Internationalisation and Globalisation in Mathematics and Science Education

Mathematics Curriculum Evaluation

Following up on efforts to improve the quality and quantity of international publications of lecturers and students of UPI (Indonesia University of Education) Postgraduate Schools, Master Program in Chemistry, Physics, Biology, Science and Mathematics Education and Doctor Program in Science and Mathematics Education collaboratively conducted International Conference on Mathematics and Science Education 2019 on Saturday 29 June 2019 at the Grand Mercure Setiabudi Bandung.The theme of the conference was “Mathematics and Science Education Research for Sustainable Development”, with coverage of Mathematics Education, Physics Education and STEM (Science, Technology, Engineering and Mathematics).The main objective of this conference is to improve the academic atmosphere within the UPI environment, particularly at the UPI Postgraduate School and strengthen the lecturer and student publications through the International Conference on Mathematics and Science Education (ICMScE )2019. Specific objectives to be achieved regarding this conference are (1). Increase the number of scientific publications of lecturers and Postgraduate students in conference proceedings, and (2). Increase the number of citation index lecturers and students of the UPI Graduate School in the Master Program in Chemistry, Physics, Biology, Science and Mathematics Education and Doctor Program in Science and Mathematics Education.List of Committees and Conference Photographs are available in this PDF.

A modern understanding of the cell and its functions has been translated into learning goals for K-12 students by Project 2061's Benchmarks for Science Literacy (American Association for the Advancement of Science [AAAS], 1993 ) and by the National Research Council's National Science Education Standards (NSES) (National Research Council [NRC], 1996 ). Nearly every state has used these national documents to develop their own science standards, so that there is now a fairly broad consensus on what it is that students need to know and be able to do in science generally and in biology more specifically. While this consensus represents an important first step toward improving science education, without curriculum, instruction, and assessments that are well aligned with these goals, teachers will find it extremely difficult to help their students achieve them. Here, we first highlight a few of the key findings regarding cell biology from Project 2061's study of high school textbooks and their alignment with standards. We then describe Project 2061's current efforts to develop new knowledge and tools that educators, researchers, and practitioners can use to help all students become literate in science, mathematics, and technology. Project 2061 is a long-term K–12 education initiative of the American Association for the Advancement of Science.

Contents: D. Williams, A Framework for Thinking About Research in Mathematics and Science Education. R. Zevenbergen, Ethnography in the Mathematics and Science Classrooms. J.S. Schaller, K. Tobin, Establishing Credibility and Authenticity in Ethnographic Studies. J. Truran, K. Truran, Using Clinical Interviews in Qualitative Research. R. Bleicher, Classroom Interactions: Using Interactional Sociolinguistics to Make Sense of Recorded Classroom Talk. P. Taylor, V. Dawson, Critical Reflections on a Problematic Student-Supervisor Relationship. G. Leder, H. Forgasz, J. Landvogt, Higher Degree Supervision: Why It Worked. L. White, Teacher, Researcher, Collaborator, Student: Multiple Roles and Multiple Dilemmas. F.E. Crawley, Guiding Collaborative Action Research in Science Education Contexts. J.A. Malone, On Supervising and Being Supervised at a Distance. W-M. Roth, M.K. McGinn, Legitimate Peripheral Participation in the Training of Researchers in Science and Mathematics Education. A. Begg, B. Bell, V. Compton, E.A. McKinley, Supervision in a Graduate Centre. T. Cooper, A.R. Baturo, L. Harris, Scholarly Writing in Mathematics and Science Education Higher-Degree Courses. J. Hourcade, H. Anderson, Writing for Publication. D. Squires, The Impact of New Developments in Information Technology on Postgraduation Research and Supervision. P. Rillero, B. Gallegos, Databases: A Gateway to Research in Mathematics and Science Education Research.

This article describes a laboratory supplementary program that was integrated into a traditional mining engineering mathematics unit. The practical classes consisted of computer investigations designed to help develop mathematical concepts. The program described here was mainly web based and did not directly rely on a computer algebra system for its implementation. An evaluation of the program is included. References S. Cunningham. The visualization environment for mathematics education. In Visualization in Teaching and Learning Mathematics , ed. W. Zimmermann and S. Cunningham, 67--76. USA, Mathematical Association of America, 1991. A. Franco, P. Franco, A. Garcia, F. Garcia, F. J.Gonzalez, S. Hoya, G. Rodriguez, and A. de la Villa. Learning calculus of several variables with new technologies. The International Journal of Computer Algebra in Mathematics Education , 7 (4), 295--309, 2000. B. E. Garner and L. E. Garner. Retention of concepts and skills in traditional and reformed applied calculus. Mathematics Education Research Journal , 13 (3), 165--184, 2001 S. Habre. Visualization enhanced by technology in the learning of multivariate calculus. The International Journal of Computer Algebra in Mathematics Education , 8 (2), 115--130, 2001. B. H. Hallet. Visualization and calculus reform. In Visualization in Teaching and learning Mathematics , ed. W. Zimmermann and S. Cunningham, 121--126, 1991. USA, Mathematical Association of America F. Marton and R. Saljo. Approaches to learning. In eds. F. Marton, D. Hounsell and N. Entwistle, The Experience of Learning , 36--55, 1984. Scottish Academic Press, Edinburgh. R. Moreno and R. Mayer. Verbal redundancy in multimedia learning; When reading helps listening. Journal of Educational Psychology , 94 (1), 153--163, 2002. L. D. Murphy. Computer algebra systems in calculus reform, MSTE, University of Illinois at Urbana-Champaign, 1999. http://mste.illinois.edu/users/Murphy/Papers/CalcReformPaper.html M. Pemberton. Integrating web-based maple with a first year calculus and linear algebra course. Proceedings of the 2nd International Conference on the Teaching of Mathematics , Hersonissos, Greece, July 2002. http://www.math.uoc.gr/ ictm2/Proceedings/pap316.pdf R. Pierce and K. Stacey. Observations on students' responses to learning in a cas environment. Mathematics Education Research Journal , 13 (1), 28--46, 2001. M. D. Roblyer. Integrating Educational Technology Into Teaching (4th Ed.), 2006. Pearson, New Jersey, USA. J. Stewart. Calculus (5th Ed.), 2003. Brooks/Cole, Belmont, USA. E. J. Tonkes, B. I. Loch and A. W. Stace. An innovative learning model for computation in first year mathematics. International Journal of Mathematical Education in Science and Technology , 36 (7), 751--759, 2005. L. M. Villarreal. A step in the positive direction: Integrating a computer laboratory component into developmental algebra courses. Mathematics and Computer Education , 37 (1), 72--78, 2003. S. Vinner. The pseudo-conceptual and the pseudo-analytical thought processes in mathematics learning. Educational Studies in Mathematics , 34 (2), 97--129, 1997. P. Vlachos and A.K. Kehagias. A computer algebra system and a new approach for teaching business calculus. The International Journal of Computer Algebra in Mathematics Education . 7 (2), 87--104, 2000.

