Language Learning Strategy Taxonomy Used by the Teacher in Teaching English

Language Learning Strategies is simply refers to an individual‘s approach to complete a task. This is an individual way of organizing and using a particular set of skills in order to learn content or accomplish other tasks more effectively and efficiently in school as well as in nonacademic settings. Some previously conducted research found that good language learners actively involve themselves in the language learning process by identifying and seeking preferred learning environments and exploring them. The newly adapted curriculum in Indonesia emphasizes on the discovery learning. This study is aimed to find facts dealing with learning strategies used by high achievers and underachievers, whether there are any differences between the two groups. After research was conducted, the data shows that there are some differences in the learning strategies used by the two groups. The high-achievers uses more varied strategies

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.

The use of additional information in problem-oriented learning environments

Self-directed learning with authentic and complex problems (problem-oriented learning) requires that learners observe their own learning and use additional information when it is appropriate – e.g. hypertextual information in computer-supported learning environments. Research results indicate that learners in problem-oriented learning environments often have difficulties using additional information adequately, and that they should be supported. Two studies with a computer-supported problem-oriented learning environment in the domain of medicine analyzed the effects of strategy instruction on the use of additional information and the quality of the problem representation. In study 1, an expert model was used for strategy instruction. Two groups were compared: one group with strategy modeling and one group without. Strategy modeling influenced the frequency of looked-up hypertextual information, but did not influence the quality of learners' problem representations. This could be explained by difficulties in applying the general hypertext information to the problem. In study 2, the additional information was presented in a more contextualized way as graphical representation of the case and its relevant concepts. Again, two groups were compared: one with a strategy instruction text and one without. Strategy instruction texts supported an adequate use of this graphical information by learners and had an effect on the quality of their problem representations. These findings are discussed with respect to the design of additional help systems in problem-oriented learning environments

Genius Learning Strategy Berbasis Magic Formulasebagai Upaya Peningkatan Hasil Belajar Siswakelas V Mapel Matematika Materi Bangun Ruangdi SD Negeri Kowangbinangun Kalasan

This study is intended to know about the role of Magic Formula-Based GeniusLearning Strategy can improve the output of mathematic learning at SD NegeriKowangbinangun Kalasan.The study employed a quasi-experimental approach. The technique of datacollection was done by participation observation and documentation. The subject of theresearch was the students Grade V at SD Negeri Kowangbinangun, Kalasan.The result of the study shows that the implementation of Magic Formula-BasedGenius Learning Strategy achieved good results, meaning that the students had activerole in the learning process. This strategy could increase and motivate the students tolearn mathematics, specifically geometry or shape. The postest of the second cycleproduced better scores. The students\u27 average scores was 5. 25 and the average scoresin the posttest of the second cycle was 8.15. The student also became active and thesituation of mathematic class became enjoyable

Practical Deep Reinforcement Learning Approach for Stock Trading

Stock trading strategy plays a crucial role in investment companies. However, it is challenging to obtain optimal strategy in the complex and dynamic stock market. We explore the potential of deep reinforcement learning to optimize stock trading strategy and thus maximize investment return. 30 stocks are selected as our trading stocks and their daily prices are used as the training and trading market environment. We train a deep reinforcement learning agent and obtain an adaptive trading strategy. The agent's performance is evaluated and compared with Dow Jones Industrial Average and the traditional min-variance portfolio allocation strategy. The proposed deep reinforcement learning approach is shown to outperform the two baselines in terms of both the Sharpe ratio and cumulative returns

Making the case for action learning as an effective framework for strategy making

Action learning encourages individual reflection, insightful questioning and assumption breaking that result in changes in attitude and behaviour. This learning process provides the potential to explore and solve complex organizational problems, such as, the question of how to develop a future business strategy. Existing literature on the process of strategy making presents a multi-faceted debate, with the ‘Learning School’ of strategic management being one of the main approaches to conceptualise strategy formation. This school of thought suggests that strategy making is a process of emergent learning over time, where strategy makers critically reflect on past experience and adapt their strategies accordingly. Learning from action, change and reflection, is therefore, considered to be more useful in strategy making than formal analysis and subsequent strategy formulation. The premises of the Learning School of strategy making are similar to the premises of action learning, yet, the action learning paradigm has made little or no impact in strategic management literature. This is particularly surprising since the fundamental tenets of action learning could enable it to make an important contribution to strategy makers and business strategy development. This paper makes the case for action learning to feature more prominently in strategic management literature, and particularly, in the Learning School. It proposes that using an action learning methodology can effectively contribute to the development of business strategy, particularly for those organizations operating in competitive environments that are complex and unpredictable. In this type of environment, strategic responses tend to evolve from a process of experimentation, trial and error. Action learning is advocated as a suitable framework to encapsulate this emergent and experimental process and provide a platform for the development of effective strategy making

Strategy as Learning: Capturing Emerging Knowledge

The process of strategy making presents a multi-faceted debate, with the ‘Learning School’ of strategic management being one of the main approaches to conceptualise strategy formation. This approach suggests that strategy making is a process of emergent learning over time, where strategy makers critically reflect on past experience, experiment in new competitive conditions and adapt their strategies accordingly. The premises of the Learning School are similar to the premises of action learning, and yet, the action learning paradigm appears to have made little or no impact in strategic management literature and practice. This paper proposes that implementing an action learning methodology into the process of strategy making could make an important contribution to strategy makers by capturing, harnessing and developing organizational learning and knowledge