Enhancing Learning through Mobile Technology: The Cognitive Apprenticeship Model

Jan 26, 2026

110 likes | 237 Vues

This presentation discusses the integration of mobile technology and Web 2.0 tools into vocational education and training (VET), emphasizing the Cognitive Apprenticeship Model. It highlights how mobile learning (mLearning) enables knowledge acquisition anytime, anywhere, influencing learning styles among young learners. Survey results indicate that e-learning can improve future employment outcomes. Practical applications of iLectures, podcasts, and the use of mobile phones in workplace-based learning are explored, showcasing the need for responsive educational approaches in the digital age.

Share Presentation

Embed Code

ganya

Télécharger la présentation

Enhancing Learning through Mobile Technology: The Cognitive Apprenticeship Model

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

G/T in a “Flat” World: Redesigning Opportunities for 21 st Century Learning

G/T in a “Flat” World: Redesigning Opportunities for 21 st Century Learning. KAGE Conference 2006 February 23, 2006 Tom Welch. Friedman on change . . . “Change is hard. Change is hardest on those caught by surprise. Change is hardest on those who have difficulty changing too.

1.39k views • 84 slides

e-Learning: Concepts, Usage and Tools

e-Learning: Concepts, Usage and Tools Martin Molhanec Abstract What is e-Learning? Concept of e-Learning. Usage of e-Learning. Tools for e-learning. Resources Malo, R., Motyčka, A.: eLearning solution at Mendel University in Brno. E3 Event, Roma 2003 Marcel de Leeuwe

1.08k views • 52 slides

THE GUIDANCE- ORIENTED APPROACH TO LEARNING

THE GUIDANCE- ORIENTED APPROACH TO LEARNING. Presented by: Sandra Salesas and Cheryl Pratt Quebec federation of home and school association October 21st, 2006. A Little Reminder.

1.14k views • 39 slides

Learning Theories, Learning Styles and Differentiated Instruction

Learning Theories, Learning Styles and Differentiated Instruction. Rhonda Christensen University of North Texas. What is Learning?. Learning is a transfer of knowledge Not necessarily directly from teacher to student Multiple Theories of how we Learn Behaviorist Cognitivist.

1.89k views • 32 slides

Learning Style and Intelligence

Learning Style and Intelligence. Chapter 3. What is learning style?. Your learning style is your learning preference. How do you like to learn?. Knowing about Your Learning Style Helps You to:. Be more productive Increase achievement Be more creative Improve problem solving

1.32k views • 83 slides

Marc Prensky

Learning in the 21 st Century April 5, 2006 Shrewsbury, UK. Marc Prensky. marc@games2train.com www.marcprensky.com. © 2006 Marc Prensky. © 2006 Marc Prensky. © 2003 Marc Prensky. © 2005 Marc Prensky. My New Book:. © 2005 Marc Prensky. Serious training. in a game environment.

2.26k views • 202 slides

Chapter 6 Learning

Chapter 6 Learning. Learning. Learning is defined as any relatively permanent change in behavior that is based upon experience. It is an area of psychology that seems simple to evaluate but is in fact quite complex.

3.78k views • 132 slides

Semi-supervised learning and self-training

Semi-supervised learning and self-training. LING 572 Fei Xia 02/14/06. Outline. Overview of Semi-supervised learning (SSL) Self-training (a.k.a. Bootstrapping). Additional Reference. Xiaojin Zhu (2006): Semi-supervised learning literature survey.

1.17k views • 36 slides

Ontology Learning and Population from Text

Ontology Learning and Population from Text. Philipp Cimiano Springer, 2006. Ontology Learning and Population from Text. Tutorial at EACL-2006 Paul Buitelaar , Philipp Cimiano 11th Conference of the European Chapter of the Association for Computational Linguistics

1.11k views • 83 slides

Machine learning: Unsupervised learning

Machine learning: Unsupervised learning. David Kauchak cs311 Spring 2013 adapted from: http://www.stanford.edu/class/cs276/handouts /lecture17-clustering.ppt. Administrative. Assignment 5 out soon. Machine learning code. Weka Java based Tons of approaches

1.01k views • 68 slides

IT Enters A new Learning Environment

IT Enters A new Learning Environment. Conceptual Models of Learning. Constructivism. Generative Learning. Discovery Learning. Meaningful Learning. Meaningful Learning. It gives focus to new experience that is related to what the learner already know.

