The concept of the metaverse, recently re-emerging in public discourse, is viewed by some as the internet's next evolutionary stage, while others regard it as a dubious promise of a future where physical and digital worlds merge seamlessly. As the metaverse takes shape, it is crucial to question whether its design will embody the values of the societies it aims to serve.

LLM-based tools such as ChatGPT, GitHub Copilot, and the like have already arrived in software development practice, and continue to change the way of how software is created. Students use Generative AI tools for any purpose, whether we agree with the use or not. In this paper, we argue that in order to appropriately prepare our students for professional life, we educators need to incorporate the use of these tools explicitly into the teaching and learning process, so that students will learn a systematic and professional usage of these tools. Teaching basic software development concepts to students with only little or no prior knowledge has always been a challenge. Incorporating GenAI-based tools into software development education requires some careful rethinking of teaching concepts, especially with respect to constructive alignment, i. e. aligning learning objectives, teaching and learning methods, and exams to address GenAI-based support. Based upon first observations on the usage of GenAI tools in class, in this paper we suggest and compare concepts for teaching and learning basic software development that integrate GenAI tools at different levels of intensity and at different points during a semester. From these observations, we derive recommendations both for teaching and learning settings and for corresponding assessments, for teaching software development in a constructively aligned way in the age of GenAI tools.

The principle of constructive alignment requires that learning objectives, exam objectives and learning methods should be aligned with each other. This talk focuses on the alignment of learning objectives and exams for modern educational settings in software-related courses. As the use of LLM-based tools such as github-copilot or chatGPT has become an integral part of software technology, knowledge about LLM-based tools and their responsible use will also be addressed. For our courses on software-related topics we as instructors need to formulate learning objectives at different levels of granularity: from module descriptions down to fine-grained objectives for a single lecture or learning nugget. The definition of competence-oriented learning objectives at all levels of granularity is discussed, based on Anderson and Krathwohl's revision of Bloom's six-level taxonomy. For the assessment process, it is necessary to find appropriate forms of examinations that are constructively aligned with the learning objectives. Assessing programming skills requires forms other than just pen-and-paper exams. Suggestions for hands-on lab exams are discussed as well as tasks that can be used.

To assess in a constructively aligned way those programming competences that are relevant for the professional practice of future software developers, an assessment format would be suitable where students actively program, within the integrated development environment (IDE) that they are individually used to, and with unrestricted access for researching in the web. A format that accommodates these needs well is “Bring Your Own Device, Open Book, Open Web”, where students work on their own devices against given git repositories, with full access on knowledge bases and the internet. In this work, we share experiences and suggest well established practices for executing this exam type. As well, we discuss how the ready availability of large language models impacts this assessment type.

In our teaching, we observe that students rarely explicitly ask questions, no matter what channels we offer, and even though there obviously are open issues that need to be clarified, both organizational and content-related. However, to support our students properly, we require their cooperation in order to identify what they really need. To achieve this, we analyzed the situation in more detail, identifying possibly relevant facets such as the ability to identify open issues at all, formulating a specific question, selecting an appropriate channel for posing a question, as well as emotional issues such as shyness, shame or fear of humiliation. In order to validate the relevance of these different facets, we conducted both qualitative and quantitative investigations with our cohorts over the last two years. The results indicate that students struggle with each of these facets to a certain degree, especially with the emotional aspects. To improve the situation, we suggest a set of good teaching practices and interventions that foster our students' abilities to identify open issues, formulate specific question, select an appropriate channel for posing their question, and to overcome possible shyness or even fear.

AI -systems that are based on large language models, such as ChatGPT, have quickly increased their prowess over the last year, and at the same time became readily available. As of now, many disciplines gain experience in using tools such as ChatGPT in a professional setting - and software engineering is no exception. Just as with any new kind of tooling, it is to be expected that in the era of ChatGPT, some traditional skills of the discipline will become rather obsolete, while at the same time new skill sets emerge that will be required from future professionals. Therefore, as educators we must reconsider the skill set we aim at fostering in our software engineering students, and adapt our intended learning outcomes accordingly. Furthermore, we need to adapt both assessment strategies and the teaching and learning methods we employ, in order to provide our students with a study experience that adheres to the principle of constructive alignment.

