Vocabulary Learning Based on Learner-Generated Pictorial Annotations: Using Big Data as Learning Resources
Abstract
:1. Introduction
- Which source of big data do students prefer for pictorial annotation creation, Google images or images from social media? What may be the possible explanations for such results?
- Which type of pictorial annotations do students highly rate, the annotations created with Google images or those with images from social media? What may be the possible explanations for such results?
- Which type of pictorial annotations promote better vocabulary learning, the annotations created with Google images or those with images from social media? What may be the possible explanations for such results?
2. Literature Review
2.1. Big Data in Language Learning
2.2. Google and Social Media
2.3. Multimedia Annotations for Vocabulary Learning
3. Method
3.1. Research Design
3.2. Assessment and Scoring
3.3. Collection and Analysis of Interview Data
4. Results
4.1. Perceptions of Google Data and Social Media Data for Multimedia-Annotations Creation
4.2. Scores of Learner-Generated Google Pictorial Annotations and Social Media Pictorial Annotations
4.3. Learning Performance of the Participants Who Learned with Textual Annotations, Google Pictorial Annotations, and Social Media Pictorial Annotations
5. Discussion
5.1. Perceptions of Using Google Data and Social Media Data for Learning Resource Creation
5.2. Effectiveness of Google Pictorial Annotations and Social Media Pictorial Annotations in Promoting Language Learning
5.3. Potential of Using Big Data as Language Learning Resources
5.4. Challenges of Using Big Data as Language Learning Resources
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
- To what extent do you agree that it is easy to search for images that can appropriately depict the target word meanings?
- To what extent do you agree that the images presented by the data sources are relevant, reliable, appropriate, and interesting?
- To what extent do you agree that the images from Google data and social media data can depict the meanings of the target words accurately and properly?
- To what extent do you agree that the pictorial annotations can facilitate your learning of the target vocabulary?
- What factors or features related to the pictorial annotations do you find useful for your learning of the target vocabulary?
- What are your feelings, perceptions, or experiences about the learning process?
- To what extent are you satisfied with the learning approach?
- Do you have any other comments on the learning process and approach?
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Google Data | Social Media Data | |
---|---|---|
The idea of using this data set as resources for language enhancement is interesting/creative/fun. | 27/30 (90%) | 28/30 (93%) |
The idea of using this data set as resources for language enhancement is feasible/reliable. | 26/30 (87%) | 24/30 (80%) |
It is easy to search for images that appropriately depict target word meanings from this dataset. | 29/30 (97%) | 20/30 (67%) |
The images of this dataset are relevant to the keywords for search. | 26/30 (87%) | 19/30 (63%) |
The images of this dataset are appropriate/make sense. | 23/30 (76%) | 12/30 (40%) |
Google Pictorial Annotations | Social Media Pictorial Annotations | |||||
---|---|---|---|---|---|---|
N | M | SD | N | M | SD | |
Scores of the annotations | 300 | 4.21 | 0.67 | 300 | 3.42 | 0.70 |
Levene’s Test | t-Test | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
F | p. | t | df | p | MD | SED | Lower | 95% CI Upper | ||
Scores of the learner-generated annotations | Equal variances assumed | 3.73 | 0.05 | 14.04 | 598 | 0.00 | 0.79 | 0.05 | 0.68 | 0.90 |
Equal variances not assumed | 14.04 | 596.89 | 0.00 | 0.79 | 0.05 | 0.68 | 0.90 |
Scores of the Annotations of the 6 Verbs | Scores of the Annotations of the 3 Nouns and 1 Adjective | ||
---|---|---|---|
Google pictorial annotations | N | 180 | 120 |
M | 4.56 | 3.70 | |
SD | 0.56 | 0.47 | |
Social media pictorial annotations | N | 180 | 120 |
M | 3.82 | 2.81 | |
SD | 0.56 | 0.38 | |
Overall | N | 360 | 240 |
M | 4.19 | 3.25 | |
SD | 0.67 | 0.62 |
Levene’s Test | t-Test | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
F | p. | t | df | p | MD | SED | Lower | 95% CI Upper | ||
Scores of the learner-generated annotations | Equal variances assumed | 0.42 | 0.51 | 17.22 | 598 | 0.00 | 0.93 | 0.05 | 0.82 | 1.04 |
Equal variances not assumed | 17.50 | 539.68 | 0.00 | 0.93 | 0.05 | 0.83 | 1.04 |
N | Pre-Test | Immediate Post-Test | Delayed Post-Test | ||||
---|---|---|---|---|---|---|---|
M | SD | M | SD | M | SD | ||
Learning with Google multimedia | 32 | 0.06 | 0.24 | 8.03 | 1.33 | 6.84 | 2.35 |
Learning with social media pictorial annotations | 30 | 0.06 | 0.25 | 6.96 | 1.62 | 5.50 | 1.92 |
Learning with textual annotations | 31 | 0.09 | 0.30 | 6.00 | 1.75 | 3.93 | 1.93 |
SS | df | MS | F | p | |
---|---|---|---|---|---|
Between Groups | 65.05 | 2 | 32.52 | 13.07 | 0.00 |
Within Groups | 223.93 | 90 | 2.48 | ||
Total | 288.98 | 92 |
95% CI | ||||||
---|---|---|---|---|---|---|
MD | SE | Sig. | LB | UB | ||
Learning with Google pictorial annotations | Learning with social media pictorial annotations | 1.06 * | 0.40 | 0.02 | 0.10 | 2.01 |
Learning with textual annotations | 2.03 * | 0.39 | 0.00 | 1.08 | 2.97 | |
Learning with social media pictorial annotations | Learning with textual annotations | 0.96 * | 0.40 | 0.04 | 0.00 | 1.92 |
SS | df | MS | F | p | |
---|---|---|---|---|---|
Between Groups | 133.33 | 2 | 66.66 | 15.32 | 0.00 |
Within Groups | 391.59 | 90 | 4.35 | ||
Total | 524.92 | 92 |
95% CI | ||||||
---|---|---|---|---|---|---|
MD | SE | Sig. | LB | UB | ||
Learning with Google pictorial annotations 2 | Learning with social media pictorial annotations 3 | 1.34 * | 0.53 | 0.03 | 0.08 | 2.60 |
Learning with textual annotations 1 | 2.90 * | 0.52 | 0.00 | 1.65 | 4.16 | |
Learning with social media pictorial annotations 3 | Learning with textual annotations 1 | 1.56 * | 0.53 | 0.01 | 0.29 | 2.83 |
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Zou, D.; Xie, H. Vocabulary Learning Based on Learner-Generated Pictorial Annotations: Using Big Data as Learning Resources. Sustainability 2021, 13, 5767. https://doi.org/10.3390/su13115767
Zou D, Xie H. Vocabulary Learning Based on Learner-Generated Pictorial Annotations: Using Big Data as Learning Resources. Sustainability. 2021; 13(11):5767. https://doi.org/10.3390/su13115767
Chicago/Turabian StyleZou, Di, and Haoran Xie. 2021. "Vocabulary Learning Based on Learner-Generated Pictorial Annotations: Using Big Data as Learning Resources" Sustainability 13, no. 11: 5767. https://doi.org/10.3390/su13115767