Texas Administrative Code
Title 19 - EDUCATION
Part 2 - TEXAS EDUCATION AGENCY
Chapter 111 - TEXAS ESSENTIAL KNOWLEDGE AND SKILLS FOR MATHEMATICS
Subchapter C - HIGH SCHOOL
Section 111.46 - Discrete Mathematics for Problem Solving, Adopted 2013 (One-Half to One Credit)
Universal Citation: 19 TX Admin Code ยง 111.46
Current through Reg. 49, No. 38; September 20, 2024
(a) General requirements. Students shall be awarded one-half to one credit for successful completion of this course. Prerequisite: Algebra II.
(b) Introduction.
(1) The desire to achieve educational
excellence is the driving force behind the Texas essential knowledge and skills
for mathematics, guided by the college and career readiness standards. By
embedding statistics, probability, and finance, while focusing on fluency and
solid understanding, Texas will lead the way in mathematics education and
prepare all Texas students for the challenges they will face in the 21st
century.
(2) The process standards
describe ways in which students are expected to engage in the content. The
placement of the process standards at the beginning of the knowledge and skills
listed for each grade and course is intentional. The process standards weave
the other knowledge and skills together so that students may be successful
problem solvers and use mathematics efficiently and effectively in daily life.
The process standards are integrated at every grade level and course. When
possible, students will apply mathematics to problems arising in everyday life,
society, and the workplace. Students will use a problem-solving model that
incorporates analyzing given information, formulating a plan or strategy,
determining a solution, justifying the solution, and evaluating the
problem-solving process and the reasonableness of the solution. Students will
select appropriate tools such as real objects, manipulatives, paper and pencil,
and technology and techniques such as mental math, estimation, and number sense
to solve problems. Students will effectively communicate mathematical ideas,
reasoning, and their implications using multiple representations such as
symbols, diagrams, graphs, and language. Students will use mathematical
relationships to generate solutions and make connections and predictions.
Students will analyze mathematical relationships to connect and communicate
mathematical ideas. Students will display, explain, or justify mathematical
ideas and arguments using precise mathematical language in written or oral
communication.
(3) In Discrete
Mathematics for Problem Solving, students are introduced to the improved
efficiency of mathematical analysis and quantitative techniques over
trial-and-error approaches to management problems involving organization,
scheduling, project planning, strategy, and decision making. Students will
learn how mathematical topics such as graph theory, planning and scheduling,
group decision making, fair division, game theory, and theory of moves can be
applied to management and decision making. Students will research
mathematicians of the past whose work is relevant to these topics today and
read articles about current mathematicians who either teach and conduct
research at major universities or work in business and industry solving
real-world logistical problems. Through the study of the applications of
mathematics to society's problems today, students will become better prepared
for and gain an appreciation for the value of a career in
mathematics.
(4) Statements that
contain the word "including" reference content that must be mastered, while
those containing the phrase "such as" are intended as possible illustrative
examples.
(c) Knowledge and skills.
(1) Mathematical process
standards. The student uses mathematical processes to acquire and demonstrate
mathematical understanding. The student is expected to:
(A) apply mathematics to problems arising in
everyday life, society, and the workplace;
(B) use a problem-solving model that
incorporates analyzing given information, formulating a plan or strategy,
determining a solution, justifying the solution, and evaluating the
problem-solving process and the reasonableness of the solution;
(C) select tools, including real objects,
manipulatives, paper and pencil, and technology as appropriate, and techniques,
including mental math, estimation, and number sense as appropriate, to solve
problems;
(D) communicate
mathematical ideas, reasoning, and their implications using multiple
representations, including symbols, diagrams, graphs, and language as
appropriate;
(E) create and use
representations to organize, record, and communicate mathematical
ideas;
(F) analyze mathematical
relationships to connect and communicate mathematical ideas; and
(G) display, explain, and justify
mathematical ideas and arguments using precise mathematical language in written
or oral communication.
(2) Graph theory. The student applies the
concept of graphs to determine possible solutions to real-world problems. The
student is expected to:
(A) explain the
concept of graphs;
(B) use graph
models for simple problems in management science;
(C) determine the valences of the vertices of
a graph;
(D) identify Euler
circuits in a graph;
(E) solve
route inspection problems by Eulerizing a graph;
(F) determine solutions modeled by edge
traversal in a graph;
(G) compare
the results of solving the traveling salesman problem (TSP) using the nearest
neighbor algorithm and using a greedy algorithm;
(H) distinguish between real-world problems
modeled by Euler circuits and those modeled by Hamiltonian circuits;
(I) distinguish between algorithms that yield
optimal solutions and those that give nearly optimal solutions;
(J) find minimum-cost spanning trees using
Kruskal's algorithm;
(K) use the
critical path method to determine the earliest possible completion time for a
collection of tasks; and
(L)
explain the difference between a graph and a directed graph.
