บาฮามาส, สวรรค์วันหยุดที่ดีที่สุดคือปลายทางบังอาจมากที่เสนอช่วง sceneries สูงสุดไป. วันหยุดใน บาฮามาส cruising ดีสามารถแสดงให้คุณไปที่ชายหาดที่มีชื่อเสียงและโดดเด่นรีสอร์ททรายขาว. หากคุณกำลังค้นหาตื่นเต้นครอบครัวหรือแยกโรแมนติก, ล่องเรือ บาฮามาส จะหนีวันหยุดเหมาะสำหรับคุณ. คุณสมบัติสำคัญของวันหยุด cruising ใน บาฮามาส รวมถึงชายฝั่งแพคเกจท่องเที่ยวเช่นดำน้ำ,ให้อาหารฉลามและขว้างกับปลาโลมา. นอกจากนี้ยังมีเว็บไซต์จำนวนมากมาให้คุณไป. เกาะให้น้ำท่วมกิจกรรมและเสน่ห์ตั้งแต่การตั้งถิ่นฐานทำลายผู้จงรักภักดีและ Glass Window Bridge หยุดหลุมของโคลัมบัสใน New World ซึ่งเป็นระบบที่ใหญ่ที่สุดถ้ำใต้น้ำได้รับการยอมรับในปัจจุบัน. เพียงเลือกแพคเกจล่องเรือที่ดีที่สุดที่มีการผนวกนี้.

สภาพอากาศดีชาวโปรดปรานและการค้าการท่องเที่ยวที่มีชื่อเสียงให้ทั้งหมด festivities และเยี่ยมชมมากเสน่ห์และ doable. ร้านอาหารอนันต์, รีสอร์ท, ร้านค้าและตลาดจะพบว่าเป็นสาเหตุที่เกาะจะรับรู้เป็นชายหาดยอดเยี่ยมจากไปเป็นวันหยุด. เพื่อให้วันหยุดของคุณจำได้ง่ายคุณสามารถทำวิจัยในเทศกาลมากมายและ happenings ที่เกิดขึ้นและกำหนดจัดตามความสนใจของคุณแน่นอน. เหตุผลชัดเจนว่าทำไมนักท่องเที่ยวจำนวนมากที่ใช้วันหยุดใน บาฮามาส cruising ทุกปีเป็นที่รู้จักของทรายชายหาด. มีชายหาดอนันต์ในเกาะที่คุณอาจพบมากที่ล่องเรือพักผ่อนทุกปีที่ผ่าน.

ว่าคุณกำลังค้นหาความสนุกสนานสินค้าฟุ่มเฟือยหรือเพียงแค่ต้องการให้บ้านเป็นของที่ระลึกพิเศษเพื่อรำลึกถึงวันหยุดใน บาฮามาส cruising คุณสามารถค้นพบเลือกโดยดีเพื่อซื้อสิ่งในศูนย์การค้า. เหล่านี้ merchandises สินค้าประกอบด้วยทั้งที่บ้านผลิตสินค้าและชื่อทางการค้าสูง end. บาฮามาส คือชื่อเสียงฟางทำเช่นผลิตถุง; hats และบางสินค้าที่ผลิตภายใน. แนสซอแกรนด์ บาฮามาส เกาะสวรรค์เกาะมีหลายสถานที่หัวหน้าไปซึ่งทุกคนสามารถค้นพบสินค้าคุณภาพสูง.

Cruising วันหยุดใน บาฮามาส อาจเป็นทัวร์ระยะสั้นเหมาะสำหรับใครเพียงผู้รักธรรมชาติ. Panorama วิวที่นี่แน่นอนจะเชื่อมต่อคุณแผ่นดินแม่และจะให้อิสระยอดเยี่ยมจากความสับสนวุ่นวายของชีวิตประจำวันรวมทั้งประสบการณ์ของการผจญภัยที่น่าตื่นเต้น. มีหลายเกาะมัน บาฮามาส เป็นแน่นอนสวรรค์เขตร้อนของกิจกรรมมากมายที่พวกเขาให้. คุณสามารถ เดินทาง รอบพื้นที่ทั้งหมดโดยจักรยานหรือเพียงการพักผ่อนเดินลงหาดทรายสีขาวงดงาม.

พายเรือสนุกสนานในทะเล bordering ภูมิประเทศจะให้คุณได้รับโอกาสใกล้ชิดกับชีวิตทางทะเลประสบความสำเร็จ. หมู่เกาะเป็นตำนานสำหรับน้ำทึบในทั่วโลกที่สามารถมองเห็นถึง60 เมตร. บาฮามาส เป็นบ้านยังไปหลายโลกที่แปลกประหลาดที่สุด mammals ทะเลและปลาโลมาต้องการ whales. ที่ล่องเรือไป บาฮามาส คุณจะได้มีโอกาสดำน้ำลึกและพบแนวปะการังทะเลและอัศจรรย์และแปลกสัตว์ทะเล.

การเดินทางไปเกาะนี้ บาฮามาส แน่นอนคือความปิติยินดีสำหรับคนทั้งเด็กและผู้ใหญ่ควบคู่ไปกับกิจกรรมมากมายที่ดำเนิน. ว่าสิ่งที่คุณต้องการเพื่อเป็นเพียงใช้เวลาจมในทะเลนั้นดำน้ำหรือดำน้ำหรือเพียงสำรวจ sites วิวต่างๆเกาะสามารถให้คุณทั้งหมดนี้. ดังนั้นสำหรับ บาฮามาส พิเศษล่องเรือประสบการณ์พื้นที่เป็นสถานที่ยอดเยี่ยมเต็มด้วยความตื่นเต้น, สำรวจความเหงาโรแมนติกและหลายหลาย more.So เลือกแพคเกจล่องเรือที่ดีที่สุดสายเรือต่างๆมีให้ในวันหยุด cruising ของคุณ บาฮามาส.

For the past couple of years, I have had a couple of questions about machine learning research that I have wanted to ask some experts, but never got the chance to do so. I did not even know if my questions made sense at all. I would probably write about them on a blog post soon enough.

