An Oxonian's Learning Journey

Modelling in Education

by aysekok @ 2008-10-10 – 17:39:22

Most of us associate modelling with the area of fashion and modelsYet, it aplies to almost any area ranging from economics to eduction.

Mellar and Bliss (1994) define modelling is thinking about one thing in terms of simpler artificial things. Mellar and Bliss (1994) also state that all modelling activities share the following three features:
- one thing used in place of another
- idealization and simplification of modelling resources
- a tendency to play with the modelling resources for their own sake

Despite the artificiality, simplicity and fully predetermined nature, models may lead to new and powerful insights (Mellar, Bliss, 1994). Although models fit more or less all we know about some aspects of reality they may also point to new things to look for, so they provide new thinking as much as they solve old problems (Mellar, Bliss, 1994). Mellar and Bliss (1994) summarize the major problems with modelling as follows:

- Modelling can be done more or less badly, so much so that it can become dangerous.
- The modelling of situations involving human choice raises various difficulties that don’t arise in modelling the behaviour of inanimate objects.
- Models once created may be used in dubious ways.

Various psychologists tried to explain what is happening when people are thinking. To exemplify, Piaget’s formulation of how we think describes what one uses to think with, the mental tools for thought which he called as operations or schemes. These include mental classification schemes that allow children to differentiate between living and non-living things, or between objects that will sink or float. The bottom line is that modelling is associated with cognitive development, so it should be more emphasized by educators and tried to be understood more in detail as it may provide great support for the cognitive development especially via use of online tools such as virtual worlds or simulations.

Theories of Intelligence

by aysekok @ 2008-10-09 – 16:24:14

Here are some theories of intelligence that might be useful for anyone intersted in brain-comptabile learning:

- Gardner's Multiple Intelligence:

-- Verbal
-- Logical
-- Visual/spatial
-- Bodily/kinesthetic
-- Musical/rhytmic
-- Intrapersonal
-- Interpersonal

- Costa's intelligent behavior

-- Persistence
-- Decreasinh impulsivity
-- Emptahetic listening
-- Flexibility in thinking
-- Metacognition
-- Checking for accuracy
-- Posing questions
-- Drawing on past
-- Applying it onto new situations
-- Using precise language
-- Using all senses
-- Creativity
-- Being excited about world
-- Risking appropriately
-- Using humor
-- Colaborative interdependence
-- Being open to new learning

- Goleman's EI

-- Self-awareness
-- Managing emotions
-- Self-motivtion
-- Empathy
-- Social arts

I think that being able to combine all of these skills would be great :))

How to Solve Ill-Strutured Problems?

by aysekok @ 2008-10-08 – 19:51:33

Ill-structured problems have various solutions and multiple solving processes that can be derived based on the solver’s perception (Hong, 1998). They also involve more complicated processes and require components such as content knowledge, structural knowledge, domain-specific strategy and general searching strategy as well as evaluation and justification skills (Hong, 1998). Consequentially, traditional learning environments that present single analogies or discrete procedures that are oversimplified or over generalized are not sufficient for enhancing ill-structured problem-solving skills (Hong, 1998). Hong (1998) states the following steps of the process of solving ill-structured problems:

- Recognizing that there is a problem
- Finding out what the problem is
- Searching information about it
- Developing justification by identifying alternatives
- Organizing information to fit a new situation
- Generating possible solutions
- Deciding on the best solution by the solver’s perception
- Implementing the solution

Cognition including domain-specific knowledge, metacognition including general search strategies, non-cognitive variables such as value, attitude and justification skills such as developing argumentation are necessary for solving ill-structured problems.

Dynamic Complexity

by aysekok @ 2008-10-07 – 19:39:25

Dynamic complexity arises because of the following factors (Sterman, 2001):

- Systems are constantly changing: Change in systems occur at many times whereas these scales sometimes interact.
- Systems are tightly coupled: Everything is connected to everything else.
- Systems are governed by feedback: Decisions taken may give rise to a new situation that may change the state of the world. System dynamics arise from feedbacks.
- Systems are nonlinear: As multiple factors interact in decision making effect is rarely proportional to cause.
- Systems are history- dependent: Taking one road often precludes taking others.
- Systems are self-organizing: The dynamics of systems arise from their internal structure and the elements of the system.
- Systems are adaptive: As people learn from experience hey learn new ways to achieve their goals.
- Systems are characterized by trade-offs: Time delays in feedback channels mean the long-run response of a system is different from its short-run response.
- Systems are counterintuitive: In complex systems cause and effect are distant in time and space.
- Systems are policy resistant: The complexity of the systems in which we are embedded overwhelms our ability to understand them.

