Zeynab Mohseni
Doctoral studentZeynab (Artemis) Mohseni received her associate degree in Software Computer from Sabzevar Technical and Vocational College, Khorasan, Iran in 2007, the B.Sc. in Computer Engineering from Khorasan Institute of Higher Education, Mashhad, Khorasan, Iran in 2009 and the M.Sc. in Computer Engineering from Science and Research Branch, Islamic Azad University, Tehran, Iran in 2015. From 2017 to 2019 she worked as a researcher at Universidad Antonio de Nebrija, Madrid, Spain. Her research interests are in the areas of Visual Learning Analytics (VLA), fault tolerance techniques, Network on Chip, embedded and real-time systems and scheduling algorithms.
Teaching
Teaching assistant in the following courses:
4ME603 - Computer logical thinking and programming in school (1 year)
1DV534 - Object Oriented Programming with C ++ (1 year)
1DV533 - Structured programming with C ++
(3 years)
4DV510 - Data Mining (3 years)
4DV807 - Project in visualization and data analysis (3 years)
Research
My research focuses on Visual Learning Analytics (VLA) tools for teachers to support decision-making and learning trajectories. This topic is part of the EdTechLnu research group that aims to better understand and engineer complex educational data. I develop VLA approaches and tools to analyze data collected from Digital learning resources. In consequence, teachers are enabled to better understand the students' learning progress. By merging diverse individual visualizations, VLA tools also assist teachers in facilitating and promoting students' study achievements.
In 2022, I was one of two winners of Linnaeus University's EUniWell's pitch competition for doctoral students in individual and social sustainability as well as environment and sustainability. The scholarship is SEK 5,000 each and a workshop in science communication at Nantes Université, France. See the news item in Swedish below.
My research groups
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Computational Social Sciences The research in the area Computational Social Sciences within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is about producing and…
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EdTechLnu The research within the EdTechLnu field of knowledge has three main strands: • Developing new technology to support education and learning. • Studying teaching and learning where students…
My ongoing research projects
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Doctoral project: Visual learning analytics to support teachers’ pedagogical work This doctoral project features a collaboration with a number of EdTech companies that develop digital learning…
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Project: Educational Technology in Schools The project aims to change teachers' everyday practice and improve students' school results. This will be done by means of data-driven support and analysis…
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Seed project: Investigate Machine Learning Techniques for Decision-Making Support in K-12 Educational Context The main aim of this seed application is to investigate the use and application of Machine…
Publications
Article in journal (Refereed)
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Mohseni, Z., Martins, R.M., Masiello, I. (2022). SBGTool v2.0: An Empirical Study on a Similarity-Based Grouping Tool for Students’ Learning Outcomes. Data. 7 (7).
Status: Published
Conference paper (Refereed)
- Holmberg, K., Andersson Gidlund, T., Masiello, I., Rack, J., Mohseni, Z. (2023). Teachers' approaches to digital technology : when organizations' and teachers' practices are not constructively aligned. Nordic Educational Research Association (NERA): Digitalization and Technologies in Education Opportunities and Challenges 15 -17 March, 2023.
- Mohseni, Z., Martins, R.M., Masiello, I. (2021). SAVis : a Learning Analytics Dashboard with Interactive Visualization and Machine Learning. CEUR Workshop Proceedings, Volume 2985.
- Mohseni, Z., Martins, R.M., Masiello, I. (2021). SBGTool : Similarity-Based Grouping Tool for Students’ Learning Outcomes. Proceedings of the 2021 Swedish Workshop on Data Science (SweDS).
- Mohseni, Z., Martins, R.M., Milrad, M., Masiello, I. (2020). Improving Classification in Imbalanced Educational Datasets using Over-sampling. Proceedings of the 28th international conference on computer in education. 278-283.
Article in journal (Other academic)
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Mohseni, Z., Kiani, V., Rahmani, A.M. (2019). A Task Scheduling Model for Multi-CPU and Multi-Hard Disk Drive in Soft Real-time Systems. International Journal of Information Technology and Computer Science. 11 (1).
Status: Published -
Mohseni, Z., Reviriego, P. (2019). Reliability Characterization and Activity Analysis of lowRISC Internal Modules against Single Event Upsets Using Fault Injection and RTL Simulation. Microprocessors and microsystems. 71.
Status: Published -
Mohseni, Z., Reshadi, M. (2018). A Deadlock-free Routing Algorithm for Irregular 3D Network-on-Chips with Wireless Links. Journal of Supercomputing. 74 (2). 953-969.
Status: Published -
Kiani, V., Mohseni, Z., Rahmani, A.M. (2015). Real-time Scheduling for CPU and Hard Disk Requirements-Based Periodic Task with Aim of Minimising Energy Consumption. International Journal of Information Technology and Computer Science. 7 (10). 54-60.
Status: Published