Author(s)
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Application
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Teaching
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(Faraj, 2022)
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AI can help students develop the skills of the future; being necessary that universities should implement AI in teaching to help students achieve their goals.
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(Ramallal et al., 2022)
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Information and communication technologies with artificial intelligence (ICT-IA), seen from the perspective of virtual training with artificial intelligence (VITI), are considered emerging tools with the potential to enrich teaching at all levels. From the perspective of university students, there is a willingness to incorporate these techniques in their autonomous learning.
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(Nikonova et al., 2023)
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The use of mobile applications in language teaching is advancing and showing effectiveness even without AI algorithms; however, it is suggested to use it in the educational systems of higher institutions; likewise, it seeks to increase collaboration among various experts to develop more advanced language learning systems.
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(Guan et al., 2021)
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The state of mind of teachers promotes academic level and teaching skills, based on the management of interactive environments with AI.
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Learning
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(Huang et al., 2022)
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The effectiveness of different AI-based self-regulated learning strategies was evaluated in a game-based learning environment; the results showed that these strategies can help higher education students to improve their academic achievements.
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(Ilić et al., 2021)
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In Serbian universities, AI and extended reality have been introduced as effective methodologies in higher education to encourage analytical learning and increased student engagement during the educational process.
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(Li et al., 2021)
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The application of an artificial intelligence-based higher education system, student model, teacher model, teaching strategy and intelligent teaching inference engine are essential components that need to be analyzed in detail to guarantee effective learning.
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(Walczak & Cellary, 2023)
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Universities must prepare students for continuous learning in an constantly changing world and AI can help, but academic experts are still needed to validate knowledge.
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(Kelly et al., 2023)
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The generative artificial intelligence tools are transforming higher education, but it is important to use them ethically and in a responsible way to ensure the academic integrity of students.
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(Chaudhry et al., 2023)
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The implementation of AI through ChatGPT in education has the potential to improve the learning and academic performance of higher education students.
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(Wang, 2023)
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AI can help students learn languages in a personalized and collaborative way, allowing them to develop their language skills more effectively.
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(Currie et al., 2023)
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AI through GPT3.5, has limited capability to assist medical imaging students in writing, because it lacks deep knowledge, breadth of research and currency of information; however, there are several useful applications of ChatGPT that could be adopted to enrich students learning in medical imaging.
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(Nazari et al., 2021)
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The application of the artificial intelligence-driven Grammaly tool improves graduate students self-efficacy, engagement, and emotions in learning English language academic writing.
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(Yang et al., 2023)
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The application of gamified AI educational robots (AIER) has been shown significant improvements in student performance and motivation; these systems, such as the gamified artificial intelligence educational robot (GAIER), simulate virtual teachers, interact with students providing personalized information, assessment and feedback during learning; they reduce the cognitive load of the educational process.
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(Ananthi & Arul, 2023)
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Using the Random Forest method supported by the XGBoost algorithm, it has a greater influence on the final performance, offering a higher accuracy at 93%; also, students believe that online learning is more effective when each student receives the lecture, regardless of the number of students present in the virtual classroom.
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(Elkhodr et al., 2023)
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Undergraduate and graduate ICT students saw ChatGPT as a valuable and attractive tool for learning, showing much interest in employing AI, such as ChatGPT, in their future studies; they also showed better results in functionality, fluency of use, hierarchy of content and information compared to those who used search engines.
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(Al-Abdullatif et al., 2023)
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The positive influence of the Bashayer chatbot system, as an artificial intelligence-based tool, to enhance learning motivation and support cognitive and metacognitive learning strategies among graduate students.
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(Alqahtani, 2023)
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The application of AI through automatic learning makes it possible to make learning in electronic environments more flexible so that students have experience in handling topics related to entrepreneurship and business start-ups.
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(Wang et al., 2022)
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Believed that student-centered content design, use of tools and teaching strategies based on visual programming, can help students learn AI concepts without constraints of programming syntax, questions, and practical learning tasks, more easily.
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(Zhu & Ren, 2022)
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AI plays a role in the cognition of the education system, because course learning is related to the understanding of course content and teaching methods; therefore, teachers are limited by the degree of students' understanding, the amount of resources and data processing capabilities.
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Teaching - Learning
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(Leoste et al., 2021)
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Emerging technologies (ET) have the potential to transform teachers' teaching and students' learning; however, teachers' unfamiliarity with ET also poses challenges, such as the need for training and support for effective implementation.
