Pixel International Conferences

The use of imagery and iconic representation of scientific concepts is a key component in improving Critical Thinking (CT) skills while maintaining optimal Cognitive Load (CL) within higher education STEM learners.  Laboratory experiences are a vital component within science education, while rote traditional lab experiments are currently not addressing inquiry nor linking with educational technologies [8].  Instructional approaches based on active discovery and problem-based learning using digital games is becoming more commonplace in today’s educational forum.  Opportunities to alternatively assess learning and evaluate comprehension in a digital learning environment are supportive from both a theoretical perspective [7] and an empirical research perspective [6].  Using educational games for assessment not only measures previously outlines learning objectives and goals, but allows learners to measure their cognitive load abilities in these scenarios.

Existing research regarding science learning using visualizations for information design processes such as underscoring vital information through cueing [1] and color coding [5], have focused on presenting a dynamic association between the integration of multiple representations with one another.  Current research on the interaction design features of dynamic visualizations focuses on learner control and manipulation of content for best practices in the facilitation of learning [2] [3].  Iconographic representations aid learners in comprehension as a form of intervention in learners who have a lower level of prior knowledge, while this method of assistance in higher levels of prior knowledge learners would impede further learning.  Interaction design features must account for expertise reversal effect in the cognitive load schema targeting long-term memory [3] [4].  By mitigating for this effect while constructing intervention processes, researcher and educators can reduce the impact on working memory through the use of carefully integrating iconic representations into learning of complex problem-solving techniques.

The research performed was a causal-comparative quantitative study with 150 learners enrolled at a two-year community college, to determine the effects of virtual laboratory experiments on CT skills and CL.  Data collection involved a quantitative analysis of pre/post-laboratory experiment surveys that included a comparison using the Revised Two-Factor Study Process survey, Motivated Strategies for Learning Questionnaire, and the Scientific Attitude Inventory survey, using a Repeated Measures ANOVA test for treatment or non-treatment [9].  By studying the manner in which learners comprehend information and reducing their cognitive load while conducting scientific experiments in Virtual Learning Environments (VLEs), we are provided with the information required to structure pedagogical changes and appropriate technology resources in applicable teaching modalities [10].