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  1. 1. Portfolio of Evidences on Demonstrating C Programming Laboratories Dr James Cunha Werner 2005 University of Manchester Certificate for Learning and Teaching in High Education Postgraduate course
  2. 2. Outcomes Evidences 1. Design and plan learning activities for C Programming Laboratory demonstration. 1. Diagram showing the relationship between data modelling and implementation (3 cases). 2. Case 1: pointers implementation 3. Solution 4. Case 2: pointer’s loop implementation 5. Solution 6. Case 3: pointer of pointer implementation 7. Solution 8. Diagram of data modelling (structures). 9.Case 4: problem description 10.Solution 11. Diagram of algorithm implementation 12. Case 5: matrix problem description 13. Solution 2. Carry out support of learning 1. Diagram showing the relationship between data modelling and implementation 8. Diagram of data modelling (structures). 11. Diagram of algorithm implementation 14 and 15. Report from Imperial College 16.Tutor assessment from University of Manchester 17.Lab Supervisor assessment from University of Manchester 3. Devise and apply appropriate strategies and criteria for assessment 18. Computer assessment 19 to 21. manual assessment form 22. Workshop on assessment 23. Learning sets on dealing with student’s emotional responses to assessment. 4. Monitor and critically evaluate own professional practice and its impact on the student experience 24. Book’s solution beyond student’s comprehension. 25. Support problem solution 26. pointer’s student solution 27. pointer’s loop student solution 28. pointers of pointers student solution 29. Student’s assessment 5. Perform teaching and academic administration effectively 30. Supervision spreadsheet. 6. Provide support to students on academic matters 24. Book’s solution beyond student’s comprehension. 25. Support problem solution 26. pointer’s student solution 27. pointer’s loop student solution 28. pointers of pointers student solution 29. Student’s assessment
  3. 3. 7. Develop personal and professional coping strategies 1. Diagram showing the relationship between data modelling and implementation 8. Diagram of data modelling (structures). 11. Diagram of algorithm implementation 24. Book’s solution beyond student’s comprehension. 25. Support problem solution 26. pointer’s student solution 27. pointer’s loop student solution 28. pointers of pointers student solution 29. Student’s assessment 8. Reflect on own personal and professional practice and development 31 to 33. Career development. 34 and 35. Professional experience in industry. 36 to 41. Professional experience in academia. 9. Overview of mind maps to design learning activities (Project-based developing learning and teaching module). 42. Mind map training at Univ. of Manchester. 43. Mind map for my talk. 44. From mind map to slides. 45. Slides. 46. Evaluation 2 months later. 47. References about mind maps. 10. Show how own practice with regard to the above outcomes is underpinned by specific proof values 48. First material sent to my tutor. 49. Successful experiences. 50. Learning agreement. 51. Peer assessment about my portfolio.
  4. 4. Introduction This document presents a critical evaluation and discussion of my abilities as learning process facilitator for undergraduate students, to obtain the Certificate of Learning and Training in High Education. Every requirement was fulfilled with evidences obtained teaching C programming Laboratory in undergraduate courses at University of Manchester and Imperial College. C programming laboratory is a very demanding task, because students are agents in learning process, and demonstrators only have to provide support and guidance that allows them achieve their goals without tell the answers. Chapter 1 describes the design and plan of learning activities through different pedagogical scenarios. Chapter 2 describes how I carried out support for learning activities based in a taxonomy of situations. Feedback was provided through assessment (Chapter 3), which provide me with information to evaluate my own professional practice (Chapter 4) and management (Chapter 5). Underpinning all this work, there are the concern about student support on academic matter (Chapter 6) and more general coping strategies (Chapter 7). This holistic point of view allowed me reflect on my own personal and professional practice and development (Chapter 8) and how it underpinned my practice (Chapter 10). Chapter 9 describes the use of mind maps to support design and plan of learning activities, a proposal to be developed during the next year.
  5. 5. 1. Design and plan learning activities for C Programming Laboratory demonstration. Design and plan a learning activity requires from lecturers/demonstrators the knowledge of the following issues: 1. What are the major models of learning process to understand how people acquire skills. Select a winner teaching strategy requires understand how people assimilate new information, and change their behaviour (learn). There are 3 major learning theories: Behaviorism, Cognitivism, and Constructivism. Behaviorism uses conditioning to achieve learned responses. The repetition of stimula/response automatises the behaviour. Learning is accomplished when a proper response is demonstrated following the presentation of a specific environmental stimulus[1] . Thorndike [1] introduced 3 laws to explain his point of view: • Law of exercise: Repetition of exercise increases the probability of correct response. <with practice, the associations are strengthened or weakened and the appropriate behaviour is emitted more reliably>. • Law of effect: A satisfying state of affairs following the response strengthens the connection between the stimulus and the behaviour, whereas an annoying state weakens the connection. <associations are made only when the behaviour is connected with a reinforcing consequence>. • Law of transfer: The conditioned behaviour will only occur under stimulus conditions similar to those in which the behaviour was initially learned.
  6. 6. Pavlov pointed out that reflex actions (involuntary) were trained so that the reflexes can be elicited by a stimulus other than that which naturally elicits them. Pavlov showed that when a conditioned stimulus is paired with another neutral stimulus, the second stimulus can also become conditioned. Cognitivism is based in the thought process behind the behaviour. In cognitive theories, knowledge is viewed as symbolic mental constructs in the learner's mind, and the learning process is the means by which these symbolic representations are committed to memory. Changes in behaviour are observed as indication of what is going on in learner's head[2] . Piaget studied how a child comes to know his or her world. He is renowned for constructing a highly influential model of child development and learning. Piaget's theory is based on the idea that the developing child builds cognitive structures--in other words, mental "maps," schemes, or networked concepts for understanding and responding to physical experiences within his or her environment. Piaget further attested that a child's cognitive structure increases in sophistication with development, moving from a few innate reflexes such as crying and sucking to highly complex mental activities. Vygotsky’s concepts of the social formation of the mind and the Zone of Proximal Development add much to our understanding of human development. The social cognition learning model asserts that culture is the prime determinant of individual development. Humans are the only species to have created culture, and every human child develops in the context of a culture. Therefore, a child's learning development is affected in ways large and small by the culture--including the culture of family environment--in which he or she is enmeshed.
  7. 7. Construtivism is based in the conception of learning. Von Glasersfeld[3] argues that: "From the constructivist perspective, learning is not a stimulus- response phenomenon. It requires self-regulation and the building of conceptual structures through reflection and abstraction" (p.14). Fosnot [4] adds that "Rather than behaviours or skills as the goal of instruction, concept development and deep understanding are the foci (...) (p.10). For educators, the challenge is to be able to build a hypothetical model of the conceptual worlds of students since these worlds could be very different from what is intended by the educator [5],[6] . In this paradigm, learning emphasizes the process and not the product. How one arrives at a particular answer, and not the retrieval of an 'objectively true solution', is what is important. Learning is a process of constructing meaningful representations, of making sense of one's experiential world. In this process, students' errors are seen in a positive light and as a means of gaining insight into how they are organizing their experiential world. The notion of doing something 'right' or 'correctly' is to do something that fits with "an order one has established oneself"[7] . This perspective is consistent with the constructivist tendency to privilege multiple truths, representations, perspectives and realities. Ertmer[8] make a comparative study of all three theories[9] . 2. What are the requirements students will face after the learning process, or, what the learning process is intended for. Physicists are entitle to work teaching at Universities and High Schools, or developing complex system models for industries, banks, and engineering
  8. 8. companies. Physics course teaches students how to develop these models and use it for optimisation and understanding of nature processes. Models are mathematical relations between variables of the process and performance index are defined based in economic issues. System optimisation cares to make the system as profitable as possible. The system under study will be company’s activity process. If working for a transport company it could be a transport system (such as underground or busses) and the goal will be increase the number of passengers transported during the day with lower costs and time travel. Working for sugar and alcohol companies, it could be a fermentation process optimisation through changes in the sugar feed rate. Steel companies demand highly efficient production recipes and process operations to increase steel production with costs reduction, due third world competitive market. These models represent reality abstracting exogenous factors (considered as perturbations) and allow the physicist study system characteristics and forecast behaviours and properties to find the most economic procedure. Unfortunately, due the complexity of mathematical models most of them (if not all) do not have an analytical solution, e.g. a solution can be written as a mathematical equation. Most of them, the physicist can not develop experiments in the real process, and the model provide all necessary information for development of a system simulator. To overcome these difficulties, computer programming uses numerical methods to solve models that do not have analytical solution and provide physicists with the solution they need to perform their job.
  9. 9. Most of simulation systems will later be used as decision support and operators training support. 3. Professional requirements and assessments. The assessment of a model and its computational implementation are defined by its stability, robustness and accuracy. Results accuracy is affected by hypothesis mistakes and computer program errors. Hypothesis can be checked against data from the process, to evaluate its accuracy. However, computer program errors are much more difficult to be found. There are trivial mistakes such as syntax and language requirements that most of time are found by the compiler. The compiler is the tool that converts the program language (understand by humans) into executable commands (understand by computers). When the error came from logic, it is more difficult find out. The error could be hiding in a place of code not executed because the test set does not cover all the possible conditions the software will have to face with, or the difference introduced by the error is not representative in comparison with other result components. In synthesis, students that have attended Computer programming course must be able to perform rational thinking and reduce complex problems models to a limited set of elementary tasks through analysis and synthesis that can be coded in a language to be executed by the computer with accuracy.
