Programming Tutor Research Articles

Knowledge tracing: Modeling the acquisition of procedural knowledge

This paper describes an effort to model students' changing knowledge state during skill acquisition. Students in this research are learning to write short programs with the ACT Programming Tutor (APT). APT is constructed around a production rule cognitive model of programming knowledge, called theideal student model. This model allows the tutor to solve exercises along with the student and provide assistance as necessary. As the student works, the tutor also maintains an estimate of the probability that the student has learned each of the rules in the ideal model, in a process calledknowledge tracing. The tutor presents an individualized sequence of exercises to the student based on these probability estimates until the student has ‘mastered’ each rule. The programming tutor, cognitive model and learning and performance assumptions are described. A series of studies is reviewed that examine the empirical validity of knowledge tracing and has led to modifications in the process. Currently the model is quite successful in predicting test performance. Further modifications in the modeling process are discussed that may improve performance levels.

Reader's perception of importance: What ASP readers think is important and why

The authors conducted a study with Psychology I Academic Support Programme (ASP) students and tutors which explored readers' perception of importance in reading a Psychology I text. They explored a) what readers think is important and b) what strategies readers use to determine importance. From the analysis of the data four categories of readers emerged according to the strategies which they were using to process the text for important sentences. There was no significant difference between the performance on the selection task or the essay by the three different categories of ASP students. However, the findings are consistent with other research on differences between good and poor readers and support some of the general theories about learning problems of students from disadvantaged educational backgrounds.

A structured planning and debugging environment for elementary programming

How could an appropriately structured environment facilitate the acquisition of programming skills? Significant theoretical strides are needed before human-quality performance can be expected from a computer-based programming tutor. As an intermediate step, a system has been implemented which serves primarily as an editing language and diligent clerk. However, it differs from conventional programming environments in two crucial ways: (1) it interacts with the student using a vocabulary of concepts about planning and debugging, derived from an explicit model of the design process; and (2) it actively prompts the student with a menu of design alternatives, within the overall framework of a mixed-initiative dialogue. The current system is not a tutor; but the process of implementing and testing it has been instrumental in refining our model of the design process, thereby bringing us a step closer to realizing a computer-based programming tutor.

Assuming That Everyone Can Learn Everything, Will Some Learn Less?Human Characteristics and School Learning. Benjamin S. Bloom

Previous articleNext article No AccessReview EssayAssuming That Everyone Can Learn Everything, Will Some Learn Less? Human Characteristics and School Learning. Benjamin S. Bloom Lauren B. ResnickLauren B. Resnick Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Volume 85, Number 3May, 1977 Article DOIhttps://doi.org/10.1086/443354 Views: 6Total views on this site Citations: 9Citations are reported from Crossref Journal History This article was published in The School Review (1893-1979), which is continued by the American Journal of Education (1979-present). Copyright 1977 The University of ChicagoPDF download Crossref reports the following articles citing this article:Albert T. Corbett, Akshat Bhatnagar Student Modeling in the ACT Programming Tutor: Adjusting a Procedural Learning Model With Declarative Knowledge, (Jan 1997): 243–254.https://doi.org/10.1007/978-3-7091-2670-7_25Albert T. Corbett, John R. Anderson Knowledge tracing: Modeling the acquisition of procedural knowledge, User Modelling and User-Adapted Interaction 4, no.44 (Jan 1995): 253–278.https://doi.org/10.1007/BF01099821David W. Dalton, Michael J. Hannafin The Effects of Computer-Assisted and Traditional Mastery Methods on Computation Accuracy and Attitudes, The Journal of Educational Research 82, no.11 (Jan 2015): 27–33.https://doi.org/10.1080/00220671.1988.10885861Robert E. Slavin Mastery Learning Reconsidered, Review of Educational Research 57, no.22 (Jun 2016): 175–213.https://doi.org/10.3102/00346543057002175Marshall Arlin Time, Equality, and Mastery Learning, Review of Educational Research 54, no.11 (Jun 2016): 65–86.https://doi.org/10.3102/00346543054001065Marshall Arlin Time Variability in Mastery Learning, American Educational Research Journal 21, no.11 (Jun 2016): 103–120.https://doi.org/10.3102/00028312021001103Gary E. Dunkleberger, Henry W. Heikkinen Mastery learning: Implications and practices, Science Education 67, no.55 (Oct 1983): 553–560.https://doi.org/10.1002/sce.3730670503 Marshall Arlin Teacher Responses to Student Time Differences in Mastery Learning, American Journal of Education 90, no.44 (Oct 2015): 334–352.https://doi.org/10.1086/443652Sandra Anselmo Book Reviews: Bloom’s Human Characteristics and School Learning in Perspective, Educational Researcher 10, no.1010 (Jul 2016): 29–30.https://doi.org/10.3102/0013189X010010029

INTELLITUTOR: Integrated IntelligentProgramming Environment For Novices

The INTELLITUTOR was designed as an integrated environment for both learning programming and friendly programming aid. The system consists of three software modules, i.e., GUIDE, ALPUS and TUTOR, one document database and four knowledge bases. GUIDE is a guided editor for easy coding, ALPUS is a knowledge-based program understander, and TUTOR is an embedded intelligent tutoring system. ALPUS infers user's intentions from buggy program codes by means of knowledge-based reasoning. INTELLITUTOR attempts to work as a human programming tutor to guide a user in programming, to detect logical errors within a user' program, and to make advices not only for fixing them but also for letting him notice his misunderstandings. The key knowledge used to understand user's programs is the knowledge about algorithms, which is organized in a form of hierarchical data structure called Hierarchical Procedure Graph(HPG). The knowledge about programming techniques and errors are organized around it. Although the experimental system is dealing with PASCAL programs most knowledge maintained within the knowledge base is applicable to other procedure-oriented programming languages as well. The system was implemented in the frame-based knowledge engineering environment ZERO on a UNIX workstation.