@inproceedings{GoldVeerkamp2018, author = {Gold-Veerkamp, Carolin}, title = {Using Grounded Theory Methodology to Discover Undergraduates' Preconceptions of Software Engineering}, publisher = {IEEE}, pages = {713 -- 717}, year = {2018}, subject = {Software Engineering}, language = {en} } @inproceedings{RueckerPancratzGoldVeerkampetal.2017, author = {R{\"u}cker, Michael T. and Pancratz, Nils and Gold-Veerkamp, Carolin and Pinkwart, Niels and Brinda, Torsten}, title = {Workshop zu Alltagsvorstellungen in der Informatik: Erhebungsmethodik und Implikationen f{\"u}r den Unterricht}, series = {Informatische Bildung zum Verstehen und Gestalten der digitalen Welt}, booktitle = {Informatische Bildung zum Verstehen und Gestalten der digitalen Welt}, editor = {Diethelm, Ira}, publisher = {K{\"o}llen Druck+Verlag GmbH}, address = {Bonn}, isbn = {978-3-88579-668-8}, pages = {393 -- 401}, year = {2017}, abstract = {Ein zentrales Konzept jeder konstruktivistisch gepr{\"a}gten Auffassung von Lernen ist, dass das Vorwissen, die Pr{\"a}konzepte und ggf. Fehlvorstellungen der Lernenden einen direkten Einfluss auf den Lernprozess haben: sowohl negativ als auch positiv. Speziell f{\"u}r die Informatik gilt, dass Lernende heutzutage von Beginn an in einer Welt aufwachsen, die von informatischen Artefakten und Systemen nahezu vollst{\"a}ndig durchdrungen ist. Sie beobachten sie, interagieren mit ihnen und formen so Vorstellungen {\"u}ber ihre Funktionsweisen und Eigenschaften. Sie bilden somit bereits im Alltag und vor dem Beginn jeglicher Schulbildung koh{\"a}rente Konzeptionen {\"u}ber zentrale Gegenst{\"a}nde und Inhalte der Informatik. Im Rahmen dieses Workshops werden zun{\"a}chst verschiedene methodische Ans{\"a}tze und erste Ergebnisse zu Erhebungen solcher Lernervorstellungen vorgestellt. Anschließend sollen diese anhand von drei Leitfragen verglichen und diskutiert werden: Welche St{\"a}rken und Schw{\"a}chen haben die jeweils verwendeten empirischen Methoden bei der Erhebung von Lernervorstellungen in der Informatik? Wie k{\"o}nnen sie sich ggf. sinnvoll erg{\"a}nzen? Welche Implikationen haben die erhobenen Vorstellungen f{\"u}r die Unterrichtspraxis?}, subject = {Forschungsmethode}, language = {de} } @inproceedings{GoldVeerkamp2018, author = {Gold-Veerkamp, Carolin}, title = {Using Grounded Theory Methodology to Discover Undergraduates' Preconceptions of Software Engineering}, series = {2018 IEEE Global Engineering Education Conference (EDUCON)}, booktitle = {2018 IEEE Global Engineering Education Conference (EDUCON)}, publisher = {IEEE}, pages = {707 -- 711}, year = {2018}, subject = {Software Engineering}, language = {en} } @inproceedings{GoldVeerkamp2019, author = {Gold-Veerkamp, Carolin}, title = {A Software Engineer's Competencies: Undergraduate Preconceptions in Contrast to Teach-ing Intentions}, series = {Proceedings of the 52nd Hawaii International Conference on System Sciences 2019}, booktitle = {Proceedings of the 52nd Hawaii International Conference on System Sciences 2019}, isbn = {978-0-9981331-2-6}, pages = {7789 -- 7797}, year = {2019}, abstract = {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.}, subject = {Software Engineering}, language = {en} } @inproceedings{Klopp2019, author = {Klopp, Marco}, title = {Teaching Generic Competences in Software Engineering via E-Learning}, series = {International Conference on Teaching, Assessment and Learning for Engineering (TALE)}, booktitle = {International Conference on Teaching, Assessment and Learning for Engineering (TALE)}, pages = {758 -- 765}, year = {2019}, abstract = {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.}, subject = {E-Learning}, language = {en} } @inproceedings{Klopp2020, author = {Klopp, Marco}, title = {Work-in-Progress: Learning Culture of Generation Z in Informatics}, publisher = {IEEE}, pages = {1589 -- 1593}, year = {2020}, abstract = {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.