  10. 10. These skills are not able to be performed using any magic rules or recipes. There are methodologies that help to perform the process, representing knowledge and relationships, but the final result is programmer’s creation. The practical fulfilment of these requirements is realised by construtivism approach. Learning is not a stimulus-response phenomenon. It is the construction of a meaningful solution based in student's hypothetical model of the conceptual worlds, ruled by syntax and logic of programming language. Learn the necessary information and be able to perform the activity demands a very practical approach. Students attending a lecture most of the time are driven by the lecturer. Karen Anderson[10] analysed lectures structure at MIT physics course and their change to Technology Enabled Active Learning, or TEAL, a student centred approach where lectures became more practical. It is almost impossible develop a lecture where students are agent of the process. It would be a disaster teach programming language using lectures approach only because there are infinite ways to solve the same problem under a creative centred approach. Each approach has positive and negative points and are valid as far they can produce the correct solution. It is not only the algorithm they are using to solve the problem. It is how they write the algorithm using computer language. For example, they could use different types of loops to perform the task. All of them are correct, but showing different reasoning. They have to develop the ability to use the correct code structure and logical reasoning from a problem description in English. The code must be clear to
  11. 11. allow any physicist to make maintenances and changes to reuse the software in another condition, saving money and efforts. The way to drive students develop these skills is through laboratories classes, using a construtivism approach. There are two different approaches I have work with: lectures with laboratories at University of Manchester and only laboratories at Imperial College. Both courses follow the same synopses, but they differ in the way theory and practice is delivered. These differences are crucial in the laboratory demonstration and students learning process besides the total number of hours and the issue are the same. Lectures+Lab adopted at Manchester follows the conventional course structure. The theory was covered and one or more examples are described in class. Laboratory consists in a different problem using pieces of the example and something more the student have to develop by themselves. The important point is the need of a complete understanding of the example, and the theory behind it to perform the task. This perspective is consistent with the constructivist tendency to privilege multiple truths, representations, perspectives and realities to perform the task and acquire learn in the process. Laboratory only approach adopted at Imperial College is much more demanding for students. This is a 100% student-centred learning. Students receive a theory description divided in modules and a series of tasks related with each theory module.
  12. 12. Students need to read the theory and establish a reasoning by themselves to solve the tasks. They have to be active learners, because they do not have the lecturer experience support during the class and the example to be adapted to solve the problem. This approach requires trivial problems at beginning to develop the basis for a more complex reasoning. Another important point is the tasks must use previous tasks to be solved. For example, one task was simple pendulum, coupled pendulum model, variable length pendulum, and the final project was the study of chaotic behaviour of coupled pendulum when the length of the pendulum is changed. Both approaches can be represented in Kolb's learning cycle (Fig. 1). Lab only approach goes from concrete experience to abstract concept, while lectures +lab in opposite direction. However, in both cases the agent of learning process is the student and the laboratory demonstration was defined to overcome difficulties and provide the means for a consistent learning process. In both scenarios, demonstration in the laboratory requires from the demonstrator deep understanding of the problem and all possible solutions. He/she must be able to look at the screen and see the problem at once, and provide support. Demonstration process occurs following always the same protocol. At the beginning students call the demonstrator, and ask “why the software is not working?”. Only later in the course, the student calls and asks some technical aspect of logic or syntax and discusses implementation alternatives.
  13. 13. Fig 1. The learning process in programming laboratory. The demonstrator must look the software and identify the problem. Them, without solve the problem, the demonstrator has to ask questions about the theory that are not clear and the lack of understanding that are the cause for the mistake. Sometimes, just tell the student about the method to acquire information about the problem is enough to allow them find the solution by themselves. This interactive process is very demanding because the demonstrator can not tell the answer, but drive the student in the solution direction. If the demonstrator just tells the problem solution, the student will not acquire the reasoning to solve the problem, and will have deeper and deeper problems every week due the lack of previous structures. To support in this process, the demonstrator have to be prepared to point the solution in a higher level of abstraction that the student is doing. It means the demonstrator will explain WHAT must be done and not HOW it needs to be Concrete experience DOING Reflective observation REFLECTING Abstract conceptualisation THINKING/GENERALIS ING Active experimentation PLANNING
  14. 14. implemented. Doing this, the student is in charge of the learning process using their creativity to implement their solution. I use to have a schema diagram showing in high level the solution and the relationship with previous and related theory to support my explanations. This is a very good way to reduce the time to answer a question and avoid give too much information (more they discovered by themselves, better!). It is important to forecast what will be students questions to prepare the diagrams, and make them clean. Evidence #1 shows the diagram for bubble sort class. The problem asks to sort a series of numbers using a technique that looks like a bobble going up in the glass of liquid. Take the first number, compare with the second and swap if the first is bigger. Then, take the second number, compare with the third and swap if the second is bigger. Repeat the process until the end of the list. After this, the last number is the greater of all. Repeating the same process again until the before last, you will have the penultimate number, and so on. The problem requires the student develop 3 solutions using arrays of numbers (evidence #2 and #3), pointers (evidences #4 and #5), and pointers of pointers (evidences #6 and #7). The schema shows the three different approaches and how to represent differences between the solutions, without show the solution itself. The main goal of this module is to show how different representations (arrays, pointers, and pointers of pointers) can be used to deal with large amounts of data. It contains the data modelling, algorithmic implementation, and its relationship.
  15. 15. Evidence #8 shows the diagram for structures. Structures are a very important concept, because it will be the foundations to object oriented programming. Objects can use structures that bound its constituents and methods to access the data, which define a class. The diagram shows blocks with components inside, and its relation with screen output, mathematical operations, and organisation in memory. The ideas behind are to show concept of block structure to represent data. Problem description (evidence #9) and solution (evidence #10) allow to define the strategy I should use to draw the diagrams that will support my demonstration. It is interesting that from implementation complexity point of view, this laboratory is trivial when compared with the previous one (bubble sort). However, there are deep theoretical implications of structures that will be studied in another programming course about classes and C++ frameworks (optional course). Evidence #11 was the course final project. For some reason, during the lecturers course evaluation meeting, there were complains about the difficulty level of the laboratory problems. As consequence, the final project was to obtain the inverse 3x3 matrix, and multiply by the original matrix and obtain the identity. I suggested a more interesting problem. The solution of a coupled first order differential equation system by Runge Kutta Method using structures to store data and pointers to functions to access each coupled differential equation. My suggestion was not accepted, and we went to the matrix problem. There was 2 weeks to solve the problem, but the students have done it by the end of
  16. 16. the first day (evidences 12 describe the problem and evidence 13 the solution). The course could be improved if a logic representation of the algorithms (flowchart) could be introduced to support a deep understanding and concept representation (main concerns in constructivism school). 2. Carry out support of learning Programming Computers at University of Manchester was organised in lectures followed by laboratory sections. Each laboratory has 125 students and 5 demonstrators. Demonstrators can attend any student that requires help. Imperial College adopted the only laboratory approach, and each demonstrator carry on 10 students. I will show my ability to carry out support of learning through a taxonomy of situations when students require help for both scenarios and describe what course of action I have adopted: a. Trivial question due lack of knowledge, not described in the lectures notes: this is the case where the course fails to provide some basic information. Most of the cases are trivial links between the computer, operating system and the program itself. I believe it happens because it is very difficult to describe, but trivial to show in practice. Another source of missing information are knowledge so trivial and part of the common jargon of experts, that lecturers and material writers forget to explain. One very common question is how the program works in the computer. If the demonstrator answer “the computer runs the program”, will be meaningless for the student.
  17. 17. The students do not have an idea that computers are sequential machines, which means, the computer takes one instruction from the program, execute it, and them takes next, execute it, and so on. But, where is the first instruction? The program structure corroborates to make thinks difficult. It contains first include libraries, context definition, global variables, prototypes, and only them the main function which is the entry point for the program. Evidences #3, #5, #7, #10, and #13 contains source codes. It is difficult find the main function. The best approach for these situations is to show in the student’s draft what is going on. To answer the above problem, I use to say the student that “you are the computer. You are fast, but stupid. You cannot think, you just perform each task after another. What do you want to do? “ The student will answer “I do not know!”. This is the answer I need to point how his program works: “Right, because you do not know where is your program’s first command!” Them I will show in the student’s draft the main function, and I will tell them that this is the entry point and he will have to do each command sequentially. Operating system loads users programs and points the computer for the first command inside the main function. “Now, what do you have to do?” Them the student goes in the main function and starts describing each command of the program and what actions and consequence it generates in the context.
  18. 18. This approach allows students establish a link between his mental structures, the program, the context and the computer system (hardware + operating system). Students ask how the program works, but he really wants to know where is the first instruction and what happens next to follow the logic implemented in the algorithm. There will be a comparison between student's cognitive structure and realisation of it in the computer's program. Divergences will result in program's changes or cognitive structure adaptation (learning from experience) to achieve the goals. b. Trivial question due lack of knowledge, described in the text: sometimes students do not read the text. We could think the student is lazy, but this is not the case. Lazy students do not ask questions. Actually, there are not lazy students. There are not motivated students, unless they have some personal problems interfering the learning process. The problem with questions about thinks that are in the text is because the student did not understand how the information is organised in the text. In this case, instead answer, demonstrator should talk about how the text was written and how the information is organised and where look for the answer. For example, each command must follow language syntax. Students use to ask how to repeat some command several times. This is a command of loop type. They can use FOR, WHILE, or DO … WHILE. This question could be answered explaining that the text is organised in different types of structures and commands. If you want to describe data, there are lectures notes 1,2, and 3. If you want to perform a loop, e.g. repeat the same command several times, they have to look at lecture note 6. Them, I
  19. 19. pointed the student to the piece of text which describes all the loop commands, and not the one they have to use because I want the student have to decide what is the best solution for his problem. Students will have to establish a connection between their cognitive structures and different loop commands. This commands map all primitive cognitive structures that deal with command's loops. Another very frequent question are referring with information provided in the problem text. They have to perform rational thinking and reduce complex problems models to a limited set of elementary tasks, which means, they have to read the problem text (jargon calls it “spec”) and write a piece of code that performs the task exactly as described. The first problem in this case is related with English (or any other language) structure. There are prepositions, adverbs, etc that do not corroborate in the program coding process. Only subjects and verbs carry actions that can be coded in the program. Another point is how to convert “read up to 1000 numbers” in a series of commands. You can read from keyboard or file, and store it in arrays or dynamic allocated memory referenced as pointers. There is an abstraction and modelling process in program design. The demonstrator must make very clear these points, because any difference between spec and code results are mistakes, sometimes with terrible consequences if the software is controlling an underground or a steel production process.
