Gerard De Melo
Biographic Data
| ID | 1906522 |
|---|---|
| NAME | Gerard De Melo |
| GIVEN NAMES | Gerard |
| FAMILY NAME | De Melo |
| SIGNATURE | DE MELO G |
| AFFILIATIONS | Chair of Artificial Intelligence and Intelligent Systems Hasso‐Plattner‐Institute/University of Potsdam Potsdam Germany |
| ORCID | 0000-0002-2930-2059 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 3 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
A process-oriented perspective on pre-service teachers' self-efficacy and their motivational messages
BackgroundRecent studies have examined the relation between teacher motivation, motivational messages and student learning but are limited to an achievement-related context, primarily using survey data. Moreover, our understanding of the relation between various teacher characteristics, such as teacher self-efficacy (TSE), and their motivational message use remains limited.AimsOur study tested whether teacher speech can be classified into self-de…
The potential and limitations of large language models for automatic classification of teachers' motivational messages in educational research
IntroductionThe rapid advancement of artificial intelligence (AI) has created new opportunities in educational research, particularly in the efficient analysis of complex social interactions within classrooms. One promising area involves the classification of teachers' motivational messages. Traditionally, such assessments have relied on self-reports and observer evaluations, which require a lot of staff and time resources. Recently, large langua…
Understanding archetypes of fake news via fine-grained classification
Constructions and frames meet language technology
Preview this article: Constructions and frames meet language technology: From the guest editors of the C&F special issue on frames, constructions, and computation, Page 1 of 1 /docserver/preview/fulltext/cf.6.1.01int-1.gif
A process-oriented perspective on pre-service teachers' self-efficacy and their motivational messages
BackgroundRecent studies have examined the relation between teacher motivation, motivational messages and student learning but are limited to an achievement-related context, primarily using survey data. Moreover, our understanding of the relation between various teacher characteristics, such as teacher self-efficacy (TSE), and their motivational message use remains limited.AimsOur study tested whether teacher speech can be classified into self-de…
The potential and limitations of large language models for automatic classification of teachers' motivational messages in educational research
IntroductionThe rapid advancement of artificial intelligence (AI) has created new opportunities in educational research, particularly in the efficient analysis of complex social interactions within classrooms. One promising area involves the classification of teachers' motivational messages. Traditionally, such assessments have relied on self-reports and observer evaluations, which require a lot of staff and time resources. Recently, large langua…
Constructions and frames meet language technology
Preview this article: Constructions and frames meet language technology: From the guest editors of the C&F special issue on frames, constructions, and computation, Page 1 of 1 /docserver/preview/fulltext/cf.6.1.01int-1.gif
Understanding archetypes of fake news via fine-grained classification
A process-oriented perspective on pre-service teachers' self-efficacy and their motivational messages
BackgroundRecent studies have examined the relation between teacher motivation, motivational messages and student learning but are limited to an achievement-related context, primarily using survey data. Moreover, our understanding of the relation between various teacher characteristics, such as teacher self-efficacy (TSE), and their motivational message use remains limited.AimsOur study tested whether teacher speech can be classified into self-de…
The potential and limitations of large language models for automatic classification of teachers' motivational messages in educational research
IntroductionThe rapid advancement of artificial intelligence (AI) has created new opportunities in educational research, particularly in the efficient analysis of complex social interactions within classrooms. One promising area involves the classification of teachers' motivational messages. Traditionally, such assessments have relied on self-reports and observer evaluations, which require a lot of staff and time resources. Recently, large langua…
Computer Science (2 works) · Linguistics (2 works) · Psychology (2 works) · Topic Modeling (2 works) · Artificial Intelligence (1 work) · Competence (human resources) (1 work) · Computation (1 work) · Computer security (1 work) · Context (archaeology) (1 work) · Data science (1 work)