An Editor for Helping Novices to Learn Standard ML

This paper describes a novel editor intended as an aid in the learning of the functional programming language Standard ML. A common technique used by novices is programming by analogy whereby students refer to similar programs that they have written before or have seen in the course literature and use these programs as a basis to write a new program. We present a novel editor for ML which supports programming by analogy by providing a collection of editing commands that transform old programs into new ones. Each command makes changes to an isolated part of the program. These changes are propagated to the rest of the program using analogical techniques. We observed a group of novice ML students to determine the most common programming errors in learning ML and restrict our editor such that it is impossible to commit these errors. In this way, students encounter fewer bugs and so their rate of learning increases. Our editor, C Y NTHIA, has been implemented and is due to be tested on st..

Are the Mechanisms for Assessing the Quality of Training for Graduates of the Russian Penitentiary System Perfect?

The relevance of the study is due to the need to assess the quality of training of graduates of the Russian penitentiary system and the lack of an effective tool to assess the quality and level of training of graduates who have mastered professional educational programs at educational institutions of the Federal Penitentiary Service of Russia. In this regard, this article is aimed at identifying or disclosing mechanisms for evaluating the quality of educational services by independent experts, representatives of the employer, through professional and public accreditation of educational programs in educational institutions of the Federal Penitentiary Service of Russia. The leading methods to the study of this problem are general scientific methods (analysis, synthesis, analogy, generalization, etc.), which to introduce allow a comprehensive review of the procedure for professional and public accreditation of educational programs in the system of the Russian Federation. The article reveals the expected results of introducing the institution of professional public accreditation of educational programs in the Russian penitentiary system: improving the quality of the implemented educational programs, the level of organization of staff training, the quality and relevance of educational services, and the image of departmental services. The materials of the article are of practical value for improving the evaluation system of professional educational programs implemented in educational institutions of the Federal Penitentiary Service of Russia

Are the Mechanisms for Assessing the Quality of Training for Graduates of the Russian Penitentiary System Perfect?

The relevance of the study is due to the need to assess the quality of training of graduates of the Russian penitentiary system and the lack of an effective tool to assess the quality and level of training of graduates who have mastered professional educational programs at educational institutions of the Federal Penitentiary Service of Russia. In this regard, this article is aimed at identifying or disclosing mechanisms for evaluating the quality of educational services by independent experts, representatives of the employer, through professional and public accreditation of educational programs in educational institutions of the Federal Penitentiary Service of Russia. The leading methods to the study of this problem are general scientific methods (analysis, synthesis, analogy, generalization, etc.), which to introduce allow a comprehensive review of the procedure for professional and public accreditation of educational programs in the system of the Russian Federation. The article reveals the expected results of introducing the institution of professional public accreditation of educational programs in the Russian penitentiary system: improving the quality of the implemented educational programs, the level of organization of staff training, the quality and relevance of educational services, and the image of departmental services. The materials of the article are of practical value for improving the evaluation system of professional educational programs implemented in educational institutions of the Federal Penitentiary Service of Russia

Are the Mechanisms for Assessing the Quality of Training for Graduates of the Russian Penitentiary System Perfect?

The relevance of the study is due to the need to assess the quality of training of graduates of the Russian penitentiary system and the lack of an effective tool to assess the quality and level of training of graduates who have mastered professional educational programs at educational institutions of the Federal Penitentiary Service of Russia. In this regard, this article is aimed at identifying or disclosing mechanisms for evaluating the quality of educational services by independent experts, representatives of the employer, through professional and public accreditation of educational programs in educational institutions of the Federal Penitentiary Service of Russia. The leading methods to the study of this problem are general scientific methods (analysis, synthesis, analogy, generalization, etc.), which to introduce allow a comprehensive review of the procedure for professional and public accreditation of educational programs in the system of the Russian Federation. The article reveals the expected results of introducing the institution of professional public accreditation of educational programs in the Russian penitentiary system: improving the quality of the implemented educational programs, the level of organization of staff training, the quality and relevance of educational services, and the image of departmental services. The materials of the article are of practical value for improving the evaluation system of professional educational programs implemented in educational institutions of the Federal Penitentiary Service of Russia

Proof-Pattern Recognition and Lemma Discovery in ACL2

We present a novel technique for combining statistical machine learning for proof-pattern recognition with symbolic methods for lemma discovery. The resulting tool, ACL2(ml), gathers proof statistics and uses statistical pattern-recognition to pre-processes data from libraries, and then suggests auxiliary lemmas in new proofs by analogy with already seen examples. This paper presents the implementation of ACL2(ml) alongside theoretical descriptions of the proof-pattern recognition and lemma discovery methods involved in it