  20. 20. c. implementation questions: these are very interesting questions and students only achieve this level by the middle to the end of the course. Here the demonstrator is able to give more than answers, but his own experience as well. It is more related with how to perform the task and its efficiency. For example, why use DO…WHILE instead WHILE…DO? The difference is the first case is used always you have at least one element to perform the loop, and the second is used when you can have no element at all. Another case is differences between FOR and WHILE loops. The first contains an index, which varies sequentially and have to run from the first until the last (break the loops is not elegant in structured programming). The second case, repetition process could be more complex and flexible using events or states to control the loop. One example of code optimisation is in evidence #1 problem. You do not need to cover all string every time, because the last n elements are already sorted. If you do it, will make no difference in the result but it will take longer. d. unexpected problems and implementations: these are very rare questions and problems. For example, there is a function called swap available in the compiler libraries. The student was developing a function and called it swap as well, but with different parameters from the one in the compiler’s library. When the student call the function he gave the parameters type from swap function in the library. This is a very interesting problem because the student was not running his code, and any change done in it makes no difference.
  21. 21. Usually, the solution for these problems is to use old debug techniques, like write the values in the screen during program execution. This allows the student (and the demonstrator!) to understand what is going on. These 4 types of situations occur in both scenarios of lectures and labs/ labs only. Students start only with type “a” questions, after evolve to “b”, and so on. The difference between both scenarios is the timing necessary to achieve more complex levels. I believe the students which only laboratory course achieve a level of understanding faster them students with lab and lectures. This is really a paradox. Students with less information are able to develop faster. Maybe the reason is student lab-only has to understand the text organisation from the beginning, and maybe this is the fundamental difference between both approaches. They have to acquire a knowledge of the text organisation that allow them navigate in the document and find the necessary information faster them the other students. Probably students with lectures do not read the texts with the same attention from the beginning, and this could result in longer development. Evidences that I am able to carry out support of learning are my good performance teaching at Imperial College lab-only approach (Evidence #14) and lecture+lab at University of Manchester (Evidences #15, #16, and #17). These experiences provided me with practical skills, and have I been provided with theory bases by this postgraduate course.
  22. 22. 3. Devise and apply appropriate strategies and criteria for assessment Understand assessment stress demands understand students’ context. Most students have education loan or are spending considerable amount of family’s resources in their education. They are facing adulthood transition, and they are not sure about their own capabilities. Under this context, for them fail in one examination could means fail as individual. High marks represent a pay back for their families, increase in their self-esteem, and develop confidence. By the other side, assessment is also a society's guarantee that when the students become a professional he will not kill someone due his (or his teachers') incompetence. I have been in several accident evaluation and recovery due software implementation, and the causes sometimes are sensor failure due environmental conditions, and regretfully, sometimes are software implementation. Hazard operation evaluation could prevent most accidents, it is a mandatory step in the implementation of any software (such as underground or steel production), but accidents still happening. Methods of Assessment [11] from Constructivism point of view are the idea that learning is an active process of building meaning for oneself. Thus, students fit new ideas into their already existing conceptual frameworks. Constructivists believe that the learners' preconceptions and ideas about science are critical in shaping new understanding of scientific concepts. Assessment based on constructivist theory must link the three related issues of student prior knowledge (and misconceptions), student learning styles (and multiple abilities), and teaching for depth of understanding rather than for breadth of
  23. 23. coverage. Meaningful assessment involves examining the learner's entire conceptual network, not just focusing on discreet facts and principles. To overcome these difficulties assessment can be easier done since some ground rules are established between who assess and the students. a. Criteria It is fundamental importance describe what will be required from them when working as physicists. What type of software they will have to develop and what type of application defines the role programming will have in their life. Describing how they will be evaluate, based in their professional demands, helps them to study and be better prepared to compete in the market. Evidence #18 shows some list of criteria that will be required at Manchester, and it is a very good reference. It shows the importance of test beds, style, and documentation. The conventional forms for evaluation shows the criteria in the weight on top of it (evidences #19, #20, and #21). b. Performance index Assessment deals with objective and subjective evaluation. At Imperial College, 20% mark comes from student participation in laboratory and 80% from final project. At Manchester, every week the student accumulates points and the final project represents 20%. Clear definition about how marks are given is important to develop management skills. They attend several courses, with several tasks, and they have to prioritise their time according with results importance and weight. It is another important skill, because deliver in time is professional requirement.
  24. 24. In synthesis, performance index will define how much time and effort the student will spend in each task, and should take in account professional requirements. c. Recovery from crashes Learn how to deal with stress is very important. Some times stress makes students fail. An example is Olympic Games. Every competitor has usually only one chance in life to get a gold medal. What if in the competition day he is sick, or not in his best shape? It is over. Life usually is not so rigid. You can delay or change things due exogenous events. This is contingency management, and is another important management skill students have to acquire to keep themselves in the safe side. It is already taking in account when defining the performance index. If the project represents 20% and the students have a problem in the project week, they will be able to recover with only week tasks evaluation. However, if there is only a final exam, 100% of mark, there is nothing to do. The means to perform the evaluation can be done by marks of the project (adopted at Imperial College) or by an evaluation software (adopted at University of Manchester). The problems with demonstrators marking are: a. Each demonstrator give different amount of points for the same work.
  25. 25. b. Takes long time marking, and demonstrators are only part time academics. They have their research to perform. c. The demonstrator becomes a hangman. This could make students afraid to make questions and show “they are not good enough”. Under these circumstances, the introduction of CourseMark software is a very interesting approach Manchester adopted. First of all, student can be evaluate every week, which reduces the stress about final exams. Second, criteria are clearly defined, and are the same for all of them. The most important, make demonstrators and lecturers facilitators in the learning process. Students are agents in the learning process. The National Committee into Higher Education in 1997 (the Dearing Report) does not refer to "lecturers" but to "facilitators of student learning". We are there to help them overcome CourseMark. This is an incredible step forward. Another interesting result is plagiarism control. The software is able to cross students solutions and match any plagiarism. Students knew the software does this control, and every week only 6 students over 120 made plagiarism. Evidence #22 contains a learning set about assessment, and evidence #23 a learning set about dealing with student’s emotional responses to assessment. 4. Monitor and critically evaluate own professional practice and its impact on the student experience
  26. 26. It is easy to evaluate my own practice in laboratory, because even with 120 students, there are less them 3 cases every week that requires special attention. Some students are more than once under “observation”. The strategy I use to adopt is to go and start asking questions about what they are doing like if I have “nothing to do”. This is very easy, and students do not feel intimidated. Indeed, if things are not going as planned, I am able to help them without they know, offering relevant information when appropriate. Evidence #24 shows one female Chinese student case trying to solve bubble sort copying a solution from a book. The problem was the solution uses several pointers and concepts she didn’t have yet in class. She was very confused not only with the problem, but with the theory and syntax as well. I gave her an overview, and we abandoned the book solution and she started solving the problem with my supervision, explaining all the doubts she had. She was doing thinks based in questions I was asking her (evidence #25). Evaluation of my work comes in the next weeks, when she was able to solve all problems using pointers (evidence #26 and #27), and the challenge problem using pointers of pointers (evidence #28). Her mark was excellent at CourseMark (evidence #29). My approach allow me monitor and critically evaluate my professional practice because I am able to: a. Diagnostic learning problems with short notice, and adopt an effective course of action. b. Develop a contingency strategy to deal with the problem.
  27. 27. c. Help the student to be agent in the solution of their problems without take the control, developing their self confidence to deal with unexpected occurrences. d. Evaluate the learning process through next week problems and performance. e. Be facilitator in the learning process. This case happened every week, and it is a rewarding experience for lecturers and demonstrators. The feeling they are learning and achieving their goals. A wider evaluation will be done in the outcome Professional evaluation (section 8). 5. Perform teaching and academic administration effectively Management is required because there is a limited time and resources to achieve the best results, and the final evaluation should be based in accurate records and documentation. From the point of view of lectures and laboratory classes, it is important to point what have been done and where next class start. At Imperial College, I used to control how many tasks students have to perform and where is the critic threshold every week. Students close to the threshold will require a closer monitoring to achieve their goals (evidence #30). From assessment point of view, records are required to evaluate participation of students and work delivered. This is important to guarantee a fare assessment at end of course.
