Characteristics of Learning Tasks in Accounting Textbooks: An AI Assisted Analysis

Autor/inn/en	Stütz, Simone; Berding, Florian; Reincke, Sven; Scheper, Lena
Titel	Characteristics of Learning Tasks in Accounting Textbooks: An AI Assisted Analysis
Quelle	In: Empirical Research in Vocational Education and Training, 14 (2022), Artikel 10 (33 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
DOI	10.1186/s40461-022-00138-2
Schlagwörter	Learning Activities; Accounting; Textbooks; Artificial Intelligence; Foreign Countries; Content Analysis; Germany + Suchen Sie Ihr Suchwort? Lernaktivität; Abrechnung; Buchführung; Buchhaltung; Textbook; Text book; Schulbuch; Lehrbuch; Künstliche Intelligenz; Ausland; Inhaltsanalyse; Deutschland
Abstract	Tasks in accounting textbooks play a vital role when it comes to learning processes. However, hardly any empirical evidence on the quality of accounting tasks exists regarding accounting-relevant characteristics. This is why a new category system containing accounting-relevant aspects was developed to analyze a total of 3,361 tasks from 14 different German accounting textbooks. Descriptive analysis and correlation analysis were performed to assess task characteristics and identify relationships between categories. In addition, in light of the large number of tasks to be analyzed, AI assisted the content analysis, and its usefulness was evaluated. The results indicate that tasks are not sufficiently able to instill accounting competencies such as interpreting data, assessing the relevance of information, or identifying and solving underlying accounting problems. The findings further show that AI and human coding yield similar results in most categories, suggesting that AI assistance is useful for content analysis when evaluating a large number of tasks. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01