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Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9

  • NAP - How People Learn (On-Line) (pages for Thurs. reading)
  • The College Board SAT Program (from ETS)
  • FairTest: The National Center for Fair & Open Testing (A organization
    • --A Sample of FairTest Views from SAT Questions and Answers --
    • What Does SAT Stand For? Nothing. Initially titled the Scholastic Aptitude Test and then the Scholastic Assessment Test, it is now officially named just SAT I because of uneasiness at ETS and the College Board about defining just what the test measures. "SAT is not an initialism; it does not stand for anything," say the testmakers.
    • What is the SAT Used For? The SAT is validated for just one purpose: predicting first-year college grades. It does not do even this very well. Testmakers acknowledge that high school grade-point average (GPA) or class rank are the best predictors of first-year grades, despite the huge variation among high schools and courses. The SAT predicts other outcomes, such as graduation rates, even more poorly. As more colleges move away from using the SAT for making admissions decisions, the testmakers are promoting its use for course placement purposes. However, studies show that the individual colleges' exams are much more accurate tools for placing students.
    • What is on the SAT? A direct descendant of the racist anti-immigrant Army Mental Tests of the 1920s, the SAT was first administered in 1926 but did not become a fully multiple-choice exam until after World War II. From the beginning the test was designed to be independent of high school curricula (unlike the SAT's main competitor, the ACT). It now consists of analogies, sentence completions, reading comprehension, standard math and quantitative comparisons. The SAT does not include advanced mathematics topics nor does it attempt to assess higher-order thinking or reasoning skills. Though a "Verbal" score is provided, test takers do not write a single word. http://www.fairtest.org/facts/satfact.htm
  • ETS's version of testing: Too Much Testing of the Wrong Kind; Too Little of the Right Kind in K-12 Education
  • PBS: Secrets of the SAT
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  • National Assessment of Educational Progress (NAEP)
  • Texas Education Agency (TEA)
  • TEA - Remediation for TAAS: What Works - interesting list (but where's "teach math")
  • TEA - Student Assessment Division
  • TEA - Division of Performance Rating
  • TEA - Press Release (2000): Texas TAAS passing rates hit seven-year high; four out of every five students pass exam
    • AUSTIN - Texas students, for the seventh year in a row, set a record high passing rate on the Texas Assessment of Academic Skills test, Commissioner of Education Jim Nelson announced today. Preliminary results show that 80 percent of all students tested in grades three-10 passed the English version of the TAAS this spring, compared to 78 percent last year.
    • This latest passing rate is 27 points higher than the 1994 passing rate for all students. That year, 53 percent of the students passed all tests taken.
    • "Texas students continue to perform impressively on the TAAS test. The performance is a testament to the strong instruction and learning that is going on in our schools. Texas students, teachers and parents can be proud of these results. Texas has justifiably gained national recognition for the performance gains being made by our students," Nelson said.
  • TEA - Press Release (2000): Texas students' performance improves on biology, English and history tests; algebra performance remains unchanged
    • AUSTIN - Texas public school students did better on the state's end-of-course tests in biology, English II, and U.S. history this year than in 1999, but their performance on the state's Algebra I test was unchanged from last year, Commissioner of Education Jim Nelson announced today.
    • The passing rate on the Algebra I end-of-course test remained unchanged between 1999 and 2000 with 45 percent of students passing the exam.
    • Performance on the Algebra I test remained weak for most student groups. Among white students, 57 percent passed the test, but only 34 percent of Hispanic students, 32 percent of economically disadvantaged students, and 27 percent of African-American students did so.
    • "Being able to only add, subtract, multiply and divide isn't going to be enough to make it in the real world," Nelson said. "Our students need to develop the higher-level mathematics skills that can only be developed through rigorous courses like Algebra I."
  • Maldef's Post Trial Brief - Facts on TAAS Case
  • The Harmful Impact of the TAAS System of Testing in Texas: Beneath the Accountability Rhetoric
  • Fairtest criticizes decision in TAAS Case
  • Education Week - A beefed-up accountability system spurs schools to focus on their poor and minority students.
    • Texas has pursued a two-pronged strategy for raising student achievement: giving schools greater regulatory flexibility on the one hand, and holding them more accountable for results on the other.
    • That approach, Texans like to boast, has improved urban and nonurban schools alike by shining a light on the low-performing schools where change is most needed.
    • In particular, he points to the performance of the state's minority students on the national assessment. A far higher percentage of black 4th graders scored at or above the "basic" level in Texas than in any other state on the 1996 NAEP math exam, and the state's Hispanic students ranked fifth.
    • At the 8th grade level, the percentage of Hispanics achieving a "proficient" score met the national average for Hispanics, and the percentage of black students working at the proficient level exceeded the national average for African-Americans.
    • State officials also like to cite a 1997 study by the RAND Corp., a think tank based in Santa Monica, Calif., that looked at state NAEP scores in relation to their student demographics, such as the percentages of poor and minority students. When demographics were considered, "we came out near the top," Mr. Moses boasts.
    • One of the most important features of the accountability system, according to its supporters, is that it tracks performance for each significant ethnic group within a school or school district. To avoid being labeled as low-performing, schools and districts must ensure that a minimum percentage of students in each ethnic group, as well as among their disadvantaged students, passes the state tests; it's not enough just to post an acceptable overall score. Many of the schools that have been labeled low-performing over the years actually had acceptable average scores.
  • Education Week/Washington Post - Texas Testing System: Success or Failure?

Week 2

Week 3

  • Skinner's definition of teaching
    • "So far as we are concerned here, teaching is simply the arrangement of contingencies of reinforcement." (p. 5)
    • "Education is perhapts the most important branch of scientific technology." (p. 19)
    • "The simple fact is that, as a mere reinforcing mechanism, the teacher is out of date. This would be true even if a single teacher devoted all her time to a single child, but her inadequacy is multiplied many fold when she must serve as a reinforcing device to many children at once. If the teacher is to take advantage of recent advances in the study of learning, she must have the help of mechanical devices." (p.22) (Quotes from: The Technology of Teaching)
  • Does it Compute? - (ETS) (Excerpts in the course packet later in semester)
    • Professional development and higher-order thinking are both positively related to academic achievement: Students with teachers who have had such professional development show higher levels of achievement, as do those who are taught higher-order skills with computers.
    • Finally, using computers for drill and practice, the lower-order skills, is negatively related to academic achievement.
    • While minority, poor, and urban students are no less likely to use computers at school frequently, frequency of use is not associated with gains in achievement or social environment. Yet minority, poor, and urban students are less likely to receive exposure to computers for higher-order learning, and poor and urban students are less likely to have teachers who have received professional development on technology use. Thus, where technology matters, there are significant inequities; only where technology does not matter have these inequities been successfully erased.
  •  Computers and Classrooms: The Status of Technology in U.S. Schools - (ETS)
    • Students in schools with the largest percentage of poor and minority students have less access to most types of classroom technology
  • Computer Assisted Instruction (CAI) URL's

Week 4

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Week 5

  • More about Piaget  
    • While botanists have catalogued all the world's plants, and zoologists have counted the hairs upon every little animal, and that at each stage of their growth , the science of child development i.e. the embryology of the human spirit itself in effect, continues to be confined to general studies, upon which teaching techniques and therapy etc. can be based only in the most empirical fashion. (Piaget)
  • SimCalc Central - Creaters of MathWorlds Java, MathWorlds Mac, and Calculator MathWorlds
  • SimCalc Texas - The beginnings of a Texas Integrated Calculus Initiative

     

