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Instructors in STEM classrooms often frame students' interactions with technologies to help them learn content. For instance, in many STEM domains, instructors commonly help students translate physical 3D models into 2D drawings by prompting them to focus on (a) orienting physical 3D models and (b) generating 2D drawings. We investigate whether framing prompts that target either of these practices enhance the effectiveness of an educational technology that supports collaborative translation among multiple representations. To this end, we conducted a quasi-experiment with 565 undergraduate chemistry students. All students collaboratively built physical 3D models of molecules and translated them into 2D drawings. In a business-as-usual control condition, students drew on paper, without support from an educational technology. In two experimental conditions, students drew in an educational technology that provided feedback and prompted collaboration. One condition received framing prompts to focus on physical models (model condition); another received prompts to generate intermediary drawings on paper (draw condition). Compared to the control condition, the model condition showed higher learning gains, but the draw condition showed lower learning gains. Analyses of log data showed that students made more model-based errors, and the prompts in the model condition reduced these model-based errors. However, interviews with instructors showed that they prefer drawing-focused prompts, in contrast to our results. These findings offer theoretical insights into how students learn to translate among representations. Furthermore, they yield practical recommendations for the use of educational technologies that support learning with multiple representations. 

Students often struggle to translate between physical and virtual models when learning concepts in STEM courses. Collaborative activities may help students overcome these difficulties, especially if collaboration scripts prompt students to discuss shared representations. Which representation should collaboration scripts focus students’ interactions on? We investigate this question in a quasi-experiment with 560 undergraduate chemistry students. All students collaboratively built physical ball-and-stick models of molecules and translated them into wedge-dash drawings. Two experimental conditions received a collaboration script. For the model condition, the script prompted students to focus on the physical ball-and-stick models. For the draw condition, the script prompted students to generate intermediary drawings on paper. Compared to a control condition with unscripted collaboration, the model condition showed higher learning gains and the draw condition showed lower learning gains—especially for students with low spatial skills. Our results yield theoretical and practical implications for collaborative practices with multiple representations