Andreas Prinz

• Øvensen, Elisabeth Cederberg; Scholz, Tobias; Andersen, Rune & Prinz, Andreas (2025). FROM GAME ELEMENTS TO MEANINGFUL MOTIVATION: A DESIGN-CENTRED APPROACH TO GAMIFICATION. ICERI Proceedings. p. 7744–7753. Full text in Research Archive
• Payenda, Mohammad Arif; Wang, Shuaishuai; Prinz, Andreas; Hussiny, Mohammad Ali & Jiang, Zhiyu (2025). Predicting Mooring Tensions of a Floating Wind Turbine Using Motion Sensors and Neural Networks. Journal of Physics: Conference Series (JPCS). ISSN 1742-6588. 3131. doi: 10.1088/1742-6596/3131/1/012032. Full text in Research Archive Show summary

  In floating wind turbines, mooring systems are vital for station-keeping and operational safety. Ensuring the safe and cost-effective maintenance of these systems is of great importance. In this research, we have investigated the performance of nacelle motion accelerometers in predicting mooring line tensions under various operational conditions using deep learning algorithms. An accelerometer with varying degrees of freedom (DOFs) is assumed to be placed inside the nacelle to measure platform vibrations. To predict dynamic mooring tensions, we propose a hybrid model (CNN-BiLSTM) that combines Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) networks, leveraging the strengths of both algorithms to improve prediction accuracy. Our findings show that including the surge motion accelerometer has the greatest effect in predicting mooring tensions, with an R 2 value of 0.9941, compared to an R 2 of 0.9907 for the 6-DOF model without accelerometers, representing a 0.34% increase. However, the sway motion shows a 0.15% increase with an R 2 value of 0.9956, and the heave motion shows a 0.17% increase with an R 2 value of 0.9956, both relative to the surge motion accelerometer. The robustness of the model under varying dynamic conditions suggests its potential utility in other predictive maintenance tasks in the marine energy sector.

• Chatterjee, Ayan; Gerdes, Martin; Prinz, Andreas; Riegler, Michael & Martinez, Santiago (2024). Semantic representation and comparative analysis of physical activity sensor observations using MOX2-5 sensor in real and synthetic datasets: a proof-of-concept-study. Scientific Reports. 14(1), p. 1–21. doi: 10.1038/s41598-024-55183-6. Full text in Research Archive
• Øvensen, Elisabeth Cederberg; Scholz, Tobias Michael; Andersen, Rune & Prinz, Andreas (2024). DEFINING A GAMEFUL EXPERIENCE IN A LEARNING ENVIRONMENT, 16th International Conference on Education and New Learning Technologies. International Academy of Technology, Education and Development. ISSN 9788409629381. p. 3824–3834. doi: 10.21125/edulearn.2024.0977. Full text in Research Archive
• Payenda, Mohammad Arif; Wang, Shuaishuai; Jiang, Zhiyu & Prinz, Andreas (2024). Prediction of mooring dynamics for a semi-submersible floating wind turbine with recurrent neural network models. Ocean Engineering. ISSN 0029-8018. 313(3). doi: 10.1016/j.oceaneng.2024.119490. Full text in Research Archive Show summary

  Offshore wind technology emerges as a promising solution to tap into wind resources in shallow and deep waters. For floating wind turbines, mooring systems provide station-keeping functionalities. Efficient monitoring of mooring loads is critical for safe and cost-effective operation and maintenance. As direct measurement of the dynamic mooring line tension is expensive, alternative means are needed. To this end, this article focuses on predicting mooring tensions based on accessible motion data of the floating platform and proposes utilizing deep learning algorithms, i.e., recurrent neural networks (RNNs). We selected three RNN algorithms: Gated Recurrent Units (GRU), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM). These algorithms were trained with various load cases of a 10-MW floating wind turbine and their efficacy was assessed using unseen data. Among the three algorithms, the BiLSTM algorithm performed best, achieving R2 of more than 0.97 under various load conditions. Further, a statistical assessment of the tension time series demonstrates an excellent agreement between the predicted and the measured mooring line tensions with a percentage difference in the peak tension of less than 0.5%. The outcomes of this paper contribute to real-time prediction and structural health monitoring of floating wind turbines.

• Payenda, Mohammad Arif; Vahidi, Abdul Razaq; Hussiny, Mohammad Ali; Prinz, Andreas & Øvrelid, Lilja (2024). PashtoEmo: Enhancing Text-Based Emotion Analysis in the Pashto Language Through Dataset Creation. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 14763, p. 225–236. doi: 10.1007/978-3-031-70242-6_22. Full text in Research Archive Show summary

  This paper presents the comprehensive PashtoEmo dataset for emotion analysis in the Pashto language. PashtoEmo contains 8016 text instances from X social media platform covering several topics, including politics, women’s rights, social justice, culture, sports, and education. The texts are annotated with six emotional categories and an additional ‘Other’ class. We tested PashtoEmo for emotion analysis with several machine learning, deep learning, and transformer models. Even the best model, XLM-RoBERTa-large, achieved only a 76.85% F1 score and a 78.11% accuracy. This indicates that the data set must be extended with adequate resources in Pashto language text-based applications.

• Prinz, Andreas; Engebretsen, Martin; Gjøsæter, Terje; Møller-Pedersen, Birger & Xanthopoulou, Themis Dimitra (2023). Models, systems, and descriptions: A cross-disciplinary reflection on models. Frontiers in Computer Science. 5. doi: 10.3389/fcomp.2023.1031807. Full text in Research Archive Show summary

  There are many different notions of models in different areas of science that are often not aligned, making it difficult to discuss them across disciplines. In this study, we look at the differences between physical models and mental models as well as the difference between static and dynamic models. Semiotics provides a philosophical underpinning by explaining meaning-making. This allows for identifying a common ground between models in different areas. We use examples from natural sciences and linguistics to illustrate different approaches and concepts and to find commonalities. This study distinguishes between systems, models, and descriptions of models. This distinction allows us to understand the commonalities of mental and physical models in different areas.

• Handeland, Jorunn Aas; Prinz, Andreas; Ekra, Else Mari Ruberg & Fossum, Mariann (2023). ‘I realised it when we played with the doll!’: nursing students’ learning from participation in an action research project that included manikins. Educational Action Research. ISSN 0965-0792. doi: 10.1080/09650792.2023.2242425. Full text in Research Archive Show summary

  This qualitative educational action research study aimed to gain knowledge about nursing students’ learning from participating in a developmental project that included human-like manikins. Twenty-three second-year Bachelor of Nursing students, one teacher, and one researcher participated in the study conducted at a Norwegian university. In collaboration, they planned and executed a developmental project with manikins in a nursing course. The project put manikins’ reflective, explorative, and experiential potentials into play. Two Action Research cycles were carried out. Data were collected using audio recordings, observations, and written responses. The concepts of sayings, doings, and relatings guided the analysis to identify how the modified learning conditions influenced and changed the students’ learning. The following four themes illustrate the students’ learning in the project: ownership of the learning process, collaborative learning, understanding theory’s significance for practice, and taking the patient’s perspective. The student’s participation in the project, including their independent use and exploration of the manikins, provided freedom and responsibility in decision-making, helped them experience problems, fostered creativity, and stimulated inner motivation. This moved their learning in a more practice-relevant direction.

• Chatterjee, Ayan; Prinz, Andreas; Riegler, Michael & Das, Jishnu (2023). A systematic review and knowledge mapping on ICT-based remote and automatic COVID-19 patient monitoring and care. BMC Health Services Research. 23(1). doi: 10.1186/s12913-023-10047-z. Full text in Research Archive Show summary

  e-Health has played a crucial role during the COVID-19 pandemic in primary health care. e-Health is the cost-effective and secure use of Information and Communication Technologies (ICTs) to support health and health-related fields. Various stakeholders worldwide use ICTs, including individuals, non-profit organizations, health practitioners, and governments. As a result of the COVID-19 pandemic, ICT has improved the quality of healthcare, the exchange of information, training of healthcare professionals and patients, and facilitated the relationship between patients and healthcare providers. This study systematically reviews the literature on ICT-based automatic and remote monitoring methods, as well as different ICT techniques used in the care of COVID-19-infected patients.The purpose of this systematic literature review is to identify the e-Health methods, associated ICTs, method implementation strategies, information collection techniques, advantages, and disadvantages of remote and automatic patient monitoring and care in COVID-19 pandemic. The search included primary studies that were published between January 2020 and June 2022 in scientific and electronic databases, such as EBSCOhost, Scopus, ACM, Nature, SpringerLink, IEEE Xplore, MEDLINE, Google Scholar, JMIR, Web of Science, Science Direct, and PubMed. In this review, the findings from the included publications are presented and elaborated according to the identified research questions. Evidence-based systematic reviews and meta-analyses were conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Additionally, we improved the review process using the Rayyan tool and the Scale for the Assessment of Narrative Review Articles (SANRA). Among the eligibility criteria were methodological rigor, conceptual clarity, and useful implementation of ICTs in e-Health for remote and automatic monitoring of COVID-19 patients.

