A meta-analysis with examination of moderators of student cognition, affect, and learning outcomes while using serious educational games, serious games, and simulations

There has been an increased focus on the use of cognitive strategies in the science classroom, in part this increased focus is due to the implementation of the Next Generation Science Standards (NGSS). This focus has created the need to examine claims regarding the cognitive basis for disciplinary approaches such as video lecture, virtual reality (VR), Serious Educational Games (SEGs), and hands on activities. The purpose of this study was to investigate differences in the level of hemodynamic response as it relates to four different approaches to teaching topics in the life sciences. The first approach used a video based lecture approach. The other approaches used an immersive Serious Educational Game and a virtual reality environment in which students were exposed to an experience involving the process of deoxyribonucleic acid (DNA) replication. The final condition was that of a hands-on activity. Researchers used functional near-infrared spectroscopy to examine hemodynamic localization and intensity as it related to each condition. In addition to examination of cognitive dynamics, content learning gains were also examined. Results provide evidence that there is parity between the hands on condition, Serious Educational Games, and the virtual reality conditions in learning outcomes and cognitive processing.

Comparison of virtual reality and hands on activities in science education via functional near infrared spectroscopy

Cognitive Psychology. 2nd ed.

Teacher-directed and inquiry-based science instructional practices have been shown to influence students’ performance on science assessments. However, only a small body of research has examined the...

https://www.tandfonline.com/doi/pdf/10.1080/1046560X.2020.1753309

Teacher-Directed Versus Inquiry-Based Science Instruction: Investigating Links to Adolescent Students' Science Dispositions Across 66 Countries

This study is intended to provide an example of computational modeling (CM) experiment using machine learning algorithms. Specific outcomes modeled in this study are the predicted influences associated with the Science Writing Heuristic (SWH) and associated with the completion of question items for the Cornell Critical Thinking Test. The Student Task and Cognition Model in this study uses cognitive data from a large-scale randomized control study. Results of the computational model experiment provide for the possibility to increase student success via targeted cognitive retraining of specific cognitive attributes via the SWH. This study also illustrates that computational modeling using machine learning algorithms (MLA) is a significant resource for testing educational interventions, informs specific hypotheses, and assists in the design and development of future research designs in science education research.

Computational Modeling of the Effects of the Science Writing Heuristic on Student Critical Thinking in Science Using Machine Learning

Attention on P-20 science, technology, engineering, and mathematics (STEM) education has increased tremendously in recent years. Many efforts are underway to promote STEM major and career selection...

Psychosocial factors impacting STEM career selection

Video games with violent content have raised considerable concern in popular media and within academia. Recently, there has been considerable attention regarding the claim of the relationship between aggression and video game play. The authors of this study propose the use of a new class of tools developed via computational models to allow examination of the question of whether there is a relationship between violent video games and aggression. The purpose of this study is to computationally model and compare the General Aggression Model with the Diathesis Mode of Aggression related to the play of violent content in video games. A secondary purpose is to provide a method of measuring and examining individual aggression arising from video game play. Total participants examined for this study are N = 1065. This study occurs in three phases. Phase 1 is the development and quantification of the profile combination of traits via latent class profile analysis. Phase 2 is the training of the artificial n...

Examining human behavior in video games: The development of a computational model to measure aggression

The purpose of this study is to explore the impact of persistence within STEM learning environments as a function of cumulative stress and latent trauma. The biopsychosocial impact of prolonged stressors due to hostile environments and academic demands has deleterious health effects on historically underrepresented students who enter STEM disciplines. The Trauma Symptoms Checklist for Children, clinical histories, and psychophysiomeasurement tools were used to measure the effects of cumulative stress and latent trauma as historically underrepresented students persisted through high school STEM discipline classes. Elevated responses on the inventory and history were triangulated through measures of biological markers for cumulative stress and developed into a profile combination of traits to identify those students likely to show symptomology consistent with the negative effects of cumulative stress and latent trauma. Examination of these outcomes using a latent class profile analysis model suggested the presence of cumulative stress resulting from program participation was significant.

Psychological Allostatic Load: the Cost of Persistence in STEM Disciplines

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Psychosocial factors impacting STEM career selection

Examining human behavior in video games: The development of a computational model to measure aggression

Psychological Allostatic Load: the Cost of Persistence in STEM Disciplines