Alessio Gaspar
Alessio Gaspar publishes mostly in Artificial Intelligence, Computer Science Applications and Media Technology, on topics such as Teaching and Learning Programming, Evolutionary Algorithms and Applications and Experimental Learning in Engineering.
- World rank
- #4,608,646 of 7,710,434 ranked researchers
- Rank in United States
- #1,219,510 of 1,627,098
- Works
- 57
- Citations
- 402
- Citations per work
- 7.1
What does Alessio Gaspar research?
Alessio Gaspar's work is mostly in Computer Science (49%), Engineering (14%), Psychology (9%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences3663.5%
- Computer Science2849.1%
- Engineering814.4%
- Everything else1527.1%
- Social Sciences59.4%
- Psychology59.4%
- 1Artificial Intelligence23% of their works
- 2Computer Science Applications18% of their works
- 3Media Technology9% of their works
- 4Developmental and Educational Psychology9% of their works
- 5Information Systems8% of their works
- 6Control and Systems Engineering5% of their works
Research topics
- Teaching and Learning Programming
- Evolutionary Algorithms and Applications
- Experimental Learning in Engineering
- Metaheuristic Optimization Algorithms Research
- Educational Games and Gamification
- Online Learning and Analytics
- Innovative Teaching and Learning Methods
- Advanced Multi-Objective Optimization Algorithms
Which keywords describe Alessio Gaspar's research?
The keywords of their largest research topics: STEM Education, Evolutionary Algorithms, Learning Analytics, Machine Learning, Multiobjective Optimization, Computational Thinking, Programming Education and Classification.
- Surrogate Modeling
- Self-Regulation
- Massive Open Online Courses
- Gamification
- Differential Evolution
- Student Engagement
- Remote Laboratories
- Particle Swarm Optimization
- Classification
- Computational Thinking
- Machine Learning
- Evolutionary Algorithms
- STEM Education
- Learning Analytics
- Multiobjective Optimization
- Programming Education
- Genetic Programming
- Engineering Education
- Motivation
- Ant Colony Optimization
- Game-Based Learning
- Educational Data Mining
- Metacognition
- Genetic Algorithm
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most.
All 24 words, with their numbers
- STEM Education362 topics
- Evolutionary Algorithms343 topics
- Learning Analytics272 topics
- Machine Learning242 topics
- Multiobjective Optimization222 topics
- Computational Thinking211 topic
- Programming Education211 topic
- Classification181 topic
- Genetic Programming181 topic
- Particle Swarm Optimization162 topics
- Engineering Education151 topic
- Remote Laboratories151 topic
- Motivation132 topics
- Student Engagement132 topics
- Ant Colony Optimization121 topic
- Differential Evolution121 topic
- Game-Based Learning71 topic
- Gamification71 topic
- Educational Data Mining61 topic
- Massive Open Online Courses61 topic
- Metacognition61 topic
- Self-Regulation61 topic
- Genetic Algorithm41 topic
- Surrogate Modeling41 topic
Where does Alessio Gaspar work?
Alessio Gaspar's main affiliation in the publication record is University of South Florida, United States.
How many publications and citations does Alessio Gaspar have?
OpenAlex counts 57 works and 402 citations for Alessio Gaspar, an h-index of 11, ranking #4,608,646 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
Discussion
Ask a question or share a note about Alessio Gaspar. Posts are plain text and can be reported.