Information Processing Apparatus for Adaptive Vocabulary Learning
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Solution Overview
Problem
Existing linguistic learning systems restrict user flexibility in selecting content and fail to maintain the authenticity of expressions, leading to a less enjoyable learning experience and reduced effectiveness in learning vocabulary from interested content.
Innovation Solution
An information processing apparatus that receives user input, associates vocabularies with difficulty levels, calculates frequency of use, and specifies relevant vocabularies for learning based on user level, allowing users to learn and confirm the effect of learning while enjoying content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system pre-analyzes and classifies video teaching materials to select learning content, then the learning content can be matched to user level, but the user's flexibility in selecting content is restricted
Solution Approach 1:
Instead of pre-classifying all video materials and requiring users to choose from limited options, the system inverts the approach by allowing users to freely select any content they are interested in, and then automatically extracts and classifies learning vocabulary from the user-chosen content. This resolves the contradiction by prioritizing user flexibility while still providing personalized learning content through automatic analysis.
2Adaptability or versatility
If sentences are modified based on changing rules to match user level, then learning can be adapted to user ability, but the expression differs from the original content causing learning effectiveness to decrease
Solution Approach 1:
Instead of modifying original sentences which changes their expression and reduces learning effectiveness, the system extracts specific vocabulary words, idioms, and phrases from the user's chosen content and creates learning materials based on these extracted elements. This maintains the authenticity of the original content expressions while adapting the learning difficulty by selecting appropriate vocabulary for the user's level.
3Measurement precision
If comprehensive vocabulary analysis and classification is performed, then learning content can be precisely matched to user level, but the system complexity increases
Solution Approach 1:
The system employs automatic natural language processing and machine learning algorithms to perform vocabulary extraction, classification, and difficulty assessment without requiring manual pre-analysis of all content. The system self-services by automatically analyzing user-selected content, extracting relevant vocabulary, and adapting learning materials based on user performance feedback, thereby reducing overall system complexity while maintaining precision.
Data Source
AI summary
To provide an information processing apparatus for allowing a learner to enjoy viewing and listening of the content and to perform linguistic learning, and to check the effect of learning. A Dictionary DB 101 associates a vocabulary with a difficulty level determined for each vocabulary, and stores the vocabulary and the difficulty level, the vocabulary including a word, an idiom, or a phrase consisting of two or more words in a language to learn. A registration unit 102 registers a degree of learning of the language to learn of a learner as a learning level. A calculating unit 104 calculates the number of the vocabularies to learn used in the content as a frequency in use. A specifying unit 106 specifies, according to the calculated frequency in use and the registered learning level, and among the vocabularies of the language to learn used in the content, a vocabulary which is an object to learn as a vocabulary to learn. A main control unit 113 causes an input operation received by an input unit 111 during the output of the content to be registered as an input operation in response to the output of the vocabulary to learn.