Музыка, математика и информатика: особенности функционирования музыкально-компьютерных технологий

On 28-29 April 2000, the Board on Mathematical Sciences and the Computer Science and Telecommunications Board of the National Research Council cosponsored a workshop on the interface between the mathematical sciences and three areas of computer science: network traffic modeling, computer vision, and data mining. The workshop's goal was to identify some open research questions in the mathematical sciences whose solutions could contribute to important unsolved problems in those computer science disciplines. The 48 participants engaged in lively discussions and identified at least 36 research challenges of a mathematical, statistical, or probabilistic nature.

In the first years of the 21st century a lot of educative innovation has been developed. One of the most relevant innovations for higher education institutions are the Massive Open On-line Courses (MOOC). In the field of Computer and Information Sciences, a lot of MOOC have been performed. In this paper we analyze the courses that are available in Coursera, one of the most popular platforms for delivering MOOC. Our intention is to assess to which extent the subjects suggested for the careers of Computer and Information Sciences are covered by the courses in Coursera. Despite the fact that are many courses in certain subjects, our results show that some subjects are not very well covered. Another conclusion that can be elicited from our analysis is that there are strong relationships among the courses that are available in Coursera. Key Words Massive Open On-line Courses (MOOC), Distance education, Computer Science.

Assalamu’alaikum Wr. Wb. and Greetings.I am pleased and honored to welcome you at the First International Conference on Computer Science and Applied Mathematic (ICCSAM 2018), which was held this year by AMIK and STIKOM Tunas Bangsa Pematangsiantar in collaboration with the Indonesian Computer and Information Professional Association (IPKIN), Indonesian Mathematical Society (INDOMS) and Bank Muamalat. As Chair of the Foundation, I would like to convey a greeting Welcome to Parapat City Lake Toba to presenters from various countries and especially those I respect for the presence of scientists in the field of Computer and Mathematical Sciences and industry practitioners in the 2018 ICCSAM event.I see that this activity is designed to enhance the exchange of knowledge and new discoveries in computer science and mathematics and related fields in industry. I hope that scientists in the field of computer science and mathematics and those who work in the industry can share knowledge and work together as a team that has mutual relations with each other. I am very pleased to say that the theme of this conference, “Advancing Computability Innovation” is very much in line with the objectives of AMIK and STIKOM conferences and missions, namely “to become a Science and Technology based Study Program that meets industrial needs and functions as a research center in Information Data Science. The conference was held in response to output and aoutcame which had a significant contribution in the field of computer science and mathematics as an inseparable unit of science towards the development of local and global industries. It is our happiness and honor to welcome distinguished professors present to convey their expertise at this conference.I hope this meeting will enable the development of productive dialogue between participants from various countries. They also provide invaluable opportunities for networking among participants, institutions and industries. I also hope that diversity in these fields can reveal more opportunities for researchers and practitioners from all over the world to start a lot of research related to the industry in the future.I would like to congratulate AMIK and STIKOM Tunas Bangsa for starting this conference with a synergistic contribution from dedicated partners namely the USU Faculty of Mathematics and Natural Sciences, USU’s Faculty of Computer and Information Technology, the Indonesian Computer and Informatics Professional Association (IPKIN), Indonesian Mathematical Society (INDOMS), Bank Muamalat, Malaysia Pahang University (UMP), University of Essex, United Kingdom, Ankara, Turkey and Institute of Applied Mathematics Middle East Technical University to all delegates for their full support, cooperation and contribution to the 2018 ICCSAM. I also want to thank the Organizing Committee for their perseverance and extraordinary efforts. Various sponsors are also rewarded for their contributions. I really hope that all participants will get a pleasant stay here at NIAGARA HOTEL and bring back unforgettable experiences and valuable knowledge from this conference.Thanks.H. Ahmad Ridwansyah Putra

