Detailanzeige
Aufsatz (Zeitschrift) zugänglich unter
URN: urn:nbn:de:0111-pedocs-290467
DOI: 10.25656/01:29046; 10.26529/cepsj.1367
URN: urn:nbn:de:0111-pedocs-290467
DOI: 10.25656/01:29046; 10.26529/cepsj.1367
| Originaltitel |
Identifying reading fluency in pupils with and without dyslexia using a machine learning model on texts assessed with a readability application |
|---|---|
| Paralleltitel | Prepoznavanje tekočnosti branja pri učencih z disleksijo in brez nje z uporabo modela strojnega učenja na besedilih, ocenjenih z aplikacijo za berljivost |
| Autoren |
Žabkar, Jure;
Urankar, Tajda;
Javornik, Karmen;
Košak Babuder, Milena  |
| Originalveröffentlichung | CEPS Journal 13 (2023) 4, S. 233-256  |
| Dokument | Volltext (695 KB) |
| Lizenz des Dokumentes |
|
| Schlagwörter (Deutsch) | Schüler; Lesen; Leseschwäche; Lesefertigkeit; Lesbarkeit; Text; Schwierigkeitsgrad; Test; Lesetest; Mündlicher Test; Dyslexie; Kontrollgruppe; Vergleich; Differenz; Bewertung; Modell; Anwendung; Künstliche Intelligenz; Empirische Untersuchung |
| Teildisziplin | Empirische Bildungsforschung Pädagogische Psychologie |
| Dokumentart | Aufsatz (Zeitschrift) |
| ISSN | 2232-2647; 1855-9719; 22322647; 18559719 |
| Sprache | Englisch |
| Erscheinungsjahr | 2023 |
| Begutachtungsstatus | Peer-Review |
| Abstract (Englisch): | Measurement of readability is an important tool for assessing reading disorders such as dyslexia. Among the screening procedures for dyslexia is the reading fluency test, which is defined as the ability to read with speed, accuracy and proper expression. The reading fluency test often consists of a sequence of unrelated written texts ranging from simple short sentences to more difficult and longer paragraphs. In psychological testing instruments, subjective text assessment is often replaced by objective readability formulas, e.g., the Automated Readability Index. Readability formulas extract multiple features from a given text and output a score indicating the difficulty of the text. The aim of the present study is to build a machine learning model that discriminates between pupils identified with dyslexia and a control group without dyslexia based on fluency in oral reading of texts assessed with a readability application developed within the project For the Quality of Slovenian Textbooks. The authors focus on differentiation between both groups of pupils by analysing data obtained from transcriptions of audio recordings of oral reading. The empirical study was conducted with 27 pupils aged 8 and 9 with officially diagnosed dyslexia and a control group without identified dyslexia. (DIPF/Orig.) |
| weitere Beiträge dieser Zeitschrift | CEPS Journal Jahr: 2023 |
| Statistik |  Anzahl der Zugriffe auf dieses Dokument
|
| Prüfsummen | Prüfsummenvergleich als Unversehrtheitsnachweis |
| Eintrag erfolgte am | 13.03.2024 |
| Quellenangabe | Žabkar, Jure; Urankar, Tajda; Javornik, Karmen; Košak Babuder, Milena: Identifying reading fluency in pupils with and without dyslexia using a machine learning model on texts assessed with a readability application - In: CEPS Journal 13 (2023) 4, S. 233-256 - URN: urn:nbn:de:0111-pedocs-290467 - DOI: 10.25656/01:29046; 10.26529/cepsj.1367 |
Inhalt auf sozialen Plattformen teilen
Teile diese Seite:
