Abstract: A method and system to identify first content in a first language. Second content in a second language is identified that matches the first content in the first language. A machine learning process is employed to map a set of similarities between the first content in the first language and the second content in the second language. Based on the set of similarities and a schema, modified content including a ratio of a first portion of the first content in the first language to a second portion of the second content in the second language is generated. The modified content to a user system and one or more inputs associated with the modified content are received from the user system. Based at least in part on the one or more inputs, one or more exercises associated with the modified content are generated.

Abstract: An electronic platform to generate and display blended multilingual content. The methods and systems can be employed in an educational environment to assist a user fluent in a native language in learning a target language. One or more blended combinations of content in the native language and the target language are generated and displayed to the user. A machine learning component can be used to evaluate performance data to execute adjusts to the level and type of blending applied to the blended combinations to increase and improve learning efficiency.

Abstract: An electronic platform to generate and display blended multilingual content. The methods and systems can be employed in an educational environment to assist a user fluent in a native language in learning a target language. One or more blended combinations of content in the native language and the target language are generated and displayed to the user. A machine learning component can be used to evaluate performance data to execute adjusts to the level and type of blending applied to the blended combinations to increase and improve learning efficiency.