In this paper, we propose a calibration estimator of population mean in stratified sampling using the known mean and variance information from multi-auxiliary variables. The problem of determining the optimum calibrated weights is formulated as a Nonlinear Programming Problem (NLPP) that is solved using the Lagrange multiplier technique. Numerical example with real data is presented to illustrate the computational details of the proposed estimator. A comparison study is also carried out using real and simulated data to evaluate the performance and the usefulness of the proposed estimator. The study reveals that the proposed estimator with multi-auxiliary information is more efficient estimator of the population mean as it provides least estimated variance and highest gain in relative efficiency (RE). References Jean Claude Deville and Carl Erik Sarndal. Calibration estimators in survey sampling. Journal of the American statistical Association, 87(418):376–382, 1992. doi:10.1080/01621459.1992.10475217 . Victor M Estevao and Carl Erik Sarndal. Survey estimates by calibration on complex auxiliary information. International Statistical Review, 74(2):127–147, 2006. doi:110.1111/j.1751-5823.2006.tb00165.x Patrick J Farrell and Sarjinder Singh. Model-assisted higher-order calibration of estimators of variance. Australian and New Zealand Journal of Statistics, 47(3):375–383, 2005. doi:10.1111/j.1467-842X.2005.00402.x Wolfram Research, Inc. Mathematica, Version 11.3. Champaign, IL, 2018. Jong Min Kim, Engin A Sungur, and Tae Young Heo. Calibration approach estimators in stratified sampling. Statistics and probability letters, 77(1):99–103, 2007. doi:10.1016/j.spl.2006.05.015 Phillip S Kott. Using calibration weighting to adjust for nonresponse and coverage errors. Survey Methodology, 32(2):133, 2006. Dinesh K Rao. Mathematical programing in stratified random sampling. PhD thesis, School of Computing, Information and Mathematical Sciences, The University of the South Pacific, Fiji, February 2017. Dinesh K. Rao, Tokaua. Tekabu, and Mohammad G M Khan. New calibration estimators in stratified sampling. In Proceedings of Asia-Pacific World Congress on Computer Science and Engineering, pages 66–70. IEEE, 2016. Gurmindar K Singh, Dinesh K Rao, and Mohammed GM Khan. Calibration estimator of population mean in stratified random sampling. In Proceedings of Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE), pages 1–5. IEEE, 2014. Sarjindar Singh, Stephen Horn, and Frank Yu. Estimation of variance of general regression estimator: Higher level calibration approach. Survey Methodology, 24:41–50, 1998. Sarjinder Singh. Advanced Sampling Theory With Applications: How Michael Selected Amy, volume I and II. Kluwer Academic Publishers, Netherlands, 2003. Sarjinder Singh. On the calibration of design weights using a displacement function. Metrika, 75(1):85–107, 2012. doi:10.1007/s00184-010-0316-6 Sarjinder Singh, Stephen Horn, Sadeq Chowdhury, and Frank Yu. Theory and methods: Calibration of the estimators of variance. Australian and New Zealand Journal of Statistics, 41(2):199–212, 1999. doi:10.1111/1467-842X.00074 D S Tracy, S Singh, and R Arnab. Note on calibration in stratified and double sampling. Survey Methodology, 29(1):99–104, 2003. Changbao Wu and Randy R Sitter. A model-calibration approach to using complete auxiliary information from survey data. Journal of the American Statistical Association, 96(453):185–193, 2001. doi:10.1198/016214501750333054

Computational Physics holds a pivotal position in interdisciplinary research spanning Mathematics, Astrophysics, and Computational Science, offering solutions to intricate problems.Employing numerical analysis, computational physics harnesses programs and algorithms written in scientific languages like FORTRAN, C/C++, to tackle advanced research challenges.Through computational techniques, we can visualize complex phenomena such as the wave function of particles in a confined space (e. g. , particle in a box problem) or the wave function of a Harmonic Oscillator. Additionally, we can model the trajectories of satellites. These methodologies extend beyond visualization, serving simulation purposes for complex research issues in space exploration. Computational physics significantly contributes to advancing research in mathematical sciences and space exploration, whether theoretical or experimental in nature. This paper delves into the multifaceted applications of computational techniques across various research domains.