It is however ironical that I came to know my questions were valid and well discussed (I never knew what to search for them, I used expressions not used by researchers) only by the death of Ray Solomonoff (he was one researcher who worked on it, and an obituary on him highlighted his work on it, something I missed). Solomonoff was one of the founding fathers of Artificial Intelligence as a field and Machine Learning as a discipline within it. It must be noted that he was one of the few attendees at the 1956 Dartmouth Conference, basically an extended brain storming session that started AI formally as a field. The other attendees were : Marvin Minsky, John McCarthy, Allen Newell, Herbert Simon, Arthur Samuel,  Oliver Selfridge, Claude Shannon, Nathaniel Rochester and Trenchand Moore. His 1950-52 papers on networks are regarded as the first statistical analysis of the same.  Solomonoff was thus a towering figure in AI and Machine Learning.

[Ray Solomonoff  : (25 July 1926- 7 December 2009)]

Solomonoff is widely considered as the father of Machine Learning for circulating the first report on the same in 1956. His particular focus was on the use of probability and its relation to learning. He founded the idea of Algorithmic Probability (ALP)  in a 1960 paper at Caltech, an idea that gives rise to Kolmogorov Complexity as a side product. A. N. Kolmogorov independently discovered similar results and came to know of and acknowledged Solomonoff’s earlier work on Algorithmic Information Theory. His work however was relatively unknown in the west than in the soviet union, which is why Algorithmic Information Theory is mostly referred to as Kolmogorov complexity rather than “Solomonoff Complexity”. Kolmogorov and Solomonoff approached the same framework from different directions. While Kolmogorov was concerned with randomness and Information Theory, Solomonoff was concerned with inductive reasoning. And in doing so he discovered ALP and Kolomogorov Complexity years before anyone did. I would write below on only one aspect of his work that I have studied to some degree in the past year.

Solomonoff With G.J Chaitin, another pioneer in Algorithmic Information Theory

[Image Source]

The Universal Distribution:

His 1956 paper, “An inductive inference machine” was one of the seminal papers that used probability in Machine Learning. He outlined two main problems which he thought (correctly) were linked.

The Problem of Learning in Humans : How do you use all the information that you gather in life in making decisions?

The Problem of Probability : Given you have some data and some a-priori information, how can you make the best possible predictions for the future?

The problem of learning is more general and related to the problem of probability. Solomonoff noted that the Machine learning was simply the process of approximating ideal probabilistic predictions for practical use.

Building on his 1956 paper, he discovered probabilistic languages for induction at a time when it was considered out of fashion. And discovered the Universal Distribution.

All induction problems could be basically reduced to this form : Given a sequence of binary symbols how do you extrapolate it? The answer being that we could assign a probability to a sequence and then use Bayes Theorem to make a prediction on which particular continuation of a string was how likely. That gives rise to an even more difficult question that was the basic question for a lot of Solomonoff’s work and on Algorithmic Probability/Algorithmic Information Theory. This question is : How do you assign probabilities to strings?

Solomonoff approached this problem using the idea of a Universal Turing Machine. Suppose this Turing Machine has three types of tapes, an unidirectional input tape, an unidirectional output tape and a bidirectional working tape. Suppose this machine will take some binary string as input and it may give a binary string as output.

It could do any of the following :

1. Print out a string after a while and then come to a stop.

2. It could print an infinite output string.

3. It could go in an infinite loop for computing the string and not output anything at all (Halting Problem).

For a string , the ALP would be as follows :

If we feed some bits at random to our Turing Machine, there will always be some probability that the output would start with a string . This probability is the algorithmic or universal probability of the string .

The ALP would be given as :

Where would be the universal probability of string with respect to the universal turing machine . To understand the placement of in the above expression, let’s discuss it a little.

There could be many random strings that after being processed by the Turing Machine give an output string that begins with string . And is the such string. Each such string carries a description of . And since we want to consider all cases, we take the summation. In the expression above gives the length of a string and the probability that the random input would output a string starting with .

This definition of ALP has the following properties that have been stated and proved by Solomonoff in the 60s and the 70s.

1. It assigns higher probabilities to strings with shorter descriptions. This is the reverse of something like Huffman Coding.

2. The value for ALP would be independent of the type of the universal machine used.

3. ALP is incomputible. This is the case because of the halting problem. Infact it is this reason that it has not received much attention. Why get interested in a model that is incomputible? However Solomonoff insisted that approximations to the ALP would be much better than existing systems and that getting the exact ALP is not even needed.

4. is a complete description for . That means any pattern in the data could be found by using . This means that the universal distribution is the only inductive principle that is complete. And approximations to it would be much desirable.

__________

Solomonoff also worked on Grammar discovery and was very interested in Koza’s Genetic Programming system, which he believed could lead to efficient and much better machine learning methods. He published papers till the ripe old age of 83 and is definitely inspiring for the love of his work.  Paul Vitanyi notes that :

It is unusual to find a productive major scientist that is not regularly employed at all. But from all the elder people (not only scientists) I know, Ray Solomonoff was the happiest, the most inquisitive, and the most satisfied. He continued publishing papers right up to his death at 83.

Solomonoff’s ideas are still not exploited to their full potential and in my opinion would be necessary to explore to build the Machine Learning dream of never-ending learners and incremental + synergistic Machine Learning. I would write about this in a later post pretty soon. It was a life of great distinction and a life well lived. I also wish strength and peace to his wife Grace and his nephew Alex.

The five surviving (in 2006) founders of AI who met in 2006 to commemorate 50 years of the Dartmouth Conference. From left : Trenchand Moore, John McCarthy, Marvin Minsky, Oliver Selfridge and Ray Solomonoff

__________

Refernces and Links:

1. Ray Solomonoff’s publications.

2. Obituary: Ray Solomonoff – The founding father of Algorithmic Information Theory by Paul Vitanyi

3. The Universal Distribution and Machine Learning (PDF).

4. Universal Artificial Intelligence by Marcus Hutter (videolectures.net)

5. Minimum Description Length by Peter Grünwald (videolecures.net)

6. Universal Learning Algorithms and Optimal Search (Neural Information Processing Systems 2002 workshop)

__________

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]]> http://irresistibledisgrace.wordpress.com/2009/12/17/the-role-of-parsing-in-mormonism/ Fri, 18 Dec 2009 03:54:26 +0000 Andrew http://irresistibledisgrace.wordpress.com/2009/12/17/the-role-of-parsing-in-mormonism/

If you’ve read through the Mormon Bloggernacle long enough, then you’ve probably come across Ray (aka Papa D of Things of My Soul.) Ray is noteworthy for a great many things (for one, I have never seen Ray lose his cool. I have seen him express strong sentiments against Calvinism at rare times, but he seems to be one of the most level-headed people I know), but one of the things I find most striking is his affinity for parsing. Here’s an example from his site with Alma 56.