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(Kuleto et al., 2021)
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AI can provide individualized learning experiences for students, and professors have the opportunity to adapt their teaching methods and strategies to meet those needs; therefore, higher education institutions can adopt a machine learning-centered approach as a way to promote the use of AI.
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(Chiu, 2023)
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Teachers must be willing to co-learn with students in the classroom, the higher learners have the facility to teach and develop higher learning using generative AI.
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(Essel et al., 2022)
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The use of chatbot (artificial intelligence) in education generated high student satisfaction by providing instant feedback without delay, generating a positive change in the teaching, and learning process, improving student performance and self-efficacy.
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(Bucea-Manea-Țoniş et al., 2022)
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AI will allow personalizing the learning process, identifying the best materials, contributing significantly in teaching; AI also helps to search for materials and content, make fewer mistakes, create learning plans and provide better information from the students to the teacher.
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(McGrath et al., 2023)
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University professors showed low levels of understanding about AI, being necessary more training in AI technologies to use them in teaching; however, a good percentage thought that AI could serve as a support for students.
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(Kelly et al., 2023)
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In the current university context, an ethical approach is required in the use of generative artificial intelligence (GenIA) in academic activity and student learning; in its practice, teaching and evaluation must be flexible in the integration of these tools, considering the benefits and limitations.
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Educational Management
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(Quy et al., 2023)
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Digital transformation with AI is an inevitable trend in higher education, but it requires effort on the part of institutions to overcome legal, technological and organizational challenges.
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(Grabińska et al., 2021)
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Artificial intelligence can transform the finance and accounting professions; forcing universities to adapt their curriculum and teaching methods, promoting the development of new skills to succeed in the future.
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(Benhayoun-Sadafiyine & Lang, 2021)
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Higher education is responding to the emerging needs of the labor market in terms of the use of AI, in relation to technical, interdisciplinary, and interpersonal skills; therefore, academic training in AI must be aligned with the needs of the market and provide teachers with an overview of the skills to be achieved as learning outcomes in their subjects.
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(Ouyang et al., 2023)
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The proposal for an integrated approach combining AI performance prediction and feedback to promote personalized learning and the implications between AI model development and educational application.
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(Almaraz-López et al., 2023)
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Student interest in AI is growing because it will continue having an increased impact on personal and professional life, being necessary to provide AI training to university students of all disciplines, in order to use them in a safe and responsible way.
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(Wang et al., 2021)
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U.S. universities established AI decision systems to help solve complex decision-making problems, setting up a communication platform to exchange opinions on academic issues and establishing an evaluation system for professors to participate in the critical decision-making process of universities.
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(Gupta & Mishra, 2022)
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For predictive analytics models to be successful, they must have large samples and must involve teacher participation, coupled with classroom management and exhibition participation, act as predictors of student academic performance.
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(Tominc & Rožman, 2023)
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The document proposes practical guidelines for educators, focused on boosting students’ preparedness for AI, emphasizing the importance of strengthening awareness and knowledge about it, adapting curriculum to integrate relevant skills, essential in today's job landscape.
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(Marchante, 2022)
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Those in charge (authorities) of university institutions make the decision to invest in intelligent tutoring systems, technologies, and AI, which promote digital training for teachers and students, overcoming their own barriers and seeing a different future.
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(Jiao et al., 2022)
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The artificial intelligence-based quantitative prediction model can be used to assess and predict learning performance, through knowledge acquisition, class participation, and summative performance in online engineering education.
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(Chiu, 2023)
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The curriculum should be reformulated in initial teacher training, incorporating generative AI in the classroom, being a new literacy for teacher education.
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(Romero-Rodríguez et al., 2023)
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The acceptance of ChatGPT artificial intelligence by university students provides relevant information for faculty to make decisions and redesign their teaching and training; it also has implications for the learning process, research, and educational practice in higher education.
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(Rezapour & Elmshaeuser, 2022)
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Universities should focus on providing face-to-face and synchronous classes supported with asynchronous components to facilitate healthy learning for students, as well as working on the financial aspect of the students to avoid economic stress for them.
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(Afzaal et al., 2023)
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The algorithm-based approach (dashboard) provided advance information on students' progress and performance, which allowed planning and monitoring students' studies, providing information on learning achievements, self-regulated learning skills and positively affected students’ performance.
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(Subirats et al., 2023)
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It was possible to determine student profiles, those who study continuously, at the end and low performance, with artificial intelligence; in all of them different learning strategies applied before and after confinement were used, they were very relevant to change the habits of the students, proposing gamification strategies for being motivating and of continuous use.