The article discusses the problem of teaching computer science, mathematics and logic in modern education, in particular, in a secondary general education school as inherited from the problems of the existing relationships between the sciences of computer science and mathematics, as well as generated by the prevailing forms and practice of teaching in the system of general education. The methodological aspects of teaching computer science, mathematics and logic are considered inherent in them and applied to them in a differentiated form: - a meaningful approach inherent in computer science and applied in mathematics and logic; - a formal approach inherent in mathematics and used in computer science and logic; - a socio-cultural approach characteristic of the triad ”computer science-mathematics-logic”. Against the background of the existing correspondence of the selected approaches (or the measure of this correspondence) to each local and independent element of the triad, it is assumed that there is an identification of the regular relations between the subject and the subject of education, the principles of organizing the processes of implementing methodological knowledge based on these regularities. For our study, it is important that the methodology and methodology of each differentiated system of the triad should contain everything that is ”necessary and sufficient” for the functioning of the educational system of the corresponding level. In this aspect, the article notes that mathematics studies form, computer science - form and content. The study of objects only in form leads to formalism in the information sphere (which is unacceptable), therefore, possible integration must be combined with the necessary differentiation. Since the processes of the development of knowledge of science, its methodology and teachingmethods are interrelated and interdependent, it is unconditionally interesting to reveal the potential (possibilities) of intersubject and metasubject connections and relations of the triad under consideration as close, but not homogeneous educational systems that have their own subject. specificity of the content, methods and forms of training. In this perspective, possible ways of solving the problems that have arisen are proposed in the context of changes in the school curricula of the content of information and mathematics education under the influence of the requirements of the new federal state educational standards and the structure of subject teaching in computer science and mathematics, ensuring their efficiency and effectiveness.

Geographical AnalysisVolume 8, Issue 1 p. 77-93 Free Access Surface Networks John L. Pfaltz, John L. Pfaltz This research was supported in part by National Science Foundation Grant DCR-74–13353. John L. Pfaltz is associate professor, Department of Applied Mathematics and Computer Science, University of Virginia.Search for more papers by this author John L. Pfaltz, John L. Pfaltz This research was supported in part by National Science Foundation Grant DCR-74–13353. John L. Pfaltz is associate professor, Department of Applied Mathematics and Computer Science, University of Virginia.Search for more papers by this author First published: January 1976 https://doi.org/10.1111/j.1538-4632.1976.tb00530.xCitations: 66 John L. Pfaltz is associate professor, Department of Applied Mathematics and Computer Science, University of Virginia. This research was supported in part by National Science Foundation Grant DCR-74–13353. AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume8, Issue1January 1976Pages 77-93 ReferencesRelatedInformation

Note from the EditorsToo often, biology has been considered by both students and faculty as the ideal major for the scientifically inclined but mathematically challenged, even though the advantage of quantitative approaches in biology has always been apparent.Increasingly, biologists are utilizing mathematical skills to create simulations or manage and query large data sets.The need for basic mathematical and computer science (CS) literacy among biologists has never been greater.But does this require a fundamental change in the organization of the undergraduate biology curriculum?What is the utility of math/CS in different areas of biology?How can we best provide math/CS instruction to biologists so that the utility is appreciated?Do all biology students require a stronger math/CS foundation, or only those interested in research careers?Given the speed at which technology changes, what is the best preparation?Three different points of view are offered below.Dr. Roger Brent, President and Director of the Molecular Sciences Institute, reflects on the "innumeracy" common among biologists and argues that significant insights into biological problems may be gained from better mathematical intuition.

∗Department of Mathematics, Statistics, and Computer Science, St. Olaf College, Northfield, MN 55057 (berliner@stolaf.edu), (coxn@stolaf.edu). Research of N. Cox supported by NSF DMS 0750986 †Department of Mathematics, Carleton College, Northfield, MN 55057 (brownc@carleton.edu). Research supported by NSF DMS 0750986. ‡Department of Mathematics, Iowa State University, Ames, IA 50011 (jmsdg7@iastate.edu), (warnberg@iastate.edu), (myoung@iastate.edu). Research of J. Carlson supported by ISU Holl funds. Research of M. Young supported by NSF DMS 0946431. §Department of Mathematics, Iowa State University, Ames, IA 50011, (lhogben@iastate.edu) and American Institute of Mathematics, 360 Portage Ave, Palo Alto, CA 94306 (hogben@aimath.org). ¶Department of Mathematics, University of California, Berkeley, CA 94720-3840 (jason.hu@berkeley.edu). Research supported by NSF DMS 0750986. ‖Department of Mathematics, Pomona College, 610 North College Avenue, Claremont, CA 91711 (klj02011@mymail.pomona.edu). Research supported by NSF DMS 0750986. ∗∗Department of Mathematics and Computer Science, Central College, Pella, IA 50219 (manternachk1@central.edu). Research supported by ISU Holl funds. ††Natural and Mathematical Science Division, Culver-Stockton College, Canton, MO 63435 (tpeters319@gmail.com).

