OpenLLM-France/wikimedia huggingface dataset:
# Kinematics/Vector Review

Some physical quantities are completely described by a numerical value alone. Such quantities are called scalars or scalar quantity.
But for description of some physical quantities value as well as direction is required. Velocity of a particle is one such example. The magnitude of velocity is represented by a number such as 5 m/s and tells us how fast a body is moving. But description of velocity is complete only when direction of velocity is specified. Such quantities are called vectors.

## Equality Of Vectors

Two vectors are equal if and only if they have same magnitude(numerical value) and direction. Thus, a parallel translation of a vector does not bring about any change in it.

## Addition Of Vectors

Vectors cannot be added subtracted by normal laws of algebra. they are added according to The triangle law of vector addition. The parallelogram law of vector addition and The polygon law of vector addition are extensions of triangle law.
# Kinyarwanda/Pronunciation

Kinyarwanda has five vowels which are either long or short, high-toned and no tones. The high tone can appear either on first mora or the second mora. These vowels are the two high vowels i and u, the midvowels e and o and the center low vowel a. The midvowels e and o are not allowed in both the (pre)prefix and suffix positions. In verbs, however, these midvowels can appear in the suffix position as a result of vowel harmony if the vowel of the verb stem is a midvowel. ex. gukosa 'to make mistakes' gukosoora 'to correct' /ku-kos-uur-a/; kumenya 'to know' kumenyeesha /ku-meny-iish-a/. The majority of word stems have the same identical vowel in all syllables: u-mu-biri 'body', u-bu-riri 'bed, i-ki-reenge 'leg', i-béere 'breast', u-mu-góongo 'back', u-mu-hoondo 'yellow', u-ku-guru 'leg', u-ru-túgu 'shoulder', igihaánga 'skull', i-ki-gaanza 'hand palm'. This observation raises the question as to whether the stem is assigned only one vowel which is copied or spreads to other syllables. Since kinyarwanda has open syllables only, loan-words with cluster consonants copy the vowel of the syllable on the right or a default vowel u with bilabial consonants and i with others. As the following work loan-word porogaramu 'program' shows, both vowels o and a are copied on the preceding vowelless consonants and the vowel u is inserted after the final consonant m.
# Kinyarwanda/Verbs
### Verbs

All Kinyarwanda verb infinitives begin with 'gu-' or 'ku-' (morphed into 'gw-' or 'kw-' before vowels). To conjugate, the infinitive prefix is removed and a prefix agreeing with the subject takes its place. Then a tense infix can be inserted.
Noun Prefix | Subject Prefix
Sing./Pl. | Sing./Pl.
u-mu-/a-ba- | a-/ba-
u-mu-/i-mi- | u-/i-
i-(ri)-/a-ma- | ri-/a-
i-ki- (i-gi-)/i-bi- | ki- (morphs to cy- before vowels)/bi-
i-n-/i-n- | i-/zi-
u-ru-/i-bi- | ru-/bi-
a-ka-/u-tu- | ka-/tu-
u-bu-/u-bu- | bu-/bu-
u-ku-/a-ma- | ku-/a-
a-ha-/a-ha- | ha-/ha-
The prefixes for pronouns are as follows.
I = n-
you (sing.) = mu-
he = y-/a-
she = y-/a-
we = tu-
you (pl.) = u-
they (human) = ba-
Tense markers include the following.
-Ø- | Present
-ra- (morphs to -da- when preceded by 'n' | Present Progressive - to be doing
-za- | Future - will do
-racya- | to still be doing
The past tense can be formed by using the present and present progressive infixes and modifying the aspect marker suffix.
# Kinematics/Transformations

