Evaluating Bayesian networks' precision for detecting students' learning styles

By Patricio García, Analía Amandi, Silvia N. Schiaffino, Marcelo R. Campo. Comput. Educ., 2007

480 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Science Applications, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/b05fe43b15db57e6b41b80212de8cb2df204e451

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Cristóbal Romero
2. Sebastián Ventura
3. Huong May Truong
4. Francisco Herrera
5. Anastasios A. Economides
6. Z. Papamitsiou

In Computer Science Applications

1. Cristóbal Romero
2. Sebastián Ventura
3. Huong May Truong
4. Ben Kai Daniel
5. Anastasios A. Economides
6. Z. Papamitsiou
7. Alejandro Peña Ayala
8. Rebecca Ferguson

In Developmental and Educational Psychology

1. Huong May Truong

Citations in the corpus

• Educational Data Mining: A Review of the State of the Art (2010, background): “knowing a skill at a given time through cognitive tutors [18]; to detect students’ learning styles in a web-based education system [91]; to predict whether a student will answer a problem”
• Integrating learning styles and adaptive e-learning system: Current developments, problems and opportunities (2016, methodology): “Franzoni, Assar, Defude, and Rojas (2008), García, Schiaffino, & Amandi (2008), García et al. (2007), Germanakos et al.”