• Chatterjee, Ayan; Prinz, Andreas; Riegler, Michael Alexander & Meena, Yogesh Kumar (2023). An automatic and personalized recommendation modelling in activity eCoaching with deep learning and ontology. Scientific Reports. 13(1). doi: 10.1038/s41598-023-37233-7. Full text in Research Archive Show summary

  Electronic coaching (eCoach) facilitates goal-focused development for individuals to optimize certain human behavior. However, the automatic generation of personalized recommendations in eCoaching remains a challenging task. This research paper introduces a novel approach that combines deep learning and semantic ontologies to generate hybrid and personalized recommendations by considering “Physical Activity” as a case study. To achieve this, we employ three methods: time-series forecasting, time-series physical activity level classification, and statistical metrics for data processing. Additionally, we utilize a naïve-based probabilistic interval prediction technique with the residual standard deviation used to make point predictions meaningful in the recommendation presentation. The processed results are integrated into activity datasets using an ontology called OntoeCoach, which facilitates semantic representation and reasoning. To generate personalized recommendations in an understandable format, we implement the SPARQL Protocol and RDF Query Language (SPARQL). We evaluate the performance of standard time-series forecasting algorithms [such as 1D Convolutional Neural Network Model (CNN1D), autoregression, Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU)] and classifiers [including Multilayer Perceptron (MLP), Rocket, MiniRocket, and MiniRocketVoting] using state-of-the-art metrics. We conduct evaluations on both public datasets (e.g., PMData) and private datasets (e.g., MOX2-5 activity). Our CNN1D model achieves the highest prediction accuracy of 97, while the MLP model outperforms other classifiers with an accuracy of 74. Furthermore, we evaluate the performance of our proposed OntoeCoach ontology model by assessing reasoning and query execution time metrics. The results demonstrate that our approach effectively plans and generates recommendations on both datasets. The rule set of OntoeCoach can also be generalized to enhance interpretability.

• Chatterjee, Ayan; Pahari, Nibedita; Prinz, Andreas & Riegler, Michael Alexander (2023). AI and semantic ontology for personalized activity eCoaching in healthy lifestyle recommendations: a meta-heuristic approach. BMC Medical Informatics and Decision Making. 23(1). doi: 10.1186/s12911-023-02364-4. Full text in Research Archive Show summary

  Background Automated coaches (eCoach) can help people lead a healthy lifestyle (e.g., reduction of sedentary bouts) with continuous health status monitoring and personalized recommendation generation with artificial intelligence (AI). Semantic ontology can play a crucial role in knowledge representation, data integration, and information retrieval. Methods This study proposes a semantic ontology model to annotate the AI predictions, forecasting outcomes, and personal preferences to conceptualize a personalized recommendation generation model with a hybrid approach. This study considers a mixed activity projection method that takes individual activity insights from the univariate time-series prediction and ensemble multi-class classification approaches. We have introduced a way to improve the prediction result with a residual error minimization (REM) technique and make it meaningful in recommendation presentation with a Naïve-based interval prediction approach. We have integrated the activity prediction results in an ontology for semantic interpretation. A SPARQL query protocol and RDF Query Language (SPARQL) have generated personalized recommendations in an understandable format. Moreover, we have evaluated the performance of the time-series prediction and classification models against standard metrics on both imbalanced and balanced public PMData and private MOX2-5 activity datasets. We have used Adaptive Synthetic (ADASYN) to generate synthetic data from the minority classes to avoid bias. The activity datasets were collected from healthy adults (n = 16 for public datasets; n = 15 for private datasets). The standard ensemble algorithms have been used to investigate the possibility of classifying daily physical activity levels into the following activity classes: sedentary (0), low active (1), active (2), highly active (3), and rigorous active (4). The daily step count, low physical activity (LPA), medium physical activity (MPA), and vigorous physical activity (VPA) serve as input for the classification models. Subsequently, we re-verify the classifiers on the private MOX2-5 dataset. The performance of the ontology has been assessed with reasoning and SPARQL query execution time. Additionally, we have verified our ontology for effective recommendation generation. Results We have tested several standard AI algorithms and selected the best-performing model with optimized configuration for our use case by empirical testing. We have found that the autoregression model with the REM method outperforms the autoregression model without the REM method for both datasets. Gradient Boost (GB) classifier outperforms other classifiers with a mean accuracy score of 98.00%, and 99.00% for imbalanced PMData and MOX2-5 datasets, respectively, and 98.30%, and 99.80% for balanced PMData and MOX2-5 datasets, respectively. Hermit reasoner performs better than other ontology reasoners under defined settings. Our proposed algorithm shows a direction to combine the AI prediction forecasting results in an ontology to generate personalized activity recommendations in eCoaching. Conclusion The proposed method combining step-prediction, activity-level classification techniques, and personal preference information with semantic rules is an asset for generating personalized recommendations.

• Chatterjee, Ayan; Prinz, Andreas & Riegler, Michael (2022). Prediction Modeling in Activity eCoaching for Tailored Recommendation Generation: A Conceptualization, 2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665482998. doi: 10.1109/MeMeA54994.2022.9856556. Full text in Research Archive Show summary

  The collective effects of a sedentary lifestyle are correlated with numerous adverse health consequences, including increased risk of obesity, diabetes type II, high blood pressure, depression, and cardiovascular risks. Research in eHealth can provide methodologies to enhance personal healthcare with Information and Communication Technologies (ICTs). An eCoach system may allow people to manage a healthy lifestyle with health state monitoring (e.g., physical activity) and tailored recommendation generation. Daily step count is an important feature to provide a direct and indirect reflection on individual activity levels. Therefore, a personalized, predictive model may be beneficial to forecast future "steps" based on the temporal analysis of the individual “step” pattern. In this study, we have conceptualized the same idea with statistical forecast models (e.g., Kalman Filter (KF), Autoregressive Integrated Moving Average (ARIMA), and Seasonal Autoregressive Integrated Moving Average (SARIMA)) and a ruleset for activity type determination in personalized activity eCoaching. First, we used the publicly available “PMData” dataset of 16 adults (M: 13; F:3) to train and test the models and explore the possibility of accurate univariate time-series forecasting of “step counts”. Second, we established an idea to generate personalized activity recommendations based on the forecasting outcome, ruleset, and personal preference settings. The ARIMA model has outdated other predictors against root mean squared error (RMSE). Therefore, we conceptualized using the ARIMA in our eCoach system to generate personalized recommendations to motivate participants to accomplish their activity goals (e.g., complete “X” steps daily and stay active for the entire week) as proof of concept.

• Xanthopoulou, Themis Dimitra; Prinz, Andreas & Shults, Fount LeRon (2022). The Problem with Bullying: Lessons Learned from Modelling Marginalization with Diverse Stakeholders. In Czupryna, Marcin & Kamiński, Bogumił (Ed.), Advances in Social Simulation. Proceedings of the 16th Social Simulation Conference, 20–24 September 2021. Springer Nature. ISSN 9783030928438. p. 289–300. doi: 10.1007/978-3-030-92843-8_22. Full text in Research Archive Show summary

  While building a simulation model to gain insights on bullying interventions, we encountered challenging issues that forced us to reconsider the concepts we model. We learned lessons about the need for quality assurance and a more demanding construction process when building models that aim to support decision making. One of the lessons is that even academically accepted concepts such as “bullying” can be ambiguous. Experts and interested parties do not agree about how to define and use the term bullying. Indeed, before we can model “bullying”, we need a shared understanding, of its meaning. Otherwise, insights from the model could be misinterpreted and lead to misleading conclusions. Concepts are inherently imprecise and contain grey areas. Although this may be true, not all of them are ambiguous. For the scope of this paper, ambiguity implies that the same word is used to point to different concepts. For different reasons, bullying has evolved to point to different concepts for different people and sometimes even for the same person. We propose to solve these challenges by identifying which concrete bullying behaviors to target, and by focusing on simulation models for interventions addressing those behaviors.

