Alisa Lincke

Alisa Sotsenko is a PhD Student in Computer and Information Science at Linnaeus University, Sweden, since August 2014. She holds a MSc in Computer Science (ONPU) Odessa, Ukraine and in Computer Science (Linnaeus University), Växjö,Sweden. She conducts her research under the supervision of Prof. Dr. Marc Jansen with the CeLekT group at the Media Technology Department of Linnaeus University.

Alisa's research focus is on designing a rich context model for the development of contextualised mobile applications. Currently, she is working on developing cloud-based Contextualization Service as SaaS approach for mobile software developers to develop highly personalised mobile applications.

Research Interests:

- contextualized and personalized mobile applications;

- the use of modern technologies ( like IoT, Big Data analytics and Cloud Services) to enhance the teaching and learning experience in m-learning, e-learning and e-health scenarios;

- cloud-based contextualized Services and learning analytics Services;

- interactive e-Books with personalized and contextualized content and guiding support;

- contextualized public displays though personalized mobile devices;

- m-learning, m-health and e-health use-cases/scenarios and more.

Publications

Article in journal (Refereed)

Fellman, D., Lincke, A., Berge, E., Jonsson, B. (2020). Predicting Visuospatial and Verbal Working Memory by Individual Differences in E-Learning Activities. Frontiers in Education. 5.
Fellman, D., Lincke, A., Jonsson, B. (2020). Do Individual Differences in Cognition and Personality Predict Retrieval Practice Activities on MOOCs?. Frontiers in Psychology. 11. 1-10.
Backåberg, S., Hellström, A., Fagerström, C., Halling, A., Lincke, A., et al. (2020). Evaluation of the Skeleton Avatar Technique for Assessment of Mobility and Balance Among Older Adults. Frontiers of Computer Science. 2. 1-13.
Herault, R.C., Lincke, A., Milrad, M., Forsgärde, E., Elmqvist, C. (2018). Using 360-degrees interactive videos inpatient trauma treatment education : design, development and evaluationaspects. Smart Learning Environments. 5.

Conference paper (Refereed)

Hagelbäck, J., Lincke, A., Löwe, W., Rall, E. (2019). On the Agreement of Commodity 3D Cameras. Proceedings of the 2019 International Conference on Image Processing, Computer Vision, & Pattern Recognition. 36-42.
Hagelbäck, J., Liapota, P., Lincke, A., Löwe, W. (2019). Variants of Dynamic Time Warping and their Performance in Human Movement Assessment. 21st International Conference on Artificial Intelligence (ICAI'19: July 29 - August 1, 2019, Las Vegas, USA). 9-15.
Lincke, A., Lozano Prieto, D., Herault, R.C., Forsgärde, E., Milrad, M. (2019). Visualizing learners’ navigation behaviour using 360 degrees interactive videos. Proceedings of the 15th International Conference on Web Information Systems and Technologies. 358-364.
Lincke, A., Fellman, D., Jansen, M., Milrad, M., Berge, E., et al. (2019). Correlating Working Memory Capacity with Learners´ Study Behavior in a Web-Based Learning Platform. Proceedings of the 27th International Conference on Computers in Education Conference Proceedings. 90-92.
Lincke, A., Jansen, M., Milrad, M., Berge, E. (2019). Using Data Mining Techniques to Assess Students’ Answer Predictions. ICCE 2019 - 27th International Conference on Computers in Education, Proceedings : Volume 1. 42-50.
Hagelbäck, J., Liapota, P., Lincke, A., Löwe, W. (2019). The performance of some machine learning approaches in human movement assessment. 13th Multi Conference on Computer Science and Information Systems (MCCSIS). 35-42.
Herault, R.C., Lincke, A., Milrad, M., Forsgärde, E., Elmqvist, C., et al. (2018). Design and Evaluation of a 360 Degrees Interactive Video System to Support Collaborative Training for Nursing Students in Patient Trauma Treatment. 26TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION (ICCE 2018). 298-303.
Lincke, A., Lundberg, J., Thunander, M., Milrad, M., Lundberg, J., et al. (2018). Diabetes Information in Social Media. Proceedings of the 11th International Symposium on Visual Information Communication and Interaction (VINCI '18). 104-105.
Sotsenko, A., Jansen, M., Milrad, M., Rana, J. (2016). Using a Rich Context Model for Real-Time Big Data Analytics in Twitter. 2016 IEEE 4TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (FICLOUDW). 228-233.
Sotsenko, A., Jansen, M., Milrad, M. (2015). Using a Rich Context Model for People-to-People Recommendation. 2015 3rd International Conference on Future Internet of Things and Cloud (FiCloud), 24-26 Aug. 2015, Rome. 703-708.
Sotsenko, A. (2015). Exploring Different Use Cases for a Rich Context Model for Mobile Applications. Proceedings of Doctoral Symposium of the 9th International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT 2015). 23-31.
Sotsenko, A., Jansen, M., Milrad, M. (2014). Implementing and Validating a Mobile Learning Scenario Using Contextualized Learning Objects. Proceedings of the 22^nd International Conference on Computers in Education ICCE 2014 : November 30, 2014 - December 4, 2014, Nara, Japan. 522-527.
Sotsenko, A., Jansen, M., Milrad, M. (2014). Using a Rich Context Model for a News Recommender System for Mobile Users. UMAP 2014 Extended Proceedings : Posters, Demos, Late-breaking Results and Workshop Proceedings of the 22nd Conference on User Modeling, Adaptation, and Personalization co-located with the 22nd Conference on User Modeling, Adaptation, and Personalization (UMAP2014) Aalborg, Denmark, July 7-11, 2014.. 13-16.
Sotsenko, A., Jansen, M., Milrad, M. (2013). About the Contextualization of Learning Objects in Mobile Learning Settings. QScience Proceedings : Vol. 2013, 12th World Conference on Mobile and Contextual Learning (mLearn 2013). 67-70.
Sotsenko, A., Jansen, M., Milrad, M. (2013). Supporting Content Contextualization in Web Based Applications on Mobile Devices. Proceedings of the 9th International Conference on Web Information Systems and Technologies : Aachen, Germany, 8-10 May, 2013. 501-504.

Chapter in book (Refereed)

Sotsenko, A., Zbick, J., Jansen, M., Milrad, M. (2016). Flexible and Contextualized Cloud Applications for Mobile Learning Scenarios. Mobile, Ubiquitous, and Pervasive Learning : Fundaments, Applications, and Trends. Springer. 167-192.
Sotsenko, A., Zbick, J., Jansen, M., Milrad, M. (2015). Contextualization of Mobile Learners. Mobile Learning : Trends, Attitudes and Effectiveness. Nova Science Publishers, Inc.. 39-54.

Doctoral thesis, comprehensive summary (Other academic)

Lincke, A. (2020). A Computational Approach for Modelling Context across Different Application Domains. Doctoral Thesis. Växjö, Linnaeus University Press. 106.

Licentiate thesis, comprehensive summary (Other academic)

Sotsenko, A. (2017). A Rich Context Model : Design and Implementation. Licentiate Thesis. Växjö, Faculty of Technology, Linnaeus University. 103.