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
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How instructors frame students' interactions with educational technologies can enhance or reduce learning with multiple representations
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.
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- Award ID(s):
- 1651781
- NSF-PAR ID:
- 10097818
- Date Published:
- Journal Name:
- Computers & education
- Volume:
- 128
- ISSN:
- 1873-782X
- Page Range / eLocation ID:
- 199-213
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Background Recent engineering education research has found improved learning outcomes when instructors engage students actively (e.g., through practice problems) rather than passively (e.g., in lectures). As more instructors shift toward active learning, research needs to identify how different types of activities affect students' cognitive engagement with concepts in the classroom. In this study, we investigate the effects of prompting novice students to draw when solving problems, a professional practice of engineers.
Purpose We investigate whether implementing instructional prompts to draw in an active learning classroom (a) increases students' use and value of drawing as a problem‐solving strategy and (b) enhances students' problem‐solving performance.
Method We compared survey data and exam scores collected in one undergraduate class that received prompts to draw in video lectures and in‐class problems (drawing condition) and one class that received no drawing prompts (control condition).
Results After drawing prompts were implemented, students' use and value of drawing increased, and these effects persisted to the end of the semester. Students were more likely to draw when provided drawing prompts. Furthermore, students who received prompts outperformed students who did not on exam questions that target conceptual understanding.
Conclusions Our findings reveal how implementing drawing prompts in an active learning classroom may help students engage in drawing and solve problems conceptually. This study contributes to our understanding of what types of active learning activities can improve instructional practices in engineering education. Particularly, we show how prompts that foster authentic engineering practices can increase cognitive engagement in introductory‐level engineering courses.
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Abstract As future decision-makers, students must develop interdisciplinary, systems thinking skills to make effective management decisions; however, systems thinking remains challenging for many students. Here, we use the Food-Energy-Water (FEW) Nexus as a framework to examine how drawings can help students cultivate systems thinking skills. Drawings can be tools to make implicit mental models of systems connections explicit for instructors to better comprehend student learning. Our goal was to understand how drawing can help students make connections across systems compared to using only verbal explanations. In 2021, we interviewed undergraduates, asking them to draw and verbally explain the FEW Nexus. Analysis revealed that student drawings showed an increase in the number of connections that half of students could describe when compared to verbal-only explanations. Instructors may benefit from this study by recognizing areas where students might struggle to understand FEW Nexus connections, where additional course emphasis is needed, and how drawings can help assess student learning.
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Abstract Ensuring undergraduate students become proficient in relating protein structure to biological function has important implications. With current two‐dimensional (2D) methods of teaching, students frequently develop misconceptions, including that proteins contain a lot of empty space, that bond angles for different amino acids can rotate equally, and that product inhibition is equivalent to allostery. To help students translate 2D images to 3D molecules and assign biochemical meaning to physical structures, we designed three 3D learning modules consisting of interactive activities with 3D printed models for amino acids, proteins, and allosteric regulation with coordinating pre‐ and post‐assessments. Module implementation resulted in normalized learning gains on module‐based assessments of 30% compared to 17% in a no‐module course and normalized learning gains on a comprehensive assessment of 19% compared to 3% in a no‐module course. This suggests that interacting with these modules helps students develop an improved ability to visualize and retain molecular structure and function.
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Offsite construction (e.g., wood modular houses) has many advantages over traditional stick-built construction, ranging from schedule/cost reduction to improvement in safety and quality of the built product. Unlike stick-built, offsite construction demands higher levels of design and planning coordination at the early stages of the construction project to avoid cost overruns and/or delays. However, most companies still rely on 2D drawings in the development of shop drawings, which are required for the fabrication of the building components such as walls and roofs. In practice, the process of developing shop drawings is usually based on manually interpreting the 2D drawings and specifications, which is time-consuming, costly, and prone to human errors. A 3D information model can improve the accuracy of this process. To help achieve this, the authors developed a semi-automated method that can process 2D orthographic views of building components and convert them to 3D models, which can be useful for fabrication. The developed 3D information model can be further transformed to building information models (BIMs) to support collaboration amongst users and data exchanges across platforms. The developed method was evaluated in the development of wall components of a student apartment project in Kalamazoo, MI. Experimental results showed that the developed method successfully generated the 3D information model of the wall components. A time comparison with the state-of-the-art practices in developing the wall components was performed. Results showed that the developed method utilized approximately 22% of the time it took the state-of-the-art manual method to generate the 3D models.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/https://doi.org/10.1016/j.compedu.2018.09.012