Kinematics and SL(2,R)
Kinematics is the study of motion without regard to force or momentum. SL(2,R) is the special linear group of 2 x 2 real matrices with determinant 1. It is a continuous group of three dimensions as the four matrix entries are constrained by determinant fixed at 1.
The coordinate plane may be taken as a frame of reference (t, x). When an element of SL(2, R) acts on the coordinate plane, the area of figures is preserved due to the determinant condition. Some matrices yield a rotation of the plane, which preserves distance as well as area. Kinematic transformations with zero acceleration are expressed by matrices that preserve area but not distance.
The first instance is linear motion of velocity v where a new position of x, after time t, is x + vt. The linear transformation is expressed:
    $(t,x){\begin{pmatrix}1&v\\0&1\end{pmatrix}}=(t,tv+x).$
It is called a shear transformation in linear algebra. This shear transformation is part of classical mechanics and has been replaced in the electronic age as follows:
The supreme velocity in kinematics is the velocity of light c, so a kinematic velocity v satisfies v < c or v /c < 1. The concept of rapidity is introduced using hyperbolic angles and the hyperbolic tangent function. This function is also bounded above by 1, so rapidity w satisfies tanh w = v /c. Change of frame of reference is accomplished by hyperbolic rotation:
    $(t,x){\begin{pmatrix}\cosh w&\sinh w\\\sinh w&\cosh w\end{pmatrix}},$
where cosh w is hyperbolic cosine of w and sinh w is hyperbolic sine of w. The trigonometric identity
    $\cosh ^{2}w-\sinh ^{2}w=1$ confirms that the transformation is in SL(2, R).
Velocity measured with hyperbolic angle uses wings for units, where one wing is the speed of light in water as w:Ludwik Silberstein notes on page 181 of The Theory of Relativity (1914). More modest speeds are commonly described in miles per hour (mph) in English measure. Naturally one mph is 1 mile/3600 seconds compared to c = 186,000 miles per second. The ratio 1 mph/c is about 1.5 x 10$^{−9}$. Thus the rapidity w for one mph satisfies tanh w = 1.5 x 10$^{−9}$.
Since the derivative of tanh w is sech$^2$ w, the maximum rate of change of tanh w is one when w=0, and away from zero the slope of tanh nears zero. So for small values of w, tanh behaves as the identity function. Thus the rapidity corresponding to a mile per hour is 1.5 nanowings where a nanowing is 10$^{−9}$ wings. A hundred mile per hour fastball has 150 nanowings rapidity. A kilometer per hour is 0.9375 nanowings.
Recall that rotations are in SL(2,R) and note the angular measure of these transformations. The classical and modern transformations for linear motion also have angular measures: differences of slope and hyperbolic angle. See Geometry/Unified Angles for details.
# Kirby Super Star

Kirby Super Star is a Super Nintendo game released at near the end of the system's life cycle. It actually has many modes to play and lots of abilities. Many Kirby fans agree this is one of the best Kirby games with a lot of replay value. In 2008, it received a remake for the Nintendo DS, Kirby Super Star Ultra, which has even more features.

## Table of Contents
### General

* Basic Controls
* Abilities

### Games

* Spring Breeze
* Dyna Blade
* The Great Cave Offensive
** Treasure locations
* Meta Knight's Revenge
* Milky Way Wishes

### Extra games

* Samurai Kirby
* Megaton Punch
* Gourmet Race
# LMIs in Control/Stability Analysis/Deduced LMI Conditions for H-infinity Index

H-infinity Index Deduced LMI
Although the KYP Lemma, also known as the Bounded Real Lemma, is a basic condition to evaluate an upper bound on the H$_∞$, the verification of the bound on the H$_∞$-gain of the system can be done via the deduced condition.

## The System

A state-space representation of a linear system as given below:
    ${\begin{aligned}{\dot {x}}(t)&=Ax(t)+Bw(t)\\y(t)&=Cx(t)+Dw(t)\end{aligned}}$
where $x(t)\in \mathbb {R} ^{n}$, $y(t)\in \mathbb {R} ^{m}$ and $w(t)\in \mathbb {R} ^{r}$ are the system state, output, and the disturbance vector respectively. The transfer function of such a system can be evaluated as:
    ${\begin{aligned}G(s)=C(sI-A)^{-1}B+D\end{aligned}}$

## The Data

Number of states n, number of outputs m and number of external noise channels r need to be known. Moreover, the system matrices A,B,C,D are also required to be known.

