Learning Flow of Control
Recursive and Iterative Procedures
Bibliographic Data
| ID | 15216166 |
|---|---|
| Authors | Claudius Kessler (Carnegie Mellon University, corresponding author), J Anderson (0000-0002-9488-8447), Jared R Anderson (0000-0002-3094-8885, Carnegie Mellon University) |
| Year | 1986 |
| Volume | 2 |
| Issue | 2 |
| Pages | 135-166 |
| Publication date | 1986-06-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Human-Computer Interaction (JOURNAL) |
| Journal identifiers | ISSN: 0737-0024 • E-ISSN: 1532-7051 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1207/s15327051hci0202_2 |
| OpenAlex | W2071201688 |
| Language | EN |
| Citations received | 2 |
| References cited | 7 |
Two experiments were performed to study students' ability to write recursive and iterative programs and transfer between these two skills. Subjects wrote functions to accumulate instances into a list. Problems varied in terms of whether they were recursive or iterative, whether they operated on lists or numbers, whether they accumulated results in forward or backward manner, whether they accumulated on success or failure, and whether they simply skipped or ejected on failure to accumulate. Subjects had real difficulty only with the dimensions concerned with flow of control, namely, recursive versus iterative, and skip versus eject. We found positive transfer from writing iterative functions to writing recursive functions, but not vice versa. A subsequent protocol study revealed subjects had such a poor mental model of recursion that they developed poor learning strategies which hindered their understanding of iteration. It is argued that having an adequate model of the functionality of programming is prerequisite to learning to program, and that it is sensible pedagogical practice to base understanding of recursive flow of control on understanding iterative flow of control
Algorithm · Control (management · Control flow · Flow (mathematics · Iterative learning control · Iterative method · Machine learning · Programming language · Protocol (science · Recursion (computer science · Recursive partitioning · Computer Science · Educational Games and Gamification · Intelligent Tutoring Systems and Adaptive Learning · Mathematics · Medicine · Teaching and Learning Programming · Artificial Intelligence
| Unique citing works | 2 |
|---|---|
| Citations per year | 0,06 |
| Citation span | 1991 - 1995 (5) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |