Best Practices in Science Education and Next Generation Science Standards: A Review of Systems Thinking, Inquiry-based Learning and Culturally Sustainable Practices

Public School science educators are given the task to teach students dynamic, interpretable material based on grade level as well as national and state standards. Science is at the forefront of many jobs and future economic stability and also encompasses a wide range of disciplinary topics. Having educators use the best resources in curriculum development and teaching methodology is crucial to successfully empowering future scientific research and understanding. The Whole Ecosystems in Balance (WEB), A Natural Resource Curriculum, originally created in 1995, was used to support science teaching efforts in Eastern Oregon. In order to continue its relevance, the curriculum needed to be revised and aligned with current standards. In an attempt to use the most pertinent and current resources available in WEB curriculum revision, this capstone puts into practice findings in answer to the research question, How to develop a highquality sixth-grade science curriculum to meet Next Generation Science Standards while incorporating teaching best practices? Inquiry-based learning, Systems Thinking and Culturally Sustainable Practices (CSP) were identified through research as the most effective means by which to encourage student growth and comprehension. The WEB curriculum which was created as an Environmental Education (EE) resource developed for Public School use, incorporated these principles as they are part of founding EE principles. Next Generation Science Standards were developed in 2013 and adopted by the state of Oregon in 2014, were not included in the WEB curriculum. Considering the depth of science education and the constant need for highquality resources, Environmental and Public School education would benefit from a more cohesive bond between curriculum development and classroom incorporation. By so doing will help achieve the consistent use of teaching best practices and science education relevancy. As a result of this capstone, the WEB curriculum was successfully aligned with NGSS and revised to better meet the identified best practices for the sixth grade. It stands as an example of a highquality curriculum resource for teachers in Eastern Oregon and for future curriculum revision

Learning by Asking Questions

We introduce an interactive learning framework for the development and testing of intelligent visual systems, called learning-by-asking (LBA). We explore LBA in context of the Visual Question Answering (VQA) task. LBA differs from standard VQA training in that most questions are not observed during training time, and the learner must ask questions it wants answers to. Thus, LBA more closely mimics natural learning and has the potential to be more data-efficient than the traditional VQA setting. We present a model that performs LBA on the CLEVR dataset, and show that it automatically discovers an easy-to-hard curriculum when learning interactively from an oracle. Our LBA generated data consistently matches or outperforms the CLEVR train data and is more sample efficient. We also show that our model asks questions that generalize to state-of-the-art VQA models and to novel test time distributions

Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives

This paper tackles the problem of reading comprehension over long narratives where documents easily span over thousands of tokens. We propose a curriculum learning (CL) based Pointer-Generator framework for reading/sampling over large documents, enabling diverse training of the neural model based on the notion of alternating contextual difficulty. This can be interpreted as a form of domain randomization and/or generative pretraining during training. To this end, the usage of the Pointer-Generator softens the requirement of having the answer within the context, enabling us to construct diverse training samples for learning. Additionally, we propose a new Introspective Alignment Layer (IAL), which reasons over decomposed alignments using block-based self-attention. We evaluate our proposed method on the NarrativeQA reading comprehension benchmark, achieving state-of-the-art performance, improving existing baselines by $51\%$ relative improvement on BLEU-4 and $17\%$ relative improvement on Rouge-L. Extensive ablations confirm the effectiveness of our proposed IAL and CL components.Comment: Accepted to ACL 201

'They don't use their brains what a pity': school mathematics through the eyes of the older generation

The paper considers issues in the teaching of mathematics from the viewpoint of a group of people aged 75 and over. Drawing on written accounts of their use of and attitude to mathematics, extracts are identified in which they reflect on their own experiences of learning mathematics at school or give their views on more recent mathematics education. Common themes are mental arithmetic and the use of calculators. Most respondents report positive assessments of their own mathematics education and reservations about more recent systems. Some accounts display inaccurate views of current practices in mathematics teaching and possible reasons for this are considered