Computer-aided simulation-based platforms have been shown to be effective tools for teaching STEM concepts. At the same time, Computer Supported Collaborative Learning (CSCL) platforms encourage different viewpoints and approaches from the learners which can enrich the learning experience in STEM classrooms. The deployment in recent years of networked personal devices such as Chromebooks in classrooms has motivated educators to design collaborative learning tools for these devices. However, prior work has shown that using one-on-one devices may discourage students from talking among each other, which hinders collaboration. To understand the affordances of personal devices for CSCL tools within Biology curricula, we designed a collaborative plant growth simulation application that provides mirrored plant growth simulation views for every group member to facilitate a common visualization. In this paper, we present our findings from an in-the-wild study that evaluated the affordance and usability of the plant growth simulation application and investigated the nature of collaboration and engagement aided through the simulation mirroring feature. Our study results showed that the plant simulation application had high usability and acceptance. Moreover, mirroring the plant growth simulation improved collaboration, generated excitement, and stimulated conversation. We also identified episodes where collaboration was hindered due to off-task activities, troubleshooting, group dynamics, and lack of understanding that led us to outline some potential guidelines to improve the collaborative learning experience for the students in Biology classroom.

Simulations are widely used to teach science in grade schools.These simulations are often augmented with a conversational artificial intelligence (AI) agent to provide real-time scaffolding support for students conducting experiments using the simulations.AI agents are highly tailored for each simulation, with a predesigned set of Instructional Goals (IGs), making it difficult for teachers to adjust IGs as the agent may no longer align with the revised IGs.Additionally, teachers are hesitant to adopt new third-party simulations for the same reasons.In this research, we introduce SimPal, a Large Language Model (LLM) based meta-conversational agent, to solve this misalignment issue between a pre-trained conversational AI agent and the constantly evolving pedagogy of instructors.Through natural conversation with SimPal, teachers first explain their desired IGs, based on which SimPal identifies a set of relevant physical variables and their relationships to create symbolic representations of the desired IGs.The symbolic representations can then be leveraged to design prompts for the original AI agent to yield better alignment with the desired IGs.We empirically evaluated SimPal using two LLMs, ChatGPT-3.5 and PaLM 2, on 63 Physics simulations from PhET and Golabz.Additionally, we examined the impact of different prompting techniques on LLM's performance by utilizing the TELeR taxonomy to identify relevant physical variables for the IGs.Our findings showed that SimPal can do this task with a high degree of accuracy when provided with a well-defined prompt.

Creating effective middle school STEM curricula requires a combination of individual and collaborative learning. Prior studies showed that finding a proper balance and providing uninterrupted knowledge transmission between different learning modes can be challenging in such mixed pedagogical approaches. In this paper, we present a multi-device interactive educational platform named SimSnap to teach biology curriculum to middle school children. SimSnap facilitates interactions among touchscreen Chromebooks to perform in-class individual and group activities. We present a usability analysis study with eight middle school children where they learn about the influence of temperature on tomato plant growth. Our study demonstrated that SimSnap facilitates group discussions to complete collaborative tasks. It also creates seamless knowledge propagation between prior to current tasks to learn about more complex concepts from previous simpler activities. Middle school children gave overall high usability ratings and positive feedback on SimSnap. This study also helped to outline some design recommendations for future improvements of SimSnap.

This article discusses the design of Concept Mapped Project-Based Activity Scaffolding System (CoMPASS) and the theoretical foundations that it is based on. CoMPASS is a hypertext system that presents students with external, graphical representations in the form of concept maps as well as textual representations both of which change dynamically as students traverse through the domain and make navigational decisions. In a study in which middle school students used CoMPASS, students' navigation paths, as well as their learning outcomes, were analyzed. A comparison class in which students used the system without the maps for navigation provided information about students' use of the maps for navigation and its effect on their learning. It was found that students who used the maps version of the system performed significantly better in a concept mapping test as well as an essay test, and their navigation was more focused. This article discusses the findings of the study and its implications for designing hypertext systems.