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Automatic Programming: Overviews


A Survey of Automated Programming Hint Generation -- The HINTS Framework

arXiv.org Artificial Intelligence

Automated tutoring systems offer the flexibility and scalability necessary to facilitate the provision of high quality and universally accessible programming education. In order to realise the full potential of these systems, recent work has proposed a diverse range of techniques for automatically generating hints to assist students with programming exercises. This paper integrates these apparently disparate approaches into a coherent whole. Specifically, it emphasises that all hint techniques can be understood as a series of simpler components with similar properties. Using this insight, it presents a simple framework for describing such techniques, the Hint Iteration by Narrow-down and Transformation Steps (HINTS) framework, and it surveys recent work in the context of this framework. It discusses important implications of the survey and framework, including the need to further develop evaluation methods and the importance of considering hint technique components when designing, communicating and evaluating hint systems. Ultimately, this paper is designed to facilitate future opportunities for the development, extension and comparison of automated programming hint techniques in order to maximise their educational potential.


AN OVERVIEW OF

AAAI Conferences

As a first step, a system has been implemented to assist in the trial-anderror process of developing new models and techniques for quantitative interpretation of well logs. The user interface exploits graphical techniques to enable petroleum scientists to describe their models in the natural concepts of the domain. The resulting specification can be implemented in any of several different target languages. The system is in active use by petroleum scientists, who find that it has significantly reduced the time to get feedback on hypothesized models.


Some Studies in Machine Learning Using the Game of Checkers, II - Recent Progress

Classics

A new signature table technique is described together with an improved book learning procedure which is thought to be much superior to the linear polynomial method described earlier. Full use is made of the so called “alpha-beta” pruning and several forms of forward pruning to restrict the spread of the move tree and to permit the program to look ahead to a much greater depth than it other- wise could do. While still unable to outplay checker masters, the program’s playing ability has been greatly improved.See also:IEEE XploreAnnual Review in Automatic Programming, Volume 6, Part 1, 1969, Pages 1–36Some Studies in Machine Learning Using the Game of CheckersIBM J of Research and Development ll, No.6, 1967,601