Data-driven learning: Technology-enhanced learning of semantic prosody
This exploratory study investigated the use of technology-enhanced activities to teach the semantic prosody of certain English expressions through a method known as Data-driven learning (DDL). The study involved 83 undergraduate social sciences students enrolled in a mandatory English course at a un...
Αποθηκεύτηκε σε:
| Τόπος έκδοσης: | URI:https://journals.openedition.org/alsic, |
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| Κύριοι συγγραφείς: | , |
| Μορφή: | Article ou chapitre numérique |
| Γλώσσα: | Anglais |
| Έκδοση: |
Alsic
2024
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| Θέματα: | |
| Διαθέσιμο Online: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |
| Περίληψη: | This exploratory study investigated the use of technology-enhanced activities to teach the semantic prosody of certain English expressions through a method known as Data-driven learning (DDL). The study involved 83 undergraduate social sciences students enrolled in a mandatory English course at a university. Various online tools, such as YouGlish and SKELL, were employed and found to enhance the learning experience in formal contexts. However, the Milanote platform did not fulfil its expected role in linking formal and non-formal learning contexts, as students were reluctant to continue their learning outside the classroom. Based on the results, this paper suggests ways to integrate formal and non-formal learning contexts by normalising DDL. By treating DDL as a technique for addressing real language problems and ensuring spontaneity, accessibility, efficiency, and effective scaffolding, DDL can bridge the gap between formal and non-formal learning contexts. |
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