• Chatterjee, Ayan; Gerdes, Martin; Khatiwada, Pankaj & Prinz, Andreas (2022). SFTSDH: Applying Spring Security Framework with TSD-Based OAuth2 to Protect Microservice Architecture APIs. IEEE Access. 10, p. 41914–41934. doi: 10.1109/ACCESS.2022.3165548. Full text in Research Archive Show summary

  The Internet of Medical Things (IoMT) combines medical devices and applications that use network technologies to connect healthcare information systems (HIS). IoMT is reforming the medical industry by adopting information and communication technologies (ICTs). Identity verification, secure collection, and exchange of medical data are essential in health applications. In this study, we implemented a hybrid security solution to secure the collection and management of personal health data using Spring Framework (SF), Services for Sensitive Data (TSD) as a service platform, and Hyper-Text-Transfer-Protocol (HTTP (H)) security methods. The adopted solution (SFTSDH = SF + TSD + H) instigated the following security features: identity brokering, OAuth2, multifactor authentication, and access control to protect the Microservices Architecture Application Programming Interfaces (APIs), following the General Data Protection Regulation (GDPR). Moreover, we extended the adopted security solution to develop a digital infrastructure to facilitate the research and innovation work in the electronic health (eHealth) section, focusing on solution validation with theoretical evaluation and experimental testing. We used a web engineering security methodology to achieve and explain the adopted security solution. As a case study, we designed and implemented electronic coaching (eCoaching) prototype system and deployed the same in the developed infrastructure to securely record and share personal health data. Furthermore, we compared the test results with related studies qualitatively for the efficient evaluation of the implemented security solution. The SFTSDH implementation and configuration in the prototype system have effectively secured the eCoach APIs from an attack in all the considered scenarios. The eCoach prototype with the SFTSDH solution effectively sustained a load of (≈) 1000 concurrent users in the developed digital health infrastructure. In addition, we performed a qualitative comparison among the following security solutions: SF security, third-party security, and SFTSDH, where SFTSDH showed a promising outcome.

• Chatterjee, Ayan; Pahari, Nibedita; Prinz, Andreas & Riegler, Michael (2022). Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation. Scientific Reports. 12. doi: 10.1038/s41598-022-24118-4. Full text in Research Archive
• Chatterjee, Ayan; Pahari, Nibedita & Prinz, Andreas (2022). HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study. Sensors. 22(10). doi: 10.3390/s22103756. Full text in Research Archive
• Chatterjee, Ayan; Prinz, Andreas; Gerdes, Martin; Martinez, Santiago; Pahari, Nibedita & Meena, Yogesh Kumar (2022). ProHealth eCoach: user-centered design and development of an eCoach app to promote healthy lifestyle with personalized activity recommendations. BMC Health Services Research. 22. doi: 10.1186/s12913-022-08441-0. Full text in Research Archive Show summary

  Background: Regular physical activity (PA), healthy habits, and an appropriate diet are recommended guidelines to maintain a healthy lifestyle. A healthy lifestyle can help to avoid chronic diseases and long-term illnesses. A monitoring and automatic personalized lifestyle recommendation system (i.e., automatic electronic coach or eCoach) with considering clinical and ethical guidelines, individual health status, condition, and preferences may successfully help participants to follow recommendations to maintain a healthy lifestyle. As a prerequisite for the prototype design of such a helpful eCoach system, it is essential to involve the end-users and subject-matter experts throughout the iterative design process. Methods: We used an iterative user-centered design (UCD) approach to understend context of use and to collect qualitative data to develop a roadmap for self-management with eCoaching. We involved researchers, non-technical and technical, health professionals, subject-matter experts, and potential end-users in design process. We designed and developed the eCoach prototype in two stages, adopting diferent phases of the iterative design process. In design workshop 1, we focused on identifying end-users, understanding the user’s context, specifying user requirements, designing and developing an initial low-fdelity eCoach prototype. In design workshop 2, we focused on maturing the low-fdelity solution design and development for the visualization of continuous and discrete data, artifcial intelligence (AI)-based interval forecasting, personalized recommendations, and activity goals. Results: The iterative design process helped to develop a working prototype of eCoach system that meets end-user’s requirements and expectations towards an efective recommendation visualization, considering diversity in culture, quality of life, and human values. The design provides an early version of the solution, consisting of wearable technology, a mobile app following the “Google Material Design” guidelines, and web content for self-monitoring, goal setting, and lifestyle recommendations in an engaging manner between the eCoach app and end-users. Conclusions: The adopted iterative design process brings in a design focus on the user and their needs at each phase. Throughout the design process, users have been involved at the heart of the design to create a working.

• Chatterjee, Ayan & Prinz, Andreas (2022). Personalized Recommendations for Physical Activity e-Coaching (OntoRecoModel): Ontological Modeling. JMIR Medical Informatics. 10(6). doi: 10.2196/33847. Full text in Research Archive
• Handeland, Jorunn Aas; Prinz, Andreas; Ekra, Else Mari Ruberg & Fossum, Mariann (2022). The sense of a patient: An ethnographic multi-site field study exploring the influence of manikins on nursing students' learning. International Journal of Educational Research Open. 3. doi: 10.1016/j.ijedro.2021.100110. Full text in Research Archive Show summary

  The purpose of this ethnographic study was to gain insight into the influence of full-body human-like manikins on nursing students’ learning. The research question that guided the study was: How do the presence and use of human-like manikins influence nursing students’ learning? Data were collected during 15 educational sessions, using different manikins for various activities. Applying cultural-historical activity theory, this study explored the use of manikins as a mediated activity. The study’s main result was the interplay of five categories. In the first category, manikin as an object, manikins were used to teach and learn technical skills. In the second category, manikin as a subject, manikins were used to teach and learn to perform those skills with care. The third category, the interplay, illustrates how these two approaches were present in all sessions. Category four, the individual learning space, provided students with a feeling of working with a patient. Category five, the collective learning space, awarded collaborative and reflexive learning opportunities. We concluded from this study that manikins may introduce students to the balance between the technical and interpersonal aspects of nursing practice. Being aware of how manikins influence learning, educators can make more targeted use of manikins and support lower-grade nursing students in their learning process and professional development.

• Prinz, Andreas; Xanthopoulou, Themis Dimitra; Gjøsæter, Terje & Møller-Pedersen, Birger (2022). On abstraction in the OMG hierarchy: systems, models, and descriptions, ACM / IEEE 25th International Conference on Model Driven Engineering Languages and Systems (MODELS). Association for Computing Machinery (ACM). ISSN 9781450394673. p. 322–330. doi: 10.1145/3550356.3561573. Full text in Research Archive Show summary

  The Model-Driven Architecture (MDA) uses a metadata hierarchy with several layers that are placed on top of each other. The traditional view is that the layers provide abstractions related to models in languages defined by meta-models. Over the years, it has been difficult to define a consistent understanding of the layers. In this paper, we propose such a consistent understanding by clarifying the relations between the different elements in the hierarchy. This is done based on the Scandinavian approach to modelling that distinguishes between systems and system descriptions. Systems can be physical, digital, or even mental, while descriptions can be programs, language descriptions, specifications, and diagrams. We relate descriptions and systems by explaining where semantics of objects originate and how they apply in the hierarchy.

