*** Data underlying the BSc thesis: Dynamically Transparent Ghost Instructors and Their Effect on Learning and Skill Retention in Virtual Reality Environments ***
Author: C.M.S. Visser
Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology


*** General Introduction ***
The bachelor thesis aimed to explore the effect that dynamically transparent ghost instructors can have on the learning and retention of skills in Virtual Reality environments. A ghost instructors is shown to the student as a semi-transparent ghost avatar superimposed on the student's avatar so that students may see and imitate the intended movement from a first-person perspective. The research contrasts the effect of statically transparent (constant transparency) ghost instructors with that of dynamically transparent (transparency depends on student performance) ghost instructors through a user study in which students were taught to trace a 3D curve in a virtual environment. 

The reason that the data is being published is to allow other researchers to use this data in their own research.


*** User Study Procedure ***
The user study was performed using the Unity application developed throughout the course of the research. The code can be found in the GitHub repository available at https://github.com/C-Hoek/thesis-vr-dynamic-ghost-instructors-2024. The experiment version is marked by a tag. This repository also includes the Python scripts used to analyse the data.

12 participants were recruited for the user study. They were evenly divided between a group taught by the dynamically transparent ghost instructor, and a group taught by the statically transparent ghost instructor. Participants wore a HTC Vive Pro 2 Head-Mounted Display (HMD) and used two Vive controllers to control the hands and (through inverse kinematics) the arms of the human avatar.

The experiment was divided into a training and a testing phase. The first 3 trials were identical for both groups. After the third trial, the dynamically transparent ghost avatar's transparency started to vary based on the student's performance. The ghost avatar was not visible in the test trials for either group. The user experiment followed the following general procedure:

1. Run the first 5 training trials.
	a. If the participant is from group A, tell them after trial 3 that they may now experience changes in transparency depending on how well they perform the motion.
2. Have the participants recite the alphabet from Z back to A repeatedly during a 1-minute break without wearing the HMD.
3. Run the last 5 training trials.
4. Have the participants attempt to solve 3 Sudoku puzzles during a 10-minute break without wearing the HMD.
5. Run the 3 test trials.


*** File structure ***
The dataset contains 12 sets of 13 log files. There is one log file for each trial that was run.
The file naming is based on the following: "UUID_TrialIndex" with an optional addition of "_ExtraInformation" where:
- "UUID" details the Version 4 Universally Unique Identifier assigned to a participant. All log files from the same participant are marked by the same UUID.
- "TrialIndex" details the 0-based trial number. The first training trial is thus trial 0, while the last testing trial is trial 12.
- "ExtraInformation" starts after the underscore following the trial index, and ends at the end of the file name. This field is used to describe deviations from the experiment procedure. Before using files with extra information added to their file name, make sure to consider if this data should be used for your analysis based on the difference in procedure. Not all important deviations can be fully represented in the file name due to the file name length limit. Make sure to keep this in mind.

Each log file consists of a partially-CSV-formatted header detailing information about the set of trials (e.g. dynamic or static, etc.) followed by CSV-formatted log messages. These log messages contain information about:
- The error between the student and ghost position based on the error calculation system of the code.
- The transparency of the ghost instructor. This is logged as an alpha value.
- The position of various ghost avatar parts and target positions.
- The position of various student avatar parts and target positions. The rotation of several parts is also included.
- Whether or not the trial was completed within the time limit.
- Trial statistics (e.g. time taken to complete the trial, the average error, and the task performance).

The files can safely be opened in a plain-text editor.


*** Extra Information Data ***
Out of the 3 sets of participants that were marked by extra information, two were not used for the analysis due to relatively large deviations from the experiment procedure, and are marked by "_not-use" (followed by an optional "d" due to the file name length limit) at the end of the Extra Information field. 


*** License ***
The collected data is released under a CC BY 4.0 license.