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

Current data sources used for the prediction of student outcomes average about 55% accuracy and require a significant amount of input data and time for researchers and educators to produce predictive models of student outcomes. The aim of this study is to examine how neurocognitive data collected via functional near infrared spectroscopy (fNIRS) may be used to create predictive models of student outcomes with greater speed and accuracy when using a synthetic adaptive learning environment (SALEs). Specifically, this study examines the utility of using neurocognitive data to develop student response prediction on a science content test. Participants were recruited from schools located in the United States ( n = 40). Participants in the study engaged in three conditions: no content, video and virtual reality. The lesson video and virtual reality lesson provides an explanation of deoxyribonucleic acid replication. Observed neurocognitive responses were collected during each condition and used to predict the success of student responses on an assessment. On average the predicative accuracy of this approach is 85% and occur within 300 ms. Predictive error rates are less than 15%. Results of this study provides evidence to support the use of neurocognitive data for adaption of digitally presented content and how machine learning approaches and artificial intelligence may be used to classify student data in real-time as students engage with content. Results also illustrate good accuracy and capture of moment-to- moment fluctuations of cognition in real-time. These findings may help the development of artificially intelligent tutors and improve student-based learning analytics. • Classification of neurocognitive data lends itself to prediction of student outcomes. • Describes neurocognitive data sources for development of predictive learning platforms. • Hemodynamic response can help to understand levels of student attention and engagement. 

Real-time prediction of science student learning outcomes using machine learning classification of hemodynamics during virtual reality and online learning sessions

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

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Psychosocial factors impacting STEM career selection