Ray goes through scriptures, line by line…part by part…teasing the explicit meanings from the faulty inferences that people may make. By pointing out these faulty inferences, he frees himself from questionable and undesirable viewpoints. You can see more here and here. Others have written about the vagueness that allows this possibly being a gospel principle.

Lots of places have talked about “Middle Way Mormonism” recently. If we can call call “Middle Way Mormonism” an emerging, yet somewhat loosely organized school of thought, then I think that one common aspect of it is parsing. And although Ray is the resident parser, I find many people in the “John Dehlinistic” school of thought use it in some way or fashion. OK, so now I’ll have to explain…

As Ray said in a comment to a post “Freedom and Honesty,” one can still express heterodox opinions within the church…if one is not a threat, then one will not be seen as a threat, then one will not be treated as a threat. (And there are other posts from others about how to go about not being a threat.)

This comment seems minor…but I think it’s important to Middle Way Mormonism.vIt forms a major part of John Dehlin’s philosophy in “staying LDS” after a major crisis of faith, and I see that people who have coalesced around Dehlin (wow, this sounds so much more…epic…than real life actually is) in ventures such as Mormon Matters, even if they have not faced major crises of faith, exhibit this kind of thinking. So often do I read blogs from faithful members — who regard themselves as such, true believers — who seem to have quite heterodox views.

I think it’s because they have found a way to be authentic within their heterodoxy. I mean heterodoxy in a greater sense than “well, everyone picks and chooses.” Even while I look at John Dehlin’s “How to Stay” essay and wonder about his section on answer the temple recommend interview (which I covered here, but read Dehlin’s thoughts here and ctrl+f for “Temple Recommend”), I can’t help but feel that this approach is a meta-game…a game about the Mormon language that “takes advantage of” the system by parsing out expectations about particular words and answers and then ceasing to live by those expectations and assumptions. I feel uneasy about this…how could I answer in such a way when I still wholeheartedly believe that the “assumptions” and “expectations” I’ve just parsed out are what other members think about when I assent to certain statements?

I made some comments on a Mormon Matters topic in this vein. This “creative honesty,” if caught, could lead one to be seen as a threat. John Dehlin, after all, doesn’t lack ideological enemies or people within the church who view him as a “wolf in sheep’s clothing.” So, I had a nagging suspicion that “creative honesty,” “parsing,” “the Middle Way,” and so on, were somewhat illegitimate. Somewhat sneaky. Somewhat underhanded.

But recently, I have come to realize that it’s not sneaky to use a tool of the trade…and in fact, perhaps the other side isn’t so innocent. I came across it from reading a blog post at The Post-Mormon Perspective responding to Daniel Peterson.

See, William, the post-Mormon in question, is reacting to apologist Daniel Peterson’s open and copious parsing with respect to the church and information about its history. Peterson’s contention (and a contention that some other apologists have shared) is that ex-Mormons harbor faulty, if popular inferences about the nature of inspiration, prophets, church history…and when these inferences are falsified, they become wrongly disaffected. The apologists would argue that proper parsing would show that Mormon prophets should not be held as infallible (despite what any popular interpretations of quotes, scriptures, doctrines, or rumors are), and in fact, one can see fallibility and defect from times of old to times today. The disaffection that so often strikes people when members learn “how history actually went” is unwarranted, because these members should’ve never believed in faulty inferences and unjustified conclusions about history, doctrine, no matter how plausible these seem or seemed. (So, apologetics often becomes something like, “Oh, yeah, so that seemingly negative claim about the prophet is…true. But it shouldn’t harm your faith; it shouldn’t be a dealbreaker because the prophet is still human.)

And then a thought struck me. If apologists or the church use this same system of parsing, cutting away what is believed to be “false expectations” or “faulty inferences,” (perhaps even “ignorance” and “sloth”) when it is convenient, then why should I have disdain for members who use this same crucial tool to take Mormonism back on their own terms? If everyone is playing the meta-game, then isn’t that meta-game fit and proper?

I absolutely love the idea of rating teachers by students.   In fact, I think it is a valuable way for the teacher, administrators and the public to get a read on what/how a teacher is doing. This allows for teachers to self reflect and plan a strategy to improve. These are all positive aspects of this system.

In order for the data to be accurate, it must be from a large enough sample (ex: at a middle or high school, say 100 students over two years), it must be anonymous and the sampling must be done at specific intervals.  The data must be for current teachers at a particular school and the data can not overlap from different subject areas, grades taught, etc. If the data is not managed, it becomes slipshod and does not help anyone do an effective evaluation or work on improvement.

When students are allowed to rate teachers randomly, as is the case with Ratemyteachers.com   ,  what happens is that teachers are allowed to (1) develop a personality cult if they so desire by having students ‘vote’ for them, especially multiple times (2) students are allowed to run a hate campaign at a teacher who may not have given them the grade they WANTED.  Parents and students are able to rig the system and determine how education is delivered by creating inaccurate data.

In theory, Ratemyteachers is great but in actuality it has many mistakes which make it a useless tool.

Example in point:   I have not worked at Wood Middle School in Alameda, CA for over three years and yet I am still on the posting for being rated. I currently live in Eldoret, Kenya and yet a student just rated me……….pretty interesting.

When I have tried to e-mail the website for removal, it can not be done as the captcha code on the website requires 3-D glasses that I do not have in Kenya.

Since I know enough about data, I find it more amusing at this point and would use this as a tool myself to evaluate a school administrator who puts any credence into the numbers. Ratemyteachers.com seems to do a fine job of not teaching statistics.…..oh, wait, isn’t that math?

My Penguin Osbert by Elizabeth Cody Kimmel is a story that will make children smile, connect, and wonder.  The theme fits the holiday season – children making their wish lists.  I especially like the letter writing feature that  begins the story.  A young boy, Joe, is writing his letter to Santa asking for a specific present.  Joe shares that he is being very specific about his request.  This book gives a good example of describing an object with specific language.

I also think the My Penguin Osbert will appeal to your boys.  The illustrator, H. B. Lewis, paints a two page spread of a red racecar in the beginning.  The main character, Joe, reminds me of my youngest. Since he has had difficulty getting the exact present that he wanted in years past, Joe goes all out and is detailed in the size, color, actions of his request.  Joes wanted a penguin, not a stuffed one, but a penguin from Antarctica. 

