This page lists on-going and past research projects that have received external funding. Much of LeTech's other work (that is not listed here) is carried out in thesis projects, faculty members' personal research and are based on education development grants from the university. For more information about thesis projects, see a separate list
The Intelligent Systems and Content Creation project (älykkäät oppimisympäristöt ja niiden sisällöntuotanto in Finnish, shortened to älyOppi) develops and improves digital learning materials and environments for university level use. Intelligent learning environments can be for example automatic checking procedures, visualizations and simulations. These are used to offer the students interactive materials, support to their self-studying, and model and analyze field-specific materials.
The purpose of the project is to benefit both the students and the teachers. The goal is to build unified learning environments between universities, polytechnics and colleges, and to ensure free usage of these environments in all learning institutions. Field-specific networks are built to offer support for sharing and helping among teachers from all the institutions.
The project is divided into three parts according to the fields: programming, mathematics and physics.
The programming subproject puts emphasis on improving the cooperation of polytechnic universities, for example by unifying course descriptions and materials, opening courses for students from other universities, and developing the course materials so that they can be completed and automatically evaluated in different programming languages while using the same environments.
The mathematics subproject develops the Abacus material bank, built on the STACK system. The purpose of the subproject is to build search functionality for the exercise bank, as well as create an automatic examination system using both STACK and EXAM systems. Other features under development are exercise update functionality and ready-made course templates for a variety of topics.
The physics subproject further develops the ABACUS exercise bank, as well as automatic examination system in cooperation with the mathematics subproject. The subproject also generates exercises suitable for courses in universities of applied sciences, such as medicinal calculation courses, and applied exercises for automation and electrical engineering. In addition, the physics subproject translates course materials into English to ensure international collaboration.
The project is coordinated by Aalto University, and it is implemented in cooperation with University of Helsinki, University of Eastern Finland, University of Jyväskylä, Lappeenranta University of Technology, University of Oulu, Tampere University of Technology, University of Tampere, University of Vaasa, Arcada yrkeshögskolan, Metropolia University of Applied Sciences and Tampere University of Applied Sciences. The Ministry of Education and Culture funds the project for 2018-2020.
The Intelligent Systems project also collaborates with the Digital Education For All (DEFA) project.
More information on the project can be found here (in Finnish).
Person in charge: Prof. Lauri Malmi(firstname.lastname@example.org)
Programming Subproject: Ari Korhonen (email@example.com)
Physics Subproject: Petri Salo (firstname.lastname@example.org)
Mathematics Subproject: Simo Ali-Löytty (email@example.com)
Finance: Paula Latvala (firstname.lastname@example.org)
Project Coordinator: Nea Pirttinen (email@example.com)
SAVI FUN (2013-2014): A Finland-U.S. Network for Engagement and STEM Learning in Games.
The Finnish-US Network (FUN) is blending methods and testbeds from both countries to obtain a broader picture of how engagement and learning are entwined in the growing field of game-based learning. As part of a SAVI, teams from the Educational Gaming Environments group (EdGE) at TERC, WGBH and Northern Illinois University are partnering with Finnish researchers from Aalto University, University of Tampere, and University of Jyväskylä. Each team is this consortium examines engagement in game-based learning in different yet complementary ways. Methods within the FUN research team include a variety of surveys, video analysis techniques, experience sampling methods, and educational data mining. The FUN researchers are conducting cross-team studies to look for similarities and differences arising in difference cultures and different gaming environments.
This component of the Finland-USA SAVI effort carries out research on knowledge representation techniques for visualizing and presenting STEM content digitally in order to engage students and engender deep learning. The principal investigators are integrating the results of their research (in an iterative fashion) toward the development of new representation, interaction, and navigation techniques for digital STEM content. Content along with new navigation and automated assessment techniques are being developed and then classroom tested for college-level Computer Science and middle school-level Physics and Biology. Collaboration is a key component of this work, as the team is testing its theoretical framework for dynamic digital texts with content in science and computing, for middle school and college, in both Finnish and US educational settings.
ISiCLE project is going to improve the current state of educational systems in Aalto University. Currently, courses provide separate educational systems supporting teachers and learners. The first goal of this project is to make it easier for other universities to take these systems into use. A further vision of this project is to provide a uniform environment for teachers and students by combine multiple educational systems into one platform.Another aspect of research is to provide social media aspects to learning environments.
Visualization of Spatial Data Structures and Algorithms is a joint research project between the Software Visualization Group at the Department of Computer Science and Engineering and the Institute of Cartography and Geoinformatics funded by Academy of Finland. The project aims at applying software visualization (SV) techniques to spatial data structures and algorithms. Spatial data is used in numerous different fields, including Geographic Information Systems (GIS), robotics, computer graphics, virtual reality, as well as in other disciplines such as computer-aided design, biology, and statistics. In this project, however, the focus is on spatial data structures in geoinformatics where visualization are widely utilized for illustrating data accurately and understandably. Such visualizations often contain different types of maps and diagrams that make it easier to analyze the data. The maps are primarily aimed at showing the data in an accurate and understandable manner, but lack the representation of the underlying data structures needed to implement the applications. Thus, the idea is to promote SV techiques and tools to provide the user a better insight into the data stuctures used to store the data and the algorithms used to manipulate it.
TAPAS is a collaborative project between the Department of Computer Science and Engineering at the Helsinki University of Technology (HUT) and the Department of Computer Science at the University of Joensuu (UJ). The aim is to develop methods and tools for free text and program text analysis by combining the strengths of the two universities.
SIMUTRAF is a cooperative research project organized by the Laboratory of Software Technology and the Laboratory of Transportation Engineering funded by the Helsinki University of Technology. The goal of SIMUTRAF is to combine visual algorithm simulation as a tool to create more versatile and user-friendly traffic simulators. Another goal in SIMUTRAF is to build the DIGITRAFFIC projectdatabase where all traffic model information is stored. As a whole, the combination of Software Visualization techniques and DIGITRAFFIC simulation program can provide a totally new level of interactive visual traffic simulations.
Automatic Assessment and Feedback on Algorithm Simulation is a research project funded by Academy of Finland. The project concentrates on improving the use of interactive software visualization methods and tools as an aid for learning and exploring data structures and algorithms. Especially, we are promoting the feedback an automatic assessment tool can provide for the learner during the interaction. The current activity includes the study of misconceptions that is currently an emerging research field in Computer Science Education. The aim is to identify several misconceptions automatically in terms of dedicated algorithms that can mimic user mistakes. The algorithms are altered to follow the (faulty) user simulation sequence in order to automatically detect which algorithm the user has in is or her mind (see also Machine Learning, Programming by Demonstration, and Fault Injection). After a successful detection, the user can be informed about the misconception he/she most probably have, thus the system can be put to promote learning by giving better feedback.