Erinma Ochu
Biographic Data
| ID | 7840594 |
|---|---|
| NAME | Erinma Ochu |
| GIVEN NAMES | Erinma |
| FAMILY NAME | Ochu |
| SIGNATURE | OCHU E |
| AFFILIATIONS | University of the West of England |
| ORCID | 0000-0002-7268-278X |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Feeding the machine
This paper examines the human implications of AI's ‘data dilemma' in three different and contrasting sectors: pharmaceuticals, higher education, and the arts. The ‘data dilemma' refers to the challenge of obtaining sufficient and suitable data to effectively train AI algorithms. The research, conducted in the UK, involved interviews, focus groups, and observations with 65 practitioners employed across these three sectors. The findings reveal that…
Beliefs, Values and Emotions in Practitioners’ Engagements With Learning Analytics in Higher Education
Internet entrepreneurs, EdTech companies, AI enthusiasts, and other powerful stakeholders around the world have promoted the idea that big data and learning analytics (LA) have the potential to revolutionise education. LA, defined as the continuous measurement, collection, analysis and reporting of data about learners and their context (Gašević et al., 2015, p. 1), is increasingly being used to track and evaluate what students do in internet-medi…
No prominent works on this page.
Beliefs, Values and Emotions in Practitioners’ Engagements With Learning Analytics in Higher Education
Internet entrepreneurs, EdTech companies, AI enthusiasts, and other powerful stakeholders around the world have promoted the idea that big data and learning analytics (LA) have the potential to revolutionise education. LA, defined as the continuous measurement, collection, analysis and reporting of data about learners and their context (Gašević et al., 2015, p. 1), is increasingly being used to track and evaluate what students do in internet-medi…
Feeding the machine
This paper examines the human implications of AI's ‘data dilemma' in three different and contrasting sectors: pharmaceuticals, higher education, and the arts. The ‘data dilemma' refers to the challenge of obtaining sufficient and suitable data to effectively train AI algorithms. The research, conducted in the UK, involved interviews, focus groups, and observations with 65 practitioners employed across these three sectors. The findings reveal that…
Analytics (1 work) · Computer Science (1 work) · Data science (1 work) · Dilemma (1 work) · Ethics and Social Impacts of AI (1 work) · Information Systems Theories and Implementation (1 work) · Learning analytics (1 work) · Online Learning and Analytics (1 work) · Psychology (1 work) · Research Data Management Practices (1 work)