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  1. Free, publicly-accessible full text available April 3, 2023
  2. To sensitively detect multiple and cross-species disease-related targets from a single biological sample in a quick and reliable manner is of high importance in accurately diagnosing and monitoring diseases. Herein, a surface-enhanced Raman scattering (SERS) sensor based on a functionalized multiple-armed tetrahedral DNA nanostructure (FMTDN) immobilized silver nanorod (AgNR) array substrate and Au nanoparticle (AuNP) SERS tags is constructed to achieve both multiplex detection and enhanced sensitivity using a sandwich strategy. The sensor can achieve single, dual, and triple biomarker detections of three lung cancer-related nucleic acid and protein biomarkers, i.e. , miRNA-21, miRNA-486 and carcinoembryonic antigen (CEA) in human serum. The enhanced SERS signals in multiplex detections are due to the DNA self-assembled AuNP clusters on the silver nanorod array during the assay, and the experimentally obtained relative enhancement factor ratios, 150 for AuNP dimers and 840 for AuNP trimers, qualitatively agree with the numerically calculated local electric field enhancements. The proposed FMTDN-functionalized AgNR SERS sensor is capable of multiplex and cross-species detection of nucleic acid and protein biomarkers with improved sensitivity, which has great potential for the screening and clinical diagnosis of cancer in the early stage.
    Free, publicly-accessible full text available March 24, 2023
  3. Research focusing on the integration of computational thinking (CT) into science, technology, engineering, and mathematics (STEM) education started to emerge. We conducted a semi-systematic literature review on 55 empirical studies on this topic. Our findings include: (a) the majority of the studies adopted domain-general definitions of CT and a few proposed domain-specific CT definitions in STEM education; (b) the most popular instructional model was problem-based instruction, and the most popular topic contexts included game design, robotics, and computational modelling; (c) while the assessments of student learning in integrated CT and STEM education targeted different objectives with different formats, about a third of them assessed integrated CT and STEM; (d) about a quarter of the studies reported differential learning processes and outcomes between groups, but very few of them investigated how pedagogical design could improve equity. Based on the findings, suggestions for future research and practice in this field are discussed in terms of operationalizing and assessing CT in STEM contexts, instructional strategies for integrating CT in STEM, and research for broadening participation in integrated CT and STEM education.
  4. Integrating engineering design into K-12 curricula is increasingly important as engineering has been incorporated into many STEM education standards. However, the ill-structured and open-ended nature of engineering design makes it difficult for an instructor to keep track of the design processes of all students simultaneously and provide personalized feedback on a timely basis. This study proposes a Bayesian network model to dynamically and automatically assess students’ engagement with engineering design tasks and to support formative feedback. Specifically, we applied a Bayesian network to 111 ninth-grade students’ process data logged by a computer-aided design software program that students used to solve an engineering design challenge. Evidence was extracted from the log files and fed into the Bayesian network to perform inferential reasoning and provide a barometer of their performance in the form of posterior probabilities. Results showed that the Bayesian network model was competent at predicting a student’s task performance. It performed well in both identifying students of a particular group (recall) and ensuring identified students were correctly labeled (precision). This study also suggests that Bayesian networks can be used to pinpoint a student’s strengths and weaknesses for applying relevant science knowledge to engineering design tasks. Future work of implementing thismore »tool within the computer-aided design software will provide instructors a powerful tool to facilitate engineering design through automatically generating personalized feedback to students in real time.« less