Michael Burkhard
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Burkhard
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Michael
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michael.burkhard@unisg.ch
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+41 71 224 7574

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  • Publication
    Type: journal article
    URL: https://www.learntechlib.org/primary/p/220264/
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/109738
  • Publication
    Fostering Students' Academic Writing Skills: Feedback Model for an AI-enabled Support Environment.
    (Association for the Advancement of Computing in Education (AACE), 2021-11-09)
    Seufert, Sabine
    ;
    Burkhard, Michael
    ;
    Handschuh, Siegfried
    Due to recent advances in natural language processing (NLP), a new generation of digital learning support systems is emerging, which make it possible to analyse the writing quality of texts offering individual, linguistic feedback to writers through various kinds of automated text evaluation. These intelligent tutoring systems (ITS) have to be integrated into existing teaching practices alongside traditional feedback providers (e.g., tutor, peer students). Therefore, this paper explores how academic writing skills of students could be fostered by providing different types of feedback from a tutor, peer students and an ITS. It proposes a feedback model for academic writing in an AI-enabled learning support environment and illustrates the importance of the different feedback providers in an academic writing use case. Through this, the paper aims to contribute to a better understanding of the changing nature of how students' academic writing skills can be fostered in the age of artificial intelligence.
    Type: journal article
    URL: https://www.learntechlib.org/primary/p/220270/
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/109740
  • Publication
    Student Perceptions of AI-Powered Writing Tools: Towards Individualized Teaching Strategies
    ( 2022-11-10)
    Burkhard, Michael
    Due to the advances of artificial intelligence (AI) and natural language processing, new kinds of Internet-based writing tools have emerged. Among other things, these AI-powered writing tools can be used by students for text translation, to improve spelling or for rewriting and summarizing texts. On the one hand, they can provide detailed recommendations for the adaptation of text elements within seconds. On the other hand, they also produce inconsistencies and errors, that students might not be aware of. How to deal with these tools in an educational context is a difficult question. Since writing tools are usually used unsupervised and without further instructions, students may need guidance from the teacher in interacting with those tools, to prevent the risk of misapplication. To better understand this underlying issue, the paper at hand uses survey data of 365 freshmen students to describe and analyze student perceptions of AI-powered writing tools. Regarding AI-powered writing tools, different student types were identified by using the k-means clustering method. The results suggest that students have different attitudes towards AI-powered writing tools. Some students may use them in an unreflective, non-sceptical way, which can lead to (un)voluntary plagiarism. Other students may not use writing tools at all, partly because they are sceptic, but also because they may lack meaningful learning strategies in general (course repeaters). Depending on the different student types, individualized teaching strategies might be helpful to promote or urge caution in the use of these tools.
    Type: conference paper
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/108085
  • Publication
    Educational Chatbots for Collaborative Learing: Results of a Design Experiment in a Middle School
    ( 2022-11-09)
    Burkhard, Michael
    ;
    Seufert, Sabine
    ;
    Cetto, Matthias
    ;
    Handschuh, Siegfried
    Educational chatbots promise many benefits for teaching and learning. Although chatbot use cases in this research field are rapidly growing, most studies focus on individual users rather than on collaborative group settings. To address this issue, this paper investigates how chatbot-mediated learning can be designed to foster middle school students in team-based assignments. Using an educational design research approach, quality indicators of educational chatbots were derived from the literature, which served as a guideline for the development of the chatbot Tubo (meaning tutoring bot). Tubo is part of a web-based team learning environment in which students can chat with each other and collaboratively work on their group assignments. As a team member and tutor of each group, Tubo guides the students through the learning journey by different scaffolding elements and helps with content-related questions the students have. As part of a first design cycle, the chatbot application was tested with a school class of a technical vocational school in Switzerland. The received feedback suggests that the approach of team-based learning with chatbots has a lot of potential from the students' and teachers' point of view. However, the role distribution of the individual group members may have to be further specified to address the different needs of autonomous as well as more control-oriented students.
    Type: conference paper
    URI: https://www.alexandria.unisg.ch/handle/20.500.14171/108091