Dataset concerning: Lilobot: a cognitive conversational agent to train child helpline counselors on social support

DOI:10.4121/7b024697-659a-47ad-95a4-0497bf52b432.v2
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/7b024697-659a-47ad-95a4-0497bf52b432

Datacite citation style

Grundmann, Sharon; Al Owayyed, Mohammed (2023): Dataset concerning: Lilobot: a cognitive conversational agent to train child helpline counselors on social support. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/7b024697-659a-47ad-95a4-0497bf52b432.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Version 2 - 2023-11-13 (latest)
Version 1 - 2023-07-19

Data collected as part of an evaluation study of a BDI-based conversational agent for training counsellors of a child helpline to publish a paper, "Dataset concerning: Lilobot: a cognitive conversational agent to train child helpline counselors on social support". This dataset contains survey responses of participants with regards to two measures - counselling self-efficacy and perceived usefulness of the agent, in addition to usefulness and BDI scores. It also contains double coding analysis and training materials. The design of the study is available at https://osf.io/hkxzc. This dataset was built on a previous dataset made for Sharon Grundmann's Master thesis: https://doi.org/10.4121/17371919

History

  • 2023-07-19 first online
  • 2023-11-13 published, posted

Publisher

4TU.ResearchData

Format

*.Rmd, *.pdf, *.csv, *.md

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Department of Intelligent Systems

DATA

Files (10)