The Role of Teaching-Learning Style Fit and Content Complexity in Information Systems Courses
Hayward Andres North Carolina A&T State University
Abstract It is common knowledge that engineering, computer science, and information systems course content have been often described as difficult to learn by most students. Content complexity associated with information is a function of the number of causal links in a chain of actions, physical states, or mental states. Causal links between units of information are typically defined through the use of temporal (e.g., before, and then, after), causal (e.g., which caused, which enabled, because, if-then), or intentional (e.g., in order that, so that, to allow) connectives. As the number of causal links needed to convey an idea or concept increases (i.e., causal chain length), working memory becomes overloaded because it is limited in the number of related ideas that can be simultaneously stored and processed. According to cognitive load theory, all cognitive processing and learning occurs through a very limited working memory and an unlimited long-term memory to structure a set of hierarchically ordered schemas. Cognitive load theory suggests that “how” information is presented (i.e. teaching style) to students will impact working-memory load and thus be a critical factor in determining learning success. If the cognitive load exceeds the limits of working memory, then learning will be hindered.
Learning styles theories define learning as a cognitive process that entails the use of encoding, processing, and synthesis of information during a learning or problem solving task. The varied current learning style theories/models view the learning process and outcomes to be based on 1) learner motivations, 2) perception and processing of information, 3) sensory preferences, and 4) active demonstration with experiential immersion. A synthesis of these varied perspectives reveal that any attempt to provide instructional delivery that would fit learning style preferences should account for appropriate information modality (e.g., verbal vs. visual), locus of control (e.g., teacher-centered vs. student-centered), self-efficacy effects, and student engagement. Any “mis-fit” between teaching style and both course content complexity and student learning style preferences can potentially lead to diminished student self-regulated learning and subsequently minimal learning success (e.g., course satisfaction, passing grades). In contrast, an appropriate teaching style (e.g., traditional lecture versus active learning) should help to promote self-regulated learning – information encoding and recall, self-assessment of learning, and motivation.
Information complexity, cognitive load, and teaching-learning style fit are argued to be critical aspects of a learning situation and all collectively impact learning outcomes. More specifically, teaching style should account for cognitive load associated with content complexity and learning style preferences in order to maximize learning outcomes. Cognitive load and learning style theories are used as the theoretical framework to derive a structural equation model that is used to test the causal relationships among these factors.
Recommended Citation: Andres, H., (2015). The Role of Teaching-Learning Style Fit and Content Complexity in Information Systems Courses. Proceedings of the EDSIG Conference, (2015) n.3602, Wilmington, NC