Analysis of University STEM Students' Mathematical, Linguistic, Rhetorical-Organizational Assignment Errors

Autor/inn/en	Arévalo, María-José; Cantera, María Asun; García-Marina, Vanessa; Alves-Castro, Marian
Titel	Analysis of University STEM Students' Mathematical, Linguistic, Rhetorical-Organizational Assignment Errors
Quelle	In: Education Sciences, 11 (2021), Artikel 173 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Arévalo, María-José) ORCID (Cantera, María Asun) ORCID (García-Marina, Vanessa) ORCID (Alves-Castro, Marian)
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2227-7102
Schlagwörter	STEM Education; Instructional Design; Essays; Computational Linguistics; Error Analysis (Language); Interdisciplinary Approach; Pilot Projects; Undergraduate Students; Writing (Composition); Engineering Education; Writing Skills; Error Patterns; Classification; Rhetoric; Communication Strategies; Mathematics; Connected Discourse; Writing Evaluation; Spanish; Integrated Learning Systems; Foreign Countries; Syntax; Punctuation; Writing Improvement; Spain + Suchen Sie Ihr Suchwort? STEM; Lesson concept; Lessonplan; Unterrichtsentwurf; Essay; Aufsatzunterricht; Linguistics; Computerlinguistik; Error analysis; Language; Fehleranalyse; Fächerübergreifender Unterricht; Fächerverbindender Unterricht; Interdisziplinarität; Pilot project; Modellversuch; Pilotprojekt; Schreibübung; Ingenieurausbildung; Writing skill; Schreibfertigkeit; Fehlertyp; Classification system; Klassifikation; Klassifikationssystem; Rhetorik; Kommunikationsstrategie; Mathematik; Spanisch; Ausland; Interpunktion; Spanien
Abstract	Although Error Analysis (EA) has been broadly used in Foreign Language and Mother Tongue learning contexts, it has not been applied in the field of engineering and by STEM (Science, Technology, Engineering, and Mathematics) students in a systematic way. In this interdisciplinary pilot study, we applied the EA methodology to a wide corpus of exercises and essays written by third-year students of mechanical engineering, with the main purpose of achieving a precise diagnosis of the students' strengths and weaknesses in writing skills. For the analysis to be as exhaustive as possible, the errors were typologized into three main categories (linguistic, mathematical, and rhetorical-organizational), each of which is, in turn, subdivided into 15 items. The results show that the predominant errors are rhetorical-organizational (39%) and linguistic (38%). The application of EA permits the precise identification of the areas of improvement and the subsequent implementation of an educational design that allows STEM students to improve their communicative strategies, especially those related to the writing skills and, more precisely, those having to do with the optimal use of syntax, punctuation, rhetorical structure of the text, and mathematical coherence. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/1/01