  28. 28. At Manchester, the use of CourseMark is a huge help from management point of view. All marks and deadlines are managed by it. Demonstrators do not have to take notes or do management tasks. However, it introduces a secondary management task: help students to plan their tasks and monitor if they are not wasting time, because they have to finish the problem by 5:00 pm, when the computer is powered off and they will not have access to CourseMark. By 3:00 I use to look after all the students and discuss with them the problems. It is an active approach instead passive adopted during the first part of section, but I try to make them agents in the process, only pointing problems and guiding them to obtain by themselves the solution. This is a very demanding task, because I have to perform the process for all students. One interesting case was one student did not have interest for computer programming, and she just did not understand what was going on. She attend the course because was mandatory at Imperial College, and she regrets “her lack of intelligence”. It was very unusual, because she apologise before ask questions and she had no self-confidence at all. Unfortunately, in the first class one of her colleagues answered her showing how stupid her questions were. I approach them and start telling more deep points about her question, and develop her confidence pointing her question was interesting. I kept a record of where she was every class, how many questions have she done, because I did not want to loose her. If the problem becomes severe, she could abandon the course, which would mean a failure of the system.
  29. 29. It was a rewarding surprise she finished the course with A mark, and she performed the project properly. Her development was outstanding, not only in computer programming but in self confidence and self esteem as well. Management records shown in evidence #30 allow an effective help of students in need. At the end of the day, management is to use the resources available (students time) to obtain the optimal result (good projects and learning process done) in time. 6. Provide support to students on academic matters Most of students frustration in the lab is consequence of do not establish a connection between their cognitive structure and the algorithm’s reasoning. Diagnostic students going through this anger/frustration state is trivial. Work in laboratory consists develop software in the computer, using only hands and brain. If the student start to look around, and move too much in his chair, it is frustration processing growing. This is result of anxiety because clock is ticking, 5:00 pm the work must be done, and the student is paralysed. The strategy I use to cope with this stressing condition is the direct approach. Just ask the student "How do you do?" and wait him formalise the problem and help him to find the right direction. Student verbal explanation contains only part of the necessary elements to write the problem specification and reduce it to a logic structure that can be coded in the computer program. The demonstrator has to fulfil the reasoning with pieces to form the complete algorithm.
  30. 30. Evidence #24 shows student copying the solution from a book, which uses a different technique and was far from the student's comprehension, which drive her upset because she does not understand the reasoning. There was not a cognitive structure to connect with the algorithm. My intervention was precisely what she needs. Point out structures she did not know what was about (evidence #25), and guide her developing her own solution. Verification of the success came next week, when she was able to solve all the problems (evidences #26 and #27) even the challenge problem and achieve excellent marks (evidence #29). Solution of challenge problem (evidence #28) was an evidence of her overcoming difficulties. The barrier for a demonstrator successful attack is sort out the missing links in student reasoning. We have to form a map, based in their description, of what is missing. There is a lost of information due the verbal communication as well. Under stress, it is difficult to the student to describe the reasoning. Demonstrator has to show confidence and knowledge about what is going on, and supports the student to overcome the difficulties. Sometimes, start from a common ground is a good strategy. For example, tell the student what is the goal of the problem and what elementary tasks need to be done. This is a common ground, there are no arguments about it, and give the demonstrator some time to understand what is going on, and what is missing in the student reasoning.
  31. 31. In any case, situation must end with the demonstrator making clear for the student that this is a normal process, and the student should think about how they have overcome the difficulties using rational strategy, and how they have coped with anxiety. It is not a coincidence that computers analysts have higher incidence of heart attack and strokes due the lack of anxiety dealing mechanisms and sedentary life. 7. Develop personal and professional coping strategies There are several barriers in any apprenticeship. Some endogenous to the issue, such as familiarity with abstraction, modelling, conceptualism, logic, and implementation approaches. Chapter 6 point out how to cope with these endogenous barriers specifically in programming languages. However students are not alone, without social interaction. They are in a cosmopolitan society, where several exogenous barriers could interfere with learning process. From the constructivist point of view[12] , "Whether knowledge is seen as socially situated or whether it is considered to be an individual construction has implications for the ways in which learning is conceptualized. From the radical constructivist perspective, how can their theory encompass both the collective activity and the individual experience to take into account the important classroom social interactions that are so much a part of the entire educational process? Such questions underlie the complexities involved in translating the diversity of perspectives into a common set of principles that can be operationalized."
  32. 32. Let us address some of these exogenous barriers in the laboratory and its influence in learning process, to overcome the complexities and provide a taxonomy of causes and possible course of actions. a. Student’s background issues. British education system is based in chronological classification of students. Students are classified by age and each class evolves during all years without any assessment. Promotion to next year is inevitable, besides mediocre achievement. British students face a new environment in the University with new rules. Each course has its own evaluation process, and students are required to be agents of learning process. This introduces a need for management skills and techniques to cope with uncertainty and contingencies. Academic staff must provide the necessary support in this new learning process. Teach them how to learn and improve is vital. b. Language issues. Most students travel to UK to learn not only a new professional skill, but to learn speak English. Students have the necessary level to understand and be understood, but communication can be a barrier. The problem is how different languages express information and how the student will assimilate new knowledge in a new language.
  33. 33. There are differences of context and every language has its own way to code information. To reduce impact of foreigner language, demonstrators must speak slowly, pronounce every word, and avoid use of idiomatic expressions. c. Cultural issues. Every country and group of people has his own set of values and principles, which constitute their culture. Culture affects religion, social stratification, and gender relations. University is a cosmopolitan place, and students must not be discriminated because they have different cultural values. In matter of fact, students should have incentive to share their believes and cultural values, when it is convenient and would improve or expand the issue under discussion. Discussion should be driven taking in account that differences came from different countries, with different geography, politics, economics and cultural conditions. The conclusion is every student is unique, with a different point of view, adequate to their environment. They must be respect as individuals and learning process must explore this diversity. I have been working with Muslins, Russians, British, and every culture has his appeal. I always tried to respect their beliefs as if their values are mine. They are individuals like me, and if I have grown up in their environment, I probably have their beliefs and costumes.
  34. 34. Evidences #1, #8, #11 shows the respect for their limits in the way I use to prepare diagrams that avoid description in any language. The stress the Chinese student went through (evidences #24 to #29) and the student at Imperial College that apologise at any question are another examples of coping strategies, dealing with all sort of personal problems, developing student’s self-steam and avoiding impacts in the learning process. There are several techniques I use to prepare to cope with different situations (talks, lectures, and students’ interaction). Body language is an issue. You can say thinks in a very methodological and conscious level, and your body can still all your credibility. Sometimes, even slight behaviours can affect the learning process. The tone of your voice can be even worse. Students will not believe you are not upset if you are shouting (a common behaviour when students are not able to understand the concept). Simulation of several classes of actions in front of a mirror is the best solution, if you can not afford a video camera. See yourself in a crises situation is important to give you a clear image of how you looks like, which allow you use your own knowledge of how you behave to become more reliable for the audience. 8. Reflect on own personal and professional practice and development Students went to University to acquire professional and personal values. These values represent skills and abilities to perform a critic problem
  35. 35. evaluation and propose solutions, be able to manage its implementation, and evaluate critically the work done. At the end of the course, students want to achieve a professional status and have their place in society as an active member. My career development started in my Bachelor in Physics (evidence #31), Master in Science (evidence #32) and PhD in Mechanical Engineering (evidence #33). I can supervise students to achieve an excellence professional status because I have been working developing new technologies for industry since 1971. I developed 15 automation projects for steel companies, 5 systems for public transport in Sao Paulo (the second biggest city in the world), 9 automation projects for sugar and alcohol production, 5 modernisation master plans for companies, and four technological departments implementation (see evidence #34 and #35). In academia, I developed several research projects using artificial intelligence and grid technology (see evidence #36 to #40). A complete list of publications is available at evidence #41. I am able to establish a relation between the issue under discussion and its relevance for a company project. These links make a huge difference in student attention, and in the learning process. When the issue has a clear relationship with practical and professional matters, students pay a lot of attention and expend time considering options and strategies. It is an effective and useful learning process. The student is facing the future working challenge under controlled and supervised conditions. They are able to make mistakes and learn with it.
  36. 36. In this context, I am able to provide students with guidance and support prepare them for real situations that will make them better professionals and better prepared for life. During this course and teaching was a rewarding experience, and I am thinking about became a lecturer to contribute to improve the supervision and teaching process with my practical experience. Evidence 52 shows that I am able to contribute even with my peers, through a friendly and interactive teaching process. 9. Overview of mind maps to design learning activities (Project-based developing learning and teaching module). When I am preparing a talk or a class, millions of ideas came to my mind at same time. I am not able to establish a sequential and sounding argument at once. I use to do a brainstorm and represent the ideas with mind maps (evidence #42, training course at University of Manchester). Evidence #43 to #46 shows the mind map for grid technology talks at BabarGrid-UK (Manchester), GridPP meeting (Liverpool), and Babar Meeting (Dresden/Germany). I start drawing mind map by one phrase/concept description (evidence #43). I know everybody has his own interests, but what would I like people remember from my talk? I use to think as if I am waiting the lift and Bill Gates stands with me. We enter the lift, and I have few minutes to sell him my idea. What should I say for him? This is my phrase/concept description.
