Constructivism

1. encourages students to take __________ and take ownership for their own learning, thereby developing their own intellectual identity
2. uses raw data and primary sources along with manipulative, __________, and physical materials
3. uses __________ terminology such as “classify,” “analyze,” “predict,” and “create” when framing tasks
4. allows student __________ to drive lessons, shifts instructional strategies, and alters content
5. inquires about students’ understandings of concepts before __________ their own understandings of those concepts
6. encourages students to engage in __________ both with the teacher and with one another
7. encourages student inquiry by asking thoughtful, __________ questions and encouraging students to ask questions of each other
8. seeks __________ of students’ initial responses
9. engages students in experiences that might engender contradictions to their initial __________ and then encourage discussion
10. asks open-ended questions
11. allows a waiting __________ after posing questions
12. provides time for students to construct relationships and create __________
13. nurtures students’ natural __________

Bonnie Nardi & Activity Theory, Situated Cognition and Distributed Cognition

She argues that Activity Theory is most comprehensive and useful for studying learning in contexts.

Do we agree or not? Why?

Jarrod Bell, Vanessa Case, Chantal Drolet, Sophie Rosso

       Nardi’s Human-Computer Interaction perspective provides insight into the differences between Situated Action Theory, Distributed Cognition and Activity Theory (AT) by explaining how educators can use technology for the benefit of the learner. We agree with Nardi that AT is the most comprehensive and best suited theory for studying people learning in contexts.

      In the Situated Action Theory, researchers consider the fluctuations of daily contexts and avoid the use of specific learning objectives because learning is seen as unintentional. These parameters present encumbrances when examining the learner in educational contexts. Indeed, investigators must record and manage minuscule fragments of interactions. Due to the improvisational and reactive targeting of the learner’s objectives within this framework, enquiries evade introspective artefacts, thus negating the student an active role in the analysis.

       Conversely, the Distributed Cognition approach facilitates detailed data collection and enables corrective actions through a co-operative, observable system; however, it fails to clearly differentiate the learner from the concepts studied. It views humans as abstract “channels”, blurring who is learning from what is being learned.

       In contrast, AT asserts that the learner is at the heart of the experience. Clearly defined activities take into account the learners’ motivations and decision-making abilities. The “learning is what you do” (Nardi, 1995) standpoint sharpens the researcher’s focus. It also allows the consideration of external dynamics (community, organization) while monitoring the learner’s control within those contexts. Furthermore, comparing learners is easier since researchers distinguish learners from the artefacts of learning contexts.

       In summary, Nardi’s AT selection enables a wide-ranging research of the interaction between the learner and technology while keeping the student at the centre of learning contexts. Furthermore, the AT approach provides manageable objectives, observable in a reasonable timeframe. For these reasons, AT is the most effective investigative approach for the study of human learning contexts.

References

Driscoll, M. (2005). Situated Cognition, Psychology of Learning for Instruction (pp. 153-182). Toronto: Pearson.

Hutchins, E. (2000). Distributed Cognition. Retrieved July 7, 2008, from IESBS Distributed

Cognition: http://eclectic.ss.uci.edu/~drwhite/Anthro179a/DistributedCognition.pdf

Nardi, B. (1998). Concepts of cognition and consciousness: four voices. Journal of Computer Documentation , 31-48.

Nardi, B. (1995). Studying context: A comparison of activity theory,situated action models, and distributed cogniton. In B. Nardi, Context and Consciousness: Activity Theory and Human-Computer Interaction (pp. 35-52). Cambridge: MIT Press.

Rogers, Y. (1997). A Brief Introduction to Distributed Cognition. Retrieved July 7, 2008, from http://www.slis.indiana.edu/faculty/yrogers/papers/dcog/dcog-brief-intro.pdf

Spasser, M. (1999). Informing information science: The case for activity theory. Journal of the American Society for Information Science , 1136-1138. Retrieved June 30, 2008 from http://dx.doi/10.1002/(SlCl)1097-4571(1999)50:12<1136AlD-ASl17>3.0.CO;2-0

Tolman, C. (1988). The basic vocabulary of Activity Theory. Activity Theory , 14-20. Retrieved June 30, 2008 from http://www.comnet.ca/~pballan/AT2.htm

Is learning online theoretically different?

Can it be encompassed under existing theories of learning?  

       Every new educational theory draws from previous learning perspectives. For instance, cognitivism promotes previous knowledge retrieval, also advocated by constructivism. Theories’ uniqueness resides in their respective definition of learning, which emerged from particular historical and sociological environments. Moreover, their inherent instructional strategies adjusted to the tools available at that time.

Online learning as a theory

       Learning online, recently associated with connectivism, warrants its own theory. The educational views it implies spring from the current societal ecology in which technological instruments prescribe a new definition of learning as well as interactive pedagogical strategies.

What is learning?