1.62k views • 14 slides

2006 RMU Town Hall Meetings

2006 RMU Town Hall Meetings. April 11-12, 2006. Overview Purpose Process Questions at End. Town Hall 2006. Town Hall 2006. President’s Update. Search--Vice President for Institutional Advancement Vice President and General Counsel—Sid Zonn. Town Hall 2006. Observations About RMU.

1.16k views • 88 slides

學習導向的評估 Learning Oriented Assessment

學習導向的評估 Learning Oriented Assessment. 香港教育學院 The Hong Kong Institute of Education Centre for Assessment Research & Development, Assessment Project 莫慕貞 Magdalena M. C. Mok HKIEd, January 2006. Purpose of Sharing Today 今天的目的. 1. What is Learning Oriented Assessment? 學習導向的評估

1.29k views • 67 slides

January 18, 2006: IAP 2006 12.091 Session 3A: P. ILA

MEDICAL GEOLOGY/GEOCHEMISTRY PILLALAMARRI ILA Earth Atmospheric & Planetary Sciences Neutron Activation Analysis Laboratory Massachusetts Institute of Technology Cambridge, MA 02139 IAP 2006: 12.091 Credit Course: January 9 - 23, 2006 Session 3A - January 18, 2006.

904 views • 64 slides

Learning and Learning Disabilities

Learning and Learning Disabilities. Definition Determination Related Aspects in the Classroom. People should not be identified as learning disabled until a proper attempt at instruction has been made. Types of Learning Disabilities:.

7.61k views • 61 slides

What is learning?

What is learning?. What makes a good comedian?. Learning is the Hedgehog Concept of schools. Where does learning happen in schools?. FOUR STATES RELATED TO LEARNING New Consolidated Treading Water Drowning. What learning isn’t. Learning isn’t… brand new.

1.2k views • 79 slides

George D. Kuh Maricopa Student Success Conference September 29, 2006

Designing for Success: Creating Conditions That Matter. George D. Kuh Maricopa Student Success Conference September 29, 2006. We all want the same thing—an undergraduate experience that results in high levels of learning and personal development for all students. Overview.

988 views • 78 slides

Machine Learning

Machine Learning. Georg Pölzlbauer December 11, 2006. Outline. Exercises Data Preparation Decision Trees Model Selection Random Forests Support Vector Machines. Exercises. Groups of 2 or 3 students

1.22k views • 101 slides

Social Learning and Consumer Demand

Social Learning and Consumer Demand. Markus Mobius (Harvard University and NBER) Paul Niehaus (Harvard University) Tanya Rosenblat (Wesleyan University and IAS) 28 April, 2006. Introduction. We “seed” a known social network with information by

1.1k views • 94 slides

Inductive Transfer Retrospective & Review

Inductive Transfer Retrospective & Review. Rich Caruana Computer Science Department Cornell University. Inductive Transfer: a.k.a. …. Bias Learning Multitask learning Learning (Internal) Representations Learning-to-learn Lifelong learning Continual learning Speedup learning Hints

1.02k views • 75 slides

More Related

Enhancing Learning through Mobile Technology: The Cognitive Apprenticeship Model

Enhancing Learning through Mobile Technology: The Cognitive Apprenticeship Model

Presentation Transcript

G/T in a “Flat” World: Redesigning Opportunities for 21 st Century Learning

e-Learning: Concepts, Usage and Tools

THE GUIDANCE- ORIENTED APPROACH TO LEARNING

Learning Theories, Learning Styles and Differentiated Instruction

Learning Style and Intelligence

Marc Prensky

Chapter 6 Learning

Semi-supervised learning and self-training

Ontology Learning and Population from Text

Machine learning: Unsupervised learning

IT Enters A new Learning Environment

2006 RMU Town Hall Meetings

學習導向的評估 Learning Oriented Assessment

January 18, 2006: IAP 2006 12.091 Session 3A: P. ILA

Learning and Learning Disabilities

What is learning?

George D. Kuh Maricopa Student Success Conference September 29, 2006

Machine Learning

Social Learning and Consumer Demand

Inductive Transfer Retrospective &amp; Review

Inductive Transfer Retrospective & Review