{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T16:32:17Z","timestamp":1649003537650},"reference-count":0,"publisher":"Sciedu Press","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIR"],"abstract":"<jats:p>Professionalism has been estimated as the most important fundamental impetus in progress. Teacher profession as the most\u00a0important within-school factor has been emerged to explain effective teaching and learning by research. In viewing of teacher\u00a0in-service training, professional development and innovation is thus highlighted as key prerequisite for high quality teaching.\u00a0Factor analysis of teacher professional development and evaluation based on math methods was primarily to identify factorial\u00a0sequences of activity involving two teamwork in the classroom. The purpose of this study is to perform to: 1) Couple quantitative\u00a0and qualitative accesses to display teaching research; 2) Deliver the differences of pedagogical reasoning between graduate\u00a0students and undergraduate students; 3) Analyze and visualize the educational practices based on math methods, the former is\u00a0to embody educational performance in academic features, the latter is to communicate concretely and contextually. Researchtechniques herewith are Nagai\u2019s proposals of Rasch model GSP curve (RaschGSP curve), Grey structural modeling (GSM) and\u00a0Matrix-based structure modeling (MSM) have been applied to illustrate structural analysis.<\/jats:p>","DOI":"10.5430\/air.v6n1p91","type":"journal-article","created":{"date-parts":[[2017,1,4]],"date-time":"2017-01-04T05:53:06Z","timestamp":1483509186000},"page":"91","source":"Crossref","is-referenced-by-count":1,"title":["Factor analysis of teacher professional development and evaluation based on math methods of RaschGSP curve, ISM, GSM and MSM"],"prefix":"10.5430","volume":"6","author":[{"given":"Hui-Chung","family":"Ho","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Duc-Hieu","family":"Pham","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Phung-Tuyen","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Woody Jann-Der","family":"Fann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hsiu-Jye","family":"Chiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masatake","family":"Nagai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"3394","published-online":{"date-parts":[[2017,1,3]]},"container-title":["Artificial Intelligence Research"],"original-title":[],"link":[{"URL":"http:\/\/www.sciedu.ca\/journal\/index.php\/air\/article\/viewFile\/10046\/6617","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/www.sciedu.ca\/journal\/index.php\/air\/article\/viewFile\/10046\/6617","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,1,4]],"date-time":"2017-01-04T05:53:06Z","timestamp":1483509186000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.sciedu.ca\/journal\/index.php\/air\/article\/view\/10046"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,1,3]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,7,19]]}},"URL":"https:\/\/doi.org\/10.5430\/air.v6n1p91","relation":{},"ISSN":["1927-6982","1927-6974"],"issn-type":[{"value":"1927-6982","type":"electronic"},{"value":"1927-6974","type":"print"}],"subject":[],"published":{"date-parts":[[2017,1,3]]}}}