Selected aspects of the university social responsibility (USR) in Poland

Motivation: In accordance with the Law on Higher Education, the mission of the Polish education and science system is to provide top quality education and scientific activity, develop civic attitudes, and be involved in social development and creation of an innovation-based economy. The third mission of an academy focusing on social responsibility is to build mutual relations with the community in order to popularise and implement research results. In recent years, university social responsibility (USR) has turned into one of the priorities for Polish academic authorities, although research shows this to be a new matter in this area, which often leads to incorrect classification of activities resulting from regular obedience of the law as activities confirming the social responsibility of the organisation. Aim: The main objective of this article is to identify examples of socially responsible activity assumed by Polish academies and demonstrate the similarities with such activities conducted by other foreign academies. The author also wanted to associate the name of Professor Karol Adamiecki with social responsibility affairs what is usually overlooked in studies on this subject. Results: The conducted analyses confirmed that Polish academies are assuming socially responsible activity voluntarily and not just in order to fulfil the criterion of conformity with the currently effective laws. Furthermore, these results also confirm that — in comparison with academies abroad — the involvement of Polish academies in implementation of the concept of social responsibility is on the right path of development, although not as popularised, which only confirms the genuine and non-marketing approach to the matter of social responsibility.

Usage Experience and Capabilities of the VEGA-Science System

Currently, when satellite data volumes grow rapidly and exceed petabyte values and their quality provides reliable analysis of long-term time series, traditional data handling methods assuming local storage and processing may be impossible to implement for small or distributed research teams. Thus, new methods based on modern web technologies providing access to very large distributed data archives are gaining increasing importance. Furthermore, these new data handling solutions should provide not just access but also analysis and processing features, similar to desktop solutions. This paper describes the VEGA-Science web GIS—an open-access novel tool for satellite data processing and analysis. The overview of its architecture and basic technical components is given, but most attention is paid to examples of actual system application for various applied and research tasks. In addition, an overview of projects using the system is given to illustrate its versatility and further development directions are considered.

USE OF TOOLS AND SERVICES OF CLOUD-BASED SYSTEMS IN TEACHERS’ TRAINING AND PROFESSIONAL DEVELOPMENT: ASPECT OF AUGMENTED REALITY

The article reveals the aspect of using augmented reality (AR) as a means of a cloud-based open education and science system. Research methods: analysis, generalization, systematization of scientific-methodical sources on the research problem, analysis of cloud-based tools and services, determination of theoretical bases of teacher professional development on using cloud-oriented systems of open education and science. In the context of open science, the interest of scientists in the use of ICT during the period of the large-scale COVID-19 pandemic was analyzed and it was found that the number of publications in the areas of use of information and communication technologies, the introduction of distance learning, the development of information and communication and STEM competence has increased rapidly. The survey of lyceums teachers resulted that teachers chose three simple means for organizing distance learning, as well as the direct dependence in the choice of these means – digital analogs of full-time education (Zoom – lesson, Viber – diary, website – school announcements). The author considered the issue of the lack of high-quality digital content and the use of AR-objects, implemented using the MERGE Cube technology, in pedagogical practice. The cloud-based system of using MERGE Cube for learning is described, the stages of using MERGE Cube in the educational process, the criteria for the quality of AR-content (correspondence of virtual additions to the content of the lesson or the topic being studied; sound effects emphasize artistic or other meaning; video fragments demonstrate processes, events or video instructions by content; the process of playing AR objects is simple, intuitive; the process of playing AR is technically stable; the text font is dynamic; 3D images are clear; AR objects are reproduced in various operating systems). The author draws attention to the need to develop instructions and digital maps for the lesson. It was found that the key factor in the spread of AR technology in education is open access to educational content and the development of teachers’ relevant competencies.

