"Connecting Concepts Helps Put Main Ideas Together": Cognitive Load and Usability in Learning Biology with an AI-Enriched Textbook

Autor/inn/en	Koc-Januchta, Marta M.; Schönborn, Konrad J.; Roehrig, Casey; Chaudhri, Vinay K.; Tibell, Lena A. E.; Heller, H. Craig
Titel	"Connecting Concepts Helps Put Main Ideas Together": Cognitive Load and Usability in Learning Biology with an AI-Enriched Textbook
Quelle	In: International Journal of Educational Technology in Higher Education, 19 (2022), Artikel 11 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Koc-Januchta, Marta M.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2365-9440
DOI	10.1186/s41239-021-00317-3
Schlagwörter	Cognitive Processes; Difficulty Level; Usability; Biology; Artificial Intelligence; Electronic Publishing; Textbooks; Educational Technology; Introductory Courses; Learning Processes + Suchen Sie Ihr Suchwort? Cognitive process; Kognitiver Prozess; Schwierigkeitsgrad; Biologie; Künstliche Intelligenz; Elektronisches Publizieren; Textbook; Text book; Schulbuch; Lehrbuch; Unterrichtsmedien; Einführungskurs; Learning process; Lernprozess
Abstract	Rapid developments in educational technology in higher education are intended to make learning more engaging and effective. At the same time, cognitive load theory stresses limitations of human cognitive architecture and urges educational developers 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 offering the possibility to ask questions and receive answers. The study aimed to shed more light on differences between three sub-types (intrinsic, germane and extraneous) of cognitive load and their relationship with learning gain, self-regulated learning and usability perception while students interacted with the AI-enriched book during an introductory biology course. We found that students displayed a beneficial learning pattern with germane cognitive load significantly higher than both intrinsic and extraneous loads showing that they were engaged in meaningful learning throughout the study. A significant 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 deflects cognitive resources away from meaningful processing accompanied lower learning gains. Nevertheless, students reported substantially more favourable than unfavourable opinions of the AI-book. The findings provide new approaches for investigating cognitive load types in relation to learning with emerging digital tools in higher education. The findings also highlight the importance of optimally aligning educational technologies and human cognitive architecture. (As Provided).
Anmerkungen	BioMed Central, Ltd. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: customerservice@springernature.com; Web site: https://www.springer.com/gp/biomedical-sciences
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01