Learning What at Went Well l Leade dershi ship p & Managem - PowerPoint PPT Presentation

Sep 12, 2022 •131 likes •167 views

BCoT Ofsted Experience Online Learning What at Went Well l Leade dershi ship p & Managem agement nt Safegua uardi ding ng & Su Suppo port Leaders and Managers were commended for their prep work weeks prior - staff were

BCoT Ofsted Experience Online Learning What at Went Well l – Leade dershi ship p & Managem agement nt – Safegua uardi ding ng & Su Suppo port Leaders and Managers were commended for their prep work weeks prior - staff were • briefed and received training on how to deliver remote learning All classes being carried out in timetabled slots has created good continuity and a • ‘business as usual’ approach Training teams (Digital, Learning Support, RAP’s, IT Systems) working closely with • teacher teams was commended - ‘being led by the pedagogy’ The recording of lessons provides an opportunity for students to review and revisit • The Individual and team needs being identified was a strong point to differentiate support • 1- 1’s have been in place for learners through Chat or Video call, opportunities to attend • college where needed are provided, at risk were supported well Chromebooks that IT Systems quickly gave out to students to enable Remote Learning - • Access to WiFi dongles for the learners in need Maintaining well-being support remotely - providing continuity commended • Access to online content and checking on student well-being commended •
BCoT Ofsted Experience Online Learning What at Went Well l – Teachi hing ng and Learning ning Use of Google Classroom • Students with learning difficulties • Students reported that this way of working has been a chance to develop their • ‘flexibility, resilience, and independence’ Students engage well with new content through; • quizzes • video assessment feedback • annotation of the presentation alongside them to mirror the in class • use of submitting photos for feedback • talking to employers • writing references collaboratively for one another and reflecting at the end of • their course Observing practical demonstrations •
BCoT Ofsted Experience Online Learning THINGS S FOR THE SECTOR TO C CONSID IDER ER How might we best capture the quality of online teaching and learning? • How might we consider the integration of the practical elements of our courses • for September? How might we ensure students are made more conscious of the risk of being • online more (we use tutorials for this but how can we raise awareness more)? Safety online needs to be a priority across the sector? How might we test that students are developing knowledge and skills and • behaviours at the beginning of the year? How might we see their progress?

Recommend

Learning is a never-ending process Tasks come and go, but learning is forever Learn more e ff

NeurIPS 2018 Tutorial on Automatic Machine Learning Learning to Learn Learning Learning Learning Learning Learning automl.org/events -> AutoML Tutorial -> Slides Frank Hutter Joaquin Vanschoren Eindhoven University of Technology

1.36k views • 40 slides

What is Action Learning? What is an ALC? 1 What is Action Learning? Learning by doing

What is Action Learning? What is an ALC? 1 What is Action Learning? Learning by doing Process for bringing together a group of people with varied levels of skills and experience (but with influence, passion, etc. to impact an

191 views • 5 slides

Learning From Data Lecture 2 The Perceptron The Learning Setup A Simple Learning Algorithm: PLA

Learning From Data Lecture 2 The Perceptron The Learning Setup A Simple Learning Algorithm: PLA Other Views of Learning Is Learning Feasible: A Puzzle M. Magdon-Ismail CSCI 4100/6100 recap: The Plan 1. What is Learning? 2. Can We do it?

613 views • 25 slides

4. Learning in MAS 4.1. What is learning? One definition: Bower, Hilgard: Theories of learning,

4. Learning in MAS 4.1. What is learning? One definition: Bower, Hilgard: Theories of learning, Prentice-Hall, 1975: Learning refers to the change in a subjects behavior to a given situation brought about by his repeated experiences in

173 views • 15 slides

What are learning outcomes? Learning Outcomes Learning outcomes are statements that specify what

What are learning outcomes? Learning Outcomes Learning outcomes are statements that specify what learners will know or be able to Everybody Wins do as a result of a learning FYE 2007 activity. Dr. Carolyn Hopper Middle Tennessee State

344 views • 11 slides

Machine Learning 11 AI Slides (6e) c Lin Zuoquan@PKU 1998-2020 11 1 11 Machine Learning

Machine Learning 11 AI Slides (6e) c Lin Zuoquan@PKU 1998-2020 11 1 11 Machine Learning 11.1 Learning agents 11.2 Inductive learning 11.3 Deep learning 11.4 Statistical learning 11.5 Reinforcement learning 11.6 Transfer learning

1.7k views • 159 slides

04 FOCUS ON LEARNING STUDENTS REFLECTING ON THEIR LEARNING In this unit we are learning to

workshop 04 FOCUS ON LEARNING STUDENTS REFLECTING ON THEIR LEARNING In this unit we are learning to . discuss the role of reflection as an important part of learning identify strategies that will help students to reflect on their

539 views • 14 slides

The JOY of LEARNING Think of a topic you are passionate about Think about your learning

The JOY of LEARNING Think of a topic you are passionate about Think about your learning process How much time was spent? How did you practice? To experience research-based learning tools: Focus/Diffuse modes of thinking

1.03k views • 18 slides

Complex learning example: curve fitting t = sin(2 x ) + noise t n t 1 y ( x n , w ) 0 1

Artificial Intelligence: Representation and Problem Solving 15-381 April 10, 2007 Introduction to Learning & Decision Trees Learning and Decision Trees to learning aka: regression What is learning? pattern recognition

