Resumen de “Connecting concepts helps put main ideas together”: cognitive load and usability in learning biology with an AI-enriched textbook
Marta M. Koc Januchta, Konrad J. Schönborn, Casey Roehrig, Vinay K. Chaudhri, Lena Tibell, H. Craig Heller
Rapid developments in educational technology in higher education are intended to make learning more engaging and efective. At the same time, cognitive load theory stresses limitations of human cognitive architecture and urges educational develop‑ ers to design learning tools that optimise learners’ mental capacities. In a 2-month study we investigated university students’ learning with an AI-enriched digital biology textbook that integrates a 5000-concept knowledge base and algorithms ofering the possibility to ask questions and receive answers. The study aimed to shed more light on diferences between three sub-types (intrinsic, germane and extraneous) of cogni‑ tive load and their relationship with learning gain, self-regulated learning and usability perception while students interacted with the AI-enriched book during an introduc‑ tory biology course. We found that students displayed a benefcial learning pattern with germane cognitive load signifcantly higher than both intrinsic and extraneous loads showing that they were engaged in meaningful learning throughout the study.
A signifcant correlation between germane load and accessing linked suggested questions available in the AI-book indicates that the book may support deep learning.
Additionally, results showed that perceived non-optimal design, which defects cogni‑ tive resources away from meaningful processing accompanied lower learning gains.
Nevertheless, students reported substantially more favourable than unfavourable opin‑ ions of the AI-book. The fndings provide new approaches for investigating cognitive load types in relation to learning with emerging digital tools in higher education. The fndings also highlight the importance of optimally aligning educational technologies and human cognitive architecture.
