Michael Burkhard
Last Name
Burkhard
First name
Michael
Email
michael.burkhard@unisg.ch
Phone
+41 71 224 7574
6 results
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Item type:Publication, Social Robots as Teaching Assistance System in Higher Education: Conceptual Framework for the Development of Use CasesThis paper provides an overview of the current state of research on social robots in higher education and the existing frameworks to categorize and develop social robot applications. Based on the existing work, we present our own framework to develop use cases for social robots in the education sector. Our framework is based on a heuristic and symbiotic design approach that serves as a guideline for developing use cases and views human-robot interaction as two complementary and mutually reinforcing roles. We illustrate our framework by means of a use case that we have conducted in 2019 during the initial lecture of the large-scale course ‘Introduction to academic writing’.Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Who is Best Suited for the Job? Task Allocation Process Between Teachers and Smart Machines Based on Comparative StrengthsDue 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.Type:book sectionScopus© Citations 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Social robots in education: conceptual overview and use case of academic writing(Springer, 2022-01); ; ; ; Ifenthaler, DirkSocial 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.Type:book section - Some of the metrics are blocked by yourconsent settings
Item type:Publication, When Lecturers have a Choice: Covid-19 Teaching Format Preferences in a Large-Scale Course of Freshmen Students in Switzerland(Gesellschaft für Informatik e.V., 2021-09); ; ; 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.Type:book section - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Paradigm Shift in Human-Machine Interaction: A New Learning Framework for Required Competencies in the Age of Artificial Intelligence?(2021-01); ; Smart machines (e.g., chatbots, social robots) are increasingly able to perform cognitive tasks and become more compatible with us. What are the implications of this new situation for the competency requirements in the 21st century? This paper evaluates the underlying paradigm shift with relation to smart machines in education. It discusses the potentials and current limitations of smart machines in education in order to eliminate prejudices and to contribute to a more comprehensive picture of the technological advances. In light of human augmentation, the paper further proposes a possible learning framework that includes the human-smart machine relationship as a normative orientation for new competency requirements.Type:conference posterVolume:Volume 1Scopus© Citations 4 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Relative Strengths of Teachers and Smart Machines: Towards an Augmented Task Sharing(2021-01); ; In education, smart machines (e.g., chatbots or social robots) have the potential to support teachers in the classroom in order to improve the quality of teaching. From a teacher's point of view, smart machines also pose a challenge because the presence of smart machines in the classroom questions traditional teacher and student roles. This paper presents a theoretical basis for the use of smart machines in education. It describes the relative strengths of teachers and smart machines and presents them in a framework, which makes a proposal for an augmented task sharing. In light of human augmentation, the framework proposes ways in which teachers can position themselves with regard to smart machines in a complementary and mutually reinforcing way. It also has implications for knowledge that is necessary for teachers to play an active role in the digital transformation.Type:conference posterVolume:Volume 1Scopus© Citations 3