Last week’s lecture on actor-network theory reminded me on my final paper written for my first course on “Technology, knowledge and learning: An introduction”. The resources and discussions in this course turned out to be a solid base for understanding the Actor-Network Theory (ANT). In fact, my final conclusion partly aimed at this theory, by saying that technology is neither fully determined nor neutral. However, this is only a scratch on the surface and this blog post is intended to support my personal reflection in the ANT and the collection of some useful material.
Actor-Network Theory in brief
ANT can be described as
[…] a vocabulary that does take the distinction between subjects and objects, the subjective and the objective, into consideration. […] an “actant”, for example, is more than a human actor. Both humans and nonhumans may be actants.
The important fact here is not that humans and nonhumans are treated symmetrically (a given in social semiotics and ecosocial dynamics) but that they are defined relationally as arguments or functors in the network, and not otherwise. This leads to a relational epistemology which rejects the naive positivist view of objects or actors as existing in themselves prior to any participation in ecosocial and semiotic networks of interactions (including the interactions by which they are observed, named, etc.).
This framework (network) is comprised of components (actors) not all of which are usually (if ever) considered by the academically oriented sociologists. The network consists not only of people and social groups, but also artifacts, devices, and entities. Engineers who elaborate a new technology as well as all those who participate at one time or anotherin it’s design, development, and diffusion constantly construct hypotheses and forms of argument that pull these participants into the field of sociological analysis. Whether they want to or not, they are transformed into sociologists, or what Callon calls engineer-sociologists. (Resource)
Given the fact, that I am fairly new to this theory, I found it very helpful to think about the following question: “Can technology force us to learn in a specific way?” (adapted from a question our professor asked us during the lecture). I said, that without the motivation to learn there is no possibility for technology to force anyone. However, reflecting on my statement now, this assumed that technology would (be) develop(ed) in a “social vacuum”, where motivation is not considered but instead would possibly change the intended purpose of a technology. What is missing here, that it can be the other way around: technology could trigger motivation as well. By saying so, it could be an actant in the network.
I still find this hard to grasps and will surely develop further on this. As a foundation, I attach my final assignment for reviewing purposes (not changes made, this is how it was handed in) and I hope some of you might find it useful.
The final assignment
The final paper was supposed to be an answer to a fictive friend, asking for advice regarding a planned university course. This covered the learning outcomes of the course, in particular (in the field of IT and learning) “identify epistemological differences and theoretical contributions, identify and critically examine current popular theories and applications in relation to major historical research traditions, demonstrate and problematize the relations between theories of learning, knowledge and technological change and contextualize technology use within different designs of learning and knowledge domains.”
I’ve heard you’re attending an International Master’s programme in IT and Learning – congratulations! I’m contacting to ask for some advice. I am a planning a similar introduction course you are attending at the moment (ours is part-time and offered in Swedish however). My problem is that my colleagues have different opinions on how we should design and plan for the course. Many think that the most important thing is that students have flexibility in time and possibility to take net-based self-study course modules. However, others think we should have more of live-streamed lectures and on-campus group work. Could you give me some pros and cons on whether to choose one or the other? Or rather, are there other aspects we should consider instead in our pedagogical approach or design of the course? We know our students are geographically spread and are working or studying part time, but we are also required to offer the students some on-campus meetings during the course.
You know I’m a novice here, but very curious about the insights into the field of IT and Learning – what are the big differences in ways of approaching designs for learning? And if you can, please update me on important movements, ideas, or technologies etc, relating to our dilemma, so that we might read about them in my work team.
thanks for your letter I hope you find my explanations useful. Your requests consists of three main themes, asking for
(1) guidance in terms of your course design that is
(2) related to contrasting design approaches for learning within the field of IT & Learning in general
(3) and to input on important (current) developments concerning your situation.
Your course is designed for Swedishspeaking parttime students, which are geographically spread however, oncampus meetings are required. The two views on the course design can be described as flexible (netbased selfstudy) and less flexible (livestream lectures and oncampus group work). Each of these designs has its assets and drawbacks. You should be aware of common mistakes when designing a distance education programme (including false expectations, missing technical support, vague requirements, etc.) and of implications of terminology when it comes to distance and online education [Garrison, R. (2009)]. Let me emphasize the learners’ needs as the primary source for course design implications. By examining these constantly the course can be tailored to individual needs, improving both the learner’s performance and the course quality. The emerging field of learning analytics facilitates this immediate feedback process and research on related phenomena such as predicting course dropouts [Baker, R., & Siemens, G. (2014)]. In your letter you are missing this point you are describing the participants in a broad manner. What are their expectations? Why do they choose your programme? How can you ensure that the expectations are met and that your course idea is communicated properly to the learner before and throughout the course?
Comparing your proposed designs, the flexible programme offers more individual freedom with the possible shortcoming of a slower socialising process due to missing facetoface meetings. In contrast, the less flexible programme limits individual freedom but attendance classes can support socialising and the groupwork process. Due to the requiredattendance classes at least a mixture of netbased and oncampus meetings is useful. There are more pros and cons to be named when evaluating design approaches. I want to focus on the aspect of socialisation. The field of IT & Learning has changed over time recently specifically targeting the learner and his/her social learning environment. It has become important to evaluate interdependencies of technology and learning understanding their (historical) development plays a crucial role in it. In the science of learning we have come a long way from more or less radical behaviorists (e.g. Watson, Skinner, Thorndike) that believed in observable behavior as the true scientific approach to research on learning, over the serious study of mental functioning triggered by the new field of cognitive science in the late 1950s (e.g. Simon, Turkle) to the importance of the social and cultural contexts of learning. In addition we may not forget the focus on the processes of knowing in the new science of learning (e.g. Piaget, Vygotsky) [Committee on Developments in the Science of Learning, 2000]. Including the work of Suchmann we reach the level of defining humanmachineinteraction and aliveness. The development from behaviorism over cognitivism to situative/pragmatistic sociohistoric views can be seen in educational technology as well. Some of the above mentioned authors state the potential of technology in the learning process. Learning theories can be related to paradigm shifts in instructional technology. Whereas CAI (computer assisted instruction) can be classified as behavioristic (how well can software support the learner to achieve specific knowledge), ITS (Intelligent Tutoring Systems) belong to the cognitivistic theory (how well does software mimic a real teacher). LogoasLatin can be arranged within the constructivistic tradition (how well can software support students in transferring knowledge) whereas CSCL (computer supported collaborative learning) is connected to situated learning (how well does the software support learners in engaging in knowledge communities) [Greeno, J. G., Collins, A. M. & Resnick, Lauren B. (1996); Koschmann, T. D. (1996)]. The major outcome of this development is that knowledge, learning and transfer are seen dissimilarly in learning theories and thus the role of technology is shifting, too. Likewise, the generations of distance education exemplify the changing roles of cognitive, social and teaching presence [Anderson, T. & Dron, J.; 2011].
Current developments in IT & Learning emphasize learnercentered learning environments and scaffolding. Learnercenteredness describes the focus on the learner’s psychological learning process or her/his participation in a sociocultural learning process [Hoadley, C. & Van Haneghan, J. (2012)]. Although the notion of scaffolding has changed over time one of it’s main implication is individual cognitive growth through a more competent tutor adapting to evolving knowledge and skills of a less competent tutee [Puntambekar, S., & Hübscher, R. (2005)]. These current developments point towards the individual learner and his/her learning needs. I am referring back to the beginning of my letter, where I emphasized these needs as well. Learning technologies become tailormade and can adapt flexibly to different users. Some examples of emerging trends in education are gaming, MOOCS and EduPunk. [Open University (2013), Liyanagunawardena, T.R., Adams, A. A. & Williams, S A. (2013), Innovation Unit (no date), Kamenetz, A. (2010)]. This broad range speaks for itself and is reflected and linked to the aspect of the crossdisciplinarity of the field [Kalz, M. and Specht, M. (2014)]. As many fields of research, IT & Learning does not withstand critique on e.g. it’s methodical capacity [Bulfin, S., Henderson, Johnson, N F, Selwyn, N. (2014)] or technological determinism [Oliver, M. (2011)]. Selwyn, N. & Fracer, K. (2013) cover the critical use of digital technology in education from a broader perspective, by analysing the stakeholders in educational technology, the use of technology in education and how it should be used for which educational causes. Gaming as a panacea has been criticized [Linderoth, J. (2012) as well as the underestimated use of procedural rhetoric [Bogost, I. (2007)].