## The Feasibility LMI

For an arbitrary $\gamma$, the transfer function G(s) satisfies
    $\left\|G(s)\right\|_{\infty }<\gamma$
if and only if there exists a symmetric matrix X > 0 and a matrix $\Omega .$ such that:
       ${\begin{aligned}{\text{Find}}\;X,\Omega :&\\\Theta +\Phi ^{\top }\Omega \Psi +\Psi ^{\top }\Omega ^{\top }\Phi <0\end{aligned}}$
where:
       ${\begin{aligned}\Theta &={\begin{bmatrix}0&X&0&0&0\\X&-X&0&0&0\\0&0&-\gamma I_{m}&0&0\\0&0&0&-X&0\\0&0&0&0&\gamma I_{r}\end{bmatrix}}\\\Phi &={\begin{bmatrix}-I_{n}&A^{\top }&C^{\top }&I_{n}&0\\0&B^{\top }&D^{\top }&0&-\gamma I_{r}\end{bmatrix}}\\\Psi &={\begin{bmatrix}I_{n}&0&0&0&0\\0&0&0&0&I_{r}\end{bmatrix}}\end{aligned}}$
The above LMI can be combined with the bisection method to find minimum $\gamma$ to find the minimum upper bound on the H$_∞$ gain of $G(s)$.

## Conclusion:

If there is a feasible solution to the aforementioned LMI, then the $\gamma$ upper bounds the infinity norm of the system G(s).

## Implementation

To solve the feasibility LMI, YALMIP toolbox is required for setting up the feasibility problem, and SeDuMi is required to solve the problem. The following link showcases an example of the feasibility problem:
https://codeocean.com/capsule/1465618/tree

## Related LMIs

Bounded Real Lemma

## External Links

A list of references documenting and validating the LMI.
* LMIs in Control Systems: Analysis, Design and Applications - by Guang-Ren Duan and Hai-Hua Yu, CRC Press, Taylor & amp; Francis Group, 2013, Section 5.2.2 pp. 153–156.
# LMIs in Control/Stability Analysis/Discrete Time/DiscreteTimeStrongStabilizability
## The System

Consider the continous-time LTI system, $G:L_{2e}\rightarrow L_{2e}$ with state-space realization ($A_{d},B_{d},C_{d},0$)
    ${\begin{aligned}{\dot {x}}(k)&=A_{d}x(k)+B_{d}u(k),\\y(k)&=C_{d}x(k),\end{aligned}}$
where $A_{d}\in \mathbb {R} ^{n\times n}$, $B_{d}\in \mathbb {R} ^{n\times m}$, $C_{d}\in \mathbb {R} ^{p\times n}$, and it and it is assumed that ($A_{d},B_{d}$),is stabilizable, ($A_{d},C_{d}$) is detectable, and the transfer matrix $G(s)=C_{d}(s1-A_{d})^{-1})B_{d}$ has no poles on the imaginary axis.

## The Data

The matrices $A_{d},B_{d},C_{d}$.

## The Optimization Problem

The system G is strongly stabilizable if there exist $P\in \mathbb {S} ^{n}$, $Z\in \mathbb {R} ^{n\times p}$, and $\gamma \in \mathbb {R} _{>0}$, where $P>0$, such that
    ${\begin{aligned}{\displaystyle {\begin{aligned}{\begin{bmatrix}A_{d}^{T}PA_{d}-P-A_{d}^{T}ZC_{d}-C_{d}^{T}Z^{T}A_{d}&&C_{d}^{T}Z^{T}\\*&&-P\\*&&*&&-\gamma I\end{bmatrix}}<0\end{aligned}}}\\{\displaystyle {\begin{aligned}{\begin{bmatrix}N_{11}&&(A_{d}+B_{d}F)^{T}Z&&XB_{d}&&C_{d}^{T}Z^{T}\\*&&-\gamma I&&0&&Z^{T}\\*&&*&&-\gamma I&&0\\*&&*&&*&&-P\end{bmatrix}}<0\end{aligned}}}\\\end{aligned}}$

## Conclusion:

where $N_{11}=(A_{d}+B_{d}F)^{T}P(A_{d}+B_{d}F)-P+(A_{d}+B_{d}F)^{T}ZC_{d}^{T}Z^{T}(A_{d}+B_{d}F),F=-B_{d}^{T}X,X=Y$ and $X\in S_{n}$ , $X\geq 0$ is the solution to the discrete-time Lyapunov equation given by
    ${\begin{aligned}A_{d}XA_{d}^{T}+X-B_{d}B_{d}^{T}X=0\end{aligned}}$
Moreover, a controller that strongly stabilizes G is given by the state-space realization
    ${\begin{aligned}{\dot {x}}_{c,k+1}=(A_{d}+B_{d}F+P^{-1}ZC_{d})x_{k}-P^{-1}Zu_{k}\\y_{c,k}=-B_{d}^{T}Xx_{k}\end{aligned}}$

## Implementation

* -example code

## Related LMIs

* https://en.wikibooks.org/wiki/LMIsinControl/StabilityAnalysis/ContinuousTime/StrongStabilizability - Continuous Time Strong Stabilizability

## External Links

* http://control.asu.edu/MAE598_frame.htm LMI Methods in Optimal and Robust Control- A course on LMIs in Control by Matthew Peet.\\
* https://https://arxiv.org/abs/1903.08599/ LMI Properties and Applications in Systems, Stability, and Control Theory] - A List of LMIs by Ryan Caverly and James Forbes.\\
* https://web.stanford.edu/~boyd/lmibook/ LMIs in Systems and Control Theory- A downloadable book on LMIs by Stephen Boyd.
# LMIs in Control/Stability Analysis/Continuous Time/Transient Output Bound for Non-Autonomous LTI Systems
## The System

Consider a continuous-time LTI system with a state-space representation of:
${\dot {x}}=Ax+Bu,$
$y=Cx,$
where $A\in \mathbb {R} ^{n\times n}$, $B\in \mathbb {R} ^{n\times m}$, $C\in \mathbb {R} ^{p\times n}$ and $x(0)=x_{0}$,
the transient bound on the output can be evaluated with the following LMI.

## The Data

$A\in \mathbb {R} ^{n\times n}$, $B\in \mathbb {R} ^{n\times m}$, $C\in \mathbb {R} ^{p\times n}$ and $x(0)=x_{0}$.

## The LMI:

The Euclidean norm of the output satisfies
$\lVert y(T)\rVert _{2}^{2}\leq \gamma ^{2}(\lVert x_{0}\rVert _{2}^{2}+\lVert u\rVert _{2}T^{2}),\forall T\in \mathbb {R} _{+},$
if there exists $P\in \mathbb {S} ^{p}$ and $\gamma \in \mathbb {R} _{++}$, where $P>0$, such that
* $P-\gamma I\leq 0,$
* ${\begin{bmatrix}P&C^{T}\\*&\gamma I\end{bmatrix}}\geq 0,$
* ${\begin{bmatrix}PA+A^{T}P&PB\\*&-\gamma I\end{bmatrix}}\leq 0.$

## Conclusion

By using these LMIs, the transient output bound can be found for a given non-autonomous LTI system such that if $x_{0}=0$ and $u$ is a unit-energy input (i.e., $\lVert u\rVert _{2}T^{2}\leq 1,\forall T\in \mathbb {R} _{+}$), then the preceding conditions ensure that $\lVert y(T)\rVert _{2}\leq \gamma ,\forall T\in \mathbb {R} _{+}$.

## Implementation

The LMI given above can be implemented and solved using a parser such as YALMIP, along with an LMI solver such as SeDuMi, or MOSEK. (For a detailed list of solvers, please visit this page on Relevant Solvers).

## References

Caverly, Ryan; Forbes, James (2021). LMI Properties and Applications in Systems, Stability, and Control Theory.
# LMIs in Control/Stability Analysis/Detectability LMI

LMIs in Control/Stability Analysis/Detectability LMI
This is a Template for Creating An LMI Page

## The System

    ${\begin{aligned}{\dot {x}}(t)&=Ax(t)+B_{p}p(t)+B_{w}w(t),\\z(t)&=C_{z}x(t)\\p_{i}(t)&=\phi _{i}(q_{i}(t)),i=1,\dots ,n_{p}\\q&=C_{q}x,\\0&\leq \sigma \phi _{i}(\sigma )\leq \sigma ^{2}\ \forall \sigma \in \mathbb {R} \end{aligned}}$

## The Data

The matrices $A,B_{p},B_{w},C_{q},C_{z}$.

## The LMI: The Lyapunov Inequality

Title and mathematical description of the LMI formulation.
       ${\begin{aligned}{\text{Find}}\;&P>0,\Lambda =diag(\lambda _{1},\dots ,\lambda _{n_{p}}),T=diag(\tau _{1}):\\{\begin{bmatrix}X\end{bmatrix}}&>0\\{\begin{bmatrix}A^{T}X+XA\end{bmatrix}}&<0\end{aligned}}$

## Conclusion:

Interpretation of the results of the LMI

## Implementation

A link to CodeOcean or other online implementation of the LMI

## Related LMIs

Links to other closely-related LMIs

## External Links

A list of references documenting and validating the LMI.
* LMI Methods in Optimal and Robust Control - A course on LMIs in Control by Matthew Peet.
* LMI Properties and Applications in Systems, Stability, and Control Theory - A List of LMIs by Ryan Caverly and James Forbes.
* LMIs in Systems and Control Theory - A downloadable book on LMIs by Stephen Boyd.
# LMIs in Control/Stability Analysis/Discrete Time/Polytopic Uncertainty/Open-Loop Robust Stability
## The System

Consider the set of matrices ${\mathbf {A}}=\{{\mathbf {A}}_{d}(\alpha )\in \mathbb {R} ^{n\times n}|{\mathbf {A}}_{d}(\alpha )=\Sigma _{i=1}^{n}\alpha {\mathbf {A}}_{d,i},{\mathbf {A}}_{d,i}\in \mathbb {R} ^{n\times n},\alpha _{i}\in \mathbb {R} _{\geq 0}\},\Sigma _{i=1}^{n}\alpha _{i}=1\$,

## The Data

The discrete-time LTI system ${\mathbf {x}}_{k+1}={\mathbf {A}}_{d}(\alpha ){\mathbf {x}}_{k+1}$ is asymptotically stable for all ${\mathbf {A}}_{d}(\alpha )\in \mathbb {\mathbf {A}}$ if there exists ${\mathbf {P}}\in \mathbb {S} ^{n}$ ,$i=1,...,n$ , and ${\mathbf {G}}\in \mathbb {R} ^{n\times n}$ , where ${\mathbf {P}}_{i}>0,i=1,...,n$ , such that
${\begin{bmatrix}{\mathbf {P}}_{i}&{\mathbf {P}}A_{d,i}^{T}{\mathbf {G}}^{T}\\*&{\mathbf {G}}+{\mathbf {G}}^{T}-{\mathbf {P}}_{i}\end{bmatrix}}<0.$ , $i=1,...,n$

## Implementation

This is used to get open-loop stability.

