender, and Programming-Oriented Spreadsheet Skills

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