Sébastien Louvigné, Neil Rubens, Fumihiko Anma, and Toshio Okamoto
goal-setting, observational learning, data mining
Goal-Setting enhances learning by providing a sense of direction and purpose. Often only a few goals are suggested, as a result many learners fail to find the goals that they can relate to. To address this problem, we propose to extract a large number and variety of goals from social media. Learners can then observe goal-based messages from others and adopt the ones they find useful. Conceptually, proposed approach could be considered a combination of Goal-Setting and Observational Learning. To provide a practical implementation, we automate this process by (1) retrieving a large number of messages from Twitter, (2) classifying which of the messages contain goals, (3) determining what those goals are.
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