  37. 37. My talk needed to sell the idea that University of Manchester achieved the necessary resources when I joined it to integrate Grid technology with Babar experiment software. I developed a prototype and was important to show that something was running with problems to justify a new funding, but with potential to succeed. Grid technology consists in middleware software called LCG2. It contains all necessary infrastructures to allow users run its application using Internet as if all available computers are one single huge computer resource. Babar experiment software is a library with more than 850 modules physicists can install and use to study matter constituents (called quarks). It uses data from Linear Accelerator at University of Stanford (USA). What I want people remember is that we are able to integrate LCG2 Job submission with Babar CM2 software at Manchester for Tau physics modelling, analysis and Monte Carlo generation. This is the central point of the mind map, and its starting point. Another important point is show possible interesting research using edge technology to solve fundamental problems in grid production. I proposed the use of Artificial Intelligence to model interactions and production environment for optimisation of resource use. After have define the central concept, I just write the ideas with links in the central concept, and ideas connected with other ideas, creating a map of concepts and its relationship. This is in agreement with constructivist point-of- view.
  38. 38. The next step I took lots of A4 half pages and start writing the ideas with some relation (evidence #44). This establishes independent modules that can be reused or removed from the final talk. To deliver these modules, I use PowerPoint to edit slides in a very didactic and attractive way. I try do not use too much visual effects to avoid pollution (evidence #45). To evaluate efficacy of my talk I invited a colleague to attend it (evidence #46). Two months later, I sent her a set of questions about my talk and asked her to answer without review my slides. She got the important points, what the software was intended to do and there still having problems to sort out and solve. She pointed even interesting points about how I could present the work in a more collaborative approach and get people involved. This feedback was very important because I had worked only 2 months in the project when I gave the talk, and I need to obtain the funding to stay at University of Manchester. The talk was a success, the funding was renewed and I received a lot of feedback from Babar Community. I would like to develop mind maps to represent knowledge and support learning design because it is a graphical way to represent knowledge and how it is related in our brain’s cognitive structure, based in a constructivist point of view. There are extensive references (evidence #47), and evidence #46 supports its efficacy. 10. Show how own practice with regard to the above outcomes is underpinned by specific proof values Learning process can be seen as a complex interactive system, with several components (Fig. 2).
  39. 39. Students are under pressure to achieve several goals, attend social demands, and find their place in society. Every student is unique, with his cultural and social development. Students are agents of learning process, but facilitators can improve and fastener the process. Facilitator should provide means for students overcome difficulties and develop themselves through his experience and skills. My own practice is underpinned by several professional values, which I have been showing in this portfolio. The understanding of how people learning is supported by constructivist understanding of how students acquire new knowledge and skills through reflection and abstraction (evidences #1 to #13), and how assessment should be understood as a feedback in the student’s agent learning process. Evidences of different assessment methods are a testimony of my attempt to improve it encouraging the facilitator with the student to overcome the assessment (evidences #18 to #23).
  40. 40. Fig. 2 Learning Process Context. I have been evaluated by several independents referees, my ability to teach, and my commitment to scholarship (evidences #14 to #17, and #51). The process have going through a team work with colleagues from CLTHE, other demonstrators, and senior lecturers which whom I have exchange experiences and discussed several issues. This is a continuity of my own work methodology in industry, where team work is fundamental because none has all skills and experiences, and a collective work supersedes in quality and standards compliance. Lectures and demonstrators work effectively with diversity, inclusivity and coping strategies in their day-by-day. Students have to overcome technical issues (evidences #24 to #28) and achieve their goals (evidence #29). They STUDENT: -values/culture -Background -Motivation -Knowledge -Feelings WORK MARKET -Companies’ goals -Requirements -Qualifications -Rewards SOCIAL ENVIRONMENT: -Behavioural requirements -Interaction -Resources -Demand Pressure FACILITATOR: -manage learning process -Provide support (academic/pastor al) -Professional experience -Skills LABORATORY: -Experiencing the learning process -Controlled and supervised resource
  41. 41. are allowed to make mistakes and I guide them learning and understanding what was wrong through inducing them think in a holistic point of view. I believe this is my duty, prepare them to assume a critical posture in front difficulties and problems. This will allow them deliver solutions and analysis with mature skills. At the end of the day, this is the requirement for a successful professional in modern work market. Be able to adapt him easily to a world changing in the speed of light, keeping always critical evaluation of him and the environment surrounding. We need to support them in the process, providing guidance and inspiration through a critical and systematic reflection on our own professional practice (evidences #31 to #41). This is an endless process, evident through my own development process in this course. Evidence #48 shows the first material I sent to my tutor Dr David Riley, my successful experiences (evidence #48) and the learning agreement of this project (evidence #49). Evidence #50 contains the assessment to my portfolio by my colleague Katja. Through the development of this portfolio, I have been through a deep discussion about all the outcomes and their impact in my professional practice. My evolution since the first ideas about the portfolio reflects a deep understanding of my role as learning facilitator. The portfolio is itself an evidence of this outcome. References 1. 2. 3. von Glasersfeld, E. (1995). A constructivist approach to teaching. In L. Steffe & J. Gale (Eds.). (1995). Constructivism in education, (pp.3-16). New Jersey: Lawrence Erlbaum Associates, Inc.
  42. 42. 4. Fosnot, C. (1996). Constructivism: A Psychological theory of learning. In C. Fosnot (Ed.) Constructivism: Theory, perspectives, and practice, (pp.8- 33). New York: Teachers College Press. 5. von Glasersfeld, E. (1996).Introduction: Aspects of constructivism. In C. Fosnot (Ed.), Constructivism: Theory, perspectives, and practice, (pp.3-7). New York: Teachers College Press. 6. 7. von Glasersfeld, E. (1987). Learning as a constructive activity. In C. Janvier, Problems of representation in the teaching and learning of mathematics, (pp.3-17). New Jersey: Lawrence Erlbaum Associates, Inc., p. 15 8. Ertmer, P.A. and Newby, T.J. (1993). Behaviorism, Cognitivism, Constructivism: Comparing critical features from an Instructional Design perspective. Performance Improvement Quarterly, 6(4), 50-72. 9. 10. PEDAGOGY AND SOCIOLOGY; 11. 12. Murphy, Elizabeth, 1997, Constructivist Learning Theory. On-line Available
  43. 43. 1. Diagram showing the relationship between data modelling and implementation (3 cases). The diagram shows the three different implementations to be developed in the problems, from the data modelling point of view (right hand side) and data modelling point of view (left hand side). The idea is to show how the three implementations are different and how use different C structures to implement it. 8. Diagram of data modelling (structures). The diagram shows the concept of data container and how to operate with it. Each box represents a structure element and its components. Components are also grouped in su- structures. Latter in the course, students will learn about classes and establish a relationship between the boxes and classes. This is a very important concept in software development: object oriented programming. 11. Diagram of algorithm implementation This diagram shows the algorithm to implement matrix multiplication. Each element of the resultant matrix is related with operations between elements highlighted by different colours. 18. Computer assessment This is the output of CourseMark software. Each criteria and requirement are clearly explained and the final mark is compose from each achieved requirement. 30. Supervision spreadsheet I developed this spreadsheet to mark students at Imperial College. The central part represents where each student were seat along all course, and their names. Each week I collected what task they have achieved and control the rhythm of the course to allow them have 3 weeks for the final project. Students late would have special attencion.
