In higher education, learners become increasingly heterogeneous as they differ in, e.g., knowledge levels, competences, learning styles and media preferences. It is difficult for instructors to cater for these differences individually in face-to-face courses due to the effort for individualized supervision which does not scale for larger groups. One solution is to supplement face-to-face contact with tailored learning materials for use outside of regular physical classes. However, learners often do not know which material is most appropriate for them, which is why individualised recommendations are necessary. This paper outlines the reference architecture of an adaptive digital learning environment and how it interfaces to other independent information systems, e.g., to retrieve student data which is available anyway. The digital learning platform offers personalised recommendations for learning elements, such as learning videos or quizzes, based on the behaviour and individual characteristics of the learner. It combines AI technologies with a didactic foundation based on self-directed learning. The reference architecture fulfils previously gathered requirements and integrates the platform well in an existing software landscape due to its flexible design.

Abstract Learning is at the heart of every progress the human species makes. It is most effective when it considers who we are as individuals, what learning approach we prefer and what we already know to begin with. In the digital age, we strive to capture such information in the form of a digital representation—the so-called learner model—, to tailor learning-related systems to this information and build upon it to create more personalised learning experiences. Over recent years, the proliferation of diverse models across various educational applications and disciplines has made it challenging to access targeted research. In this survey, we aim to address this gap, reviewing the latest advances in learner modelling and conducting a comprehensive analysis of the existing approaches, focusing on developments from 2014 to 2023. With the help of a systematic literature review (SLR), we want to provide designers and developers of learner models with a structured overview and simplified entrance into the topic and the field of learner models. We investigate the question: What do learner models look like and how are they filled, kept up to date and used? To this end, we analyse and classify existing approaches. Our findings provide a comprehensive and structured overview of the field of learner modelling, allowing researchers to navigate and understand the diverse approaches more easily and providing developers of learner models or adaptive systems with a practical tool to access relevant information according to their needs.

Software engineering requires quite a few competences, technical ones along with non-technical ones. This talk presents some examples of how several interlinked modules in software engineering education were modified, refined and enriched over time. Starting out from largely instructive lectures, the modules were enriched with activating elements that aim at making students discover several relevant issues in software engineering by themselves. Thus, they better understand the rationale behind the methods and techniques that are available for resolving these issues. For instance, students work on a group exercise which clarifies that capturing requirements from stakeholders is a communication process. This is followed by several additional assignments in which student teams prepare and conduct a requirements elicitation session with largely realistic external customers. Besides, we offer additional learning elements in an adaptive digital learning environment, in particular short learning videos. This allows students to revisit topics they did not understand properly or to dive deeper into specific issues in a self-directed fashion. This is supported by AI technology which recommends learning elements that best serve the individual needs and characteristics of the individual learner.

Students in higher education tend to become increasingly heterogeneous groups of learners. This is due to different levels of prior knowledge or competences, diverse learning styles, differing affinity to (digital) media, and other factors. Learner-centred education needs to cope with that heterogeneity in order to make specific learning offers to the individual learner. This is difficult in physical classes where the coaching effort cannot be increased without limitation. This paper presents an individualized digital learning environment, iLE, that is intended to be used as an additional learning aid that supplements physical classes. iLE provides recommendations of learning material such as learning videos targeted to the specific needs of individual learners. The paper presents the technical approach behind iLE, in particular a combination of data- and knowledge-driven artificial intelligence techniques, as well as the didactical underpinning of iLE.

In modern education, individualized learning environments play a vital role by allowing learners to tailor their learning paths based on personal needs, interests, and abilities. Achieving effective individualization relies on dynamic adaptation of the learning path, typically facilitated by recommender systems. These systems offer personalized suggestions, commonly employing content-based or collaborative filtering approaches. However, traditional recommender systems often lack consideration of the semantics of learning elements. To address this limitation, ontology-based recommender systems integrate semantic modeling, establishing additional connections within a domain to enhance precision and context in recommendations. Notably, these systems mitigate the cold start problem and are particularly advantageous in learning environments with limited data. While videos are prevalent in learning platforms, their unstructured nature poses challenges for processing. This paper introduces an innovative approach, leveraging Large Language Models, specifically GPT, to extract metadata from learning videos. The proposed method intelligently augments videos and links them to a domain ontology, enabling the integration of videos into ontology-based recommender systems. The application of this approach is demonstrated through a case study in software engineering education, showcasing its potential to enhance individualized learning experiences in specific domains. The presented method offers an automated alternative to manual video processing, aligning with the evolving landscape of education technology.

Data science becomes increasingly important since large volumes of data is available that embody valuable, but hidden pieces of knowledge. Higher education needs to react by establishing study programs that focus on data science. Yet, data science is not a merely technical challenge, but involves many non-technical aspects that are often overlooked. This paper presents a systematic competence-oriented approach to curriculum development, paying equal respect to all types of required competences. As a case study, we show how this approach was used to design the curriculum of a data-science-oriented study program.

