Auflistung Künstliche Intelligenz 36(1) - März 2022 nach Erscheinungsdatum
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- ZeitschriftenartikelSurvey: Artificial Intelligence, Computational Thinking and Learning(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Dohn, Nina Bonderup; Kafai, Yasmin; Mørch, Anders; Ragni, MarcoLearning is central to both artificial intelligence and human intelligence, the former focused on understanding how machines learn, the latter concerned with how humans learn. With the growing relevance of computational thinking, these two efforts have become more closely connected. This survey examines these connections and points to the need for educating the general public to understand the challenges which the increasing integration of AI in human lives pose. We describe three different framings of computational thinking: cognitive, situated, and critical. Each framing offers valuable, but different insights into what computational thinking can and should be. The differences between the three framings also concern the views of learning that they embody. We combine the three framings into one framework which emphasizes that (1) computational thinking activities involve engagement with algorithmic processes, and (2) the mere use of a digital artifact for an activity is not sufficient to count as computational thinking. We further present a set of approaches to learning computational thinking. We argue for the significance of computational thinking as regards artificial intelligence on three counts: (i) Human developers use computational thinking to create and develop artificial intelligence systems, (ii) understanding how humans learn can enrich artificial intelligence systems, and (iii) such enriched systems will be explainable. We conclude with an introduction of the articles included in the Special Issue, focusing on how they call upon and develop the themes of this survey.
- ZeitschriftenartikelProgramming and Computational Thinking in Mathematics Education(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Tamborg, Andreas Lindenskov; Elicer, Raimundo; Spikol, DanielArtificial intelligence (AI) has become a part of everyday interactions with pervasive digital systems. This development increasingly calls for citizens to have a basic understanding of programming and computational thinking (PCT). Accordingly, countries worldwide are implementing several approaches to integrate critical elements of PCT into K-9 education. However, these efforts are confronted by difficulties that the PCT concepts are for students to grasp from purely theoretical perspectives. Recent literature indicates that the playful nature is particularly important when novices from both both early and higher education are to learn AI. These playful activities are characterised by setting a scene where PCT concepts such as algorithms, data processing, and simulations are meant to draw on to understand better how AI is integrated into our everyday digital life. This discussion paper analyses playful PCT resources developed around the game rock-paper-scissors developed in the UK and Denmark. Resources from these countries are interesting starting points since both have been or are in the process of integrating PCT as part of the K-9 curriculum. The central discussion raised by the paper, is the nature of the integration between mathematics and PCT in these tasks. These resources provide opportunities for discussion of how we may better integrate PCT and mathematics from the perspective of both subjects to build a solid foundation for a critical understanding of AI interactions in future generations.
- ZeitschriftenartikelWhat is the Problem? A Situated Account of Computational Thinking as Problem-Solving in Two Danish Preschools(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Odgaard, Ane BjerreThis paper presents a case study of in situ activities in two Danish preschools. In the activities, learning computational thinking (CT) plays a central part. The participating 4- to 5-year-old children are invited by an external educator to employ tangibles, such as robots, for structured problem-solving tasks within an overall narrative framing. In accordance with elaborations on CT as a problem-solving strategy, it is examined how the children engage in CT as problem-solving. The activities are part of a municipal initiative that involves preschools in a larger Danish city. The aim of this municipal initiative is to support young children’s understanding of technologies, coding and robotics as an element of twenty-first century skills. Based on video observations, the study provides a situated account of how the children engage in problem-solving in the observed activities. In empirical terms, the study shows how problem-solving tasks, such as programming a robot to move from A to B, merge with complex endeavors of engaging meaningfully with things and people in social situations. These empirical findings are analyzed by employing theoretical conceptualizations of problem-solving from a sociocultural perspective. This leads to a critical discussion regarding the relevance, potentials and pitfalls of introducing CT through problem-solving tasks with tangible tools in Danish preschool settings.
- 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
- ZeitschriftenartikelA Double Take at Conferences: The Hybrid Format(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Turhan, Anni-Yasmin
- ZeitschriftenartikelFabric-Based Computing: (Re)examining the Materiality of Computer Science Learning Through Fiber Crafts(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Keune, AnnaFiber crafts, such as weaving and sewing, occupy a tension-filled space within computing. While associated with domestic practices, fiber crafts have been recognized as a precursor of the earliest computers and continue to present sources of computational inspiration. The connections between fiber crafts and computing have the potential to uncover possibilities for computing to become more diversified in terms of materials, cultural practices, and ultimately people. To explore the promises of fiber crafts for STEM education, this qualitative dissertation built on constructionist and posthumanist perspectives to examine two fiber crafts (i.e., weaving and fabric manipulation) as contexts for computer science learning. Collectively, the dissertation effectively aligned fiber crafts with computational concepts and showed their potential as a promising context for computer science learning. The work further showed that materials used for STEM learning are non-neutral. Materials matter in what can be learned computationally. Lastly, guided by posthumanist perspectives, the dissertation uncovered computational learning as the process of producing physical expansions and highlighted learning as the process of how computational concepts physically change. The work has implications for theorizing learning, designing for learning, and educational practice. For example, the dissertation presents the utility of posthumanist perspectives as an additional theoretical approach to the study of learning that can surface and help address ongoing relational deficit orientations.
- 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)
- ZeitschriftenartikelIn Memoriam Pamela McCorduck(KI - Künstliche Intelligenz: Vol. 36, No. 1, 2022) Piel, Helen; Seising, Rudolf