462 views • 17 slides

Further thoughts How does e-Learning relate to instruction? How does eLearning change

Ideas from group What is the difference between learning and training? What is the difference between learning and education? Where does learning take place? Who learns? What is the role of instruction in learning? Further

800 views • 47 slides

Learning Sciences: Impact on Learning Technologies & Learning Activities Phillip D. Long,

Learning Sciences: Impact on Learning Technologies & Learning Activities Phillip D. Long, Ph.D. 12-May, 2015 Narrative Arc ( 5 2) Conclusion: What do we want? Learning learning |lrniNG | noun the acquisition of knowledge or

653 views • 36 slides

The Learning Tree Workshop: The Learning Tree Workshop: Regulating Sensation Series on Learning

The Learning Tree Workshop: The Learning Tree Workshop: Regulating Sensation Series on Learning Differences, Learning Challenges, and Learning Strengths Transcript by Stanley I. Greenspan M.D. Narration by Brian MacDonald Sensory Modulation

453 views • 16 slides

Foundations of AI Why learning works 1 6 . Statistical Machine Learning Bayesian Learning and

Contents Statistical learning Foundations of AI Why learning works 1 6 . Statistical Machine Learning Bayesian Learning and Why Learning Works W olfram Burgard, Bernhard Nebel, and Andreas Karw ath 10/ 1 10/ 2 Statistical Learning

305 views • 5 slides

Welcome to Welcome to The Learning Tree Workshop Series on Learning Differences, Learning

Welcome to Welcome to The Learning Tree Workshop Series on Learning Differences, Learning Challenges, and Learning Strengths Strengths As a companion to Dr. Greenspans The Learning Tree : g Overcoming Learning Disabilities From the

367 views • 16 slides

Active Learning Passive Learning Active Learning 1. Think 1. Acquisition of knowledge Ability

Active Learning Passive Learning Active Learning 1. Think 1. Acquisition of knowledge Ability 2. Decision making 2. Application of knowledge 3. Explain/communicate 1. Deep learning Approach to Uni-directional 2. Interactive Learning

282 views • 5 slides

Traditional Machine Learning: Unsupervised Learning Juhan Nam Traditional Machine Learning

GCT634/AI613: Musical Applications of Machine Learning (Fall 2020) Traditional Machine Learning: Unsupervised Learning Juhan Nam Traditional Machine Learning Pipeline in Classification Tasks A set of hand-designed audio features are selected

398 views • 26 slides

1 Why Study Machine Learning? Why Study Machine Learning? Cognitive Science The Time is Ripe

What is Learning? Herbert Simon: Learning is any process by which a system improves performance from CS 391L: Machine Learning experience. Introduction What is the task? Classification Problem solving / planning /

603 views • 6 slides

Meta Learning Shengchao Liu Background Meta Learning (AKA Learning to Learn) A

Meta Learning Shengchao Liu Background Meta Learning (AKA Learning to Learn) A fast-learning algorithm: quickly adapted from the source tasks to the target tasks Key terminologies Support Set & Query Set C-Way K-Shot

2k views • 41 slides

MACHINE LEARNING, STATISTICAL LEARNING AND PARALLEL COMPUTING INTRODUCTION VS MACHINE LEARNING

JACOPO DI IORIO, MATTEO FONTANA, DANIELE OCCHIUTO, CLAUDIA VOLPETTI MACHINE LEARNING, STATISTICAL LEARNING AND PARALLEL COMPUTING INTRODUCTION VS MACHINE LEARNING STATISTICAL LEARNING Separate evolutions, but with shared methodologies MERGE

565 views • 55 slides

Improving Integration of Learning in Learning Communities Through the Development of a Shared

Improving Integration of Learning in Learning Communities Through the Development of a Shared Learning Space Presented by: Emily Richardson richardsone2@queens.edu Director of the Hayworth Center for Online Learning; CATO School of Education

547 views • 15 slides

UNSUPERVISED LEARNING, CLUSTERING UNSUPERVISED LEARNING UNSUPERVISED LEARNING Supervised

UNSUPERVISED LEARNING, CLUSTERING UNSUPERVISED LEARNING UNSUPERVISED LEARNING Supervised learning: X - y pairs, f(x) function approximation Unsupervised learning: only X, no y Exploring the space of X measurements,

440 views • 14 slides

3. Preference Learning Techniques a. Learning Utility Functions b. Learning Preference

AGENDA 1. Preference Learning Tasks 2. Performance Assessment and Loss Functions 3. Preference Learning Techniques a. Learning Utility Functions b. Learning Preference Relations c. Structured Output Prediction d. Model-Based Preference

583 views • 39 slides

Machine Learning: Study of algorithms that improve their performance P at some task T

Machine Learning 10-601 Tom M. Mitchell Machine Learning Department Carnegie Mellon University January 12, 2015 Today: Readings: What is machine learning? The Discipline of ML Decision tree learning Mitchell, Chapter 3

872 views • 29 slides

Learning about vs learning to be It's not what you know, It's what you want to learn. How to

Learning about vs learning to be It's not what you know, It's what you want to learn. How to get a job 1. study hard 2. Get good grades 3. Make a resume 4. Do research 5. Apply to jobs 6. Get interviewed 7. Get an offer 8. Accept the

422 views • 26 slides