(Dataset ) 4PADAFE and Generative AI in MOOC

Published: 11 February 2025| Version 1 | DOI: 10.17632/875f3882xf.1
Contributor:
Patricia Acosta-Vargas

Description

The "4PADAFE and Generative AI in MOOC" dataset contains survey responses from 20 participants, detailing demographic data, study modality, and experiences using the 4PADAFE methodology and generative AI tools in MOOC design. It includes insights on instructional design, collaboration, skill development, and the impact of AI on educational innovation.

Files

Steps to reproduce

Steps to Reproduce the Dataset Analysis Access the Dataset Download the "4PADAFE and Generative AI in MOOC" dataset from the provided repository or data source. Load the Data Use Python (pandas) or Excel to open and explore the dataset. Check for missing or inconsistent data. Preprocess the Data Clean and format categorical variables (e.g., career, study modality, gender, and age range). Convert necessary fields into numerical values if required for analysis. Perform Descriptive Analysis Generate summary statistics (e.g., participant distribution by study modality, gender, and age). Visualize data using bar charts, pie charts, or heatmaps. Analyze the Impact of 4PADAFE and AI Identify patterns in MOOC instructional design using AI-based tools. Evaluate participant responses related to collaboration, learning experiences, and skill development. Interpret Results Compare findings with existing literature on AI in education and MOOC methodologies. Identify key insights regarding the effectiveness of generative AI tools in course creation. Report Findings Summarize observations and create a visual presentation of the results. Highlight trends and recommendations for future research or practical applications in MOOC design.

Institutions

Universidad de Las Americas

Categories

Massive Open Online Course, Artificial General Intelligence

Licence