Skip to content
#small language model Open access

Supporting metacognitive awareness through AR-assisted ASICC worksheets on the respiratory system

Oct 2026 · Research and Development in Education (RaDEn)
Innovative Teaching and Learning Methods

Abstract

Background-Students’ metacognitive awareness remains a challenge in biology learning, including the respiratory system. Objectives- This study aimed to develop AR-assisted ASICC worksheets and examine metacognitive awareness and skills. Methods-The study employed Educational Design Research using the Plomp model. Feasibility was evaluated through expert validation, one-to-one, and small-group evaluation, while metacognitive awareness were examined among 33 eleventh-grade students using a single-group pretest–posttest design. Metacognitive awareness was measured using the Metacognitive Awareness Inventory (MAI) and analyzed using Wilcoxon signed-rank tests, effect sizes, and N-Gain, whereas metacognitive skills were assessed using a Corebima rubric-based summative test. Results-The worksheets showed high validity (94.2% for material and language, 84.6% for media, and 86.61% for the practitioner) and high practicality (92.80% one-to-one; 91.03% small-group). MAI scores increased in eight subdimensions (Holm-adjusted p ≤ 0.039), with the largest effects for Comprehension Monitoring (r = 0.68), Declarative Knowledge (r = 0.59), and Planning (r = 0.58) and the smallest for Procedural Knowledge (r = 0.36), in which about half the students had reached the maximum pretest score. Spearman’s rank correlation indicated a significant but modest positive association between MAI posttest and summative scores (ρ = 0.404, p = 0.020). Conclusions-The worksheets were valid and practical, although findings require cautious interpretation within the single-group design.

Read PDF

Similar papers

#small language model Dataset Open access Oct 2026

Socratic guiding questions in synthetic arithmetic data: matched LoRA runs (revision v2)

Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...

O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al. · 465 citations
#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6

Related blog posts

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

Microsoft Research Blog Oct 15, 2026

Proof-based general-purpose computing with Magnetar

Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.