The pandemic forced our institution from classroom teaching to complete online remote teaching. After the pandemic we are faced with questions of how we will continue with remote and especially with hybrid teaching formats. This includes the development of effective setups for hybrid and remote teaching scenarios - and to determine which setup is to be preferred in which context. Furthermore we have to find didactic formats to use in remote and hybrid teaching settings. In this paper we present our experiences with the evolution of a hybrid teaching setup as it grew while we detected and incorporated more and more requirements. Our main goal was to overcome several issues related to technical handling during the hybrid lectures, and to simultaneously create a motivating environment for students. The setups considered demand for different effort in terms of technical investment and operations. The most important idea was to separate presentation and video conferencing to different computers, thus tremendously simplifying the handling. One setting is then evaluated for a cohort of the module Software Development during summer term 2022. Evaluation results are very promising. We further coin several didactic issues for hybrid teaching scenarios.

We believe that we need to put more emphasis on helping students develop problem solving capabilities in our teaching on software development.Our research question is how much mental effort students invest in the different phases of problem solving: Understanding, Solution Planning, Implementation and Review. Other questions are which category of thinking they focus on, and how the effort put into each phase correlates to success.We designed and performed an empirical study with the intention to gain insights into problem solving skills of our students. In this study, CS-students were asked to solve different typical programming problems and they were guided through the process of problem solving with a kind of coding interview. First results show that that the implementation makes up the smallest portion of the effort, measured in terms of number of characters in our interviews’ transcripts. Students who were more thorough in analyzing the problem had generally longer implementation phases, indicating more substantial changes to the implementation than those who could not solve the problem. Unexpectedly, the analyzing phase took the successful students just as long as the ones who were not successful.All students repeatedly switched between the typical phases of problem solving. Students who proceeded in a more structured manner were the most successful. We see evidence that a lack of programming knowledge was not a main cause of failure in the fact that those students who could not solve the task have already failed at the problem analysis.Using insights gained from this kind of study will help to improve teaching of problem solving in introductory programming courses the future.

We continuously face high dropout rates in our faculty's Bachelor degree programs in Computer Science and in Information Systems. This is a quite common problem across engineering and computer science departments. Economically, for the university dropout means a waste of resources. On the other hand, to the young people it means a waste of lifetime, even though they might gain some experience. Furthermore, the labor market demands for many more well-educated engineers and IT specialists than are currently output. When we want to take special care of students that are in danger of dropping out, we must ensure that we identify those that really need this support. This group is sometimes called the “murky middle”. To identify them, we not only have to differentiate them from those students that will eventually earn their degree even without counseling, but also have to distinguish them from those students that do not seriously study at all - which is quite a significant number. Data analysis techniques on students' demographic and progress data have shown potential for an early prediction of dropout. We use logistic regression to identify factors for study success or failure, and we apply decision tree analysis to support the process of deciding which students we should invite to special counseling programs. Our models reach a similar high accuracy as previously reported studies with respect to predicting whether a student will drop out after the first semester. We also demonstrate that we are able to predict reasonably well whom we should - or should not - invite for counseling after the first semester.

At least in the western hemisphere, women in tech still are a minority instead of the matter of course that they should be. This holds true for the domain of Computer Science as well. Comparatively few women enter into CS-related courses of study, and even fewer of them finish these programs successfully. Thus, both the work force and society lose a large amount of the women's potential, which would be desperately needed to ensure that the technical innovation we need to cope with the pressing problems of our age are designed appropriately to address the needs of a wide range of people.To ensure that both women and men have comparable chances of successfully graduating in CS-related courses of study, we need to gain a closer insight into the hurdles that especially women are facing during their study process. For this means, we apply data analysis to the student data of our student administrative system, in order to identify major differences between the study progress of women and men, and to better understand where our female students struggle the most. Only if we understand this properly, we are able to improve our teaching purposefully in a gender sensitive way, and to introduce any structural changes that might help to increase and strengthen the women in our student body.