UML (Unified Modeling Language) is the current de facto as well as de jure standard (ISO/IEC 19505:2012) notation to visualize models in software development. UML provides essential guidelines and rules to visualize and understand complex software systems. This is the reason why it has become part of curricula for software engineering courses at many universities worldwide. It is well known, however, that UML is hard to grasp for novices, mainly due to its complexity. In order to tackle the problem of teaching UML to novice students appropriately, it is inevitable to understand their needs and problems much better than we do now. This paper presents empirical insights into students’ problems when developing common UML diagrams. Identified problems are generalized, giving rise to a problem catalogue that is derived from our empirical findings, thus establishing a basis for addressing these problems through focused learning arrangements.

Commonly, learning is expected to happen uniformly even in large classes. Typically, instructors can provide only a single learning setting in presence courses. Yet, student groups are heterogeneous in terms of their learning styles. This paper presents a learning concept which uses Kolb’s Learning Style Inventory to address different groups of learning habits adequately. This learning concept is used as a pilot in an introductory course on software engineering for learning modelling with the Unified Modelling Language.

Software engineering is concerned with the development of complex software systems and requires a high degree of multidisciplinarity. This presents great challenges for the learning of software engineering, since this complexity requires a comprehensive development of competences and in addition to the training of professional knowledge, the genesis of context-sensitive and general interdisciplinary competences. The reflection process plays an important role in the educational debates in order to apply what has been learned and to facilitate the integration of theoretical contents of the study into practice. A systematic investigation of the importance of reflection for the learning process of students in software engineering is, however, so far missing.

Requirements engineering is widely accepted as a top success factor for IT (and non-IT) projects. Qualified requirements engineers need to possess not just factual knowledge, but also many skills. Yet, it is unclear which competences requirements engineers actually need, and how these competences may be addressed appropriately in education. As a methodological framework, we devised an approach, Competence-Oriented Didactics, which rests on a sound pedagogical underpinning. This paper shows how Competence-Oriented Didactics is applied to a requirements engineering course in several iterations. In contrast to more traditional teaching approaches, students shall not only acquire technical requirements engineering knowledge, but, at the same time, develop non-technical competences that are necessary for requirements engineering. In particular, students shall better understand why requirements engineering and its core methods, techniques, and skills are needed. Moreover, students shall develop and expand the necessary skills for requirements engineering. Consequently, learning shifted from an instructive to an active and inductive style, which makes students actively discover relevant requirements engineering issues and gain hands-on experiences through carefully devised exercises. Systematic evaluations indicate that the described didactical settings works well. This paper has two main contributions: first, a systematic, competence-driven approach to develop learning settings, and second, a learning setting that is equally directed towards technical and non-technical competences of requirements engineers and demonstrably achieves its goals.

Software project management (SPM) and software quality management (SQM) are important aspects of software engineering. Unfortunately, these topics are fairly hard to teach to informatics students, mainly because they are very abstract and often seen as dull and boring by students. This contribution presents a didactical setting that the authors developed and used successfully for teaching SPM and SQM in a DisQspace format. A major aspect in the didactical setting lies on getting students actively involved and largely control their learning processes themselves. The paper presents the details of the approach, its didactical underpinning, and an evaluation of its efficacy.

Good requirements are commonly viewed as a key success factor for IT (and non-IT) projects, but still there seems to be insufficient insight into which competences requirements engineers need to have these days. Digitalization is likely to pose new challenges to requirements engineering. Chances are that digitalization will change the competences that are necessary for successful requirements engineering. This paper proposes a research design that will be used for clarifying which competences requirements engineers need nowadays and how these competences change due to digitalization. To that end, qualitative and quantitative research methods will be combined for developing a comprehensive competence profile for requirements engineering on a scientific basis. The resulting competence profile constitutes a starting point for devising competence-oriented learning settings. Thus, our research contributes to a better understanding of competences for requirements engineering and improves education of future requirements engineers, in particular for coping with challenges posed by digitalization.

Requirements are of paramount importance for the quality of software systems. Yet, requirements engineering education at universities is surprisingly hard. University students encounter difficulties in understanding the role of requirements and applying relevant methods to deal with requirements appropriately. One potential cause may be a lack of authenticity, i.e. settings that are too artificial to mirror the complexity of real-world situations adequately. This paper presents an innovative and integrated didactical approach for teaching requirements engineering that was devised in a goal- and competence-oriented manner to avoid some of these shortcomings, in particular by including requirements elicitation with real customers into an integrated didactic step-by-step approach. Obviously, requirements engineering education is far more than assembling technical knowledge. Rather, it involves many non-technical skills that obtain a specific flavor in requirements engineering. Our didactic approach also addresses these skills, while resting on a sound pedagogical underpinning. The paper also summarizes indications for the success of this approach, in particular by participants' self-evaluations.

