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Title of the thesis: Students' topic-specific difficulties in learning data structures and algorithms

Thesis defender: Artturi Tilanterä 
Opponent: Professor Jan Vahrenhold, University of Münster, Germany
Custos: Professor Lauri Malmi, Aalto University School of Science

Undergraduate computer science studies begin with a course named Introductory Programming, which means how to instruct a computer to do something new. This subject is followed by a course named Data Structures and Algorithms (DSA), which teaches how to write the aforementioned instructions so that they use sparingly the processing time and memory of the computer. An algorithm is a stepwise procedure to solve a particular computing problem. A data structure is a collection of pieces of information which have been linked together to facilitate computation. Basic knowledge of DSA helps professionals build fast computer and mobile applications and cost-effective digital services.

This dissertation investigates how students’ lacking knowledge of introductory programming affect in their difficulty to learn DSA. In addition, the dissertation has surveyed misconceptions related to DSA. A misconception is a student’s belief which differs from the scientific consensus, for example, ”a program with less instructions is more efficient”. Certain researchers view misconceptions as an obstacle for learning, because a students cannot recognize them. Therefore, a teacher who knows misconceptions can help their students efficiently forward.

A literature review in the dissertation compiled DSA misconceptions into a catalogue which helps teachers integrate this knowledge in their teaching. In addition, the catalogue helps teachers develop examples and exercises which rectify students’ misconceptions.

A test designed to reveal students lacking knowledge in Introductory Programming and DSA gave promising empirical results. The test can distinguish these two topics, but is not suitable for diagnosing students’ difficulties in subtopics. The skill of program comprehension, meaning a person’s ability to read the source code of a computer program and execute it mentally, should be taught even after the first Introductory Programming course.

The DSA teaching at Aalto University has utilized visual algorithm simulation exercises since 2000s. In such an exercise, a student produces the execution steps of an algorithm by clicking a data structure visualization, such as table, tree, or network. The dissertation produced new evidence that students confuse similar algorithms that have different purposes. The methods introduced in the dissertation will help building exercises which provide automated feedback which supports learning.

Keywords: programming, data structure, algorithm, learning difficulty, misconception, algorithm visualization

Contact information: 
Artturi Tilanterä
artturi.tilantera@aalto.fi 
 

Thesis available for public display 7 days prior to the defence at .