Systematic review on the current state of computer-supported argumentation learning systems

Context:

Argumentation is a fundamental part of learning, communication and problem-solving not only in software engineering but all education. Teaching argumentation is a long-standing practice, and with the advance of digital learning, it, too, has been transitioning to an online format.

Objective:

As computer-supported argumentation learning progresses, other learning domains have much to learn from it on how to enable argumentation and reasoning in automated and scalable online learning solutions.

Methods:

To review the current state of the field, we conducted a systematic literature review on the last decade of academic research and design on computer-supported argumentation learning systems. We reviewed and summarised the central aspects and approaches of reported systems.

Results:

We reviewed 34 different argumentation learning tools. The review showed that approaches to computer-supported argumentation vary significantly in many aspects, e.g., argumentation theory, learning task types and collaboration status. However, the use of argumentation graphs is quite common. Most modern tools seem to embrace the role of feedback in learning.

Conclusions:

The role of individual learning has risen in computer-supported argumentation learning. This is in opposition to previous predictions and statements on the role of collaborative learning of argumentation. Automated feedback has, on the other hand, become commonplace in collaborative and individual-use argumentation learning tools. The modern generation of argumentation teaching tools is Web-based but recently we have also seen the emergence of mobile-based solutions.