On Christmas morning, Santa game through.  To the delight of Joe, Osbert the Penguin is waiting for him.  Joe is ready to open more presents, but realizes his friend wanted to go outside and play.  Each time Joe wants to do something, he renders his wishes for his friend.  You can almost hear Joe’s thinking and sense his conflict. 

“But I had asked for Osbert, and now I had him.”

Osbert was the penguin he had asked for, but Joe did not realize that a penguin would be so much work.  Sound familiar with a pet?  After a while, Joe writes a secret letter to Santa.  He explains that he loves Osbert, but that if Santa thought Joe should have a different present, he would swap.  Santa does reply and sends Joe on an adventure to the Antarctic World exhibit at the zoo.  Osbert loves the exhibit and Joe relinquished his pet out of love.  In the end, Joe shares the lesson he has learned.

Savorings for reading and in writing for My Penguin Osbert:

• Adjectives – specific descriptions
• Letter writing -
• Inference – the clues will lead the children to conclude Joe’s reasoning for giving up his pet
• Varied Sentences – the author does an excellent job of writing long, complex sentences and then integrating some simple sentences.  “Then I waited.”
• Colon – used with a sign
• Hyphenated words – snow-globe; fire-engine-red

Retell: This is the biography of Cesar Chavez, the leader of the National Farm Workers Association who worked to organize farm workers to rally together and fight for better pay and working conditions.

Topics: family, Cesar Chavez, conflict, drought, California, farming, Spanish, migrant workers, unions, La Causa, strikes, protests, boycotts, farm workers

Units of Study: Nonfiction, Social Issues

Tribes: personal best, mutual respect, appreciations/no put-downs

Habits of Mind: persisting

Reading Skills: inference, interpretation, determining importance, synthesis, empathy

My Thoughts: Back when I taught in California this was required reading–in the Bay Area Cesar Chavez’s birthday is a school holiday.  This book could fit into different types of text sets.  For example, you could include this book when teaching a unit on the labor unit.  You could also choose to read this book as a companion text to Esperanza Rising.

Retell: During a drought, the Logan family shares water from their well with anyone who needs it, be they white or black.  Hammer, the narrator’s brother, finds it difficult to share with the Simms family who have tormented the Logans for being black.  After Hammer defends his brother David and beats up Charlie Simms, he and David are forced to work on the Simms’ farm to avoid jail.  Hammer, however, never quite manages to swallow his pride and gets involved in another altercation that causes Charlie to take revenge.

Topics: drought, racism, segregation, bullying, fighting, family

Units of Study: Historical Fiction, Talking and Writing About Texts, Social Issues

Tribes: mutual respect, right to pass, appreciations/no put-downs

Habits of Mind: managing impulsivity

Reading Strategies: inference, synthesis, interpretation, envisionment

My Thoughts: I’ve been trying to locate shorter chapter books to read aloud.  I’m finding that some of my favorite chapter books are too long to complete before the end of a unit. The Well is short, only 92 pages and can be completed within a month-long unit.  I think this could be a great book to read if a class is struggling with the issue of revenge.  In this story, Hammer cannot control his temper.  The situation is extremely unfair, and you empathize with Hammer for fighting with Charlie.  But on the other hand, his decision to take revenge led to his family’s well getting poisoned.  It raises the question whether or not it’s better to fight back with violence or fight back in other ways.

Recent research on children’s inferencing has found that although adults typically adopt the pragmatic interpretation of some (implying not all), 5- to 9-year-olds often prefer the semantic interpretation of the quantifier (meaning possibly all). Do these failures reflect a breakdown of pragmatic competence or the metalinguistic demands of prior tasks? In 3 experiments, the authors used the visual-world eye-tracking paradigm to elicit an implicit measure of adults’ and children’s abilities to generate scalar implicatures. Although adults’ eye-movements indicated that adults had interpreted some with the pragmatic inference, children’s looks suggested that children persistently interpreted some as compatible with all (Experiment 1). Nevertheless, both adults and children were able to quickly reject competitors that were inconsistent with the semantics of some; this confirmed the sensitivity of the paradigm (Experiment 2). Finally, adults, but not children, successfully distinguished between situations that violated the scalar implicature and those that did not (Experiment 3). These data demonstrate that children interpret quantifiers on the basis of their semantic content and fail to generate scalar implicatures during online language comprehension. (PsycINFO Database Record (c) 2009 APA, all rights reserved)

from Developmental Psychology

Hi guys!

Sorry to be posting late in the weekend. For tonight’s post, please write a a reading letter to me, consisting of two paragraphs:

Criteria for Success:

1. Dear Stabookski,

2. My username is: __________________

Retell what you’ve read in your book over the weekend. Explain whether or not you are in the exposition, rising action, climax, falling action or resolution of your book. This paragraph should be approximately 4 or 5 sentences long.

3. Second paragraph: Pick a digging deeper skill. You can write about a theme and the author’s perspective on that theme. You can write about a symbol (or more than one symbol). Explain what the symbol represents and how the author uses it in the story. You can write about any literary device (foreshadowing, figurative language, etc.) and how the author uses it in the text.

Paragraph 2 is all about digging deeper. It should be about 6 sentences long. Feel free to call me if you are at all confused. Good luck!

Love,

Stabookski

Retell: James has always wanted to play basketball on the main court.  Knowing that he’s too young and too small, he practices on the side court.  One day a player gets injured and he volunteers to play.  Though he misses shots and fouls other players, he gains his courage and ends up winning the game.

Topics: basketball, courage, playground, body image, boys

Units of Study: Realistic Fiction, Personal Narrative

Tribes: personal best, appreciations/no put-downs

Reading Skills: envisionment, inference

Writing Skills: incorporating similes, alliteration, using commas to list action, balancing internal thinking, action and dialogue

My Thoughts: This book was hiding on my read aloud shelf in my classroom.  I forgot all about it and now I’m kicking myself for not reading it to my class during our recent Realistic Fiction unit.  This is a fantastic small moment mentor text.  The events of the story are few:  a boy practices, enters a game, struggles, and wins.  However through a balance of internal thinking, small action and dialogue, the author creates a suspenseful, meaningful story.

Retell: One evening Rosalinda awakes to find a man stealing lemons from her lemon tree.  During the theft, a branch is broken and the tree becomes sick.  Rosalinda searches her village for a cure.  A mysterious woman helps her cure her sick tree and help a family in need.

