Machine Learning based Psychology: Advocating for A Data-Driven Approach
| Autor: | Jorge I. Vélez |
|---|---|
| Jazyk: | English<br />Spanish; Castilian |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | International Journal of Psychological Research, Vol 14, Iss 1 (2021) |
| Druh dokumentu: | article |
| ISSN: | 2011-2084 2011-7922 20112084 |
| DOI: | 10.21500/20112084.5365 |
| Popis: | Since its beginnings, Psychology has been prone to both data generation and understanding of human behavior through data analysis. Back in 1879, Dr. Wilheim Wundt opened the first experimental psychology lab at the University of Leipzig to study reaction times. To many, this is considered the start of Psychology as a separate scientific discipline and the use of data analysis for data-driven decision making in the field (Flis, 2019; Tweney, 2003). In this Editorial, we briefly discuss how Psychology students, clinicians, and researchers may take part of the data revolution and help transforming Psychology, as we know it, into Machine Learning Psychology. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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