Eye-Movement Correlates of Cognitive Load of Experts and Novices in Programming

Cognitive Load Theory (CLT) was developed by John Sweller. It is a leading research approach in education (Sweller, 2011). It is based on the idea that people can accumulate vast amounts of knowledge in long-term memory. However, their working memory has a limited capacity to analyze new information. Ensuring that working memory is not overloaded and that cognitive load is maintained at optimal levels is critical to the effectiveness of learning and processing new data. Creating and actively using cognitive schemas helps reduce the load on working memory. This improves the ability of professionals to adapt to new information. Some researchers have argued (Kirschner, Ayers, and Chandler, 2011) that a key challenge in this area of research is the development of tools to measure cognitive load. Traditional studies have used subjective indicators such as self-report measures and rating scales. They have also used proxies such as errors and time spent studying. This is because physiological measures, which require specialized equipment, can have an impact on the naturalness of the research setting and are often not appropriate for standard classroom settings. In the context of studying the difference in experience between novice and expert programmers, the recording of oculomotor activity has been actively used. This allows us to analyze in more detail how the ways of processing visual information differ depending on the level of experience and expertise (Sharafi et al., 2015). The study of differences in visual effort, as in Chen's (2011) research, is in support of this. The main purpose of this study is the analysis of the relationship and identification of patterns between visual effort and subjective cognitive load in experts and novices during a software code error detection task. The study results confirmed the main hypothesis of a positive relationship between visual effort, including mean fixation duration and mean duration on relevant stimuli, and subjective cognitive load. This is in line with the results of the studies that investigated the visual effort of programmers as well as the meta-analysis (Obaidellah et al., 2018). However, the assumption that experienced programmers show shorter fixations on areas of interest compared to novices was not supported by the results of the study. This finding was inconsistent with the expectation that experienced subjects, due to their familiarity with the material, would be able to process the information more quickly and, therefore, would spend less time on individual items. The lack of support for this hypothesis suggests a more complex picture of the relationship between experience and cognitive processes. This may indicate the possibility of other factors influencing fixation duration within a given task. The results of this study may increase the value of physiological data as a possible tool for the measurement of cognitive load within the Sweller approach. Likewise, this study highlights the importance of research into the relationship and interrelationship between working memory capacity and visual effort.