PERBANDINGAN ALGORITMA KLASIFIKASI SUPPORT VECTOR MACHINE DAN NAIVE BAYES PADA IMBALANCE DATA

Question classification is a computer science system, which aims to analyze questions and can label each question based on existing categories. Questions can be collected from several materials or topics that are many and different. Therefore, the researcher intends to create a classification system for quiz questions Data Warehouse and Business Intelligence which can be grouped into topics Data Warehouse, Business Intelligence, Data Analytics, and Performance Measurement. One way to solve this problem is by approach machine learning. In this study, researchers used a comparison of machine learning algorithms, namely the algorithm NaïveBayes and SupportVectorMachine using SMOTE and methods Cross-Validation The results of this study show the best accuracy results and are very helpful. The results obtained in the method cross-validation before SMOTE resulted in an accuracy rate of 82.02% for the results after going through the SMOTE stage of 94.79% on the algorithm Naïve Bayes, while the algorithm SupportVectorMachine get accuracy of 81.39% in the process before SMOTE for the results after going through SMOTE of 96.52%. Keywords: Cross-Validation; Machine Learning; Naive Bayes; Support Vector Machine; Question Classification Abstrak: Klasifikasi pertanyaan merupakan sebuah sistem ilmu komputer, yang bertujuan untuk menganalisis pertanyaan serta dapat memberi label pada setiap pertanyaan berdasarkan kategori yang ada. Pertanyaan soal dapat dikumpulkan dari beberapa materi atau topik yang banyak dan berbeda. Oleh karena itu, bermaksud untuk membuat sistem klasifikasi pertanyaan soal kuis Data Warehouse dan Business Intelligence yang dapat dikelompokkan menjadi topik Data Warehouse, Business Intelligence, Data Analitik, dan Pengukuran Kinerja. Cara yang dapat dilakukan untuk permasalahan ini dengan menggunakan pendekatan MachineLearning. Pada penelitian kali ini menggunakan perbandingan algoritma MachineLearning yaitu algoritma NaïveBayes dan SupportVectorMachine menggunakan metode SMOTE dan Cross-Validation. Hasil penelitian ini menunjukkan hasil akurasi yang terbaik dan sangat membantu. Hasil yang diperoleh pada metode cross-validation sebelum SMOTE menghasilkan tingkat akurasi sebesar 82.02% untuk hasil sesudah melalui tahap SMOTE sebesar 94.79 % pada algoritma Naïve Bayes, sedangkan pada algoritma Support Vector Machine menghasilkan akurasi sebesar pada proses sebelum SMOTE 81.39% untuk hasil sesudah melalui SMOTE sebesar 96.52%. Kata kunci: Klasifikasi Pertanyaan; Pembelajaran Mesin; Naive Bayes; Support Vector Machine; Cross-Validation

Methodological sensitivities for co-producing knowledge through enduring trustful partnerships

Indigenous ways of caring for the environment have long been marginalised through research methodologies that are blind to a range of ways of knowing the world. Co-production of knowledge across Indigenous knowledge systems and Western scientific approaches is receiving attention both internationally and within the science system in Aotearoa New Zealand. Addressing power asymmetries as part of the co-production process is also slowly gaining recognition. Those involved in knowledge co-production initiatives must support learning about different world views, ways of knowing and accounting for the environment, while also enabling learning of the many biases and assumptions built into methodologies. This deliberation is needed, so non-Indigenous researchers can form enduring trustworthy partnerships and contribute to co-production initiatives. Presented here are insights shared by a cohort of environment research practitioners who have been deliberating on co-production occurring across knowledge systems in Aotearoa New Zealand. Originating from analysis of interviews undertaken about relationships recreational groups have with Te Urewera (forested hill country in the North Island of Aotearoa New Zealand), this paper depicts a layered reflection on how non-Māori (primarily but not exclusively) across Aotearoa New Zealand are learning to be manuhiri (those being welcomed on arrival to a place by the Indigenous people of that place). As a contribution to this collective learning, a set of methodological sensitivities are proposed as support for research amidst changing relationships with places. Doing so we aim to contribute to reflexive and decolonising encounters with Indigenous approaches to environmental care.

