GenAI-LA-LD Survey Dataset – Educator Perceptions on Integration of Generative AI, Learning Analytics, and Learning Design
Description
Overview: This dataset was collected as part of a quantitative survey-based study conducted in higher education institutions in the UAE and India. The study explores educators' and instructional designers’ perceptions of integrating Generative AI (GenAI), Learning Analytics (LA), and Learning Design (LD) to inform educational decision-making and instructional improvement. Purpose: To validate the GenAI-LA-LD Synergy Framework and identify key predictors of adoption intent, usability, and institutional readiness for integrating GenAI, LA, and LD in higher education pedagogy. 📋 Data Collection Method: Online structured survey Participants: 312 respondents (university faculty and instructional designers) Countries: United Arab Emirates and India Timeframe: March–May 2025 Format: CSV/Excel compatible with Jamovi, SPSS, and R 📁 Variables Included Variable Name Description Type Scale Respondent_ID Unique anonymized ID per respondent Categorical Nominal Country Country of respondent (UAE or India) Categorical Nominal DigitalConfidence Confidence in using digital tools Numeric 1–5 Likert InstitutionalTraining Perception of institutional training and support Numeric 1–5 Likert PedagogicalAlignment Degree of alignment between GenAI/LA tools and pedagogy Numeric 1–5 Likert PerceivedUsefulness Usefulness of GenAI and LA tools for instruction Numeric 1–5 Likert EaseOfIntegration Ease of integrating these tools in teaching workflows Numeric 1–5 Likert EthicalConcerns Concern about ethics, privacy, and responsible AI use Numeric 1–5 Likert IntentionToAdopt Likelihood of adopting GenAI-LA-LD integration in future practices Numeric 1–5 Likert 📊 Use Cases for Analysis Descriptive statistics and visualization Reliability analysis (Cronbach’s alpha) Correlation and multiple regression One-way ANOVA for country-based comparisons Factor analysis and validation of the GenAI-LA-LD Synergy model 🧪 Potential Applications Policy research on AI in education Learning design innovation tracking Faculty development and digital readiness assessment Comparative studies between countries or institutions