Josef Guggemos
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PD Dr.
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Guggemos
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Josef
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josef.guggemos@unisg.ch
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+41 71 224 26 92

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Publication

Who is Best Suited for the Job? Task Allocation Process Between Teachers and Smart Machines Based on Comparative Strengths

2022-08-21 , Burkhard, Michael , Guggemos, Josef , Seufert, Sabine

Due to advances in machine learning (ML) and artificial intelligence (AI), computer systems are becoming increasingly intelligent and capable of taking on new tasks (e.g., automatic translation of texts). In education, such AI-powered smart machines (e.g., chatbots, social robots) have the potential to support teachers in the classroom in order to improve the quality of teaching. However, from a teacher’s point of view, it may be unclear which subtasks could be best outsourced to the smart machine. Considering human augmentation, this paper presents a theoretical basis for the use of smart machines in education. It highlights the relative strengths of teachers and smart machines in the classroom and proposes a staged process for assigning classroom tasks. The derived task allocation process can be characterized by its three main steps of 1) break-down of task sequence and rethinking the existing task structure, 2) invariable task assignment (normative and technical considerations), and 3) variable task assignment (efficiency considerations). Based on the comparative strengths of both parties, the derived process ensures that subtasks are assigned as efficiently as possible (variable task assignment), while always granting priority to subtasks of normative importance (invariable task assignment). In this way, the derived task allocation process can serve as a guideline for the design and the implementation of smart machine projects in education.

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Publication

Digitale Kompetenzen von Lehrpersonen – Ergebnisse einer empirischen Untersuchung in der Berufsbildung

2022 , Seufert, Sabine , Guggemos, Josef , Gerholz, Karl-Heinz , Schlottmann, Philipp , Slepcevic-Zach, Peter , Stock, Michaela

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Das Evidence-centered design zur Konstruktion von Lern- und Testaufgaben

2021 , Guggemos, Josef , Kreuzer, Christine

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Lehrer*innenbildung von digitalen Kompetenzen in einer forschungsbasierten Lerngemeinschaft. Fallbeispiel i-MOOC zur Förderung von Informationskompetenzen auf der Sekundarstufe II

2020 , Moser, Luca , Seufert, Sabine , Guggemos, Josef , Kaspar, K , Becker-Mrotzek, M , Hofhues, S , König, J , Schmeinck, D

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Publication

Computational Thinking Assessment – Towards More Vivid Interpretations

2022-01-27 , Guggemos, Josef , Seufert, Sabine , Román-González, Marcos , Ifenthaler, Dirk

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Publication

Shaping AI Transformation: Digital Competencies and Augmentation Strategies of HRD Professionals

2022 , Spirgi, Judith , Guggemos, Josef , Seufert, Sabine , Dirk, Ifenthaler , Seufert, Sabine

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Learning Organizations in the Age of Smart Machines. Fusion Skills, Augmentation Strategies, and the Role of HRD Professionals

2021-01 , Meier, Christoph , Seufert, Sabine , Guggemos, Josef , Spirgi, Judith , Ifenthaler, Dirk , Hofhues, Sandra , Egloffstein, Marc , Helbig, Christian

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Social robots in education: conceptual overview and use case of academic writing

2022-01 , Guggemos, Josef , Seufert, Sabine , Sonderegger, Stefan , Burkhard, Michael , Ifenthaler, Dirk , Isaías, Pedro , Sampson, Demetrios

Social robots are increasingly being used in education. They can take over various roles including teaching assistant, tutor, and novice. This chapter aims to provide a conceptual overview of the phenomenon. A classification of social robots is outlined; the criteria are: visual appearance, social capabilities, and autonomy and intelligence. The majority of robots used in education are humanoid; Nao from SoftBank Robotics is a quasi-standard type. An important social capability is empathy; a model illustrating how a robot can show empathy is discussed. A taxonomy is presented in order to capture the various degrees of robot autonomy. To achieve autonomy, artificial intelligence is necessary. This chapter advocates for a symbiotic design approach where tasks are collaboratively carried out by the teacher and the social robot, utilizing the complementary strength of both parties. This may be in line with the concept of hybrid intelligence. The ethical aspects of social robot use are explored, including privacy, control, responsibility, and the role of teachers. Moreover, the acceptance of social robots is discussed. Overall, attitudes towards social robots seem to be positive; however, there are also contrary findings. Finally, results are presented from a technology acceptance study with a sample of N = 462 university students from the social sciences. The chapter closes with suggestions for further research.

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When Lecturers have a Choice: Covid-19 Teaching Format Preferences in a Large-Scale Course of Freshmen Students in Switzerland

2021-09 , Burkhard, Michael , Guggemos, Josef , Seufert, Sabine , Sonderegger, Stefan

Covid-19 is increasingly forcing educational institutions to explore new avenues and weight the pros and cons between on-site instruction, online instruction, and mixed formats. Understanding teaching format preferences of lecturers may be helpful for creating meaningful solutions with educational technologies. The paper at hand documents and reflects on the organization and implementation of a large-scale first-semester course in Switzerland in the fall term 2020, where seminar lecturers were free to decide on their used course format (on-site, online, mixed). The format preferences of all 39 seminar lecturers were captured and evaluated. Our results indicate that seminar lecturers predominantly opted for mixed or online seminars; often they like to conduct the very first lesson on site for the purpose of becoming familiar with the students.

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Soziale Roboter im Bildungsbereich: Konzeptioneller Überblick zum Einsatz sozialer Roboter in der Bildung

2021-10 , Seufert, Sabine , Guggemos, Josef , Sonderegger, Stefan , Bendel, Oliver

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