Over the last years, electronic exams have received increasing attention, as they offer far more potential than simply replacing paper-based questions by electronically supported multiple choice questions, or replacing blank paper by text fields in a web-browser or PDF form. Especially in the area of software development and software engineering, both students and teachers expect to benefit from an exam environment where students can utilize the same set of tools that they are used to from working on their homework exercises. Furthermore, teachers expect that electronic exams provide support with respect to automatic assessment. In this paper, we investigate applying electronic exams to introductory programming courses. In these exams, students have to solve programming problems using an integrated development environment, and hand in source code as their solution. This, however, requires a shift in formulating exam tasks, in order to align these tasks with learning objectives. It also requires careful investigation into the students' ability to cope with the environment and the rigorous supervision by a compiler and other checkers under time restrictions and, possibly, the nerves of an exam situation. To achieve this, we discuss how programming tasks can be designed in a manner that allows addressing all levels of Bloom's taxonomy of learning objectives, in order to implement constructive alignment. Furthermore we analyze our students' behavior during exams and their perception of this kind of exam. As well, we analyze the resulting solutions and identify typical error patterns that occur.

Dropout rates in STEM subjects are consistently high almost all over the world. To remedy the situation, many universities are taking measures that aim at reducing dropout rates. For these measures to be most effective, tools are required to predictively identify those students that are at risk of dropping out, to identify the individual causes of their struggles, to then select and apply appropriate interventions and finally to assess the effects that these interventions achieve.In this study, we focus on the first of these steps, i.e., identifying early indicators for potential risk of student dropout in our CS related degree programs. To achieve this, we analyse the data from our student administration system, focusing on our students’ performance in their first semester of studies. More precisely, we relate dropout to success rates and investigate into different behavioural patterns that lead to student dropout. Furthermore, we identify several factors that increase the risk of dropping out, and document some first early indicators for student dropout.

In many Computer-Science study programs, first-year students struggle with the transition from secondary school to academic education. To improve the situation at our institution, we designed an innovative, competency-oriented prep course for our first-year students. Instead of just repeating basic mathematics, this preparatory course took a more holistic approach by addressing both technological and non-technological skills that are considered to be essential for a successful start in CS-related study programs. These competences comprise self-regulation and learning techniques, problem solving, abstract and logical thinking as well as the reactivation of fundamental mathematics from school. To analyze the effectiveness of our approach, we evaluated the pilot run.

It is commonly agreed that the competence of abstract thinking is an important skill for software developers. The analysis of students’ answers of our in-house developed Abstract Thinking Assessment (ATA) provides evidence that the competence of abstract thinking is an essential prerequisite for the acquisition of professional software development skills. Moreover, a deficit in abstract thinking competence of first-year students is indicated by the data. Thus, teaching professional software development skills should address the competence of abstract thinking explicitly.The question we try to answer is: How can we promote abstract thinking competence in a course on software development? This work proposes a concept to address the students’ competence of abstract thinking integrated into a class on software development. This paper presents the revision of the teaching concept of the module Software Development I with regard to the competence of abstract thinking. Concepts and approaches from literature are discussed. Moreover, we present the preparation of the teaching units, the material used and how they have been put into practice. This process considers findings from the competence model, the analysis of the ATA and the literature review. Furthermore, the teaching style has been changed from a traditional approach to pair-teaching. In the end, the teaching concept is evaluated.

Every student has to write a thesis statement at the end of their study programme. However, despite of this universality, both the process of supervision and the criteria used in the process of grading theses statements vary widely. In literature, there is a gap regarding the definition of demands and expectations on theses statements from a competence-oriented point of view. A thorough investigation of cognitive, non-technical competences that are required to successfully accomplish a thesis project and write the thesis itself has not yet been performed. In this paper, we propose a set of competences that are required to perform a thesis project and to create a thesis statement. Our goal is to apply the principles of constructive alignment to the supervision of thesis statements, as it is commonly done for lecture-based or lab-based teaching. Based on a review of literature and module specifications, we specify requirements for thesis statements and use them as a basis for deriving appropriate learning objectives for thesis projects. Then, we identify cognitive competences that are required to fulfill these learning objectives. On this basis, recommendations are developed for teaching practices in the process of supervision, as well as for grading of thesis statements.

