Research Title: pH-responsive chlorhexidine LbL coated silica nanoparticles for managing skin wound infections

Author: Raida W. Khalil, Published Year: 2025

Colloid and Interface Science Colloids and Surface, 726

Faculty: Science

Abstract: Skin wound infections pose a significant challenge for clinical treatment due to the development of biofilm. In this study, a wound dressing was employed to accelerate healing by enhancing the release and effectiveness of antimicrobial agents. pH-sensitive silica nanoparticles (SiNP) were designed to enable targeted drug delivery in both acidic and neutral wound environments, optimizing drug delivery. Chlorhexidine (CHX), a well-known antiseptic, was incorporated into SiNP using a layer-by-layer (LbL) coating method. The nanoparticles were characterized for size (TEM), surface charge (zeta potential), FTIR, TGA, CHX release. The CHX-loaded SiNP (CHX-SiNP) exhibited a 2–3 times higher release at pH 5 compared to pH 7.4. Additionally, CHX-SiNP demonstrated strong antibacterial activity against both Gram-negative and Gram-positive bacteria, without showing cytotoxicity in cell viability tests. To enhance usability, CHX-SiNP were incorporated into alginate hydrogels. Their antibacterial efficacy was further evaluated using artificial wounds created in an ex vivo human skin, where alginate-formulated CHX-SiNP treatment resulted in decrease in viable bacterial cells, compared to negative controls. These findings confirm that CHX-SiNP enable effective pH-responsive drug release, ensuring strong antibacterial performance. Furthermore, this study highlights the clinical potential of CHX-SiNP in treating wound infections.

Keywords: pH-responsive chlorhexidine LbL

Research Title: Jordanian nursing students’ perceptions of the compassionate actions of their clinical instructors: a mixed-methods study

Author: Rabia Hani Amin Haddad, Published Year: 2025

BMC Nursing, 24

Faculty: Nursing

Abstract: Background: In helping professions such as nursing, caring is regarded as a fundamental principle. Observations of nursing students revealed both caring and non-caring behaviors, highlighting the complexity of professional development within clinical and educational settings. Aim: This study sought to understand how Jordanian nursing students perceived the caring behavior of clinical instructors during their clinical training. Method A mixed-methods approach was utilized to recruit data from (n = 200) nursing students using the Nursing Students’ Perception of Instructor Caring (NCPIC) developed by Wade and Kasper (2006). Result: The findings showed that the average mean score for clinical instructor behaviors perceived by nursing students was at a medium level (M = 3.40 out of 6). Four themes were extracted, namely, communication, professionalism, holistic caring (mothering), and motivation. In contrast, the non-caring behaviors were reflected in poor communication, governing, and unfavorable personal traits of the clinical instructors, as well as acting in a non-professional manner. Conclusion: Caring has been emphasized as a key component of nursing education. It should be inherent in the behavior and actions of clinical instructors when they interact with nursing students in a clinical setting. Clinical trial number Not applicable.

Keywords: Caring, Caring behavior, Nursing students, Professionalism, Clinical instructor, Non-clinical behavior

Research Title: pH-responsive chlorhexidine LbL coated silica nanoparticles for managing skin wound infections

Author: Yazan Mohammad Al-Thaher, Published Year: 2025

Colloids and Surfaces A: Physicochemical and Engineering Aspects, Volume 726, Part 1,

Faculty: Pharmacy

Abstract: Skin wound infections pose a significant challenge for clinical treatment due to the development of biofilm. In this study, a wound dressing was employed to accelerate healing by enhancing the release and effectiveness of antimicrobial agents. pH-sensitive silica nanoparticles (SiNP) were designed to enable targeted drug delivery in both acidic and neutral wound environments, optimizing drug delivery. Chlorhexidine (CHX), a well-known antiseptic, was incorporated into SiNP using a layer-by-layer (LbL) coating method. The nanoparticles were characterized for size (TEM), surface charge (zeta potential), FTIR, TGA, CHX release. The CHX-loaded SiNP (CHX-SiNP) exhibited a 2–3 times higher release at pH 5 compared to pH 7.4. Additionally, CHX-SiNP demonstrated strong antibacterial activity against both Gram-negative and Gram-positive bacteria, without showing cytotoxicity in cell viability tests. To enhance usability, CHX-SiNP were incorporated into alginate hydrogels. Their antibacterial efficacy was further evaluated using artificial wounds created in an ex vivo human skin, where alginate-formulated CHX-SiNP treatment resulted in decrease in viable bacterial cells, compared to negative controls. These findings confirm that CHX-SiNP enable effective pH-responsive drug release, ensuring strong antibacterial performance. Furthermore, this study highlights the clinical potential of CHX-SiNP in treating wound infections.

Keywords: PH-response, Silica nanoparticles, Controlled drug release, Wound infection, Ex vivo skin.

