InnovPLUS 2020 Flame Awards
In 2020, Serious Games Asia and our partners clinched two InnovPLUS 2020 Flame Awards.
Partnering with the Singapore General Hospital and the National University of Singapore, the first award was to develop an intravenous cannulation training and assessment kit, By leveraging on game technology, microfluidic sensors and state-of-the art 3D printing, this kit can be used to assesses the dexterity skill of the learner.
The integrated approach serves as an innovative virtual medical training application to aid practitioners in training and mastering a task skill. In addition, the game-based assessments with massive un-curated data derived from behavioral outcome enables skills-based competency assessment models to be established.
This pedagogical approach can also be applied to lifelong training and development in other industries.
InnovPLUS 2020 Flame Awards
The second InnovPLUS 2020 Flame Awards, on addressing issues in the training and education industry, was a partnership with the Singapore University for Technology and Design and FX Media Internet.
In the ‘new COVID-19 normal’ world, the delivery of knowledge, skills and attitudes in tertiary and adult education are commonly conducted via online. However, these competency-based lessons are often un-interesting and do not yet have a cheat-proof, structured assessment system that is needed for tertiary-level home-based learning.
There needs to be a better strategy in developing online lessons – one that leverages on simulation game and virtual reality technology; is quickly adaptable to changing environment; and possesses an updated, well-structured assessment modality.
We have to go beyond standard online synchronous lectures and asynchronous video recordings, as they are exhausting and un-motivating for the learner. We are also limited in our mode of online assessment that currently includes MCQs and open-ended take home assignments.
A simulation games and VR content platform is proposed to address these issues. The platform allows the development, hosting and deployment of single and multiplayer games with a scalable game scenario builder. It will also be capable of leveraging on the aggregated learner game log data for analyses. This lays the foundation for adaptive and personalized learning algorithms to be developed and personal learning journeys mapped out for each learner, thus enhancing learning outcomes.
2019 | Learning Technology Adoption Grant (LTAG)
Together with SingHealth and Playware Studio, Serious Games Asia won the Learning Technology Adoption Grant (LTAG) from Skills Future SG in 2019,
This grant was awarded for the development of ten training & assessment games for SingHealth.
These training & assessments games are part of the effort in transforming our healthcare professionals into a modern skills-based workforce. The objectives of deploying these games in training are to:
- reduce training cost;
- increase workforce productivity;
- improve patient safety records; and
- establish a national standard for the deployment of immersive media training & development practices.
InnovPLUS 2018 Flame Awards
In 2018, Serious Games Asia LP was the solutionist appointed by the The Logistic Institute Asia Pacific @ National University of Singapore (NUS-TLIAP) and the team won the InnovPLUS Flame Award 2018.
The problem statement was to address the challenges of training personal in responsive humanitarian logistics in the critical and early phases of disaster relief operations.
A serious game entitled “72-hour Disaster Relief Game” was developed to teach learners how they can strategically pre-position stockpiles of relief supplies for the fastest response. Learners will also learn through the game how they can reduce the risk of supply starvation and increase efficiency of the supply logistics.
For the trainers, the game included a simple-to-use game authoring tool kit, allows them (who are not game developers) to code new mitigation strategies and gamify scenarios with an emphasis on learning points.
Watch Game Trailer
Alongside with the “72-Hour Disaster Relief Game”, we developed a predictive game analytics engine – GamesTrax – based on a deep learning model (LSTM) to predict the learner’s choices in the subsequent phases based on his/her choices and game metrics from the current and previous stages. This resulted in the “break point” that could be converted into game triggers to increase or decrease game difficulty where needed.