  • G. Polya - How to Solve It (Excerpts)
  • Connection to General Problem Solver - (Simon on Newell)
    • On completing his service in the Navy, Allen enrolled in Stanford University, where he majored in physics. Undergraduate research led to his first paper, on X-ray optics (Newell and Baez, 1949). Stanford also exposed him in the classroom to George Polya, who was not only a distinguished mathematician but also a thoughtful student of mathematical discovery. Polya's widely read book, How to Solve It, published in 1945, had introduced many people (including me) to heuristic, the art of discovery. Allen came away from that experience aware that the processes of discovery could be investigated and analyzed and that heuristic--the art of guided search--played a key role in creative thinking. (Our common fascination with heuristic helps account for the rapidity with which Allen and I established common ground on first meeting early in 1952.)
    • At this time the ideas of cybernetics and artificial life were abroad. W. Ross Ashby had published in 1952 his Design for a Brain. W. Grey Walter (1953) in England had constructed some mechanical "turtles" that wandered about the room searching for a wall outlet when their batteries ran low, and similar creatures were built by Merrill Flood's group at RAND. By 1950 both Turing and Shannon had described (but not actually programmed) strategies for computer chess, and in 1952 I described (but did not implement) a program extending Shannon's ideas. On an auto trip en route to observing some Air Force exercises in the summer of 1954, Allen and I discussed at length the possibilities of using a computer to simulate human problem solving, but we were not then diverted from our current research on organizations.
    • THINKING-ALOUD PROTOCOLS

      There are severe difficulties in testing a theory of human thinking that predicts the sequence of thought processes each of only a few hundred milliseconds duration. Apart from neurological evidence, which is only now beginning to become available for tracing some processes, there were few obvious ways of obtaining data while a task was being performed, even at a density of one data point per second.

      It occurred to the team to instruct subjects to think aloud while performing problem-solving tasks. However, fifty years earlier the method called "introspection" had been thoroughly discredited as a means of obtaining reliable data in psychology. Hence, it was necessary to show that the thinking-aloud method was quite different from classical introspection and to determine the circumstances under which it could provide objective evidence about thought processes. A program of laboratory experimentation using thinking-aloud methods was launched by the beginning of 1957; formal methods were developed for encoding protocol data (problem behavior graphs); and a decade later Allen and Don Waterman made the first, only partially successful, attempt at automating protocol analysis (Waterman and Newell, 1971).

    • THE GENERAL PROBLEM SOLVER (GPS)

      In the summer of 1957, during a workshop at Carnegie Tech on organizational behavior, Al and I extracted from the protocol of a single subject solving logic problems what proved to be a key mechanism in human problem solving: means-ends analysis.

      In M-E analysis the problem solver compares the current situation with the goal situation; finds a difference between them; finds in memory an operator that experience has taught reduces differences of this kind; and applies the operator to change the situation. Repeating this process the goal may gradually be attained, although there are generally no guarantees that the process will succeed.

      The idea of M-E analysis led to the General Problem Solver (Newell, Shaw, and Simon, 1960), a program that could solve problems in a number of domains after being provided with a problem space (domain representation), operators to move through the space, and information about which operators were relevant for reducing which differences. The research also discovered schemes that permitted GPS to produce its own operators from a small set of primitives and to learn which operators were relevant for reducing which differences.

  • NCTM Principles and Standards 2000
    • Standards - The Process Standards&emdash;Problem Solving, Reasoning and Proof, Communication, Connections, and Representation&emdash;highlight ways of acquiring and using content knowledge.
    • Problem Solving - Problem solving means engaging in a task for which the solution method is not known in advance. In order to find a solution, students must draw on their knowledge, and through this process, they will often develop new mathematical understandings. Solving problems is not only a goal of learning mathematics but also a major means of doing so. Students should have frequent opportunities to formulate, grapple with, and solve complex problems that require a significant amount of effort and should then be encouraged to reflect on their thinking.
  • Developing Problem Solving Strategies (Van de Walle) - An elementary math methods text
  • Notes about ELIZA from Witness to Software History: The Mascot of Project MAC
    • David was also there when Joseph Weizenbaum, to his later regret unveiled ELIZA, probably the most widely quoted and widely misunderstood program in history -- the program that seems to be an uncannily perceptive psychiatrist, but is actually a programmer's semantic trick.
    • Joseph Weizenbaum showed up at MIT in 1963, and when he created ELIZA between 1964 and 1966, he changed the way everybody thought about what computers can't do -- and that included changing his own mind about where the whole computer-AI enterprise was heading. ELIZA was a clever way of mimicking human interaction through a computer-mediated dialogue; what the inventor hadn't anticipated was people's willingness to be taken in by the mimicry -- even people who should have known better. By the time Weizenbaum recovered from the shock of seeing the way people reacted to his program, he was convinced that something very dangerous lurked in the much-heralded computer revolution.

