Dr Thushari Atapattu

Research Associate
Dr Thushari Atapattu
  Org Unit School of Computer Science
  Email thushari.atapattu@adelaide.edu.au
  Telephone +61 8 8313 9077
  Location Floor/Room 4 46 ,  Ingkarni Wardli ,   North Terrace

2015- : Postdoctoral Research Fellow, School of Computer Science, University of Adelaide

2011-2014: PhD in Computer Science, University of Adelaide

2010-2011: Software Engineer

2008-2009: Research Assistant, University of Colombo School of Computing

2004-2008: Bachelor of Computer Science (Hons), University of Colombo

2017: Adelaide Women's Research Excellence Award

2015: Dean's Commendation for Doctoral Thesis Excellence

2013: Finalist for Google Anita Borg scholarship (PhD category in Asia-Pacific Region)

2012: Google PhD Travel Award

2011: University of Adelaide PhD Scholarship

I will be teaching following courses;

2017 (Semester 1): COMP SCI 7098 - Master of Computing & Innovation Project

2017 (Semester 2): COMP SCI 1106 - Introduction to Software Engineering

  • Data Science - In particular, I am more experienced in 'Learning Analytics' and 'Large scale Text Mining'

Currently, I am focusing on discourse analysis at large scale, particularly from Massive Open Online Courses (MOOCs). 

  • Natural Language Processing - Both theory and applications of NLP

  • Computer Science Education - Read more about our CSER work here

  • Knowledge Representation - In particular, I am experienced in 'Ontology learning' and 'Concept Map Mining' and I have strong interests on Data Visualisation

  • Neuroscience Education - In particular, I am intereted in applying Neuroscience to improve programming skills

For potential students (Honours, Masters and PhD):

If you have a passion for any of the above areas and would like to pursue higher studies in the University of Adelaide, feel free to email me with your current CV, transcripts of all degrees and a statement about your research interest.

Some information about Postgraduate scholarship (domestic and international) can be found here


Current HDR/Research students

Menasha Thilakaratne (PhD) with Katrina Falkner - Natural Language Processing techniques for learning at scale, 2017-2020

Roland Croft (Topics in Computer Science) with Christoph Treude, Identifying the topics of Stack Overflow discussions, 2017

K. Falkner, R. Vivian and T. Atapattu, Understanding the relationship between social community formation and progression within MOOC environments, Research Contract, Google Australia, $37,687 (2017).


Atapattu, T., Falkner, K. and Falkner, N. A Comprehensive text analysis of Lecture Slides to Generate Concept Maps. Computers & Education, 115, pp. 96-113, December 2017

Atapattu, T., Falkner, K. Discourse analysis to improve the effective engagement of MOOC videos. Accepted for the 7th International Learning Analytics and Knowledge conference (LAK), Vancouver, BC, Canada, March 2017


Atapattu, T., Falkner, K. and Tarmazdi, H. Topic-wise classification of MOOC discussions: A visual analytics approach. Proceedings of the 9th International conference on Educational Data Mining (EDM), Raleigh, NC, USA, June 2016

Atapattu, T., Falkner, K. A Framework for Topic Generation and Labeling from MOOC Discussions. Proceedings of the Third Annual ACM Conference on Learning at Scale (L@S), Edinburgh, Scotland, April 2016


Atapattu, T., Falkner, K. and Falkner, N. Educational Question Answering Motivated by Question-specific Concept Maps. Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED), Madrid, Spain, June 2015 (Nominated for Best Paper Award)

Atapattu, T., Falkner, K. and Falkner, N. Task-adapted Concept Map Scaffolding to Support Quizzes in an Online Environment. Proceedings of the 20th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), Vilnius, Lithuania, July 2015

Atapattu, T., Falkner, K. and Falkner, N. An Evaluation Methodology for Concept Maps Mined from Lecture Notes: An Educational Perspective. Communications in Computer and Information Science (CCIS), 510, pp, 68-83, Springer International Publishing, 2015 (Book Chapter)


Atapattu, T., Falkner, K. and Falkner, N. Acquisition of Triples of Knowledge from Lecture Notes: A Natural Language Processing approach. Proceedings of the 7th International conference on Educational Data Mining (EDM), London, July 2014

Atapattu, T., Falkner, K. and Falkner, N. Evaluation of Concept Importance in Concept Maps Mined from Lecture Notes: Computer vs Human. Proceedings of the 6th International Conference on Computer Supported Education, Barcelona, Spain, April 2014 (Nominated for Best Student Paper Award)


Atapattu, T. Automated Generation of Practice Questions from Semi-Structured Lecture Notes. ICER' 12, Auckland, New Zealand, Sep 2012 (Doctoral abstract)

Atapattu, T., Falkner, K. and Falkner, N. Automated Extraction of Semantic Concepts From Semi-Structured Data: Supporting Computer-based Education through the Analysis of Lecture Notes. Dexa 2012, Vienna, Austria, Sep 2012


Atapattu, T., De Zoysa, K. Accessing an Interactive learning tool using telephone communications. In the proceedings of the ICT2010, Singapore, June 2010


Atapattu, T., De Zoysa, K. V-Learning: Using voice for Distant Learning in Emerging Regions. In the proceedings of the International conference on Computer Supported Education, Lisboa, Portugal, March 2009


Unpublished works

Atapattu, T., Falkner, K., Falkner, N. and Palmer, E. 2015. A computational model for task-adapted knowledge organisation: improving learning through concept maps extracted from lecture slides, University of Adelaide, Australia (PhD thesis)


Association for Computer Linguistics (ACL)

International Artificial Intelligence in Education Society (IAIED)

Society for Learning Analytics Research (SOLAR)

International Educational Data Mining Society (IEDM)


Co-developer and co-instructor for the CSER Digital technologies MOOC (Next steps) for Years 7-8

Committee member of Higher Education Research Group of Adelaide (HERGA)

Member of Google Anita Borg Alumni community

Member of Learning Analytics Community of Practice - University of Adelaide

Committee member of Learning Analytics Operations Group (LAOG) - University of Adelaide

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Entry last updated: Friday, 13 Oct 2017

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