• Chatterjee, Ayan & Prinz, Andreas (2022). Applying Spring Security Framework with KeyCloak-Based OAuth2 to Protect Microservice Architecture APIs: A Case Study. Sensors. 22(5). doi: 10.3390/s22051703. Full text in Research Archive Show summary

  : In this study, we implemented an integrated security solution with Spring Security and Keycloak open-access platform (SSK) to secure data collection and exchange over microservice architecture application programming interfaces (APIs). The adopted solution implemented the following security features: open authorization, multi-factor authentication, identity brokering, and user management to safeguard microservice APIs. Then, we extended the security solution with a virtual private network (VPN), Blowfish and crypt (Bcrypt) hash, encryption method, API key, network firewall, and secure socket layer (SSL) to build up a digital infrastructure. To accomplish and describe the adopted SSK solution, we utilized a web engineering security method. As a case study, we designed and developed an electronic health coaching (eCoach) prototype system and hosted the system in the expanded digital secure infrastructure to collect and exchange personal health data over microservice APIs. We further described our adopted security solution’s procedural, technical, and practical considerations. We validated our SSK solution implementation by theoretical evaluation and experimental testing. We have compared the test outcomes with related studies qualitatively to determine the efficacy of the hybrid security solution in digital infrastructure. The SSK implementation and configuration in the eCoach prototype system has effectively secured its microservice APIs from an attack in all the considered scenarios with 100% accuracy. The developed digital infrastructure with SSK solution efficiently sustained a load of (≈)300 concurrent users. In addition, we have performed a qualitative comparison among the following security solutions: Spring-based security, Keycloak-based security, and their combination (our utilized hybrid security solution), where SSK showed a promising outcome.

• Chatterjee, Ayan; Pahari, Nibedita; Riegler, Michael & Prinz, Andreas (2022). LSTM Step Prediction and Ontology-Based Recommendation Generation in Activity eCoaching, 2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665469753. p. 13–18. doi: 10.1109/WiMob55322.2022.9941356. Full text in Research Archive Show summary

  An eCoach system may allow people to manage a healthy lifestyle with health state monitoring (e.g., physical activity) and personalized recommendation generation. Daily step count is an important feature to provide a direct and indirect reflection on individual activity levels. Therefore, a personalized, predictive model may be beneficial to forecast future “steps” to motivate participants based on the temporal “step” pattern. Here, we have conceptualized the idea with a Bidirectional Long-ShortTerm-Memory (LSTM) model for weekly activity forecasting and a rule-base for personalized recommendation generation with Ontology reasoning and querying in activity eCoaching. First, we have used the publicly available “PMData” dataset of 16 adults (M: 13; F: 3) to train and test the models and explore the possibility of accurate univariate time-series forecasting of “step counts”. Second, we have created an Ontology and a rule-base to generate personalized activity recommendations to motivate participants to accomplish their activity goals (e.g., complete “X” steps daily and stay active for the entire week).

• Chatterjee, Ayan; Prinz, Andreas; Pahari, Nibedita; Das, Jishnu & Riegler, Michael (2022). Sleep Monitoring with Wearable Sensor Data in an eCoach Recommendation System: A Conceptual Study with Machine Learning Approach, Frontiers of ICT in Healthcare. Springer Nature. ISSN 9789811951916. p. 551–564. doi: 10.1007/978-981-19-5191-6_44. Full text in Research Archive Show summary

  The collective effects of sleep loss and sleep disorders are correlated with many adverse health consequences, including increased risk of high blood pressure, obesity, diabetes, depressive state, and cardiovascular symptoms. Research in eHealth can provide methods to enrich personal health care with information and communication technologies (ICTs). An eCoach system may allow people to manage a healthy lifestyle with extended health state monitoring (e.g., sleep) and tailored recommendation generation. Using supervised machine learning (ML) techniques, this study investigated the possibility of classifying sleep stages at night for adults on hourly and daily basis. The daily total sleep minutes and hourly total sleep minutes for defined sleeping period served as input for the classification models. We first used publicly available Fitbit dataset to build the initial classification models. Second, using the transfer learning approach, we re-used the top five best-performing models on a real dataset as collected from the MOX2-5 wearable medical-grade activity device. We found that support vector classifier (SVC) with “linear” kernel outdated other classifiers with a mean accuracy score of 99.92% for hourly sleep classification and a K-nearest neighbor (KNN) outpaced other classifiers with a mean accuracy score of 99.47% for daily sleep classification, for the public Fitbit datasets. Moreover, to determine the practical efficacy of the classifier models, we conceptualized to use the classifier models in an eCoach prototype system to attain tailored sleep goals (e.g., a weekly goal of 49–63 h of sleeping).

• Prinz, Andreas (2021). What is the Natural Abstraction Level of an Algorithm? In Raschke, Alexander; Riccobene, Elvinia & Schewe, Klaus-Dieter (Ed.), Logic, Computation and Rigorous Methods Essays Dedicated to Egon Börger on the Occasion of His 75th Birthday. Springer Publishing Company. ISSN 9783030760205. p. 199–214. doi: 10.1007/978-3-030-76020-5_12. Full text in Research Archive
• Prinz, Andreas (2021). Teaching Language Engineering Using MPS, Domain-Specific Languages in Practice with JetBrains MPS. Springer Publishing Company. ISSN 9783030737573. p. 315–336. doi: 10.1007/978-3-030-73758-0_11. Full text in Research Archive
• Chatterjee, Ayan; Prinz, Andreas; Gerdes, Martin & Martinez, Santiago (2021). Digital interventions on healthy lifestyle management: Systematic review. Journal of Medical Internet Research (JMIR). ISSN 1439-4456. 23(11). doi: 10.2196/26931. Full text in Research Archive Show summary

  Background: Digital interventions have tremendous potential to improve well-being and health care conveyance by improving adequacy, proficiency, availability, and personalization. They have gained acknowledgment in interventions for the management of a healthy lifestyle. Therefore, we are reviewing existing conceptual frameworks, digital intervention approaches, and associated methods to identify the impact of digital intervention on adopting a healthier lifestyle. Objective: This study aims to evaluate the impact of digital interventions on weight management in maintaining a healthy lifestyle (eg, regular physical activity, healthy habits, and proper dietary patterns). Methods: We conducted a systematic literature review to search the scientific databases (Nature, SpringerLink, Elsevier, IEEE Xplore, and PubMed) that included digital interventions on healthy lifestyle, focusing on preventing obesity and being overweight as a prime objective. Peer-reviewed articles published between 2015 and 2020 were included. We used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and a framework for an evidence-based systematic review. Furthermore, we improved the review process by adopting the Rayyan tool and the Scale for the Assessment of Narrative Review Articles. Results: Our initial searches identified 780 potential studies through electronic and manual searches; however, 107 articles in the final stage were cited following the specified inclusion and exclusion criteria. The identified methods for a successful digital intervention to promote a healthy lifestyle are self-monitoring, self-motivation, goal setting, personalized feedback, participant engagement, psychological empowerment, persuasion, digital literacy, efficacy, and credibility. In this study, we identified existing conceptual frameworks for digital interventions, different approaches to provide digital interventions, associated methods, and execution challenges and their impact on the promotion of healthy lifestyle management. Conclusions: This systematic literature review selected intervention principles (rules), theories, design features, ways to determine efficient interventions, and weaknesses in healthy lifestyle management from established digital intervention approaches. The results help us understand how digital interventions influence lifestyle management and overcome the existing shortcomings. It serves as a basis for further research with a focus on designing, developing, testing, and evaluating the generation of personalized lifestyle recommendations as a part of digital health interventions.

• Chatterjee, Ayan; Gerdes, Martin; Prinz, Andreas & Martinez, Santiago (2021). Comparing Performance of Ensemble-Based Machine Learning Algorithms to Identify Potential Obesity Risk Factors from Public Health Datasets. In Hassanien, Aboul Ella; Bhattacharyya, Siddhartha; Chakrabati, Satyajit; Bhattacharya, Abhishek & Dutta, Soumi (Ed.), Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing. Springer. ISSN 9789811599262. p. 253–269. doi: 10.1007/978-981-15-9927-9_26. Full text in Research Archive
• Chatterjee, Ayan; Gerdes, Martin; Prinz, Andreas & Martinez, Santiago (2021). A Comparative Study to Analyze the Performance of Advanced Pattern Recognition Algorithms for Multi-Class Classification. In Tavares, J. M. R. S.; Chakrabarti, S.; Bhattacharya, A. & Ghatak, S. (Ed.), Emerging Technologies in Data Mining and Information Security. Springer. ISSN 9789811597732. p. 111–124. doi: 10.1007/978-981-15-9774-9_11. Full text in Research Archive
• Chatterjee, Ayan; Gerdes, Martin; Martinez, Santiago & Prinz, Andreas (2021). Human Coaching Methodologies for Automatic Electronic Coaching (eCoaching) as Behavioral Interventions with Information and Communication Technology: Systematic Review. Journal of Medical Internet Research (JMIR). ISSN 1439-4456. 23(3). doi: 10.2196/23533. Full text in Research Archive
• Chatterjee, Ayan; Prinz, Andreas; Gerdes, Martin & Martinez, Santiago (2021). An Automatic Ontology-Based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management: Proof-of-Concept Study. Journal of Medical Internet Research (JMIR). ISSN 1439-4456. 23(4), p. 1–28. doi: 10.2196/24656. Full text in Research Archive
• Fischer, Joachim; Møller-Pedersen, Birger; Prinz, Andreas & Thalheim, Bernhard (2021). Models Versus Model Descriptions. In Dahanayake, Ajantha; Pastor, Oscar & Thalheim, Bernhard (Ed.), Modelling to Program Second International Workshop M2P 2020, Lappeenranta, Finland, Revised Selected Papers. Springer Nature. ISSN 9783030726959. p. 67–89. doi: 10.1007/978-3-030-72696-6_3. Full text in Research Archive Show summary