## Related Links

* LMIs in Control/Stability Analysis/Discrete Time/Transient Bound for Discrete-Time Non-Autonomous LTI Systems

## References

Caverly, Ryan; Forbes, James (2021). LMI Properties and Applications in Systems, Stability, and Control Theory.
# LMIs in Control/Stability Analysis/Discrete Time/Output Energy Bound for Autonomous LTI Systems

Output Energy Bound for Autonomous LTI Systems
Autonomous systems are initialized under a given set of initial conditions, and then run without any additional inputs. It is useful to know ahead of time the bounds such a system will operate within. This analysis can be used to determine the upper bound on the output of a given autonomous LTI system.

## The System

Consider the continuous-time, LTI autonomous system with state space representation
${\mathbf {\dot {x}}}={\mathbf {Ax}}$,
${\mathbf {y}}={\mathbf {Cx}}$,
where ${\mathbf {A}}\in \mathbb {R} ^{n\times n},{\mathbf {C}}\in \mathbb {R} ^{p\times n}$ and ${\mathbf {x}}(0)={\mathbf {x}}_{0}.$

## Determining an Upper Bound

The output of this system will satisfy
${\sqrt {\int _{0}^{T}{\mathbf {y^{T}y}}dt}}=\left\vert \left\vert {\mathbf {y}}\right\vert \right\vert _{2T}\leq \gamma \left\vert \left\vert {\mathbf {x}}_{0}\right\vert \right\vert _{2},\forall T\in \mathbb {R} _{\geq 0}$
if there exists some matrix ${\mathbf {P}}\in \S ^{p}$and scalar $\gamma \in \mathbb {R} _{>0}$ such that
${\mathbf {P}}>0$,
${\mathbf {P}}-\gamma {\mathbf {I}}\leq 0$,
${\begin{bmatrix}{\mathbf {PA}}+{\mathbf {A^{T}P}}&{\mathbf {C^{T}}}\\*&-\gamma {\mathbf {I}}\end{bmatrix}}\leq 0$.

## Conclusion

Given an autonomous system with an initial operating condition, the parameter $\gamma$ can be used to determine the largest feasible bound on the output of that system.

## External Links

A list of references documenting and validating the LMI.
* LMI Methods in Optimal and Robust Control - A course on LMIs in Control by Matthew Peet.
* LMI Properties and Applications in Systems, Stability, and Control Theory - A List of LMIs by Ryan Caverly and James Forbes.
* LMIs in Systems and Control Theory - A downloadable book on LMIs by Stephen Boyd.
# LMIs in Control/Stability Analysis/Continuous Time/Transient State Bound for Non-Autonomous LTI Systems
## The System

For a continuous-time LTI system with a state-space representation of:
${\dot {x}}=Ax+Bu$
where $A\in \mathbb {R} ^{nxn}$, $B\in \mathbb {R} ^{nxm}$ and x(0) = x$_0$,
the transient bound can be evaluated with the following LMI.

## The Data

$A\in \mathbb {R} ^{nxn}$, $B\in \mathbb {R} ^{nxm}$ and x(0) = x$_0$.

## The LMI:

The Euclidean norm of the state satisfies:
$\lVert x(T)\rVert _{2}^{2}\leq \gamma ^{2}(\lVert x_{0}\rVert _{2}^{2}+\lVert u\rVert _{2T}^{2}),\forall T\in \mathbb {R} _{\geq 0}$
if there exists $P\in \mathbb {S} ^{n}$ and $\gamma \in \mathbb {R} _{>0}$, where P > 0, such that:
* $P-\gamma 1\leq 0,$
* ${\begin{bmatrix}P&1\\*&\gamma 1\end{bmatrix}}\geq 0,$
* ${\begin{bmatrix}PA+A^{T}P&PB\\*&-\gamma 1\end{bmatrix}}\leq 0.$
if x$_0$ = 0 and u is a unit-energy input ($\lVert u\rVert _{2T}\leq 1,\forall T\in \mathbb {R} _{\geq 0}$), then the above LMIs ensure that $\lVert x(T)\rVert _{2}\leq \gamma ,\forall T\in \mathbb {R} _{\geq 0}$

## Conclusion

By using this LMI the transient state bound can be analyzed for a given non-autonomous LTI system.

