مؤتمر
Mining, Analyzing, and Modeling the Cognitive Strategies Students Use to Construct Higher Quality Causal Maps
| العنوان: | Mining, Analyzing, and Modeling the Cognitive Strategies Students Use to Construct Higher Quality Causal Maps |
|---|---|
| اللغة: | English |
| المؤلفون: | Allan Jeong, Hyoung Seok-Shin |
| المصدر: | International Association for Development of the Information Society. 2023. |
| الإتاحة: | International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org |
| Peer Reviewed: | Y |
| Page Count: | 8 |
| تاريخ النشر: | 2023 |
| نوع الوثيقة: | Speeches/Meeting Papers Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Critical Thinking, Learning Strategies, Concept Mapping, Learning Analytics, Algorithms, Causal Models, Persuasive Discourse, Problem Solving, Undergraduate Students, Scores |
| مستخلص: | The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the same processes produce higher-quality causal maps. This study analyzed the first five nodes that students (n = 37) placed in their causal maps to reveal that: 1) use of backward, forward, breadth-first, and depth-first processing produced maps of similar quality; and 2) backward processing had three times more impact on maps scores than depth-first processing to suggest that linking events into chains using backward chaining is one approach to constructing higher quality causal maps. These findings are compared with prior research findings and discussed in terms of noted differences in the task demands of constructing argument versus causal maps to gain insights into why, how, and when specific processes/strategies can be applied to create higher-quality causal maps and argument maps. These insights provide guidance on ways to develop diagramming and analytic tools that automate, analyze, and provide real-time support to improve the quality of students' maps, learning, understanding, and problem-solving skills. [For the full proceedings, see ED636095.] |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| رقم الأكسشن: | ED636496 |
| قاعدة البيانات: | ERIC |
| الوصف غير متاح. |