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Exploring the Interaction of Abstraction and Engagement in Learning Programming Concepts

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Title: Exploring the Interaction of Abstraction and Engagement in Learning Programming Concepts
Author(s): Heinonen, Ava
Contributor: University of Helsinki, Faculty of Science, none
Discipline: none
Degree program: Master's Programme in Computer Science
Specialisation: Networking and Services
Language: English
Acceptance year: 2020
The design of instructional material affects learning from it. Abstraction, or limiting details and presenting difficult concepts by linking them with familiar objects, can limit the burden to the working memory and make learning easier. The presence of visualizations and the level to which students can interact with them and modify them also referred to as engagement, can promote information processing. This thesis presents the results of a study using a 2x3 experimental design with abstraction level (high abstraction, low abstraction) and engagement level (no viewing, viewing, presenting) as the factors. The study consisted of two experiments with different topics: hash tables and multidimensional arrays. We analyzed the effect of these factors on instructional efficiency and learning gain, accounting for prior knowledge, and prior cognitive load. We observed that high abstraction conditions limited study cognitive load for all participants, but were particularly beneficial for participants with some prior knowledge on the topic they studied. We also observed that higher engagement levels benefit participants with no prior knowledge on the topic they studied, but not necessarily participants with some prior knowledge. Low cognitive load in the pre-test phase makes studying easier regardless of the instructional material, as does knowledge on the topic being studied. Our results indicate that the abstractions and engagement with learning materials need to be designed with the students and their knowledge levels in mind. However, further research is needed to assess the components in different abstraction levels that affect learning outcomes and why and how cognitive load in the pre-test phase affects cognitive load throughout studying and testing.
Keyword(s): Computer science education Interactive learning environments E-learning

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