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astro300_f16:day8 [2016/10/03 04:55] – [Homework] bethmcbrideastro300_f16:day8 [2016/10/03 05:13] – [Homework] bethmcbride
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   - Section video-taping is happening this week. We will send you a link to your section video by the end of the week. Watch it, and complete the {{:video.pdf|Section Video Recap Worksheet}} (due 10/12, next week!).   - Section video-taping is happening this week. We will send you a link to your section video by the end of the week. Watch it, and complete the {{:video.pdf|Section Video Recap Worksheet}} (due 10/12, next week!).
   - Bring your lesson plan notebooks to 375 next week.    - Bring your lesson plan notebooks to 375 next week. 
-  - Read papers: +  - Look through the abstracts from some of the following conference proceedings. Choose one paper to read and answer the questions at the bottom of this page. 
-  * Learning @ Scale: mainly focused on MOOC learning, but does have research on using student data, http://dl.acm.org/citation.cfm?id=2876034 +  * Learning @ Scale: mainly focused on learning from MOOCs (massively open online courses), but also includes research onusing student data to understand aspects of learning, http://dl.acm.org/citation.cfm?id=2876034 
-  * ICLS: International Conference of the Learning Sciences, best research in the field, includes some research in higher education, https://www.isls.org/icls/2016/index.html (see proceedings, volumes 1 & 2 on homepage) +  * ICLS: International Conference of the Learning Sciences, top research conference in the field and mainly focuses on STEM education, includes some research in higher education, https://www.isls.org/icls/2016/index.html (see proceedings, volumes 1 & 2 on homepage) 
-  * NARST: National Association of Research in Science Teaching, mainly focused on practitioners and applied research, http://narst.org/annualconference/2016_Narst_International_Conference_Program.pdf +  * NARST: National Association of Research in Science Teaching, mainly focused on practitioners and research that comes from classrooms or is being applied to classrooms, http://narst.org/annualconference/2016_Narst_International_Conference_Program.pdf 
-  * EDM: Educational Data Mining, mainly focused on machine learning as a method of understanding student learning, http://www.educationaldatamining.org/EDM2016/proceedings/edm2016_proceedings.pdf +  * EDM: Educational Data Mining, mainly focused on machine learning as a method for using data to understand student learning, http://www.educationaldatamining.org/EDM2016/proceedings/edm2016_proceedings.pdf 
-  * AIED: Artificial Intelligence in Education, more comprehensive data mining and methods (including natural language processing) as a means to understand student learning, http://www.springer.com/us/book/9783319197722 +  * AIED: Artificial Intelligence in Education, more comprehensive methodology than EDM (including natural language processing) as a means to understand student learning, http://www.springer.com/us/book/9783319197722 
-  * AERA: American Educational Research Association, biggest conference for presenting new work, but the proceedings are a real pain to sift through, http://www.aera.net/Publications/Online-Paper-Repository/AERA-Online-Paper-Repository+  * AERA: American Educational Research Association, the biggest conference for presenting new work in all areas of education (including higher education, STEM education, etc.), but the proceedings are a pain to sift through, http://www.aera.net/Publications/Online-Paper-Repository/AERA-Online-Paper-Repository 
 + 
 +Answer these questions about your articles: 
 +  * What is the title? 
 +  * What were the main take-aways (conclusions) from the article? 
 +  * What methods did the authors use to come to their conclusions? 
 +  * Do you agree with the conclusions? What critiques do you have about the paper? 
 +  * What did you find most interesting about your article or about the proceedings in general?
  

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