http://sbreeden71.blogspot.com/
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Monday, May 10, 2010
8845 MOD 5 Blog
Assumptions
The assumptions that educators have a positive attitude toward experimenting with new technologies in the workplace and that there exist educators who have low self-efficacy in experimenting with new technologies are safe in my school district. The phenomenon where a teacher has an interactive whiteboard in his/her classroom but underutilizes it is an all too common happenstance therein. The following is a description of a case where I intervened.
The mathematics teacher was deeply ensconced in the traditional ethic of ‘drill for skill.’ His only use of the whiteboard was to link to TeacherTube. The selections never seemed to mesh with the ‘drill for skill’ content, audio and video was always poor, he did not know how to maximize the image, and the class would inevitably and quickly lose interest. I had no choice but to talk to the teacher.
In retrospect, without familiarity with Keller’s ARCS model at the time, my initiatives reflected all its elements. My first move was to engage the teacher in his room during his free prep period (I had his Attention). As per our assumptions, he was a willing experimenter with low self-efficacy in the use of whiteboard technology.
During the first session we talked about the importance of exploiting the potential of the technology for purposes of effective teaching and learning (I made the technology Relevant). Subsequent sessions had the teacher practice with hands-on functioning. Technology-based lessons were modeled (we built Confidence). Finally, he taught a technology-based lesson to his classes (Satisfaction was realized).
While many things can be assumed regarding technology in education, many others cannot. One such thing that cannot be assumed is that technology in the classroom is an automatic cause for learning. To those that would make the assumption, I direct them to the first three letters in the word.
Driscoll, M. P. (2005). Psychology of learning for instruction (3rd ed.). Boston: Pearson Education, Inc.
The assumptions that educators have a positive attitude toward experimenting with new technologies in the workplace and that there exist educators who have low self-efficacy in experimenting with new technologies are safe in my school district. The phenomenon where a teacher has an interactive whiteboard in his/her classroom but underutilizes it is an all too common happenstance therein. The following is a description of a case where I intervened.
The mathematics teacher was deeply ensconced in the traditional ethic of ‘drill for skill.’ His only use of the whiteboard was to link to TeacherTube. The selections never seemed to mesh with the ‘drill for skill’ content, audio and video was always poor, he did not know how to maximize the image, and the class would inevitably and quickly lose interest. I had no choice but to talk to the teacher.
In retrospect, without familiarity with Keller’s ARCS model at the time, my initiatives reflected all its elements. My first move was to engage the teacher in his room during his free prep period (I had his Attention). As per our assumptions, he was a willing experimenter with low self-efficacy in the use of whiteboard technology.
During the first session we talked about the importance of exploiting the potential of the technology for purposes of effective teaching and learning (I made the technology Relevant). Subsequent sessions had the teacher practice with hands-on functioning. Technology-based lessons were modeled (we built Confidence). Finally, he taught a technology-based lesson to his classes (Satisfaction was realized).
While many things can be assumed regarding technology in education, many others cannot. One such thing that cannot be assumed is that technology in the classroom is an automatic cause for learning. To those that would make the assumption, I direct them to the first three letters in the word.
Driscoll, M. P. (2005). Psychology of learning for instruction (3rd ed.). Boston: Pearson Education, Inc.
Tuesday, April 27, 2010
8845 MOD 4 Post Reflection - Connectivism
A Thousand Words
A picture is worth a thousand words, someone once expressed. So is a mind map. My own mind map on connectivist learning (previous blog link) is no exception. It very neatly explains how my network has changed the way I learn, articulates important digital tools that best facilitate this learning, and implies how I learn new knowledge when I have questions. Ohh yes it doeoeoess. . . .
It, at once, models Siemens’ notion that in order to best come to grips with the exponential growth of new information, connecting to and through networks is crucial. It illustrates his Three Broad Stages of Connectivist Learning Theory, i.e. First level: Neural Networking, Second Level: Conceptual Networking, and Third Level: Social Networking. It further supports his insistence that knowledge is networked, and that learning is the act of creating and navigating those networks. (Laureate, 2008)
My mind map is a resounding acknowledgment of these, and in this manner all three stages described are prominent. I use the computer as an analog for the brain (neural network administrator), and highlight the role that concept (knowledge) plays in networked learning. Therein also, I represent the social network as an additional node for conceptual input and output. “Connectivist learning requires mashups, or taking content and ideas that others have produced and reusing and repurposing them in different contexts.” (Laureate, 2008)
‘To know’ is no longer a result of massive personal memorization of detail; it is instead, a confident exploitation of content rich networks. Connecting effectively to these then becomes the critical element. In this regard, I could have cited the thousand words in my mind map.
