Technical Assistance for Expanded Learning Opportunities in California

The After School Division (ASD) of the California Department of Education in collaboration with Public Profit, has released Technical Assistance for Expanded Learning Opportunities in California. This report shares high-level information about the availability of technical assistance (TA) by region, strategy, and links to Quality Standards for Expanded Learning. Regional Profiles provide at-a-glance information about providers in each of California's 11 regions.This report will help to inform the ongoing conversations about how to support high quality Expanded Learning Opportunities in California for all youth. California is a national leader in Expanded Learning, both for the breadth of its publicly funded Expanded Learning programs and for its growing focus on quality. THe ASD is further enhancing its supports for program quality through the System of Support, including fuding for TA. Understanding the current TA landscape enahnces the ASD's ability to make strategic investments to support Expanded Learning Opportunities

Perancangan User Interface E-learning Berbasis Web

E-Learning steadily growing and the ongoing struggle to convince the skeptics of the potential of e-Learning and online virtual classrooms, quality design is the foundation for a successful distance learning program. The design of the instruction and the design of the user interface are critical elements in providing quality education with a virtual, e-Learning model. This White Paper will focus on the design of the e-Learning user interface (UI). This paper provides examples of user interface design from e-Learning prototype

Towards a Lightweight Approach for Modding Serious Educational Games: Assisting Novice Designers

Serious educational games (SEGs) are a growing segment of the education community’s pedagogical toolbox. Effectively creating such games remains challenging, as teachers and industry trainers are content experts; typically they are not game designers with the theoretical knowledge and practical experience needed to create a quality SEG. Here, a lightweight approach to interactively explore and modify existing SEGs is introduced, a toll that can be broadly adopted by educators for pedagogically sound SEGs. Novice game designers can rapidly explore the educational and traditional elements of a game, with a stress on tracking the SEG learning objectives, as well as allowing for reviewing and altering a variety of graphic and audio game elements

Abduction-Based Explanations for Machine Learning Models

The growing range of applications of Machine Learning (ML) in a multitude of settings motivates the ability of computing small explanations for predictions made. Small explanations are generally accepted as easier for human decision makers to understand. Most earlier work on computing explanations is based on heuristic approaches, providing no guarantees of quality, in terms of how close such solutions are from cardinality- or subset-minimal explanations. This paper develops a constraint-agnostic solution for computing explanations for any ML model. The proposed solution exploits abductive reasoning, and imposes the requirement that the ML model can be represented as sets of constraints using some target constraint reasoning system for which the decision problem can be answered with some oracle. The experimental results, obtained on well-known datasets, validate the scalability of the proposed approach as well as the quality of the computed solutions

A Student-Centered Effective Learning Framework For Quality Education

Effective teaching and learning process is essential for providing quality education at all levels.  This research addresses growing quality concerns of Pakistan’s educational sector and makes a case for shifting the focus from teacher-centered to student-centered learning process for quality educational experience. A conceptual framework for effective learning is presented based upon studies of educational psychology, cognitive learning and personal teaching experience. The framework combines student-centered teaching strategies with classroom assessment techniques to create a dynamic and interactive classroom environment. To create an organizational context conducive for effective learning the framework assigns roles and responsibilities to all the stakeholders and requires their active participation and collaboratio

Unsupervised Learning with Self-Organizing Spiking Neural Networks

We present a system comprising a hybridization of self-organized map (SOM) properties with spiking neural networks (SNNs) that retain many of the features of SOMs. Networks are trained in an unsupervised manner to learn a self-organized lattice of filters via excitatory-inhibitory interactions among populations of neurons. We develop and test various inhibition strategies, such as growing with inter-neuron distance and two distinct levels of inhibition. The quality of the unsupervised learning algorithm is evaluated using examples with known labels. Several biologically-inspired classification tools are proposed and compared, including population-level confidence rating, and n-grams using spike motif algorithm. Using the optimal choice of parameters, our approach produces improvements over state-of-art spiking neural networks

Rethinking university assessment

Developments in globalisation and new technologies are making significant impacts in higher education. Universities in a global market are increasingly concerned to reorient their degree programmes to meet the vocational needs of the Knowledge Economy. A growing adoption of technology enhanced learning, through blended and networked learning, has the potential to transform higher education practice – but assessment methods have been slow to change. This paper argues the case for universities to align assessment methods to meet the needs of 21st Century knowledge workers. It identifies skills and dispositions associated with graduate occupations in the Knowledge Economy, informing a new conceptual model for assessment. Radical recommendations are made to faculty staff and university policymakers: instead of centring assessment on the personal, academic achievements of individuals at the end of a degree course, the focus should instead be on the quality of the collective, applied achievements of students operating in project teams