Enhancing argumentative writing with automated feedback and social comparison nudging

The advantages offered by natural language processing (NLP) and machine learning enable students to receive automated feedback on their argumentation skills, independent of educator, time, location. Although there is a growing amount literature formative feedback, empirical evidence the effects adaptive mechanisms novel NLP approaches enhance argumentative writing remains scarce. To help fill this gap, aim present study investigate whether social comparison nudging internalize improve logical abilities in an undergraduate business course. We conducted mixed-methods impact 71 field experiment. Students treatment group 1 completed assignment while receiving whereas 2 same with nudge that indicated how other performed assignment. control received generalized based rules syntax. found participants who wrote more convincing texts higher-quality compared two benchmark groups (p < 0.05). measured self-efficacy, perceived ease use, qualitative data provide valuable insights explain effect. results suggest embedding combination nudges enables increase skills triggering psychological processes. Receiving only form in-text highlighting without any further guidance appears not significantly influence students’ when syntactic feedback.