  In the development of computer-based systems, modelling is often advocated in addition to programming, in that it helps in reflecting the application domain and that it makes the design and experiment activities of development more efficient. However, there is disagreement about what models are and how they can be used in software systems development. In this paper, we present the Scandinavian approach to modelling, which makes a clear distinction between models and model descriptions. This paper explains the connections between models, descriptions, systems, and executions. Combining the Scandinavian approach with the Kiel notion of model, we establish that both descriptions and executions are closely connected instruments with different roles. The paper argues that (program) executions are the models of dynamic systems, not their descriptions in terms of diagrams and text. So in a general sense programming is about writing descriptions for systems. In particular the paper clarifies when programming is also modelling.

• Fischer, Joachim; Møller-Pedersen, Birger & Prinz, Andreas (2020). Real Models are Really on M0 - Or How to Make Programmers Use Modeling. In Hammoudi, Slimane; Pires, Luís Ferreira & Selic, Bran (Ed.), Modelsward 2020. SciTePress. ISSN 9789897584008. p. 307–318. doi: 10.5220/0008928403070318. Full text in Research Archive Show summary

  This paper discusses the term ’model’ and the role of the level M0 in the four-layer metamodeling architecture of MOF/OMG. It illustrates the failures of the OMG MOF standard and how a model is an abstraction, not a description. We apply two simple approaches: (1) observing the use of models (of real or planned systems) in system development, including prototyping, simulations, and models in general, and (2) comparing modeling with programming. These approaches lead to the conclusion that models should be placed on M0, while UML models are model descriptions. This conclusion leads to a better understanding of InstanceSpecification for description of snapshots, and of metamodeling applied to ontologies.

• Schulz, Renee Patrizia; Smaradottir, Berglind; Prinz, Andreas & Hara, Takahiro (2020). User-centred Design of a Scenario-based Serious Game: Game-based Teaching of Future Healthcare. IEEE Transactions on Games (TG). ISSN 2475-1502. 12(4), p. 376–385. doi: 10.1109/TG.2020.3033437. Full text in Research Archive
• Xanthopoulou, Themis Dimitra; Puga-Gonzalez, Ivan; Shults, F. LeRon & Prinz, Andreas (2020). Modeling Marginalization: Emergence, Social Physics, and Social Ethics of Bullying, Proceedings of the 2020 Spring Simulation Conference (SpringSim’20). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781565553705. doi: 10.22360/SpringSim.2020.HSAA.005. Full text in Research Archive Show summary

  In this paper, we outline the construction and initial simulation experiment results of the Marginalization model (MARG). We experiment under different group parameters because the theoretical paradigm we follow views bullying as a result of social processes. Our primary research question explores the possibility of bullying emergence as agents select interaction partners in a university setting. Based on the simulated process, our results take indications of the stress of marginalization in a student group as a proxy for emer-gent marginalization. MARG simulates two types of interactions between pairs of students: forced and hang-out interactions. In the latter, students decide whether to interact based on individual preferences formed by social norms and individual tolerance related to those norms. The emergence of intensified mar-ginalization from MARG processes leads to some ethical considerations and provides ground for discus-sions concerning suitable interventions.

• Prinz, Andreas & Mezei, Gergely (2020). The Art of Bootstrapping, Model-Driven Engineering and Software Development. Springer. ISSN 9783030378738. p. 182–200. doi: 10.1007/978-3-030-37873-8_8. Full text in Research Archive Show summary

  Language workbenches are used to define languages using appropriate meta-languages. Meta-languages are also just languages and can, therefore, be defined using themselves. The process is called bootstrapping and is often difficult to achieve. This paper compares four different bootstrapping solutions. The EMF environment and the Meta-Programming System (MPS) use a compiled bootstrapping for their own definition. The platforms LanguageLab and DMLA are using interpreted bootstrapping. This paper compares these kinds of bootstrapping and relates them to the definition of instantiation. Besides the structural aspects of the bootstraps, the dynamism is also elaborated. It is shown how the bootstrap is related to the execution environment. Finally, the level of changeability is also discussed. It is shown that all approaches are quite similar and provide very flexible environments.

• Chatterjee, Ayan; Gerdes, Martin; Prinz, Andreas; Martinez, Santiago & Medin, Anine Christine (2020). Reference Design Model for a Smart e-Coach Recommendation System for Lifestyle Support Based on ICT Technologies. In Sendra, Sandra; Murata, Yoshitoshi; Civit-Masot, Javier & Rajh, Arian (Ed.), eTELEMED 2020, The Twelfth International Conference on eHealth, Telemedicine, and Social Medicine. International Academy, Research and Industry Association (IARIA). ISSN 9781612087634. p. 52–58. doi: 10.13140/RG.2.2.33574.47689. Full text in Research Archive Show summary

  As acknowledged by the World Health Organization (WHO), the demographic development shows that by 2030, 8 out of the 10 foremost causes of death will be connected to risk conditions of lifestyle diseases, regardless of gender. Chronic illness associated with modifiable lifestyle factors will be accountable for the highest death worldwide. Health behavior change should be given priority to avoid serious reparations. An Electronic Coach (e-Coach) system can empower people to achieve a healthy lifestyle with early risk predictions and appropriate tailored lifestyle recommendations. Research in eHealth has the potential to provide methods in order to improve personal healthcare with Information and Communication Technologies (ICT). An Electronic Health (e-Health) virtual coaching recommendation system can monitor people and convey the appropriate recommendations in context with enough time to prevent, ameliorate the living with non-communicable or lifestyle diseases. This paper addresses the potential of selected emerging information and communication technologies to make e-Health systems smarter, more collaborative and more efficient. As a result of the analysis, a reference design is discussed here to develop and validate the performance of a smart e-Coach system utilizing ICT, Internet of Things (IoT) and Artificial Intelligence (AI) to provide individual lifestyle recommendations aiming at a healthier lifestyle to prevent obesity and overweight. The healthcare sector is still looking for collaborative, user-friendly, optimized, cost-effective, reliable systems for health e-Coaching with contextual, tailored lifestyle recommendations and our current research is focused on its implementation and validation, considering obesity and overweight as a case study.

• Xanthopoulou, Themis Dimitra; Prinz, Andreas; Puga-Gonzalez, Ivan & Shults, F. LeRon (2020). Modeling marginalization: Emergence, social physics, and social ethics of bullying. Simulation Series. ISSN 0735-9276. 52(1), p. 452–463. Full text in Research Archive
• Handeland, Jorunn Aas; Prinz, Andreas; Ekra, Else Mari Ruberg & Fossum, Mariann (2020). The role of manikins in nursing students' learning: A systematic review and thematic metasynthesis. Nurse Education Today. ISSN 0260-6917. p. 1–11. doi: 10.1016/j.nedt.2020.104661. Full text in Research Archive Show summary

  Objectives To summarise and synthesise findings from qualitative primary research studies of nursing students' experiences from educational activities using manikins to gain a deeper understanding of the role these manikins play in the students' learning. Design and data sources A systematic review and thematic metasynthesis were conducted. Cinahl+, Ovid Medline, ERIC and Embase were searched systematically. Review methods Sandelowski and Barroso's framework guided the review process. A comprehensive search to identify qualitative studies of nursing students' experiences from learning with manikins was performed in January 2019 and updated in April 2020. Study selection was guided by six screening questions derived from these inclusion criteria: qualitative primary studies, published from 2008, in English or Scandinavian, presenting findings of undergraduate nursing students' experiences with manikins at all fidelity levels. Thomas and Harden's method for thematic synthesis was followed. Results Twenty-eight articles of twenty-seven studies were included. We identified three synthesised analytic themes: Seeing the manikin as a doll or a patient, Experiencing yourself as a nurse caring for a patient, and Being a team member. Conclusions When it is perceived as a patient, a manikin can give students a realistic experience of what it means to behave like nurses. Consequently, this realism lets students practice and acquire relational, communicative, and collaborative nursing skills. Using a manikin can facilitate the development of students' professional identity.

