{'fraction_non_alphanumeric': 0.019558359621451103, 'fraction_numerical': 0.005047318611987382, 'mean_word_length': 5.925764192139738, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Detecting and Correcting Misconceptions with Lifelike Avatars in 3 D Learning Environments

Lifelike pedagogical agents offer significant promise for addressing a central problem posed by learning environments: detecting and correcting students’ misconceptions. By designing engaging lifelike avatars and introducing them into task-oriented 3D learning environments, we can enable them to serve a dual communication role. They can serve as students’ representatives in learning environments and simultaneously provide realtime advice to address their misconceptions. We describe a three-phase avatar-based misconception correction framework in which (1) as students navigate their avatars through 3D learning environments, a misconception detector tracks their problem-solving activities by inspecting task networks, (2) when they take sub-optimal or incorrect actions, a misconception classifier examines misconception trees to identify the most salient misconceptions, and (3) the avatars employ a misconception corrector to intervene with tailored advice. The framework has been implemented in a misconception system for the lifelike avatar of CPU CITY, a 3D learning environment testbed for the domain of fundamentals of computer architecture. In CPU CITY, students direct their lifelike avatar to navigate a 3D world consisting of a virtual computer, to transport data and address packets, and to manipulate computational devices. Informal studies with students interacting with CPU CITY suggest that the framework can is an effective tool for addressing students’ misconceptions.