Refine
Document Type
- Part of a Book (6)
- Conference Proceeding (6)
- Article (5)
Has Fulltext
- no (17)
Keywords
- ChatGPT (2)
- Higher Education (2)
- AI (1)
- AI Influences (1)
- Agile Approaches (1)
- Agile Methods (1)
- Agile Requirements (1)
- Agile Transformation (1)
- Agile UX (1)
- E-Government (1)
Institute
Value delivery is becoming an important asset for an organization due to increasing competition in industry. Therefore, companies apply Agile Software Development (ASD) to be more competitive and reduce time to market. Using ASD for the development of systems implies that established approaches of Requirements Engineering (RE) undergo some changes in order to be more flexible to changing requirements. To this end, the field of agile RE is emergent and different process models for agile RE have arisen. The aim of this paper is to build an abstract layer about the variety of existing process models by means of a metamodel for agile RE. It has been created in several iterations and relies on the evaluation of related process models. Furthermore , we have derived process models for agile RE in industry by presenting instances of the metamodel in two different cases: one is based on Scrum whereas the other is based on Kanban. This paper contributes to the software development body of knowledge by delivering a metamodel for agile RE that supports researchers and practitioners modeling and improving their own process models. We can conclude that the agile RE metamodel is highly relevant for the industry as well as for the research community, since we have derived it following empirical research in the field of ASD.
On November 30th, 2022, OpenAI released the large language model ChatGPT, an extension of GPT-3. The AI chatbot provides real-time communication in response to users’ requests. The quality of ChatGPT’s natural speaking answers marks a major shift in how we will use AI-generated information in our day-to-day lives. For a software engineering student, the use cases for ChatGPT are manifold: assessment preparation, translation, and creation of specified source code, to name a few. It can even handle more complex aspects of scientific writing, such as summarizing literature and paraphrasing text. Hence, this position paper addresses the need for discussion of potential approaches for integrating ChatGPT into higher education. Therefore, we focus on articles that address the effects of ChatGPT on higher education in the areas of software engineering and scientific writing. As ChatGPT was only recently released, there have been no peer-reviewed articles on the subject. Thus, we performed a structured grey literature review using Google Scholar to identify preprints of primary studies. In total, five out of 55 preprints are used for our analysis. Furthermore, we held informal discussions and talks with other lecturers and researchers and took into account the authors’ test results from using ChatGPT. We present five challenges and three opportunities for the higher education context that emerge from the release of ChatGPT. The main contribution of this paper is a proposal for how to integrate ChatGPT into higher education in four main areas.
Context: Higher education is changing at an accelerating pace due to the widespread use of digital teaching and emerging technologies. In particular, AI assistants such as ChatGPT pose significant challenges for higher education institutions because they bring change to several areas, such as learning assessments or learning experiences.
Objective: Our objective is to discuss the impact of AI assistants in the context of higher education, outline possible changes to the context, and present recommendations for adapting to change.
Method: We review related work and develop a conceptual structure that visualizes the role of AI assistants in higher education.
Results: The conceptual structure distinguishes between humans, learning, organization, and disruptor, which guides our discussion regarding the implications of AI assistant usage in higher education. The discussion is based on evidence from related literature.
Conclusion: AI assistants will change the context of higher education in a disruptive manner, and the tipping point for this transformation has already been reached. It is in our hands to shape this transformation.
Due to circumstances such as digital teaching during the coronavirus pandemic and the emergence of powerful artificial intelligence tools (e.g., ChatGPT), digitization in higher education has increased rapidly in recent years. For this reason, innovative didactic concepts are being applied, and new teaching methods are being tested. One of these is value-based learning, an approach that aims to develop students’ values alongside specialist knowledge. The objective of this research is to investigate how value-based learning can be implemented in higher education through agile practices and agile values. Thus, we have chosen a multiple case study research method that includes three case studies at different German universities of applied sciences. The results show that the application of agile practices and values varies by context and is individualized. Therefore, we developed a conceptual model that shows how value-based learning can be applied to higher education through agile practices and agile values. This conceptual model shows how courses and modules, as well as students and lecturers, evolve through continuous feedback over the course of a semester. Moreover, it allows students to be taught competencies that enable them to adapt to continuous change.