• Schewe, Klaus-Dieter; Prinz, Andreas & Börger, Egon (2019). Concurrent Computing with Shared Replicated Memory. In Schewe, Klaus-Dieter & Singh, Neeraj kumar (Ed.), Model and Data Engineering. MEDI 2019. Springer Nature. ISSN 9783030320645. doi: 10.1007/978-3-030-32065-2_16. Full text in Research Archive
• Sherratt, Edel & Prinz, Andreas (2019). Eventual Consistency Formalized. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 11753 LNCS, p. 249–265. doi: 10.1007/978-3-030-30690-8_15. Full text in Research Archive
• Prinz, Andreas & Shatalin, Alexander (2019). How to Bootstrap a Language Workbench. In Hammoudi, Slimane; Pires, Luís Ferreira & Selic, Bran (Ed.), Modelsward 2019. SciTePress. ISSN 9789897583582. p. 345–352. doi: 10.5220/0007398203450352. Full text in Research Archive
• Schewe, Gerhard; Prinz, Andreas & Börger, Egon (2019). Concurrent Computing with Shared Replicated Memory. arXiv.org. ISSN 2331-8422. 11815 LNCS, p. 219–234. doi: 10.1007/978-3-030-32065-2_16. Full text in Research Archive
• Kikhia, Basel Salah; Boytsov, Andrey; Guinea, Alejandro Sanchez & Prinz, Andreas (2019). Utilizing a Wristband to Detect the Quality of a Performed CPR. Journal of Advances in Information Technology. 10(4), p. 123–130. doi: 10.12720/jait.10.4.123-130. Full text in Research Archive
• Schulz, Renee Patrizia; Smaradottir, Berglind; olsen, joakim torblå & Prinz, Andreas (2019). Scenario-based Serious Game to Teach about Healthcare, 2019 IEEE 7th International Conference on Serious Games and Applications for Health (SeGAH). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781728103006. doi: 10.1109/SeGAH.2019.8882480. Full text in Research Archive Show summary

  In this paper, we explore the concept of a scenario-based serious game for healthcare solutions. The complexity of the interactions and the multitude of actors is captured in a scenario, which is then played with the help of an additional game platform, here called “scenario system”. The platform allows high school students to play through a healthcare scenario, possibly including eHealth technology, thereby teaching them about interactions and technology used in modern healthcare. The mobile serious game is based on context and role-triggered tasks for the players so that the game is guided, but includes a certain dynamic and flexibility. The project contributes a method and a tool to use scenarios for user testing of eHealth systems and services as well as an alternative method for teaching the complex domain of eHealth systems to unfamiliar users (e.g. highschool students).

• Xanthopoulou, Themis Dimitra; Prinz, Andreas & Shults, F. LeRon (2019). Generating Executable Code from High-Level Social or Socio-Ecological Model Descriptions. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 11753 LNCS, p. 150–162. doi: 10.1007/978-3-030-30690-8_9. Full text in Research Archive
• olsen, joakim torblå; Prinz, Andreas & Smaradottir, Berglind (2019). Simulation of eHealth Scenarios with Role-play Supported by an Interactive Smartphone Application. Studies in Health Technology and Informatics. ISSN 0926-9630. 257, p. 418–423. doi: 10.3233/978-1-61499-951-5-418. Full text in Research Archive
• Somappa, Admar Ajith Kumar; Kristensen, Lars Michael & Prinz, Andreas (2018). Model-based specification and validation of the dual-mode adaptive MAC protocol. International Journal of Critical Computer-Based Systems. ISSN 1757-8779. 8(2), p. 108–140. doi: 10.1504/IJCCBS.2018.096190. Full text in Research Archive Show summary

  Wireless sensor and actuator networks (WSANs) rely on MAC protocols to coordinate access to the wireless medium access and for managing the radio unit on each device. The dual-mode adaptive MAC (DMAMAC) protocol is a recently proposed protocol designed to reduce the energy consumption of the radio communication in WSANs. The DMAMAC protocol targets the industrial WSANs used for real-time process control. At its core, DMAMAC exploits the distinction between transient and steady of the controlled plant process to dynamically adapt the MAC superframe structure and thereby conserve energy. The switch between steady and transient mode of operation is a safety-critical part of the protocol. The contribution of this paper is to develop a rigorous specification of the DMAMAC protocol using timed automata and the supporting Uppaal software tool. The Uppaal tool is also used to verify key functional and real-time properties of the protocol. Finally, we have used execution sequences from the formal specification model to validate an OMNET simulation model used for performance evaluation of DMAMAC, and to validate a nesC implementation of the protocol on the TinyOS platform.

• Chatterjee, Ayan & Prinz, Andreas (2018). Image Analysis on Fingertip Video to Obtain PPG. Biomedical and Pharmacology Journal (BPJ). ISSN 0974-6242. 11(4), p. 1811–1827. doi: 10.13005/bpj/1554. Full text in Research Archive Show summary

  Cardiovascular problems are evolving as the chief cause of death worldwide. Heart Rate, Blood Pressure, Respiratory Rate, Oxygen Saturation, Systolic Upstroke Time, Heart Beat duration, Diastolic time, RR intervalare some important physiological parameters that help to monitor our daily health condition. Those parameters are very useful to determine if a person is suffering from any cardiovascular problems or not based on daily data collection and monitoring over a certain period of time and in this context machine learning algorithms will be very helpful for developing a smart cardiovascular tele-monitoring & recommendation system for better lifestyle. Irregularities in the heart signal can pop up a serious indication for upcoming cardiac problem. Here, we have concentrated on intensity variation based heart rate calculation process from PPG with major analysis on captured contact video. Here we have used normal handy smart phone camera which is available to everyone and able to capture fingertip videos of flowing blood in the vessels with visible light wavelength. In this paper, we have performed analysis on captured videos for accurate health parameter capturing and compared it with standard devices (FDA approved).

• Nabushawo, Harriet M.; Muyinda, Paul Birevu; Isabwe, Ghislain Maurice Norbert; Prinz, Andreas & Mayende, Godfrey (2018). Improving Online Interaction Among Blended Distance Learners at Makerere University, Teaching and Learning in a Digital World roceedings of the 20th International Conference on Interactive Collaborative Learning. Springer. ISSN 9783319732091. p. 63–69. doi: 10.1007/978-3-319-73210-7_8. Full text in Research Archive
• Prinz, Andreas (2018). Distributed computing on distributed memory. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 11150 LNCS, p. 67–84. doi: 10.1007/978-3-030-01042-3_5. Full text in Research Archive
• Mayende, Godfrey; Prinz, Andreas; Muyinda, Paul Birevu & Isabwe, Ghislain Maurice Norbert (2018). Towards Technology for Supporting Effective Online Learning Groups, 11th IMCL 2017: Interactive Mobile Communication Technologies and Learning. Springer. ISSN 9783319751757. p. 361–371. doi: 10.1007/978-3-319-75175-7_37. Full text in Research Archive Show summary

  Group learning has been advocated for increasing active learning among distance learners. However, there is limited understanding on how to engage learners in online courses. Following the design science methodology, we iteratively developed guiding factors for supporting effective online learning groups. The factors for effective online learning groups cover five key dimensions, namely institutional policies, institutional technology, group activity, group composition, and facilitation. The factors are validated through repetitive evaluation using authentic online learning courses, as well as using a focus group discussion with experienced online facilitators. This way, the factors provide pedagogical and technological guidelines for introducing online course groups. Moreover, they give requirements for online learning systems supporting effective online learning groups.

