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Learning and Instruction in the Digital Age

:	Geeske Bakker, Clemens Bechter, Laura Benvenuti, Axel M. Blessing, Maria Boubouka, Edita Butrime
:	Michael Spector, Dirk Ifenthaler, Kinshuk
:	Learning and Instruction in the Digital Age
:	Springer-Verlag
:	9781441915511
:	1
:	CHF 133.00
:

:	Schulpädagogik, Didaktik, Methodik
:	English

:	404
:	Wasserzeichen/DRM
:	PC/MAC/eReader/Tablet
:	PDF

Instruction tailored to the individual student, learning and teaching outside the limits of time and space-ideas that were once considered science fiction are now educational reality, with the prospect of an intelligent Web 3.0 not far distant. Alongside these innovations exists an emerging set of critical-thinking challenges, as Internet users create content and learners (and teachers) take increased responsibility in their work.Learning and Instruction in the Digital Age nimbly balances the technological and pedagogical aspects of these rapid changes, gathering papers from noted researchers on a wealth of topics relating to cognitive approaches to learning and teaching, mental models, online learning, communications, and innovative educational technologies, among them:

Co nition and student-centered, Web-based learning,

T e progression of mental models throughout a course of instruction,

Experiencing education with 3D virtual worlds,

Exp nding educational boundaries through multi-school collaboration,

LI>Adapting e-learning to different learning styles,

The student blog as reflective diary.

With its blend of timely ideas and forward thinking,Learning and Instruction in the Digital Age will enrich the work of researchers in educational psychology, educational technology, and cognitive science.

	Preface	8
	Acknowledgments	10
	Contents	12
	Contributors	14
	Reviewers	17
	Part I Cognitive Approaches to Learning and Instruction (Spector)	18
	1 Learning and Instruction in the Digital Age	19
	1.1 The Dawn of the Digital Age	19
	1.2 Opportunities and Concerns for Learning and Instruction in the Digital Age	20
	1.3 A Step Forward: Personal Learning Management Systems	22
	1.4 Beyond the Digital Age	24
	References	25
	2 Cognition and Student-Centered, Web-Based Learning: Issues and Implications for Research and Theory	27
	2.1 Introduction	27
	2.2 Assumptions Underlying Student-Centered Learning	28
	2.2.1 Locus and Nature of Knowledge	29
	2.2.2 Role of Context	30
	2.2.3 Role of Prior Knowledge and Experience	31
	2.3 Nagging Issues	31
	2.3.1 Technical System Knowledge and Familiarity	31
	2.3.2 Disorientation	31
	2.3.3 Canonical Versus Individual Meaning: Misconceptions	32
	2.3.4 Knowledge as Accretion Versus Tool	32
	2.3.5 To Scaffold or to Direct	33
	2.3.6 Attitudes, Beliefs, and Practices	33
	2.3.7 Cognitive Load	34
	2.3.8 Metacognitive Demands	34
	2.4 Implications for Research, Theory, and Design	34
	2.4.1 Can Student-Centered, Web-Based Learning Be Scaffolded?	34
	2.4.2 Will Students Critically Assess the Legitimacy, Veracity, and Accuracy of Resources?	35
	2.4.3 Will Scaffolding Help Students to Manage Cognitive Complexity?	35
	2.4.4 Will Students Negotiate Their Individual Learning Needs?	35
	2.4.5 Will Students Identify Appropriate and Relevant Resources?	35
	References	36
	3 Testing as Feedback to Inform Teaching	40
	3.1 Introduction	40
	3.1.1 Summative Versus Formative Testing	41
	3.1.2 Substituting Memorization for Understanding	42
	3.1.3 The Test Interpretation Problem	42
	3.1.4 Meaning from Alternative Answers	17
	3.2 An Alternative Approach to Test Scoring	44
	3.2.1 Solving the Linear Dependency Issue	45
	3.2.2 Interpreting the Patterns	46
	3.3 Implications for Testing Theory	47
	3.3.1 Heads or Tails: The Dichotomy Dilemma?	48
	3.3.2 A Dicey Alternative	49
	3.3.3 Exposing the Dynamics of Learning	50
	3.3.4 Associating Independent Tests	52
	3.4 A New Model for Assessing Learning	55
	3.4.1 Illustrations Using Actually Student Data	55
	3.4.2 Student Performance Change	56
	3.4.2.1 Student 2350	56
	3.4.2.2 Student 1660	57
	3.4.2.3 Student 1150	58
	3.4.2.4 Student 160	59
	3.5 Summary, Conclusions, and Implications	60
	Appendix	62
	Notes for Appendix	63
	References	63
	4 Enhancing Learning from Informatics Texts	65
	4.1 Introduction	65
	4.2 The ConstructionIntegration Model	68
	4.2.1 Text Coherence	69
	4.2.2 The Measurement of Learning	70
	4.3 The Study	71
	4.3.1 Method	71
	4.3.1.1 Participants	71
	4.3.1.2 Procedure	72
	4.3.2 Materials and Tasks	72
	4.3.2.1 Matching Activity (Pre-reading and Post-reading Test)	72
	4.3.2.2 Texts	72
	4.3.2.3 The Propositional Representation of Text	73
	4.3.3 Text Recall	73
	4.3.4 Assessment Questions	73
	4.3.5 Data Collection	74
	4.4 Results	74
	4.4.1 Matching Activity	74
	4.4.1.1 Reading Rates	75
	4.4.1.2 Text Recall	75
	4.4.1.3 Assessment Questions	76
	4.5 Conclusions and Future Plans	77
	References	78
	Part II Knowledge Representation and Mental Models (Ifenthaler)	80
	5 Model-Based Knowledge Mapping	81
	5.1 Introduction	81
	5.2 Theoretical Background	82
	5.2.1 Semantic Interpretation and Categorization	82
	5.2.2 Mental Models and Model-Centered Instruction	83
	5.2.3 Distributed Cognition	83
	5.2.4 Model-Based Knowledge Management	84
	5.3 Conventional Knowledge Mapping