Dynamic User Interfaces via Incremental Knowledge Management - Kohlhase, Michael; Marcus, Richard; Roux, Navid; Schihada, John (CICM-WS 2021: Workshop Papers of the 14th Conference on Intelligent Computer Mathematics (CICM 2021). Joint Proceedings of the FMM, FVPS, MathUI, NatFoM, and OpenMath Workshops, Doctoral Program, and Work in Progress at the Conference on Intelligent Computer Mathematics 2021 co-located with the 14th Conference on Intelligent Computer Mathematics (CICM 2021), 2022)
Extending the UFrameIT Framework, we propose an upgrade to the User Interface features that is directly built on the knowledge-based part, Mmt. In the game engine, it suffices to interpret the output and visualize it accordingly, resulting in features that work generically and out of the box for all games built with UFrameIT. Initially, we were using fixed text descriptions and a static UI that created unnecessary mental load when players were trying to match between the abstract problem description and concrete game situations. To improve this, we introduce dynamic UI synchronization. We relate the progress of the player to the abstract formalized solution and give hints accordingly. These hints are generated via partial views; given a partial solution to the problem, Mmt can check the dependencies and point towards the missing information. In the game, we can use this to highlight not yet assigned as well as even not yet existing facts in the game. This way, the player gets immediate feedback during the solution process.
CRIS-Team Scopus Importer:2024-12-16
Keywords: Development Tool; Game Engine; Knowledge Management; MMT; Serious Games; Unity; User Experience; User Interfaces

FrameIT: Detangling Knowledge Management from Game Design in Serious Games - Kohlhase, Michael; Bösl, Benjamin; Marcus, Richard; Müller, Dennis; Rochau, Denis; Roux, Navid; Schihada, John; Stamminger, Marc (Lecture Notes in Computer Science, vol 12236, 2020)
Serious games are an attempt to leverage the inherent motivation in game-like scenarios for an educational application and to transpose the learning goals into real-world applications. Unfortunately, serious games are also very costly to develop and deploy. For very abstract domains like mathematics, already the representation of the knowledge involved becomes a problem. We propose the FrameIT Method that uses OMDoc/Mmt theory graphs to represent and track the underlying knowledge in serious games. In this paper we report on an implementation and experiment that tests the method. We obtain a simple serious game by representing a “word problem” in OMDoc/Mmt and connecting the Mmt API with a state-of-the-art game engin
Keywords: Unity; Serious Game; Artificial Intelligence; AI; game engine; MMT; logic; knowledge management

Structure-Preserving Diagram Operators - Roux, Navid; Rabe, Florian (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2021)
Theory operators are meta-level operators in logic that map theories to theories. Often these are functorial in that they can be extended to theory morphisms and possibly enjoy further valuable properties such as preserving inclusions. Thus, it is possible to apply them to entire diagrams at once, often in a way that the output diagram mimics any morphisms or modular structure of the input diagram. Our results are worked out using the Mmt language for structured theories instantiated with the logical framework LF for basic theories, but they can be easily transferred to other languages. We investigate how Mmt/LF diagram operators can be defined conveniently and give multiple examples.
CRIS-Team Scopus Importer:2021-05-07