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Vogel, Freydis; Kollar, Ingo; Fischer, Frank; Reiss, Kristina; Ufer, Stefan – International Journal of Computer-Supported Collaborative Learning, 2022
Collaboration scripts and heuristic worked examples have been described as powerful scaffolds to support skill acquisition in CSCL. While CSCL scripts particularly facilitate argumentative discourse within groups, heuristic worked examples provide heuristics and worked out pathways to solve domain-specific tasks. Yet, both scripts and heuristic…
Descriptors: Mathematics Instruction, Computer Assisted Instruction, Teaching Methods, Comparative Analysis
Vogel, Freydis; Kollar, Ingo; Ufer, Stefan; Reichersdorfer, Elisabeth; Reiss, Kristina; Fischer, Frank – Instructional Science: An International Journal of the Learning Sciences, 2016
Collaboration scripts and heuristic worked examples are effective means to scaffold university freshmen's mathematical argumentation skills. Yet, which collaborative learning processes are responsible for these effects has remained unclear. Learners presumably will gain the most out of collaboration if the collaborators refer to each other's…
Descriptors: Persuasive Discourse, Skill Development, Mathematics Skills, Computer Assisted Instruction
Sonnenberg, Christoph; Bannert, Maria – Journal of Learning Analytics, 2015
According to research examining self-regulated learning (SRL), we regard individual regulation as a specific sequence of regulatory activities. Ideally, students perform various learning activities, such as analyzing, monitoring, and evaluating cognitive and motivational aspects during learning. Metacognitive prompts can foster SRL by inducing…
Descriptors: Metacognition, Cues, Control Groups, Outcomes of Education
Crowley, Rebecca S.; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia – Advances in Health Sciences Education, 2013
The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to…
Descriptors: Heuristics, Computer Assisted Instruction, Medical Education, Pathology