Especially at the beginning of university studies, students form a group that is heterogeneous in many aspects. Compared with other disciplines, there is a significant dropout in computer science. We ascribe this to the fact that first-semester students often have significant deficits in cognitive competences - such as systematic and logical thinking - which are crucial for studying computer science successfully. To capture the students' learning capabilities, we developed a diagnostic test containing tasks that aim at evaluating the incoming students' initial level of highly relevant cognitive competences. In this paper, we evaluate the quality of this diagnostic test from a statistical point of view. Particular emphasis is placed on the analysis of the methodical competence. We assume that this component of the students' cognitive competences is of particular importance, as it is relevant not only for a successful start into the study phase, but is also essential for acquiring new skills and technical competences in computer science.

Several weeks after new first-year students in Computer Science arrived, many lecturers complain that some of their students are not well-equipped with all competences necessary to study successfully. Hence, they struggle. This situation appears at different universities in various countries. Otherwise, there are students in every place, which meet the study requirements rather easily. This paper describes the development of a test, assessing first-year students' cognitive competences as well as basic knowledge in maths and computer usage. The test allows insights into the first-year students' initial level of competences. Thus, lecturers can base their lectures on the students current level. We conducted this test in the last four years: a pilot study as well as three regular runs. Until now we collected test results of over 750 students. First insights into the results facilitate the assumption that important competences are lacking and already influence our teaching in introductory courses. The next step is to clarify with help of the data, which competences influence the study success respectively the study failure.

How do lecturers know that their teaching is effective? If they want to formally assess this, they first have to define learning objectives that specify the intended outcome of their teaching, in terms of competencies to be developed in their students. On this basis, they can then design appropriate assessment tools, such as formal exams, that attempt to objectively measure to what extent the aspired competencies have been developed. As an example, we focus an introductory, two-term class on software development. We provide a subset of a generic definition of learning objectives that covers all six levels of Bloom's taxonomy. Based on that, we design an exam concept that matches these objectives, specifying the share that each competence level holds in the overall exam. Finally, we analyze exam results focusing on competence levels that our students reached.

The student entry phase is the period of a study process in which fundamental technical and non-technical skills should be acquired. The interrelation of those skills is not only crucial for the study process itself. Rather, the systematic, well-reflected methodological usage of specific technical knowledge is a key element for the future professional career after graduation. Unfortunately, during our last years of teaching we noticed that most of the novices in software engineering are neither well equipped with the necessary soft skills, nor can they handle the key technical skills in an appropriate way at the end of their first semester. Therefore, we designed a project that addresses technical and non-technical competencies in an integrated way. In the project, we induce students to actively increase their awareness of their own proficiency in technical and non-technical skills by guided reflection and feedback processes, both individually as well as in a group.

Many programming errors that we observe in novice programmers coincide with those that are described in literature. Due to their vast number, it is practically impossible to list all errors explicitly and describe interventions for each specific error. Therefore, to reduce the number of single instances that have to be considered, we developed an error classification scheme that enables us to classify errors into seven classes. These classes are based on the revised Bloom-taxonomy and focus on the underlying problem that causes the observed errors. Based on these classes, we investigate and develop interventions that focus on the underlying problems, thus addressing the problem causes rather than their symptoms. In this paper, we describe both the interventions themselves, and the research process we applied for identifying these interventions.

In this paper we present accumulated results from two years of experience with a teaching unit on debugging Java programs. With this special teaching unit, we strive to foster the debugging skills of our students. Students were asked to find different defects in given code, to analyze these and finally to fix them. As well, students were requested to document their approach in writing. The achieved results ranged from “all bugs found and fixed” to “completely lost in the code”. When analyzing these results, we discovered that the debugging skills of our students seem to correlate with some non-technical skills that are essential base competencies in software engineering, such as the ability to work in a systematic way. This implies that for improving our students' debugging skills, it is helpful to address not only the technical aspects of debugging, but to foster the required base competencies as well.

Just-in-Time Teaching (JiTT) is an activating teaching method that is highly popular in today's university education systems. In this paper, we use the experience we made using JiTT during two semesters to analyze the effectiveness of this teaching method.

For us a lecturers, it is important to assess early on in a class whether we effectively reach our students and create the desired teaching outcome. Usually, the major assessment is some kind of exam which takes place at the end of term - and thus at a time when it is generally too late to change anything. Instead, lecturers need a toolset of different feedback and evaluation techniques that provide feedback as required, at different intervals throughout term, adequate for different teaching settings and group sizes, and with a reasonable amount of time and effort required from all parties involved. To help choose a suitable feedback technique for a specific teaching context, we introduce a classification scheme for feedback techniques. On this basis, we rate a variety of well-established feedback techniques, thus making it possible to select those feedback techniques that best suit one's individual needs.

