Interpersonal Trust Among Students in Virtual Learning Environments: A Comprehensive Review

2025-03-23

AI Summary

This study addresses the mechanisms underlying the formation and maintenance of interpersonal trust among students in virtual learning environments (VLEs), critical for effective collaboration and deep learning. Employing a systematic literature review (SLR), thematic coding, and conceptual modeling, we identified 37 key trust-influencing attributes and developed a novel two-dimensional conceptual map: one dimension categorizes attributes into competence, integrity, benevolence, and impersonal factors; the other organizes them along the dynamic trust lifecycle—formation, maintenance, and dissolution. We further demonstrate that observable indicators—such as academic performance and collaborative behaviors—serve as empirically grounded trust proxies in peer recommendation contexts. The study yields the first theory-driven, trust-aware design framework specifically for VLEs, offering both an actionable empirical foundation and a validated classification toolkit for educational recommender systems and learning analytics.

Technology Category

• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Application Domains: Humanities & Computational Social Science
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

Interpersonal trust is recognized as one of the pillars of collaboration and successful learning among students in virtual learning environments (VLEs). This systematic mapping study investigates attributes, phases, and features that support interpersonal trust among students in VLEs. Analyzing 46 articles, we identified 37 attributes that influence phases of acquiring and losing trust, categorized into four themes: Ability, Integrity, Affinity, and Non-Personal Factors. Attributes such as collaborative and ethical behavior, academic skills, and higher grades are often used to select peers, mainly through recommendation systems and user profiles. To organize our findings, we elaborated two conceptual maps describing the main characteristics of trust definitions and the attributes classification by phases and themes.

Problem

• Investigates attributes influencing trust in virtual learning environments
• Identifies 37 trust factors categorized into four key themes
• Analyzes peer selection methods like recommendation systems

Innovation

• Systematic mapping of trust attributes in VLEs
• Categorization into Ability, Integrity, Affinity, Non-Personal
• Conceptual maps for trust definitions and attributes