Purpose of research. The purpose of the paper is to describe the possibilities of including tasks for the design, development, use and experimental evaluation of “inverted” educational resources in the professional training of future teachers of mathematics and computer science for the development of their subject-methodical readiness. The formation and development of subject-methodical readiness is the main goal of professional training of future lecturers at a pedagogical university. The process of creating “inverted” educational resources requires from their author quite serious subject and methodological training. Potentially, the inclusion of tasks for the design, development, expertise, practical use and evaluation of “inverted” educational resources in the professional training of future teachers of mathematics and computer science can create conditions conducive to the formation of competencies of future teachers to create a comprehensive educational process in a digital environment. Since, on the one hand, in such didactic means, the educational content should be presented systematized and structured, have logic and hierarchical connections. On the other hand, the problematic issues included in the resources should reflect specific subject educational results in accordance with a given taxonomic model in the curriculum.Materials and methods. Based on the analysis of theoretical and methodological sources, the article substantiates the relevance of the problem of finding new ways and means of implementing additional subject training in mathematics and computer science for both schoolchildren and future teachers in the context of digitalization of education. The analysis of examples of “inverted” educational resources, which are the results of the implementation of project tasks by undergraduate students of the Krasnoyarsk State Pedagogical University named after V.P. Astafiev, is presented. Through theoretical and methodological substantiation, the main possibilities of including tasks for working with such resources at different stages of professional training of future teachers of mathematics and computer science at a pedagogical university are synthesized.Results. In this study, the problems related to the possibility of including “inverted” educational resources as digital didactic tools in the training programs of future teachers of mathematics and computer science were updated. The authors’ position on the issue of the purpose of such teaching tools in the context of the digitalization of education is presented and substantiated. Examples of the results of the implementation of project tasks by senior students during the 2021-2022 academic year were demonstrated. The key didactic and information technology features, possible tools for creating “inverted” educational resources are given. The definition of the subject-methodical readiness of the future teacher of mathematics and computer science as an essential component of professional readiness is concretized. The possibilities of strengthening subject-methodical training by including tasks for work with “inverted” educational resources are described: analytical – in junior courses when mastering disciplines related to the use of digital technologies in education; project – in the middle courses when mastering methodological disciplines; experimental and expert - in the senior courses when passing industrial (pedagogical) practice and mastering the final disciplines of the professional educational program of higher pedagogical education.Conclusion. On a final note, the results and conclusions obtained in the paper are summarized; the key positions of the authors on the inclusion of “inverted” educational resources in the professional training of future teachers of mathematics and computer science are given. The materials of the article may be of interest to lecturers of pedagogical universities who train future teachers, representatives of schools cooperating with organizations of higher pedagogical education, researchers in the field of digitalization and digital transformation of education.

