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Computer Lab Work on Theory
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0003-3199-8953
Abstract [en]

This paper describes an attempt to introduce computer lab exercises on NP-completeness proofs in a class already containing computer lab exercises on algorithms and data structures. In the article we are interested in the answer of the following question: Can the students feel that their understanding of theoretical computer science is improved by performing a computer lab exercise on the subject? The class is mandatory for students in a computer science program, and is taken by about 130 students each year. Theory of NP-completeness proofs with reductions has previous years been examined on an individual assignment with written solutions handed in and later explained orally by the student to a teacher. The new assignment is performed as a computer lab exercise where students are working in small groups of two. This exercise is placed before the individual assignment, and is examined first by running automated test cases and later by an oral presentation in lab to a teacher. An improvement can be observed of the students' average results since the new assignment was introduced. This is not enough to prove the benefit of using the new assignment. However, the responses to questionnaires at course evaluations show that almost all students think that the assignment redly gave them better understanding of polynomial reductions in NP completeness proofs. The students' result on the new assignment corresponds closely to their results on the following individual assignment. Seemingly, the new assignment predicts accurately who is going to pass the following assignment.

Place, publisher, year, edition, pages
Keyword [en]
reductions, learning theoretical computer science, computer lab work
National Category
Computer Science
URN: urn:nbn:se:kth:diva-31020ISI: 000286906900021ScopusID: 2-s2.0-77955134619ISBN: 978-1-60558-820-9OAI: diva2:402257
15th Innovation and Technology in Computer Science Education Conference
QC 20110307Available from: 2011-03-07 Created: 2011-03-07 Last updated: 2014-09-29Bibliographically approved
In thesis
1. On difficult topics in theoretical computer science education
Open this publication in new window or tab >>On difficult topics in theoretical computer science education
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis primarily reports on an action research project that has been conducted on a course in theoretical computer science (TCS). The course is called Algorithms, data structures, and complexity (ADC) and is given at KTH Royal Institute of Technology in Stockholm, Sweden.

The ADC course is an introduction to TCS, but resembles and succeeds courses introducing programming, system development best practices, problem solving, proving, and logic. Requiring the completion of four programming projects, the course can easily be perceived as a programming course by the students. Most previous research in computer science education has been on programming and introductory courses.

The focus of the thesis work has been to understand what subject matter is particularly difficult to students. In three action research cycles, the course has been studied and improved to alleviate the discovered difficulties. We also discuss how the course design may color students’ perceptions of what TCS is. Most of the results are descriptive.

Additionally, automated assessment has been introduced in the ADC course as well as in introductory courses for non-CS majors. Automated assessment is appreciated by the students and is directing their attention to the importance of program correctness. A drawback is that the exercises in their current form are not likely to encourage students to take responsibility for program correctness.

The most difficult tasks of the course are related to proving correctness, solving complex dynamic programming problems, and to reductions. A certain confusion regarding the epistemology, tools and discourse of the ADC course and of TCS in general can be glimpsed in the way difficulties manifest themselves. Possible consequences of viewing the highly mathematical problems and tools of ADC in more practical, programming, perspective, are discussed. It is likely that teachers could explicitly address more of the nature and discourse of TCS in order to reduce confusion among the students, for instance regarding the use of such words and constructs as “problem”, “verify a solution”, and “proof sketch”.

One of the tools used to study difficulties was self-efficacy surveys. No correlation was found between the self-efficacy beliefs and the graded performance on the course. Further investigation of this is beyond the scope of this thesis, but may be done with tasks corresponding more closely and exclusively to each self-efficacy item.

Didactics is an additional way for a professional to understand his or her subject. Didactics is concerned with the teaching and learning of something, and hence sheds light on that “something” from an angle that sometimes is not reflected on by its professionals. Reflecting on didactical aspects of TCS can enrichen the understanding of the subject itself, which is one goal with this work.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2014. vi, 94 p.
TRITA-CSC-A, ISSN 1653-5723 ; 2014:15
National Category
urn:nbn:se:kth:diva-152357 (URN)978-91-7595-267-3 (ISBN)
Public defence
2014-10-17, F3, Lindstedtsvägen 26, KTH, Stockholm, 14:00 (English)

QC 20140929

Available from: 2014-09-29 Created: 2014-09-25 Last updated: 2014-09-29Bibliographically approved

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