Browsing by Author "Sinchai Jansem"

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    On some new simpsonÕs formula type inequalities for convex functions in post-quantum calculus
    (MDPI, 2021) Miguel J. Vivas-Cortez; Muhammad Aamir Ali; Shahid Qaisar; Ifra Bashir Sial; Sinchai Jansem; Abdul Mateen; M.J. Vivas-Cortez; Facultad de Ciencias Exactas y Naturales, Pontificia Universidad Cat—lica del Ecuador, Escuela de Ciencias Matem‡ticas y F’sicas, Quito, Av. 12 de Octubre 1076, Apartado, 17-01-2184, Ecuador; email: mjvivas@puce.edu.ec; M.A. Ali; Jiangsu Key Laboratory for NSLSCS, School of Mathematical Sciences, Nanjing Normal University, Nanjing, 210023, China; email: mahr.muhammad.aamir@gmail.com
    In this work, we prove a new (p, q)-integral identity involving a (p, q)-derivative and (p, q)-integral. The newly established identity is then used to show some new SimpsonÕs formula type inequalities for (p, q)-differentiable convex functions. Finally, the newly discovered results are shown to be refinements of comparable results in the literature. Analytic inequalities of this type, as well as the techniques used to solve them, have applications in a variety of fields where symmetry is important. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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    The role of context expertise when comparing data
    (2011) Cynthia Langrall; Steven Nisbet; Edward Mooney; Sinchai Jansem; C. Langrall; Department of Mathematics, Illinois State University, Normal, IL 61761, Campus Box 4520, United States; email: langrall@ilstu.edu
    Our research addresses the role that context expertise plays when students compare data. We report findings from a study conducted in 3 countries: Australia, United States, and Thailand. In each country, six middle school students analyzed authentic data relating to selected students' areas of interest. We examined the data analysis processes and discussion among students as each country cohort worked in two groups of three, where only one group included a student with particular expertise with the data context. We found that students used context knowledge to (a) bring new insight or additional information to the task, (b) explain the data, (c) provide justification or qualification for claims, (d) identify useful data for the task at hand, and (e) state facts that may enhance the picture of the data but are irrelevant to the process of analyzing the data. Implications for practice are discussed. © Taylor & Francis Group, LLC.