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ERIC Number: ED527507
Record Type: Non-Journal
Publication Date: 2008
Pages: 158
Abstractor: As Provided
Reference Count: N/A
ISBN: ISBN-978-1-1243-2443-2
ISSN: N/A
The Effect of Concept Mapping with Different Levels of Generativity and Learners' Self-Regulated Learning Skills on Knowledge Acquisition and Representation
Lim, Kyu Yon
ProQuest LLC, Ph.D. Dissertation, The Pennsylvania State University
The purpose of this study was to investigate the effectiveness of concept mapping strategies with different levels of generativity in terms of knowledge acquisition and knowledge representation. Also, it examined whether or not learners' self-regulated learning (SRL) skills influenced the effectiveness of concept mapping strategies with different levels of generativity. Four research questions were posed: (1) Do concept mapping strategies with different levels of generativity influence factual and conceptual knowledge acquisition? (2) Do different levels of self-regulated learning skills influence factual and conceptual knowledge acquisition? (3) Do different levels of self-regulated learning skills affect the effectiveness of different concept mapping strategies in terms of factual and conceptual knowledge acquisition? (4) Do different levels of self-regulated learning skills influence the knowledge representation of learners who study with a fully learner-generated concept map? The participants were 285 undergraduate students who enrolled in a 200-level statistics course at a large northeastern university. The independent variables of this study were the levels of self-regulated learning skills and the levels of generativity in concept mapping strategies. The levels of SRL skills were divided into high and low, while the levels of generativity in concept mapping were operationalized in three treatments: Expert-generated concept mapping, partially learner-generated concept mapping, and fully learner-generated concept mapping. Dependent variables were knowledge acquisition (factual and conceptual knowledge), and knowledge representation of concept maps (the proposition quality, overall quality, and the quantity of propositions). According to the MANOVA results for the first research question, three levels of generativity operationalized in concept mapping strategies produced significantly different levels of effectiveness for knowledge acquisition (F = 3.094; p = 0.016; Wilk's Lambda = 0.939). Tukey post hoc comparisons showed that the expert-generated concept map group outperformed the partially learner-generated concept map group in factual knowledge, while the expert-generated concept map group outperformed both the partially learner-generated concept map group and the fully learner-generated concept map group in conceptual knowledge. Regarding the second research question, self-regulated learning skills caused significant difference in factual knowledge (F = 7.627, p = 0.006). Regarding the third research question, no significant interaction was found, when using MANOVA, between the levels of generativity in concept mapping and the levels of self-regulated learning skills. However, regression analysis indicated that the higher the participants' self-regulated learning skills, the higher the factual knowledge acquisition score, only for the expert-generated concept map group and partially learner-generated concept map group. Regarding the last research question on knowledge representation, a significant effect of the levels of self-regulated learning skills was found in proposition quality, overall quality, and the quantity of proposition (F = 3.004; p = 0.037; Wilk's Lambda = 0.880). More specifically, the participants with high self-regulated learning skills scored significantly higher in the overall quality of knowledge representation and the quantity of propositions made in each concept map. Instructional implications included: (1) When using expert-generated concept maps, learners should be encouraged to actively interact with the given map; (2) When using partially-learner generated concept maps, learners should be guided not to focus only on the fill-in-the-blank activity; (3) When using fully learner-generated concept maps, consider details of procedures as a secondary component; (4) When evaluating fully learner-generated concept maps, use the quality of cross-link as an indicator of high self-regulators. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A