Nonformal education for sustainable development: A Bangladeshi perspective

Sustainable development means ‘development that meets the needs of the present without compromising the ability of future generations to meet their needs’ (WCED, 1987:43). Meanwhile, any education worth the name is a life-long process for the betterment of human well-being. The social purposes of education are located in the long term, and it is right therefore that education should be oriented towards the construction and maintenance of a sustainable future. However, many children in developing countries get very little education. They have little chance to attend even low-quality primary schools, and dropout and failure rates are alarming; many leave semi-literate, soon to relapse into illiteracy, with disastrous consequences for their participation as individuals in the creation of a sustainable world. Moreover, the majority of those who are at school experience a traditional, formal education paradigm, aimed primarily at selecting and building human capital for economic growth. This paradigm is seen to be increasingly at odds with the concept of education for sustainability. Since the 1960s, nonformal education has comprised a wide spectrum of educational and training activities organised outside the formal school system. Innovative learning methods are aimed at the development of practical skills, including matters of health, sanitation, literacy, to be applied in real life situations. As an alternative approach to basic education, the nonformal sector as a whole thus increases pressure for change in the wider education system. Drawing on a three-year empirical study of young people at the point of transition between the nonformal and formal sectors of schooling in Bangladesh, this paper will develop a framework for analysing how the nonformal education paradigm could usefully and realistically increase practice for sustainability in the formal system

Program Predicts Time Courses of Human/Computer Interactions

CPM X is a computer program that predicts sequences of, and amounts of time taken by, routine actions performed by a skilled person performing a task. Unlike programs that simulate the interaction of the person with the task environment, CPM X predicts the time course of events as consequences of encoded constraints on human behavior. The constraints determine which cognitive and environmental processes can occur simultaneously and which have sequential dependencies. The input to CPM X comprises (1) a description of a task and strategy in a hierarchical description language and (2) a description of architectural constraints in the form of rules governing interactions of fundamental cognitive, perceptual, and motor operations. The output of CPM X is a Program Evaluation Review Technique (PERT) chart that presents a schedule of predicted cognitive, motor, and perceptual operators interacting with a task environment. The CPM X program allows direct, a priori prediction of skilled user performance on complex human-machine systems, providing a way to assess critical interfaces before they are deployed in mission contexts

The relevance of formal and nonformal primary education in relation to health, wellbeing and environmental awareness:Bangladeshi pupils’ perspectives in the rural contexts

Purpose: This article reports part of a study focusing on young people’s transition from the nonformal to the formal education sector, and explores how the experiences of children and young people in remote formal and nonformal schools affect their awareness of issues of health, well-being and the environment. One of the main objectives of Bangladeshi extensive nonformal primary education, run by nongovernmental organizations (NGOs) in parallel with the formal system, is to prepare children outside schools to enter or re-enter the formal education sector. The study addresses the issue of educational relevance from pupils’ perspectives and looking at the implications for pupil transition between these two sectors. Method: Interviews and observations of students and their classes were conducted in two contrasting rural high schools in different areas of Bangladesh, and their feeder primary schools. Results: Where formal primary graduates focus more in high school on learning from their textbooks, nonformal primary graduates aim to put their knowledge into practice in their day-to-day life on a range of critical issues. Conclusion: The results suggest an important contrast between nonformal and formal education sectors regarding students’ agency and knowledge of health and well-being, hygiene and environmental awareness in rural Bangladesh

Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization

We propose a framework for including information‐processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of rational action. Theories are specified as optimal program problems , defined by an adaptation environment, a bounded machine, and a utility function. Such theories yield different classes of explanation, depending on the extent to which they emphasize adaptation to bounds, and adaptation to some ecology that differs from the immediate local environment. We illustrate this variation with examples from three domains: visual attention in a linguistic task, manual response ordering, and reasoning. We explore the relation of this framework to existing “levels” approaches to explanation, and to other optimality‐based modeling approaches.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106911/1/tops12086.pd

Amortised experimental design and parameter estimation for user models of pointing

Funding Information: This work was supported by the Academy of Finland (Flagship programme: Finnish Center for Artifcial Intelligence FCAI) and ELISE Networks of Excellence Centres (EU Horizon:2020 grant agreement 951847) and Bitville Oy. The authors want to thank the Probabilistic Machine Learning (PML) and the User Interfaces research groups at Aalto University for fruitful discussions and feedback. Publisher Copyright: © 2023 Owner/Author. | openaire: EC/H2020/951847/EU//ELISEUser models play an important role in interaction design, supporting automation of interaction design choices. In order to do so, model parameters must be estimated from user data. While very large amounts of user data are sometimes required, recent research has shown how experiments can be designed so as to gather data and infer parameters as efficiently as possible, thereby minimising the data requirement. In the current article, we investigate a variant of these methods that amortises the computational cost of designing experiments by training a policy for choosing experimental designs with simulated participants. Our solution learns which experiments provide the most useful data for parameter estimation by interacting with in-silico agents sampled from the model space thereby using synthetic data rather than vast amounts of human data. The approach is demonstrated for three progressively complex models of pointing.Peer reviewe

Towards machines that understand people

The ability to estimate the state of a human partner is an insufficient basis on which to build cooperative agents. Also needed is an ability to predict how people adapt their behavior in response to an agent's actions. We propose a new approach based on computational rationality, which models humans based on the idea that predictions can be derived by calculating policies that are approximately optimal given human-like bounds. Computational rationality brings together reinforcement learning and cognitive modeling in pursuit of this goal, facilitating machine understanding of humans.peerReviewe

Queering disasters: on the need to account for LGBTI experiences in natural disaster contexts

This article seeks a queering of research and policy in relation to natural disasters, their human impacts, management and response. The human impacts of natural disasters vary across different social groups. We contend that one group largely absent from scholarly and policy agendas is sexual and gender minorities, or lesbian, gay, bisexual, transgender/transsexual and intersex (LGBTI) populations. To demonstrate that these minorities have particular experiences that need to be addressed, we critically review five case studies that comprise the limited scholarly and policy research on LGBTI populations in disasters to date. Building on this, we offer some specific ways forward for queer disaster research that accounts for the vulnerabilities, needs and resilient capacities of LGBTI populations. In doing so, we recognise and urge researchers, policy-makers and aid agencies to acknowledge that LGBTI populations are not homogeneous and have different needs wrought by intersections of socio-economic resources, gender, race/ethnicity, age and regional or national location.Australian Research Council-DP130102658,DP130100877 University of Western Sydne