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关键词： education   interprofessional collaboration   computer science   health sciences   higher education  

摘要： In the digital age of health, health professionals face the major challenge of adapting to rapidly evolving digital technologies. Interprofessional collaboration (IPC) and communication are essential skills to use the potential of a digital health system and project work in Creative Labs, especially regarding high-risk projects that bring together professionals from different backgrounds for the common goal of developing innovative concepts and products. So far, too little interprofessional competence acquisition is offered at universities. In this article, we present a joint teaching program in which students of computer science and health sciences design and develop digital health projects in joint project work. The teaching program consists of different phases, including thematic basics, accompanying identification of ideas for the project work, working sessions, and final presentation of the digital health projects. We also present the teaching concept, as well as the piloting of the program and the results of its evaluation. The results point to the high potential that can unfold in IPC teaching and how important it is for future healthcare professionals to be adaptable to new technologies and IPC. Practical recommendations include considerations for joint teaching, module structure, and a brief discussion of challenges on an organizational level.

关键词： Machine learning   Computer science   Industry  

摘要： Stanford University’s 2024 AI Index charts the meteoric rise of artificial-intelligence tools.

关键词： creative labs   computer science education   educational strategies   interdisciplinary learning  

摘要： Creative labs play a crucial role in transforming computer science education by fostering interdisciplinary, project-based learning that bridges theory and real-world applications. Focusing on the *** within Hamburg's *** Network of Labs, this study highlights how such labs address the limitations of traditional curricula. Students are encouraged to explore innovative solutions with the freedom to fail, viewing setbacks as valuable learning steps. By integrating diverse academic and societal perspectives, creative labs prepare future computer scientists to handle complex, multidisciplinary challenges. The article emphasizes educational strategies and practices that support open-ended, exploratory learning, making creative labs pivotal in the progression of computer science education.

关键词： Reliability analysis  

摘要： Artificial Intelligence (AI), with ChatGPT as a prominent example, has recently taken center stage in various domains including higher education, particularly in Computer Science and Engineering (CSE). The AI revolution brings both convenience and controversy, offering substantial benefits while lacking formal guidance on their application. The primary objective of this work is to comprehensively analyze the pedagogical potential of ChatGPT in CSE education, understanding its strengths and limitations from the perspectives of educators and learners. We employ a systematic approach, creating a diverse range of educational practice problems within CSE field, focusing on various subjects such as data science, programming, AI, machine learning, networks, and more. According to our examinations, certain question types, like conceptual knowledge queries, typically do not pose significant challenges to ChatGPT, and thus, are excluded from our analysis. Alternatively, we focus our efforts on developing more in-depth and personalized questions and project-based tasks. These questions are presented to ChatGPT, followed by interactions to assess its effectiveness in delivering complete and meaningful responses. To this end, we propose a comprehensive five-factor reliability analysis framework to evaluate the responses. This assessment aims to identify when ChatGPT excels and when it faces challenges. Our study concludes with a correlation analysis, delving into the relationships among subjects, task types, and limiting factors. This analysis offers valuable insights to enhance ChatGPT’s utility in CSE education, providing guidance to educators and students regarding its reliability and efficacy. Copyright © 2024, The Authors. All rights reserved.

关键词： Students  

摘要： Researchers in the CSCW community have long problematized the separation of social and ethical considerations from design work. Despite increasing attention to tech ethics and ethics education, however, computer scientists' sense of ethical responsibility remains of concern. This paper offers insights on how this boundary between tech and ethics is maintained and reinforced for students as they develop their identities as computer scientists. Drawing on interviews with eight undergraduate computer science (CS) students at McGill University, we explore the role that ethics play in the legitimate peripheral participation of students inside and outside their formal education. We found that while individual opinions on the importance of ethics varied, students agreed that ethics are not valued or rewarded in their education, extracurriculars, or future work prospects. We describe how placing ethics outside the boundary of computing acts as a form of occupational closure, excluding both important multidisciplinary work and marginalized bodies. We argue that in order to promote ethical practice in the design of CSCW systems, we must make it in the interest of future designers to learn socially grounded ethics. This requires that designers, researchers, and future employers actively reshape the boundaries of computing by asserting social and ethical considerations as values of computing and design. © 2024 Copyright held by the owner/author(s).

