En este articulo Terry Anderson presenta una revision de teorias tradicionales y emergentes de aprendizaje y diseño instruccional que pueden ser de ayuda para el diseño efectivo de contextos de aprendizaje con nuevas tecnologias.

I was drawn to thinking about the technologies in the context of Moore's (1989) description of educational communications as being made up of student-student, student-content, and student-teacher interactions. We had already written (Anderson & Garrison, 1998) about the other three possible interactions — teacher-content, teacher-teacher, and content-content — but continued to focus on the ones most relevant to a learning centric view, those that involved students. I created the diagram shown in Figure 2.1 and then had an insight: perhaps these three student interactions were more or less equivalent. Creating very high-quality levels of any one type of interaction would be sufficient to create a high-quality learning experience. If this was the case, the other two interactions could then be reduced or even eliminated, with little or no impact on learning outcomes or learner attitudes. If true, this “learning equivalency theory” could be used to rationalize expenditures in one area, yet allow for time and money savings in the other two. I further speculated that “high levels of more than one of these three modes will likely provide a more satisfying educational experience, though these experiences may not be as cost- or time-effective as less interactive learning sequences” (Anderson, 2003).


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(...) Bob Bernard (Bernard et al., 2009) and his colleagues at Concordia University, had thought deeper than I, and had established a set of protocols that allowed them to conduct a meta-analysis of distance education studies designed to validate my contentions. As usual, the number of control group studies in distance education is limited and thus so are the results. However, Bernard et al. (2009) concluded that “when the actual categories of strength were investigated through ANOVA, we found strong support for Anderson’s hypothesis about achievement and less support for his hypothesis concerning attitudes.”
Thus, my “equivalency theory” gained some empirical support, and from e-mails I have received from distance educators in a variety of countries, I know the theory has helped both researchers to research nd practitioners to design and deliver cost-efficient and learning-effective interventions.

Teorias de aprendizaje:


Constructivismo

Constructivism has long philosophical and pedagogical roots and has been associated with the works of John Dewey, George Mead, and Jean Piaget. Like many popular theories, it has been defined and characterized by many — often with little consistency among authors. However, all forms of constructivism share an understanding that
individuals construct knowledge that is dependent upon their individual and collective understandings, backgrounds, and proclivities. Debate arises, however, over the degree to which individuals hold common understandings and if these understandings are rooted in any single form of externally defined and objective reality (Kanuka & Anderson, 1999). As much as constructivism is touted as driving the current educational discussion, it should be noted that it is a philosophy of learning and not one of teaching. Despite this incongruence, many authors have extracted tenants of constructivist learning and from them developed principles or guidelines for the design of learning contexts and activities. Among these are: that active engagement by the learners is critically important, and that multiple perspectives and sustained dialogue lead to effective learning. Constructivists also stress the contextual nature of learning and argue that learning happens most effectively when the task and context are authentic and hold meaning for the learners.

Teoria de complejidad

Implications of complexity theory for learning and for education operate on at least two levels. At the level of the individual learner, complexity theory, like constructivist theory, supports the learner’s acquisition of skills and power such that he or she can articulate and achieve personal learning goals (chapters 6 and 9). By noting the presence of agents and structures that both support and impede the emergence of effective adaptive behaviour, individual learners are better able to influence and indeed survive in often threatening and always complex learning environments.
At the level of organization of either formal or informal learning, complexity theory highlights the social structures that we create to manage that learning. When these management functions begin to inhibit the emergence of positive adaptive behaviour or give birth and sustain behaviours that are not conducive to deep learning, we can expect negative results. Organizational structures should help us to surf at the “edge of chaos,” not function to eliminate or constrain the creative potential of actors engaged at this juncture. Further, this understanding can guide us to create and manage these complex environments not with a goal of controlling or even completely understanding learning, but with a goal of creating systems in which learning emerges rapidly and profoundly. Complexity theory also encourages us to think of learning contexts (classrooms, online learning cohorts, etc.) as entities themselves. These entities can be healthy or sick; emerging, growing, or dying. By thinking at the systems level, reformers search for interventions that promote healthy adaptation and the emergence of cultures, tools, and languages that produce healthy human beings.
Finally, complexity theory helps us to understand and work with the inevitable unanticipated events that emerge when disruptive technologies are used in once stable systems (Christensen, 1997). Learning to surf this wave of equal opportunity and danger (and do it masterfully) becomes the goal of educational change agents.

Con la apariencia de la Web han emergido nuevas teorias que intentan sacar provecho de este nuevo contexto de enseñanza y aprendizaje.