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(Martín-Núñez et al., 2023)
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The acceptance of ChatGPT artificial intelligence by university students provides relevant information for faculty to make decisions and rethink their teaching and training; it also has implications for the learning process, research, and educational practice in higher education.
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(Mahmmod et al., 2022)
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The proposed model seeks to identify and analyze the factors that affect the academic performance of students through the use of AI, being the desire of academic organizations to improve the academic performance of their students through the use of AI.
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(Ilieva et al., 2023)
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An analysis of the influence of intelligent chatbots in university education reveals that many students recognize their educational potential and have employed them. This experience generated solid interest in their continued use, particularly among those who better understand their benefits.
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(Ruiz-Rojas et al., 2023)
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It highlights the relevance of using generative AI tools and instructional design arrays to improve virtual classrooms and enrich the learning process. This implies personalization adapted to each student, greater motivation and engagement, content automation, efficiency in the management and organization of material, coherent planning of activities and a clear structure for educational design.
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(Sanabria-Z et al., 2023)
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The fusion of physical (Ideathon) and digital (Transition Design) environments offers a route to investigate hybrid achievements in pedagogy in an agile and competitive manner. Proof of concept with AI to assess complex thinking can be applied to diverse areas and integrated into learning management systems (LMS).
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(Saadé et al., 2023)
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Higher education teachers make limited use of the Internet of Things (IoT) in their personal lives, and few apply it in teaching. This highlights the need to develop their continuous training in IoT and AI through institutional policies that provide financial support and services. In addition, it is crucial to educate about IoT concepts, sensors, and potential applications in order to effectively integrate it into teaching practice.
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(Akiba & Fraboni, 2023)
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Academic advisors could leverage generative AI tools, such as ChatGPT, during advising to verify critical data; this intelligence has been shown to offer a wide range of balanced considerations when addressing professional challenges of elementary school teachers, which could benefit human advisors.
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(Rahman, 2022)
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The findings highlight relevant institutional challenges and student concerns, such as the expansion of information technology infrastructure geographically is important for country-wide and universal connectivity, technical training programs are needed to improve confidence in tools, and a government budget review is needed to strengthen digital infrastructure in higher education.
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(Çetinkaya et al., 2023)
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The most effective method for producing superior results is the cubic support vector machine (SVM) and it holds great potential for accurately predicting the programming aptitude of students at this level of education; the results can motivate educators and parents to push students towards careers in programming, for example if a student has no experience and excels in the spatial test, used here to predict programming skills, it is recommended to encourage their interest in this career area.
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(Chan, 2023)
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It proposes a policy framework for AI ecological education for integration in university environments, including three key dimensions: pedagogy, governance, and operability, that ensure the responsible and ethical incorporation of AI in university education and maximizing its benefits.
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(Koć-Januchta et al., 2022)
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The study highlights that books enriched with AI facilitate more meaningful learning with less mental effort, because they require fewer resources and are positively linked to cognitive strategies, usability, and access to additional information, promoting deep learning and curiosity.
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(Mohd et al., 2022)
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With chatbots, we looked for the development of a new model that would allow users to ask frequently asked questions about academic and university topics, the results of which can be used in the administrative field and in customer service.
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(Bamatraf et al., 2021)
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It is evident that there are considerable ethical concerns about the social implications that AI may generate, in terms of job losses and labor changes in Saudi Arabia.
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(Parapadakis, 2020)
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In education you can have detectable patterns of behavior, the same ones that can aid decision making and the best decisions can produce benefits for students; the successes of AI in industry can help in a variety of problem areas in education, providing some useful insights, but they cannot support algorithmic accountable decision making.
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(Artiles-Rodríguez et al., 2021)
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The use of conversational virtual agents as a tool for tutoring university student work, the data reveals a high student satisfaction with the use of Chatbots, the experience has been remarkable for students.
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Research
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(Albasalah et al., 2022)
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It was determined that there is a very strong correlation between the objectives of collaborative scientific research between professors and university students of health sciences and humanities in university centers.
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(Samuel, Chubb, et al., 2021)
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In higher education institutions, the academics suggest that ethics in this research should be based on public health, focusing on justice, population well-being and equity rather than just protecting individuals from possible research risks.
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(Samuel, Diedericks, et al., 2021)
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It has been shown that research can be hindered by interested parts to whom the research is disseminated and less interested in listening to scientific practice, which can have implications for the social responsibility of research and the political environment.
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