Assessing Digital Competency Among Thai Citizens: A Comprehensive Study in the Post-Covid-19 Era
Bibliographic record
Abstract
During the past Covid-19 pandemic, the digital skills of Thai citizens have transformed. This study will lead to ways to promote and develop digital skills and competency in various fields in order to be ready to cope with the Next Normal era. The study of digital competency of Thai citizens aimed to 1) study the digital competency of Thai people, and 2) compare the digital competency of Thai citizens in terms of gender, age and educational background. The 912 research samples were obtained by volunteer sampling. The research instrument was an online evaluation form. Data were analyzed by percentage, mean, standard deviation, t-test for independent samples by one-way ANOVA. The research found that 1) the overall digital competency of Thai citizens was at a high level, in terms of digital knowledge and skills and characteristics to use digital information technology and communication with confidence and creativity to achieve goals related to work, learning, and participation in society. When considering each aspect, it was found that communication and collaboration, safety, information and data literacy, problem solving, and digital content creation were all at a high level respectively; and 2) When comparing the digital competency of Thai citizens, it was found that the samples with different genders had no statistically significant difference in digital competency. As for age and educational backgrounds, there was a statistically significant difference in digital performance at the .05 level, except for the digital competency in safety which had no statistically significant difference. The overall digital competency of Thai citizens at all educational levels is high, and those in advanced professional fields have the highest level of digital competency overall. This is in line with the regulations of numerous Thai universities and vocational schools, which mandate that final-year students take a Digital Literacy Test.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".