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Auflistung Künstliche Intelligenz 36(1) - März 2022 nach Erscheinungsdatum
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- ZeitschriftenartikelNews(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022)
- ZeitschriftenartikelSimplifying Programming for Non-technical Students: A Hermeneutic Approach(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Valente, Andrea; Marchetti, EmanuelaThis paper investigates the simplification of programming for non-technical university students. Typical simplification strategies are outlined, and according to our findings CT courses for non-technical students typically address learners from different faculties, providing generic and basic knowledge, not specifically related to their major. In this study, we propose instead a hermeneutic approach to simplify programming, in which we aim at clarifying the problem-solving aspect of programming, addressing computational problems that are specific to their studies and leveraging on learners’ preunderstanding of the digital media they have experienced as users. The practical counterpart of our theoretical approach is a minimalistic Python multimedia library, called Medialib, that we designed to enable university students with a non-technical profile to create visual media and games with short and readable code. We discuss the use of Medialib in two empirical case studies: a collaboration with the university of Kyushu in Fukuoka, Japan, and a coding module for Media Studies students at the University of Southern Denmark. Furthermore, we use Notional Machines to attempt a comparison of the simplicity of learning tools for programming, and to ground our claim that Medialib is “simpler” for learners than other popular approaches. The main contribution is a hermeneutic approach to the simplification of programming for specific contexts that combines the hermeneutic spiral and notional machines. The approach is supported by a tool, the Medialib library; the two case studies provide examples of how the approach and tool can be deployed in beginners in CT courses.
- ZeitschriftenartikelThe German EU Council Presidency Translator(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Pinnis, Mārcis; Busemann, Stephan; Vasiļevskis, Artūrs; Genabith, JosefThis contribution describes the German EU Council Presidency Translator (EUC PT), a machine translation service created for the German EU Council Presidency in the second half of 2020, which is open to the general public. Following a series of earlier presidency translators, the German version exhibits important extensions and improvements. The German EUC PT is the first to integrate systems from commercial vendors, public services, and a research center, using a mix of custom and generic translation engines, and to introduce a new webpage translation widget. A further important feature is the close collaboration with human translators from the German ministries, who were provided with computer-assisted translation tool plugins integrating machine translation services into their daily work environments. Uptake by the public reflects a huge interest in the service, showing the need for breaking language barriers.
- ZeitschriftenartikelPrimary Mathematics Teachers’ Understanding of Computational Thinking(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Nordby, Siri Krogh; Bjerke, Annette Hessen; Mifsud, LouiseComputational thinking (CT) is often regarded as providing a ‘soft start’ for later involvement with artificial intelligence and, hence, as a crucial twenty-first century skill. The introduction of CT in primary mathematics curricula puts many demands on teachers, and their understanding of CT in mathematics is key to its successful introduction. Inspired by an information ecology perspective, we investigate how four primary school teachers understand CT in mathematics and how they go ahead to include CT in their mathematics teaching practice. Through observations and interviews, we find promising starting points for including CT, related to pattern recognition, problem solving and the use of programming activities. Our findings indicate that teachers’ lack of knowledge affects CT adoption in two ways: during its inclusion in the existing mathematics curriculum and as a new element focussed on programming and coding, leaving mathematics in the background. For the inclusion to be fruitful, we suggest there is a need to help teachers understand how CT can be used productively in mathematics and vice versa.
- ZeitschriftenartikelComputational Thinking as a Social Movement(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Mørch, Anders; Kafai, Yasmin
- ZeitschriftenartikelIn Memoriam Pamela McCorduck(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Piel, Helen; Seising, Rudolf
- ZeitschriftenartikelThe Cyber Weapon: Decomposing Puzzles in Unplugged Computational Thinking Practices with Computational Objects(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Hachmann, RolandThis article contributes empirically to an ongoing discussion in the cross-section between computer science and the learning sciences. It takes on the question of how pupils can approach basic concepts of computer science and computational thinking skills through problem-solving activities in school. By responding to propositions from researchers within the field suggesting that broader perspectives on integrating computational thinking in subjects should be investigated, examples from an empirical study are given. The study examines a design for learning computational thinking using an unplugged approach, highlighting tangible computational objects as mediators for problem-solving. Three groups of 8th-grade pupils were followed and observed as they set out to collaborate on solving the escape puzzle: The Cyber Weapon, by manipulating computational objects and retrieving a code to stop a virus from spreading. The article highlights how pupils move from open trial-and-error approaches to systematic and iterative decomposing strategies. The article further discusses the implications of tangible computational objects framing problem-solving activities. This is done from a subject-didactical approach, highlighting the interrelatedness between problems, people, and tools as well as how designs like The Cyber Weapon reflect an alternative way to teach pupils basic concepts of computational thinking.
- ZeitschriftenartikelNews(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022)
- ZeitschriftenartikelExpertise depends on reasoning through alternative scenarios(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Dohn, Nina Bonderup; Ragni, Marco
- ZeitschriftenartikelMulti-phase Fine-Tuning: A New Fine-Tuning Approach for Sign Language Recognition(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Sarhan, Noha; Lauri, Mikko; Frintrop, SimoneIn this paper, we propose multi-phase fine-tuning for tuning deep networks from typical object recognition to sign language recognition (SLR). It extends the successful idea of transfer learning by fine-tuning the network’s weights over several phases. Starting from the top of the network, layers are trained in phases by successively unfreezing layers for training. We apply this novel training approach to SLR, since in this application, training data is scarce and differs considerably from the datasets which are usually used for pre-training. Our experiments show that multi-phase fine-tuning can reach significantly better accuracy in fewer training epochs compared to previous fine-tuning techniques