Welcome to HINA Workshop!

While learning analytics has advanced our ability to capture complex learning processes, methodological advancement is key in the field. This workshop will introduce a new learning analytics tool — HINA (Heterogeneous Interaction Network Analysis). 

HINA offers a flexible technical solution to model and analyze interactions across diverse entities (e.g., students, behaviors, artefacts) as networked relationships. By transforming multimodal learning data into heterogeneous interaction networks (HINs), HINA enables researchers to uncover hidden patterns, test theoretical assumptions, and generate actionable insights about how learning unfolds.

This half-day workshop consists of two parts: 

• a hands-on tutorial introducing the HINA web tool together with its methodological foundations, empowering participants to apply network analytic techniques to their own learning datasets. 

• an interactive session, showcasing empirical applications through invited presentations, demonstrating HINA’s utility across contexts (e.g., collaborative problem solving, self-regulated learning, human-AI interactions). It will also feature lightning talks to spark discussion on new datasets and collaborations, concluding with a collaborative discussion about future directions for learning analytic tools’ development and adoption.

In this workshop, participants will gain the skills to analyze complex learning interactions using HINA, a versatile open-source tool specifically designed for learning analytics research. Participants will leave with practical, hands-on experience in network analysis and new connections to drive their own methodological research forward. 

We are excited to meet you, receive your contributions, and collaborate to advance learning analytics research together! 

Organizing Committee: 

Shihui Feng (University of Hong Kong, Hong Kong)

Baiyue He (University of Hong Kong, Hong Kong)

Mutlu Cukurova (University College London, UK)  

Dragan Gasevic (Monash University, Australia) 

Inquires about the workshop, please contact Shihui Feng, shihuife@hku.hk 

Featured Presentations 

💎 Kester Yew Chong Wong, University College London

Title: Uncovering the Structural Effects of Scaffolding in Collaborative Problem Solving Processes using HINA

Collaborative Problem Solving (CPS) is a dynamic process between individuals and other members of the collective group involving concurrent engagement of cognitive, social, and affective domains of collaboration. Different studies have examined the impact of various forms of scaffolding to support learners during CPS. Here, we discuss the value of Heterogeneous Interaction Network Analysis (HINA) for expanding the range of methodological approaches that can be used to analyse CPS processes. In particular, the presentation will provide a practical demonstration on how HINA can be performed to analyse students' engagement and behaviours at the individual level in each distinct problem solving phase of CPS.

💎 Tongguang Li & Linxuan Zhao, Monash University 

Title: Understanding Students’ Self-regulation Processes in GAI-powered Adaptive Scaffolding using HINA 

Self-regulated learning (SRL) involves the control, monitoring, and regulation of cognitive and metacognitive processes, such as planning, self-evaluation, and self-reflection. However, effectively implementing SRL strategies can be challenging for students due to the complex interplay among these learning processes. To address this, researchers have developed SRL scaffolds to support learners in acquiring these skills. This talk will introduce a study that uses Heterogeneity Interaction Network Analysis (HINA) to examine how GAI-powered scaffold leads to different SRL processes at the individual level. Additionally, it will demonstrate how dyadic-level HINA can identify distinct SRL patterns across different condition groups, offering valuable insights for designing future SRL scaffolds.