Providing educational media content items based on a determined context of a vehicle or driver of the vehicle

A computer-implemented method, comprising:

• training, by a system comprising a processor, using training data associated with vehicles and drivers, a machine learning model to infer intents of drivers based on contexts of the vehicles and the drivers, and select media contents features of the vehicles based on the contexts and the inferred intents of the drivers;
• determining, by the system, a context of a vehicle or a driver of the vehicle, wherein the context comprises the driver of the vehicle operating a feature of the vehicle;
• inferring, by the system, using the machine learning model, an intent of the driver;
• determining, by the system, that the driver of the vehicle has repeatedly operated the feature of the vehicle in an incorrect manner with respect to the inferred intent of the driver;
• selecting, by the system, using the machine learning model, a media content item relating to a feature of the vehicle based on the determined context and the inferred intent of the driver, wherein the machine learning model performs a utility-based analysis by factoring cost of making an incorrect selection versus benefit of making a correct selection;
• and
• outputting, by the system, the selected media content item in response to a result of the utility-based analysis meeting a criterion.

A computer program product comprising a non-transitory computer readable medium having program instructions embodied therewith, the program instructions being executable by a processor to cause the processor to:

• train, by the processor, using training data associated with vehicles and drivers, a machine learning model to infer intents of drivers based on contexts of the vehicles and the drivers, and select media contents features of the vehicles based on the contexts and the inferred intents of the drivers;
• determine, by the processor, a context of a vehicle or a driver of the vehicle, wherein the context comprises the driver of the vehicle operating a feature of the vehicle;
• infer, by the processor, using the machine learning model, an intent of the driver;
• determining, by the processor, that the driver of the vehicle has repeatedly operated the feature of the vehicle in an incorrect manner with respect to the inferred intent of the driver;
• select, by the processor, using the machine learning model, a media content item relating to a feature of the vehicle based on the determined context and the inferred intent of the driver, wherein the machine learning model performs a utility-based analysis by factoring cost of making an incorrect selection versus benefit of making a correct selection;
• and
• output, by the processor, the selected media content item in response to a result of the utility-based analysis meeting a criterion.