  44. 44. /******************************************************************** ***** * * Three-dimensional vector_sum program * PWM 16/11/04 * ********************************************************************* *****/ #include <iostream> #include <fstream> #include <cmath> using namespace std; /* vec3 represents a 3D vector, where x = r*sin(phi)*cos(theta) y - r*sin(phi)*sin(theta) z = r*cos(phi) r = sqrt(x*x + y*y + z*z) theta = atan(y/x) phi = acos(z/r) */ struct vec3{ double x; double y; double z; double r; double theta; double phi; }; // vec3 functions, taking pointer to vec3 as first argument void print_vec3(vec3* vp); void x_y_z(vec3* vp); void r_theta_phi(vec3* vp); void sum_array(vec3* vp2, vec3* vec_array, vec3* end); int main(void){ const int MAX = 100; vec3 va[MAX]; // read in the r, theta, phi values // after input end points just past end of active array // input terminates when r < 0 vec3* end; for(end = va; end - va < MAX; ++end){ cout << "Please enter three values for r, theta and phi (r < 0 to end): "; cin >> end->r; if(end->r < 0) break; cin >> end->theta >> end->phi; x_y_z(end); } // output the values cout << "nThe array of 3D vectors is: " << endl;
  45. 45. for(vec3* vp = va; vp - end; ++vp){ cout << "Element " << int(vp - va) << ':'; print_vec3(vp); cout << endl; } // now sum the vectors in the array vec3 vsum; vsum.x = vsum.y = vsum.z = 0; sum_array(&vsum, va, end); r_theta_phi(&vsum); // output the vector sum cout << "nThe vector sum of the array elements is " << endl; print_vec3(&vsum); cout << endl << endl; } // end of main() // function to print out one vector void print_vec3(vec3* vp){ cout << "tx = " << vp->x << "ty = " << vp->y << "tz = " << vp->z << 'n' << "ttr = " << vp->r << "ttheta = " << vp->theta << "tphi = " << vp->phi ; } // calcualte x, y and z, given r,theta and phi void x_y_z(vec3* vp){ vp->x = vp->r * sin(vp->phi) * cos(vp->theta); vp->y = vp->r * sin(vp->phi) * sin(vp->theta); vp->z = vp->r * cos(vp->phi); } // calculate r, theta and phi, given x, y and z void r_theta_phi(vec3* vp){ vp->r = sqrt(pow(vp->x, 2) + pow(vp->y, 2) + pow(vp->z, 2)); vp->theta = atan2(vp->y, vp->x); if(vp->r) vp->phi = acos(vp->z/vp->r); else vp->phi = 0.; } // sum the vectors in the array vec_array up to end; result in *vp2 void sum_array(vec3* vp2, vec3* vec_array, vec3* end){ for(vec3* vp1 = vec_array; vp1 - end; ++vp1){ vp2->x += vp1->x; vp2->y += vp1->y; vp2->z += vp1->z; } }
  46. 46. /******************************************************************** *********** * * 3 x 3 matrix inversion * PWM * 25/11/04 * ********************************************************************* **********/ #include <iostream> #include <fstream> #include <cstdlib> #include <cmath> using namespace std; void print_mat3(double m[3][3]); int main(){ double m1[3][3], m2[3][3], m3[3][3] = {}; char infilename[20]; cout << "Please enter input file name. " ; cin >> infilename; ifstream in(infilename); if(!in){ cerr << "Failed to open input file " << infilename << endl; exit(1); } // read in matrix dimension int dim; in >> dim; if(dim != 3){ cerr << "Program deals only with 3 x 3 matrices." << endl; exit(1); } for(int j = 0; j < 3; ++j) for(int k = 0; k < 3; ++k) in >> m1[j][k]; // output matrix cout << "nThe original matrix is " << endl; print_mat3(m1); double a = m1[0][0], b = m1[0][1], c = m1[0][2]; double d = m1[1][0], e = m1[1][1], f = m1[1][2]; double g = m1[2][0], h = m1[2][1], i = m1[2][2]; // calculate determinant double det_m1 = a*(e*i - f*h) - b*(d*i - f*g) + c*(d*h - e*g); if(!det_m1){
  47. 47. cout << "Singular matrix." << endl; exit(2); } else cout << "The determinant of the matrix is " << det_m1 << endl; // calculate inverse matrix m2[0][0] = e*i - f*h; m2[0][1] = c*h - b*i; m2[0][2] = b*f - c*e; m2[1][0] = f*g - d*i; m2[1][1] = a*i - c*g; m2[1][2] = c*d - a*f; m2[2][0] = d*h - e*g; m2[2][1] = b*g - a*h; m2[2][2] = a*e - b*d; for(int j = 0; j < 3; ++j) for(int k = 0; k < 3; ++k) m2[j][k] /= det_m1; // print out inverse cout << "nThe inverse matrix is " << endl; print_mat3(m2); // multiply m1 and m2, result in m3 for(int j = 0; j < 3; ++j) for(int k = 0; k < 3; ++k) for(int m = 0; m < 3; ++m) m3[j][k] += m1[j][m] * m2[m][k]; // print out product cout << "The product of the two is " << endl; print_mat3(m3); } // end of main() void print_mat3(double m[3][3]){ cout << endl; for(int j = 0; j < 3; ++j){ for(int k = 0; k < 3; ++k) cout << m[j][k] << 't'; cout << endl; } cout << endl; }
  48. 48. To: jamwer <> From: "Joanna D. Haigh" <> Subject: Re: James CLTHE Hello James We're fine. Computing teaching is much the same but with additional introductory sessions on measurements,errors & statistics and how to use Excel to plot graphs and do stats. I'm glad all is going well in Manchester and that you are taking a teaching course. I don't have any criticisms of your teaching in our C++ lab so I attach the reference I sent to Manchester for your files. Best wishes, Joanna At 10:29 01/11/2004, you wrote: >Dear Joanna, >How are you? >I am fine here at Manchester. I enjoyed so much demonstrate laboratory >under your supervision that I am attending the post graduate course to >obtain the Certificate Learning and Teaching in High Education. >I also am teaching C here in Manchester. >I would appreciate very much if you could send me an email telling your >evaluation about my work with you with sugestions to improve. This is very >important because I would drive my studies with it. I will put it in >my portfolio with evidences to demonstrate that I have experience >demonstrating laboratories. >Thanks. All the best! >James > >------------------------------------------- > >James Cunha Werner PhD, MSc, Bsc >Optimisation and Automation Technologies > >Phone: 0161 275 4150 >Fax: 0161 273 5867 > >High Energy Physics- Physics Department >University of Manchester >Schuster Laboratory >Brunswick Street >Manchester M13 9PL >
  49. 49. >Homepage: > >------------------------------------------- Prof. Joanna D. Haigh Space and Atmospheric Physics, Blackett Laboratory, Imperial College London, London SW7 2AZ, UK phone: +44 (0)20 7594 7671 fax: +44 (0)20 7594 7900 email: www:
  50. 50. Date: Wed, 1 Dec 2004 14:16:16 +0100 From: David Riley <> Reply-To: To: jamwer <> Subject: Re: Observation feedback Hi, Here is the observation; I used the layout of the form for feedback you have an example of. David. Observer comments: 1.Clarity of aims, objectives and outcomes The aims of each session are clear for the students, as it is part of a well structured course. The objectives also are clear and the outcome. I felt that the way the session was electronically marked might have been a bit clearer for them but this wasn^? part of your design in the course. 2.Delivery and presentation (eg. Structure, pace, voice management) This was clear and well tailored to each student^? ability. You were able to help without revealing any one ^?orrect^?way to solve the problem. 3.Knowledge of subject: (eg. Evidence of research/scholarship, ability to convey enthusiasm) Very impressive knowledge, enthusiasm and humour. 1. Student focus (eg. Awareness of individual and diverse need, rapport, flexibility) Well thought out approach, treating students as individuals. Aware of the different levels and pace students were working at 5.Management of learning environment (eg facilitation skills and planning/maintenance of physical environment)
  51. 51. This was not something you have control over. It seems to work well enough as it is. Any thoughts as to how you would want to do it? Was it different in other places you have taught? 6.Structure and timekeeping Not really applicable. Do you find students struggle to finish the problems in the time allocated sometimes? What do you do about this? 7.Use of resources: Your diagram on your notes (the program in memory etc.) seemed to work well and students seemed to understand it as an aid to your explanations. Interpersonal skills:(eg ability to give feedback, offer counsel or guidance, show sensitivity Very good; see 2 and 4 above. 9.General comments on any other aspects as agreed: An interesting session to observe; I look forward to any thoughts you may have. David Riley Programme Head, History & Archaeology Centre for Continuing Education Humanities Building University of Manchester Oxford Road Manchester M13 9PL Tel: 0161 275 3303
  52. 52. Date: Mon, 13 Dec 2004 12:42:30 +0000 From: Peter Mitchell <> To: jamwer <> Subject: Re: James - Laboratory Demo Dear James, Here are my comments. Sorry for the delay. With best wishes, Peter Mitchell Lecturer for PC2161 ======================================================== > 1.Clarity of aims, objectives and outcomes > > James has always come to the lab sessions having thought hard about the exercises set for that week. He has made notes to refer to to assist the students, and he has been very clear as to what is to be communicated. > 2.Delivery and presentation (eg. Structure, pace, voice management,) > > Computer lab demonstrating requires one-to-one discussion, which he has conducted professionally. > 3.Knowledge of subject: (eg. Evidence of research/scholarship, ability to > convey enthusiasm) > > > James is probably better qualified than I am concerning the material (C++ language), but his enthusiasm has been positively infectious. > 4. Student focus (eg. Awareness of individual and diverse need, rapport, > flexibility) > > He has been able to address each student's needs on demand. > 5.Management of learning environment (eg facilitation skills and > planning/maintenance of physical environment) > >
  53. 53. This has not been within his control. > 6.Structure and time-keeping > > His time-keeping has been impeccable. > 7.Use of resources: (eg AV equipment, handouts, IT) > > It is unusual in the context of demonstrating a computer lab to use aids, but James has devised and prepared some interesting and very helpful diagrams to assist the students' understanding. He has used these on a one-to-one basis very effectively. > 8.Interpersonal skills:(eg ability to give feedback, offer counsel or > guidance, show sensitivity > > You can sometimes detect that students would prefer NOT to be seen by a particular demonstrator. I have not seen that with James, but if anything the reverse. They wait until he is free before asking for help. So I think he must be doing this part right. > 9.General comments on any other aspects as agreed: > > James is one of a small number of demonstrators on whom I have relied when I have needed to discuss particular aspects of the exercises, or even finer points of the language. I have struggled to think of any suggestions for improvement. Peter W Mitchell 13th December 2004 ======================================================== On 29 Nov 2004, at 8:42, jamwer wrote: > Dear Peter, > I need your evaluation of my work in your laboratories to attach in my > portfolio. Would you please answer the following questions about my > demonstrations sections? > > 1.Clarity of aims, objectives and outcomes
  54. 54. > > > 2.Delivery and presentation (eg. Structure, pace, voice management,) > > > 3.Knowledge of subject: (eg. Evidence of research/scholarship, ability to > convey enthusiasm) > > > 4. Student focus (eg. Awareness of individual and diverse need, rapport, > flexibility) > > > 5.Management of learning environment (eg facilitation skills and > planning/maintenance of physical environment) > > > 6.Structure and time-keeping > > > 7.Use of resources: (eg AV equipment, handouts, IT) > > > 8.Interpersonal skills:(eg ability to give feedback, offer counsel or > guidance, show sensitivity > > > 9.General comments on any other aspects as agreed: > > > Thank you very much. > James > >
