Shayla Sharmin

h-index6
2papers
112citations

2 Papers

9.6HCJul 9
Neurophysiological Insights into Multimedia-based Education: A PRISMA-ScR Review of fNIRS in Game-Integrated Learning Systems

Shayla Sharmin, Gael Lucero-Palacios, Behdokht Kiafar et al.

Game-integrated learning systems (GILS) are a growing form of multimedia education. Brain-based evidence can help researchers and designers understand how GILS design choices shape how learners think and process information. This scoping review follows PRISMA-ScR and synthesizes 20 empirical studies (2014-2025) in which functional near-infrared spectroscopy (fNIRS) measured brain activity during GILS use. This corpus shows that fNIRS can capture brain responses across GILS platforms and game elements, and points to how neurophysiological evidence can inform multimedia design decisions, such as that different platforms activate different brain regions, that adaptive difficulty reduces cognitive load and improves performance simultaneously, and that collaborative gameplay predicts knowledge retention. The 20 studies in this corpus reflect a field with substantial room to grow. Causal links between brain activation and learning outcomes would give designers more reliable evidence for platform decisions. As fNIRS and multimedia devices improve, standardized methods, classroom settings, and real-time neural adaptation represent directions where future work can translate these findings into practical multimedia learning systems.

1.3HCJul 10
Indirect and Direct AI Scaffolding for Computational Problem Posing: A Pilot Experience Report

Shayla Sharmin, Mohammad Fahim Abrar, Mohammad Al-Ratrout et al.

Problem posing is a valuable learning activity in computing education, encouraging learners to actively construct, refine, and reflect on problems rather than simply solving them. This experience report presents the design and pilot deployment of two LLM-powered scaffolding systems for supporting problem posing across two computational scenarios with different levels of task openness. Both systems assessed student-generated problems using Bloom's Taxonomy-based criteria and applied the same assessment framework, differing only in output modality: one provided guiding questions (Indirect scaffolding), while the other offered worked examples (Direct scaffolding). We conducted a within-subjects, counterbalanced pilot study with 20 graduate students and collected problem-quality ratings, user-experience surveys, and post-session interviews. Our deployment showed that both systems supported problem refinement in complementary ways, each offering distinct benefits. Direct scaffolding produced greater immediate improvements, while interviews showed that participants valued Indirect scaffolding for promoting deeper reflection on their own problem design. Based on these findings, we suggest sequencing the two modalities by beginning with Indirect scaffolding to promote reflection, then shifting to Direct scaffolding when learners become stuck. These lessons offer an initial practical strategy for integrating LLM-based scaffolding into computing classrooms.