(3) Planning and scheduling. The
student uses heuristic algorithms to solve real-world problems. The student is
expected to:
(A) use the list processing
algorithm to schedule tasks on identical processors;
(B) recognize situations appropriate for
modeling or scheduling problems;
(C) determine whether a schedule is optimal
using the critical path method together with the list processing
algorithm;
(D) identify situations
appropriate for modeling by bin packing;
(E) use any of six heuristic algorithms to
solve bin packing problems;
(F)
solve independent task scheduling problems using the list processing algorithm;
and
(G) explain the relationship
between scheduling problems and bin packing problems.
(4) Group decision making. The student uses
mathematical processes to apply decision-making schemes. The student analyzes
the effects of multiple types of weighted voting and applies multiple voting
concepts to real-world situations. The student is expected to:
(A) describe the concept of a preference
schedule and how to use it;
(B)
explain how particular decision-making schemes work;
(C) determine the outcome for various voting
methods, given the voters' preferences;
(D) explain how different voting schemes or
the order of voting can lead to different results;
(E) describe the impact of various strategies
on the results of the decision-making process;
(F) explain the impact of Arrow's
Impossibility Theorem;
(G) relate
the meaning of approval voting;
(H)
explain the need for weighted voting and how it works;
(I) identify voting concepts such as Borda
count, Condorcet winner, dummy voter, and coalition; and
(J) compute the Banzhaf power index and
explain its significance.
(5) Fair division. The student applies the
adjusted winner procedure and Knaster inheritance procedure to real-world
situations. The student is expected to:
(A)
use the adjusted winner procedure to determine a fair allocation of
property;
(B) use the adjusted
winner procedure to resolve a dispute;
(C) explain how to reach a fair division
using the Knaster inheritance procedure;
(D) solve fair division problems with three
or more players using the Knaster inheritance procedure;
(E) explain the conditions under which the
trimming procedure can be applied to indivisible goods;
(F) identify situations appropriate for the
techniques of fair division;
(G)
compare the advantages of the divider and the chooser in the divider-chooser
method;
(H) discuss the rules and
strategies of the divider-chooser method;
(I) resolve cake-division problems for three
players using the last-diminisher method;
(J) analyze the relative importance of the
three desirable properties of fair division: equitability, envy-freeness, and
Pareto optimality; and
(K) identify
fair division procedures that exhibit envy-freeness.
(6) Game (or competition) theory. The student
uses knowledge of basic game theory concepts to calculate optimal strategies.
The student analyzes situations and identifies the use of gaming strategies.
The student is expected to:
(A) recognize
competitive game situations;
(B)
represent a game with a matrix;
(C)
identify basic game theory concepts and vocabulary;
(D) determine the optimal pure strategies and
value of a game with a saddle point by means of the minimax
technique;
(E) explain the concept
of and need for a mixed strategy;
(F) compute the optimal mixed strategy and
the expected value for a player in a game who has only two pure
strategies;
(G) model simple
two-by-two, bimatrix games of partial conflict;
(H) identify the nature and implications of
the game called "Prisoners' Dilemma";
(I) explain the game known as
"chicken";
(J) identify examples
that illustrate the prevalence of Prisoners' Dilemma and chicken in our
society; and
(K) determine when a
pair of strategies for two players is in equilibrium.
(7) Theory of moves. The student analyzes the
theory of moves (TOM). The student uses the TOM and game theory to analyze
conflicts. The student is expected to:
(A)
compare and contrast TOM and game theory;
(B) explain the rules of TOM;
(C) describe what is meant by a cyclic
game;
(D) use a game tree to
analyze a two-person game;
(E)
determine the effect of approaching Prisoners' Dilemma and chicken from the
standpoint of TOM and contrast that to the effect of approaching them from the
standpoint of game theory;
(F)
describe the use of TOM in a larger, more complicated game; and
(G) model a conflict from literature or from
a real-life situation as a two-by-two strict ordinal game and compare the
results predicted by game theory and by TOM.
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