Ongoing educational research

Last modified: February 2021

This outline provides a high-level overview of some of the ongoing educational studies conducted on the platform for the purposes of improving the education and teaching offered at the Aalto University. For additional information about the ongoing educational research on this platform, contact Arto Hellas (firstname.lastname@aalto.fi).

At Aalto University and in Finnish Universities, teaching and research are strongly linked together — teachers are researchers and researchers are teachers. As such, teachers also continuously study ways to improve their teaching.

The Finnish Universities Act (558/2009) ↗ states that: The mission of the universities is to promote independent academic research as well as academic and artistic education, to provide research-based higher education and to educate students to serve their country and humanity at large. In carrying out their mission, the universities shall promote lifelong learning, interact with the surrounding society and promote the social impact of university research findings and artistic activities.

In general, in educational research ↗, teachers and researchers study teaching and learning processes to understand how learning takes place, often with the purpose of developing new tools and methods for improving teaching and learning. Such research is conducted also within disciplines: for example, computing education research — which these ongoing studies situate in — studies teaching and learning in computer science, reflecting the practices and knowledge of the discipline.

Here, we outline some of the studies that are being conducted within the platform and the courses. The objective of all of these studies is to improve teaching and learning.

All of the work outlined here is conducted within the guidelines of Aalto University’s Research Ethics Committee ↗ and The Finnish National Board on Research Integrity TENK ↗.

Understanding the use of online learning materials

There is a lot to learn on how to construct online learning materials for high-quality learning. On a broad level, when seeking to understand how high-quality online learning materials should be constructed, plenty of focus is put on how current online learning materials are used. This includes studying what parts of the offered learning materials are important and/or unimportant for particular tasks, how course tasks posed in the online materials are solved, and what sorts of behaviors lead to intended learning outcomes. Such information is used when adjusting learning materials. As a part of this work, we are studying how course participants use the materials and whether and how using the course materials are related to the performance on course assignments and the courses in general.

Supporting learning and increasing engagement

In general, all teachers want that their students learn. Studying takes plenty of effort and can be hindered, for example, by poorly designed interaction with the learning environment and/or the materials. We are looking into what sorts of distractors there are in online learning environments and studying ways for helping learners focus and engage on the specific (current) tasks. This work includes, for example, studying how online learning management systems should present information in general (including navigation, menus, points), what sorts of signals should be used by the learning materials, and how these should be adjusted to increase engagement with the content.

As an example of presenting specific information, previous research has suggested that e.g. adding emotion-inducing illustrations to learning materials can change how people process the learning materials and consequently may influence learning. Although there is evidence on “emotional design” influencing comprehension, it is unclear whether and how these results apply in computing education — e.g. in learning programming. On the platform, we are studying whether and to what extent adding illustrations based on emotional design and personalization influences learning of computing education specific concepts.

As an example of increasing engagement, there is evidence that asking students to form questions about the topic at hand can lead to better learning outcomes. On the platform, we are looking into the use of student-generated questions both for rehearsal content for others and for improving the retention of already learned content.

Working with challenging topics and misconceptions

Knowledge is built piece by piece on top of existing knowledge. If existing knowledge of a specific concept is fragile, or is based on misconceptions, the foundation of newly learned information will be shaky. Misconceptions can be formed by accident, but it is also possible that teachers intentionally want to provide an incomplete picture of a phenomenon for the purposes of teaching another, more important phenomenon. Misconceptions are intertwined with difficult concepts in that one will, probably, more likely form a misconception of a difficult and not yet familiar topic than of an easy and already familiar topic. As a part of the work conducted on the platform, we are looking into identifying the misconceptions and errors related to the taught topics and concepts, and studying how the organization of materials and assignments, including their use, possibly contribute to built misconceptions. Naturally, as a part of this work, we also study how materials and assignments should be constructed to avoid misconceptions.

One particular goal related to this is constructing learner models and intelligent tutoring systems. Intelligent tutoring systems — including systems that provide learners new assignments and materials until learners have learned the concept at hand — can improve learning outcomes. Learner models, on the other hand, are built to estimate to what extent a learner has learned a concept. Studies suggest that intelligent tutoring systems may improve learning outcomes by at least one standard deviation in course scores when compared to groups without intelligent tutoring systems. When developing the platform and the courses, we are studying learner modeling as well as the opportunity of providing new assignments to learners based on their current level of knowledge, and looking into whether and how providing personalized content influences learner’s behavior in the platform. This not only helps us help the learners but also helps us in developing better assignments and materials.

A note on publishing study results

To help others learn from our insights, and more broadly, advance science (“standing on the shoulders of giants”), results from the studies may be published in scientific venues and in media. Individual course participants cannot be identified from possible publications.