From a traditional perspective, induction and deduction have been discussed as key ways to generate new knowledge. On the other hand, Charles Sanders Peirce introduced the notion of abduction, distinct from deduction and induction, to avoid the pitfalls of empiricism and rationalism. Abduction is the process of forming an explanatory hypothesis on an observed surprising result (C.P. 5.171). Peirce emphasized that abductive reasoning is the only way of creating new ideas, and both epistemologists and educational researchers have attempted to tackle this notorious problem, the so-called learning paradox, from a Peircean perspective on knowledge generation (Prawat, 1999). With mathematics educators’ recent interests in semiotic approaches, there has been growing attention to the importance of investigating abductive reasoning in mathematics education research. Studies have attempted to clarify the forms and uses of abductive reasoning in students’ mathematical inquiries in order to identify how students generate new mathematical ideas. Researchers also consider that investigating students’ abductive reasoning may help to interpret and understand what occurs in mathematics classrooms. Thus, exploring abductive reasoning in mathematics education may provide a more helpful cornerstone in understanding how mathematics teaching and learning progresses. This special issue of EURASIA Journal of Mathematics, Science and Technology Education aims to share current and future issues on abductive reasoning in mathematics education. In inviting the contributions for this special issue, we intend to offer the reader, original elements of reflection from a wide range of issues on abductive reasoning in mathematics education. David Reid gives an overview of the discussion of abductive reasoning in mathematics education researches based on a meta-analysis of the state-of-the-art literature. He presents the origins of the concept of abductive reasoning and identifies the most significant approaches in mathematics education literature that refers to abductive reasoning. He then proposes a framework in which the different approaches taken in the research literature can be placed and compared. Michael Hoffmann presents very fundamental issues regarding abductive reasoning. Hoffmann tackles two crucial questions related to knowledge creation from a Peircean perspective: Can diagrammatic reasoning indeed be conceived as a foundation of abductive creativity? What is the relationship between abduction and diagrammatic reasoning? To answer these questions, he clarifies the Peircean concept of diagram and diagrammatic reasoning and analyzes the significance of a consistent system of representation for diagrammatic reasoning. He then examines how diagrammatic reasoning and creation of abduction are related. Three further contributions address how abduction is related to various contexts of mathematics learning. Bettina Pedemonte presents the role of abduction in the proving process of students solving a geometrical problem. She focuses on two types of rules in problem solving: strategic rules and definitory rules. She then compares two types of abductions that are related to these two rules, and analyzes the relationship between these two types of abductions and the deductive proof. Ferdinand Rivera examines elementary students’ pattern generalization. He focuses on identifying multiple abductive actions in their pattern generalization, and shows how multiple abductions can be coordinated and how this coordination is related to pattern generalization. He also analyzes the relationship between elementary children’s structural incipient generalizations and the natural emergence of their understanding of functions, especially the central role of abduction in such an understanding. JinHyeong Park and Kyeong-Hwa Lee investigate the abductive nature of mathematical modeling and the characteristics of mathematical inquiries triggered by mathematical modeling. They identify four characteristics of mathematical inquiries triggered by mathematical modeling based on an analysis of didactical and historical cases: abductive, recursive, analogical, and context-dependent. Michael Meyer presents various task-design options that can be used to support students in discovering mathematical properties that refer to abductive reasoning. These task-design options are identified using intense scrutiny of the processes of discovering and verifying mathematical properties from a Peircean perspective on learning and knowledge creation. He also presents concrete examples of task design and empirical findings on the implementation of tasks. From theoretical issues to more practical issues, these contributions in this special issue present state-of-the-art issues in abductive reasoning in the mathematics education research community. We hope that these offer an informative insight into the lively research on abductive reasoning in mathematics education.

This essay responds to Kirchgasler's (2026) analysis of affective hierarchies in post‐ Brown science education as part of the special issue Centering Affect and Emotion Toward Justice and Dignity in Science Education . Drawing on prior work on racialized deviance in mathematics education, I argue that both science and mathematics education reforms have positioned Black children as emotionally and cognitively deficient, requiring pedagogical intervention to attain citizenship and dignity. I use Kirchgasler's argument for the three ways that science education enacted racialized hierarchies of affect post‐ Brown to extend my prior argument about the operation of the genre function in equity‐oriented mathematics education research to science education. I connect Kirchgasler's first—dividing students into tiered emotional regimes—and second—making dignity conditional on developing a depoliticized scientific self—analytical points to the two rules of equity research in mathematics education. This analysis highlights the necessary social function of mathematics and limiting the focus on equity to the descriptive.

A number of national science and mathematics education professional associations, and recently technology education associations, are united in their support for the integration of science and mathematics teaching and learning. The purpose of this historical analysis is two‐fold: (a) to survey the nature and number of documents related to integrated science and mathematics education published from 1901 through 2001 and (b) to compare the nature and number of integrated science and mathematics documents published from 1990 through 2001 to the previous 89 years (1901–1989). Based upon this historical analysis, three conclusions have emerged. First, national and state standards in science and mathematics education have resulted in greater attention to integrated science and mathematics education, particularly in the area of teacher education, as evidenced by the proliferation of documents on this topic published from 1901–2001. Second, the historical comparison between the time periods of 1901–1989 versus 1990–2001 reveals a grade‐level shift in integrated instructional documents. Middle school science continues to be highlighted in integrated instructional documents, but surprisingly, a greater emphasis upon secondary mathematics and science education is apparent in the integration literature published from 1990–2001. Third, although several theoretical integration models have been posited in the literature published from 1990–2001, more empirical research grounded in these theoretical models is clearly needed in the 21st century.

