Learning Parameterized Skills

We introduce a method for constructing skills capable of solving tasks drawn from a distribution of parameterized reinforcement learning problems. The method draws example tasks from a distribution of interest and uses the corresponding learned policies to estimate the topology of the lower-dimensional piecewise-smooth manifold on which the skill policies lie. This manifold models how policy parameters change as task parameters vary. The method identifies the number of charts that compose the manifold and then applies non-linear regression in each chart to construct a parameterized skill by predicting policy parameters from task parameters. We evaluate our method on an underactuated simulated robotic arm tasked with learning to accurately throw darts at a parameterized target location.Comment: Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012

Learning and Skills Council : update

"The Newsletter for Partners and Stakeholders of the Learning and Skills Council" -- front cover

Service-learning @ Lingnan : facts & figures

This booklet summarizes the results and findings from the ongoing research and evaluation studies of Service-Learning. It provides supporting evidence that Service-Learning enhances students’ development in seven learning outcomes: Subject-Related Knowledge, Communication Skills, Social Competence, Problem- Solving Skills, Research Skills, Organization Skills and Civic Orientation.https://commons.ln.edu.hk/osl_book/1011/thumbnail.jp

A Learning and Skills Strategy

"The Learning and Skills Strategy sets out a vision for a learning region and offers a framework for achieving that vision. It is entirely encompassed within the Regional Strategy (as the Investing in People section). The strategy is based on a formal Labour Market assessment and the extensive consultation exercise undertaken by the NWDA; it has been further informed by a standing group (the Skills and Learning Forum) representing key players in education and training and a group of employers and their representatives. Throughout the strategy the phrase ‘learning and skills’ embraces all elements of education and learning appropriate to social and economic fulfillment.

A New Learning and Skills Landscape? The central role of the Learning and Skills Council

This is the first paper from a project which is part of the Economic and Social Research Council’s Programme of research into “Teaching and Learning”. The project, entitled “The Impact of Policy on Learning and Inclusion in the New Learning and Skills Sector”, explores what impact the efforts to create a single learning and skills system (LSS) are having on teaching, learning, assessment and inclusion for three marginalised groups of post-16 learners. Drawing primarily on policy documents and 62 in-depth interviews with national, regional and local policymakers in England, the paper points to a complex, confusing and constantly changing landscape; in particular, it deals with the formation, early years and recent reorganisation of the Learning and Skills Council (LSC), its roles, relations with Government, its rather limited power, its partnerships and likely futures. While the formation of a more unified LSS is broadly seen as a necessary step in overcoming the fragmentation and inequalities of the previous post-16 sector, interviewees also highlighted problems, some of which may not simply abate with the passing of time. Political expectations of change are high, but the LSC and its partners are expected to carry through ‘transformational’ strategies without the necessary ‘tools for the job’. In addition, some features of the LSS policy landscape still remain unreformed or need to be reorganised. The LSC and its partners are at the receiving end of a series of policy drivers (eg planning, funding, targets, inspection and initiatives) that may have partial or even perverse effects on the groups of marginalised learners we are studying

Effects of the Jigsaw and Teams Game Tournament (TGT) Cooperative Learning on the Learning Motivation and Mathematical Skills of Junior High School Students

