TY - CHAP A1 - Gold-Veerkamp, Carolin T1 - Using Grounded Theory Methodology to Discover Undergraduates’ Preconceptions of Software Engineering KW - Software Engineering KW - Grounded theory Y1 - 2018 SP - 713 EP - 717 PB - IEEE ER - TY - CHAP A1 - Rücker, Michael T. A1 - Pancratz, Nils A1 - Gold-Veerkamp, Carolin A1 - Pinkwart, Niels A1 - Brinda, Torsten ED - Diethelm, Ira T1 - Workshop zu Alltagsvorstellungen in der Informatik: Erhebungsmethodik und Implikationen für den Unterricht T2 - Informatische Bildung zum Verstehen und Gestalten der digitalen Welt N2 - Ein zentrales Konzept jeder konstruktivistisch geprägten Auffassung von Lernen ist, dass das Vorwissen, die Präkonzepte und ggf. Fehlvorstellungen der Lernenden einen direkten Einfluss auf den Lernprozess haben: sowohl negativ als auch positiv. Speziell für die Informatik gilt, dass Lernende heutzutage von Beginn an in einer Welt aufwachsen, die von informatischen Artefakten und Systemen nahezu vollständig durchdrungen ist. Sie beobachten sie, interagieren mit ihnen und formen so Vorstellungen über ihre Funktionsweisen und Eigenschaften. Sie bilden somit bereits im Alltag und vor dem Beginn jeglicher Schulbildung kohärente Konzeptionen über zentrale Gegenstände und Inhalte der Informatik. Im Rahmen dieses Workshops werden zunächst verschiedene methodische Ansätze und erste Ergebnisse zu Erhebungen solcher Lernervorstellungen vorgestellt. Anschließend sollen diese anhand von drei Leitfragen verglichen und diskutiert werden: Welche Stärken und Schwächen haben die jeweils verwendeten empirischen Methoden bei der Erhebung von Lernervorstellungen in der Informatik? Wie können sie sich ggf. sinnvoll ergänzen? Welche Implikationen haben die erhobenen Vorstellungen für die Unterrichtspraxis? KW - Forschungsmethode KW - Konstruktivismus Y1 - 2017 UR - https://dl.gi.de/bitstream/handle/20.500.12116/4340/paper.pdf?sequence=1&isAllowed=y SN - 978-3-88579-668-8 SP - 393 EP - 401 PB - Köllen Druck+Verlag GmbH CY - Bonn ER - TY - CHAP A1 - Gold-Veerkamp, Carolin T1 - Using Grounded Theory Methodology to Discover Undergraduates’ Preconceptions of Software Engineering T2 - 2018 IEEE Global Engineering Education Conference (EDUCON) KW - Software Engineering Y1 - 2018 SP - 707 EP - 711 PB - IEEE ER - TY - CHAP A1 - Gold-Veerkamp, Carolin T1 - A Software Engineer's Competencies: Undergraduate Preconceptions in Contrast to Teach-ing Intentions T2 - Proceedings of the 52nd Hawaii International Conference on System Sciences 2019 N2 - Unlike numerous scientific disciplines, the field of engineering has rarely been subject to investigations of undergraduate pre-/misconceptions except for STEM subjects within engineering degrees. When it comes to Software Engineering, some special issues have to be taken into account (e.g. novelty of the discipline and immateriality of the product) that make this discipline hard to teach and learn. Additionally, it requires a wide range of different technical competencies as well as soft skills. As a consequence, the goal is to improve learning by using undergraduates’ “right” conceptions as “points of departure” and reduce learning obstacles by facing misconceptions. This paper is giving some first insights into a quantitative study conducted with undergraduates – before and after instruction – as well as two professors using a questionnaire to rate Software Engineering competencies to elicit preconceptions. KW - Software Engineering Y1 - 2019 SN - 978-0-9981331-2-6 SP - 7789 EP - 7797 ER - TY - CHAP A1 - Klopp, Marco T1 - Teaching Generic Competences in Software Engineering via E-Learning T2 - International Conference on Teaching, Assessment and Learning for Engineering (TALE) N2 - The discipline ‘Software Engineering’ is difficult to represent in higher education, because of the complexity of software development projects and the variety of skills required. In addition to specialist skills (professional competences), generic competences are increasingly becoming the focus of education. This paper deals with the training of generic competences in the software engineering module. For this purpose, an existing didactic concept was enhanced by E-Learning with the help of a Moodle course. KW - E-Learning KW - Software Engineering Y1 - 2019 SP - 758 EP - 765 ER - TY - CHAP A1 - Klopp, Marco T1 - Work-in-Progress: Learning Culture of Generation Z in Informatics N2 - A new generation of students is entering the university - Generation Z. This generation is characterized mainly by the existing digitization, since they grew up entirely in it. With regard to different generations, the relationship of the different ages and the associated large cohort difference in the interaction between lecturers and learners should be taken into account and analysed. It’s important because, according to the Hattie study, the most important influencing factor for the learning success of learners are the teachers. This means that excellence in teaching (according to the characteristics of the learners) is the most important single factor for the learning outcome. In order to draw the link to Informatics, the consideration of the subject-related culture and the connected learning culture is of central importance. It is