Error Recognition Model: High-mathability End-user Text Management
Sebestyén Katalin, Csapó Gábor, Mária Csernoch, Bernadett Aradi · Acta Polytechnica Hungarica · 2022
Discussion, evaluation and error recognition, in natural language digital texts, is one of the most neglected areas in the digital world, despite the fact that text management is the most prevalent computer related activity.Millions of erroneous text-based documents of different types are in circulation, without us being aware of how fragile, damaged and harmful they are.It is well accepted in programming and even in other end-user activities, that error recognition plays a crucial role in teaching, learning and in real-world problemsolving processes.In the present paper, we introduce the High-mathability Error Recognition Model, which consists of the processes used in discussion and concept-based problemsolving and we also provide examples of the utilization of the model.We argue that error recognition and correction, and the assessment of problems in text management are as important as in other fields of informatics and computer sciences.In our study experimental groupsstudying with the Error Recognition Modeland control groupsstudying with low-mathability tool-centered approacheswere compared.It was found that the Error Recognition Model is more effective in digital text management, than for the tool-centered methodologies, in two error types: the typographic and layout-breaking error categories and a strong compensation effect was found in the syntax error category.