This special issue of the Canadian Journal of Science, Mathematics and Technology Education invokes questions intended to further the discourse of citizenship in science and mathematics education, such as, How do we define citizen and democracy? Is our call for student action hypocritical? Does positioning school science through the work of Ranciere present a “straw man” argument for change? To what extent does the ghost of John Dewey animate and inform a “wild pedagogy” in science education? Challenging the view of the science and mathematics curriculum as a barrier to overcome, this article argues that possibilities for developing citizenship and critical thinking can be found and developed in existing curriculum formations and practices of school science and mathematics education.

to general feelings such as liking/disliking of mathematics, nor is it meant to exclude perceptions of the difficulty, usefulness, and appropriateness of mathematics as a school subject. There are several ways affective variables are related to mathematics learning. It is likely that a student who feels very positive about mathematics will achieve at a higher level than a student who has a negative attitude toward mathematics. It is also likely that a high achiever will enjoy mathematics more than a student who

Introduction I suggest a simple thought experiment. Science fiction books occasionally mention an imaginary device: a replicator. It consists of two boxes; you put an object in a box, close the lid, and instantly get its undistinguishable fully functional copy in the second box. In particular, a replicator can replicate smaller replicators. Now imagine the economy based on replicators. It needs two groups of producers: a very small group of engineers who build and maintain the biggest replicator and a very diverse, but still small, group of artisans, designers, and scientists who produce a single original prototype of each object. This hypothetical economy also needs service sector, mostly waste disposal. Next, try, if you can, imagine a sustainable, stable, equal, and democratic model of education that supports this lopsided economy. But this apocalyptic future is already upon us – in the information sector of economy, where computers act as replicators of information. Mathematics, due to its special role in the information technology, is the most affected part of human culture. The new patterns of division of labour split mathematics for makers from mathematics for users and trigger a crisis of mathematics education. The latter increasingly focuses on mathematics for users and undermines itself because sustainable reproduction of mathematics requires teachers educated as makers. The ultimate replicating machines I borrowed the title of this section from a chapter in my book [1]. I argue there that the essence of mathematics is its precise replicability which imitates the stability of laws of the physical universe, that Mathematics is the ultimate in the technology transfer. [2] A mathematical theorem needs to be proved only once – and then used for centuries. An algorithm needs to be developed only once – and then it can serve, as the Google Ranking Algorithm does, as a kingpin of a global information system. In previous historic epochs, every use of a mathematical result required participation of humans, who had to understand what they were doing and therefore had to be mathematically educated; the criterion of understanding was the ability to reproduce the proof. Nowadays, mathematics is used mostly by computers, not by people, and used in an instantly replicable way. This creates a completely different socio-economic environment for mathematics. Division of labour As I argue in my paper [3], the history of human civilisation is the history of division of labour. By the start of the 21st century, the ever deepening division of labour has reached a unique point when 99% of people have not even the vaguest idea about the workings of 99% of technology in their immediate surrounding. This transformation is deeper than the Great Industrial Revolution of 18th and 19th centuries, and its social consequences have a chance to be more dramatic. Mathematics and mathematics education are the proverbial canaries in the mine, they are more sensitive to this technological change. It costs to make ("replicate") a smartphone, it costs to write an app for smartphone, but the per unit cost of mathematics encoded and hardwired within the phone converges to zero. There are more mobile phones in the world now than toothbrushes. But the mathematics built into mobile communication systems is beyond the understanding