The Probabilistic Revolution: Volume 1, Ideas in History; Volume 2, Ideas in the Sciences.; Vol. 1: L. Kruger, L. J. Daston, and M. Heidelberger (eds.). Vol. 2: L. Kruger, G. Gigerenzer, and M. S. Morgan (eds.). Cambridge, MA: MIT Press, 1987. Vol. 1: xiv + 449 pp., $32; Vol. 2: xvii + 459 pp., $32.50; $60 (set). Reviewed by James T. Austin Lectures on Topics in Probability Inequalities.; M. L. Eaton. Amsterdam: Centre for Mathematics and Computer Science, 1986. vi + 191 pp. Dfl. 30.40. Reviewed by Y. L. Tong Probability: An Introduction.; Geoffrey Grimmett and Dominic Welsh. Oxford, U.K.: Oxford University Press, 1986. ix + 211 pp. $19.95 (paperback). Reviewed by Marcel Neuts Dependence in Probability and Statistics: A Survey of Recent Results.; Ernst Eberlein and Murad S. Taqqu (eds.). Boston: Birkhäuser, 1986. xi + 473 pp. $39.50. Reviewed by Wlodzimierz Bryc Non-Uniform Random Variate Generation.; Luc Devroye. New York: Springer-Verlag, 1986. xvi + 834 pp. $68. Reviewed by Bruce Schmeiser Akaike Information Criterion Statistics.; Y. Sakamoto, M. Ishiguro, and G. Kitagawa. Dordrecht: D. Reidel, 1986. xix + 290 pp. $89. Reviewed by Emanuel Parzen Probability and Statistics (2nd ed.).; Morris H. DeGroot. Reading, MA: Addison-Wesley, 1986. xi + 723 pp. $41.95. Reviewed by Jeffrey A. Witmer Italian Contributions to the Methodology of Statistic.; A. Naddeo (ed.). Padova, Italy: Società Italiana di Statistica, 1987. xvi + 660 pp. L. 50,000. Reviewed by Theodore M. Porter Nonlinear Parameter Estimation: An Integrated System in BASIC.; John C. Nash and Mary Walker-Smith. New York: Marcel Dekker, 1987. xiii + 493 pp. $65 (U.S. and Canada); $78 (elsewhere). Reviewed by Douglas M. Bates Statistical Design: Theory and Practice.; Charles E. McCulloch, Steven J. Schwager, George Casella, and Shayle R. Searle (eds.). Ithaca, NY: Cornell University, 1986. ix + 231 pp. $20. Reviewed by Dallas E. Johnson Optimal Paired Comparison Designs for Factorial Experiments.; E. E. M. van Berkum. Amsterdam: Centre for Mathematics and Computer Science, 1987. ii + 153 pp. Dfl. 24.20 (paperback). Reviewed by John Stufken Measurement Error Models.; Wayne A. Fuller. New York: John Wiley, 1987. xxiii + 440 pp. $44.95. Reviewed by John Buonaccorsi Linear Models for Unbalanced Data.; Shayle R. Searle. New York: John Wiley, 1987. xxiv + 536 pp. $49.95. Reviewed by Robert J. Boik Applied Statistics: Analysis of Variance and Regression (2nd ed.).; Olive Jean Dunn and Virginia A. Clark. New York: John Wiley, 1987. xii + 445 pp. $36.95. Reviewed by Nancy J. Carter A First Course in Linear Regression.; Mary Sue Younger. Boston: Duxbury Press, 1985. xv + 703 pp. $33.75. Reviewed by Ronald R. Regal A Distance Approach to Nonlinear Multivariate Analysis.; Jacqueline Meulman. Leiden, Holland: DSWO Press, 1986. viii + 206 pp. Dfl. 30 (paperback). Reviewed by Wei-Yin Loh Bayesian Analysis and Uncertainty in Economic Theory.; Richard M. Cyert and Morris H. DeGroot. Totowa, NJ: Rowman & Littlefield, 1987. xiv + 206 pp. $34.95. Reviewed by Thomas Leonard Traffic Processes in Queueing Networks: A Markov Renewal Approach.; R. L. Disney and P. C. Kiessler. Baltimore: Johns Hopkins University Press, 1987. xix + 251 pp. $49.50. Reviewed by P. A. Jacobs Applied Reliability.; Paul A. Tobias and David Trindade. New York: Van Nostrand, 1986. x + 237 pp. $34.95. Reviewed by Donald S. Ermer Quality Programming.; Chin-Kuei Cho. New York: John Wiley, 1987. xxvi + 473 pp. $43.95. Reviewed by Thomas Beilman The Analysis of Cross-Classified Data Having Ordered Categories.; Leo A. Goodman. Cambridge, MA: Harvard University Press, 1984. xvii + 414 pp. $22.50. Reviewed by Kinley Larntz Order Dependence.; B. F. Schriever. Amsterdam: Centre for Mathematics and Computer Science, 1986. iii + 115 pp. Dfl. 17.60. Reviewed by Kinley Larntz Contemporary Classics in the Social and Behavioral Sciences.; N. J. Smelser (ed.). Philadelphia: ISI Press, 1987. xv + 361 pp. $39.95. Reviewed by Lloyd G. Humphreys The Color Line and the Quality of Life in America.; Reynolds Farley and Walter R. Allen. New York: Russell Sage Foundation, 1987. xxiv + 493 pp. $37.50. Reviewed by William W. Ellis Analysis of Variance: The Basic Designs.; Charles E. Collyer and James T. Enns. Chicago: Nelson-Hall, 1987. x + 310 pp. $29.95 (cloth); $18.95 (paperback). Reviewed by Frank B. Baker Elements of Statistics for the Life and Social Sciences.; Braxton M. Alfred. New York: Springer-Verlag, 1987. xiii + 190 pp. $36. Reviewed by Richard G. Cornell Statistics in Linguistics.; Christopher Butler. Oxford, U.K.: Basil Blackwell, 1985. x + 214 pp. $39.95 (cloth); $9.95 (paperback). Reviewed by Richard G. Cornell Statistical Methods for Psychology (2nd ed.).; David C. Howell. Boston: Duxbury Press, 1987. viii + 636 pp. $40; solutions manual (restricted). Reviewed by Richard G. Cornell Statistics for the Social and Behavioral Sciences.; David A. Kenny. Boston: Little, Brown, 1987. xvii + 407 pp. $35.25; workbook (restricted); instructors manual (restricted). Reviewed by Richard G. Cornell New Developments in Statistics for Psychology and the Social Sciences.; A. D. Lovie (ed.). New York: Methuen, 1987. ix + 177 pp. $55. Reviewed by Stanley Wasserman Dictionary of Demography: Multilingual Glossary.; William Petersen and Renee Petersen. Westport, CT: Greenwood Press, 1986. vii + 259 pp. $100. Reviewed by Edward G. Stockwell Dictionary of Demography: Biographies (2 vols.).; William Petersen and Renee Petersen. Westport, CT: Greenwood Press, 1986. xx + 1365 pp. $125. Reviewed by Edward G. Stockwell Dictionary of Demography: Terms, Concepts, and Institutions (2 vols.).; William Petersen and Renee Petersen. 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The meeting Researches in Didactics of Mathematics and Computer Sciences was held in Novi Sad, Serbia from the 23th to the 25th of January, 2015 at the University of Novi Sad. It was organized by the PhD School of Mathematics and Computer Sciences of the University of Debrecen and the Department of Mathematics and Informatics of the University of Novi Sad. The 70 participants – including 42 lecturers, and 18 PhD students – came from 9 countries, 28 cities and represented 40 intstitutions of higher education.