Laureate Education, Inc. (Producer). (2008). Connectivism learning theory featuring Dr. George Siemens.
A picture is worth a thousand words, someone once expressed. So is a mind map. My own mind map on connectivist learning (previous blog link) is no exception. It very neatly explains how my network has changed the way I learn, articulates important digital tools that best facilitate this learning, and implies how I learn new knowledge when I have questions. Ohh yes it doeoeoess. . . .
It, at once, models Siemens’ notion that in order to best come to grips with the exponential growth of new information, connecting to and through networks is crucial. It illustrates his Three Broad Stages of Connectivist Learning Theory, i.e. First level: Neural Networking, Second Level: Conceptual Networking, and Third Level: Social Networking. It further supports his insistence that knowledge is networked, and that learning is the act of creating and navigating those networks. (Laureate, 2008)
My mind map is a resounding acknowledgment of these, and in this manner all three stages described are prominent. I use the computer as an analog for the brain (neural network administrator), and highlight the role that concept (knowledge) plays in networked learning. Therein also, I represent the social network as an additional node for conceptual input and output. “Connectivist learning requires mashups, or taking content and ideas that others have produced and reusing and repurposing them in different contexts.” (Laureate, 2008)
‘To know’ is no longer a result of massive personal memorization of detail; it is instead, a confident exploitation of content rich networks. Connecting effectively to these then becomes the critical element. In this regard, I could have cited the thousand words in my mind map.
Laureate Education, Inc. (Producer). (2008). Connectivism learning theory featuring Dr. George Siemens.
Monday, April 12, 2010
MOD 3 Blog - 8845
Instinct
Instinct is defined as an innate tendency or response of a given species to act in ways that are essential to its existence, development, and preservation. This definition implies that causes that affect these latter can be manipulated by external forces. During the agricultural age, families instinctually worked the land collaboratively for their existence and preservation. Before then, collaborative hunting and gathering within larger communities for the same purposes was prevalent.
Collaborations during the agricultural age did not, however, preclude the instinctual self-interests of competing farmers or plundering desperados. Nor were the hunters and gatherers safe from warring communities whose intent was territorial domination. In this manner, it can be seen that the decision to operate alone or cooperatively is a function of one’s perception of existence and self-preservation at the moment. Instinctually, one is able to do either. Moreover, the previous accounts indicate that both can, and do coexist. The question then becomes, which instinct dominates the moment?
At the onset of the industrial age, reliance on family collaboration was mitigated by a redefined need for existence and preservation. This new perspective was borne of the necessity to leave the farms to relocate to industrial centers, and then to separate from the wife and children for long hours to go earn a living in factories. This emphasis persists in today’s classrooms, where the moment is dominated by self-reliant traditional instruction.
While, like in society at-large, there is growing acceptance of the need for collaborative means, different from larger society, there exists a dearth of the trust necessary to facilitate cooperative learning in education. The macro-society appears to be modeling a trust in technologies that have realized such latter-day collaborative accomplishments as the Genome Project, CERN Particle Accelerator, and development of the Big Bang Theory, solutions that could not have been realized otherwise. In this regard, a teacher too, must trust in the virtues of the educational technologies that would leverage the power of constructivist collaboration in education. Therein, survival is defined in terms of teaching and learning.
As exemplified previously, students too have the instinctual capacity for learning either individually or collaboratively. It is the teacher’s role to manipulate the classroom micro-society and environment to connect to these instincts. Trusting in technology will aid in this process.
Trust is defined as a confident reliance on the integrity, honesty, veracity, or justice of another: It is not innately instinctual; collaborative learning is. In order to tap the instincts for collaborative learning in our students, trust for educational technology must be engendered.
Rheingold, H. (2008). Howard Rheingold: Way-New collaboration. Retrieved on April 12, 2010 from
http://www.ted.com/index.php/talks/howard_rheingold_on_collaboration.html
Instinct is defined as an innate tendency or response of a given species to act in ways that are essential to its existence, development, and preservation. This definition implies that causes that affect these latter can be manipulated by external forces. During the agricultural age, families instinctually worked the land collaboratively for their existence and preservation. Before then, collaborative hunting and gathering within larger communities for the same purposes was prevalent.
Collaborations during the agricultural age did not, however, preclude the instinctual self-interests of competing farmers or plundering desperados. Nor were the hunters and gatherers safe from warring communities whose intent was territorial domination. In this manner, it can be seen that the decision to operate alone or cooperatively is a function of one’s perception of existence and self-preservation at the moment. Instinctually, one is able to do either. Moreover, the previous accounts indicate that both can, and do coexist. The question then becomes, which instinct dominates the moment?