Research Title: Workplace violence in Jordanian hospitals: sociodemographic and occupational characteristics influences, effect on quality of care and recommended solutions

Author: Audi Naji Khaled Al Smadi, Published Year: 2025

Journal of Health Organization and Management,

Faculty: Business

Abstract: Purpose – Workplace violence (WPV) negatively affects the well-being of healthcare workers (HCWs) and the healthcare system. This study explores how sociodemographic factors impact WPV prevalence, its effect on the quality of care, and possible solutions to decrease WPV in Jordanian hospitals. Design/methodology/approach – This study employs a retrospective cross-sectional design, using a webbased survey of 651 HCWs. The data were analyzed using descriptive statistics, logistic regression, an independent sample t-test, and path analysis. Findings – Around 651 HCWs participated in this study, and only 316 revealed they experienced WPV. Multivariate logistic regression analysis confirmed the significance of occupation, sector, and education level in influencing WPV. The result revealed a significant reduction in the quality of care of HCWs exposed to WPV. HCWs shared valuable recommendations to decrease WPV in their workplace. The recommendations were categorized under seven main areas: cultural issues, legal and legislative, administrative measures, internal organization arrangement, quality of health care services, physical working environment, and finally, training and awareness. Practical implications – Hospital management and policymakers should consider factors like local culture, legal and administrative measures, policies, healthcare quality, work environment, and community awareness when addressing WPV. Moreover, healthcare workers can offer valuable recommendations to reduce WPV prevalence and impact in healthcare settings. Originality/value – This is a unique study that explores the relationship between WPV and quality of care in Jordanian hospitals. It considers sociodemographic and occupational characteristics as contributing factors to WPV in hospitals and seeks realistic solutions from the victims’ perceptions.

Keywords: Workplace violence, Quality of care, Hospital, Jordan

Research Title: An overview of teaching AI literacy to university students

Author: Lamis Al-Qoran, Published Year: 2024

Faculty: Information Technology

Abstract: Although artificial intelligence (AI) is increasing in influence across different fields, the subject of AI literacy in higher education (HE) remains inadequately explored. Through a systematic review of 19 peer-reviewed journal articles, this chapter fills that gap. The findings of this study highlight the advancements in AI literacy education across different subject disciplines. It emphasizes the importance of critical thinking, ethical reasoning, and practical skills in managing the increasingly complicated world driven by AI.

Keywords: AI literacy education, Ethical AI, AI curriculum design, AI in higher education, Impact of AI literacy, AI and students with disabilities

Research Title: The Role of User Experience in Software Sustainability Designing for Longevity

Author: Lamis Al-Qoran, Published Year: 2025

2025 16th International Conference on Information and Communication Systems (ICICS), Jordan University of Science and Technology

Faculty: Information Technology

Abstract: User experience (UX) design plays a key role in ensuring the application's long-term sustainability by improving maintainability, usability and to adapt in continuously evolving digital environments. UX design has been shown to improve user engagement and satisfaction. It also reduces technical cost by reducing unconventional redesigns. Poor UX design can lead to abandoning the program as the user is directed towards easier alternatives, which increases the cost of maintenance. This paper investigates the role of UX design in the production of software systems that live over the long term and to explain its contribution to the focus on the user. This paper aims to examines the role of UX design in the long-term production of software systems and explain its contribution to user centeredness, iterative design processes, simple interfaces and customized interfaces that are supported by artificial intelligence in increasing software longevity and operating efficiency. Our research brings together current studies and best practices, reviews the comparison of successful user experience design with unsustainable software, and focuses on the benefits of investing in UX design. We concluded that UX practices significantly improve maintainability, retain users, and extend the life of the software. The study highlights the importance of incorporating sustainability into UX design, as this produces more scalable and future-proof software products. Index Terms—UX Design, Software Sustainability, Long-Term Viability, Technical Debt, Iterative Design, Minimalism, AI- Driven Personalization

Keywords: Costs , Production , Software systems , User experience , Maintenance , Iterative methods , Sustainable development , Usability , Artificial intelligence , Software development management

Research Title: Challenges and Benefits of Online Learning in Master's Programs: An Observational Qualitative Study

Author: Lamis Al-Qoran, Published Year: 2025

2025 16th International Conference on Information and Communication Systems (ICICS), Jordan University of Science and Technology

Faculty: Information Technology

Abstract: Online learning has become a popular learning model in the Jordanian higher education, especially during the COVID-19 pandemic. While numerous studies have investigated online learning effectiveness in various contexts, the unique challenges and benefits for master's students remain insufficiently studied. This study addresses this gap by exploring master's students' experiences with online learning, including emotional, technical, and management difficulties, as well as benefits such as flexibility, convenience, and skill development. We utilize a triangulated qualitative approach that combines observations, interviews, and a focus group approach. Thematic analysis was employed and it provided six themes, including fragmented learning, reliance on recorded lectures, work integrated learning, emotional isolation, time management, and transition anxiety. Our research provides recommendations to educators and educational institutions, such as having adaptive course structures, virtual peer communities to enhance the interaction between the students, and educators' training to address these challenges and optimize online learning for graduate students. These recommendations have the potential to help in improving the quality and effectiveness of online learning in master's programs. Therefore, our preliminary results pertain exclusively to the university and field of study, which restricts their relevance to other institutions or disciplines. Our future research will benefit from quantitative research to generalize our findings by expanding the sample size and including diverse set of learners.

