Logo des Repositoriums

Auflistung nach Schlagwort "students"

1 - 4 von 4
  • Conference paper
    Analyzing Chat Protocols of Novice Programmers Solving Introductory Programming Tasks with ChatGPT
    (Proceedings of DELFI 2024, 2024) Scholl, Andreas; Schiffner, Daniel; Kiesler, Natalie
    Large Language Models (LLMs) have taken the world by storm, and students are assumed to use related tools at a great scale. In this research paper we aim to gain an understanding of how introductory programming students chat with LLMs and related tools, e.g., ChatGPT-3.5. To address this goal, computing students at a large German university were motivated to solve programming exercises with the assistance of ChatGPT as part of their weekly introductory course exercises. Then students (n=213) submitted their chat protocols (with 2335 prompts in sum) as data basis for this analysis. The data was analyzed w.r.t. the prompts, frequencies, the chats’ progress, contents, and other use pattern, which revealed a great variety of interactions, both potentially supportive and concerning. Learning about students’ interactions with ChatGPT will help inform and align teaching practices and instructions for future introductory programming courses in higher education.
  • Textdokument
    Barriers to Digital Higher Education Teaching during the COVID-19 Pandemic from Teachers’ and Students’ Perspectives
    (INFORMATIK 2022, 2022) Draxler-Weber,Nicole; Brink,Henning; Packmohr,Sven
    During the COVID-19 pandemic, the rapid transition to digital teaching enabled higher education institutions (HEIs) to continue teaching. The strict execution exposed barriers that both teachers and students have faced towards digital higher education teaching around the world. In this paper, the barriers from both perspectives are identified and systematically processed. For this purpose, a quantitative survey of 396 students from HEIs in Sweden, Türkiye, and Germany was conducted. The students’ barriers were identified and assigned to categories based on teachers’ barrier categories, which were analyzed in a pre-study by conducting a literature review. The teachers’ barrier categories could be confirmed by the students’ survey. However, within the subcategories, the two perspectives differ. All categories and subcategories are described in detail so that this contribution offers an overview of barriers that have to be overcome if digital higher education teaching will be followed in the future.
  • Textdokument
    A study on the quality mindedness of students
    (Software Engineering im Unterricht der Hochschulen (SEUH 2022), 2022) Dick, Steffen; Schulz, Stefan; Bockisch, Christoph
    Awareness of software quality is a skill generally agreed to be very important working in the industry, but we have observed that it receives little attention in the first-year programming education at universities. Besides preparing students for work life, we assume that good knowledge of software quality also helps computer science students to study more successfully. In this paper, we present a method for determining the quality-awareness, based on a diagnostic assignment and a questionnaire. Using the method we establish a baseline measurement in two courses that students typically follow in their first year, showing that quality awareness correlates with good grades. According to the baseline, the level of quality-mindedness of approximately half the students is not satisfactory.
  • Konferenzbeitrag
    Understanding the Adoption of ChatGPT in Higher Education: A Comparative Study with Insights from STEM and Business Students
    (Proceedings of Mensch und Computer 2024, 2024) Kubullek, Ann-Kathrin; Kumaç, Nadire; Dogangün, Aysegül
    Since ChatGPT’s introduction, generative artificial intelligence (AI) has significantly influenced the media, technological innovation, and educational discourse. Its increasing importance, especially in academia, necessitates a detailed examination of the impact of AI on higher education, particularly on how it changes teaching and learning processes. This study therefore looks at the factors affecting students’ attitudes towards AI technologies in the university setting, with a particular focus on the differences between business and STEM programmes. Using a mixed methods approach, the study combines surveys and interviews to collect data on students’ perceptions, attitudes and experiences with generative AI technology in academia. The data collected is analysed both quantitatively and qualitatively to reveal significant trends and insights into the adoption and use of generative AI tools in the university environment. The main objective of the study is to shed light on the determinants that determine the varying degrees of AI adoption in different academic disciplines. The findings have the potential to inform the implementation of educational technology and assist in the development of strategies for the effective integration of generative AI tools to meet the different needs and preferences of students in a range of academic contexts.