En el articulo introductorio a la edicion especial de Journal of Interactive Media in Education dedicado a los usos de la Web semantica en la educacion, Anderson y Whitelock (2004) han formulado tres caracteristicas de la Web que definen su importancia en la ensenañza y el aprendizaje. La primera es su capacidad de comunicacion a bajo coste. Esta comunicacion puede ser sincrona o asincrona, expresarse en texto, voz, video y otras formas de interaccion, y sus artefactos pueden ser almacenados, indizados, recuperados, buscados y organizados. La comunicacion puede ser uno a uno, uno a muchos, o muchos a muchos, sin grandes diferencias de costes entre las modalidades. Entonces, los educadores han pasado de un mundo en el que la comunicacion fue expensiva, restringida geograficamente (muchas veces limitada a los individuos reunidos en la misma aula), y privilegiada (limitada a los que tienen acceso a los medios de produccion). Ademas, la comunicacion en la red permite el acceso a los individuos con varias discapacidades. El surgimiento del software social permite a los estudiantes compartir dudas, ideas y recursos, creando nuevas oportunidades de aprendizaje organizado por los alumnos, y formar comunidades para varias formas de aprendizaje colaborativo, informal y de toda la vida.
La segunda caracteristica es que la web crea el contexto que nos lleva desde la escasez de la informacion hacia su abundancia. La web permite el acceso al contenido educativo en varios formatos y en muchos casos enriquecidos por mulimedia. Ademas, permite a los educadores y a los estudiantes crear su propio contenido y editar y enriquecer las producciones dd los otros.
La tercera caracteristica es la web semantica con sus agentes autonomos que pueden recoger, agregar, sintetizar, y filtrar la web en busca del contenido relevante para individuos o grupos de estudiantes y docentes.

La pedagogia de la proximidad

Es la propuesta de Mejias (2005), en la que la interaccion, la colaboracion, y el aprendizaje on line no son mejores ni peores que las interacciones con la gente que esta cerca de nosotros. El aprendizaje en linea no significa abandonar los espacios fisicos, sino sirve para facilitar, documentar y profundizar las relaciones del mundo real. Mejias argumenta que no la proximidad de las relaciones cara a cara no es la unica oportunidad para la ensenanza y el aprendizaje, y que mas bien necesitamos esas formas de reflexion especificas para la experiencia en linea y que no se pueden realizar en otro contexto no mediado. Aunque las redes digitales no han terminado con la distancia, nuestra experiencia de tiempo y espacio fue alterada por la reduccion de barreras de ambos. Segun Mejias necesitamos aplicaciones que combinan ambas formas de interaccion y los estudiantes y los docentes necesitan nuevas competencias para actuar efectivamente en ambos contextos y saber pasar rapidamente de uno al otro.

Heutagogia

La heutagogia ve el alumno como el que controla y desarrolla su propio aprendizaje. El control por parte del estudiante es visto como un factor critico en el mundo de hoy, caracterizado por los rapidos cambios economicos y culturales. Segun Hase y Kenyon dada la rapidez de innovacion y la estructura cambiante de comunidades y empresas en el futuro la competencia fundamental sera "saber aprender". Este futuro requiere que la educacion va mas alla de ensenar y verificar las competencias, hacia facilitar y soportar al alumno en su busca de capacidad mas que competencia. Capacidad significa entre otras cosas ser capaz de aprender en nuevos y desconocidos contextos. El diseno instruccional deja de centarase en la difusion del contenido existente y es visto como exploracion de problemas relevantes para la vida de los estudiantes. El rol del docente es el de faciliyador y guia del estudiante quein utiliza una variedad de recursos tradicionales y virtuales para resolver problemas y buscar entendimiento y capacidad personal. Heutagogia pone enfasis en la eficaciacia en el uso de las herramientas y los fuentes de informacion accesibles en la web.

