Articles in this special issue present recent advances in using state-of-the-art software systems that gather data with which to examine and measure features of learning and particularly self-regulated learning (SRL). Despite important advances, there remain challenges. I examine key features of SRL and how they are measured using common tools. I advance the case that traces of cognition and metacognition offer critical information about SRL that other state-of-the-art measurements cannot.
机构:
Univ British Columbia, Carl Wieman Sci Educ Initiat, Vancouver, BC V5Z 1M9, CanadaCarnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USA
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McLaren, Bruce M.
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Carnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USACarnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USA
McLaren, Bruce M.
;
Koedinger, Kenneth R.
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机构:
Carnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USACarnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USA
机构:
Univ British Columbia, Carl Wieman Sci Educ Initiat, Vancouver, BC V5Z 1M9, CanadaCarnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USA
Roll, Ido
;
McLaren, Bruce M.
论文数: 0引用数: 0
h-index: 0
机构:
Carnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USACarnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USA
McLaren, Bruce M.
;
Koedinger, Kenneth R.
论文数: 0引用数: 0
h-index: 0
机构:
Carnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USACarnegie Mellon Univ, Human Comp Interact Inst, Pittsburgh, PA 15217 USA