Suche

Wo soll gesucht werden?
Erweiterte Literatursuche

Ariadne Pfad:

Inhalt

Literaturnachweis - Detailanzeige

 
Autor/inn/enRakovic, Mladen; Winne, Philip H.; Marzouk, Zahia; Chang, Daniel
TitelAutomatic Identification of Knowledge-Transforming Content in Argument Essays Developed from Multiple Sources
QuelleIn: Journal of Computer Assisted Learning, 37 (2021) 4, S.903-924 (22 Seiten)Infoseite zur Zeitschrift
PDF als Volltext Verfügbarkeit 
ZusatzinformationORCID (Rakovic, Mladen)
ORCID (Winne, Philip H.)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0266-4909
DOI10.1111/jcal.12531
SchlagwörterPersuasive Discourse; Essays; Writing (Composition); Writing Skills; Undergraduate Students; Sentences; Classification; Computation
AbstractDeveloping knowledge-transforming skills in writing may help students increase learning by actively building knowledge, regardless of the domain. However, many undergraduate students struggle to transform knowledge when drafting essays based on multiple sources. Writing analytics can be used to scaffold knowledge transforming as writers bring evidence to bear in supporting claims. We investigated how to automatically identify sentences representing knowledge transformation in argumentative essays. A synthesis of cognitive theories of writing and Bloom's typology identified 22 linguistic features to model processes of knowledge transforming in a corpus of 38 undergraduates' essays. Findings indicate undergraduates mostly paraphrase or copy information from multiple sources rather than engage deeply with sources' content. Eight linguistic features were important for discriminating evidential sentences as telling versus transforming source knowledge. We trained a machine learning algorithm that accurately classified nearly three of four evidential sentences as knowledge-telling or knowledge-transforming, offering potential for use in future research. (As Provided).
AnmerkungenWiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
Literaturbeschaffung und Bestandsnachweise in Bibliotheken prüfen
 

Standortunabhängige Dienste
Bibliotheken, die die Zeitschrift "Journal of Computer Assisted Learning" besitzen:
Link zur Zeitschriftendatenbank (ZDB)

Artikellieferdienst der deutschen Bibliotheken (subito):
Übernahme der Daten in das subito-Bestellformular

Tipps zum Auffinden elektronischer Volltexte im Video-Tutorial

Trefferlisten Einstellungen

Permalink als QR-Code

Permalink als QR-Code

Inhalt auf sozialen Plattformen teilen (nur vorhanden, wenn Javascript eingeschaltet ist)

Teile diese Seite: