Scaffolding argumentation in mathematics with CSCL scripts: Which is the optimal scripting level for university freshmen?

ABSTRACT

Argumentative scripts for computer-supported collaborative learning are scaffolds that prompt learners to take over distributed roles and to move through a sequence of activities that specify an argumentative learning discourse. Argumentative scripts may lead to suboptimal effects on learning outcomes when their level of scaffolding does not fit learners’ prerequisites regarding argumentation. This study compares the effects of three different levels of argumentative scripts on learners’ argumentation knowledge and learning motivation. Results show that university freshmen in the context of mathematics seem to learn best when the argumentative script targets a medium level, scaffolding the sequence of social discourse, but not necessarily the construction of single arguments. Non-significant results regarding the effects on motivational variables speak against the concern that a too detailed structure of scripts may be detrimental for learning due to reduced learning motivation.

KEYWORDS:

• CSCL script
• argumentation
• motivation
• scaffolding
• university students

Acknowledgments

This work was supported by the Deutsche Forschungsgemeinschaft (DFG) under grants RE 1247/9-1 and FI 792/7-1.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Deutsche Forschungsgemeinschaft [RE 1247/9-1 and FI 792/7-1.].

Notes on contributors

Freydis Vogel

Dr. Freydis Vogel is an Assistant Professor of Learning Sciences at the University of Nottingham with research expertise in computer-supported collaborative learning and argumentation. She focuses on the analysis of social learning processes in small groups.

Dr. Ingo Kollar is Full Professor for Psychology with a special emphasis on Education Psychology at Augsburg University. His research foci include scientific reasoning and argumentation as well as technology supported teaching and learning.

Dr. Stefan Ufer is Full Professor for Mathematics Education at Ludwig Maximilian University of Munich. His research is dedicated to mathematics education, psychology of mathematics, and instructional support for mathematical argumentation and proof skills.

Dr. Anselm Strohmaier did his PhD at the Technical University of Munich and he is now research assistant at the Center for Empirical Research on Language and Education at Leuphana University Lüneburg. His research expertise is focused on reading and mathematics education.

Dr. Kristina Reiss is Full Professor for Mathematics Education at the Technical University of Munich. Her research focuses on reasoning and proof, learning with heuristic worked examples, and the development of mathematical competence.

Dr. Frank Fischer is Full Professor of Educational Science and Educational Psychology at Ludwig Maximilian University of Munich. He is Director of the Munich Center of the Learning Sciences and his research topics include learning with digital media and scientific reasoning.