  55. 55. Week 4 Assignment A 3-vector class and a Lorentz 4-vector class Marking Sheet Assignment should be finished by 4:45 pm 25th February 2005. Marked sheet should be returned to Dr. H. Zhang. Weight 15%. Student Name: 1. Complete the 3-vector class, defined in Vec3.h and Vec3.cpp (5%). 1. Add subtraction and vector product (2%). 2. Add accessors for polar coordinates - magnitude and polar and azimuthal angles (2%). 3. Write a program to test and demonstrate the features that you add (1%). 4. Submit source (.cpp) files, header (.h) files, test program and sample output. 2. Design and implement a Lorentz 4-vector class (10%). 1. The 4-vector should be composed of your 3-vector for the space part and a double for the time part (3%). 2. Implement Lorentz boost (5%). 3. Write a program to test and demonstrate your implementation (2%). 4. Submit source (.cpp) files, header (.h) files, test program and sample output. Tutor’s name: Signature: Date:
  56. 56. Week 5 Assignment A string class based on C strings Marking Sheet Due time: before 4:45 pm, Friday, 11th March, 2005. Marked sheet should be returned to Dr. H. Zhang. Name: Date: You may submit the assignment by finishing either the basic part or the basic + advanced parts. For the advanced parts, you should finish on your own to get full marks. Basic requirements (5%): • It should have a constructor to initialize a string (e.g., string a(“hello”)) (1%) • Copy function (1%) • Addition of strings (2%) • Assignment operation (1%) Advanced requirements (5%): • Implement left addition of a C character and a C string (1%). • Implement right addition of a C character and a C string (1%) • implement find operations on a C character, a C string and your string (3%). Tutor Name Tutor Signature Date
  57. 57. Week 7 Assignment Marking Sheet Exercise of inheritance – construct a cube class based on a rectangle class Due time: 15 April 2005 Marked sheet should be returned to Dr. H. Zhang Weight (5%) Name: Date: 1. (2%) To construct a rectangle class, which a) holds information such as the length, width and area of the rectangle; b) has various constructors and destructor; c) has functions to access the details of the rectangle and compute the area of the rectangle. 2. (3%) To develop a cube class, which inherits all functions of the rectangle class and d) holds information about the height and volume of the cube; e) has various constructors and destructor; 1) has functions to access the details of the cube and compute the volume of the cube. Tutor’s Name Tutor’s signature: Date
  58. 58. WorkShopAss 19th March 2005 Points under discussion by learning set members: Why assess: -We have been assessed all life. Measure what lecturers and students have achieved.Bases for mutual feedback. -Part of learning process. Gauge student's learning & ability to apply -Identify needs (individual & group). Heterogeneous classes (students with few skills to skilled ones) will drive assessment methods. -Feedback to lecturers about the course and how they are delivering the content, driving the process. -Feedback to students help them in their learning strategy and commitment, and develop their self-confidence. -Assessment and learning curve: quantitative approach. How learning courve variance influences content deliver and learning process. -Assess to provide society with professionals with satisfatory quality standards. -Education should result in changes. Assessment measure these changes. -Assessment helps reflect in Kobe cycle. -Help make connections between concepts. Assessment should be: -valid -reliable -fair -transparent -equitable. Aligning assessment: -aims -> intented learning outcomes -> methods of learning -> assessment methods & tasks -> criteria -> marking/feedback Goals of assessment: -Assessment evaluate course goals and outcomes: efficacy of learning process and every student taken their own merit. -Measure how students developed themselves in the course. Influences on assessment: -Evaluate results and achievements: subjective criterias and goals. -Different people give different marks for the same work. -Political external influences over our work. We have bosses and leaders with their own point of view. Decisions are out of our control. -Good teaching/good delive means good results. Are we intented to give good marks to show we are good? -Student/teacher interface: who is the expert? Perception of expertise: focus on diversity. Approaches to learning: -Deep approach; -Surface approach
  59. 59. -Strategic approach Planning assessment: -Manageable assessment: something lecturers will not spend too much effort. -Different goals: -during the course, formative assessment. Review feedback during course. -end of course, summative assessment. Blind assessment. Takes place at the end of a course and/or contribute to final grade. -journals show how they evolve during the course. Students are amazed with their improvement comparing their first entries with final ones. -different types described in Race Lecturer's Toolkit Book page 31. -Criteria and requirements: -present facts (process information). Structure and clear objectives. -examples and evidences -supporting the argument (case support). -references -development of argument. Clear delivery -definition of terms -critical thinking skills -concepts. How evolves. -content -process fair and transparent. -use of audio visual aids; engage audience; enthusiasm; musicallity; hand out. Ethics of assessment: -teacher's own agenda -external agendas -quality issues. -reliability issues. Knowledge X skills: -knowledge: generic information about some field. -skill: expertness, applied knowledge to some process. -Knowledge is what remains from school after long time. Skill allow professionals do their job. -Mix of both is very clear in any learning outcomes. Assessment is the judgement of evidence submitted for a specific purpose is therefore an aid of measurement. It requires two things: evidence and a standard or scale. Kathryn Eccletone; Understanding assessment; NIACE 1994 Standard or scales all involve measuring that individuals against: -referencial - an absolute criterion (driver license). -norm referenced - a cohort or group (Olympics gold medal). only top marks pass. -self-assessment: the learner's own previous performance (weightwatchers) References: Biggs,J.B. 1982; Evaluating the quality of learning the solo taxonomy structure of the observed learning outcome, New York.
  60. 60. Entwistle 1994; Teaching and the quality of learning CVCP/SRHE. Bond,D. !985; Reflecting: turning experience into learning; Kogan Page. LTSN Assessment series
  61. 61. Learning Sets: Record of Meeting Date & time of meeting: 8 April 2005 Place: Centre for Continuing Education 16.45-17.45am Names of those present: Martin Rigby Katja Stuerzenhofecker James Werner Summary of main issues discussed: Dealing with students' emotional responses to assessment • Teacher's issues: Don't become part of the students' problem. Stay on their side and leave the problem on the other side. Have clear learning outcomes to protect yourself. • Student's issues: Help students to use stress positively Help students to be more realistic Develop students' self-confidence Find the common ground Get students to use feedback for improvement Future action agreed: • Katja to email notes • Arrange the final Action Learning Set meeting to share and discuss draft portfolios (as far as we have got) in the week starting 16 May. Signed by representative of group: Katja Stuerzenhofecker
  62. 62. Evidence #41: International Conference papers Werner,J.C.; Kalganova,J.C.; “Risk Evaluation using Evolvable Discriminate Function.” ECML/PKDD2003 Discovery Challenge. Kalganova,T.; Karol, I.M.; Werner,J.C.; Silkou,N.I.; Lipnitskaya,N.G.; “Probability prediction method of throat cancer with use of discriminate function” (in Russian) 2nd International Belarusian-Polish Conference on Otorhinolaryngology: Actual Problems in Otorhinolaryngology, Grodno, 29-30 May 2003 Werner,J.C.; Kalganova,J.C.; “Disease modeling using Evolved Discriminate Function”. LNCS 2610, Proceedings 6th European Conference, EuroGP 2003, Essex, UK, April 14-16, 2003. Werner,J.C.; Fogarty,T.C.; “Severe diseases diagnostics using Genetic Programming.” Intelligent Data Analysis in medicine and pharmacology – IDAMAP2001; September 4th , 2001 London Werner,J.C.; Fogarty,T.C.; “Genetic programming applied to Collagen disease & thrombosis.” PKDD 2001 Challenge on Thrombosis data – Germany/ Freiburg September 3-7 Werner,J.C.; Fogarty,T.C.; “Genetic control applied to asset managements.” EuroGP2002 – Kinsale/Ireland April 3-5,2002. Werner,J.C.; Fogarty,T.C.; “Artificial intelligence applied to rescheduling and optimisation.” Operational Research Society (UK): Simulation Study Group Two day workshop 20-21 March 2002- University of Birmingham. Werner,J.C.; Sotelo Jr,J.; Lima,R.G.; Fogarty,T.C.; “Active noise control in ducts using genetic algorithms.” Active 2002 – Southampton July 15-17 2002. Werner,J.C.; “Genetic programming applied to pharmaceutical drugs design.” Data mining Cup 2001 of The Seventh ACM SIGKDD International Conference on Knowledge discovery and data mining – USA/ San Francisco, August 26-29,2001. Werner,J.C.; “Genetic programming applied to gene function identification.” Data mining Cup 2001 of The Seventh ACM SIGKDD International Conference on Knowledge discovery and data mining – USA/ San Francisco, August 26-29,2001 Werner,J.C.; “Genetic programming applied to gene location identification.” Data mining Cup 2001 of The Seventh ACM SIGKDD International Conference on Knowledge discovery and data mining – USA/ San Francisco, August 26-29,2001 Werner,J.C.; Sotelo Jr,J.; "A parallel DSP architecture running genetic algorithms applied to acoustic noise cancellation" II European DSP education and research conference - Paris/French - 1998. Werner,J.C.; Sotelo Jr,J.; "A parallel genetic algorithms applied to acoustic noise cancellation" Int. Symp. on artificial intelligence in real time control-USA-1998. Werner,J.C.; Sotelo Jr,J.; "A parallel genetic algorithms applied to acoustic noise cancellation" VI Pan American congress of applied mechanics - PACAM VI/DINAME 99 - Brazil. Werner,J.C.; Sotelo Jr,J.; "Active control of noise in ducts" I Iberian- American Congress of Acoustic –SOBRAC - Brazil 1998.
  63. 63. Werner,J.C.; Sotelo Jr,J.; "Active acoustic noise control in ducts in 3- dimensional enclosed space" XIII U.S. National Congress of Applied Mechanics-USA- 1998. Werner,J.C.; Sotelo Jr,J.; "Active Control of noise in ducts using genetic algorithms" II Symposium on Research Polytechnic School of USP-1997. Werner,J.C.; Sotelo Jr,J.; “Optimisation of batch fermentation through genetic algorithms and optimal techniques” IASTED Applied Modelling and Simulation /Banff - CANADA 1997. Werner,J.C.; Sotelo Jr,J.; “Active acoustic noise control in ducts” DINAME 97 - International Symposium on Dynamic of Machines of the Brazilian Association for Mechanics Science – March/1997 pages 193 to 195.