Topics: theft, family, community, trees, kindness

Units of Study: Realistic Fiction, Social Issues, Talking and Writing About Texts

Tribes: personal best, mutual respect

Habits of Mind: thinking flexibly

Reading Skills: empathy, interpretation, inference, monitoring for sense

Writing Skills: using words to describe sound, using interesting verbs, incorporating foreign languages

My Thoughts: This is a text that can be useful for many units and for many purposes.  As I was reading this text I immediately noticed the beautiful verbs the author uses.  A reader who is unfamiliar with the vocabulary in the text can easily figure out the meaning of the words by thinking about the context.  It’s a great text for teaching the strategy of playing ‘fill in the bank’ when solving tricky words.

Retell: Each year Tony’s family boards the ferry to Liberty Island at grandma’s insistence.  They brave the crowds and the cold to celebrate a special birthday.

Topics: New York, family, Statue of Liberty, grandparents, immigration

Units of Study: Social Issues, Talking and Writing About Texts

Tribes: mutual respect

Reading Skills: prediction, envisionment, inference, questioning

My Thoughts: This book is typically read during an Immigration unit.  However I don’t think I can wait that long to read this book.  A scene that stuck out for me was the part when Tony helps a young woman who pulls on his jacket, worried that the last boat has left.  Apparently no one has been able to help her because she doesn’t speak English.  Tony is patient with her and through gestures explains that another boat is on the way.  When reading this aloud, I plan on emphasizing this moment and hope it will spark a meaningful discussion about how we can help students who have limited English skills.

This is a great text for modeling expression.  Each character has a distinctive personality which may come out best if the reader creates voices for each character.  For example, Rosa talks in “a reading kind of way” and should sound official (or as we say in conferences “like a teacher”).  Mike seems a bit mischievous and should sound like it.

Retell: Jane Yolen poetically compares the rainforest to a green house.

Topics: rainforest, animals, birds, nonfiction poetry

Units of Study: Nonfiction, Content-Area, Personal Essay

Habits of Mind: gathering data through all senses

Reading Skills: envisionment, inference

Writing Skills: using repetition, incorporating rhythm and rhyme, using sparkling vocabulary, using alliteration

My Thoughts: A few months ago I received a GrowLab through a DonorsChoose grant.  We received support from an educator at the Brooklyn Botanic Gardens and created corsage box terrariums.  Students planted cuttings from three different plants that thrive in the rainforest.  I plan on reading this book soon to support our gardening experience.  The text in this book is so vivid that as I read it I can actually feel the humidity of the rainforest.  It’s a great text for teaching students how to interpret metaphors.  At the end of the book, the author writes a message to her readers encouraging us to find out more about saving the rapidly disappearing rainforest.  Though it’s not technically a personal essay, you could use sections of the message as a mentor text.

Retell: After Max is sent to bed without supper he imagines traveling to a world where he becomes king of the wild things.  Being a wild things is fun for awhile but he learns that it cannot compare to the comforts of home.

Topics: monsters, mischief, disobedience, imagination, travel, dreams, home

Units of Study: Fantasy, Talking and Writing About texts

Habits of Mind: creating-innovating-imagining

Reading Skills: envisionment, inference

Writing Skills: using repetition, crafting endings that connect to the beginning

My Thoughts: I dressed up as a wild thing for our recent school Halloween parade.  I looked more like a hairy viking than a wild thing, but I get points for trying.  To introduce my costume I read this book aloud.  Many of them had heard it before.  I’m glad I was able to tuck in this classic read aloud before the majority of my students head to the cinema to see the movie.  Upon rereading it, I realized that one has to do a huge amount of envisionment as they read the text.  The illustrations are wonderful, but they don’t reveal all.  When reading this book aloud I recommend using the pages where there is no text to have your students (or your own children) role play and act like Max or the wild things.  You can encourage them to make noise like them, talk like them, move like them and think like them.

Now that you’ve been blogging for 2 days, I am going to see if you can do this without my model post…

CRITERIA FOR SUCCESS

1. Username

2. Retell (briefly in 2-3 sentences) what you read this evening.

3. Today’s skill is: INFERENCE… Make a prediction, draw a conclusion or critique the text. INFER about the text and make more of what you read… (2-3 sentences)

Good luck!

Love,

Ms. Stabookski

Retell: Rudy Soto yearns to fly.  He climbs up a cliff and captures a young hawk in the hope that he will be able to become brothers with the hawk and thus have a sense of what it means to fly.  Eventually he sets the hawk free and is forever changed.

Topics: hawks, dreams, flying, keeping pets, freedom

Units of Study: Talking and Writing About Texts, Social Issues

Tribes: mutual respect

Reading Skills: questioning, inference, interpretation, synthesis

Writing Skills: using alliteration

My Thoughts: Each year the issue of whether or not to get a class pet comes up.  I have mixed feelings about class pets.  I think they can be very useful for studying life cycles and animal habitats, but I don’t like the idea of animals in cages.  I may read this book the next time the issue arises in my classroom.  It will be an essential text during the interpretation unit and could also be an interesting one to read or reread during Social Issues.

When I was looking for images of this book I came across a website with a fantastic resource.  Through the Magic Door is an online bookstore that has put together some fabulous lists of books that may be very useful when making text sets.  Hawk, I’m Your Brother can be found under the list of books that are all about Flying.

Retell: Masako is a Japanese-American who moves to Japan after spending her childhood in America.  Adjusting to life in Japan is rough for Masako.  She must repeat high school in order to learn Japanese, her classmates call her gaijin (a derogatory word for ‘foreigner’), and she must learn how to be a proper Japanese lady.  One day she boards a bus for Osaka and finds work, a companion and a cure for her homesickness.

Topics: English, Japanese-Americans, homesickness, culture shock, matchmaking, individuality

Units of Study: Character, Social Issues, Personal Narrative, Memoir

Tribes: right to pass

Habits of Mind: taking responsible risks, thinking flexibly

Reading Skills: inference, interpretation, prediction, empathy

My Thoughts: I especially enjoy Tea With Milk because I have a personal connection to this book.  I taught English for three years in a rural village in Japan.  I can relate to May and her struggle to get used to sitting on the floor (women are expected to sit on their knees–it’s considered rude to sit cross-legged) and missing comfort foods.  When I read this book I thought of my students who often visit the countries where their parents are from and experience an identity crisis similar to the one that May faced.  I hope that this book inspires them to write their stories.  Though this is technically a personal narrative (the main character was the author’s mother) you could angle this to fit in many different units including the current Character unit.  It’s particularly useful for modeling how readers notice subtle changes in a character.