Many freshmen students of computer science are unaware of the requirements and job profiles of their future professional domain. To provide them with a deeper insight into the requirements of their future jobs at an early point of their studies, we designed a software engineering simulation project that focuses on the main tasks a software engineer has to deal with in professional life. More precisely, this project focuses on the major software-technical, methodological and practical competencies every computer scientist-to-be must acquire. Thus, this introductory software engineering project serves as a kind of “kick off meeting” for freshmen students in computer science. It creates an initial insight into and understanding of the overall interrelation of the different tasks and skills that will be a crucial part both of their study process as well as of their future professional career.

Since unit testing is a skill required of professional software developers, lecturers have to develop this skill in their software engineering students. Therefore, we introduce the approach of “objects first, tests second”, which incorporates unit testing into introductory programming classes. We discuss requirements that teaching materials must meet to effectively support this approach, and present a concept for assessing the quality of student written tests. An analysis of students' results illustrates the effectiveness of this teaching approach.

First-year students are often not well equipped with the base competencies that are a necessary precondition for effectively acquiring complex new knowledge. Among others, these base competencies comprise self-organization, analytical thinking, or communication skills. Shortcomings in these competencies often lead to problems in the study process. To solve these problems, we need to investigate the students' initial competencies, in order to become aware of possible deficits, find ways to deal with them, and thus to enable students to reach their goals. Therefore, we developed a self-assessment on base competencies, an accompanying knowledge test and a questionnaire on personal information. The data collected by these tools was analyzed, searching for competence characteristics which influence whether our students persevere and participate in the final exam, or drop out early. The results of our data analysis support the assumption that both non-technical and technical competencies are crucial to study successfully. Correlation analysis has identified several characteristics which distinguish the students that participate in the exam from those who do not. Based on these results, we suggest ways to optimize university courses, teaching methods, and the support of first-year students to meet their needs.

Over the recent years, we experienced that a significant percentage of first-year students shows difficulties in acquiring even introductory software development knowledge, as well as in coping with the study process itself. In most cases, the core problem is not a lack of general intellectual capacity, but rather significant deficiencies in certain base competencies (i.e. self-, practical and cognitive as well as social competencies). We imply that these base competencies are crucial for successfully studying computer science or related topics. In order to identify these base competencies, we collected a superset of competencies from literature, structured this set, and performed filtering and clustering steps, resulting in almost 100 remaining base competencies that are relevant in our teaching context. As it is impossible for any lecturer to develop all these competencies in a single effort, we finally boiled this set down to a selection of those competencies that we deem to be most relevant for successfully studying software related topics at university level. Towards this end, for each competence, we defined what we the lecturers expect from our incoming freshmen students. In addition, we specified the skill level expected by the job market. Furthermore, we assessed the skill level of those 70% of our students that have obvious difficulties in coping with study requirements. Finally, we selected those competencies with a large difference between what is expected from our graduates and what we find in our incoming cohort. This analysis resulted in a selection of 27 competencies that we deem to be highly essential prerequisites for software engineering education, and which are not sufficiently well developed in the vast majority of freshmen students. For each of these base competencies we provide definitions and denote reasons for their selection.

Not all incoming students are sufficiently well endowed with those base competencies (such as self organization, analytical thinking or communication skills) that are prerequisite for acquiring complex new knowledge as well as coping with the study process itself. As lecturers, we have to be aware of our incoming students' base competency profile, in order to pick them up where they are and help them develop whatever they need to study successfully. To investigate the students' initial skills regarding their base competencies, we developed a self-assessment focusing on selected self competencies, practical and cognitive skills as well as social competencies that are crucial to study computer science or related topics. In this paper, we present our assessment approach and its design. An initial evaluation in which 320 students were involved indicates that deficits in base competencies can be made tangible for students. Based on the deficits we identified, we are going to optimize our courses to meet freshmen students' needs in a better way.

