Avatars help improve soft skills

The following files contain all the data that was analyzed in this research manuscript: <br> ---------------------------- 1. Demographic_Information.xlsx ---------------------------- Contains Unique ID for each participant in the study, followed by their Gender, and Age (columns). <br> ---------------------------- 2. Simulation_Surveys.xlsx ---------------------------- Contains the survey data for each participant with UniqueID in the study Survey data is available for each simulation Scenario, labeled as Scenario 1, Scenario 2, Scenario 3, and Scenario 4. The specific scenarios themselves are referenced in the methods section of the research manuscript. For each Scenario, participant with UniqueID is assigned a "Survey-I1", "Survey-I2" and "Survey-P" score. See "SURVEY-I" and "SURVEY-P" in the methods sections of the research manuscript for details. <br> ---------------------------- 3. Simulation_Ratings.xlsx ---------------------------- Contains the Time &lt;&gt; Rating pairs of the IMPACT metric described in the methods section (see Rating Interface) of the research manuscript. Possible rating values are -1, 0, 1, 4, and 5 as described in the manuscript. For example: <br> respondent10 2021_09_13_15_16_12 Scenario 1 3 6 0 2 0 0 231.6319965 4 266.894006 1 <br> In this row, respondent 10 had a "positive event of interest" (4) at 231.63s into the conversation and had a transition from "neutral impact to positive impact" (1) at 266.89s. <br> In addition, this file contains the counts of the "positive", "negative', and "neutral" events labeled as PosEventCount NeuEventCount NegEventCount in the columns. Values 4 and 1 contribtue to PosEventCount, 0 contributes to "NeuEventCount" and values 5 and -1 contribute to "NegEventCount". <br> Finally, SURVEY-77 is a binary variable that is "TRUE" if both SURVEY-I1 and SURVEY-I2 are greater than or equal to 7, and "FALSE" otherwise. See research manuscript for details. <br> ---------------------------- 4. Simulation_Analysis.xlsx ---------------------------- Contains a full analysis of the data from the simulations: <br> ---------------------------- 1. IMPACT that the participant had on the avatar classified as Neg_Time, Neu_Time, Pos_Time This data shows the overall impact that the participant had on the avatar over the course of the interaction. In the example below, the participant had a "Neutral" impact on the avatar for ~71% of the time and a "Positive" impact on the avatar for ~29% of the time. <br> Neg_Time Neu_Time Pos_Time 0 0.71241837 0.28758163 <br> ---------------------------- 2. Confusion Matrix (not analyzed in the manuscript but available for future work): <br> LNegNeg LNegNeu LNegPos LNeuNeg LNeuNeu LNeuPos LPosNeg LPosNeu LPosPos <br> Participants watched a video of their own performance and rated themselves after each scenario. This is a confusion matrix that shows the agreement (or disagreement) between the participant and the avatar on a second by second basis over the course of the interaction. e.g. a count of 212 in LNegNeu indicates that there were 212s of the conversation where the Learner thought their were having a "Negative" impact on the avatar while the Avatar thought the participant was having a "Neutral" impact on them. <br> ---------------------------- 3. Condition (not analyzed in the manuscript but available for future work): <br> A: Participants were given feedback prior to watching their video B: Participants did not receive any feedback prior to watching their own video <br> ---------------------------- 4. Audio Statistics: <br> SS Spk: Indicates time spent speaking by the avatar during the conversation L Spk: Indicates time spent speaking by the participant during the conversation Both Spk: Indicates when there was overlapping speech between the avatar and the participant Session Length: Indicates length of the simulation / conversation <br> ---------------------------- 5. Raw MiScore: <br> An interpersonal effectiveness score computed by a mathematical function based on the various IMPACT parameters <br> /* ------------------------------ */