Curriculum Dropout

Dropout is a very effective way of regularizing neural networks. Stochastically "dropping out" units with a certain probability discourages over-specific co-adaptations of feature detectors, preventing overfitting and improving network generalization. Besides, Dropout can be interpreted as an approximate model aggregation technique, where an exponential number of smaller networks are averaged in order to get a more powerful ensemble. In this paper, we show that using a fixed dropout probability during training is a suboptimal choice. We thus propose a time scheduling for the probability of retaining neurons in the network. This induces an adaptive regularization scheme that smoothly increases the difficulty of the optimization problem. This idea of "starting easy" and adaptively increasing the difficulty of the learning problem has its roots in curriculum learning and allows one to train better models. Indeed, we prove that our optimization strategy implements a very general curriculum scheme, by gradually adding noise to both the input and intermediate feature representations within the network architecture. Experiments on seven image classification datasets and different network architectures show that our method, named Curriculum Dropout, frequently yields to better generalization and, at worst, performs just as well as the standard Dropout method.Comment: Accepted at ICCV (International Conference on Computer Vision) 201

THE INFLUENCE OF CURRICULUM AND ASSESSMENT POLICIES AND PRACTICES ON STUDENT ENGAGEMENT AND DROPOUT RISK IN SECONDARY EDUCATION IN MOGADISHU, SOMALIA

The purpose of this research was to investigate the influence of curriculum and assessment policies and practices on student engagement and dropout risk in secondary schools in Mogadishu, Somalia. To combine the data from diverse sources, the research employed a literature review strategy. Dropout risk was defined as the possibility of students leaving school before finishing their secondary education, while student engagement was described as the degree of participation, interest, and excitement that students display in their learning process. Motivation, expectations, mental health, substance abuse, parental involvement, grade retention, IQ, learning difficulties, academic achievement, curriculum quality, relevance, consistency, alignment, teacher capacity, teaching materials, assessment system, governance, and management were identified as factors influencing student engagement and dropout risk at the individual, classroom, school, and system levels. The study found that the curriculum and assessment policies and practices in Mogadishu-Somalia were low in quality, inconsistent, irrelevant, and misaligned with the national standards and the needs of the learners and society. The study recommended improving and aligning the curriculum and assessment policies and practices in secondary education in Mogadishu-Somalia with the national standards, the needs of the learners and society, and the principles of student engagement and differentiation. To achieve this goal, the study suggested developing and sharing a clear vision and goals, involving all stakeholders in the curriculum and assessment processes, adapting the curriculum and assessment to the diverse needs of students, engaging and motivating students in the curriculum and assessment, and improving teacher capacity, curriculum framework, teaching and learning materials, assessment and certification system, and governance and management of the education sector.  Article visualizations

Excitation Dropout: Encouraging Plasticity in Deep Neural Networks

We propose a guided dropout regularizer for deep networks based on the evidence of a network prediction defined as the firing of neurons in specific paths. In this work, we utilize the evidence at each neuron to determine the probability of dropout, rather than dropping out neurons uniformly at random as in standard dropout. In essence, we dropout with higher probability those neurons which contribute more to decision making at training time. This approach penalizes high saliency neurons that are most relevant for model prediction, i.e. those having stronger evidence. By dropping such high-saliency neurons, the network is forced to learn alternative paths in order to maintain loss minimization, resulting in a plasticity-like behavior, a characteristic of human brains too. We demonstrate better generalization ability, an increased utilization of network neurons, and a higher resilience to network compression using several metrics over four image/video recognition benchmarks

Measured Progress: A Report on the High School Reform Movement

New studies on the impact of the wide-ranging efforts over the past half-decade to reform the nation's public high schools have produced important -- and encouraging -- findings

Resource Usage Analysis from a Different Perspective on MOOC Dropout

We present a novel learning analytics approach, for analyzing the usage of resources in MOOCs. Our target stakeholders are the course designers who aim to evaluate their learning materials. In order to gain insight into the way educational resources are used, we view dropout behaviour in an atypical manner: Instead of using it as an indicator of failure, we use it as a mean to compute other features. For this purpose, we developed a prototype, called RUAF, that can be applied to the data format provided by FutureLearn. As a proof of concept, we perform a study by applying this tool to the interaction data of learners from four MOOCs. We also study the quality of our computations, by comparing them to existing process mining approaches. We present results that highlight patterns showing how learners use resources. We also show examples of practical conclusions a course designer may benefit from.Comment: 30 pages, 40 figure

Secondary Education in the United States: What Can Others Learn from Our Mistakes?

Secondary schools are the least successful component of the U.S. education system. Students learn considerably less than in other industrialized nations and dropout rates are significantly higher. This paper provides an explanation for this failure, describes the standards based reforms strategies that many states are implementing to attack these problems, and evaluates the success of these efforts

Does State Policy Help or Hurt the Dropout Problem in California?

Examines the scope and causes of California's dropout problem, and assesses whether some state policies unintentionally drive students out of schools. Proposes a comprehensive policy framework focused on effectively serving at-risk students

Fishing for Answers: Barriers to Secondary Agricultural English Course Adoption

Wamba (2012) said, “...literacy education plays an important role in moving people out of poverty toward greater self-sufficiency post-graduation” (p. 109). Nearly 47% of first-time California community college students are enrolled in remedial English coursework (Student Success, 2015). Further, California high school dropout rates are at 11% due to “school-related reasons…implying a lack of engagement and lack of perceived relevance” in curriculum (Gottfried & Plasman, 2017, p. 30). Literacy in our high school classrooms must be addressed. Career and Technical Education (CTE) coursework has been linked to lower dropout rates; particularly in grades 11 and 12 (Gottfried & Plasman, 2017). University of California Curriculum Integration (UCCI) was developed to help teachers facilitate creating courses which were both CTE and academically aligned for college preparation (UCCI, 2014). The Business of Sustainable Agriculture course was developed as a UCCI curriculum project to help high school seniors gain skills in writing and entrepreneurship in agriculture while meeting University of California area “b” (English) entrance requirement for 12th graders. According to the UCCI portal, only one California school is currently offering the course. The adoption of innovative, curriculum ensures high school students are prepared for life post-graduation. This research aligns with Priority 4 of the AAAE National Research Agenda - Meaningful, Engaged Learning in All Environments (Roberts, Harder, & Brashears, 2016), by examining how agricultural education programs evolve to meet student needs. Investigating barriers preventing adoption of beneficial curriculum capable of increasing literacy, preventing dropout, and producing a viable workforce will strengthen CTE programs in agriculture

The effects of increasing the standards of the high school curriculum on school dropout

This paper evaluates the effects of a high school curriculum reform that was introduced in one German state on high school dropout. The reform increased the standards of the curriculum by reducing the freedom of choice in course selection (amongst other things) resulting in an increase in the level and the weekly teaching hours in the subjects German, a foreign language, mathematics and natural sciences. Using a quasi-experimental evaluation design exploiting variation across time and states, we identify the reform effect on students’ probability to graduate from high school. The results show that high school dropout rates have increased for males and females alike. However, the effect for males vanishes two years after reform implementation, while it remains persistent for females even after three years