Abstract
Ongoing policy discussions concerning the post-2015 future of the United Nations Millennium Development Goals are providing the basis for renewed efforts to understand and improve learning and literacy in a global perspective. Aiming for a pathway towards better scientific understanding, this paper asks a central question: What research would be necessary over the coming decade to realise the goal of improving learning and literacy in poor communities in low-income countries? The joint topics of learning and literacy development, and the factors which influence outcomes, are complex and intertwined – which is one reason why universal literacy has still not been achieved in spite of major investments over the years. Research will play a crucial part in addressing this challenge, and this paper proposes and reviews ten major areas of learning and literacy research. Designing and responding to an appropriate set of research priorities will be one of the crucial ways of addressing the question of how to improve learning, literacy and educational quality in the post-2015 period.
Résumé
Apprentissage et alphabétisation : un programme de recherche pour l’après-2015 – Les débats actuels sur les politiques relatives au devenir après 2015 des Objectifs du Millénaire pour le Développement fixés par les Nations Unies instaurent une base pour des efforts renouvelés en vue de cerner et d’améliorer l’apprentissage et l’alphabétisation dans une perspective mondiale. Cherchant une voie pour une meilleure appréhension scientifique, l’auteur de cet article pose une question centrale : quelle recherche serait nécessaire au cours de la prochaine décennie pour atteindre l’objectif d’améliorer l’apprentissage et l’alphabétisation dans les communautés défavorisées des pays à faibles revenus ? Les thèmes conjoints de l’apprentissage et de l’alphabétisation ainsi que les facteurs qui influencent leurs résultats sont complexes et imbriqués – et l’une des raisons pour lesquelles l’alphabétisation universelle n’est pas encore réalisée en dépit d’importants investissements depuis de nombreuses années. La recherche jouera un rôle décisif pour traiter ce défi, et cet article propose et analyse dix grands domaines scientifiques sur l’apprentissage et l’alphabétisation. La définition et le traitement d’un ensemble adéquat de priorités scientifiques seront l’une des voies déterminantes pour répondre à la question du comment améliorer l’apprentissage, l’alphabétisation et la qualité éducative après 2015.
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Notes
The six goals of the Dakar Framework for Action, to be met by 2015, were the following: (1) expansion and improvement of early childhood care; (2) compulsory and free good quality primary education; (3) equitable access for all to appropriate learning programmes; (4) a 50 per cent improvement in levels of adult literacy, especially for women; (5) elimination of gender disparities and achievement of gender equality; and (6) improved quality of measurement of learning outcomes (UNESCO 2000, pp. 15–17).
For a recent policy review of the institutional agency roles in defining and selecting skills as part of EFA, MDGs and the Global Monitoring Reports, see King (2011).
For the current 2015 fiscal year, low-income economies are defined as those with a per capita gross national income (GNI) of USD1,045 or less in 2013, calculated using the World Bank Atlas method, For a list of low-income countries, see the World Bank indicators at http://data.worldbank.org/about/country-and-lending-groups#Low_income [accessed 15 August 2014].
Learned helplessness, a term coined by American psychologist Martin E.P. Seligman in the 1970s, refers to “a mental state in which an organism forced to bear aversive stimuli, or stimuli that are painful or otherwise unpleasant, becomes unable or unwilling to avoid subsequent encounters with those stimuli, even if they are ‘escapable’, presumably because it has learned that it cannot control the situation” (Nolen 2014).
For a discussion of Johann Friedrich Herbart (1776–1841) and the origins of learning theory, see an historical overview of behaviourism, gestalt and cognitive psychology in de Corte (2010). By contrast, economists tend to view learning as a phenomenon reflected in an individual’s rational choices, which change in response to a product’s perceived value, increases or decreases in the market price or availability of alternatives.
Probably the best-known and most researched area of synergy is between early childhood development (ECD) programmes and primary schooling – this approach is now gaining further attention in the post-2015 discussions.
For example, see Babson (2010), and Chick (2002) on the changes in language attitudes in South Africa. There is also growing evidence in numerous countries on the role of English as a second language even in rural areas where its use may be of little value. Naturally, there is much variation in language attitudes, and this is changing with the increased internal and external mobility of speakers of different ethno-linguistic groups.
When some refer to “lifespan” approaches in literacy development, there are often several implications. One of these, and central to the present paper, is that literacy begins early and is built upon from early childhood through adulthood. A second view is that literacy is itself a function of recursive intergenerational learning: that parents, siblings and even the home literacy environment are essential parts of children’s literacy learning. This is no doubt true as well, and recent efforts to measure home literacy environments support this view (Dowd et al. 2013). A third view is that literacy may be learned at some stage of development, but may not be retained due to lack of sufficient practice – that is, the problem of “literacy retention” – as I have described elsewhere (Wagner 1998). While the latter two issues are beyond the scope of this article, they remain important concerns of literacy across the lifespan.
See Jaruzelski and Dehoff (2010). A much smaller share is spent by national ministries of education in low-income countries.
See also the work of UNESCO’s Literacy Assessment and Monitoring Programme (LAMP), which has been trying to improve data collection on literacy rates (UIS 2009).
Recent work has emphasised the importance of more timely (faster) data gathering so that early childhood development (ECD) programmes can be optimised quickly enough to make a difference while children are still in ECD programmes (Wagner 2011a). This is not to the exclusion of other types of research, such as longitudinal studies, which are also important in the longer run.
Research has begun to appear based on Early Grade Reading Assessment (EGRA) and EGRA-related tools for assessing and supporting L1 and L2 reading acquisition in various countries, including Vietnam, Bangladesh, Thailand and India (see Pinnock 2011). Of course, not all language issues concern LOI; in some countries (especially in the OECD) multi-lingualism is a direct policy goal, which necessarily involves other factors in language and literacy learning.
See the work on the Early Grade Reading (and Mathematics) Assessments (EGRA and EGMA) (Gove and Wetterberg 2011) and smaller quicker cheaper (SQC) approaches to assessments (Wagner 2011b), as well as the work of Pratham (an Indian NGO) and Uwezo (a Kenyan NGO), both of which have developed their own localised reading and maths assessments.
Some recent evidence suggests that reading instruction is quite limited in poor schools in Kenya (Piper and Mugenda 2012).
One example is India’s “bridge” programme in Andhra Pradesh state; see Wagner et al. (2010).
For one early and interesting study on the impact of literacy on productivity in agriculture, see Jamison and Moock (1984).
See Banerjee and Duflo (2011, p. 88) on a study in several countries that showed how parental beliefs of the expected incomes of their children’s schooling affected their attitudes about keeping their children in school. In countries like the U.S., the publication of school (and even classroom) outcomes is becoming more commonplace, especially with the rise of ‘choice’ and ‘charters’ in American education.
See, for example, the work of the Learning Metrics Task Force (2013).
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