Impact of Intellectual Property Rights on the National Science System

After using the 2020 developments of the COVID-19 vaccines as an example of successful cooperation between academia, industry and government for supporting research and translating its results into innovations assisted by patents, the article turns to the national science systems. First, it addresses the pioneering role of the 1945 “Science the Endless Frontier”, the Magna Carta of American Science and its patent policy. Retraced are the subsequent US developments revealing a gradual turn from incentivizing knowledge and technology transfer from government funded institutions to industry by allowing it only in the form of non-exclusive licenses, to imposing the public research sector an obligation to commercialize its research results by allowing exclusive licenses and assignments of intellectual property rights to private business. This all by recognizing and preserving academic freedom and inquiry. Next, it pays attention to developments in countries where legislators followed overall the US model. Finally, the contribution discusses the intellectual property rights system in the light of the specific needs of academic researchers.

Difficulties in Advancement of Science and Shaping the System of Science and University as a Carrier of Technological Development in Bosnia and Herzegovina

The primary function of the university, in addition to education, is scientific research. At Bosnia and Herzegovina universities, the scientific research has been neglected. There are two basic reasons for that. The first is insufficient financial investment in science and research, and the second is an underdeveloped awareness of the importance of scientific research work, both in the society of Bosnia and Herzegovina and in universities themselves. This paper indicates what needs to be done to overcome this latter difficulty. In addition, the possibilities for improving science and shaping the science system at universities in Bosnia and Herzegovina to make them research universities were analysed. Scientific research work builds on research and development work, technological development, cooperation with the economy and the development of science and technology parks. These activities are even less represented at universities in Bosnia and Herzegovina than scientific research work. This paper shows the ways how to overcome these difficulties, so that research universities become carriers of the technological development of Bosnia and Herzegovina.

Influence of development of scientometrics on the outlook and functioning of the science system in the world and in individual countries

The social significance and quality of scientific research largely depend on the usefulness of research results for the social and scientific community. The lack of funds and the desire to allocate funding to high-quality research projects make the assessment of the quality of research and the valorization of knowledge increasingly important. However, it is very difficult to apply criteria that can objectively assess scientific research, providing precise qualitative and quantitative data on which funding agencies could base their decisions. The product of scientific research is mainly information published in scientific journals. They are the basis for the dissemination of knowledge and the basic criteria for academic and scientific evaluation, fundraising for scientific research and career advancement. In addition to the evaluation of scientific publications, there is a wide range of other activities that reflect the scientific credibility of scientists, such as: number and quality of grants for scientific research projects, leadership in national or international academic societies, membership in editorial boards of reputable journals, doctoral dissertation mentorships and the like. Although these activities are important and give credibility to the scientist, the relevant scientometric systems cover only publications, neglecting other criteria of scientific importance in evaluation for purpose of academic advancement of a scientist, as well as competitions for grants for financial support of scientific research. The reason for this is the fact that these activities, regardless of their importance, are very heterogeneous, with specific characteristics, and require very diverse parameters for evaluation. Therefore, there are no universal evaluation criteria for these activities and their quality is generally assessed individually, depending on the purpose of the assessment. Regardless of the shortcomings, university ranking systems are important comparative parameters for assessing the quality of scientific and educational value of universities.

Growth rates of modern science: a latent piecewise growth curve approach to model publication numbers from established and new literature databases

Growth of science is a prevalent issue in science of science studies. In recent years, two new bibliographic databases have been introduced, which can be used to study growth processes in science from centuries back: Dimensions from Digital Science and Microsoft Academic. In this study, we used publication data from these new databases and added publication data from two established databases (Web of Science from Clarivate Analytics and Scopus from Elsevier) to investigate scientific growth processes from the beginning of the modern science system until today. We estimated regression models that included simultaneously the publication counts from the four databases. The results of the unrestricted growth of science calculations show that the overall growth rate amounts to 4.10% with a doubling time of 17.3 years. As the comparison of various segmented regression models in the current study revealed, models with four or five segments fit the publication data best. We demonstrated that these segments with different growth rates can be interpreted very well, since they are related to either phases of economic (e.g., industrialization) and/or political developments (e.g., Second World War). In this study, we additionally analyzed scientific growth in two broad fields (Physical and Technical Sciences as well as Life Sciences) and the relationship of scientific and economic growth in UK. The comparison between the two fields revealed only slight differences. The comparison of the British economic and scientific growth rates showed that the economic growth rate is slightly lower than the scientific growth rate.