This is Part 3 of my series on using exploratory and inferential data analysis (“EDA”) to solve practical problems in complex environmental scenarios. Part 1 defined EDA and Part 2 was an example of using EDA to assess sediment toxicity in a lake. This second example addresses a lawsuit against a major manufacturing facility and how, as an expert witness, I used EDA to show that the accused manufacturer could not be held liable for metal contamination of neighborhood soils.

Example 2: Big Z Corporation Litigation

This EDA addressed a lawsuit where a company was being sued for air and soil contamination. Although a real circumstance, the specifics of this example have been modified to maintain client anonymity.

Big Z Corporation (“Big Z”), was being sued by a regional authority (“RA”), and accused of contaminating soils in the vicinity of Big Z with zinc (“Zn”) via air deposition over a period of years. To press the suit, the RA collected soil samples from a large number of locations outside the boundaries of Big Z and had them analyzed for Zn and certain other metals. Because Big Z was assumed to be the largest user of Zn in the area, the finding of high Zn concentrations in many of the soil samples was sufficient for the RA to blame Big Z and incorporate this claim into the lawsuit, using the soil samples as evidence.

As the soil chemistry expert for Big Z and their attorneys, I performed EDA on soil concentration data obtained from the RA via the lawsuit to determine whether there was information in these data that would either indicate that Big Z was, or was not, the likely source for the metal contamination. The analyses presented in this paper are a subset of the EDA that was done, but were the central components.

Approach

The soil data were subjected to a variety of comparative, statistical and geographical information system (“GIS”) mapping procedures. This was done to assess whether sufficient information was contained in the analyses and concentration distributions to point to Big Z as the source or whether other sources might be responsible. Other sources could include natural soil mineralogy, historic activities, or other facilities. Initial procedures included comparison of the soil metal concentrations to Michigan’s regulatory requirements, the Part 201 Residential and Commercial 1 Generic Cleanup Criteria and Screening Levels, and to those concentrations found by the Michigan Background Soil Survey 2005.

Statistical evaluation procedures for the soil samples involved a range of analyses including simple descriptive statistics of individual analyte concentrations (mean, median, range, skewness, etc.) along with spatial, trend and regression analyses in an attempt to determine whether any information could be gleaned from these soil data that might indicate the metal sources. Tabulations of the metal analyte concentration data, comparisons of the concentrations to Part 201 criteria and background soil concentrations, as well as simple descriptive statistics and GIS maps depicting the concentration distributions of these metals across the sampled areas (with concentrations color-coded relative to Part 201 criteria), were compiled.

To develop a context for the EDA results, it was important to look at the industrial and urban uses of Zn, because the location of Big Z and the surrounding soils is in an area that has been highly industrialized for more than a century. In that regard, the specific industrial and commercial activities that occurred within and surrounding that area were also investigated, providing additional context for the soils data and the results of the EDA. Investigations such as these are useful and important because the EDA results can be supplemented and supported by them. The results of these preliminary investigations showed that Zn had been widely used and disseminated for more than a century in the area and that the natural soil background in the area had higher than average Zn concentrations, as did a lot of the industrial fill materials that had been used to level numerous properties across the region.

Sample concentration and location data were input into either a Microsoft Excel spreadsheet or the EDA program Aabel (Gigawiz.com) and transposed, coded or reorganized when necessary for GIS, data plotting or statistical analyses. Certain GIS displays of the concentration versus location data were done in the program ArcView 9.0 (not displayed here). Most of the statistical data analyses and visualizations were done in Aabel, although certain of the data were also evaluated using the R statistical program and some confirmatory statistics were carried out using the DataDesk program.

GIS displays did not sufficiently clarify the distribution of the Zn in the sampled areas relative to Big Z. To determine whether patterns of soil deposition might emerge in relation to potential sources using other approaches, transects were developed along lines of samples to establish whether there was any directionality to the distribution of the metals. Zn was chosen because this particular metal would be the one most expected to point to Big Z if this facility was the sole or even a primary source of Zn in the soils.

In terms of evaluating the transects analysis it was hypothesized:

1. A positive likelihood of Big Z being the source could be shown by a general increase in Zn concentrations as transects of soil samples directionally approached the Big Z property boundary (i.e., consistently increasing soil concentrations with approach to the facility); this result would require a plurality of transects showing this pattern.
2. A negative likelihood of Big Z being the source could be shown by decreases in, or randomness of, Zn concentrations as transects of soil samples directionally approached the Big Z property boundary (i.e., decreasing or random soil concentrations with approach to the facility).
3. A pattern of high soil concentrations at a generally consistent distance along the transects from the Big Z property boundaries might imply Zn sourcing by the Big Z facility (maximum soil deposition at a fairly consistent distance from the facility).
4. A random relationship in soil Zn concentrations, with respect to Big Z boundaries, increases the likelihood of numerous, possibly localized, sources for the Zn.

Following the transect analyses, an analysis of spatial concentration “zones” with distance from the Big Z property boundaries was done; the hypotheses for this analysis were essentially the same as for the transect analyses.

Results

Figure 6 provides an overview for the transect analyses, showing all Zn data in the vicinity of Big Z. This plot, created in the program Aabel, depicts:

• Big Z property boundaries (light blue area)
• Soil sample locations (all westerly of Big Z)
• Transects across the soil locations
• The general location of the Big Z operations
• Other potential stationary industrial emission sources (by facility code)
• Color-filled contours for the Zn concentrations to show areas of higher Zn concentration versus lower.

Figure 6. Sampling Locations, Transect Overview, and Zn Concentrations

The transect overview in Figure 6 displays information about sampling points that were high statistical lognormal outliers at the 95% upper confidence level for one or multiple metals (i.e., they were outside the expected concentration range based on the complete body of data at 95% confidence), which could potentially be called “hotspots,” highlighted by the type of marker:

• A small yellow-tan circle indicates that no constituents were outliers relative to the body of the data at that sampling location.
• A circular red “beach-ball” marker indicates a sampling location was an outlier for a metal other than Zn.
• A hexagonal black marker indicates the sample location was an outlier only for Zn.
• A hexagonal red marker indicates that the sample location was an outlier for Zn and at least one of the other metals.