of most universities' graduates. This creates a paradox: mathematics is used in everyday life millions of times more intensively than 50 or even 10 years ago – but remains invisible. Meanwhile, mathematical results and concepts involved in practical applications are much deeper and more abstract and difficult than ever before. The cutting edge of mathematics research moves further away from the stagnating mathematics education. From the point of view of an aspiring PhD student, mathematics looks like New York in the Capek Brothers' book A Long Cat Tale [4] (and notice that Karel Capek was the man who coined the word "robot"): And New York – well, houses there are so tall that they can't even finish building them. Before the bricklayers and tilers climb up them on their ladders, it is noon, so they eat their lunches and start climbing down again to be in their beds by bedtime. And so it goes on day after day. Investment cycles and research-and-development cycles in many modern industries are just two years long. On the other hand, proper mathematics education still takes at least 15 years from the age of 5 to the age of 20 – or even 20 years if postgraduate studies are needed. As I argue in [3], mathematics education is being undermined by this tension between the ever deepening specialisation of labour and ever increasing length of specialised training required for jobs at the increasingly sharp cutting edge of technology. If banks and insurance companies were interested in having numerate customers, we would witness the golden age of school mathematics – fully funded, enjoying cross-party political support, promoted and popularised by the best advertising companies in all forms of mass and social media. But they are not; banks and insurance companies need numerate workforce – and even more so they need innumerate customers. 25 years ago in the West, the benchmark of arithmetic competence at the consumer level was the ability to balance a chequebook. Nowadays, bank customers can instantly get full information about the state of their accounts from an app on a mobile phone – together with timely and tailored to individual circumstances advice on the range of available financial products. As Anna Sfard [5] put it, It is enough to take a critical look at our own lives to realize that we do not, in fact, need much mathematics in our everyday lives. In short, the present model of "mathematics education for all" is unsustainable and, not surprisingly, first cracks have started to appear. On the other hand, the reproduction cycle of mathematics primary school – high school – university – teacher training – a teacher's return to school is 20 years long, and it is not clear at all whether the current model of education could be smoothly and peacefully replaced by the new one, aimed at in-depth mathematics education of a much smaller stratum of people. Assessments of this situation from the opposite ends of the political spectrum are instructive: Failure in achieving a meaningful mathematics education is not a malfunction which could be solved through better research and a proper crew, but is endemic in capitalist schooling. (Alexandre Pais [6]) While there is an upside limit to the average intellectual capabilities of population, there is no upper limit to the complexity of technology. … With ... an apparently inbred upper limit to human IQ, are we destined to have an ever smaller share of our workforce staff our ever more sophisticated high-tech equipment and software? (Alan Greenspan [7]) Mathematics education When previously meaningful social activities (and social institutions supporting them) loose their economic purpose, they either collapse or transform themselves into a complex of rituals, "cargo cult," in the words of Richard Feynman. In the "cargo cult" environment, everything goes. This is why we see the explosive growths in the number of various approaches and methods tried at school – because there are no objective bottom-line criteria to distinguish between them. Here, I want to touch on a popular myth: that the same computer technology that kills demand for mathematics will save mathematics education. First of all, we have to distinguish between education and training. As a famous saying goes, "For those of you with daughters, would you rather have them take sex education or sex training?" This witticism makes it clear what is expected from education as opposed to training: the former should give a student ability to make informed and responsible decisions. This is the old class divide that tears many education systems apart: education is for people who are expected to make decisions