## Implementation

The LMI given above can be implemented and solved using a tool such as YALMIP, along with an LMI solver such as MOSEK.

## Related LMIs

* Output Energy Bound for Autonomous LTI Systems

## External Links

* LMI Properties and Applications in Systems, Stability, and Control Theory - A List of LMIs by Ryan Caverly and James Forbes.
# LMIs in Control/Stability Analysis/Discrete Time

      * D-Stability
      * Discrete-Time Lyapunov Stability
      * LMI for Schur Stabilization
      * L2-Gain of Systems with Multiplicative noise
      * Discrete-Time Quadratic Stability
      * Output Energy Bound for Discrete-Time Autonomous LTI Systems
      * Transient Bound for Discrete-Time Non-Autonomous LTI Systems
      * Output Energy Bound for Discrete-Time Non-Autonomous LTI Systems
      * Transient Output Bound for Discrete-Time Autonomous LTI Systems
# Introduction to Information Literacy in the K12 Classroom/Chapter 1

Introduction to Information Literacy in the K12 Classroom/Table of Contents

# Introduction to Information Literacy in the K12 Classroom

This page will summarize what our book is about.
* describe the purpose of the book
* what the book is trying to teach
* who the audience is
* what the book's scope is
* what topics each chapter in the book will cover and any other relevant information about the book

## Importance in this Digital Age

Information literacy has become an important skill for students to gain before they enter real world. Information literacy can be defined as being able to recognize when information is needed and have the ability to locate, evaluate, and use it effectively . In the past there was one main way to get information and it was by going to a library and finding a published source. Technology has made more and more information readily available. The digital age has brought about new sources that in the past would never have been even thought of. The Internet provides us with a background on almost any topic imaginable. To be literate one must find the information in a reasonable amount time. Because there is so much information pinpointing what you need and what you don’t has become a necessary skill. Using the correct search engine and searching with the correct specifications could save you hours by locating the correct information. There is much more to being literate than finding information. You must be able to decipher between good and poor sources. Some websites have information that is inaccurate and has no basis. It is important that we are aware of where the information we gather originates. Each source must be evaluated before it is used. It is imperative that we model new ways of teaching and learning in today's society. We need to help our students be successful in the 21st century -- the world in which we now live is constantly changing. We need to help prepare our students for occupations that do not even exist today. We have transitioned from using desktop-based applications to new online tools, and ultimately we are able to work differently. The web is now highly interactive, not merely a one-way street where someone controls the content. We need to provide new tools to our students so that they are prepared for the new challenges our world will bring them.
# Introduction to Information Literacy in the K12 Classroom/Chapter 1.4

Here is the beginning of the research for our Chapter addition. We had teachers in mind when we started this page. It is a work in progress and we are always looking for more to add to it.
Here is a great site with a collection of sites for teaching Information Literacy.
Here is a link to a Wiki developed by 2 MLIS students at Syracuse University for grades 6-12: https://infolit.wikispaces.com/.
Here is a web article from TechLearning.com on Teaching Information Literacy: Tips and Resources: http://www.techlearning.com/article/1108.
Here is a site from Spokane Community College that contains a Faculty Toolkit for teaching information literacy: http://www.scc.spokane.edu/?libinfolittk.
Here is a link to an Information Literacy Weblog: http://information-literacy.blogspot.com/
Here is a site that provides many ways to use information literacy: http://www.libraries.psu.edu/instruction/infolit/andyou/infoyou.htm
# Introduction to Indonesian Philosophy
## Contents

   * Preface This is a wiki textbook -- feel free to edit it, update it, correct it, and otherwise increase its teaching potential. To find out more about wikis, see Wikipedia's page on wikis.
   * The Inner Faculty of Budi
   * Leluhur as Our First Philosophers
This book has just been merged into the book entitled Introduction to Philosophy. Please feel free to read it there.