Holistic learning environments, human–AI collaborative learning, and learner development in Vietnamese higher education: A higher-order PLS-SEM approach

Description

This dataset contains quantitative survey data collected for the study entitled “Holistic learning environments, human–AI collaborative learning, and learner development in Vietnamese higher education: A higher-order PLS-SEM approach.”

The dataset was developed to examine structural relationships among Holistic Learning Environment (HLE), Human–AI Collaborative Learning (HACL), Learner Agency (LA), AI Literacy (AIL), and Holistic Student Development (HSD) within Vietnamese higher education contexts.

The study employed a cross-sectional quantitative research design and applied higher-order Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate how human-centered educational ecosystems and collaborative AI-supported learning processes contribute toward holistic learner development in contemporary university environments.

Data Collection

Data were collected from December 2025 to May 2026 through online survey administration procedures across Vietnamese higher education institutions. The questionnaire was distributed through institutional learning management systems, classroom communication channels, and lecturer-supported recruitment networks. Participation remained voluntary, and incomplete responses were removed before statistical analysis.

The final dataset includes responses from 682 undergraduate students representing multiple academic disciplines, including Education, Social Sciences, STEM, Business, Health Sciences, and Humanities. Female students represented the largest proportion of participants (58.65%), while Year 2 and Year 3 students demonstrated relatively balanced representation across the sample.

Dataset Structure

The dataset contains variables associated with five major constructs:

Holistic Learning Environment (HLE)

Human–AI Collaborative Learning (HACL)

Learner Agency (LA)

Holistic Student Development (HSD)

AI Literacy (AIL)

Holistic Learning Environment and Human–AI Collaborative Learning were conceptualized as reflective–reflective higher-order constructs within the proposed framework.

Higher-Order Constructs

Holistic Learning Environment (HLE) includes:

Human-Centered Pedagogy (HCP)

Socio-Emotional Support (SES)

Inclusive Learning Climate (ILC)

Ethical Learning Governance (ELG)

Flexible Learning Support (FLS)

Human–AI Collaborative Learning (HACL) includes:

AI-Assisted Learning Support (ALS)

Reflective AI Interaction (RAI)

AI-Supported Self-Regulation (ASR)

Human Oversight and Control (HOC)

AI-Enabled Collaborative Inquiry (ACI)

Additional reflective constructs include:

Learner Agency (LA)

Holistic Student Development (HSD)

AI Literacy (AIL)

Measurement Information

All questionnaire items employed a 7-point Likert scale ranging from:1 = strongly disagreeto7 = strongly agree.

Measurement items were adapted from established international frameworks and scales related to learning environments, learner agency, self-regulated learning, wellbeing, and AI literacy. Major measurement sources included Cornelius-White (2007), Zimmerman (2002), Bandura (2006), Butler and Kern (2016), Long and Magerko (2020), Ng et al. (2021), and Atchley et al. (2024).

Data Analysis

Data analysis was conducted using SmartPLS 4. Analytical procedures included:

Indicator reliability assessment

Internal consistency reliability analysis

Convergent validity assessment

Discriminant validity assessment

Collinearity diagnostics

Higher-order construct modeling

Structural model assessment

Effect size analysis

Indirect effects analysis

Predictive relevance assessment

PLSpredict evaluation

Bootstrapping procedures employed 5,000 resamples for significance testing and predictive evaluation.

Research Applications

The dataset supports:

Higher-order PLS-SEM methodological applications

AI in education research

Human-centered learning ecosystem research

Learner agency and self-regulated learning studies

Holistic learner development research

Digital transformation research in higher education

Comparative higher education analysis within AI-supported educational contexts

The dataset may also support secondary analysis related to learner autonomy, ethical AI engagement, collaborative AI learning, and sustainable higher education ecosystems in Global South contexts.