Student discourse in small-group collaborative contexts in real-world higher education

This dataset contains anonymised student discourse in small-group collaborative contexts in real-world higher education settings.

There are 28 sessions, composed of 10799 utterances.

The columns consist of 13 columns:

• session: the session number
• start: the starting time of the utterance
• end: the ending time of the utterance
• speaker: anonymised speaker name
• content: the content of the utterance
• ep: the episode number of the utterance. An episode refers to a single topic of discussion with multiple utterances.
• C: a binary value indicating the presence or absence of a cognitive challenge, where 0 means no challenge, and 1 means there is a cognitive challenge.
• E: a binary value indicating the presence or absence of an emotional/motivational challenge, where 0 means no challenge, and 1 means there is an emotional/motivational challenge.
• M: a binary value indicating the presence or absence of a metacognitive challenge, where 0 means no challenge, and 1 means there is a metacognitive challenge.
• T: a binary value indicating the presence or absence of a technical/other challenge, where 0 means no challenge, and 1 means there is a technical/other challenge.
• TA: a binary value indicating the presence or absence of the regulatory process "task analysis," where 0 means no regulation and 1 means task analysis is present.
• MC: a binary value indicating the presence or absence of the regulatory process "monitoring/control," where 0 means no regulation and 1 means monitoring/control is present.
• RA: a binary value indicating the presence or absence of the regulatory process "reflection/adaptation," where 0 means no regulation and 1 means reflection/adaptation is present.

This annotated dataset was used in the following paper to model challenge moments.

For more details on how the dataset was generated, please refer to the paper.