JUSThink Dialogue and Actions Corpus

<strong>1. Description</strong> The information contained in JUSThink Dialogue and Actions Corpus dataset includes dialogue transcripts, event logs, and test responses of children aged 9 through 12, as they participate in a robot-mediated human-human collaborative learning activity named JUSThink [1, 2], where children in teams of two solve a problem on graphs together. As a use case, it is processed to analyse how the children align their use of task-specific referents in their dialogue and actions (JUSThink Alignment Analysis) that is available from the Zenodo Repository, DOI: 10.5281/zenodo.4675070, and to produce the results and figures in [3]. <strong>2. Publications</strong> If you use this work in an academic context, please cite the following publications: Norman*, U., Dinkar*, T., Bruno, B., &amp; Clavel, C. (2022). Studying Alignment in a Collaborative Learning Activity via Automatic Methods: The Link Between What We Say and Do. Dialogue &amp; Discourse, 13(2), 1–48. *Contributed equally to this work. https://doi.org/10.5210/dad.2022.201 Nasir*, J., Norman*, U., Bruno, B., &amp; Dillenbourg, P. (2020). When Positive Perception of the Robot Has No Effect on Learning. 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 313–320. *Contributed equally to this work. https://doi.org/10.1109/RO-MAN47096.2020.9223343 Norman, Utku, Dinkar, Tanvi, Nasir, Jauwairia, Bruno, Barbara, Clavel, Chloé, &amp; Dillenbourg, Pierre. (2021). JUSThink Dialogue and Actions Corpus [Data set]. In Dialogue &amp; Discourse (v1.0.0, Vol. 13, Number 2, pp. 1–48). Zenodo. https://doi.org/10.5281/zenodo.4627104. <strong>3. Content</strong> The dataset is consisted of three parts: <strong>transcripts</strong>: anonymised dialogue transcripts for 10 teams of two children <strong>logs</strong>: anonymised event logs for 39 teams of two children <strong>test responses</strong>: pre-test and post-test responses for 39 teams, and the key i.e. the correct response In addition, there is metadata that contains information on the network that the children have worked on: <br> It is a JSON file in a node-link format, providing the node labels (e.g. "Mount Luzern"), node ids, x, y position of a node, edges between the nodes, and edge costs (metadata/network.json). It can be read into a NetworkX graph. <strong>2.1. Transcripts</strong> This part of the dataset contains the anonymised dialogue transcripts for 10 teams (out of 39 teams).<br> It consists of 10 files, with one tab-separated text file per team (transcripts/justhink19_transcript_&lt;team_no&gt;.csv).<br> In particular, the columns are: <em>team_no</em>: The number of the team that the dialogue belongs to <em>utterance_no</em>: The number of the utterance, starting from 0 <em>start</em>: The start timestamp of the utterance (in seconds), from the beginning of the activity <em>end</em>: The end timestamp of the utterance (in seconds) <em>interlocutor</em>: The person (or the robot) that is speaking (<em>A</em>, <em>B</em>: the participants; <em>R</em>: the robot; <em>I</em>: an experimenter) <em>utterance</em>: The content of the utterance Note that the start and end times are synchronised with the log times. <strong>3.2. Logs</strong> This part of the dataset contains anonymised event log data for 39 teams.<br> It consists of 39 files, with one tab-separated text file per team (logs/justhink19_log_&lt;team_no&gt;.csv).<br> In particular, the columns are: <em>team_no</em>: The number of the team that the event belongs to <em>attempt_no</em>: The attempt number that the event belongs to, starting from 1. An attempt is the duration of the team constructing a solution and submitting it together. <em>turn_no</em>: The turn number of the event, starting from 1. A turn is the duration where one of the participants is in figurative view, and the other is in abstract view (see [2] for a description of the views) <em>event_no</em>: The event number of the event, starting from 1 <em>time</em>: The logging timestamp of the event from the beginning of the activity (in seconds) <em>subject</em>: The person (or the robot, or the team) that the event is executed by (A, B: the participants; R: the robot; T: the team) <em>verb</em>: The verb that describes the event (e.g. "presses", "adds", "removes") <em>object</em>: The object that is acted on by the subject performing the verb (e.g. "submit (enabled)" for subject: A, verb: "presses") <strong>3.3. Test Responses</strong> This part of the dataset contains the responses of each participant in each team to the pre-test and post-test for 39 teams. <br> Each test contains 10 multiple-choice (single answer) questions (i.e. items) with 3 options (recorded as 0, 1 or 2), and assesses a concept on spanning trees (see [2]).<br> It consists of two files: one comma-separated text file for the pre-test responses (test_responses/justhink19_pretest.csv) one comma-separated text file for the post-test responses (test_responses/justhink19_posttest.csv) In particular, the columns are: <em>team_no</em>: The number of the team, or "key" for the correct responses <em>q?_A</em>: The response of participant A to a particular item (among 10 items indexed from 1 to 10) <em>q?_B</em>: The response of participant B to a particular item See <strong>README.md</strong> for further details.<br> <strong>Acknowledgements</strong> This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 765955. Namely, the ANIMATAS Project.