The impact of gamification on learning outcomes: experiences from a Biomedical Engineering course
- URL: http://arxiv.org/abs/2509.06126v1
- Date: Sun, 07 Sep 2025 16:28:07 GMT
- Title: The impact of gamification on learning outcomes: experiences from a Biomedical Engineering course
- Authors: Gonzalo R. Ríos-Muñoz, Caterina Fuster-Barcelo, Arrate Muñoz-Barrutia,
- Abstract summary: This study examines the integration of digital tools in project-based learning within a Biomedical Engineering course.<n>Students highlighted increased engagement, enhanced teamwork, and clearer criteria for performance assessment.
- Score: 0.4697971908036153
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This study examines the integration of digital tools in project-based learning within a Biomedical Engineering course to enhance collaboration, transparency, and assessment fairness. Building on prior pilot experiences, we implemented a structured learning environment that combined experiment tracking, real-time collaboration, and peer-assessment practices. The intervention was deployed across two consecutive academic years, involving master's-level students in Biomedical Image Processing. Data were collected through project outcomes, peer-assessment rubrics, and student surveys. Results show that the integration of digital platforms supported accountability, improved the quality of collaborative work, and fostered greater equity in the evaluation process. Students highlighted increased engagement, enhanced teamwork, and clearer criteria for performance assessment. Faculty reported more efficient monitoring of progress and improved feedback practices. Despite challenges such as technical adoption and the need for instructor guidance, the study demonstrates the potential of structured tool integration to support active and transparent learning environments. Findings contribute to the broader discourse on digital pedagogy, offering a replicable model for higher education contexts in science and technology.
Related papers
- Impact of UK Postgraduate Student Experiences on Academic Performance in Blended Learning: A Data Analytics Approach [0.0527359582877518]
Blended learning has become a dominant educational model in higher education in the UK and worldwide.<n>This paper investigates the interaction between different dimensions of student learning experiences and academic achievement.
arXiv Detail & Related papers (2025-11-15T18:42:43Z) - Scaffolding Collaborative Learning in STEM: A Two-Year Evaluation of a Tool-Integrated Project-Based Methodology [0.0]
This study examines the integration of digital collaborative tools and structured peer evaluation in the Machine Learning for Health master's program.<n>The framework combines real-time programming with Google Colab, experiment tracking and reporting via Weights & Biases, and rubric-guided peer assessment.
arXiv Detail & Related papers (2025-09-02T14:18:52Z) - Enhancing Collaboration Through Google Workspace: Assessing and Strengthening Current Practices [55.2480439325792]
The aim is to evaluate Google Workspace's role in enhancing blended learning practices at the University of Makati.<n>The study found that Google Workspace and rated as "Very Effective" (mean score of 4.61) in promoting teamwork.<n>It is recommended to enhance user adoption through targeted training and improve offline capabilities.
arXiv Detail & Related papers (2025-05-15T11:18:25Z) - Closing the Evaluation Gap: Developing a Behavior-Oriented Framework for Assessing Virtual Teamwork Competency [6.169364905804677]
This study develops a behavior-oriented framework for assessing virtual teamwork competencies among engineering students.<n>Using focus group interviews combined with the Critical Incident Technique, the study identified three key dimensions.<n>The resulting framework provides a foundation for more effective assessment practices.
arXiv Detail & Related papers (2025-04-20T08:12:27Z) - Level Up Peer Review in Education: Investigating genAI-driven Gamification system and its influence on Peer Feedback Effectiveness [0.8087870525861938]
This paper introduces Socratique, a gamified peer-assessment platform integrated with Generative AI (GenAI) assistance.<n>By incorporating game elements, Socratique aims to motivate students to provide more feedback.<n>Students in the treatment group provided significantly more voluntary feedback, with higher scores on clarity, relevance, and specificity.
arXiv Detail & Related papers (2025-04-03T18:30:25Z) - Assessing Teamwork Dynamics in Software Development Projects [2.823770863747379]
This study investigates teamwork dynamics in student software development projects through a mixed-method approach.<n>We analyzed individual contributions across six project phases, comparing self-reported and actual contributions to measure discrepancies.<n>Findings reveal that teams with minimal contribution discrepancies achieved higher project grades and exam pass rates.
arXiv Detail & Related papers (2025-01-21T08:23:46Z) - Benchopt: Reproducible, efficient and collaborative optimization
benchmarks [67.29240500171532]
Benchopt is a framework to automate, reproduce and publish optimization benchmarks in machine learning.
Benchopt simplifies benchmarking for the community by providing an off-the-shelf tool for running, sharing and extending experiments.
arXiv Detail & Related papers (2022-06-27T16:19:24Z) - LENAS: Learning-based Neural Architecture Search and Ensemble for 3D Radiotherapy Dose Prediction [42.38793195337463]
We propose a novel learning-based ensemble approach named LENAS, which integrates neural architecture search with knowledge distillation for 3D radiotherapy dose prediction.
Our approach starts by exhaustively searching each block from an enormous architecture space to identify multiple architectures that exhibit promising performance.
To mitigate the complexity introduced by the model ensemble, we adopt the teacher-student paradigm, leveraging the diverse outputs from multiple learned networks as supervisory signals.
arXiv Detail & Related papers (2021-06-12T10:08:52Z) - Scaling up Search Engine Audits: Practical Insights for Algorithm
Auditing [68.8204255655161]
We set up experiments for eight search engines with hundreds of virtual agents placed in different regions.
We demonstrate the successful performance of our research infrastructure across multiple data collections.
We conclude that virtual agents are a promising venue for monitoring the performance of algorithms across long periods of time.
arXiv Detail & Related papers (2021-06-10T15:49:58Z) - Canvas Adoption Assessment and Acceptance of the Learning Management
System on a Web-Based Platform [0.0]
This study aims to assess student adoption of Canvas as a new learning management system and its potential as a web-based platform in the e-learning programme of the University of the East.
The students perceived ease of use has a significant effect on their perceived usefulness but has no significant effects on their attitude towards the use of Canvas.
arXiv Detail & Related papers (2021-01-29T01:30:55Z) - Collaborative Group Learning [42.31194030839819]
Collaborative learning has successfully applied knowledge transfer to guide a pool of small student networks towards robust local minima.
Previous approaches typically struggle with drastically aggravated student homogenization when the number of students rises.
We propose Collaborative Group Learning, an efficient framework that aims to diversify the feature representation and conduct an effective regularization.
arXiv Detail & Related papers (2020-09-16T14:34:39Z) - Transfer Heterogeneous Knowledge Among Peer-to-Peer Teammates: A Model
Distillation Approach [55.83558520598304]
We propose a brand new solution to reuse experiences and transfer value functions among multiple students via model distillation.
We also describe how to design an efficient communication protocol to exploit heterogeneous knowledge.
Our proposed framework, namely Learning and Teaching Categorical Reinforcement, shows promising performance on stabilizing and accelerating learning progress.
arXiv Detail & Related papers (2020-02-06T11:31:04Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.