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Background: Despite its obvious relevance to computer science, computational thinking (CT) is transdisciplinary with the potential of impacting one's analytical ability. Although countless efforts have been invested across K‐12 education, there is a paucity of research at the postsecondary level about the extent to which CT can contribute to sustainable learning outcomes. Objectives: The current study examines how a series of Arduino‐based robotics learning activities capture the fuller essence of concepts related to CT. Methods: College students (n = 50) completed a series of six robotics learning activities. Think‐alouds, student reflections and performance scores were used to assess students' CT through a robotics challenge in virtual and physical learning environments. Results and Conclusions: Students verbalized CT concepts related to algorithmic thinking much more than abstraction, problem decomposition and testing and debugging. Students exposed to active learning performed better in a virtual robotics challenge compared to their peers in a traditional‐oriented classroom. Students' scores on the physical robotics challenge increased as a function of the number of references they made to CT concepts during the think‐alouds. It is possible to design pedagogical experiences that tap into various dimensions of CT at incremental levels of complexity through a series of Arduino‐based robotics activities. With the integration of an online simulation, students can visualize and transfer their CT skills between a virtual and physical learning environment, thus leading to more sustainable learning outcomes. Lay Description: What is already known about this topic: Computational thinking (CT) is the conceptual foundation for problem‐solving.CT shifted from unplugged to plugged activities.CT concepts can be fostered through educational robotics. What this paper adds: A multi‐dimensional approach to assessing CT.Applications of CT provide insights into skill transfer.An integrative theoretical approach to study the 'how' and the 'what' of CT. Implications for practice: Educational robotics activities can cater to a fuller range of CT skills.Virtual simulations with constructive feedback are beneficial for students in traditional settings.Mixed learning environments contribute to making links between lectures and labs. [ABSTRACT FROM AUTHOR]

Industrial systems can be complex and not intuitive to perceive. Therefore, students in technology and engineering programs can benefit from developing mental models of industrial systems during their journey in college. However, more often than not, these students do not have access to industrial facilities; thus, developing mental models for systems is a challenge. This paper examines the merit of an Immersive Virtual Reality (IVR) framework application in creating proper mental models for industrial systems in technology and engineering students. Two IVR applications were developed. One IVR application afforded interaction with components of a prefabricated industrial cooling water system (CWVR). In the other application, students designed and built industrial systems with IVR (system designer VR [SDVR]). SDVR facilitated constructive‐generative engagement. A group of 33 students was divided into two; one group (the Design, experimental group) was tasked with building a system with SDVR and interacting with the cooling water system in CWVR. The other group was tasked with directly interacting with the CWVR without building a system with SDVR (the Interaction, comparison group). Students' mental models of the cooling water system in CWVR were evaluated following completing the interaction experience with CWVR. The results demonstrate that the causal model notion of the mental model of the cooling water system was significantly higher in the Design, experimental group. The results suggest that designing a rich IVR application that facilitates constructive‐generative engagements may carry merit in informing student mental models of complex technical concepts. Lay Description: Industrial systems can be complex and not intuitive to perceive.Students in technology‐related programs may struggle to develop mental models for systems.Immersive virtual reality applications for industrial systems were developed and tested.Results indicate that virtual reality might inform mental models of systems in students. [ABSTRACT FROM AUTHOR]

Background: Previous work has identified that the benefits of learning with videogames and learning from simulations. However, recent meta‐analytic work has also identified that little research directly compares learning with videogames and learning with simulations. Objectives: This study examines two learning technologies and their corresponding pedagogical approaches and compares them for learning the Science, Technology, Engineering and Mathematics topic of electric charges. Methods: Participants were randomly assigned to either an intervention using a computer simulation for inquiry‐based learning or a computer videogame for game‐based learning. Their learning gains, self‐reported emotional state and experienced cognitive load were recorded. Results: We found that both learning environments improved conceptual learning, and there were no statistically significant differences between the two conditions. Participants did perceive the game‐based environment to be more engaging as well as more frustrating. We also found that cognitive load did not predict learning—however, different types of cognitive load correlated with different emotions. Overall, participants in both conditions were engaged and perceived understanding of the topic, yet they also experienced both confusion and task‐unrelated thoughts. Takeaways: When learning with simulations and videogames, educators need to align intended learning outcomes with pedagogical approaches enabled by technology. In addition, a balance between principles of multimedia learning to reduce or prevent extraneous processing, and scaffolding to reduce negative effects of learning with technology, need to be considered. Lay Description: What is already known about this topic: Research on the use of computer simulations for learning has identified positive learning effects regarding achievement outcomes, inquiry skills and noncognitive outcomes.Research on the use of videogames for learning has suggested learning benefits, such as improved working memory, development of creativity skills and achievement outcomes.Recent meta‐analytic work has identified that there is little research that directly compares learning with videogames and learning with simulations. What this paper adds: Learning benefits of difficult Science, Technology, Engineering and Mathematics (STEM) concepts may be different for game‐based learning (GBL) than inquiry‐based learning (IBL).Positive emotions can be experienced when learning via GBL than when learning via IBL.Students, who experience more positive emotions may also achieve higher learning gains.Students' cognitive load may be different when learning with GBL than when learning via IBL.Students experiencing high cognitive load (i.e., intrinsic and extraneous) may show lower learning gains.Students experiencing high cognitive load (i.e., intrinsic and extraneous) may show higher level of mind‐wandering, frustration, or confusion. Implications for practice and/or policy: Learning with simulated inquiry base environment and game base environment improved conceptual learning.GBL was more engaging and more frustrating for students, when learning with computer videogames.Cognitive load did not predict STEM learning with technologies.Different cognitive load correlated with different learning emotions. [ABSTRACT FROM AUTHOR]