obvious to recognize learning cultures in their cultural context, in their reasons and with their consequences for lecturers and students. Frames are therefore not static, but socially constructed and therefore changeable. Learning cultures are created in a communicative negotiation process by all actors in a learning situation. Subject-related culture research also deals with the question of whether and to what extent university teaching differs and which different behaviors can be found among its members. The aim is to classify the Informatics subject-related culture and to describe the ideas and expectations of lecturers and students in the learning environment and in the various social contexts of Informatics, and to reconstruct implicit, practical knowledge for the improvement of learning in Informatics. KW - Generation Geschichte 1995-2010 KW - Lernerfolg KW - Informatikstudium Y1 - 2020 SP - 1589 EP - 1593 PB - IEEE ER - TY - CHAP A1 - Gold-Veerkamp, Carolin A1 - Saray, Nermin T1 - A Systematic Literature Review on Misconceptions in Software Engineering T2 - Proceedings of the The Fifteenth International Conference on Software Engineering Advances (ICSEA) KW - Softwareentwicklung Y1 - 2020 UR - https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwjQ2KCbh7rvAhWW7aQKHfgpBOEQFjACegQIBBAD&url=http%3A%2F%2Fns2.thinkmind.org%2Farticles%2Ficsea_2020_1_10_10003.pdf&usg=AOvVaw1jFCohv5FyoeiAFU9gFOX0 SN - 978-1-61208-827-3 SP - 1 EP - 8 ER - TY - CHAP A1 - Gold-Veerkamp, Carolin T1 - Validated Undergraduates’ Misconceptions about Software Engineering T2 - Global Engineering Education Conference (EDUCON) KW - Software Engineering Y1 - 2021 PB - IEEE ER - TY - CHAP A1 - Klopp, Marco A1 - Dörringer, Antonia A1 - Eigler, Tobias A1 - Bartel, Paula A1 - Hochstetter, Marvin A1 - Weishaupt, Andreas A1 - Geirhos, Philipp A1 - Abke, Jörg A1 - Hagel, Georg A1 - Elsebach, Jens A1 - Rossmann, Raphael ED - Mottok, Jürgen T1 - Development of an Authoring Tool for the Creation of Individual 3D Game-Based Learning Environments T2 - ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education N2 - Game-based learning in general and serious games in particular have a promising potential in higher education. In this article we going to show the capability of serious games with regard to current challenges in higher education. The focus of this article is the presentation of the AdLer authoring tool, which offers lecturers the possibility to design and generate virtual 3D learning environments in which students can interact with learning content according to the principles of game-based learning. KW - 3D Learning Environment KW - Authoring Tool KW - Game-based Learning KW - Serious Games KW - Lernspiel KW - Dreidimensionale Computergrafik Y1 - 2023 UR - https://dl.acm.org/doi/proceedings/10.1145/3593663 SN - 978-1-4503-9956-2 VL - 2023 IS - 5. SP - 204 EP - 209 PB - Association for Computing Machinery (ACM) CY - New York, NY, United States ER - TY - CHAP A1 - Dörringer, Antonia A1 - Klopp, Marco A1 - Schaab, Lukas A1 - Hochstetter, Marvin A1 - Glaab, Daniel A1 - Bartel, Paula A1 - Abke, Jörg A1 - Elsebach, Jens A1 - Rossmann, Raphael A1 - Hagel, Georg ED - Röpke, René ED - Schroeder, Ulrike T1 - AdLer: 3D-Lernumgebung für Studierende T2 - 21. Fachtagung Bildungstechnologien (DELFI) KW - Serious Games KW - 3D-Lernumgebung KW - Game-based Learning KW - Lernspiel KW - Dreidimensionale Computergrafik Y1 - 2023 U6 - https://doi.org/10.18420/delfi2023-41 VL - 2023 SP - 251 EP - 252 ER - TY - CHAP A1 - Hock, Isabell A1 - Haug, Jim A1 - Abke, Jörg T1 - DIDACTIC INTEGRATION OF SELF-STUDY AND FACE-TO-FACE TEACHING: EXPERIENCES WITH AN ADAPTIVE LEARNING SYSTEM IN ENGINEERING EDUCATION T2 - ICERI Proceedings N2 - This paper presents a study of student perspectives on the didactic integration of digital learning elements into face-to-face university lectures and seminars. The overarching context is the use of the adaptive learning system (ALS) HASKI (short for Hochschullehre: Adaptiv, selbstgesteuert, KI-gestützt, i.e. Higher Education: Adaptive, Self-Directed, AI-Supported), which was tested in computer science teaching within a blended learning approach, more specifically in flipped classroom scenarios. The joint project, consisting of three Bavarian universities, focuses on the exploratory integration of an AI-based ALS into higher education. The system was applied in a course for mechatronics students (2nd semester) and provided a variety of adaptive learning elements. HASKI generates individual learning paths with AI based on learning behavior and learning styles. It is designed to promote personalized, self-directed learning as support for blended learning scenarios. The method chosen for data collection is a qualitative content analysis based on exploratory interviews with a semi-structured set of questions. Four central analysis criteria were considered: acceptance and perception of the learning elements, integration into lectures and exercise sessions, didactic coherence, and suggestions for improvement. The results show that students prefer explanatory scripts, interactive tasks, and quiz elements that require a certain degree of reflection. In addition, the respondents are largely