| Literature DB >> 35877297 |
Yen-Jung Chen1,2, Liwei Hsu2.
Abstract
Encouraging feedback positively affects learners' self-efficacy; in language learning, self-efficacy predicts language learner performance and behavior. Our research involved three studies to expand knowledge about why and how we can enhance English as a Foreign Language (EFL) learners' self-efficacy beliefs in online settings. In Study 1, based on an online survey with 310 participants, we ascertained the extent to which EFL learners with greater self-efficacy tend to challenge themselves by learning content that requires a proficiency level that is higher than their current proficiency. In Study 2, we recruited 120 EFL learners; the results indicate that positive feedback via emojis embedded in online courses could significantly boost EFL learners' self-efficacy beliefs about learning English. Study 3 involved 35 participants and extended the understanding provided by the first two studies, showing that EFL learners not only like to use emojis for computer-mediated communication (CMC), but also prefer to receive them as feedback. This research adds to knowledge on "why" and "how" we can enhance EFL learners' self-efficacy beliefs in online contexts. We systematically provide empirical evidence regarding the aforementioned issues and demonstrate that positive feedback through emojis has great potential to enhance EFL learners' self-efficacy, even when such feedback is subliminal.Entities:
Keywords: EFL learning; emojis; feedback; online learning; self-efficacy beliefs; subliminal feedback
Year: 2022 PMID: 35877297 PMCID: PMC9312293 DOI: 10.3390/bs12070227
Source DB: PubMed Journal: Behav Sci (Basel) ISSN: 2076-328X
Fit statistics for single-factor CFA of the QESE reading section.
| Model | CMIN/df | NFI | CFI | TLI | RMSEA | RMSEA 90% CI |
|---|---|---|---|---|---|---|
| Single-Factor | 1.87 | 0.98 | 0.98 | 0.98 | 0.05 | 0.00–0.09 |
Note: NFI = Norm Fit Index; CFI = Comparative Fit Index; TLI = Tucker Lewis Index RMSEA = Root Mean Square Error of Approximation.
Figure 1Four positive emojis used in the study (accessed on 15 December 2021 from https://www.vectorstock.com/royalty-free-vectors/vectors-by_yayayoy).
Figure 2Learning materials with and without positive feedback provided through emojis. Note: The Chinese language is the translation of English above.
Fit statistics for single-factor CFA of the QESE listening portion.
| Model | CMIN/df | NFI | CFI | TLI | RMSEA | RMSEA 90% CI |
|---|---|---|---|---|---|---|
| Single-Factor | 1.93 | 0.96 | 0.98 | 0.96 | 0.08 | 0.00–0.15 |
Note: NFI = Norm Fit Index; CFI = Comparative Fit Index; TLI = Tucker Lewis Index RMSEA = Root Mean Square Error of Approximation.
Figure 3Research procedure (Study 3).
The paired sample t-tests of the control and experimental groups.
| Mean | SD |
|
| |
|---|---|---|---|---|
| CG pre-test | 4.00 | 0.64 | −0.95 | 0.35 |
| CG post-test | 4.07 | 0.38 | ||
| EG pre-test | 4.05 | 0.50 | −2.92 | 0.005 |
| CG post-test | 4.27 | 0.49 |
Descriptive statistics (Study 3).
| Mean | SD | SEM | ||
|---|---|---|---|---|
| Listening | No | 3.8833 | 0.18647 | 0.03404 |
| Supraliminal | 4.0167 | 0.14746 | 0.02692 | |
| Subliminal | 4.0667 | 0.17287 | 0.03156 | |
| Total | 3.9889 | 0.18495 | 0.01950 | |
| Reading | No | 3.8278 | 0.26437 | 0.04827 |
| Supraliminal | 4.1056 | 0.26072 | 0.04760 | |
| Subliminal | 4.1778 | 0.23543 | 0.04298 | |
| Total | 4.0370 | 0.29326 | 0.03091 |
The results of ANOVA from Study 3.
| Source of Variance | SS |
|
|
|
|
| |
|---|---|---|---|---|---|---|---|
| Listening | Between-group | 0.54 | 2 | 0.27 | 9.36 | 0.00 | 0.18 |
| Within-group | 2.51 | 87 | 0.03 | ||||
| Total | 3.04 | 89 | |||||
| Reading | Between-group | 2.05 | 2 | 1.02 | 15.90 | 0.00 | 0.27 |
| Within-group | 5.61 | 87 | 0.06 | ||||
| Total | 7.65 | 89 |