Designing, evaluating, and reacting to a secondary science methods class

1994 ◽  
Vol 5 (1) ◽  
pp. 15-22
Author(s):  
William J. Boone ◽  
Hans O. Andersen
1999 ◽  
Vol 83 (3) ◽  
pp. 275-307 ◽  
Author(s):  
Robin Marion ◽  
Peter W. Hewson ◽  
B. Robert Tabachnick ◽  
Kathryn B. Blomker

2019 ◽  
Vol 9 (1) ◽  
pp. 29 ◽  
Author(s):  
Trina Kilty ◽  
Andrea Burrows

The purpose of this study was to describe how US secondary science preservice teachers, or those preparing to teach middle and high school science, at one university, perceive engineering and teaching engineering within an epistemological framework of required domain components pre- and post-instruction (intervention) as well as over three cohort years. Their perceptions reveal relevant prior beliefs helpful for designing instruction to address an external need to prepare secondary science teachers to teach disciplinary content ideas, cross-cutting concepts, and science and engineering practices to meet the Next Generation Science Standards. Questionnaires administered pre- and post-instruction (intervention), as well as over three years, asked participants to decide whether various scenarios qualified as engineering and then to provide reasoning. Intervention instruction included whole-class discussions of engineering design practices. The responses to the questionnaire were analyzed for thematic content. The results indicate that the secondary science preservice teachers (n = 43) have a novice understanding of engineering and teaching engineering. They gain an emerging understanding during the secondary science methods courses, consistent in all three years with expanding perspectives from narrow discipline views. As their perceptions are refined, however, there are risks of oversimplification, which may lead to forming misconceptions. The recommendations for designing instruction such as secondary science methods courses and early career professional development include creating opportunities for preservice and early career teachers to explore and challenge their perceptions of engineering design practices integrated within science and engineering practices.


2020 ◽  
Author(s):  
Saeed Nosratabadi ◽  
Amir Mosavi ◽  
Puhong Duan ◽  
Pedram Ghamisi ◽  
Ferdinand Filip ◽  
...  

This paper provides a state-of-the-art investigation of advances in data science in emerging economic applications. The analysis was performed on novel data science methods in four individual classes of deep learning models, hybrid deep learning models, hybrid machine learning, and ensemble models. Application domains include a wide and diverse range of economics research from the stock market, marketing, and e-commerce to corporate banking and cryptocurrency. Prisma method, a systematic literature review methodology, was used to ensure the quality of the survey. The findings reveal that the trends follow the advancement of hybrid models, which, based on the accuracy metric, outperform other learning algorithms. It is further expected that the trends will converge toward the advancements of sophisticated hybrid deep learning models.


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