The Applied Mathematics, Modelling, and Computational Science (AMMCS) conference aims to promote interdisciplinary research and collaboration. The contributions in this volume cover the latest research in mathematical and computational sciences, modeling, and simulation as well as their applications in natural and social sciences, engineering and technology, industry, and finance. The 2013 conference, the second in a series of AMMCS meetings, was held August 2630 and organized in cooperation with AIMS and SIAM, with support from the Fields Institute in Toronto, and Wilfrid Laurier University. There were many young scientists at AMMCS-2013, both as presenters and as organizers. This proceedings contains refereed papers contributed by the participants of the AMMCS-2013 after the conference.This volume is suitable for researchers and graduate students, mathematicians and engineers, industrialists, and anyone who would like to delve into the interdisciplinary research of applied and computational mathematics and its areas of applications.

The term gender gap refers to the significant underrepresentation of females in many subjects. In Computer Science, the gender gap exists at all career levels. In this article, we study whether there is a performance gap in addition to the gender gap. To answer this question, we analyzed statistical data on student performance in Computer Science from 129 universities in the United Kingdom covering the years 2002 to 2013. We find that male students were awarded significantly more first-class degrees than female students. We evaluate four other subjects—Subjects Allied to Medicine, Business & Administrative Studies, Mathematical Sciences, and Engineering & Technology—and find that they do not exhibit this performance gap. From this finding, we review explanations for the gender and performance gaps, as well as potential solutions to eliminate the gaps. Most solutions do not require major institutional change and could thus be implemented easily.

Quantum mechanics is a revolutionary scientific field, which lies at the crossroad section of Physics, Mathematics, Computer and Computational Science. In essence, it is considered a cross-disciplinary STEM field, advancing the philosophy of Quantum Literacy (QL), which addresses the transdisciplinary nature of real world complex problems. QL addresses the challenges of learning and skills acquisition, through specific computing activities, within a highly bounded discipline and of access to the kind of powerful knowledge that should be more accessible to a wide group of learners. It is therefore important that quantum computing and quantum technologies knowledge is accessible to students and teachers who work with real problems, in a more inclusive and interactive way. In this paper, we argue for the necessity of exposing students to new and powerful quantum tools, as provided by cutting edge quantum computing technologies. We do that by proposing contemporary and STEM related activities and gamification scenarios, in which they acquire stronger mathematical and computational - problem decomposition and modelling skills, working as real researchers. By engaging students in games and activities related to quantum computing and quantum information processing, they acquire all necessary knowledge related to: superposition, teleportation, entanglement, quantum gates and quantum information. The serious games proposed in this paper relates to quantum strategic games, necessary for STEM activities to train students within the computational thinking 2.0 framework. All scenarios were implemented using the didactic model of inquiry-based learning using Python libraries.