In recent years, teaching and learning shifted towards competence-oriented approaches. As a consequence, examinations as well as didactical approaches need to become competence-oriented. Unfortunately, competence-oriented examinations and assessments of the efficacy of didactical approaches are fairly hard - currently, no generally accepted approaches for competence-oriented evaluation are available. To make things worse, software engineering is a complex subject matter. Therefore, intended learning outcomes in software engineering education also tend to be quite complex and vary widely with a course's context. This paper provides details on how SECAT, a Software Engineering Competence Assessment Tool, is used to assess the efficacy of didactical approaches in software engineering education in a competence-oriented matter. To that end, SECAT needs to be adapted to the specific context, namely a particular didactical approach with its associated intended learning outcomes. Intended learning outcomes are related to specific competences, including non-technical skills. The paper presents results from applying SECAT for assessing the efficacy of employed didactical approaches in several software engineering courses. Furthermore, the paper shows an example of how SECAT's assessment results are used to improve didactical approaches for upcoming instances of these courses. SECAT and its underlying methodology is one step forward in competence assessment in software engineering.

Instructors not only in higher education are regularly faced with the problem that they need to develop a new course, or to adapt an existing one to changed requirements. This is especially true for topics related to information technology (IT) since technological progress is fast in this domain. However, instructors are not prepared really well for this task since they typically have a professional and educational background in areas different from pedagogy. Therefore, some sort of methodological framework to support the systematic development and refinement of courses would be highly appreciated. This paper presents such a method, called Competence- Oriented Didactics. This approach builds upon several concepts from general didactics, most notably Klafki's Didactic Analysis, and combines and extends these concepts. As a proof of concept, the method is applied to the refinement of an introductory course on information systems. This case study shows, among other things, that Competence-Oriented Didactics has the potential to be applicable for course (re-)design in other domains beyond IT as well.

If software engineering education is done in a traditional lecture-oriented style students have no other choice than believing that the solutions they are told actually work for a problem that they never encountered themselves. In order to overcome this problem, this paper describes an approach which allows students to better understand why software engineering and several of its core methods and techniques are needed, thus preparing them better for their professional life. This approach builds on active and inductive learning. Exercises that make students actively discover relevant software engineering issues are described in detail together with their pedagogical underpinning.

Requirements are of paramount importance for the quality of software systems. For various reasons, however, university students encounter difficulties in understanding the role of requirements and appropriately applying relevant methods to deal with requirements. This paper describes the concept for teaching requirements engineering that was devised at Coburg University of Applied Sciences. As a key idea, teaching requirements starts out from business process models. From these models, requirements for a workflow application can be derived and specified in a requirements document. A main benefit of this approach lies in the fact that requirements are not just presented as an abstract concept. Furthermore, students are exposed to the complexity of an almost realistic workflow application. Being more realistic than a toy project, the latter also improves understanding why requirements should be described precisely and provides opportunities to also exercise non-technical competencies that are important for successful requirements engineering.

The development of complex software systems requires a mixture of various technical and non-technical competencies. While there are some guidelines what technical knowledge is required to make a good software engineer, there is a lack of insight as to which non-technical or soft skills are required to master complex software projects. This paper proposes a body of skills (SWEBOS) for software engineering. The collection of necessary skills is developed on the basis of a clear, data-driven research design. The resulting required soft skills for software engineering are described precisely and semantically rich in a three-level structure. This approach guarantees that skills are not just characterized in a broad and general manner, but rather they are specifically adapted to the domain of software engineering.

Education invariably aims at developing competencies, technical as well as non-technical ones. As a consequence, there is also a need for methods that can be used to assess the quality of education faithfully. One possible approach is an assessment of whether intended learning outcomes are achieved, i.e. an investigation if the target audience possesses the desired competencies. Assessment of competencies, however, is tricky since competencies are often only vaguely defined. This paper presents SECAT, an approach to assess competencies, and particularly those needed for proper software engineering. To that end, SECAT builds on Rauner's approach for competency assessment in vocational education. Rauner's approach uses nine competency criteria, which are further refined by suitable issues that indicate to which extent a competency is, or should be, present. The main contribution of this paper lies in the adaptation and enhancement of this framework in order to make it useable in software engineering education. Adaptation and enhancements encompass issues such as team and individual assessments, integration of multiple perspectives from various groups of stakeholders, and product- and process-orientation. The paper also presents first insights from using SECAT in a pilot university course in software engineering.

Software process models are fairly abstract tools for organizing large, complex software development projects. Since particularly undergraduate students commonly do not have any experience in being part of such a project, their understanding of the benefits and shortcomings of particular process models is very limited. Even more, frequently they are not aware of the need to follow a particular process model since their previous one-person software assignments were too small for requiring any such model at all.

This paper describes experiences from two organizations that have used the Riskit method for risk management in their software projects. This paper presents the Riskit method, the organizations involved, case study designs, and findings from case studies. We focus on the experiences and insights gained through the application of the method in industrial context and propose some general conclusions based on the case studies.