Abstract

Artificial intelligence (AI) is increasingly integrated into higher education to enhance instructional efficiency and improve learning outcomes. However, its adoption has revealed a paradox: AI-enabled teaching may unintentionally increase student workload without corresponding educational benefits. This study examines teacher-generated “algorithmic busywork,” defined as excessive, low-value assignments produced using Artificial intelligence tools with limited pedagogical design. Using survey data from 206 undergraduate students across multiple universities, we analyze students’ exposure to AI-generated assignments, their perceived educational value, and associated cognitive and emotional responses. The findings indicate that AI misuse in teaching is linked to increased academic stress, reduced engagement, and perceived inefficiencies in learning. Many students report that AI-generated tasks are repetitive, weakly aligned with learning objectives, and detract from more meaningful learning activities.This study contributes to the information systems and digital education literature by shifting attention from student misuse to teacher-directed Artificial intelligence practices. It highlights the need for pedagogical guidelines to ensure that AI-enabled teaching improves, rather than undermines, student outcomes.

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