  64. 64. Evidence #46: Talk evaluation 2 months later. Date: Mon, 1 Nov 2004 16:57:06 +0000 (GMT) From: Christina Edgar <> To: jamwer <> Subject: Re: James Evaluation Hi James, I'll do my best. Please don't be disheartened if I can't remember details. They do say that, even with the best will in the world, most people only retain 20% of what they are told!! On Mon, 1 Nov 2004, jamwer wrote: > Dear Chris, > > I would appreciate very much if you could answer the following > questions about my talk "Enabling grid for HEP" two months ago. > I am doing postgraduate course in teaching, and I need to know > what you remember from my talk, if it make you think about, and > how did you feel. > Please do not look the slides to answer the questions. > 1. What was the talk about? Getting GRID set up at Manchester (Tier A or 1?) Also about a job submission trial you did which involved typing only one command (which didn't work a fair percentage of the time). > 2. Have the talk make you think about how grid/job submission would > help you in your day-by-day? The principle is very interesting and sounds useful - submit a job and it gets split up into many pieces to allow the workload to be spread - but I am not sure that my perception of GRID changed much. > 3. Have you changed something or have you make any decision due the talk? Nope - sorry! > 4. Tell me your impressions about the talk: > 4.1 How I delivered the issue?
  65. 65. With confidence. You were convincing as to assuring me that you knew what you were talking about. However, in places, your talk did not seem aimed at the right audience: the talk was to fellow GRID computing people but your talk was aimed at the user. This is probably as you did not know what the parallel sessions were like. In BaBar you do not need to sell yourself as having all the answers but rather you should offer up ideas and solutions for discussion with fellow BaBarians. The key word is collaboration. I hope that the people who mentioned various hypernews and helpful things did, in fact, email you details and so now you should be in contact with people working on similar issues to you. > 4.2 The slides. What do you remember of it and how do you evaluate > it? Mainly writing? Bullet points. Code written up - command line, at least. I don't remember any coloured background or template style but I could be doing you an injustice in saying that. Many talks that get given at BaBar look very plain. I think it is nice to have a standard layout throughout the presentation - maybe headers and footers or a shaded background? It is all personal preference. > 4.3 The reaction from the audience. People were definitely listening. There was a lot of feedback. Personally, I think you concentrated on your idea that "didn't quite work out" whereas you could have spent much more time describing how you have got the GRID up and working at Manchester. I think people would have been very impressed with that! The audience acknowledged your enthusiasm. An audience of people working in the same field as you can be quite hostile - I think they were. This is where the idea of presenting ideas, rather than saying you have the solution, might have helped. > 4.4 Your feelings during the talk. It was interesting. You were certainly engaging. It is not my subject at all - computing - so I was pleased to find that I understood 90% of what you were talking about. > I have to show evidences and make a self assessment based in your answers. > Your answer are crucial important for my homework. > Thanks for your help and all the best. > James >
  66. 66. I hope these ramblings are helpful. I have been honest in my opinion of your talk in the hopes of being useful to you in future presentations. Please do not take offence at any of my remarks -remember I am only giving one person's opinion. Thanks, Christina =;-) * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * Mrs Christina Edgar * * PhD Student at The University of Manchester * * * * **** **** * * * * Currently based at SLAC... * * Office phone: 650 926 8550 * * Address: Mail Stop 41, Building 280, * * SLAC, 2575 Sand Hill Road, * * Menlo Park, California 94025 USA * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
  67. 67. Dear David, Please find bellow the material for our meeting this week. It contains the 4 itens of first core task. I would like very much you could provide me with your experience not only in the dissertation structure, but in the way I intent to approach the issue as well. Do you have good references to improve the work? There are so many papers about the issue. I will be available Tuesday & Thursday all day, and Monday afternoon. Best regards, James 1. Profile and self-audit comprising: a. Hopes and expectations concerning the course I am attending this postgraduate course to increase my chances to get a permanent Lecturer job at University of Manchester. I have a good record of publications and research in computing science and artificial intelligence, however teaching still a weak point in my CV. ------------------------------------------------------------------------------------------------------ b. SWOT analysis in relation to my current role: STRONG: Professional experience in industry: I am able to supervise students and teach courses that has practical contents. Successful teaching experiences in several industries (trainning users in softwares I developed) and universitiers. Successful learning experiences, such as my PhD Enthusiasm in the issue: I like to teach computer and programming issues. Management practice in several large projects. Research portfolio with more than 20 international publications. WEAK: Knowledge of learning/teaching methods lack of experience teaching for undergraduates Modesty. OPORTUNITY: CLTHE available will boost my CV Post graduate certificate will improve my employability over other candidates Improve my skills and quality of service study programming computer laboratory and discuss different approaches and methodologies THREAT: The students do not understand the issue: -Lack of previous information (not in the module) -Lack of understanding in the session -Gap of information (something trivial for me).
  68. 68. -Relevance of issue for the student Be ready to overcome any unplanned gap/difficulty in class student plagiarism market overcrowded with lectures discrimination (I am Brazilian). reduction number students high education ------------------------------------------------------------------------------------------------ c. Summary Curriculum Vitae: Qualifications Ph.D. in Mechanical Engineering (optimisation and control) - Sao Paulo State University - 1999. Master in Science - Sao Paulo State University - 1984. Bachelor in Physics - Sao Paulo State University - 1981. Career History Researcher in Department of High Energy Physics/Grid Computing at University of Manchester from June 2004, developing grid computing for Babar community. Researcher in Department of High Energy Physics/Grid Computing at IMPERIAL COLLEGE between October 2003 and June 2004, evaluating the Community Authorisation Server (CAS) and Globus Toolkit 3 (GT3) for e-Science UK project Research Fellow in Department of Electronic and Computer Engineering at Brunel University between October 2002 and September 2003, applying the artificial intelligence framework (PhD Thesis) for medical data mining. This technology was transferred to Belarusian Medical Academy and Belarusian State University allowing the diagnostic and treatment optimisation in Belarus, consequence of Chernobyl's nuclear radioactive contamination accident. Research Fellow at South Bank University between April 2001 and September 2002, applying the artificial intelligence framework (PhD Thesis) for industrial optimisation. Partner of Gentech Inf. Aut. Tecn. S/C Ltda between 1995 and 2001, developing and applying the PhD Thesis framework in companies process simulations. Adviser in Research and Industrial Automation Manager at Zillo-Lorenzetti Company - June/1989 to April/1995, with the implementation of new technologies for industrial and agriculture processes for sugar and alcohol production. Software development for Procontrol System Engineering, Co from April/1986 to May/1989 supervising the Software Laboratory and managing the automation software projects. System Analyst at Metropolitan Company of S? Paulo (Metro) from September/1984 to April/1986, developing the Transport Simulation and Evaluation System and the scientific support of the underground system. Professor of Physics at Objetivo High School from August/1980 to March/1982. Teaching Experience
  69. 69. I have been teaching Programming Language in the Laboratory at Imperial College for 1st year Physics students (undergraduate) 6 hours/week. I supervise the project development of 7 students per term. I have developed a Modern Artificial Intelligence course, focused in adaptive methods, neural networks, genetic algorithms, genetic programming, and fuzzy logic to provide the student with a detailed knowledge of AI framework, both design and analysis. While students are encouraged to work on projects of personal interest, topics are also suggested and all projects are supervised to generate a panel for presentation in an "Artificial Intelligence Fair". Real time software I have been developing for industry requires a large effort in user training and technology transfer. It is an extreme condition teaching where the users have different previous experience and skills and the issue is a multidisciplinary field. My experience teaching Physics in high school developed new approaches and didactic for Arts, humanities and social sciences to keep them motivated and in touch with the classes (50 students per class without presence list). Research and Administration experience I have been working developing new technologies for industry since 1984. I developed 15 automation projects for steel companies, 5 systems for public transport in Sao Paulo (the second biggest city in the world), 9 automation projects for sugar and alcohol production, 5 modernisation master plans for companies, and 4 technology departments implementation. An extensive list of projects is available in my homepage: Books Werner,J.C.; "Active Noise Control in ducts using genetic algorithms." (in Portuguese) PhD Thesis at Mechanical Engineering Department - Polytechnic School/S? Paulo University, 1999, with CNPq scholarship. Werner,J.C.; "Nuclear structure effect in O16+Ti 46,50 scattering." (in Portuguese) MSc Dissertation at Physics Institute/S? Paulo University, 1984, with CNPq scholarship. International Conference papers Werner,J.C.; Kalganova,J.C.; "Risk Evaluation using Evolvable Discriminate Function." ECML/PKDD2003 Discovery Challenge. Kalganova,T.; Karol, I.M.; Werner,J.C.; Silkou,N.I.; Lipnitskaya,N.G.; "Probability prediction method of throat cancer with use of discriminate function" (in Russian) 2nd International Belarusian-Polish Conference on Otorhinolaryngology: Actual Problems in Otorhinolaryngology, Grodno, 29-30 May 2003 Werner,J.C.; Kalganova,J.C.; "Disease modeling using Evolved Discriminate Function". LNCS 2610, Proceedings 6th European Conference, EuroGP 2003, Essex, UK, April 14-16, 2003. Werner,J.C.; Fogarty,T.C.; "Severe diseases diagnostics using Genetic Programming." Intelligent Data Analysis in medicine and pharmacology - IDAMAP2001; September 4th, 2001 London