Conectivismo

The most recent network-centric theory was first developed by George Siemens, who coined the term connectivism and laid out a number of principles that define connected learning. Siemens argues that “we derive our competence from forming connections” and that our “capacity to know more is more critical than what is currently known” (Siemens, 2005). The metaphor of the network whose nodes consist of learning resources, machines that both store and generate information, and people, dominates connectivist learning. Learning occurs as individuals discover and build connections between nodes. Learning environments are thus created and used by individuals as they access information, process, filter, recommend, and apply that information with the aide of machines, peers, and experts in their learning networks. In the process of learning, they expand their own learning networks by creating useful and personalized knowledge and connecting it to the ideas and artifacts of others in their networks. Being able to see, navigate, and create connections between nodes becomes the goal of connectivist learning. Rather than learning facts and concepts, connectivism stresses learning how to create paths to knowledge when it is needed. Siemens also argues that knowledge and indeed learning itself can exist outside of a human being — in the databases, devices, tools, and communities within which a learner acts. Additionally, connectivism sees the need for formal education to expand beyond classrooms and bounded learning management systems to embrace and to become involved with the informal. As Downes (2006) notes, “Learning … occurs in communities, where the practice of learning is the participation in the community. A learning activity is, in essence, a conversation undertaken between the learner and other members of the community. This conversation, in the Web 2.0 era, consists not only of words but of images, video, multimedia and more.” Though often the topic of edublogger conversation, connectivism has yet to become widely accepted as the learning theory for the digital era as envisioned by Siemens and Downes. It has been criticized by Kerr (2007) for offering nothing new in learning theory that is not accounted for in earlier works (notably complexity theory and constructivism). Connectivism also seems to have trouble connecting to formal education. Kop and Hill (2008) note the lack of a substantive role for a teacher in connectivist theory and the requirements placed on the learner (in common with heutagogy) to be capable of and motivated to engage in very self-directed learning. Finally, Verhagen (2006) argues that connectivism is more a theory of curriculum (specifying what the goal of education should be and the way students should learn in that curriculum) than a theory of learning.

Obviously a goal of connectivist learning is to create new connections, and the classroom, or any bounded formal education system, is a relatively small context in which to build these connections. Connectivist theorists are interested in both allowing and stimulating learners to create new learning connections. In the process, learners increase the pools of expertise and resources they can draw from and thus increase their own social capital, as they become valued resources for others. Our own modest contribution to this need for expanded interactions within formal education has been to differentiate three important but substantively different contexts in which connectivist learning is employed (Dron & Anderson, 2007).
The first of these learning contexts is the familiar group. Groups (often referred to as “classes” in formal education) are secure places where students aggregate (in classroom or online) and proceed through a series of independent and collaborative learning activities. Groups tend to be closed environments, have strong leadership from a teacher or group owner, and (in formal education) be temporally bounded by an academic term. These synchronized activities result in learners supporting each other, and levels of trust can be built such that learners actively engage with and critique each other. In well-organized groups, considerable social, cognitive, and teaching presence is developed to create a community of inquiry (Garrison & Anderson, 2003). However, groups are also noted for the development of hidden curricula, constrictive and occasionally coercive acts, group think, and teacher dependency (Downes, 2006).

El termino fue inventado por George Siemens. Siemens argumenta que la gente deriva su competencia del proceso de formacion de conexiones y que la capacidad de saber mas es mas critica que lo que actualmente se sabe. La metafora de la red cuyos nodos consisten de recursos de aprendizaje, maquinas que almacenan y genran informacion, y personas, domina el aprendizaje conectivista. El aprendizaje surge cuando las personas descubren y crean conexiones entre los nodos. Los entornos de aprendizaje son entonces creados en el proceso de acceder, filtrar, recomendar, y aplicar la informacion con la ayuda de maquinas, colegas y expertos que forman sus redes de aprendizaje. En este proceso, expanden sus redes de aprendizaje creando conocimiento personalizado y conectandolo a las ideas y loa artefactos creados por otros miembros de su red. Segun Siemens el conocimiento y el aprendizaje puede existir fuera de una persona - en bases de datos, herramientas, y comunidades en los que atuan los estudiantes. Ademas conectivismo considera necesario que la educacion formal se extiende fuera de clase y LMS uniendose con el informal. El aprendizaje ocurre en comunidades, donde la practica de aprendizaje es la participacion en la comunidad. Esta conversacion consiste no solo de palabras, sino deimagenes, videos, multimedios etc.

La meta del aprendizaje conectivista es crear nuevas conexiones, y la clase o cialquier otro sistema de educacion formal es un contexto demasiado pequeno para hacerlo. En el proceso de crear conexiones, los estudiantes incrementan su base de recursos y por consiguiente su capital social, convirtiendose en recorsos de valor para otros. Dron y Anderson han determinado tres diferentes contextos en los que el aprendizaje conectivista esta utilizado:
El primer contexto es el grupo, correspondiente a "clase" de la educacion formal. Los grupos son lugares seguros en los cuales los alumnos se inscriben y alli realizan sus actividades de aprendizaje individuales o colaborativas. Los grupos tienden a ser entornos cerrados, con un lider como profesor o creador de grupo y (en la educacion formal) temporalmente restringidos.
El segundo contexto es la red. Actividades de aprendizaje en red permiten la expansion fuera de LMS permitinedo tanto los estudiantes matriculizados como el publico general a conectarse para nuevas oportunidades de estudio. La membresia en la red es mucho mas fluida que en el grupo, el liderazgo es mas bien emergente que impuesto, y las redes se extienden o contraen facilmente cuando sus miembros las consideran mas o menos utiles para resolver un problema particular. Las redes no son tan limitadas en tiempo y pueden existir despues del fin de la carrera formal.
El tercer contexto es el colectivo. Aprendizaje en colectivos requiere agregar y sintetizar miles de miles de actividades que se realizan en la web y aplicar el conocimiento obtenido de esas agregaciones a un problema concreto. Es lo que hacemos en los servicios web 2.0.