The transects in Figure 6 are shown as orange lines or polygons. The distal end (furthest away relative to the Big Z facility) of the transect line/polygon is labeled with a capital letter and a prime symbol ( ‘ ) and the proximal end (closest to Big Z) with just a plain capital letter; for example “A’ – A” signifies a transect. A total of nine transects were done on each dataset and labeled A’ – A through I’ – I. Each transect was subjected to regression analysis, i.e., Zn concentration versus distance from the Big Z property boundary as well as individual visualization using either bubble charts or spatial bar charts. An example is provided in Figure 7 for transect A’ – A.

Figure 7. A' - A Zinc Concentration Transect

Reviewing all the figures, such as Figure 7, which displayed linear regressions of the concentration data transects showed that the r² values were quite low, indicating that linear distance/direction along the transect line towards Big Z does not account well for the concentrations of Zn. It is also observed that the slopes of the regression lines are generally not very large in either direction while scatter of the points about those lines is relatively large, supporting the r² determinations and the general lack of trending in concentration versus distance from the Big Z property.

Table 2 summarizes the r² and slope values for each transect and states whether the slopes showed increasing Zn trends toward or away from the property. The table shows that there were similar numbers of transects with slopes in either direction. This tends to support the rather dispersed random-appearing hotspots and colored contours of Figure 6. These results also support Hypotheses 2 and 4 (above), or randomness of Zn concentrations relative to the Big Z property boundaries and the likelihood of numerous localized Zn sources.

Table 2. Transect Regression Data for Zinc

As an additional check on the spatial relationship of the Zn concentrations in the soil samples relative to the Big Z boundaries, the Zn data were separated into five spatially equivalent zones corresponding to surface areas replicated using the approximate shape of the Big Z boundary, extended westward across the soil sampling space. These zones were numbered one through five and are depicted in Figure 8.

Figure 8. Spatial Zones for Zinc Analysis

All the soil samples within a zone were selected as a group and the Zn concentrations within each zone’s group were compared to all the other zones, and the total of all the zones, using statistical methods. The comparisons consisted of one-way analysis of variance (ANOVA) combined with diamond plots, to compare the means, and box and whiskers plots to compare the medians. The ANOVA and mean tables along with these plots are provided in Figure 9.

Figure 9. Comparisons of Zone Means and Medians for Zinc

The diamonds in the “diamond means comparison plots” (left, Figure 9) show the concentration means (central line in each diamond) and 95% confidence intervals of those means (tips of the diamonds) for each zone relative to the grand mean of all zones combined (dashed line across the entire plot) and to one another. When the diamonds overlap, at all, the means for each zone cannot be considered different with 95% confidence. However, when they don’t overlap, the means can be considered different. In this case, the means for all five zones are almost exactly equal to one another, and to the grand mean, and the diamonds fully overlap.

The same holds true for the medians (straight connected lines) in the box and whiskers plot of Figure 9 (right plot), with very small differences in their values and overlap of the 95% confidence “notches” surrounding the medians. The overlap of the notches indicates that the medians cannot be considered different with 95% confidence. These statistical plots indicate no significant differences in the means or the medians of the five zones as one progresses westward away from the Big Z property boundary. The plots are fully supported by both the mean and ANOVA tables in Figure 9. The means, standard deviations, and both lower and upper 95% confidence intervals are almost identical in the means table while the ANOVA table yields a probability (column “P > F”) that indicates none of the means has a significantly different value from the others. The average amount of Zn in the soils is the same, whatever the distance from Big Z.

To further eliminate any doubts or questions about the equivalency of the Zn means and overall zone concentrations, two additional modifications were made to the data for further comparison (figures not shown): (1) The natural log (ln) values of the Zn concentrations within each zone were similarly evaluated and there were still no significant differences between the means and medians. (2) Likewise, all potential statistical Zn high outliers were removed from the evaluations with the same result; no significant differences between means or medians.

These concentration zone results, particularly when combined with the transect analyses, show that there is no spatial relationship of Zn soil concentrations to Big Z whatsoever and make it virtually impossible that the source is solely Big Z activities. It would be difficult or impossible to envision a scenario in which the mean soil concentrations of Zn would be exactly the same at any zonal distance from a facility in an urban area if that facility was to blame for the concentrations of the Zn in those soils. The results are far more indicative of long-term widespread deposition from numerous sources, combined with high native Zn topsoil content and with many instances of localized inputs (hotspots) that account for the high Zn values that were found in a few of the samples.

In summary, the EDA of the Zn soil data seem to indicate that Big Z was not predominantly responsible for the Zn present in the soils within the area.

SUMMARY AND CONCLUSIONS

Using the techniques of exploratory data analysis, particularly with current software packages, can be a rapid and effective way to formulate and test hypotheses using real-world data to achieve the goals and requirements of understanding site scenarios. It allows insight into the relationships among the data components through visualization of the data and elucidation of their patterns, trends and associated statistics. EDA allows the development of conceptual site models that are reality-based and are generally easy for clients and regulators to understand. It is particularly helpful for complex sites or when trying to answer complex questions about a site.

I have presented two examples of how EDA was used to resolve specific and important environmental questions. In the first example, it was possible to develop a general understanding of the locations, structure and relationships among the contaminants in Manistee Lake sediments in Michigan. EDA was then used to assess whether single contaminants or suites of contaminants were responsible for the toxic effects of the sediments on benthic organisms and then identified the most likely suite and source from all the possible contaminant combinations. Based on these results an “Action Plan” for the stakeholders and a further refined plan for sampling Manistee Lake were developed.

In the second example EDA was used, in conjunction with an historic and current understanding of the sampled area, to show in the context of a litigation that it was not possible for a company to have been the sole or primary cause of metals contamination in residential soils west of the facility.

REFERENCES

Note: These references are for Parts 1 and 2 of this series also.