Context: In agile transformations there are many challenges. One very important but less considered and treated in research are cultural challenges associated with an agile mindset. Although research shows that cultural clashes and general organizational resistance to change are part of the most significant agile adoption barriers. Objective: We identify challenges that arise from the interplay between agile culture and organizational culture. In doing so, we tackle this field and come up with important contributions for further research regarding a problem that practitioners face today. Method: This is done with a mixed-method research approach. First, we gathered qualitative data among our network of agile practitioners and derived in sum 15 challenges with agile culture. Then, we conducted quantitative data by means of a questionnaire study with 92 participants. Results: We identified 7 key challenges out of the 15 challenges with agile culture. These key challenges refer to the technical agility (doing agile) and the cultural agility (being agile). The results are presented in a conceptual model. Conclusion: Based on our results, we started deriving future work aspects to do more detailed research on the topic of cultural challenges while transitioning or using agile methods in software development and beyond.
Abstract: The corona pandemic has shown how important it is to be able to react quickly to changing conditions. In many organizations, agile process models and agile practices are used for this purpose. This paper examines how agility can be implemented in higher education. Using two case studies, we analyze how agile practices and agile values are implemented for knowledge and skills development. Our results present a student-centered approach where lecturers supported self-organized learning. In the student-centered approach, prior knowledge and experience of learners are taken into account, and the learning process is adjusted through continuous feedback. With the introduction of agility, a value shift towards value-based learning is taking place. Value-based learning supports competency-based teaching since the focus is less on imparting technical knowledge and more on imparting competencies.
Experimente
(2023)
Wie beim Problem mit der Fehler- und Lernkultur schon beschrieben, hängt dieses sehr nah mit dem nächsten Themenfeld rund um Experimente zusammen. Dieses Kapitel vertieft die Problematik, dass Menschen – egal ob als einzelne Individuen oder in einer Gruppe als Team – in Organisationen bzw. in ihrem Umfeld Angst davor haben, neue Dinge auszuprobieren. Der Begriff Experiment deutet bereits daraufhin, dass es noch keinen klaren Weg und kein vorhersagbares Ergebnis gibt und das Auszuprobierende schiefgehen kann.
Fehler- und Lernkultur
(2023)
Dieses Kapitel vertieft das Problem, dass die Menschen innerhalb einer Organisation keine Fehler machen dürfen. Bei der Einführung und Nutzung agiler Arbeitsweisen hat der Aspekt der Fehler- und Lernkultur einen besonderen Stellenwert. Die Fehlerkultur wird als Kultur verstanden, bei der die Menschen das Scheitern als Chance zum Lernen verstehen
The integration of Agile software development and User Experience (UX) has become a growing field of research, as both approaches play critical roles in building digital products and services. In this special issue on Agile UX, the current state of the field is explored through a combination of systematic literature reviews and qualitative and quantitative studies. The special issue provide an overview of the key trends, challenges, and successes in combining Agile and UX, and highlight the importance of involving stakeholders throughout development. The shift from plan-driven approaches to Agile UX approaches has brought a focus on human values and a better understanding of the importance of considering users’ needs. We present recent advances in research and practice, showing that Agile UX is a continuous journey towards changing user behavior by delivering value.
In diesem Kapitel thematisieren wir Probleme, die entstehen, wenn Entscheidungen nicht gemeinschaftlich, sondern von einzelnen Menschen innerhalb der Organisation getroffen werden. Die Verbreitung von agilen Arbeitsweisen hat in den vergangenen Jahren zu einer Veränderung der Führungs- und Entscheidungskultur in Organisationen geführt. Lange Zeit galt der Grundsatz, dass Entscheidungen maßgeblich von einzelnen Personen oder Organisationseinheiten insbesondere auf Management-Ebenen getroffen werden.