Tools for Tutoring Theoretical Computer Science Topics

This thesis introduces COMPLEXITY TUTOR, a tutoring system to assist in learning abstract proof-based topics, which has been specifically targeted towards the population of computer science students studying theoretical computer science. Existing literature has shown tremendous educational benefits produced by active learning techniques, student-centered pedagogy, gamification and intelligent tutoring systems. However, previously, there had been almost no research on adapting these ideas to the domain of theoretical computer science. As a population, computer science students receive immediate feedback from compilers and debuggers, but receive no similar level of guidance for theoretical coursework. One hypothesis of this thesis is that immediate feedback while working on theoretical problems would be particularly well-received by students, and this hypothesis has been supported by the feedback of students who used the system. This thesis makes several contributions to the field. It provides assistance for teaching proof construction in theoretical computer science. A second contribution is a framework that can be readily adapted to many other domains with abstract mathematical content. Exercises can be constructed in natural language and instructors with limited programming knowledge can quickly develop new subject material for COMPLEXITY TUTOR. A third contribution is a platform for writing algorithms in Python code that has been integrated into this framework, for constructive proofs in computer science. A fourth contribution is development of an interactive environment that uses a novel graphical puzzle-like platform and gamification ideas to teach proof concepts. The learning curve for students is reduced, in comparison to other systems that use a formal language or complex interface. A multi-semester evaluation of 101 computer science students using COMPLEXITY TUTOR was conducted. An additional 98 students participated in the study as part of control groups. COMPLEXITY TUTOR was used to help students learn the topics of NP-completeness in algorithms classes and prepositional logic proofs in discrete math classes. Since this is the first significant study of using a computerized tutoring system in theoretical computer science, results from the study not only provide evidence to support the suitability of using tutoring systems in theoretical computer science, but also provide insights for future research directions

A Computable Economist’s Perspective on Computational Complexity

A computable economist's view of the world of computational complexity theory is described. This means the model of computation underpinning theories of computational complexity plays a central role. The emergence of computational complexity theories from diverse traditions is emphasised. The unifications that emerged in the modern era was codified by means of the notions of efficiency of computations, non-deterministic computations, completeness, reducibility and verifiability - all three of the latter concepts had their origins on what may be called 'Post's Program of Research for Higher Recursion Theory'. Approximations, computations and constructions are also emphasised. The recent real model of computation as a basis for studying computational complexity in the domain of the reals is also presented and discussed, albeit critically. A brief sceptical section on algorithmic complexity theory is included in an appendix

A Computable Economist’s Perspective on Computational Complexity

A computable economist.s view of the world of computational complexity theory is described. This means the model of computation underpinning theories of computational complexity plays a central role. The emergence of computational complexity theories from diverse traditions is emphasised. The unifications that emerged in the modern era was codified by means of the notions of efficiency of computations, non-deterministic computations, completeness, reducibility and verifiability - all three of the latter concepts had their origins on what may be called "Post's Program of Research for Higher Recursion Theory". Approximations, computations and constructions are also emphasised. The recent real model of computation as a basis for studying computational complexity in the domain of the reals is also presented and discussed, albeit critically. A brief sceptical section on algorithmic complexity theory is included in an appendix.

The Category of the Conjuction in Categorial Grammar

En aquest treball es proposa un tipus categorial per a les conjuncions (i, o, etc.) dins del formalisme de la Gràmatica Categorial. En primer lloc s'exposen tres característiques fonamentals que qualsevol tractament de la conjunció ha de poder explicar. Després es contemplen les diferents aportacions que s'han fet dins aquest formalisme per a delinear una categoria de la conjunció que permeti donar compte dels fenòmens del llenguatge natural. Totes aquestes aportacions es comenten respecte de la seva adequació amb les tres característiques de la conjunció exposades al principi. Seguidament, es proposa una categoria per a les conjuncions que pot donar compte de les característiques esmentades. Aquesta categoria introdueix un nou operador n-tuple que resulta també molt útil per a l'anàlisi d'altres fenòmens del llenguatge natural.In this work a categorial type for conjunctions (and, or, etc) is proposed within the Categorial Grammar formalism. First of all, I present three main characteristics that have to be accounted for in any analysis of conjunction. Secondly, I explain the different contributions that have been made within this formalism to fmd a category for conjunction that allows us to account for natural language phenomena. All those proposals are commented on with regard to the three properties to be explained. Next, a categorial type for conjunctions is proposed which can account for those characteristics. This category introduces a new n-tuple operator which is also useful for analysing other natural language phenomena

Outline bibliography, and KWIC index on mechanical theorem proving and its applications

Bibliography and KWIC index on mechanical theorem proving and its application

Constraining Montague Grammar for computational applications

This work develops efficient methods for the implementation of Montague Grammar on a computer. It covers both the syntactic and the semantic aspects of that task. Using a simplified but adequate version of Montague Grammar it is shown how to translate from an English fragment to a purely extensional first-order language which can then be made amenable to standard automatic theorem-proving techniques. Translating a sentence of Montague English into the first-order predicate calculus usually proceeds via an intermediate translation in the typed lambda calculus which is then simplified by lambda-reduction to obtain a first-order equivalent. If sufficient sortal structure underlies the type theory for the reduced translation to always be a first-order one then perhaps it should be directly constructed during the syntactic analysis of the sentence so that the lambda-expressions never come into existence and no further processing is necessary. A method is proposed to achieve this involving the unification of meta-logical expressions which flesh out the type symbols of Montague's type theory with first-order schemas. It is then shown how to implement Montague Semantics without using a theorem prover for type theory. Nothing more than a theorem prover for the first-order predicate calculus is required. The first-order system can be used directly without encoding the whole of type theory. It is only necessary to encode a part of second-order logic and this can be done in an efficient, succinct, and readable manner. Furthermore the pseudo-second-order terms need never appear in any translations provided by the parser. They are vital just when higher-order reasoning must be simulated. The foundation of this approach is its five-sorted theory of Montague Semantics. The objects in this theory are entities, indices, propositions, properties, and quantities. It is a theory which can be expressed in the language of first-order logic by means of axiom schemas and there is a finite second-order axiomatisation which is the basis for the theorem-proving arrangement. It can be viewed as a very constrained set theory