Motivating students is a major issue for current Intelligent Tutoring Systems. Videogames are known to have a very addictive effect on their users. We have the intuition that such a phenomenon is partially due to the autonomy support videogames provide to their user. In fact, modern theories of motivation such as the Self Determination Theory (SDT) have shown the positive motivational impact of...

We examined whether the combination of two factors that have consistently been found to enhance motor learning - an external focus (EF) of attention and autonomy support (AS) - would produce additive benefits. Participants practiced throwing with their non-dominant arm. In a 2×2 design, they were or were not asked to focus externally (i.e., on the target), and were or were not given a choice (a...

In shared autonomy, user input is combined with semi-autonomous control to achieve a common goal. The goal is often unknown ex-ante, so prior work enables agents to infer the goal from user input and assist with the task. Such methods tend to assume some combination of knowledge of the dynamics of the environment, the user’s policy given their goal, and the set of possible goals the user might ...

Goal-driven autonomy (GDA) is a conceptual model for creating an autonomous agent that monitors a set of expectations during plan execution, detects when discrepancies occur, builds explanations for the cause of failures, and formulates new goals to pursue when planning failures arise. While this framework enables the development of agents that can operate in complex and dynamic environments, i...

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With the population of postgraduates increasing in China, their academic study has attracted the attention of second language acquisition researchers. But the research into postgraduates’ motivation and autonomy is unfortunately scarce. This study explores the relationship between learning motivation and learner autonomy among English-major postgraduates based on the questionnaire administered ...

We present Confidence-Based Autonomy (CBA), an interactive algorithm for policy learning from demonstration. The CBA algorithm consists of two components which take advantage of the complementary abilities of humans and computer agents. The first component, Confident Execution, enables the agent to identify states in which demonstration is required, to request a demonstration from the human tea...

A reliable representation of the environment a robot operates in is vital for solving complex tasks. Models that represent information about objects and their properties are typically trained beforehand using supervised methods. This requires intensive human labeling which makes it time-consuming and results in models that are generally inflexible to changes. We would prefer a robot that can bu...

Numerous studies in the motor learning domain have demonstrated learning advantages of self-controlled practice relative to yoked conditions. In separate lines of evidence in the social-psychological literature, findings show that providing participants with task-relevant autonomy support or minor incidental choices can result in superior outcomes when compared with conditions that thwart auton...