Sentence examples for feedback on errors from inspiring English sources

Looking at the two sequences with the highest performance scores [100] and [001], one of which had external feedback on errors (approximately 20% errors), the other which had sounds delivered on approximately 20% of the correct responses randomly distributed, there was no significant difference in accuracy scores.

The tasks were presented with and without feedback on errors committed, as outlined above.

T-test was carried out to identify the effectiveness of each type of direct feedback on errors that had helped the more advanced students improve their writings.

We welcome your feedback on errors in our data related to taxonomic and nomenclatural synonyms!

The application should be able to detect and give feedback on errors that are made by learners of DL2 at the A2 level of the Common European Framework (CEF).

FE: External feedback on errors revealed no significant effect compared to no external feedback on errors F 1, 164) = 0.69, p > 0.41, log Bayes Factor = −2.23.

In total, two emails detailing specific errors and recommendations were sent out biweekly: (1) 'General Feedback on error trends and themes' sent to all fellows, nurse practitioners and physician assistants and (2) the 'individual feedback' sent to individual frontline clinicians prescribing the errors.

FE-FCC: There was a significant interaction between errors and corrects following corrects, where external feedback on error, together with FCC100, that is, the two conditions [102] [112], resulted in reduced performance compared to other FE and FCC combinations, F 2, 164) = 71.8, p < 0.0001.

Calculating the mutual information of our two fictive sequences (see next section for details of this calculation) gives the following result: Sequence 1 (20% errors, auditory feedback on all errors) gives MI = 0.722; Note that this is the same as H o) because there is no uncertainty in the outcome after feedback (i.e., H(o| f) is zero).

One of the biggest challenges in designing computer assisted language learning (CALL) applications that provide automatic feedback on pronunciation errors consists in reliably detecting the pronunciation errors at such a detailed level that the information provided can be useful to learners.

The error phase had two levels of feedback; either external feedback on all errors (FE100) or no external feedback (FE0).