Industry-based PhD program

Cinglevue has partnered with Edith Cowan University (ECU) through their ‘Industry engagement’ program to provide scholarships to promising PhD students, where research students have the opportunity to work on projects that are aligned with our five broad areas of research interest during three years. It allows us to infuse fresh thinking, new ideas and different perspectives into our practices and solutions.

How does it work?

First and foremost, we seek PhD students whose interests are mutually aligned with ours. Someone who is incredibly passionate about research and making an impact and relentlessly eager to experiment – doing so unnaturally well. With demonstrable enthusiasm, engagement, critical thinking, self-motivation, creativity, curiosity, problem-solving skills, dogged perseverance, and a willingness to listen to advice and make changes.

You will be fully immersed in our organisation, and provided with support and tools throughout your journey to facilitate your success as we jointly develop solutions that enhance our Virtuoso platform.

The topic of the research is established between the industry partner, the student and ECU.

The industry partner provides an industry-based supervisor to work with the student, working in collaboration with the other(s) supervisor(s) from the educational institution.

Expressions of Interest are considered through Cinglevue, where a project outline and a prospective supervisor is required.

Industry-based PhD projects

Executive functions

Schema development

Capturing emotions

Executive functions

Assessing executive functions and problem-solving in students in an engaging and valid way

By Valeska Berg

From 2017, Edith Cowan University (ECU)

Supervisors

Shane Rogers and Mark McMahon from ECU, and Michael Garrett from Cinglevue.

This research focuses on the development of a child-friendly and engaging executive function measurement tool for students. With Cinglevue support, she has developed "eFun", an app with four games that are designed to measure executive functions and problem-solving in a fun and valid way.

Why is Valeska’s research important?

Executive functions are the foundation for learning. Therefore, knowing about children's executive function levels will facilitate the development of targets learning plans. Teachers will be able to access the outcome data of the app and directly integrate higher and lower executive function levels into learning interventions. For example, a child with a lower score on the working memory game might need more visual cues as reminders during the class.

Schema development

The effect of digitally supported schema development on middle school students’ problem-solving achievement

By Randa Siksek

From 2019, Edith Cowan University (ECU)

Supervisors

Mark McMahon and Kuki Singh from ECU and Michael Garret from Cinglevue.

Randa’s research is based on mathematical cognition and particular algebraic schemas. The aim is to develop features within Virtuoso that will support the measurement of schema development during learning and have this information at hand when suitable to enhance educational practice.

Why is Randa’s research important?

Grand theories of learning are too broad to operationalise effectively in the context of classrooms, provoking a paucity of transformation in secondary school education. Therefore, Randa’s research nurture the breadth and depth required to effectively investigate schema development to shape pedagogical innovation for supporting problem-solving and conceptual understanding.

Capturing emotions

Recognising educationally relevant emotions from captured video

By Yao Xia, from 2019

Edith Cowan University (ECU)

Supervisors

David Suter, Shams Islam and Zulqarnain Gilani from ECU and Michael Garret from Cinglevue

The aim of Yao’s research is to develop an AI system based on deep learning, which would be able to extract and learn multi-modal features from students facial, audio and textual data with the purpose to detect emotions that are closely related to educational learning activity.

Why is Yao’s research important?

Identify students’ emotion automatically would provide teachers with mindful insights, helping them to adopt more suitable teaching strategies to improve educational outcomes. For example, during an educational activity, students will generate a lot of spontaneous “records” from their facial expression, voice and language use. Their emotions would be hidden in these records, which would help the teacher to identify the student’s emotions and perform better next time or keep the activity.

Our PhD student’s experiences

“I started my Industry PhD with Cinglevue in 2017 and it has been an invaluable learning experience so far. The Industry PhD has allowed me to combine my passion for Education with Psychology. My PhD focuses on the development of a solution called ‘eFun’”. Valeska Berg.

“Cinglevue has given me the opportunity to be involved in collaborative projects with experts in psychology, software development, VR, AR and machine learning. The aggregate of these diverse experiences, helped me develop a greater appreciation for the wider perspectives on schema development in my PhD. I believe that industry-based PhD programs offer a solution to the gap between research and transformation. In my case, it has provided me with a tangible goal to enhance the lives of students and teachers in the classroom by becoming a valuable creator rather than a source of knowledge”. Randa Siksek.

“Artificial Intelligence will play a very important role in education and Cinglevue have seen it, being interested in a wide range of research topics, which would love to invest funds to support research. And this is the most attractive aspect to me and the reason why I believe Cinglevue is a research-driven and very foresighted company. Additionally, Cinglevue offers excellent group working circumstances, I got support from psychologists, experienced teachers and educational experts. People here are very friendly and supportive, which makes my PhD project going very well”. Yao Xia.