Understanding Collaborative Learning Processes and Outcomes Through Student Discourse Dynamics

被引:0
|
作者
Park, Seehee [1 ]
Nixon, Nia [1 ,2 ]
D'Mello, Sidney [3 ]
Shariff, Danielle [1 ]
Choi, Jaeyoon [1 ]
机构
[1] Univ Calif Irvine, Sch Educ, Irvine, CA 92697 USA
[2] Univ Calif Irvine, Dept Cognit Sci, Irvine, CA 92697 USA
[3] Univ Colorado, Inst Cognit Sci, Boulder, CO 80309 USA
基金
美国国家科学基金会;
关键词
Learning Analytics; Discourse Analytics; Natural Language Processing; Collaborative Problem Solving; Virtual Learning Environment; AFFECTIVE TONE; ROLES; LANGUAGE; WORDS; MOOD; TEXT;
D O I
10.1145/3706468.3706547
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study explores the relation between students' discourse dynamics and performance during collaborative problem-solving activities utilizing Linguistic Inquiry Word Count (LIWC). We analyzed linguistic variables from students' communications to explore social and cognitive behavior. Participants include 279 undergraduate students from two U.S. universities engaged in a controlled lab setting using the physics related educational game named Physics Playground. Findings highlight the relationship between social and cognitive linguistic variables and student's physics performance outcome in a virtual collaborative learning context. This study contributes to a deeper understanding of how these discourse dynamics are related to learning outcomes in collaborative learning. It provides insights for optimizing educational strategies in collaborative remote learning environments. We further discuss the potential for conducting computational linguistic modeling on learner discourse and the role of natural language processing in deriving insights on learning behavior to support collaborative learning.
引用
收藏
页码:938 / 943
页数:6
相关论文
共 50 条