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Virtual labs provide space for students to iteratively test, observe, and revise their understanding so as to improve their scientific literacy. However, one of the challenges that students face is that they need to think and act like scientists so as to be sensitively alert to methodological flaws and various sources of error. This study thus compared the effect of two instructional approaches using a virtual lab to enhance students' scientific literacy. Before students were given the opportunity to conduct science inquiries with the virtual lab, they were required to critique problematic inquiry cases (the critique group) or watch teachers' demonstrations (the teacher demonstration group) before taking part in the inquiry. By analyzing data from 50 middle school students, this study found that the effect of applying virtual labs can be augmented by an instructional design that engages students in critiquing experiments prior to their inquiry with the virtual lab. This study also found a limitation of the use of virtual labs in helping students transfer what they have learned from the teacher's demonstration to new inquiry contexts. A close relation among scientific literacy post-test scores, critiquing performance, and inquiry performance in the inquiry activity was detected, suggesting that student critiquing prior to inquiry is in alignment with the goal of developing students' inquiry skills and scientific literacy with virtual labs.

Background: Collaborative computer simulations are available on some online platforms which support students at distributed locations to synchronously collaborate on the simulations to learn sciences. However, how students collaborate with each other in collaborative simulations is not clear. Objectives: The aim of this study was to investigate whether functional interdependency would influence learning. Methods: Two collaborative learning models with different functional interdependencies were examined (the synchronous model and the distributed accountability model). Multiple data sources obtained from 64 students were collected and analyzed. We discuss the collaborative learning with two levels of factors: the individual-level factors (i.e., individual perceptions of teamwork quality, visual attention and learning performance before and after a simulation activity) and the pair-level factors (i.e., discourse data and joint attention). Given that the pair-level factors in the collaborative learning environment may affect the individual-level factors, we further discuss the interactions of the two levels of factors in different collaborative learning models with hierarchical linear modeling (HLM) analysis. Results and Conclusions: The analytical results of the individual-level factors found participants in the distributed accountability model demonstrated more frequent and longer attention to the learning activity. Furthermore, the results indicated that the two simulation learning activities would enhance the participants' learning performance except in Q2. For the pair-level factors, the results demonstrated that the participants in the distributed accountability model showed more active discourse segments but similar joint attention patterns in the learning activity. The results of the HLM analysis indicated that the students in the distributed accountability model had to collaborate with their partners through more constructive dialogue, and focused on the same areas of interest to enhance their learning performance, as the complexity of the distributed accountability design was implemented in a simulation learning activity. Major takeaways: We found that the increase of functional interdependency cannot guarantee students' learning effect in collaborative learning and may hinder the communication that is needed during collaboration. Researcher may need to consider other collaboration tools to enhance the reciprocal reflection.

Background: Collaborative computer simulations are available on some online platforms which support students at distributed locations to synchronously collaborate on the simulations to learn sciences. However, how students collaborate with each other in collaborative simulations is not clear. Objectives: The aim of this study was to investigate whether functional interdependency would influence learning. Methods: Two collaborative learning models with different functional interdependencies were examined (the synchronous model and the distributed accountability model). Multiple data sources obtained from 64 students were collected and analyzed. We discuss the collaborative learning with two levels of factors: the individual‐level factors (i.e., individual perceptions of teamwork quality, visual attention and learning performance before and after a simulation activity) and the pair‐level factors (i.e., discourse data and joint attention). Given that the pair‐level factors in the collaborative learning environment may affect the individual‐level factors, we further discuss the interactions of the two levels of factors in different collaborative learning models with hierarchical linear modeling (HLM) analysis. Results and Conclusions: The analytical results of the individual‐level factors found participants in the distributed accountability model demonstrated more frequent and longer attention to the learning activity. Furthermore, the results indicated that the two simulation learning activities would enhance the participants' learning performance except in Q2. For the pair‐level factors, the results demonstrated that the participants in the distributed accountability model showed more active discourse segments but similar joint attention patterns in the learning activity. The results of the HLM analysis indicated that the students in the distributed accountability model had to collaborate with their partners through more constructive dialogue, and focused on the same areas of interest to enhance their learning performance, as the complexity of the distributed accountability design was implemented in a simulation learning activity. Major takeaways: We found that the increase of functional interdependency cannot guarantee students' learning effect in collaborative learning and may hinder the communication that is needed during collaboration. Researcher may need to consider other collaboration tools to enhance the reciprocal reflection. Lay Description: What is already known about this topic: Collaborative simulations are helpful in making the learning process cohesive.The learning effects of functional interdependence in collaborative learning are under debate. What this paper adds: We examined collaborative learning models with different functional interdependencies.We discuss the collaborative learning with the individual‐, the pair‐level factors and their interactions Implications for practice and/or policy: The importance of decreasing cognitive load induced by simulation with high functional interdependency.It is necessary to increase participants' transactive and constructive engagement in collaborative models. [ABSTRACT FROM AUTHOR]

Collaborative problem solving (CPS) is considered as one of the core competencies of the 21st century. Collaborative simulations which allow multiple students to participate in CPS activities in a shared simulation session are now increasingly applied to better facilitate these activities. However, the literature has shown that students' collaboration often does not lead to an effective solution to problems. Guided by the PISA CPS framework, this study thus aimed to analyze students’ collaboration patterns and problem solving strategies in solving a physics problem, and to identify significant patterns which may lead to a successful or unsuccessful outcome. Multiple data sources including group discussions, problem solving activities in a collaborative simulation, and open-ended questionnaire feedback from 30 high school students were analyzed using the lag sequential analysis technique. It was found that collaborative simulation has the potential to help students situate their discussion in a joint concrete problem space, facilitating their formation of a path to solve the problem. More importantly, the results showed significant differences between the successful and unsuccessful groups in terms of their collaboration patterns and problem solving strategies. A considerable portion of the students could only apply an intuitive trial-and-error strategy, and failed to solve the problem in the end. These students showed an inability to monitor and analyze the problem solving process, and were unable to transform their discussion into an executable plan to solve the problem. Those students who applied analytical reasoning strategies were more likely to achieve a successful problem solving outcome. The implications for educational practice are discussed, and the directions for future studies addressed. [ABSTRACT FROM AUTHOR]