      While he was working on a more elaborate question-answering program, with greater sentence-parsing capabilities than his first version, Weizenbaum met a psychiatrist from Stanford named Kenneth Colby, who was interested in using computers to model mental states and mental disorders in order to find clues to more effective forms of psychotherapy. Colby helped Weizenbaum create a special-case version of ELIZA, known as DOCTOR. In the introduction of his 1976 book, Weizenbaum described how this most successful and disturbing version of ELIZA came into being, and conveyed a little of the flavor of the "ELIZA effect":

    • The first thing that alarmed Weizenbaum was the way people who knew enough about computers to know better began to get drawn into serious conversations with it about their lives! Even his own secretary had fallen into the habit of conversing with it! People were asking to be left alone with the machine to spill out their most intimate thoughts! Weizenbaum was so horrified that he started rethinking everything he believed. But that was just a symptom of how gullible we all might be to what he knew was just a clever hack.

      More serious, to Weizenbaum's way of thinking, was the fact that Colby and others thought that "computer-therapists" might soon be applied to some form of "automatic psychotherapy" -- an idea Weizenbaum considered "obscene." Weizenbaum's ethical debate, although it originated in the same laboratory that spawned so many important innovations in AI and computer systems design, will not be discussed at length here. His books and the ideas expressed by Weizenbaum and his critics deserve consideration on their own accord.

    • Weizenbaum was a critic of using the computer in education: "There is, as far as I know, no more evidence programming is good for the mind than Latin is, as is sometimes claimed."
    • The original academic publication regarding ELIZA
    •  ELIZA {A web version}.
  • Lessons from a Restricted Turing Test (1993)- (Turing Test is too easy and should be replaced based on 1991 results).
    • The English logician and mathematician Alan Turing, in an attempt to develop a working definition of intelligence free of the difficulties and philosophical pitfalls of defining exactly what constitutes the mental process of intelligent reasoning, devised a test, instead, of intelligent behavior. The idea, codified in his celebrated 1950 paper ``Computing Machinery and Intelligence'' [28], was specified as an ``imitation game'' in which a judge attempts to distinguish which of two agents is a human and which a computer imitating human responses by engaging each in a wide-ranging conversation of any topic and tenor. Turing's reasoning was that, presuming that intelligence was only practically determinable behaviorally, then any agent that was indistinguishable in behavior from an intelligent agent was, for all intents and purposes, intelligent. It is presumably uncontroversial that humans are intelligent as evidenced by their conversational behavior. Thus, any agent that can be mistaken by virtue of its conversational behavior with a human must be intelligent. As Turing himself noted, this syllogism argues that the criterion provides a sufficient, but not necessary, condition for intelligent behavior. The game has since become known as the ``Turing test'', a term that has eclipsed even his eponymous machine in Turing's terminological legacy. Turing predicted that by the year 2000, computers would be able to pass the Turing test at a reasonably sophisticated level, in particular, that the average interrogator would not be able to identify the computer correctly more than 70 per cent of the time after a five minute conversation.

      On November 8, 1991, an eclectic group including academics, business people, press, and passers-by filled two floors of Boston's Computer Museum for a tournament billed as the first actual administration of the Turing test.

    • One reporter noted that Weizenbaum himself was ``disturbed'' by how easily people were fooled by these programs, and more than one of the judges reported that they were disappointed in the programs' capabilities after their expectations had been raised by interacting with ELIZA in the interviewing process. Dr. Epstein, in a speech after the event, noted that he had learned from the day's proceedings that ``little progress has been made in the last twenty-five years'', that is, since ELIZA. (The authors argue instead that the test is flawed.)

Week 7
 

 

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