}, subject = {Generation Geschichte 1995-2010}, language = {en} } @inproceedings{GoldVeerkampSaray2020, author = {Gold-Veerkamp, Carolin and Saray, Nermin}, title = {A Systematic Literature Review on Misconceptions in Software Engineering}, series = {Proceedings of the The Fifteenth International Conference on Software Engineering Advances (ICSEA)}, booktitle = {Proceedings of the The Fifteenth International Conference on Software Engineering Advances (ICSEA)}, isbn = {978-1-61208-827-3}, pages = {1 -- 8}, year = {2020}, subject = {Softwareentwicklung}, language = {en} } @inproceedings{GoldVeerkamp2021, author = {Gold-Veerkamp, Carolin}, title = {Validated Undergraduates' Misconceptions about Software Engineering}, series = {Global Engineering Education Conference (EDUCON)}, booktitle = {Global Engineering Education Conference (EDUCON)}, publisher = {IEEE}, year = {2021}, subject = {Software Engineering}, language = {en} } @inproceedings{KloppDoerringerEigleretal.2023, author = {Klopp, Marco and D{\"o}rringer, Antonia and Eigler, Tobias and Bartel, Paula and Hochstetter, Marvin and Weishaupt, Andreas and Geirhos, Philipp and Abke, J{\"o}rg and Hagel, Georg and Elsebach, Jens and Rossmann, Raphael}, title = {Development of an Authoring Tool for the Creation of Individual 3D Game-Based Learning Environments}, series = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education}, volume = {2023}, booktitle = {ECSEE '23: Proceedings of the 5th European Conference on Software Engineering Education}, number = {5.}, editor = {Mottok, J{\"u}rgen}, publisher = {Association for Computing Machinery (ACM)}, address = {New York, NY, United States}, isbn = {978-1-4503-9956-2}, pages = {204 -- 209}, year = {2023}, abstract = {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.}, subject = {Lernspiel}, language = {en} } @inproceedings{DoerringerKloppSchaabetal.2023, author = {D{\"o}rringer, Antonia and Klopp, Marco and Schaab, Lukas and Hochstetter, Marvin and Glaab, Daniel and Bartel, Paula and Abke, J{\"o}rg and Elsebach, Jens and Rossmann, Raphael and Hagel, Georg}, title = {AdLer: 3D-Lernumgebung f{\"u}r Studierende}, series = {21. Fachtagung Bildungstechnologien (DELFI)}, volume = {2023}, booktitle = {21. Fachtagung Bildungstechnologien (DELFI)}, editor = {R{\"o}pke, Ren{\´e} and Schroeder, Ulrike}, doi = {10.18420/delfi2023-41}, pages = {251 -- 252}, year = {2023}, subject = {Lernspiel}, language = {de} } @inproceedings{HockHaugAbke2025, author = {Hock, Isabell and Haug, Jim and Abke, J{\"o}rg}, title = {DIDACTIC INTEGRATION OF SELF-STUDY AND FACE-TO-FACE TEACHING: EXPERIENCES WITH AN ADAPTIVE LEARNING SYSTEM IN ENGINEERING EDUCATION}, series = {ICERI Proceedings}, volume = {1}, booktitle = {ICERI Proceedings}, publisher = {IATED}, isbn = {978-84-09-78706-7}, issn = {2340-1095}, doi = {https://doi.org/10.21125/iceri.2025.1600}, pages = {5825 -- 5829}, year = {2025}, abstract = {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-gest{\"u}tzt, 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.}, subject = {E-Learning}, language = {en} } @inproceedings{SchoppelHaugManzetal.2025, author = {Schoppel, Paul and Haug, Jim and Manz, Julian and Bigler, Dimitri and Hock, Isabell and Abke, J{\"o}rg and Hagel, Georg}, title = {METHODICAL APPROACH FOR ANALYZING LEARNING PATH FITNESS IN AN AI-BASED ADAPTIVE LEARNING SYSTEM}, series = {EDULEARN Proceedings}, volume = {1}, booktitle = {EDULEARN Proceedings}, publisher = {IATED}, isbn = {978-84-09-74218-9}, issn = {2340-1117}, doi = {https://doi.org/10.21125/edulearn.2025.2430}, pages = {9438 -- 9446}, year = {2025}, abstract = {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.}, subject = {E-Learning}, language = {en} }