and give orders; training is for ones who take orders. However it is increasingly accepted that modern mathematics education is not even training of workforce for future employment (this model of education is so 20th century), it is filtering of workforce by means of mathematical tests – even if no mathematics is needed at the actual workplace. Computers could be very efficient tools for training students to pass tests – I do not dispute that. However, although the skill of passing a mathematics test remains personally important, it becomes increasingly redundant at the scale of the economy as a whole. An exam at the end of the course should test students' ability to perform certain tasks – but in case of school and college mathematics, these tasks now are much better performed by computers – see a detailed discussion of that in [3]. Then what is the aim of training? The ability to imitate robots? Are students' skills assessed are of any economic (or "real life") value if computers can pass the tests in an instant and with better scores than humans? Makers and Users So far I was looking at the emerging new social environment of mathematics. Now a few words on consequences for mathematics itself. The new patterns of division of labour split mathematics for makers from mathematics for users. How t describe the two? The replicability of mathematics mirrors the stability of laws of the physical universe, which is captured by the apocryphal formula: Mathematics is the language of contracts with Nature which Nature accepts as binding. It is dangerous to replace, in this formulation, "Nature" by "Computer" – but it appears that this increasingly frequently happens in practice. Therefore, in my understanding, Mathematics for Makers is mathematics that cannot be entrusted to computers, mathematics for those whose duty is writing contracts with Nature, in the process inventing new mathematics and new ways to apply mathematics. In terms of the "universal replicator" simile from the Introduction, these are people who produce the originals for subsequent replication. The mainstream mathematics education increasingly focuses on mathematics for users. But sustainable reproduction of mathematics requires teachers educated as makers – on that point, I refer the reader to my paper [8]. Conclusions The expansionist model of mathematics education is dying because the technological changes in the wider economy lead to the shift of demand for mathematically competent workers: smaller numbers are needed, but much better educated. Compression cracks are more destructive and less predictable than expansion gaps – for the obvious reason: where should the excessive mass go? Potential social consequences bring to mind the apocryphal curse May you live in interesting times; It looks as if interesting times are already upon us. But I do not takes sides in the increasingly politicised debate. In my view, most policies in mathematics education can be divided in two categories: rearranging chairs on the deck of Titanic (the preferred option of the political Right); helping disadvantaged passengers to get better chairs on the deck of Titanic (the preferred option of the political Left). My role is different, I am with my fellow teachers in the famous band that continues to play regardless. Not the first violin, of course; I am in the back row, with a tuba: "Boop, boop, boop, boop." I am a mathematician; I will play to the end. Disclaimer The author writes in his personal capacity; his views do not necessarily represent the position of his employer or any other person, corporation, organisation or institution. References and Notes Borovik, A. V. Mathematics under the Microscope: Notes on Cognitive Aspects of Mathematical Practice, American Mathematical Society, Providence, USA, 2010; pp. 217 – 245. Stewart, I. Does God Play Dice? The Mathematics of Chaos. Penguin, London, UK, 1990. Borovik, A. V. Calling a spade a spade: Mathematics in the new pattern of division of labour, to appear. A pdf file: http://goo.gl/TT6ncO Capek, K.; Capek, J. A Long Cat Tale, Albatros, Prague, The Czech Republic, 1996; p. 44. Sfard, A. Why Mathematics? What Mathematics? In The Best Writings on Mathematics, Pitici M., Ed.; Princeton University Press, Princeton, USA, 2013; pp. 130-142. Pais, A. An ideology critique of the use-value of mathematics, Stud. Math., 2013, vol. 84, pp. 15 – 34. Greenspan, A. The Map and the Territory: Risk, Human Nature and the Future of Forecasting, Allen Lane, USA, 2013. Borovik, A. V. Didactic transformation in mathematics teaching, http://www.academia.edu/189739/Didactic_transformation_in_mathematics_teaching

