Dr Eduardo Oliveira

I am a Senior Lecturer in the School of Computing and Information Systems at the University of Melbourne. I hold Masters and PhD in Computer Science from Federal University of Pernambuco (Brazil). Since the beginning of my teaching career I have been actively building relationship and working with universities, technology clusters, innovation institutes, governmental agencies and private companies to promote authentic and innovative teaching and learning practices. In 2022 I was the winner of the Faculty of Engineering and Information Systems (FEIT) Excellence Award in Teaching and Learning – The Kelvin Medal; in 2023 I was awarded the University-wide Edward Brown Award for Teaching Excellence. In 2024, I was awarded the University of Melbourne GEM Scott Teaching Fellowship. This prestigious and competitive award recognises the University of Melbourne’s distinguished educational leaders and is based on a program of work.

During my scientific studies initiated in 2006, I worked together with computer scientists, designers, educators and psychologists in educational contexts. My work was (and is) focused on teaching and conducting research in artificial intelligence applied in online learning and in engineering education. In 2013, my PhD was awarded Best PhD Thesis according to the Brazilian Computer Society (SBC) in Congress on Computers in Education.

I have been working with and researching the use of artificial intelligence applied in online teaching and learning together with the Melbourne School of Education, the Assessment Research Centre and the Melbourne Centre for the Study of Higher Education since 2016. My expertise is in the use of artificial intelligence to model and assist tertiary students on digital learning environments. I use machine learning and natural language processing combined with models of self-regulated learning to guide my research. I am particularly interested in: (i) understanding how tertiary students learn independently and how/when we can best support them; (ii) supporting tertiary students’ technical and professional skills development through evidence-based explainable AI; (iii) exploring the use of authorship verification/stylometry methods in academic integrity. My research approach is mainly (but not limited to) quantitative, combining the use of learning analytics with self-reported surveys. My most recent publications in Q1 journals were focused on the use of learning analytics and artificial intelligence to monitor and/or support students' performance in online environments. 

Parallel to my research, I worked for 12 years as a Specialist System Engineer and Technical Consultant at CESAR (Recife-Pernambuco/Brazil), awarded two times as the most Innovative IT Institute in Brazil, researching/leading/developing for Motorola, Samsung, Compal Electronics, Gemalto and other international projects. 

Some research projects for prospective PhD, MPhil and Masters students include:

• Artificial Intelligence and Education

1. Employability skills: closing the gap between academia and industry through personalized student journey maps 

2. Goal-oriented Dashboard to Motivate Online Learning in Canvas Learning Management Systems (LMS) 

3. Academic Integrity Writing Analysis

4. Authorship Verification and LLM 

5. Smart Learning Environments

• Software Engineering and Engineering Education

1. Motivational Model Editor Tool

2. Requirements validation and motivational models

3. User-Centred Software Design: Using Motivational Models for Teaching and Validating Requirements in Software Engineering Subjects  

4. Software Engineering and Employability Skills

For PhD supervision enquiries, please apply here: Request for Supervision