Scaffolding information problem solving in web-based collaborative inquiry learning

2012 ◽  
Vol 59 (1) ◽  
pp. 82-94 ◽  
Author(s):  
Annelies Raes ◽  
Tammy Schellens ◽  
Bram De Wever ◽  
Ellen Vanderhoven
Keyword(s):  
Problem Solving ◽  
Collaborative Inquiry ◽  
Inquiry Learning ◽  
Web Based ◽  
Information Problem Solving ◽  
Collaborative Inquiry Learning ◽  
Information Problem

scholarly journals Facilitating learners’ web-based information problem-solving by query expansion-based concept mapping

2014 ◽  
Vol 30 (5) ◽  
Author(s):  
Yueh-Min Huang ◽  
Ming-Chi Liu ◽  
Nian-Shing Chen ◽  
Kinshuk . ◽  
Dunwei Wen
Keyword(s):  
Problem Solving ◽  
Concept Mapping ◽  
Query Expansion ◽  
Concept Maps ◽  
Real Life ◽  
Higher Order ◽  
System Thinking ◽  
Web Based ◽  
Information Problem Solving ◽  
Information Problem

<p>Web-based information problem-solving has been recognised as a critical ability for learners. However, the development of students’ abilities in this area often faces several challenges, such as difficulty in building well-organised knowledge structures to support complex problems that require higher-order skills (e.g., system thinking). To resolve these issues, this study employs a semi-automatic tool that supports query expansion-based concept mapping (QECM) for assisting learners’ web-based information problem-solving. The query expansion technique aims to recommend relevant concepts and linking words for building the map. The linking of concepts also uses non-taxonomic relationships for visualising a systemic model to develop complex problem-solving. An experiment was conducted by randomly dividing 50 participants into two groups, QECM (experimental) and conventional keyword-based search system, (control), to compare their performance during web-based information problem-solving tasks. The results show that the QECM system facilitated participants in extending their queries so as to enhance the comprehensiveness of their constructed concept maps. The QECM also improved the participants’ information problem-solving performance by bridging concepts of an assigned task. The findings imply that learners using the QECM system can focus on the higher-order tasks of problem-solving and be better engaged in exploring real-life problems with the web.</p>

scholarly journals Guidance in computer-supported collaborative inquiry learning: Capturing aspects of affect and teacher support in science classrooms

2021 ◽  
Author(s):  
Tarja Pietarinen ◽  
Tuire Palonen ◽  
Marja Vauras
Keyword(s):  
Teacher Perceptions ◽  
Collaborative Inquiry ◽  
Inquiry Learning ◽  
Science Classrooms ◽  
Student Groups ◽  
Teacher Guidance ◽  
Group Outcomes ◽  
Teacher Affect ◽  
Teachers And Students ◽  
Collaborative Inquiry Learning

AbstractTechnology-enhanced collaborative inquiry learning has gained a firm position in curricula across disciplines and educational settings and has become particularly pervasive in science classrooms. However, understanding of the teacher’s role in this context is limited. This study addresses the real-time shifts in focus and distribution of teachers’ guidance and support of different student groups during in-person computer-supported collaborative inquiry learning in science classrooms. Teachers’ self-perceptions of their guidance and affect were supplemented with students’ self-reported affect. A mixed-methods approach using video analyses and questionnaire data revealed differences between teacher guidance and support associated with teacher perceptions and group outcomes. Groups’ prior science competence was not found to have an effect on teacher guidance and support, rather the teachers guided the groups they perceived as motivated and willing to collaborate. Teacher affect was compounded by student affect, suggesting that consideration of the reciprocal perceptions of teachers and students is necessary in order to understand the teachers’ role in collaborative learning.

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