• Schulz, Renee Patrizia; Lazareva, Aleksandra; Isabwe, Ghislain Maurice Norbert & Prinz, Andreas (2017). Higher Education Teachers Meet Mobile Technology: Application and Acceptance. In Chova, L. Gómez; Martínez, A. López & Torres, I. Candel (Ed.), EDULEARN17 proceedings : 9th international confererence om education and new learning technologies. International Academy of Technology, Education and Development (IATED). ISSN 9788469737774. p. 9237–9246. doi: 10.21125/edulearn.2017.0735. Full text in Research Archive
• Guttormsen, Stian; Prinz, Andreas & Gjøsæter, Terje (2017). Consistent Projectional Text Editors. In Pires, Luís Ferreira; Hammoudi, Slimane & Selic, Bran (Ed.), Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development. SciTePress. ISSN 9789897582103. p. 515–522. doi: 10.5220/0006264505150522. Full text in Research Archive
• Nunavath, Vimala & Prinz, Andreas (2017). Data sources handling for emergency management: Supporting information availability and accessibility for emergency responders. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 10274 LNCS, p. 240–259. doi: 10.1007/978-3-319-58524-6_21. Full text in Research Archive
• Nunavath, Vimala; Prinz, Andreas & Comes, Tina (2017). Identifying First Responders Information Needs: Supporting Search and Rescue Operations for Fire Emergency Response. International Journal of Information Systems for Crisis Response and Management (IJISCRAM). ISSN 1937-9390. 8(1), p. 25–46. doi: 10.4018/IJISCRAM.2016010102. Full text in Research Archive
• Øysæd, Halvard; Andersen, Rune; Garmannslund, Per Einar; Prinz, Andreas; Lazareva, Aleksandra & Schmidt, Michael (2017). Does The Introduction Of An Overall Study Strategy Empowering Students To Use Appropriate Study Strategies? ICERI Proceedings. p. 4152–4157. doi: 10.21125/iceri.2017.1098. Full text in Research Archive
• Schulz, Renee Patrizia; Isabwe, Ghislain Maurice Norbert; Prinz, Andreas & Hara, Takahiro (2017). High-Level Context Information for Tasks in Teaching, Advances in Human Factors in Training, Education, and Learning Sciences. Springer. ISSN 9783319600178. p. 278–289. doi: 10.1007/978-3-319-60018-5_27. Full text in Research Archive
• Nunavath, Vimala; Prinz, Andreas & Comes, Tina (2017). Qualitative and Quantitative Study on Videotaped Data for Fire Emergency Response. In Benlamri, Rachid & Sparer, Michael (Ed.), Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy - Proceedings of the 2016 International Conference on Leadership, Innovation and Entrepreneurship (ICLIE). Springer Publishing Company. ISSN 9783319434339. p. 149–158. doi: 10.1007/978-3-319-43434-6_13. Full text in Research Archive
• Nunavath, Vimala & Prinz, Andreas (2017). Visualization of Exchanged Information with Dynamic Networks: A Case Study of Fire Emergency Search and Rescue Operation. In Bilof, Randall (Eds.), Advance Computing Conference (IACC), 2017 IEEE 7th International. IEEE Press. ISSN 9781509015603. p. 281–286. doi: 10.1109/IACC.2017.60. Full text in Research Archive
• Mayende, Godfrey; Prinz, Andreas; Isabwe, Ghislain Maurice Norbert & Muyinda, Paul Birevu (2017). Learning Groups in MOOCs : Lessons for Online Learning in Higher Education. International Journal of Engineering Pedagogy (iJEP). 7(2), p. 109–124. doi: 10.3991/ijep.v7i2.6925. Full text in Research Archive
• Nunavath, Vimala & Prinz, Andreas (2017). Liferescue software prototype for supporting emergency responders during fire emergency response: A usability and user requirements evaluation. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 10272 LNCS, p. 480–498. doi: 10.1007/978-3-319-58077-7_39. Full text in Research Archive
• Mayende, Godfrey; Prinz, Andreas & Isabwe, Ghislain Maurice Norbert (2017). Improving Communication in Online Learning Systems, CSEDU 2017 9th INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED EDUCATION.. SciTePress. ISSN 9789897582394. p. 300–307. doi: 10.5220/0006311103000307. Full text in Research Archive Show summary

  In this paper, we study communication in online learning systems using both quantitative and qualitative research methods. Quantitative methods provide the interaction statistics, while qualitative content analysis was used for categorisation of the messages. It turns out that 20% of the active participants dominate the online learning interactions, and more than 80% are passive consumers. From the categorization, we learned that most of the communication is not related to learning, but to technical problems (26%), small talk (29%), sharing experience (16%), and encouragement (11%). Only 10% are related to the content. For improved communication, it is therefore important to use the right communication tools in the online learning systems. Especially, learning by content creation should be provided.

• Yang, Huihui; Oleshchuk, Vladimir & Prinz, Andreas (2016). Verifying group authentication protocols by Scyther. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications. ISSN 2093-5374. 7(2), p. 3–19. doi: 10.1109/pdp.2016.27. Full text in Research Archive
• Fischer, Joachim; Møller-Pedersen, Birger & Prinz, Andreas (2016). Modelling of Systems for Real. In Hammoudi, Slimane; Pires, Luís Ferreira; Selic, Bran & Desfray, Philippe (Ed.), Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development. SciTePress. ISSN 9789897581687. p. 427–434. doi: 10.5220/0005825704270434. Full text in Research Archive
• Schulz, Renee Patrizia; Isabwe, Ghislain Maurice Norbert & Prinz, Andreas (2016). Development of a Task-Driven Mobile Teaching Tool for Enhancing Teachers’ Motivation. In Uhomoibhi, James; Costagliola, Gennaro; Zvacek, Susan & McLaren, Bruce M. (Ed.), CSEDU 2016 Proceedings of the 8th International Conference on Computer Supported Education, proceedings volume 1. SciTePress. ISSN 9789897581793. p. 251–258. doi: 10.5220/0005765402510258. Full text in Research Archive
• Gjøsæter, Terje; Prinz, Andreas & Nytun, Jan Pettersen (2016). MOF-VM: Instantiation Revisited. In Hammoudi, Slimane; Pires, Luís Ferreira; Selic, Bran & Desfray, Philippe (Ed.), Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development. SciTePress. ISSN 9789897581687. p. 137–144. doi: 10.5220/0005606101370144. Full text in Research Archive Show summary

  The Model-Driven Architecture (MDA) is based on an understanding of a hierarchy of levels that are placed on top of each other and that are connected with instantiation. For practical MDA use, it is important to be clear about the kinds of objects that reside on the different levels and the relations between them as well as relations to objects outside of the MDA domain. This article aims at enhancing the understanding of these objects and relations by relating them to a virtual MOF machine.

• Yang, Huihui; Prinz, Andreas & Oleshchuk, Vladimir (2016). Formal Analysis and Model Checking of a Group Authentication Protocol by Scyther. In Cotronis, Yiannis; Daneshtalab, Masoud & Papadopoulos, George Angelos (Ed.), Proceedings of the 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP2016). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781467387750. p. 553–557. doi: 10.1109/PDP.2016.27. Full text in Research Archive
• Mayende, Godfrey; Prinz, Andreas; Isabwe, Ghislain Maurice Norbert; Muyinda, Paul Birevu & Nampijja, Dianah (2016). Philosophical and ethical concerns in researching online learning groups, 2016 IEEE Conference on e-Learning, e-Management and e-Services (IC3e 2016). IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781467390613. doi: 10.1109/IC3e.2016.8009047. Full text in Research Archive
• Øysæd, Halvard; Andersen, Rune; Prinz, Andreas & Schulz, Renee Patrizia (2016). Teaching students to learn. In Uhomoibhi, James; Costagliola, Gennaro; Zvacek, Susan & McLaren, Bruce M. (Ed.), CSEDU 2016 Proceedings of the 8th International Conference on Computer Supported Education, proceedings volume 1. SciTePress. ISSN 9789897581793. p. 91–98. doi: 10.5220/0005764800910098. Full text in Research Archive

