Workshop
Citation
Smith, H., Castro, F., Lacera, L. P., & Arroyo, I. (2021). The Wearable Learning Cloud Platform. Workshop presented at the Learning Analytics and Knowledge (LAK) 2021 Conference.
Project Overview
The Wearable Learning Cloud Platform (WLCP) is a research-driven learning analytics platform designed to support the creation, deployment, and analysis of educational games that integrate physical interaction, collaboration, and computational thinking.
This workshop paper introduced WLCP as a system for capturing fine-grained learner interaction data during game creation and gameplay, with the goal of better understanding how students demonstrate computational thinking, content knowledge, engagement, and collaboration in authentic learning contexts.
This workshop paper introduced WLCP as a system for capturing fine-grained learner interaction data during game creation and gameplay, with the goal of better understanding how students demonstrate computational thinking, content knowledge, engagement, and collaboration in authentic learning contexts.
My Role
- Contributed to platform design discussions focused on learning analytics and data capture
- Supported the conceptualization of log-based behavioral indicators for computational thinking
- Participated in workshop preparation and scholarly discussion
- Co-presented the platform and open research questions at LAK 2021
Platform Description
The Wearable Learning Cloud Platform enables learners to:
- Create games by designing states, transitions, and connections
- Play and collaborate within games that incorporate physical movement and interaction
- Generate log data capturing both creation and gameplay behaviors
Logged Data Includes
- Creation, deletion, and modification of game states and transitions
- Content edits within game elements
- Player navigation and movement through game states
- (Planned) gameplay interactions such as hint usage, correctness, and state visitation
Research Focus
The workshop centered on how WLCP data can be used to address key learning analytics questions, including:
- How computational thinking skills (e.g., sequencing, decomposition, systems thinking) can be observed through game creation and play
- How interaction log data can serve as indicators of student content knowledge
- Whether log data can function as a proxy or supplement for traditional assessments
- How engagement and collaboration can be measured using multimodal data sources
Analytical Perspective
Rather than presenting finalized results, this workshop positioned WLCP as a research infrastructure, inviting discussion around:
- Construction of behavioral indicators from log data
- Integration of multimodal data (physical interactions, in-game actions, assessments)
- Ethical and methodological considerations in learning analytics research
Why This Matters
This work contributes to the learning analytics community by:
- Advancing data-rich platforms for studying learning in interactive, embodied contexts
- Highlighting the potential of process data to reveal learning that traditional assessments miss
- Supporting the design of analytics-informed educational technologies grounded in theory
The WLCP aligns with broader efforts to move learning analytics beyond static outcomes toward dynamic models of learner behavior and cognition.
Skills Demonstrated
- Learning analytics and educational data modeling
- Platform-level thinking for data collection and analysis
- Research design for game-based and embodied learning
- Interdisciplinary collaboration (education, computer science, analytics)
- Scholarly communication in workshop settings