Peer-reviewed articles (journals and conferences):

  1. Petritsopoulou, M., & Karunaratne, T. (2021). Yes! I want my non-cognitive skills to be improved: perceptions on an ICT-enabled learning journey. Emerging Technologies in learning, Skills and Work-based Learning (in press).
  2. Karunaratne, T. (2021). For Learning Analytics to Be Sustainable under GDPR—Consequences and Way Forward. Sustainability, 13(20), 11524; https://doi.org/10.3390/su132011524
  3. Petritsopoulou, M., Karunaratne, T., & Glinos, M. (2020). The learner’s perceptions of an integrated system for learning management of non-cognitive skills. Kidmore End: Academic Conferences International Limited. http://dx.doi.org.ezp.sub.su.se/10.34190/EEL.20.110
  4. Gjøystdal S., Karunaratne T.  (2020). Effect of inadequate self-organized teams in Agile project management- a case study from the oil and gas industry. International Journal of IT Project Management: 11(3), Article 6
  5. Bergdahl, N., Nouri, J., Karunaratne, T., Afzaal, M.& Saqr, M. (2020). Learning Analytics for Blended Learning – A Systematic Review of Theory, Methodology, and Ethical Considerations. International journal of learning analytics and artificial intelligence for education, 2(2), pp.46-79.
  6. Karunaratne, T., & Mobini, P. (2019). Formal education as lifelong learning for working professionals: a case study. 18th European Conference on e-Learning (ECEL19)
  7. Karunaratne, T., Zhemcugova, H., Byungura, J., & Olsson, U. (2019). Towards an agile-based process model for effective teacher training on e-learning environments. 18th European Conference on eLearning (ECEL19)
  8. Apiola, M., Karunaratne, T., Kaila, E., & Laakso, M. (2019). Experiences from digital learning and learning analytics in Finland and Sweden: A collaborative approach. MIPRO 2019; 42nd International Convention on Information and Communication Technology, Electronics and Mechatronics. IEEE.
  9. Mobini, P., & Karunaratne, T. (2019). Towards an ICT enabler for enhancing non-cognitive skills in a lifelong learning setting. 18th European Conference on e-Learning (ECEL19).
  10. Byungura, J., Hansson, H., & Masengesho, K. (2019). Plagiarism tendencies and contributing factors in e-Learning environments: Rwandan higher education context. 18th European Conference on eLearning. Copenhagen, Denmark: ACPIL.
  11. Karunaratne, T., Peiris, R., & Hanson, H. (2018). Implementing small scale projects in ICT for Development – how challenging is it? ijEDict – International Journal of Education and Development using Information and Communication Technology, 14, 118-140.
  12. Karunaratne, T. (2018). Blended supervision for thesis projects in higher education: a case study. Electronic Journal of e-learning, 16(2), 79-90.
  13. Karunaratne, T., Hansson, H., & Aghaee, N. (2017). The effect of multiple change processes on quality and completion rate of theses: A longitudinal study. Journal of Assessment in Education: Principles, Policy & Practice, 26(2), 184-201. DOI:10.1080/0969594X.2017.1303442
  14. Karunaratne, T., & Byungura, J. (2017). Using log data of virtual learning environments to examine the effectiveness of online learning for teacher education in Rwanda. In P. Cunningham, & M. Cunningham (Ed.), IST-Africa (pp. 1-12). IIM. DOI:10.23919/ISTAFRICA.2017.8102410
  15. Karunaratne, T., Hansson, H., & Holmberg, S. (2017). Global Idea Bank – Solving Real Issues: University Collaboration with the Wider Society. Proceedings of the 26th Annual EDEN Conference. Jönköping, Sweden.
  16. Aghaee, N., Karunaratne, T., Smedbeg, Å., Jobe, W., Hansson, H., & Tedre, M. (2016). Interaction Gaps in PhD Education and ICT as a Way Forward: Results from a Study in Sweden. International Review of Research in Open and Distributed Learning (IRRODL), 17(3), 360-383. doi:http://dx.doi.org/10.19173/irrodl.v17i3.2220
  17. Byungura, J., Hansson, H., Masengesho, K., & Karunaratne, T. (2016). ICT Capacity Building: A Critical Discourse Analysis of Rwandan Policies from Higher Education Perspective. European Journal of Open, Distance and ELearning (EURODL), 19(2), 46-62.
  18. Van Jaarsveldt, L., Aghaee, N., & Karunaratne, T. (2015). What is a PhD degree? An international and comparative study of Sweden, Sri Lanka and South Africa. Fifth Biennial Conference on Research into postgraduate supervision. Stellenbosch University.
  19. Aghaee, N., Karunaratne, T., Smedbeg, Å., & Jobe, W. (2015). Communication and Collaboration Gaps among PhD Students and ICT as a Way Forward: Results from a Study in Sweden. Proceedings of E-Learn: World Conference on ELearning in Corporate, Government, Healthcare, and Higher Education, (pp. 237-244).
  20. Byungura, J., Hansson, H., & Karunaratne, T. (2015). User Perceptions on Relevance of a Learning Management System: An Evaluation of Behavioral Intention and Usage of SciPro System at University of Rwanda. EDEN 2015 Annual Conference. Barcelona, Spain.
  21. Aghaee, N., Karunaratne, T., Smedberg, Å., & Jobe, W. (2014). 2014. ICT for Communication and Collaborative Learning among PhD peers: Results of the Needs and Desires from a PhD Survey. Writers Hut (pp. 33-40). Department of Computer and Systems Sciences.
  22. Karunaratne, T., Boström, H., & Norinder, U. (2013). Comparative analysis of the use of chemoinformatics-based and substructure-based descriptors for quantitative structure-activity relationship (QSAR) modelling. Intelligent Data Analysis, 17(2), 327-341.
  23. Karunaratne, T., & Boström, H. (2012). Can frequent itemset mining be efficiently and effectively used for learning from graph data? 11th International Conference on Machine Learning and Applications (pp. 409-414). IEEE Computer Society.
  24. Karunaratne, T. (2011). Is frequent pattern mining useful in building predictive models? ECML/PKDD workshop of Collective Learning and Inference on Structured Data, (pp. 61-72). Athens, Greece.
  25. Karunaratne, T., Boström, H., & Norinder, U. (2010). Pre-processing structured data for standard machine learning algorithms by supervised graph propositionalization – a case study with medicinal chemistry datasets. 9th International Conference on Machine Learning and Applications (pp. 828-833). Washington DC, USA: IEEE Computer Society.
  26. Karunaratne, T., & Boström, H. (2009). Graph propositionalization for random forests. 8th International Conference on Machine Learning and Applications (pp. 196-201). Miami, Florida: IEEE Computer Society.
  27. Karunaratne, T., & Boström, H. (2007). Using background knowledge for graph-based learning: a case study in chemoinformatics (extended version). Proceedings of the second International Multiconference of Engineers and Computer Scientists (ICAIA-06), (pp. 153 – 157). Hong Kong.
  28. Karunaratne, T., & Boström, H. (2006). DIFFER: A Propositional Approach for Learning from Structured Data. Transactions on Science Engineering and Technology, 15, 49-51.
  29. Karunaratne, T., & Boström, H. (2006). Learning from structured data by fingerprinting. Proceedings of the 9th Scandinavian Conference on Artificial Intelligence (pp. 120-126). Helsinki, Finland: Finnish Artificial Intelligence Society.
  30. Karunaratne, T., & Boström, H. (2006). Learning to classify structured data by graph propositionalization. Proceedings of the Second IASTED International Conference on Computational Intelligence (pp. 393-398). San Francisco, USA: ACTA Press.
  31. Karunaratne, T., & Boström, H. (2006). Using background knowledge for graph-based learning: a case study in chemoinformatics. Proceedings of the 16th International Conference on Inductive Logic Programming, (pp. 116-118). Santiago De-Compostela, Spain.

