Andreas Scholl

dblp:378/5603 · DBLP profile ↗
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4ranked-venue papers
2as first author
4since 2021 · last 2026
0009-0009-1275-1374ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 4 · 2 first-author · 4 since 2021
YearPublicationVenuePosition
2026 Using the Potential of GenAI Tools for Accessibility
Natalie Kiesler, Bedour Alshaigy, Yasmine N. El-Glaly, Ilenia Fronza, Alex Gerdes, Earl W. Huff Jr., Sven Jacobs, Dominic Lohr, Raymond Pettit, Andreas Scholl, Sandra Schulz 0001, David H. Smith
ITiCSE (2)10
2025 Developing an AI Concept Inventory for Non-Experts
abstract
This working group aims to develop a research-based AI concept inventory (AI CI) to assess the understanding of foundational AI concepts among non-experts. By identifying core concepts and common misconceptions through literature reviews, expert consultations, and iterative validation, the group will create a user-friendly assessment tool that can be used to capture snapshots of AI understanding, support benchmarking across contexts, and inform educational initiatives and policy. Designed for diverse non-expert audiences, including educators, students, and the general public, this tool can provide valuable insights into how AI knowledge evolves over time, contributing to the broader goal of promoting AI literacy in everyday contexts.
Linda Mannila, Julie Henry, Tobias Bahr, Christos Chytas, Harold S. Connamacher, Henry Hickman, Barbara C. N. Müller, Simone Opel, Andreas Scholl
ITiCSE (2)9
2025 SCRIPT - Supportive Chatbot for Resolving Introductory Programming Tasks
abstract
In this poster, we present a new educational tool based on GenAI: a Supportive Chatbot for Resolving Introductory Programming Tasks (SCRIPT). Its goal is to support novice learners of programming with guardrails and predefined prompts, so they can focus on the problem-solving process, and receive quality feedback.
Andreas Scholl, Natalie Kiesler
ITiCSE (2)1
2024 How Novice Programmers Use and Experience ChatGPT when Solving Programming Exercises in an Introductory Course
abstract
This research paper contributes to the computing education research community's understanding of Generative AI (GenAI) in the context of introductory programming, and specifically, how students utilize related tools, such as ChatGPT. An increased understanding of students' use is mandatory for educators and higher education institutions, as GenAI is here to stay, and its performance is likely to improve rapidly in the near future. Learning about students' use patterns is not only crucial to support their learning, but to develop adequate forms of instruction and assessment. With the rapid advancement of AI, its broad availability, and ubiquitous presence in educational environments, elaborating how AI can enhance learning experiences, especially in courses such as introductory programming is important. To date, most studies have focused on the educator's perspective on GenAI, its performance, characteristics, and limitations. However, the student perspective, and how they actually use GenAI tools in course contexts, has not been subject to a great number of studies. Therefore, this study is guided by the following research questions: (1) What do students report on their use pattern of ChatGPT in the context of introductory programming exercises? and (2) How do students perceive ChatGPT in the context of introductory programming exercises? To address these questions, computing students at a large German university were asked to solve programming tasks with the assistance of ChatGPT as part of their introductory programming course. Students (n=298) provided information regarding the use of ChatGPT, and their evaluation of the tool via an online survey. This research provides a comprehensive evaluation of ChatGPT-3.5's application by novice programmers in a higher education context. The findings reveal that while students widely adopt GenAI, their use varies significantly, ranging from acceptance of generated solutions to dynamic, and critical engagement. Therefore, this work has implications for educators designing guardrails or forms of instructions on the use of GenAI tools in the classroom.
Andreas Scholl, Natalie Kiesler
FIE1