At the onset of the industrial age, reliance on family collaboration was mitigated by a redefined need for existence and preservation. This new perspective was borne of the necessity to leave the farms to relocate to industrial centers, and then to separate from the wife and children for long hours to go earn a living in factories. This emphasis persists in today’s classrooms, where the moment is dominated by self-reliant traditional instruction.
While, like in society at-large, there is growing acceptance of the need for collaborative means, different from larger society, there exists a dearth of the trust necessary to facilitate cooperative learning in education. The macro-society appears to be modeling a trust in technologies that have realized such latter-day collaborative accomplishments as the Genome Project, CERN Particle Accelerator, and development of the Big Bang Theory, solutions that could not have been realized otherwise. In this regard, a teacher too, must trust in the virtues of the educational technologies that would leverage the power of constructivist collaboration in education. Therein, survival is defined in terms of teaching and learning.
As exemplified previously, students too have the instinctual capacity for learning either individually or collaboratively. It is the teacher’s role to manipulate the classroom micro-society and environment to connect to these instincts. Trusting in technology will aid in this process.
Trust is defined as a confident reliance on the integrity, honesty, veracity, or justice of another: It is not innately instinctual; collaborative learning is. In order to tap the instincts for collaborative learning in our students, trust for educational technology must be engendered.
Rheingold, H. (2008). Howard Rheingold: Way-New collaboration. Retrieved on April 12, 2010 from
http://www.ted.com/index.php/talks/howard_rheingold_on_collaboration.html
Wednesday, March 31, 2010
8845 MOD 2 BLOG POST
Beating-a-Dead-Horse-isms
Last I looked around, the year was 2010. Unless we’ve been suddenly warped backwards in time, debates that argue the merits of one teaching/learning style over another are passé; and at this advanced stage in the 3rd Millennium, amount to nothing more than to beating a dead horse.
This former view is not a discount of the pioneering efforts of Thorndike, Dewey, and Kilpatrick, nor the latter day refinements of Piaget, Skinner, Vygotsky, and Gardner: These have certainly all earned a proper place in education; rather, the point is that, similar to the conclusions of Kerr and Kapp, these arguments have become moot. The global diversity of learners, or as per Gardner, their multiple intelligences, in combination with the 3rd Millennial girth and depth of content, has made it imperative that educators stop wasting time on the trivia of the described discourse, and instead focus on what teaching/learning situations a particular learning theory might best be suited for, and/or when combinations of these might apply.
The references articulated present as a century-old journey. Therein, society has indeed alternately sanctioned behaviorism (in the 60’s and 70’s), cognitivism thereafter, and now again, in the second half of the past decade, a leaning back towards back-to-basics values, a resurgence of behaviorism, if you will. In this regard a microcosmic view within the so-called Math Wars in mathematics education is representative. (O’Brien, 2007)
Typical of the popularity of cognitive learning as noted, the mathematics community had embraced the concept largely due to the persistent recommendations of such as the National Science Foundation (NSF) and the National Council for Teachers of Mathematics (NCTM) that had successfully leveraged their reform curricula; that is, curricula based on cognitive learning. In a manner of speaking, cognitive learning was winning the math war against behaviorist teaching and learning.
Research in this past decade (ending with 2009), however, had begun to erode some of cognitive learning’s luster. As a result, President George Bush commissioned the National Mathematics Advisory Panel (NMAP), an eclectic compilation of educators, researchers, et al, to deliberate and make recommendations that would effect a plan for improving existing stagnant student mathematics performance levels. In 2008, while not totally relegating cognitive learning to a subordinate status, NMAP reported a need for students having the ability for “automatic (i.e., quick and effortless) recall of facts;” an emphasis that relates directly to behaviorist concepts of reinforcement. (USDE, 2008, p. xiii)
And so as we come around to the common sense fact for the need of inclusive approaches in the classroom, I offer a final distinction. Arguing which approach is better across the board is not the same as arguing how best to use each, or when to combine them. These are clearly horses of different colors. Arguing the former would be just another horse-ism.
O’Brien, T.C. (May 2007). The old and the new. Phi Delta Kappan. Retrieved from proquest.umi.com.ezp.waldenulibrary.org
U.S. Department of Education (2008). Success: The final report of the National Mathematics Advisory Panel. Retrieved from www.scribd.com
Wednesday, March 24, 2010
Wednesday, March 17, 2010
8845 - Mod 1: Topic 1
The Learning Switch
Learning is a physical activity, and a function of the brain. While the brain is not considered a muscle, it is regularly used as an analog to indicate that, like a muscle, exercising it improves its function. This analogy presents as an approach for understanding how we best learn, by investigating how we are motivated to learn.
