Erick Gomez-Nieto
Biographic Data
| ID | 6714977 |
|---|---|
| NAME | Erick Gomez-Nieto |
| GIVEN NAMES | Erick |
| FAMILY NAME | Gomez-Nieto |
| SIGNATURE | GOMEZ-NIETO E |
| AFFILIATIONS | Universidad Católica San Pablo |
| ORCID | 0000-0001-7481-1656 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 3 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Supporting Decision-Making Process on Higher Education Dropout by Analyzing Academic, Socioeconomic, and Equity Factors through Machine Learning and Survival Analysis Methods in the Latin American Con…
The prediction of university dropout is a complex problem, given the number and diversity of variables involved. Therefore, different strategies are applied to understand this educational phenomenon, although the most outstanding derive from the joint application of statistical approaches and computational techniques based on machine learning. Student Dropout Prediction (SDP) is a challenging problem that can be addressed following various strate…
How Do Curricular Design Changes Impact Computer Science Programs
Computer science is a dynamic field of study that requires constant review and updating of the curricular designs in academic programs—in general, measuring the impact of plan changes has been little explored in the literature. In most cases, it focuses only on structuring its curricula, leaving aside several factors associated with important events or facts such as student dropout, retention, and inclusion. However, these features provide academ…
Political discourses, ideologies, and online coalitions in the Brazilian Congress on Twitter during 2019
The aim of this research is to describe the pattern of interactions of Brazilian legislators on Twitter during 2019 in the construction of political discourses. Based on 20,076 replies during 2019, posted on Twitter by 514 Brazilian legislators, we conducted descriptive analysis of legislators’ Twitter profiles, social network analyses from their interactions, and content analysis of the messages. We found that (1) there are large disparities bet…
Political discourses, ideologies, and online coalitions in the Brazilian Congress on Twitter during 2019
The aim of this research is to describe the pattern of interactions of Brazilian legislators on Twitter during 2019 in the construction of political discourses. Based on 20,076 replies during 2019, posted on Twitter by 514 Brazilian legislators, we conducted descriptive analysis of legislators’ Twitter profiles, social network analyses from their interactions, and content analysis of the messages. We found that (1) there are large disparities bet…
Political discourses, ideologies, and online coalitions in the Brazilian Congress on Twitter during 2019
The aim of this research is to describe the pattern of interactions of Brazilian legislators on Twitter during 2019 in the construction of political discourses. Based on 20,076 replies during 2019, posted on Twitter by 514 Brazilian legislators, we conducted descriptive analysis of legislators’ Twitter profiles, social network analyses from their interactions, and content analysis of the messages. We found that (1) there are large disparities bet…
How Do Curricular Design Changes Impact Computer Science Programs
Computer science is a dynamic field of study that requires constant review and updating of the curricular designs in academic programs—in general, measuring the impact of plan changes has been little explored in the literature. In most cases, it focuses only on structuring its curricula, leaving aside several factors associated with important events or facts such as student dropout, retention, and inclusion. However, these features provide academ…
Supporting Decision-Making Process on Higher Education Dropout by Analyzing Academic, Socioeconomic, and Equity Factors through Machine Learning and Survival Analysis Methods in the Latin American Con…
The prediction of university dropout is a complex problem, given the number and diversity of variables involved. Therefore, different strategies are applied to understand this educational phenomenon, although the most outstanding derive from the joint application of statistical approaches and computational techniques based on machine learning. Student Dropout Prediction (SDP) is a challenging problem that can be addressed following various strate…
Political science (3 works) · Sociology (3 works) · Computer Science (2 works) · Mathematics education (2 works) · Online Learning and Analytics (2 works) · Psychology (2 works) · Socioeconomic status (2 works) · Artificial Intelligence (1 work) · Centrality (1 work) · Content analysis (1 work)