Debunking the Myth of the Efficacy of “Push-down Academics”: How Rigid, Teacher-Centered, Academic Early Learning Environments Dis-Empower Young Children

The increased emphasis on higher academic standards in Early Childhood Education has changed the instructional landscape and developed myths of quality learning. In recent decades, pre and primary schools have begun to focus more on assessments and testing as a determinant of quality learning; this emphasis has led to a shift to “push down academics”, which refers to an increase of academic standards at a younger age (Bassok, Latham, and Rorem, 2016). The concept of “push-down academics” is contrast to the foundational components of early childhood education, which equally values socio-emotional development, academic core concepts, and natural growth (Burman, 2016; Alford, Rollins, Padron & Waxman, 2016). This paper discusses the shift in ECE educational settings from foundational components of learning to “push down academics” and reveals the commonly associated myths of the implications of “push down” academics. We also review how the implementation of “push down academics” in early childhood privileges academic concepts over other forms of learning and consequentially minimizes the importance of skills outside of the academic core (Piker & Jewkes, 2014)

Generic 3D Representation via Pose Estimation and Matching

Though a large body of computer vision research has investigated developing generic semantic representations, efforts towards developing a similar representation for 3D has been limited. In this paper, we learn a generic 3D representation through solving a set of foundational proxy 3D tasks: object-centric camera pose estimation and wide baseline feature matching. Our method is based upon the premise that by providing supervision over a set of carefully selected foundational tasks, generalization to novel tasks and abstraction capabilities can be achieved. We empirically show that the internal representation of a multi-task ConvNet trained to solve the above core problems generalizes to novel 3D tasks (e.g., scene layout estimation, object pose estimation, surface normal estimation) without the need for fine-tuning and shows traits of abstraction abilities (e.g., cross-modality pose estimation). In the context of the core supervised tasks, we demonstrate our representation achieves state-of-the-art wide baseline feature matching results without requiring apriori rectification (unlike SIFT and the majority of learned features). We also show 6DOF camera pose estimation given a pair local image patches. The accuracy of both supervised tasks come comparable to humans. Finally, we contribute a large-scale dataset composed of object-centric street view scenes along with point correspondences and camera pose information, and conclude with a discussion on the learned representation and open research questions.Comment: Published in ECCV16. See the project website http://3drepresentation.stanford.edu/ and dataset website https://github.com/amir32002/3D_Street_Vie

Leo Breiman

Statistics is a uniquely difficult field to convey to the uninitiated. It sits astride the abstract and the concrete, the theoretical and the applied. It has a mathematical flavor and yet it is not simply a branch of mathematics. Its core problems blend into those of the disciplines that probe into the nature of intelligence and thought, in particular philosophy, psychology and artificial intelligence. Debates over foundational issues have waxed and waned, but the field has not yet arrived at a single foundational perspective.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS387 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Using Preschool to Close the Socioeconomic Math Achievement Gap

Socioeconomic status (SES) heavily influences students’ academic performance, creating an achievement gap in core subjects like reading and mathematics. This thesis will describe the socioeconomic achievement gap as it relates to mathematics specifically, discuss the problem’s causes, and propose how preschool programs should be implemented more prevalently as a solution to close the gap. Children with low socioeconomic statuses enter school with lower math proficiency due to their limited math exposure in their early years and the quality of their home learning environments. This thesis will propose an expansion of preschool programs as a solution to this problem to help mediate the proficiency in foundational math concepts of low-SES students prior to school entry

Typing Context-Dependent Behavioural Variation

Context Oriented Programming (COP) concerns the ability of programs to adapt to changes in their running environment. A number of programming languages endowed with COP constructs and features have been developed. However, some foundational issues remain unclear. This paper proposes adopting static analysis techniques to reason on and predict how programs adapt their behaviour. We introduce a core functional language, ContextML, equipped with COP primitives for manipulating contexts and for programming behavioural variations. In particular, we specify the dispatching mechanism, used to select the program fragments to be executed in the current active context. Besides the dynamic semantics we present an annotated type system. It guarantees that the well-typed programs adapt to any context, i.e. the dispatching mechanism always succeeds at run-time.Comment: In Proceedings PLACES 2012, arXiv:1302.579

Child Abuse Programme Guiding Principles: Background and a More Detailed Elaboration of the Programmatic Implications of the Guiding Principles

Oak Foundation's Child Abuse Programme puts the child at the centre of all the work it supports. This statement has guided the foundation's work over the past decade, and we now feel that it is time to clarify and expand on this, with some additional details and reflection on each of the principles that help frame what we do.The work of the Child Abuse Programme is guided by six interrelated and mutually reinforcing principles.The foundational principle is that the work we support is child right's based. Thisi s a stand alone principle and one that is achieved through the integration and operation of five other core principles.The foundation's work is not operational, and so primarily these principles will be reflected through the work they support that is implemented by their partners

K6minors in 6-connected graphs of bounded tree-width

We prove that every sufficiently large 6-connected graph of bounded tree-width either has a K6 minor, or has a vertex whose deletion makes the graph planar. This is a step toward proving that the same conclusion holds for all sufficiently large 6-connected graphs. Jørgensen conjectured that it holds for all 6-connected graphs