After understanding where the learning sciences and the implications for educational design come from, we need to emphasize the evaluation of interdependencies between learning and technology. There is an ongoing discussion on the question if technology influences education or if education influences technology. In my opinion, the most critical item is avoiding technological neutralism and determinism at the same time. Technology is not just a tool that can be added to educational approaches nor does it have an undefined impact we can’t grasps. What is it then? I think as educators we are in the position to evaluate technology more critical not to give one definite answer.
Related to your letter, I can understand your request for practical and applied guidance towards solving your course design question. Yet, you are mostly taking into account the design itself and how to implement it with the help of technology. As a researcher in the field of IT & Learning let me tell you that a good course design depends on more factors than being flexible . Do new approaches in IT & Learning change the way of learning or do they try to change the learner? How do we ensure keeping the focus on the learners’ needs and on implementing the social aspect of learning with the support of technology? How do we define digital literacy and how to we implement a critical and evaluating view on educational technology?
Anderson, T. & Dron, J. (2011). Three generations of distance education pedagogy. International review of Research on Distance and Open Learning, 12(3), 8097.
Baker, R., & Siemens, G. (2014). Educational data mining and learning analytics. Cambridge Handbook of the Learning Sciences.
Bogost, I. (2007). The rhetoric of video games. In Salen, K. (Ed.), The Ecology of Games: Connecting Youth, Games, and Learning (pp. 117140). Cambridge, MA: MIT Press.
Bulfin, S., Henderson, Johnson, N F, Selwyn, N. (2014). Methodological capacity within the field of “educational technology” research: an initial investigation. British Journal of Educational Technology, 45(3), 403414.
Committee on Developments in the Science of Learning (2000). How People Learn: Brain, Mind, Experience, and School.
Garrison, R. (2009). Implications of Online Learning for the Conceptual Development and Practice of Distance Education. Journal of Distance Education, 23(2), 93104.
Greeno, J. G., Collins, A. M. & Resnick, Lauren B. (1996). Cognition and learning. In D. Berliner & R. Calfee (Eds.), Handbook of Educational Psychology (pp. 15–46). New York: Macmillan.
Hoadley, C. & Van Haneghan, J. (2012). The Learning Sciences: Where they came from and what it means for instructional designers. In R. A. Reiser & J. V. Dempsey (Eds.),
Trends and Issues in Instructional Design and Technology (3rd ed., pp. 5363). New York: Pearson.
Innovation Unit (no date). Ten ideas for 21st century education.Kalz, M. and Specht, M. (2014). Assessing the crossdisciplinarity of technologyenhanced learning with science overlay maps and diversity measures. British Journal of Educational Technology, 45(3), 415427.
Kamenetz, A. (2010). DIY U: Edupunks, edupreneurs, and the coming transformation of higher education
Koschmann, T. D. (1996). Paradigm shifts and instructional technology: An introduction. In T. D. Koschmann (Ed.), CSCL: Theory and practice of an emerging paradigm (pp. 1–23). Mahwah, NJ: Erlbaum.
Linderoth, J. (2012). Why gamers don t learn more. An ecological approach to games as learning environments. Journal of Gaming and Virtual Worlds, 4(1), 4561.
Liyanagunawardena, T.R., Adams, A. A. & Williams, S A. (2013). MOOCs: A Systematic Study of the Published Literature 20082012. International Review of Research on Distance and Open Learning, 14(3), 202227.
Oliver, M. (2011). Technological determinism in educational technology research: some alternative ways of thinking about the relationship between learning and technology. Journal of Computer Assisted Learning, 27, 373–384.
Open University (2013). Innovating pedagogy 2013 OU.
Puntambekar, S., & Hübscher, R. (2005). Tools for Scaffolding Students in a Complex Learning Environment: What Have We Gained and What Have We Missed?.Educational
Psychologist, 40(1), 112. doi:10.1207/s15326985ep4001_1
Selwyn, N. & Fracer, K. (2013). Introduction. The need for a Politics of Education and Technology. In. N. Selwyn, & K. Facer: (Eds.). The Politics of Education and Technology: Conflicts, Controversies, and Connections. New York, London: Palgrave MacMillan.
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