Similar to how one summons the motivation to do physical exercise, learning too, requires willingness and commitment to act. When we commit to physical exercise, there is, in a sense, a motivation switch that triggers a signal to action: A signal that is engendered by the need to exercise.
Need as motivation in learning is readily illustrated in examples of the learned survival strategies of predator and prey, as well as, those of the earliest human forms. It is this real need to learn that, in our learners, many times is transitory at best. Importantly, this need to learn is distinguished as an internal dynamic, not as a teacher’s external perception that there is a need for a student to learn.
In this regard, it is the teacher’s role to create the internal motivation to want to learn. This is best achieved by actively involving the student in his/her own learning; that is, to allow students to construct their own learning. This style best expresses the tenets of the constructivist approach to teaching and learning. In this model, the teacher challenges students to take charge of their own learning and, at once, to devise their own strategies for learning. This process is similar, as previously suggested, to the construction of survival learning.
Students know that they need to learn. In constructivist learning, the motivation switch is turned on when the student realizes that he/she doesn’t have to struggle with teaching styles: Easier learning is enabled by a quick transition to a personal individualized and internal best way to learn.
These former notwithstanding, the process of learning, constructivist or otherwise, is complex, and as such, not easily explained. In this respect, academicians rely heavily on theory. A case in point is my own preceding articulation. In a similar way, one can explain the purpose of learning theory in educational technology. (Driscoll, 2005, p. 2)
Quite simply, learning paradigms don’t change during the design of particular educational technologies, or of the instructional designs that would incorporate these; instead, the opposite is true. Moreover, educational technologies are seen as mechanisms that deliver instruction, and the actual technology of instruction (instructional design) as more important. In other words, the implication of learning theory on educational technology is explained by its impact on instructional design. (Anderson, 2008, p. 15)
In still another manner of speaking, learning is not activated by a computer on/off switch. It is turned on by using technology in an instructional design that instills an active need and desire to learn. The switch is a function of technology of instruction more than one of educational technology.
Anderson, T. (Ed.). (2008). The theory and practice of online learning. (2nd ed.). Edmonton, AB: Athabasca University Press.
Driscoll, M. P. (2005). Psychology of learning for instruction (3rd ed.). Boston: Pearson Education, Inc.
Learning is a physical activity, and a function of the brain. While the brain is not considered a muscle, it is regularly used as an analog to indicate that, like a muscle, exercising it improves its function. This analogy presents as an approach for understanding how we best learn, by investigating how we are motivated to learn.
Similar to how one summons the motivation to do physical exercise, learning too, requires willingness and commitment to act. When we commit to physical exercise, there is, in a sense, a motivation switch that triggers a signal to action: A signal that is engendered by the need to exercise.
Need as motivation in learning is readily illustrated in examples of the learned survival strategies of predator and prey, as well as, those of the earliest human forms. It is this real need to learn that, in our learners, many times is transitory at best. Importantly, this need to learn is distinguished as an internal dynamic, not as a teacher’s external perception that there is a need for a student to learn.
In this regard, it is the teacher’s role to create the internal motivation to want to learn. This is best achieved by actively involving the student in his/her own learning; that is, to allow students to construct their own learning. This style best expresses the tenets of the constructivist approach to teaching and learning. In this model, the teacher challenges students to take charge of their own learning and, at once, to devise their own strategies for learning. This process is similar, as previously suggested, to the construction of survival learning.
Students know that they need to learn. In constructivist learning, the motivation switch is turned on when the student realizes that he/she doesn’t have to struggle with teaching styles: Easier learning is enabled by a quick transition to a personal individualized and internal best way to learn.
These former notwithstanding, the process of learning, constructivist or otherwise, is complex, and as such, not easily explained. In this respect, academicians rely heavily on theory. A case in point is my own preceding articulation. In a similar way, one can explain the purpose of learning theory in educational technology. (Driscoll, 2005, p. 2)
Quite simply, learning paradigms don’t change during the design of particular educational technologies, or of the instructional designs that would incorporate these; instead, the opposite is true. Moreover, educational technologies are seen as mechanisms that deliver instruction, and the actual technology of instruction (instructional design) as more important. In other words, the implication of learning theory on educational technology is explained by its impact on instructional design. (Anderson, 2008, p. 15)
In still another manner of speaking, learning is not activated by a computer on/off switch. It is turned on by using technology in an instructional design that instills an active need and desire to learn. The switch is a function of technology of instruction more than one of educational technology.
Anderson, T. (Ed.). (2008). The theory and practice of online learning. (2nd ed.). Edmonton, AB: Athabasca University Press.
Driscoll, M. P. (2005). Psychology of learning for instruction (3rd ed.). Boston: Pearson Education, Inc.
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