Anderson, John R.,Reiser, Brian J., 1985, The Lisp Tutor, Byte Magazine, vol.10, Page 159-175, April Astrachan, O. (1998). Concrete teaching: Hooks and props as instructional technology. Paper presented at the Annual Joint Conference Integrating Technology into Computer Science Education, Dublin City University, Ireland.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....intelligent programming environments or intelligent tutoring systems in the field of programming use syntax oriented problem solvers to diagnose faults in students programs. Some of them are based on rule systems and examine, whether the last programming step was correct or not (cf. LISP in [1]) or whether a program can be deducted from the specification by formal transformation (cf. ABSYNT in [2] Others are case based and compare the student s program with stored correct or faulty solutions (cf. ELM in [3] or they try to identify goals and plans of correct or faulty intentions (cf. ....

Anderson, J.R.; Reiser, B.J.: The LISP tutor. In: BYTE, vol. 10, no. 4, S. 159--175, 1985.

....of some programming concepts and also in their ability to assimilate new concepts. 3 Background Many novice programmers experience difficulties and frustrations in their attempts to learn programming. Researchers in the field generally concede that programming is a difficult skill to master [2] [3] Students experience difficulties developing, comprehending and debugging programs, often reaching impasses from which they cannot proceed without assistance. Mayer [4] said that meaningful learning occurs when new knowledge is actively associated with appropriate pre existing knowledge ....

....as text books and study guides. Again these are static media which are also unresponsive if a student does not understand something the book cannot explain it in a different way. x Human tutors, teaching on a one to one basis, are probably the best way to teach novices. Anderson and Reiser [2] reported that students with access to private tutors learned as much Lisp in eleven hours as other students did in forty three hours. However, access to human tutors in educational institutions is often very limited. Another way to assist novice programmers is to provide computerised assistants ....

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ANDERSON, J. R. AND REISER, B. J. (1985). The Lisp Tutor. Byte, April, 159-175.

....to executing the next step for the student. The systems which implement this technology can watch the actions of the student, understand them, and use this understanding to provide help and to update the student model. The classic example from the domain of teaching programming is the LISP TUTOR (Anderson Reiser, 1985); recent examples 1985) are the ACT Programming Tutor (Corbett Anderson, 1992) and GRACE (McKendree, Radlinski Atwood, 1992) Interactive problem solving support technology in not as popular in Web based systems as in standalone systems because, up to now, server based WWW applications are not ....

Anderson, J. R. and Reiser, B. (1985) The LISP tutor. Byte 10 (4), 159-175.

....process through cooperative and competitive problem solving. First, the teacher presents a problem to be solved by both agents. The student and learning companion can then ask questions while they try to solve the problem. Another such tutoring system is the Lisp Intelligent Tutoring System [Anderson and Reiser, 1985], which attempts to teach the student how to program in LISP. The student is presented with a programming task, and then the system assists the student with question and answer sessions while the student solves the problem. This is done by attempting to determine what steps the student might take ....

J.R. Anderson and B.J. Reiser. The LISP tutor. Byte, 10:159--175, 1985.

....learning on demand, design, domain oriented design environments, coverage, obsolescence, information overload, making information relevant to the task at hand, critiquing. 1. Introduction Innovative uses of computers in education have focused on two major approaches: intelligent tutoring systems [Anderson, Reiser 1985; Psotka, Massey, Mutter 1988; Polson, Richardson 1988; Wenger 1987] and open learning environments [Boecker, Eden, Fischer 1991; diSessa, Abelson 1986; Wenger 1987] The strength of intelligent tutoring systems lies in their ability to teach basic concepts and skills of a problem domain. ....

....Examples and Case Based Reasoning. Examples can play a crucial role in design. Lewis and Olson [Lewis, Olson 1987] observed that the productivity of casual programmers can be increased by their adapting examples through analogy. Examples have been the focus of studies in learning LISP[Pirolli, Anderson 1985] as well as other areas [Chi et al. 1989] The catalog in our systems [Redmiles 1992] serves as a library of designs, which users can access and extend. The use of examples is similar to work in case based reasoning, in which previous solutions or cases form the basis of new plans or task ....

J.R. Anderson and B.J. Reiser, The LISP Tutor, in (eds.), BYTE, 1985,

....its actions. NEOMYCIN was built to make this knowledge more explicit. The next system to be considered tackled this difficulty by having a knowledge representation for an ideal student rather than an expert. 2.1.3. 2 Model Tracing Using an Ideal Student Model The Lisp Intelligent Tutoring System [Anderson Reiser 1985] was one of two systems designed by Anderson s group as a result of their work on ACT theory [Anderson 1983] The other, the Geometry Tutor is discussed later. Besides the cognitive theory and pedagogical recommendations of ACT , the design of the Lisp Tutor was based on studies of novices ....

