Hywel Evans
Biographic Data
| ID | 6379099 |
|---|---|
| NAME | Hywel Evans |
| GIVEN NAMES | Hywel |
| FAMILY NAME | Evans |
| SIGNATURE | EVANS H |
| AFFILIATIONS | Swansea University |
| ORCID | 0000-0001-6745-4187 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Using the Welsh Index of Multiple Deprivation in research
To avoid biased estimates, researchers using WIMD in studies on health, education, housing, physical environment, income, employment, community safety, and access to services should consider how these domains are related to their outcomes. We describe a methodology for researchers to quantify any bias in their own studies
Evidence From the Phylogenetic Domain and the Use of L1 in English Language Teaching
The theoretical foundations supporting adherence to naturalistic language learning approaches appear to have entirely collapsed, just as non-naturalistic approaches to language teaching such as translation and translanguaging have become increasingly respectable in English language teaching. In line with this, language and language learning are increasingly being understood as sociocultural phenomena, inevitably situated in local contexts, rather…
No prominent works on this page.
Evidence From the Phylogenetic Domain and the Use of L1 in English Language Teaching
The theoretical foundations supporting adherence to naturalistic language learning approaches appear to have entirely collapsed, just as non-naturalistic approaches to language teaching such as translation and translanguaging have become increasingly respectable in English language teaching. In line with this, language and language learning are increasingly being understood as sociocultural phenomena, inevitably situated in local contexts, rather…
Using the Welsh Index of Multiple Deprivation in research
To avoid biased estimates, researchers using WIMD in studies on health, education, housing, physical environment, income, employment, community safety, and access to services should consider how these domains are related to their outcomes. We describe a methodology for researchers to quantify any bias in their own studies
Artificial Intelligence (1 work) · Biostatistics (1 work) · Chronic Disease Management Strategies (1 work) · Computer Science (1 work) · Demography (1 work) · Demography (1 work) · Environmental health (1 work) · Epidemiology (1 work) · Gerontology (1 work) · Health disparities and outcomes (1 work)