convinced of the integration into the seminar, as the HASKI system adequately guides them for what to prepare for. When it comes to embedding the system into lectures, especially in the form of question rotation in small groups, the feedback is ambivalent. Although the potential for in-depth learning was recognized, the low participation of fellow students was critically reflected upon. A particular difficulty mentioned was the lack of coordination between self-study and classroom attendance. While some participants saw this as a discrepancy of coherence, others viewed the adaptive system as a balancing factor. There was a desire for a clearer time structure and more in-depth materials that go beyond mere repetition. Overall, the findings provide initial indicators of successful aspects in the integration of adaptive systems into classroom teaching. The continuous development of a clear didactic division of roles between self-study and classroom phases is of central importance here. Further research with larger samples, if necessary, could provide more comprehensive insights. KW - E-Learning KW - Ingenieurstudium KW - Unterrichtsmethode Y1 - 2025 SN - 978-84-09-78706-7 U6 - https://doi.org/https://doi.org/10.21125/iceri.2025.1600 SN - 2340-1095 VL - 1 SP - 5825 EP - 5829 PB - IATED ER - TY - CHAP A1 - Schoppel, Paul A1 - Haug, Jim A1 - Manz, Julian A1 - Bigler, Dimitri A1 - Hock, Isabell A1 - Abke, Jörg A1 - Hagel, Georg T1 - METHODICAL APPROACH FOR ANALYZING LEARNING PATH FITNESS IN AN AI-BASED ADAPTIVE LEARNING SYSTEM T2 - EDULEARN Proceedings N2 - Learning paths are a cornerstone of many adaptive learning systems, particularly those focusing on adaptive navigational techniques. Evaluating and analyzing these paths is therefore crucial to ensure they effectively support both learners and instructors. For eLearning this process must be highly scalable despite minimal oversight and little to no control over learners’ behavior. Consequently, learning path evaluation should be automated, user-friendly, and precise. However, current research on this topic often emphasizes simulations, performance metrics, or mathematical models, without fully considering the broader, learner-centered aspects necessary for meaningful adaptation. The authors prior findings also indicate that approaches to assessing the suitability of learning paths must be optimized. To address these gaps, this paper presents a potential methodological approach for comprehensive learning path evaluation, aiming to enhance both the precision of adaptive learning systems and the overall learning experience. Three different algorithms, derived from learning style tendencies and a lecturer recommendation, were analyzed as an illustrative example, although the method itself is not constrained by the form or data basis of these algorithms. The adaptive learning system utilizes various measures to gauge the suitability of a learning path, all gathered through real-time learner feedback. These measures include the correlation between students’ preferred path and each algorithm, referred to as it’s fitness, the alignment between students’ actual adherence to a generated path and their own perception of their study behavior as well as their satisfaction with the path, and the connection between algorithm fitness and both actual performance and perceived performance. To collect data, students were asked to create their own preferred learning paths by digitally arranging the provided learning elements after receiving an introduction to the respective categories. Once they had completed a topic with a generated learning path, they rated their satisfaction with it and indicated whether they had followed its sequence. They also estimated whether their knowledge level had changed. Learning analytics were then employed to compare these self-reports with students’ actual study behavior. Performance was measured using a rating system, while Spearman’s Rho and Kendall’s Tau served as the main correlation metrics for data analysis. The results indicate that all three algorithms produce paths more closely aligned with students’ preferred learning paths than the lecturer recommendation, although no single algorithm demonstrated clear dominance. Student satisfaction showed some correlation with the fitness of the generated learning path. Additionally, student ratings appeared to have a slight positive correlation with learning path fitness, whereas self-perceived performance showed no discernible difference. Analysis of the link between actual student behavior and their feedback suggested that students were not reliable in judging whether or not they had followed a learning path. These findings are consistent with the authors earlier work suggesting the potential effectiveness of the learning path algorithms examined, thus supporting this new methodological approach to analyzing learning paths. The study also provided valuable insights for further development; however, its limited sample size remains a challenge for validation. KW - E-Learning KW - Unterrichtsmethode Y1 - 2025 SN - 978-84-09-74218-9 U6 - https://doi.org/https://doi.org/10.21125/edulearn.2025.2430 SN - 2340-1117 VL - 1 SP - 9438 EP - 9446 PB - IATED ER -