In this paper we describe experiences using improvisational theater (improv) techniques in teaching acitivities. The educational setting where we aim to profit from these experiences are software engineering courses. The usefulness of improvisational theater in different contexts was discussed in the literature during the last few years. We conducted two sessions of improvisational theater with two objectives: (a) enhancing creativity and (b) enabling the process of team building. This paper describes our motivation, the goals, the educational setting and the different improv exercises performed. Results of our evaluation indicate that the majority of students enjoyed the improv sessions. Exercises focused on team building gained better results than those focusing on creativity. Our overall impression was that the success of using improv depends on careful planning and performance on the one hand and on the students' individual comfort zone on the other hand.

In our everyday teaching we experience that many first-year students are ill prepared for the demands of an academic study process in technical domains. Usually, the students' problems are not rooted in a lack of intellectual capacity or previously acquired founding expertise in the chosen course of study. Rather, it is the deficiencies in more basic competencies such as practical and cognitive, self and social areas that place a major hurdle in the students' learning process. In an attempt to elucidate and improve this situation, as a first step we develop a questionnaire that captures the lecturers' expectations on student competencies in these areas, as opposed to their view on competencies that first-year students possess in reality. This questionnaire is also applied to capture the university-employer skill gap.

Currently many efforts are undertaken to develop and install communication networks based on low Earth orbit (LEO) and intermediate circular orbit (ICO) satellites. However, many problems are to be solved before the final operation of such networks. This paper deals with basic design problems of LEO/ICO-based networks. The topology of the satellite network is considered and estimates for the number of satellites necessary, orbits and number of communication channels per satellite are derived. The features and consequences of intersatellite links are discussed. The number of communication channels per link is derived with a more elaborate model. This includes the radio links from the satellites to mobile users and to gateways, as well as intersatellite links and terrestrial lines. We introduce a formal model for LEO/ICO based networks and propose a method for the evaluation of the link capacities, given the network topology and the traffic requirements. As an example, two constellations are investigated in detail. One of these constellations is the Iridium system proposed by Motorola, the other is the LEONET concept developed in an ESA study. Finally, the influence of unequal traffic distribution is discussed.>

Currently, many efforts are undertaken to develop and install world-wide communications networks based on low Earth orbit (LEO) or intermediate circular orbit (ICO) satellites. However, many problems are still to be solved. One of these problems, namely the design of strategies for handover between satellites is addressed. Strategies that intend to maximize the instantaneous elevation angle or to minimize the handover rate are compared. The authors also consider not performing handovers at all. The main result is that sufficient call duration can be guaranteed without performing handovers when an intermediate orbit altitude (at about 6000 km) is chosen.>

A hybrid simulation tool for real-time performance measurements of complete networks is presented. The simulation tool combines the advantages of software and hardware modules. Recorded channel data are included. They allow the reproduction of realistic situations in the laboratory. Synchronization problems and noise are considered. As an example, stabilized slotted ALOHA access protocols were implemented and investigated in land-mobile satellite environments. A slotted ALOHA-based modified channel access strategy for highly unreliable channels is proposed requiring all mobile stations to estimate the link quality before starting a transmission. The different strategies are analyzed by simulation as well as the analytical methods. Transmission parameters are determined and optimized using a combination of analysis and simulation. The results show the power of the simulation tool and the better performance of stabilized slotted ALOHA with link-quality estimation in city channels.>

The capture phenomenon and its consequences in nonbitsynchronous mobile packet radio networks for binary phase-shift-keying (BPSK) and differential phase-shift-keying modulation are investigated. Exact values of the bit error probability for given signal-to-noise ratios of colliding BPSK signals are derived. Packet error rates, which are needed for analysis of slotted random multiple access methods, are obtained by simulation. Two kinds of mobile radio channels are considered: the Rayleigh fading channel and the land mobile satellite channel. In the latter, because of shadowing, the probability that one of several colliding data packets is correctly received can be on the same order as the probability that a single packet that is not experiencing a collision is correctly received. The influence of Reed-Solomon codes on packet error probabilities is also studied. A slotted ALOHA system using the land mobile satellite channel is analyzed. It is found that with significant shadowing, the overall system throughput may reach the point-to-point throughput. Also, the code rate cannot be optimized in a straightforward manner by assuming one single transmission at a time.>