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Using GPT and Authentic Contextual Recognition to Generate Math Word Problems with Difficulty Levels
Peer reviewed
Direct linkWu-Yuin Hwang; Ika Qutsiati Utami – Education and Information Technologies, 2024
Automatic generation of math word problems (MWPs) is a challenging task in Natural Language Processing (NLP), particularly connecting it to real-life problems because it can benefit students in developing a higher level of mathematical thinking. However, most of the MWPs are presented within a scholastic setting in a decontextualized way. This…
Descriptors: Artificial Intelligence, Technology Uses in Education, Mathematics Education, Word Problems (Mathematics)
Sobocinski, Márta; Malmberg, Jonna; Järvelä, Sanna – Metacognition and Learning, 2017
Investigating the temporal order of regulatory processes can explain in more detail the mechanisms behind success or lack of success during collaborative learning. The aim of this study is to explore the differences between high- and low-challenge collaborative learning sessions. This is achieved through examining how the three phases of…
Descriptors: Metacognition, Cooperative Learning, Difficulty Level, Comparative Analysis
Kupari, Pekka, Ed.; Haapasalo, Lenni, Ed. – 1993
This yearbook is the seventh for the Mathematics Education Research in Finland series and contains ten articles presented at the decennial jubilee colloquium. The first three articles discuss Constructivism both in general and with regard to mathematics education. Analysis is directed to the origins of constructivism, to the learning of…
Descriptors: Alternative Assessment, Constructivism (Learning), Deduction, Difficulty Level
