Teachable Agents and the Protégé Effect: Increasing the Effort Towards Learning
By Catherine C. Chase, Doris B. Chin, Marily A. Oppezzo, Daniel L. Schwartz. 2009
366 citations recorded by the source corpus.
Subfields: Developmental and Educational Psychology, Experimental and Cognitive Psychology
View Paper: https://www.semanticscholar.org/paper/3900e45e2e69dcd22406226cf6cbb088bf7d09c0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Developmental and Educational Psychology
- Roberta Michnick Golinkoff
- Kathy Hirsh-Pasek
- James Kennedy
- Brian Scassellati
- Na Li
- Jinhee Kim
- Tony Belpaeme
- Rita Detrick
In Experimental and Cognitive Psychology
Citations in the corpus
- Interacting with educational chatbots: A systematic review (2022, background): “• Learning by teaching Learning by teaching is a well-known pedagogical approach that allows students to learn through the generation of explanations to others (Chase et al., 2009).”
- A Review of Artificial Intelligence (AI) in Education from 2010 to 2020 (2021, result): “More than that, learners’ sense of responsibility was exerted towards the intelligent agent, which was consistent with the research from Chase et al., demonstrating that students may work harder on behalf of their agents than they would for themselves [53].”
- Communication-efficient federated learning via knowledge distillation (2021, positive): “Motivated by the Protégé Effect 29 ("while we teach, we learn ” , Seneca the Younger) in human learning, we propose an adaptive mutual distillation method to enable the local mentor and mentee models to reciprocally learn from the knowledge distilled from their predicted soft labels and intermediate”
- Pedagogical Agents: Back to the Future (2018, neutral): “Teachable agents also appear to elicit the pro-tégé effect (Chase et al. 2009), which is that learners seem to feel responsible for their teachable agents and to exert more effort to learn for their agents than when learning alone without an agent.”
- Exploring students’ perspectives on Generative AI-assisted academic writing (2024, positive): “On the other hand, AI could be designed as a Teachable Agent (TA) capitalizing on learning-by-teaching interactions where students learn by teaching the TA (e.g., assessing its knowledge by asking it questions or by getting it to solve problems) (Biswas et al., 2005; Chase et al., 2009).”
- Putting Education in “Educational” Apps (2015, background): “Clearly, having a sense of responsibility to teach another increases children’s motivation to learn (Chase, Chin, Oppezzo, & Schwartz, 2009).”
- Social robots for education: A review (2018, background): “This is an instance of learning by teaching, which is widely known in human education, also referred to as the protégé effect (72).”