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020 ▼a 9780438209466
035 ▼a (MiAaPQ)AAI10822323
035 ▼a (MiAaPQ)grad.sunysb:13712
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 310
1001 ▼a Wang, Xiaoying.
24510 ▼a Longitudinal Learning Dynamics and the Conceptual Restructuring of Evolutionary Understanding.
260 ▼a [S.l.] : ▼b State University of New York at Stony Brook., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 90 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Stephen J. Finch.
5021 ▼a Thesis (Ph.D.)--State University of New York at Stony Brook, 2018.
520 ▼a Studies of science learning at the undergraduate level are often based on comparisons of pre- and post-course results. Research is needed to understand student longitudinal learning patterns in more details. Latent Class Growth Analysis (LCGA),
520 ▼a Data for this study is from four semesters (spring and fall, 2016 and 2017) of this course, with a total of 1725 students studied. The ACORNS (Assessing COntextual Reasoning about Natural Selection) instrument was used to measure student evoluti
520 ▼a Learning patterns were replicated in the four semesters. Eighteen binary outcome variables (12 key concepts or right ideas, and 6 naive ideas or wrong ideas) from ACORNS were simultaneously used in the LCGA analysis. Three trajectory groups or l
520 ▼a The LCGA analysis showed increased mastery of evolutionary concepts as measured by ACORNS in all groups. It identified the specific ACORNS topics that were mastered well and those that were not mastered. The analysis identified specific areas th
590 ▼a School code: 0771.
650 4 ▼a Statistics.
690 ▼a 0463
71020 ▼a State University of New York at Stony Brook. ▼b Applied Mathematics and Statistics.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0771
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998463 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자