1. “Part 201 criteria.” Part 213 Tier 1 Risk-Based Screening Levels, of the Administrative Rules for Part 201, Environmental Remediation, Michigan Public Act 451, Natural Resources and Environmental Protection Act, of 1994, as amended.
2. J.W.Tukey, “Exploratory Data Analysis”, 1977, Addisson Wesley.
3. DataDesk (http://www.datadescription.com/)
4. Aabel (http://www.gigawiz.com/)
5. Schaetzl, R. J., 2004. GEO 333, Geography of Michigan and the Great Lakes Region. http://www.geo.msu.edu/geo333/MIwatershed.html.
6. Kazmierski, J., Kram M., Mills, E., Phemister, D., Reo, N., Riggs, C., and R. Tefertiller. “Upper Manistee River Watershed Conservation Plan.” Prepared for The Grand Traverse Regional Land Conservancy. M. S. Project. Donna Erickson, Faculty Advisor. University Of Michigan. School of Natural Resources & Environment. April 2002.
7. Rediske, R.; Gabrosek, J.; Thompson, C.; Bertin; Blunt, J.; and P.G. Meier. Preliminary Investigation of The Extent of Sediment Contamination in Manistee Lake. AWRI Publication # TM-2001-7, Great Lakes National Program Office #985906-01, July 2001.
8. Velleman, P. F. (1997). DataDesk Version 6.0, Handbook, Volumes 2 and 3. Ithaca, N.Y., Data Description, Inc.
9. Michigan Background Soil Survey 2005. Hazardous Waste Technical Support Unit, Hazardous Waste Section, Waste and Hazardous Materials Division.
10. ArcView 9.0 (http://www.esri.com/)
11. R (http://www.r-project.org/)

KEYWORDS

Exploratory Data Analysis, evaluation, analysis, environmental, statistics, hypotheses, data, inference, litigation, toxicity, testing, comparisons.

Retell: A thief discovers a woman who claims to be the “richest person in the world.”  He ransacks her hut but fails to find her gold.  He goes on a quest to find the woman and her gold. What he finds instead are people who teach him that being rich has little to do with gold.

Topics: gold, greed, thieves, kindness, hard work, acceptance

Units of Study: Character, Social Issues, Talking and Writing about Texts

Tribes: mutual respect

Reading Skills: prediction, interpretation, inference, empathy

Writing Skills: incorporating the rule of three

My Thoughts: I first discovered this story when I went to a Great Books training years ago.  I’ve since used it a few times during the Character unit.  It is a great text for examining how people can change because of their relationships with other people.  It’s a great text to use when you are launching whole class conversation during and after read alouds.

Retell: Allie wants to be a star basketball player like her cousin Gwen.  After receiving a brand-new basketball from her father, she gives it a test run at the neighborhood playground.  She soon finds out that not everyone is willing to accept a girl on the court.

Topics: basketball, gender issues, friendship

Units of Study: Character, Social Issues, Talking and Writing About Texts, Realistic Fiction

Tribes: mutual respect, personal best, right to pass

Habits of Mind: persisting

Reading Skills: inference, interpretation, making connections

Writing Skills: planning  a story across 2-3 scenes

My Thoughts: This book is a great read aloud for so many different units.  It’s a particularly good text to read during the Social Issues unit.  It’s nice to read this book before or after reading other books that deal with gender issues such as,  William’s Doll,  or Oliver Button is a Sissy.  It’s a good mentor text for the Realistic Fiction unit because the story takes place across two scenes.

Retell: This is the rags-to-riches story of Roberto Clemente.  Not only was he an all-star player for the Pittsburgh Pirates, he was also a humanitarian who donated a great deal of his earnings to charity.

Topics: baseball, Puerto Rico, racism, poetry

Units of Study: Nonfiction, Social Issues, Content-Area

Tribes: personal best, mutual respect

Habits of Mind: persisting, thinking flexibly, striving for accuracy

Reading Skills: inference, interpretation, envisionment

Writing Skills: including similes, using commas in lists

My Thoughts: I like sports stories that emphasize the athlete’s character rather than just his/her athletic ability.  This is a good book for showing persistence even in the face of adversity.  The book describes how Clemente grew up playing baseball with a glove made out of a coffee-bean sack and baseballs made from old soup cans.  Written in free verse but organized into two line stanzas, this is a great book to read as a model for students writing nonfiction poetry during the Content-Area unit.

Retell: Peppe and his family live in a tenement on Mulberry Street.  Though he is just a boy, he must find work to help support his family.  After several attempts, he finally finds a job as a lamplighter.  His Papa imagines a better world for him in America.  He becomes upset with Peppe for taking such a menial job.  Though he loves his job, Peppe decides to take a break from it one evening in an effort to please his father.   Later that evening both Peppe and his father discover that being the lamplighter isn’t such a bad deal after all

Topics: tenements, New York, child labor, lamplighters, family, perspectives, work

Units of Study: Historical Fiction, Social Issues, Talking and Writing about Texts

Tribes: appreciations/no put-downs

Reading Skills: inference, envisionment, interpretation

Writing Skills: using the ‘rule of three’, angling a story

My Thoughts: What I love about this text, is that it’s short, but inspires the reader to do a lot of good thinking.  It’s a fabulous text for Reading and Writing Workshop as well as Social Studies.  Using the illustrations, students can envision what New York tenement life was like during the 1800s.  Though my students are currently writing Realistic Fiction, I’m planning on reading a section of this book tomorrow to a small group of students.  I’m going to teach them how authors often incorporate the ‘rule of three’ when crafting stories (“The Three Little Pigs”, “Goldilocks and the Three Bears”).  In the beginning of the story, Peppe attempts to find a job.  The author could have chosen to describe the effort in a figurative way.  Instead, she decided to give three examples of where he looked for work:  the butcher, the bar, and the candy maker.

Rob Scotton has created a tale about an everyday happening – going to school.  Splat is a cat in the tale Splat the Cat.  It’s the first day of cat school for splat.  He’s worried.  You are invited as a reader to climb into the character’s mind.  The author italicized Splat’s thinking.  On one of the pages, you can see the contrast between dialogue and thinking.  The text has fewer sentences on the page, so your students can see the examples clearly.

Rob Scotton’s illustrations are fun and cozy.  I feel like I’m in the room with the cats.  Splat is unusual in that he has a mouse as his pet.  When he goes to school, he learns what a good cat does.  One rule is that cats chase mice.  Splat wonders why and questions his teacher.  She doesn’t have a sturdy answer, so through Splat’s power of persuasion, the class decides that they do not have to chase mice.

Savorings for reading and in writing for Splat the Cat:

• Alliteration – wiggled wildly with worry
• Character Thinking – italicize wording
• Everyday Happening – nervous about going to school and doing something new
• Wondering – Splat asks the teacher questions and wants a valid answer besides “because”.
• Bookending the Story – “Today was his second day at Cat School, and his tail wiggled wildly… with excitement.”
• Character Twist – a cat has a mouse as a friend
• Inferring – The illustrations add more emotion and understanding to the text.  The children will need to pay attention to Splat’s actions.

PES Library book and Warsaw Public Libray