....of the Lisp Tutor was based on studies of novices learning Lisp [Anderson, Farrell Sauers 1984] The Tutor has three main components used in diagnosis: an ideal student model, a bug catalogue and a set of tutoring rules. Figure 2.3 illustrates the interface to the tutor: Figure 2. 3 Lisp Tutor [Anderson et al. 1985] The ideal student model is a set of production rules which simulate the actions of an ideal student in the domain rather than an expert. The disadvantage of using an expert model is that this would contain more advanced heuristics, macro rules, compiled knowledge and techniques only covered in ....

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Anderson, J.R. & Reiser, B.J. [1985]. The LISP Tutor. Byte 10, 4, 159-175.

....This graph can be considered to be a fully connected graph, with most weights at 0. The weights, which represent the ideal way of proceeding through the course, are determined a priori by a domain expert. Unlike traditional ITSs that determine what students see (for example, the LISP tutor [1] and the Cardiac tutor [6] the MANIC system does not strictly impose presentation of prerequisite topics before a new topic is started. Additionally, we have extended the existing course by providing alternative ways to present essentially the same material. This is done by providing easy, ....

J. Anderson and B. Reiser. The LISP Tutor. Byte, 10(4):159--175, 1985.

....has proven extremely useful in improving the education of students [4] Intelligent tutoring systems can provide this individualized instruction that cannot be achieved in a lecture style class. Intelligent tutoring systems have been used to teach various types of skills, from Lisp programming [1] to treating heart attack patients [10] For training people in technical fields, we have developed educational systems that provide realistic working environments [16] These systems include simulations of machinery that are used in the real world and can provide opportunities to learn that ....

J. Anderson and B. Reiser. The lisp tutor. Byte, 10(4):159--175, 1985.

.... ITS design has been an active focus of research since the early days of AI, and over the years a number of impressive results and prototype systems have been discussed in the literature, including SCHOLAR (Carbonell, 1970) GUIDON (Clancey, 1983) STEAMER (Hollan et al. 1984) the LISP Tutor (Anderson and Reiser, 1985) and SHERLOCK (Lajoie and Lesgold, 1989) Although research in ITS has produced full systems such as those listed above, researchers have understandably expended the bulk of their efforts developing enabling technologies for ITS, e.g. student modeling and lesson planning techniques. In fact, ....

Anderson, J. R. and Reiser, B. J. (1985) The LISP Tutor. Byte, vol. 10, no. 4, pp. 159--175.

....7] The main difference is in the method of instruction. Program schemata are tought just once when the first declarative language is introduced (e.g. Lisp) Afterwards, students modify known program schemata when learning programming in the other declarative language (e.g. Prolog) Similarly to [2], we feel that students should perform as much of the program forming process as possible (i.e. they should learn by doing rather than by simply being told) Tutor should provide a student with a structure of the problem solution (i.e. provide the student with a template to fill in) We propose ....

.... (output) and (ii) second argument as input is transformed into the first one (output) In this case the program squareAll can be used for mapping elements of the input list to the list of squared elements and for finding a list of elements such that their squares form the input list: squareAll([1, 2, 3], Y) Y = 1, 4, 9] squareAll(X, 1, 4, 9] X = 1, 2, 3] In [3] program schemata are criticized that they describe entire predicates and so a novice never has to address the problems of relating clause ordering to the control flow of the predicate. So there is danger that novices do ....

[Article contains additional citation context not shown here]

J.R. Anderson and B.J. Reiser. The LISP tutor. Byte, 10(4):159--175, 1985.

....has proven extremely useful in improving the education of students [6] Intelligent tutoring systems can provide this individualized instruction that cannot be achieved in a lecturestyle class. Intelligent tutoring systems have been used to teach a variety of skills, from Lisp programming [1] to treating heart attack patients [20] For training people in technical fields, educational systems have been developed that provide realistic working environments [28] These systems include simulations of complex and dangerous machinery, thus providing opportunities to learn that otherwise ....

....bidirectional. Topics that are closely related will have higher weights on the links, while those that are not closely related will have lower weights. The weights are determined a priori by a domain expert. Unlike traditional tutors that determine what students see (for example, the LISP tutor [1] and the Cardiac tutor [20] the MANIC system does not strictly impose presentation of prerequisite topics before a new topic is started. Furthermore, it is often necessary to add course material, i.e. supplemental topics to the existing material. This might be done for two reasons: 1) material ....

