Micro Forte





imageedit_5_3949838586

Website Investments

Micro Forte

Virtual Reality - Gaming - Virtual Gaming - Gaming Online

Virtual Techniques - Virtual Sport - Safe Gaming - Video Games






Gaming For Classroom-based Learning

RRP $549.99

Click on the Google Preview image above to read some pages of this book!

In order to effectively use games in the classroom, teachers and parents need to agree on games' positive functions toward students' learning, decide and select good educational games relevant to content and tasks in the classroom, and disseminate their acquired knowledge into the teaching field. As part of an international dialogue between researchers in educational technology, Gaming for Classroom-Based Learning: Digital Role Playing as a Motivator of Study investigates whether games can motivate students to learn and improve their knowledge and skills. This collection of research aims to inform classroom and pre-service teachers of the potential of games for improving teaching and learning.


Asymptotic Theory Of Nonlinear Regression

RRP $519.99

Click on the Google Preview image above to read some pages of this book!

Let us assume that an observation Xi is a random variable (r.v.) with values in 1 1 (1R1 , 8 ) and distribution Pi (1R1 is the real line, and 8 is the cr-algebra of its Borel subsets). Let us also assume that the unknown distribution Pi belongs to a 1 certain parametric family {Pi() , () E e}. We call the triple GBPi = {1R1 , 8 , Pi(), () E e} a statistical experiment generated by the observation Xi. n We shall say that a statistical experiment GBPn = {lRn, 8 , P; ,() E e} is the product of the statistical experiments GBPi, i = 1, ...,n if PO' = P () X ...X P () (IRn 1 n n is the n-dimensional Euclidean space, and 8 is the cr-algebra of its Borel subsets). In this manner the experiment GBPn is generated by n independent observations X = (X1, ...,Xn). In this book we study the statistical experiments GBPn generated by observations of the form j = 1, ...,n. (0.1) Xj = g(j, (}) + cj, c c In (0.1) g(j, (}) is a non-random function defined on e , where e is the closure in IRq of the open set e ~ IRq, and C j are independent r. v .-s with common distribution function (dJ.) P not depending on ().



Search

Micro Forte Articles

Virtual Reality Gaming Virtual Gaming Gaming Online
Virtual Techniques Virtual Sport Safe Gaming Video Games

Micro Forte Books

Virtual Reality Gaming Virtual Gaming Gaming Online
Virtual Techniques Virtual Sport Safe Gaming Video Games

Micro Forte





imageedit_5_3949838586

Website Investments