GeoMaTech: Integrating Technology and New Pedagogical Approaches Into Primary and Secondary School Teaching to Enhance Mathematics Education in Hungary

Previous articleNext article No AccessAttitudes of Prospective Teachers toward ArithmeticWilbur H. DuttonWilbur H. Dutton Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Elementary School Journal Volume 52, Number 2Oct., 1951 Article DOIhttps://doi.org/10.1086/459310 Views: 8Total views on this site Citations: 32Citations are reported from Crossref Copyright 1951 The University of ChicagoPDF download Crossref reports the following articles citing this article:Rosetta Zan, Pietro Di Martino Students’ Attitude in Mathematics Education, (Feb 2020): 813–817.https://doi.org/10.1007/978-3-030-15789-0_146Kyoung Whan Choe, Jalisha B. Jenifer, Christopher S. Rozek, Marc G. Berman, Sian L. 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Leavy The influence of entry route to teaching on Irish pre-service primary teachers’ attitudes towards mathematics, Journal of Further and Higher Education 43, no.77 (Jan 2018): 869–883.https://doi.org/10.1080/0309877X.2017.1420148Menekşe ESKİCİ, Gökhan ILGAZ Lise Öğrencileri ve Matematik: Tutum, Başarı ve Cinsiyet Işığında, Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi (Feb 2019).https://doi.org/10.18506/anemon.422161Rosetta Zan, Pietro Di Martino Students’ Attitude in Mathematics Education, (Feb 2019): 1–5.https://doi.org/10.1007/978-3-319-77487-9_146-4Gülçin Oflaz CEBİRE YÖNELİK TUTUM ÖLÇEĞİ GELİŞTİRME ÇALIŞMASI, Hitit Üniversitesi Sosyal Bilimler Enstitüsü Dergisi (Dec 2018).https://doi.org/10.17218/hititsosbil.444718Aisling Leavy, Mairead Hourigan The beliefs of ‘Tomorrow's Teachers’ about mathematics: precipitating change in beliefs as a result of participation in an Initial Teacher Education programme, International Journal of Mathematical Education in Science and Technology 49, no.55 (Jan 2018): 759–777.https://doi.org/10.1080/0020739X.2017.1418916Aisling Leavy, Mairead Hourigan, Claire Carroll Exploring the Impact of Reform Mathematics on Entry-Level Pre-service Primary Teachers Attitudes Towards Mathematics, International Journal of Science and Mathematics Education 15, no.33 (Nov 2015): 509–526.https://doi.org/10.1007/s10763-015-9699-1Mairéad Hourigan, Aisling M. 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Litwiller Enrichment: A Method of Changing the Attitudes of Prospective Elementary Teachers Toward Mathematics, School Science and Mathematics 70, no.44 (Apr 1970): 345–350.https://doi.org/10.1111/j.1949-8594.1970.tb08636.xLewis H. Coon Attitude: A Rating Scale for Calculus, The Journal of Educational Research 63, no.44 (Jan 2015): 173–177.https://doi.org/10.1080/00220671.1969.10883972Ralph G. Anttonen A Longitudinal Study in Mathematics Attitude, The Journal of Educational Research 62, no.1010 (Jan 2015): 467–471.https://doi.org/10.1080/00220671.1969.10883904Ingvar Werdelin FACTOR ANALYSES OF QUESTIONNAIRES OF ATTITUDES TOWARDS SCHOOL WORK, Scandinavian Journal of Psychology 9, no.11 (Sep 1968): 117–128.https://doi.org/10.1111/j.1467-9450.1968.tb00524.x Wilbur H. Dutton Another Look at Attitudes of Junior High School Pupils toward Arithmetic, The Elementary School Journal 68, no.55 (Oct 2015): 265–268.https://doi.org/10.1086/460444Wilbur H. 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Software (SW) is one of the key technologies in modern society, and its importance is receiving the attention of the educational community. In addition, Computational Thinking (CT) has been studied in fields of various education such as computer science, science, mathematics, and technology. The prominence of computer science education has increased in K-12 South Korean schools with the effect of the 2015 Revised National Curriculum and the National Plan for Activating Software Education. In addition, there are active efforts to include CT in science, technology, and mathematics classrooms. Therefore, this study aims to review prior studies on CT in science and mathematics education. The results of this study are as follows: 1) CT in science and mathematics education has a different conceptual approach than CT in computer education. Science education is mostly about problem-solving activities using computers, and mathematics education mostly utilizes the ‘abstraction’ related approach. 2) The key to improving CT in both subjects is to implement practical experience in science and mathematics education. Variables of interest in prior studies were scientific and mathematical problem-solving skills, the attitude of subjects, and creativity. 3) CT education in science and mathematics education has used a convergence education approach (STEAM education). Keywords: computational thinking, mathematics education, research trend analysis, science education

Debate has continued throughout the last decade over the existence and possible causes of differences between males' and females' mathematical skills. Several observations recur as the focus of this controversy. First, adolescent boys have been found to score higher than girls on standardized mathematics achievement tests.' Second, males are more likely than females to engage in a variety of optional activities related to mathematics, from technical hobbies to careers in which math skills play an important role.2 Third, adolescent males typically perform better than their female