Krause, Kai

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Krause
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Kai
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Kai Krause

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    Publication
    SQL scrolls - A reusable and extensible DGBL experiment
    (ACM, 2022) Pustulka, Elzbieta; Krause, Kai; de Espona, Lucía; Kennel, Andrea; Stikkolorum, Dave; Rahimi, Ebrahim
    The teaching of databases and SQL is an active research area. We contribute by presenting a reusable and extensible SQL teaching experiment which uses a game and fits the paradigm of digital game based learning (DGBL). Although DGBL is hampered partly by the difficulty of obtaining statistically significant empirical results, the research shows that it may be an effective learning method and that it is in demand. We investigate the acceptance and effectiveness of an SQL learning game and focus on two areas: student reaction to games as a vehicle for teaching, and educational effectiveness. We designed a game prototype and administered a pre-test, post-test and an acceptance survey, with seven part-time and sixteen full-time students. A statistical analysis of effect sizes revealed a moderate intervention effect for the game group (d= -0.562) and a small one for the traditional group (d= -0.234). The acceptance survey means were between 4.43 and 4.70 out of 5, which shows that the game is highly acceptable. Our experiment demonstrated positive student attitudes towards DGBL in SQL teaching and showed the game to be as effective as exercises done using a workbench. We further observed interesting differences in teaching using a game and a "natural" workbench environment and had excellent course feedback. We have released the game as open source in the hope that other researchers will replicate or contradict our findings or simply use it in teaching. We close with an outline of ongoing research.
    04B - Beitrag Konferenzschrift
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    Publication
    A comparison of nearest distance optimization and ant colony optimization for order picking in a multi-aisle warehouse
    (ACM, 2021) Bertini, Lukas; Krause, Kai; Hanne, Thomas; Dornberger, Rolf
    Today, warehouses and the IT infrastructure behind them ensure smooth processing of customer orders throughout the day in all supply chains. These orders can consist of one item up to hundreds of items. The size and heterogeneity of warehouses also impedes the fastest possible processing of all orders. This research compares the nearest distance optimization heuristic and ant colony optimization to find out whether one or the other route leads to faster picking times in several scenarios depending on the warehouse size or the number of items on the picking list. For this purpose, we chose the widespread multi-aisle layout of a warehouse for our study assuming that only one human worker is involved in picking the items on the list.
    04B - Beitrag Konferenzschrift