Thus, in our courses we are developing a second form of aggregation based on networks. Networked learning activities that expand connectivity beyond the Learning Management System (LMS) to allow both registered students, alumni, and the general public to engage in creating networked learning opportunities (Anderson, 2005). Network membership is much more fluid than that of groups, leadership is emergent rather than imposed, and networks easily expand and contract as learners find them of more or less use in solving particular problems. Networks are also less temporally bonded and may continue to exist long after formal study terminates.
The third aggregation we have referred to as “collectives.” Learning in collectives involves aggregating and synthesizing the myriad activities that go on over the Net and applying knowledge gained by these aggregations to particular problems. For example, searching very large aggregations of resources, such as found in Google, YouTube, or del.icio.us, and filtering them for perceived value or use allows us to selectively mine the activities of thousands or tens of thousands of individuals. These filterings can be socially magnified through collaborative resource tagging services such as citeulike.org and diig.com. Collective activities carry with them the potential for contagion and privacy invasion, but at the same time they allow us to benefit from the traces, tracks, recommendations, and activities of others, thereby creating paths which allow us connect more easily to valued human and digital learning resources. We have expanded this discussion elsewhere to explore learning activities best suited for the “Aggregations of the Many” (Dron & Anderson, 2007).

Recursos mencionados en el texto:
Anderson, T., & Garrison, D.R. (1998). Learning in a networked world: New roles and responsibilities. In C. Gibson (Ed.), Distance Learners in Higher Education (pp. 97–112). Madison, WI: Atwood Publishing.
Anderson, T. (2003). Getting the mix right: An updated and theoretical rationale for interaction. International Review of Research in Open and Distance Learning, 4(2). Retrieved December 2007, from http://www.irrodl.org/index.php/irrodl/article/view/149/708
Anderson, T., & Whitelock, D. (2004). The educational semantic web: Visioning and practicing the future of education. Journal of Interactive Media in Education, 1. Retrieved December 2007, from http://www-jime.open.ac.uk/2004/1
Bernard, R.M., Abrami, P.C., Borokhovski, E., Wade, C.A., Tamim, R.M., Surkes, M.A., & Bethel, E.C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243–1289.
Downes, S. (2006). Learning networks and connective knowledge. Posted on IT Forum (paper 92). Retrieved November, 2008, from http://it.coe.uga.edu/itforum/paper92/paper92.html
Dron, J., & Anderson, T. (2007). Collectives, networks and groups in social software for e-learning. Paper presented at the World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, Quebec. Retrieved February 2008, from www.editlib.org/index.cfm/files/paper_26726.pdf
Garrison, D.R., & Anderson, T. (2003). E-Learning in the 21st Century. London: Routledge.
Hase, S., & Kenyon, C. (2000). From Andragogy to Heutagogy. UltiBase. Retrieved 28 December 2005, from ultibase.rmit.edu.au/Articles/dec00/hase2.htm
Hase, S., & Kenyon, C. (2007). Heutagogy: A child of complexity theory. Complicity: An International Journal of Complexity and Education, 4(1), 111–118. Retrieved March 2008, from www.complexityandeducation.ualberta.ca/COMPLICITY4/documents/Complicity_41k_HaseKenyon.pdf
Kerr, B. (2007). A Challenge to Connectivism. Transcript of Keynote Speech. Paper presented at the Online Connectivism Conference. Retrieved November, 2008, from http://ltc.umanitoba.ca/wiki/index.php?title=Kerr_Presentation
Kop, R., & Hill, A. (2008). Connectivism: Learning theory of the future or vestige of the past? The International Review of Research in Open and Distance Learning, 9(3). Retrieved November, 2008, from http://www.irrodl.org/index.php/irrodl/article/view/523/1103
Moore, M. (1989). Three types of interaction. American Journal of Distance Education, 3(2), 1–6.
Verhagen, P. (2006). Connectivism: A new learning theory? SurfSpace. Retrieved November, 2008, from http://www.surfspace.nl/nl/Redactieomgeving/Publicaties/Documents/Connectivism%20a%20new%20theory.pdf