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• Prinz, Andreas; Møller-Pedersen, Birger; Fischer, Joachim & Thalheim, Bernhard (2024). Understanding Modelling and Programming. Springer Nature. ISBN 9783031712791. 128 p. Full text in Research Archive
• Nunavath, Vimala & Prinz, Andreas (2017). Data Sources Handling for Emergency Management: Supporting Information Availability and Accessibility for Emergency Responders. Springer Cham. ISBN 9783319585246. -240259 p. Full text in Research Archive
• Nunavath, Vimala & Prinz, Andreas (2017). LifeRescue Software Prototype for Supporting Emergency Responders During Fire Emergency Response: A Usability and User Requirements Evaluation. Springer, Cham. ISBN 9783319580777. -480498 p. Full text in Research Archive

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• Chatterjee, Ayan; Pahari, Nibedita; Prinz, Andreas & Riegler, Michael (2023). Author Correction: Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation (Scientific Reports, (2022), 12, 1, (19825), 10.1038/s41598-022-24118-4). Scientific Reports. 13(1). doi: 10.1038/s41598-023-30029-9. Full text in Research Archive
• Prinz, Andreas; Xanthopoulou, Themis Dimitra; Gjøsæter, Terje & Møller-Pedersen, Birger (2022). On abstraction in the OMG hierarchy: systems, models, and descriptions. Full text in Research Archive
• Handeland, Jorunn Aas; Prinz, Andreas; Ekra, Else Mari Ruberg & Fossum, Mariann (2021). The role of manikins in nursing students' learning - A systematic review and thematic metasynthesis. Full text in Research Archive
• Xanthopoulou, Themis Dimitra; Pardede, Saga & Prinz, Andreas (2021). Bully-proofing a learning environment. Full text in Research Archive
• Prinz, Andreas; Schmidt, Michael; Xanthopoulou, Themis Dimitra & Isabwe, Ghislain Maurice Norbert (2021). How to be different - mindset and tools. Full text in Research Archive
• Xanthopoulou, Themis Dimitra & Prinz, Andreas (2020). Tutorial: ODD2ABM – Creation of NetLogo Agent-Based Models from a Formalised ODD. Full text in Research Archive
• Chatterjee, Ayan; Prinz, Andreas; Gerdes, Martin & Martinez, Santiago (2020). A Statistical Study to Analyze the Impact of External Weather Change on Chronic Pulmonary Infection in South Norway with Machine Learning Algorithms. In Intelligent Technologies and Applications. Full text in Research Archive
• Prinz, Andreas (2019). Project-based learning in IKT445 - How to flip a classroom? Full text in Research Archive
• Xanthopoulou, Themis Dimitra; Prinz, Andreas; Shults, F. LeRon; Puga-Gonzalez, Ivan & Lund, Ingrid (2019). Social Simulation of University Bullying. Full text in Research Archive
• Olsen, Joakim Torblå; Prinz, Andreas & Smaradottir, Berglind (2019). Simulation of eHealth Scenarios with Role-play Supported by an Interactive Smartphone Application. Full text in Research Archive
• Schulz, Renee Patrizia; Smaradottir, Berglind; Olsen, Joakim Torblå & Prinz, Andreas (2019). Scenario-based Serious Game to Teach about Healthcare. Full text in Research Archive
• Holen-Rabbersvik, Elisabeth; Prinz, Andreas; Gerdes, Martin; Martinez, Santiago; Thygesen, Elin & Fensli, Rune Werner [Show all 7 contributors for this article] (2018). Teaching High School Students eHealth through Role-play and Laboratory Simulation. Medicinsk Informatika. ISSN 1330-1799. 14, p. 35–36. Full text in Research Archive
• Holen-Rabbersvik, Elisabeth; Prinz, Andreas; Gerdes, Martin; Martinez, Santiago; Thygesen, Elin & Fensli, Rune Werner [Show all 7 contributors for this article] (2018). Teaching High School Students eHealth through Roleplay and Laboratory Simulation. Full text in Research Archive Show summary

  The transformation and digitalisation of health and care services foresees a need for recruitment of young individuals having a combination of health- and computer science knowledge to contribute in the workforces of the future. At the University of Agder in Norway there has been an eHealth Centre since year 2010 [1], where both already implemented and proposed eHealth services can be simulated and tested. In the project High School Students as Co-researchers in eHealth, experienced researchers allowed high school students to be enrolled in a project course to actively play and test an eHealth scenario. This paper aims at sharing the experiences on how the pilot of a class consisting of 10 high school students at the age of 17-19 years, were taught eHealth through role-play and simulation in the eHealth Centre. The research question stated was: How to introduce high school students to eHealth research and services in a life-long learning perspective?

• Prinz, Andreas (2018). E-helse: Infrastruktur, forskning og studier. Full text in Research Archive
• Prinz, Andreas (2018). Senter for eHelse og I4Helse - forskning i eHelse. Full text in Research Archive
• Prinz, Andreas (2018). Senter for eHelse og I4Helse. Full text in Research Archive
• Prinz, Andreas (2018). Senter for eHelse og I4Helse - brukerinvolvering. Full text in Research Archive
• Prinz, Andreas (2018). I4Helse. Full text in Research Archive
• Prinz, Andreas (2018). Senter for eHelse og i4Helse. Full text in Research Archive
• Xanthopoulou, Themis Dimitra; Prinz, Andreas; Shults, F. LeRon & Puga-Gonzalez, Ivan (2018). An agent-based model of bullying dynamics. Full text in Research Archive
• Nabushawo, Harriet M.; Muyinda, Paul Birevu; Isabwe, Ghislain Maurice Norbert; Prinz, Andreas & Mayende, Godfrey (2017). Improving online interaction among blended distance learners at Makerere University. Full text in Research Archive
• Mayende, Godfrey; Prinz, Andreas; Muyinda, Paul Birevu & Isabwe, Ghislain Maurice Norbert (2017). Towards Technology for Supporting Effective Online Learning Groups. Full text in Research Archive
• Prinz, Andreas (2017). Kunnskap er blitt allemannseie på nettet. Full text in Research Archive
• Prinz, Andreas (2017). Senter for eHelse og I4Helse. Full text in Research Archive
• Prinz, Andreas (2016). Teaching and Learning Habits. Full text in Research Archive
• Fossum, Mariann; Prinz, Andreas & Ekra, Else Mari Ruberg (2024). Manikins Mediate Lifelong Learning Skills in Nursing Education: A Qualitative Exploration of How Manikins Influence Nursing Students’ Learning. Universitetet i Agder. Full text in Research Archive
• Mayende, Godfrey & Prinz, Andreas (2020). Supporting Effective Online Learning Groups for eLearning Systems. Universitetet i Agder. ISSN 9788271179885. Full text in Research Archive Show summary

  Learning in groups has been advocated to increase learning based on the social constructivist learning theory. ICT has been preferred to bridge the gap between distance learning students for possibilities to enhance the benefits of learning groups. However, although learning groups can bring about meaningful learning, learning groups in online environments are often not working. To solve this problem, this study uses design science approaches to establish methods and factors that support effective online learning groups. Within design science three case studies were used. These case studies were used under three research areas: context of online learning groups, processes to support effective online learning groups and tools to support effective online learning groups. The study adopted mixed methods in the evaluation stage of the adopted design science. Establishing the context of online learning groups laid a foundation for this study. This was done using a survey approach that covered the five regions in Uganda, semi-structured interviews with experienced online learning facilitators and observation of interaction logs of online courses at both the University of Agder and Makerere University. Initially, preliminary findings of effective online learning groups were established. The preliminary findings consist of the need for: study guide, trained online tutors, motivating and sustaining interaction, high levels of cognitive interactions, peer assessment based activities and ICT. From the context of online learning groups, the Methods and Factors for Effective Online Learning Groups (FEOLG) were established. FEOLG include: supporting institutional online learning group policy; supporting institutional online learning group technology; quality of online learning group activity; quality of the online learning group; and quality of online learning group facilitation. The factors were evaluated using online learning courses based on existing Makerere University eLearning Environment (MUELE) and online learning group design. The thesis contributes: methods for creating online learning groups, methods for structuring online learning group activities, methods for facilitating online learning groups, and the establishment of factors for supporting effective online learning groups.

• Schulz, Renee Patrizia; Prinz, Andreas & Isabwe, Ghislain Maurice Norbert (2018). Listening to Teachers' Needs: Human-centered Design for Mobile Technology in Higher Education. Universitetet i Agder. ISSN 9788271178826. Full text in Research Archive

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