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Kearsley, Greg P. – 1977
This paper discusses and provides some preliminary data on errors in APL programming. Data were obtained by analyzing listings of 148 complete and partial APL sessions collected from student terminal rooms at the University of Alberta. Frequencies of errors for the various error messages are tabulated. The data, however, are limited because they…
Descriptors: Computer Science Education, Error Patterns, Programing, Programing Languages
Pea, Roy D. – 1984
Persistent conceptual bugs exist in how novices, from primary school to college age, program and understand programs. These bugs are not specific to a given programming language but appear to be language-independent. The three different classes of bugs are: (1) parallelism, the assumption that different lines in a program can be active at the same…
Descriptors: Computer Science Education, Elementary Secondary Education, Error Patterns, Higher Education
Peer reviewed Peer reviewed
Mason, Margie – Arithmetic Teacher, 1985
Using Logo to work through a maze is described. Suggested programs to help students learn to debug programs are also included, along with the story of the original "computer bug." (MNS)
Descriptors: Computer Software, Elementary Education, Elementary School Mathematics, Error Patterns
Peer reviewed Peer reviewed
Pea, Roy D. – Journal of Educational Computing Research, 1986
Three classes of conceptual bugs presenting obstacles to all novice programmers and not related to any specific program--parallelism, intentionality, and egocentrism--are identified and exemplified through student errors. It is suggested these bugs are rooted in students' intuitive feeling that programming languages, like humans, have intelligent,…
Descriptors: Classification, Egocentrism, Error Patterns, Intuition
Sleeman, D.; Gong, Brian – 1985
In order to determine the knowledge and skills needed by novice programmers to successfully learn computer programming, four studies were conducted using a clinical interview technique. The first study determined that many systematic errors in programming were due to programmers' high-level misconceptions of the nature of the computer and of the…
Descriptors: Computer Science Education, Computer Software, Computers, Error Patterns
Peer reviewed Peer reviewed
Pierson, Joan K.; Horn, Jeretta A. – AEDS Journal, 1984
Unsuccessful programing attempts by university business students in introductory COBOL classes were analyzed to determine most frequently occurring syntactical errors. Results indicate the most common errors were use of undeclared data in Procedure Division, missing periods, misspelled reserved words, missing hyphens, and use of wrong margin area.…
Descriptors: Business Education, Educational Research, Error Patterns, Higher Education
Perkins, David; And Others – 1986
To learn more about the specific nature of the teaching and learning problems involved, researchers conducted a clinical study of 20 high school students enrolled a BASIC course. Investigators presented each student with a sequence of eight programming problems, ranging from easy to difficult. They asked questions to track student thinking and…
Descriptors: Difficulty Level, Error Patterns, High Schools, Knowledge Level
Peer reviewed Peer reviewed
Nagy, G.; Pennebaker, M. Carlson – International Journal of Man-Machine Studies, 1974
An investigation which develops a method for the automatic collection of meaningful statistical information about the causes of program resubmittal in a batch-processing environment. (Author)
Descriptors: Automation, Computer Science, Data Processing, Error Patterns
Peer reviewed Peer reviewed
Perkins, D. N.; Simmons, Rebecca – Review of Educational Research, 1988
Certain misunderstandings in science, mathematics, and computer programing reflect analogous underlying difficulties. These misunderstandings are examined through four knowledge levels: (1) content; (2) problem-solving; (3) epistemic; and (4) inquiry. Analysis of several examples shows that misunderstandings have causes at multiple levels, and…
Descriptors: Cognitive Processes, Comprehension, Concept Formation, Error Patterns
Peer reviewed Peer reviewed
Attisha, M.; Yazdani, M. – Instructional Science, 1984
Describes a microcomputer-based system for diagnosing children's multiplication errors which incorporates the knowledge base of all known systematic multiplication errors, and utilizes a modular approach to cope with the program's complexity. Each module's function, how the programs interact, and the design of pupil-machine interaction are…
Descriptors: Computer Assisted Instruction, Diagnostic Teaching, Elementary Education, Error Patterns
Lee, Okhwa; Lehrer, Richard – 1987
Seven graduate students in a seminar on classroom computing received instruction in LOGO programming. Programming protocols were collected periodically and examined for errors and misconceptions; in-depth interviews were conducted in order to understand specific misconceptions better. As novice students transit from instruction to experience in…
Descriptors: Computer Oriented Programs, Computer Science Education, Concept Formation, Educational Research
Summers, Mike K.; Willett, John B. – Creative Computing, 1980
The need for traps, a program routine which checks the validity of the user's response to the computer's request for input, in Computer Assisted Learning Packages, is discussed. Several example traps are described. (MK)
Descriptors: Computer Assisted Instruction, Computer Oriented Programs, Computer Programs, Error Patterns
Putnam, Ralph; And Others – 1984
Misconceptions high school students have about constructs in the BASIC programming language were examined in this study. A total of 96 high school students received a screening test after a semester course in BASIC programming, and 56 of these students were subsequently interviewed by means of questions and short programs prepared in advance. The…
Descriptors: Computers, Error Patterns, High School Students, High Schools
Peer reviewed Peer reviewed
Pusack, James P. – System, 1983
Five categories of answer-processing for computerized drill programs in foreign languages are described: nonevaluation, right-wrong evaluation, pattern markup, error anticipation, and parsing. Each strategy is explained in terms of its operation, advantages and disadvantages, ease of use for authoring courseware, and capability to support…
Descriptors: Computer Assisted Instruction, Error Patterns, Evaluation Criteria, Evaluation Methods
Soloway, Elliot; And Others – 1982
This report examines the features and performance of the BUG-FINDing component of MENO-II, a computer-based tutor for beginning PASCAL programming students. A discussion of the use of artificial intelligence techniques is followed by a summary of the system status and objectives. The two main components of MENO-II are described, beginning with the…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer Programs, Computer Science Education
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