Keywords: Online Learning , graduate students , Master's students , higher education

Research Title: Neural Network-Based Topography Prediction for Dam-Break Events

Author: Lamis Al-Qoran, Published Year: 2025

2025 16th International Conference on Information and Communication Systems (ICICS), Jordan University of Science and Technology

Faculty: Information Technology

Abstract: This study applies the shallow water equations to simulate dam-break events and predict both bed topography and Manning's roughness coefficient. A well-balanced finite volume method is used to generate a dataset that captures the complex flow dynamics of dam failures. This dataset is then utilized to train a neural network capable of predicting terrain changes and roughness distribution after the event. The performance of the model is assessed using Root Mean Square Error (RMSE) to ensure accurate predictions. The findings demonstrate that integrating computational hydraulics with neural networks can enhance the prediction of post-event topography and hydraulic roughness. This approach provides valuable insights for flood modeling, hydraulic engineering, and infrastructure planning, contributing to more effective risk assessment and decision making in real-world scenarios.

Keywords: Computational modeling , Neural networks , Hydraulic systems , Surfaces , Predictive models , Mathematical models , Planning , Computational efficiency , Floods

Research Title: Heart Failure Early Prediction Using Machine And Deep Learning Algorithm

Author: Lamis Al-Qoran, Published Year: 2025

Fusion: Practice and Applications (FPA), 18(1)

Faculty: Information Technology

Abstract: In this article, we use machine learning approaches to give a thorough investigation into the prediction of cardiac illnesses and strokes. The Stroke Prediction Dataset and the Heart Failure Prediction Dataset are the two datasets that we use. Our objective is to maximize accuracy and minimize Mean Absolute Error (MAE) and Mean Squared Error (MSE) in order to enhance predictive performance. We use a variety of machine learning methods, such as Random Forests, Naive Bayes, Decision Trees, and k-Nearest Neighbors (KNN). We also use Artificial Neural Networks (ANN) and Multi-Layer Perceptrons (MLP) as deep learning models. We use oversampling approaches to rectify the imbalance in classes. For hyperparameter tweaking, we also use Grid Search and k-Fold Cross Validation. Our goal is to deliver valuable insights into early detection and preventive measures through comprehensive testing and assessment for prevention of strokes and heart diseases.

Keywords: Heart Disease; Machine learning; Deep learning; Multi layer perceptron; Model evaluation

Research Title: Educators’ Perceptions on Artificial Intelligence in Higher Education: Insights from the Jordanian Higher Education

Author: Lamis Al-Qoran, Published Year: 2025

,

Faculty: Information Technology

Abstract: This paper investigates educators’ perceptions of the application of Artificial Intelligence in Higher Education (AIHEd) and its benefits and concerns within the Jordanian higher education. Like in other contexts, the adoption of Artificial Intelligence (AI) in the Jordanian higher education brought many benefits and a variety of concerns. Due to the lack of regulations and clear policies to cope with such new technologies, the increasing prevalence of these concerns has a negative impact on academic integrity. We used a sequential exploratory mixed approach to accomplish our study, which is guided by the Technology Acceptance Model (TAM), which helps in analysing the adoption of AI in higher education. Our approach involves conducting interviews with university educators from three different Jordanian universities. Interviews were done to identify educators’ thoughts regarding the responsibility of universities to adopt new AI technologies, what motivates them to use AI tools and services in their daily work, whether using AI in higher education institutions is legitimate, and the concerns associated with implementing such technologies into practice. Thus, the paper tries to portray the acceptable benefits and concerns of using AI in Jordanian higher education institutions. After conducting a thematic analysis on 18 interviews with educators, we identified 10 corresponding benefit themes and 8 corresponding concern themes that resulted from the coding and theme-building process. The average rate of educators’ responses to the themes of benefits and concerns is then determined by distributing a questionnaire to 145 higher education educators to generalise the results. Although our findings offer valuable insights, further investigation in wider contexts may be necessary to ensure the representativeness and generalisability of the findings. Through the themes that the study outlined, we concluded that although AI can transform the way students learn and educators work, there are still several issues that need to be resolved by researchers and teachers who work with associated application systems. Such issues require greater emphasis on appropriately and logically handling related ethical dilemmas. These concerns also highlight the importance of developing the necessary strategies and skills for responsible AIHEd. Using a mixed approach helped us to develop a strong understanding of the current state of AIHEd in the Jordanian context.

Keywords: Artificial Intelligence (AI), higher education, educators, perceptions, developing countries, Artificial Intelligence in Higher Education (AIHEd)