Monographs:

  1. Karunaratne, T. (2014). Learning predictive models from graph data using pattern mining (PhD Thesis) (Vols. DSV Report Series 14-03). Stockholm University, Department of Computer and Systems Sciences.
  2. Karunaratne, T. (2007). Graph propositionalization for learning from structured data (Licentiate Thesis) (Vols. 07-002). Stockholm University: Department of Computer and Systems Sciences.

 

Book chapters:

  1. Karunaratne, T., & Boström, H. (2008). The effect of background knowledge in graph-based learning in the chemoinformatics domain. In O. Castillo, L. Xu, & S.-l. Ao, Trends in Intelligent Systems and Computer Engineering (Vol. 6 of Lecture Notes In Electrical Engineering, pp. 141-153). Springer US.

Books: 

  1. Theory of Computing, Course material for 3rd Year Computer Science students at the Department of Mathematics and Computer Science, The Open University of Sri Lanka.
  2. Mathematics for Computing, Course material for 3rd Year Computer Science student at the Department of Mathematics and Computer Science, The Open University of Sri Lanka.
  3. Machine Learning, Course material for 4th Year Computer Science students at the Department of Mathematics and Computer Science, The Open University of Sri Lanka.
  4. Object-Oriented Programming (Revised) for 2nd Year Computer Science students at the Department of Mathematics and Computer Science, The Open University of Sri Lanka. 2008.

Other scientific material:

  1. Olsson, U., & Karunaratne, T. (2019). How can higher education students’ generic digital competencies be defined, taught, and recognized? ASCILITE conference (workshop). Singapore: 3-4 December.
  2. Olsson, U., & Karunaratne, T. (2019). My decision matters: student perception on sharing learner data – a case study from secondary education in Sweden. ICDE Lifelong Learning Summit. Lillehammer: Oxford Abstracts.
  3. Karunaratn, T., & Olsson, U. (2019, June 27). Improve lesson plans based on student engagement statistics – Förbättra undervisning baserat på studentengagemang. doi:10.17045/sthlmuni.7087700.v1
  4. Karunaratne , T., & Olsson, U (2019, June 26). Monitoring student progress in course activities – Följ studentens framsteg i kursen. DOI:10.17045/sthlmuni.7088765.v1
  5. Olsson U. & Karunaratne T. (2018). Is it Ethical to NOT use algorithms in teaching? NU2018