An empirical study on cultivating college students' cross-cultural communicative competence based on the artificial-intelligence English-teaching mode

Artificial intelligence education will be an important part of information technology education in the future. It will enter the classroom and the learning life of students in various forms. The modern teaching media used in artificial intelligence courses at universities include some conventional t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Frontiers in psychology 2022-12, Vol.13, p.976310-976310
Hauptverfasser: Long, Jingjing, Lin, Jiaxin
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Artificial intelligence education will be an important part of information technology education in the future. It will enter the classroom and the learning life of students in various forms. The modern teaching media used in artificial intelligence courses at universities include some conventional teaching courseware, multimedia videos, and tool software. Some teaching media are unique to artificial intelligence, such as smart software, smart devices, and smart websites. The existing cross-cultural competence dimensions and evaluation scales were theoretically explained with factor analysis by comparing and selecting comprehensive evaluation methods in the work. Its main advantages were as follows: simple mathematical models and easy operation. The construction of a comprehensive evaluation model for college students' cross-cultural competence included the principles and ideas of model construction, the methods and steps of model construction, and model calculations. The survey results showed that the four-level scores of all samples had a significant positive correlation with foreign cultural knowledge, attitudes, and cross-cultural communication skills at 0.01 level (bilateral) and 0.05 (bilateral), respectively.
ISSN:1664-1078
1664-1078
DOI:10.3389/fpsyg.2022.976310