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OpenNeuro dataset - NeuroTechs Dataset for Stem Skills
OpenNeuroDatasets/ds006803
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# README
## Details related to access to the data]
- [ ] Contact person
Juan Pablo Rosado Aíza jprosadoa@gmail.com
ORCID 0009-0004-5690-1753
- [ ] Practical information to access the data
The data units are in microvolts, transformed from raw Unicorn API for Python values.
## Overview
Evaluating STEM skills in students
- [ ] Year(s) that the project ran
2025 May - July
- [ ] Brief overview of the tasks in the experiment
Participants answered a computer test through psychopy. The paradigm includes a 2 minute basal state (minute 1 with eyes closed, minute 2 with eyes open) and sections for each skill evaluated. 4 math sections, 1 per basic operation (sum, subtraction, multiplication and division), 1 programming section and 1 spatial ability section. The sections ran until either time or questions ran out. There was a 30 second break between sections.
The event markers with each question, answer and time can be found within each subject folder. The point of the paradigm is to compare different class groups and their global performance. The point of the EEG data is to image the brain for potential analysis of band activity to help explain differences in the groups. the experimental group took classes using interactive tools like Google Colab during class.
- [ ] Description of the contents of the dataset
8 Channel EEG data for 63 subjects, 23 experimental "intervention" subjects and 40 control subjects. You can find both raw (Session 1) and preprocessed (Session 2) data. All EEG data starts at second 3, since seconds (0-3) were cut in preprocessing. The timestamps in all event markers are in this time signature (Timestamp in second 3 corresponds to sample 1, second 4 is sample 251).
- [ ] Independent variables
Groups for the subjects.
- [ ] Dependent variables
Performance, EEG data.
- [ ] Control variables
Time of participation (End of semester), place for data acquisition, status as student.
## Methods
### Subjects
All subjects are either experimental or control, whose ID is in the format XXc for control and XXe for experimental.
[ ] Subject inclusion/exclusion criteria (if relevant)
Only students enrolled in the course at hand.
### Apparatus
the room was performed in a closed room with a single researcher there to give instructions and answer any questions. There was a laptop and the EEG device was mounted using conductive gel.
### Initial setup
Signing consent on paper was the first thing that was done, afterwards impedance measurements using UHB recorder software were made until all signals were "good" on the sofware.
The subjects then answered the test.
### Task organization
The test's sections are not randomized nor counterbalanced, the order is as described above. The questions within each section were randomized.
### Task details
Each question answered has a code, an answer and a timestamp, which can be found in the corresponding main section file for each subject. The questions themselves with codes and correct answers can be found in the stimuli folder.
Due to a programming quirk the first programming and first spatial ability question appearance time is lost, it should be calculated from the final answer time of a given previous section plus 30 seconds. Afterwards, the answer time for each given question is found under "question time" and the question appearance time for any given next question is under "Answer time" for the previous question. This discrepancy shall be fixed in the next release.
### Additional data acquired
Average cycle data for female subjects was calculated for each group, anonymously.
### Experimental location
All data collection was collected in a controlled environment.
### Missing data
Subject 17c, 30e, 32e and 35e where lost in the process of acquisition. All records start at second 3, instead of second 0, to eliminate connectivity noise and drift at the beginning. The basal state lasted 123 seconds to account for this, so the first 120 seconds correspond to the basal states. About
OpenNeuro dataset - NeuroTechs Dataset for Stem Skills
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