Test your AI-ELT/L knowledge
1
What are the five AI-enabled areas identified as affordances in ELT/L?
2
Which skill was least represented in the studies despite AI’s capabilities?
3
Which region dominated AIELT/L studies according to Crompton et al.?
4
Name a non-traditional AI pedagogy highlighted for ELT/L in the review.
5
Which tool was cited as enhancing pronunciation through visual spectrograms?
6
What was a notable challenge linked to AI standardising language?
7
Which AI application supported autonomous language learning via chatbots?
8
What major gap did the study identify in adult ELT/L research?
9
Which AI tool raised concerns about privacy and data handling in ELT/L?
10
What method did the researchers use to identify AI affordances and challenges?
11
What are the five areas identified as affordances of AI in ELT/L in this study?
12
What are the four challenges of using AI in ELT/L reported in the study?
13
Which region accounted for the largest share of AI in ELT/L studies according to the findings?
14
Among learner levels, where were the majority of AI and ELT/L studies conducted?
15
In the Taiwan study by Liu and Hung (2016), how did AI help with pronunciation?
16
What is a key practical implication for policy and practice highlighted by the authors?
Explicación
AI affordances span speaking, writing, reading, pedagogy and self-regulation.
Listening did not emerge as a main focus in grounded coding.
Asia accounted for the majority (72%).
LGC-based pedagogy helps personalize learning.
Liu & Hung (2016) used AI with spectrogram visuals for pronunciation.
AI translations can push a standard language bias.
Hew et al. (2023) showed chatbots aid goal setting and engagement.
Adults were underrepresented compared to higher education.
AI tools raise concerns about data privacy and opaqueness.
A grounded, inductive approach revealed emergent codes.
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