       Every respectable educational theory addresses the question “what is learning?” Online learning borrows from the constructivist approach in that learning is viewed as a continuous process occurring through interactions. Like cognitivism, learning is defined as organizing information.

       What makes the online learning outlook original is the idea that learning, with the support of technology, may happen outside the learner. Also, as part of our digital reality, what needs to be learned often shifts and becomes less important than how much and how fast one needs to learn (1).

Online instructional design

       Online instructional planning comprises new learning patterns involving decision making when confronted with diverse opinions and connecting information sources residing in data bases. Therefore educators must consider new learning challenges such as the increasing students’ responsibility over how and what they choose to learn. Learning hindrances facing future online education theorists include cultural specificities involved in learning and the quality of feedback they entail.

Conclusion

       Traditional learning theories offer valuable educational insights, but none of them is entirely adequate for the characteristics of the digital era. Conversely, online learning invites the possibility of a suitable theory for interactive technological platforms; it proffers solutions to society’s need for learner-centered (2) and networked educational experiences (1).

References

1. http://www.connectivism.ca/about.html. Retrieved July 15, 2008.
2. http://epe.lac-bac.gc.ca/100/200/300/athabasca_univ/theory_and_practice/ch2.html (CCM)
3. Connectivism (learning theory) http://en.wikipedia.org/wiki/Connectivism_(learning_theory). Retrieved July 17, 2008.
4. Siemens, G. (2005). Connectivism: Learning as Network-Creation, http://www.elearnspace.org/Articles/networks.htm. Retrieved July 17, 2008.
5. Electronic Learning, http://en.wikipedia.org/wiki/Computer-based_training#Computer-based_training. Retrieved July 15, 2008.
6. Innovating Learning, http://www.thejournal.com/the/newsletters/k12techtrends/archives/?aid=19188. Retrieved July 17, 2008.
7. Mohamed, A. (2004). Athabasca University, Theory and Practice of Online Learning, Chapter 1, Foundation of Educational Theory for Online Learning, http://cde.athabascau.ca/online_book/ch1.html, Retrieved July 15, 2008.
8. Siemens, G. (2004). Connectivism: A learning theory for the digital age.  Available online at: http://learningwithwikis.wikispaces.com/space/showimage/elearnspace.+Connectivism_+A+Learning+Theory+for+the+Digital+Age.pdf (CCM)

 Behaviourism & SCL

Introduction

       Behaviourism concentrates its attention on controlling the learning conditions in order to create observable behaviour modification. In contrast, the SCL model contends that observations of others in social settings (family, cultural environment, media diffusion) affect knowledge acquisition. Therefore, it promotes the establishment of interactive instructional environments to achieve learning outcomes.

       The two methods consider that students achieve mastery through various stages of learning and address these “steps” or “levels of processing” with “reinforcement schedules” or “scaffolding” techniques. In both cases, learning goals are predetermined and lessons either “shape” behaviour or provide “modeling” to facilitate the learner’s knowledge acquisition.

       For classical conditioning, learning happens when the individual responds to specific stimuli in a desired way. This method is well suited for tasks involving rote memorization of facts or operations (introductory learning). According to the SCL theory, learning occurs through problem-solving experiences shared with a mentor, instructor or peer. This approach lends itself to classifying, organizing or synthesizing content (advanced knowledge).

       For behaviourists, reward and punishment encourage prescribed mechanistic behaviours. SCL also uses reinforcement, but suggests that it affects the learner’s motivation rather than behaviour.

       In SCL, language is an essential transmission tool for learning. This tool not only serves to externalize the knowledge, but also as self-talk, which influences the student’s attitude. Behaviourism cannot explain how children distinguish new words without reinforcement.

       SCL assessment provides opportunities to evaluate the learning process as well as objective knowledge applications, while behaviourism usually resorts to standardized testing models. For behaviourists, self-regulated learners produce the right answer; for SCL, they monitor their own progress.

Conclusion

       In conclusion, both approaches program the learner’s knowledge acquisition and endeavour to demonstrate expertise objectively. The goal of social cognitive learning is to facilitate knowledge through communication, whereas behaviourism is about training the individual learner through successes and mistakes.

References

Standridge, M., (2002). Behaviourism. In M. Orey (Ed.), Emerging perspectives on learning, teaching, and technology. Available online: http://www.coe.uga.edu/epitt/Behaviorism.htm

Mergel, B. (1998). Design & Learning Theory. In Educational Communications and Technology, University of Saskatchewan. Retrieved from: http://www.usask.ca/education/coursework/802papers/mergel/brenda.htm, May 23, 2008. 

Boetcher, J., (1998). Pedagogy and Learning Strategies, California State University at Sacramento.

Retrieved from: http://vccslitonline.cc.va.us/usingweb/bckgrnd.htm, May 24, 2008

Stanford University, Behaviorism. First published Fri May 26, 2000; substantive revision Mon Jul 30, 2007

Retrieved from: http://plato.stanford.edu/entries/behaviorism/, May 24, 2008