This study aims to: 1) describe the effectiveness of the jigsaw and TGT cooperative learning in the learning motivation and mathematical skills of junior high school (JHS) students, and 2) investigate the significant difference in the learning motivation and mathematical skills between the JHS students learning through the jigsaw cooperative learning and those learning through the TGT cooperative learning. This study was a quasi-experimental study using the non-equivalent pretest and posttest group design. This study involved two experimental classes. The research population comprised Year VII students of SMP Pembangunan Piyungan and the research sample consisted of two classes selected from all Year VII groups, with Year VII.A receiving a treatment of the jigsaw cooperative learning and Year VII.B receiving a treatment of the TGT cooperative learning. The instruments consisted of a test, i.e. a mathematical skill test, and a non-test, i.e. a questionnaire of mathematics learning motivation. To investigate the effectiveness of the jigsaw and TGT cooperative learning in the learning motivation and mathematical skills of JHS students, the data were analyzed using the one sample test. To investigate the significant difference in the learning motivation and mathematical skills between the students learning through the jigsaw cooperative learning and those learning through the TGT cooperative learning, the data were analyzed using the T2 Hotelling. To compare the effectiveness of the jigsaw and TGT cooperative learning in the learning motivation and mathematical skills of the students, the data were analyzed using the t-test. The normality was tested using the univariate approach, namely the Kolmogorov Smirnov, the homogeneity using the Box' M test, and the equivalence of the variance-covariance matrix using the Levene's test. The results of the study show that: 1) the jigsaw cooperative learning is effective for the JHS students’ mathematical skills and mathematics learning motivation; 2) the TGT cooperative learning is effective for the JHS students’ mathematical skills and mathematics learning motivation; 3) there is a difference in the effectiveness of the jigsaw and TGT cooperative learning in the JHS students’ mathematical skills and mathematics learning motivation; 4) the jigsaw cooperative learning method is more effective than the TGT cooperative learning method for the JHS students’ mathematics learning motivation; and 5) the jigsaw cooperative learning method is more effective than the TGT cooperative learning method for the JHS students’ mathematical skills. Keyword: Cooperative Learning, Jigsaw, Teams Game Turnament, Learning Motivation, Mathematics Skill

Local curriculum in higher education institutions: consultation on draft regulations to apply the provisions of the Learning and Skills Act 2000 relating to local curriculum to institutions in the higher education sector in Wales

"This consultation aims to gather views on the Welsh Assembly Government’s proposals to make Regulations under section 33Q of the Learning and Skills Act 2000 that will apply the local curriculum provisions to higher education institutions in Wales. The provisions relating to the local curriculum were inserted into the Learning and Skills Act 2000 by the Learning and Skills (Wales) Measure 2009." - Overview

A Deep Hierarchical Approach to Lifelong Learning in Minecraft

We propose a lifelong learning system that has the ability to reuse and transfer knowledge from one task to another while efficiently retaining the previously learned knowledge-base. Knowledge is transferred by learning reusable skills to solve tasks in Minecraft, a popular video game which is an unsolved and high-dimensional lifelong learning problem. These reusable skills, which we refer to as Deep Skill Networks, are then incorporated into our novel Hierarchical Deep Reinforcement Learning Network (H-DRLN) architecture using two techniques: (1) a deep skill array and (2) skill distillation, our novel variation of policy distillation (Rusu et. al. 2015) for learning skills. Skill distillation enables the HDRLN to efficiently retain knowledge and therefore scale in lifelong learning, by accumulating knowledge and encapsulating multiple reusable skills into a single distilled network. The H-DRLN exhibits superior performance and lower learning sample complexity compared to the regular Deep Q Network (Mnih et. al. 2015) in sub-domains of Minecraft

Mathematical Communication: What And How To Develop It In Mathematics Learning?

Mathematics is the language of symbols so that everyone who studied mathematics required having the ability to communicate using the language of these symbols. Mathematical communication skills will make a person could use mathematics for its own sake as well as others, so that will increase positive attitudes towards mathematics. Mathematical communication skills can support mathematical abilities, such as problem solving skills. With good communication skills then the problem will more quickly be represented correctly and this will support in solving problems. Students' mathematical communication skills can be developed in various ways, one with group discussions. Brenner (1998) found that the formation of small groups facilitate the development of mathematical communication skills. This paper describes the mathematical communication and how to develop the mathematical communication skills in learning mathematics. For further clarify the discussion, given also the example of learning that emphasizes the development of mathematical communication skills. Keywords: Mathematical Communication, Mathematics Learning