J. Anderson and B. Reiser. The LISP Tutor. Byte, 10(4):159--175, 1985.

....systems (ITSs) have been built in which the learner model is represented using a bug catalogue, expressed as a set of production rules which describe (at some level of detail) possible bugs which a learner may have. This approach has been used in a number of subject areas: Lisp programming [ANDE 85a] Geometry [ANDE 85b] Algebra [MATZ 82; SLEE 89; ANDE 89] Fractions [EVER 82; NWAN 89] Subtraction [BROW 78] and Pascal programming [JOHN 85] A bug catalogue is a data structure which is used to facilitate the mapping between CBM and RLBM. It typically contains a list of anticipated ....

Anderson, J. R. and Reiser, B. (1985). "The Lisp tutor", Byte, vol. 10, pp. 159-175.

....medical diagnosis, chemistry, geography, economics, electronics, game playing, and computer programming. Many tutoring systems have been implemented that teach novices how to program a computer. There are automated tutors for nearly every programming language. With the exception of the LISP Tutor (Anderson Reiser, 1985), however, existing programming language tutoring systems are actually not complete tutoring systems, but merely the program debugging component (or diagnosis component) The authors of these systems claim that tutoring and student modeling components can be added to their systems, but give no ....

....Several attempts have been made to tackle either or both of these tasks for a number of programming languages. All approaches to automated program debugging require some form of plan library which consists of a collection of representative programs. Plan library approaches (e.g. the LISP Tutor (Anderson Reiser, 1985), PROUST (Johnson, 1986) TALUS (Murray, 1988) and APROPOS2 (Looi, 1988) decompose the problems into collections of well defined operations. These collections of operations are stored in a library of plans. The general approach to constructing these debuggers is to build a system with an initial ....

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Anderson, J.R. & Reiser, B.J. (1985). The Lisp Tutor. Byte, 10, 159-175.

....of research into guided discovery. They form a critical mass of research into how to interact with students as they learn complex procedural ideas in an exploratory fashion with guidance from an intelligent tutor. The growing body of interesting research being amassed around the CMU Lisp Tutor (Anderson and Reiser (1985) Reiser et al. (1985), Corbett and Anderson (1989) etc. for example, shows a relatively rare occurrence within ITS of research cumulating into some coherent pyramid (heap ) of knowledge. 8 The goals in the tutor s goal space would also be organized in subgoal hierarchies, another granularity relationship. The ....

....Faced with such free ranging behaviour, most diagnostic systems display a notorious lack of robustness. One way of controlling this problem is to restrict the student s freedom so that he or she stays within the scope of the student s knowledge (this is the approach taken in the LISP Tutor, Anderson and Reiser, 1985). We believe, however, that if the range of student behaviour and student knowledge can be arrayed in granularity hierarchies, then we can still allow the student to have free rein. While it might be impossible to recognize what a student is doing at a fine grain size, it will surely be possible ....

Anderson and Reiser (1985). J. Anderson and B. Reiser, "The LISP Tutor", Byte, 10, 4, pp. 159175.

....or behaviour. In the buggy models the rules that account for the learner s non standard performance are usually drawn from a set of known possible rules, usually called a bug catalogue. This approach has been used in subject areas such as subtraction [6] fractions [29] and Lisp programming [2]. The development of the bug catalogues which can run into several hundred rules has been very labour intensive. The implication is that it requires a great deal of time and expertise (through experimental studies and laborious analyses of learners problem solving) to develop a bug catalogue ....

Anderson J.R. and Reiser B. (1985): "The Lisp tutor". Byte, vol. 10, pp. 159-175.

....for each of these (say, n 5) and up to p steps to a solution (say, p 10) then there may be up to (m (n 1) p paths to analyse (about 10 24 ) which is clearly intractable. We can, of course, eliminate the combinatorial explosion if we ensure that p=1, as in the Lisp tutor (Anderson and Reiser, 1985), constraining the student to the smallest analysable step, with the consequent imposition of a rigid tutorial style. However, we still have the considerable difficulty of determining an appropriate grain of detail in defining the (mis)transformations. It is relatively easy to interrupt a ....

Anderson, J.R. and Reiser, B. (1985). The Lisp tutor, Byte, 10, 159-175.

.... ITS design has been a focus of research since the early days of work on AI, and over the years a variety of impressive results and implemented systems have been documented in the literature, e.g. SCHOLAR (Carbonell, 1970) GUIDON (Clancey, 1983) STEAMER (Hollan et al. 1984) the LISP Tutor (Anderson and Reiser, 1985), and SHERLOCK (Lajoie and Lesgold, 1989) As the field has matured, it has become apparent that research is being impeded by the lack of modular system architectures, reusable components and sharable knowledge bases. Given the current state of the art, each new research or development effort ....