关键词： Behavioral difficulties   Strength and difficulties questionnaire   WHO quality of life questionnaire   Syrian crises   Syrian children  

摘要： Childhood and adolescence, vital in shaping adult life and society, are profoundly impacted during conflicts like Syria's devastating war. This study explores the prevalence of behavioral disorders in Syrian children and adolescents, examining the influence of war and family-related factors. This cross-sectional study was conducted on children aged 2-17 years at a children's outpatient clinic in Damascus, Syria. We assessed parents' quality of life, war and family-related factors, and behavioral difficulties through parental interviews using two questionnaires: the Arabic version of the Strengths & Difficulties Questionnaire (SDQ) and the brief Arabic version of the World Health Organization Quality of Life Questionnaire (WHOQOL-BREF). 74.67% of children aged 2-4 years and 61.29% of children aged 5-17 years were experiencing behavioral difficulties, with emotional difficulties being the most prevalent ones. Children exposed to kidnapping, family losses, lack of school enrollment, and those with parents having lower education, lower socioeconomic status, and poorer quality of life exhibited higher Total SDQ scores. The high prevalence of behavioral difficulties among children and adolescents in Syria is a major concern, with both direct and indirect war-related factors contributing to this issue.

关键词： Students  

摘要： The integration of AI assistants, especially through the development of Large Language Models (LLMs), into computer science education has sparked significant debate, highlighting both their potential to augment student learning and the risks associated with their misuse. An emerging body of work has looked into using LLMs in education, primarily focusing on evaluating the performance of existing models or conducting short-term human subject studies. However, very little work has examined the impacts of LLM-powered assistants on students in entry-level programming courses, particularly in real-world contexts and over extended periods. To address this research gap, we conducted a semester-long, between-subjects study with 50 students using CodeTutor, an LLM-powered assistant developed by our research team. Our study results show that students who used CodeTutor (the "CodeTutor group" as the experimental group) achieved statistically significant improvements in their final scores compared to peers who did not use the tool (the "control group"). Within the CodeTutor group, those without prior experience with LLM-powered tools demonstrated significantly greater performance gain than their counterparts. We also found that students expressed positive feedback regarding CodeTutor’s capability to comprehend their queries and assist in learning programming language syntax. However, they had concerns about CodeTutor’s limited role in developing critical thinking skills. Over the course of the semester, students’ agreement with CodeTutor’s suggestions decreased, with a growing preference for support from traditional human teaching assistants. Our findings also show that students turned to CodeTutor for different tasks, including programming task completion, syntax comprehension, and debugging, particularly seeking help for programming assignments. Our analysis further reveals that the quality of user prompts was significantly correlated with CodeTutor’s response effectiveness.

关键词： Health sciences   Natural sciences   Computer science  

摘要： With advancements in large language models, artificial intelligence (AI) is undergoing a paradigm shift where AI models can be repurposed with minimal effort across various downstream tasks. This provides great promise in learning generally useful representations from biomedical corpora, at scale, which would empower AI solutions in healthcare and biomedical research. Nonetheless, our understanding of how they work, when they fail, and what they are capable of remains underexplored due to their emergent properties. Consequently, there is a need to comprehensively examine the use of language models in biomedicine. This review aims to summarize existing studies of language models in biomedicine and identify topics ripe for future research, along with the technical and analytical challenges w.r.t. interpretability. We expect this review to help researchers and practitioners better understand the landscape of language models in biomedicine and what methods are available to enhance the interpretability of their models.

关键词： Physics   Biological sciences   Computer science  

摘要： Cell therapy using proliferating human hepatocytes (ProliHHs) is an effective treatment approach for advanced liver diseases. However, rapid and accurate identification of high -quality ProliHHs from different donors is challenging due to individual heterogeneity. Here, we developed a machine learning framework to integrate single -cell Raman spectroscopy from multiple donors and identify different stages of ProliHHs. A repository of more than 14,000 Raman spectra, consisting of primary human hepatocytes (PHHs) and different passages of ProliHHs from six donors, was generated. Using a sliding window algorithm, potential biomarkers distinguishing the different cell stages were identified through differential analysis. Leveraging machine learning models, accurate classification of cell stages was achieved in both within -donor and cross -donor prediction tasks. Furthermore, the study assessed the relationship between donor and cell numbers and its impact on prediction accuracy, facilitating improved quality control design. A similar workflow can also be extended to encompass other cell types.