Anderson, J. R. and Reiser, B. J. (1985) The LISP Tutor. Byte, vol. 10, no. 4, pp. 159--175.

....7] The main difference is in the method of instruction. Program schemata are taught just once when the first declarative language is introduced (e.g. Lisp) Afterwards, students modify known program schemata when learning programming in the other declarative language (e.g. Prolog) Similarly to [2], we feel that students should practice as much of the program forming process as possible (i.e. they should learn by doing rather than by simply being told) Tutor should provide a student with a structure of the problem solution (i.e. provide the student with a template to fill in) We propose ....

.... and (ii) the second argument as input is transformed into the first one (output) In this case the program squareAll can be used for mapping elements of the input list to the list of squared elements and for finding a list of elements such that their squares form the input list: squareAll([1, 2, 3], Y) Y = 1, 4, 9] squareAll(X, 1, 4, 9] X = 1, 2, 3] In [3] program schemata are criticized that they describe entire predicates and so a novice never has to address the problems of relating clause ordering to the control flow of the predicate. So there is danger that novices do not ....

[Article contains additional citation context not shown here]

J.R. Anderson and B.J. Reiser. The LISP tutor. Byte, 10(4):159--175, 1985.

....and the trace methods of recursion are described below. 2.1 Loop method The loop method is a flawed method of recursive problem solving. Many learners acquire the loop method in their early stages of learning recursive programming (Anzai Uesato 1982; Kahney 1982; Kurland Pea 1985; Kessler Anderson 1986). This method comes into existence when the learner tries to understand and explain recursion in terms of prior knowledge about iterative programming. 5 Typically, the beginner has some basic declarative knowledge about recursion either from a text book or from a teacher. This knowledge could ....

....programming. Their findings can be summarized as follows: 1) Novices at early stages of learning about recursive programming possess a loop model; that is, they view the behavior of recursion as some sort of iterative process (Anzai Uesato 1982; Kahney 1982; Kurland Pea 1985; Kessler Anderson 1986). 2) A syntactic method of recursion has been suggested by Pirolli (1986) as an ideal novice model for coding solutions to recursive problems, yet with a syntactic model a learner cannot explain the behavior of a recursive procedure (Kahney 1982) 3) Prior learning of iteration may help learners ....

[Article contains additional citation context not shown here]

Anderson, J.R. & Reiser, B. (1986) The LISP Tutor, Byte, 159-175, April.

....planning behaviour (Anderson et al. 1984) and automatic program debuggers which provide tutorial advice (Johnson, 1986) Indeed, Intelligent Tutoring Systems (ITSs) in the domain of programming have combined many of these approaches to provide some important results. For example, the Lisp Tutor (Anderson and Reiser, 1985; Corbett et al. 1990) is a commercial product which is used regularly to teach a full semester of introductory Lisp programming at U.S. universities, and the Advanced Placement Computer Science Practice and Feedback System (APCS) Sack, 1992; Sack and Bennett, patent pending) is being developed ....

.... spinoffs that we can have our cake and eat it too (i.e. cater for the full range of programmers and possible programming tasks) We then describe our approach to Software Visualization in some detail, and show how it deals with examples taken from PROUST (Johnson, 1986) and the Lisp Tutor (Anderson and Reiser, 1985). Finally, to emphasize the scalability of our approach, we present an example of Software Visualization applied to the debugging of an operating system comprising approximately 7,500 lines of code. Four ITS Fallacies We believe that several obstacles to future progress are inherent in the ....

[Article contains additional citation context not shown here]

Anderson, J. R. and Reiser, B. J. (1985). The Lisp Tutor. BYTE: The Small Systems Journal, 10(4), 159-175.

No context found.

Anderson, John R.,Reiser, Brian J., 1985, The Lisp Tutor, Byte Magazine, vol.10, Page 159-175, April Astrachan, O. (1998). Concrete teaching: Hooks and props as instructional technology. Paper presented at the Annual Joint Conference Integrating Technology into Computer Science Education, Dublin City University, Ireland.

No context found.

Anderson, J. R., & Reiser, B. J. (1985, April). The LISP tutor. Byte, pp.159-175.

No context found.

Anderson, J. and Reiser, B. "The LISP Tutor." Byte, 10:4, 1985.

No context found.

Anderson, J. and Peiser, B. "The LISP Tutor." Byte, 10:4, 1985.

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Anderson, J.R. and Reiser, B.J. 1985. The LISP Tutor. BYTE, 10(4):159-175.

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