Aren't our lives like systems entailing a dynamic complexity?

The Boundaries of the Human Mind

by aysekok @ 2008-10-06 – 19:50:42

As Sterman argues, one of the powerful advantages of the mental model is its flexibility and hence its ability to take a wide range of information into account, and process information which is presented in various forms. Mental models can also be adopted to new situations and changed as new information becomes available (Sterman, xx). Yet, its disadvantages are they could not be examined by others as they are not explicit. Their assumptions are hard to be identified and as interpretations may differ contradictions may go unresolved.

As Simon (1957) asserted, as the capacity of the human mind for solving complex problems is very small the best-intentioned analysis of complex problems cannot account accurately for the interactions that together determine the outcome. The impacts of externally imposed changes may not be adequately assessed by mental models.

How to Understand Dynamic Behavior

by aysekok @ 2008-10-05 – 14:19:24

According to Forrester (1992), system dynamics offers a framework for giving cohesion, meaning, and motivation to education at all levels from kindergarten upward. Besides, system dynamics also allows reversing the traditional educational sequence in which synthesis of the facts learnt can be introduced at an early stage in a student’s experience. Such a synthesis can be based on facts that even elementary school students may have gleaned from life.

Forrester (1992) claims that answers to questions about how things change through time lie in the dynamic behaviour of social, personal, and physical systems rather than the static snapshots of the real world as taught by education. Education is compartmentalized into separate subjects that in the real world interact with each other. Yet, a framework for understanding the social and physical environments cannot be synthesized without teaching dynamic behaviour. The cornerstones for a more effective education would be system dynamics and learner-centered learning.

Why Systems Thinking?

by aysekok @ 2008-10-04 – 16:33:23

We don’t live in a unidirectional world in which a problem leads to an action that lead to a solution. Indeed, we live in an ongoing circular environment in which each action is based on current conditions, such actions affect conditions and the changed conditions become the basis for future action.Hence, the importance of understanding from a systems perspective is crucial. Accordingly, the objectives of a system dynamics education should be (Forrester, 1994):

- Developing personal skills: A system dynamics education should sharpen clarity of thought and improved communication. Computer modelling requires clear, rigorous statements in contrast to the human language that may entail ambiguous and illogical statements. Precision of expression to go from language to explicit statements can be achieved through building and using a simulation model. When a model is established based on the structure and decision-making rules in a system the reasons for a behaviour might be understood so that agreement can be reached. Besides, a systems education should encourage the learners being courageous to make precise statements and thinking more deeply about popular held beliefs.

Experience in computer simulation could change the way students respond to the world around them. Through simulation models, students should appreciate the complexity of social and economic systems and understand that ‘obvious’ solutions to problems may sometimes be the causes of the problems. Computer models can be used for revealing assumptions and justifying conclusions.

Moreover, systems modelling enables one to see the interrelatedness in systems and the interconnecting structure that gives meaning to the parts. System dynamics also provides a foundation underlying all subjects so that once it is mastered an individual can move from one field to another. A person with a systems understanding can see the common elements in diverse settings rather than focusing on differences. Realizing that science, economics and human behaviour rest on the same kinds of dynamic structures would allow transferability of behaviour in one particular area.

- Shaping an outlook and personality to fit the 21st century: A systems education could enable students to shape their own futures and to look for causes and solutions as working with systems reveals the strengths and weaknesses of mental models. Understanding system dynamics would also equip the learners with a broader systems perspective to appreciate the nature of complexity. Innovative tendencies can be cultivated in learners through system dynamics education so that they look for causes and works toward beneficial advances. As computer simulation modelling is a repeating process of trial and error one can learn how to progress through exploration.

Students can also learn how mental models can be useful and when they are unreliable as they are only sets of assumptions and observations gained from experience. Our mental models are often incomplete and may not draw the correct conclusions. Computer models compensate for the deficiencies of mental models by simulating the system based on the assumptions incorporated in the model. So, by interacting with computer models new insights can be gained.

- Understanding the nature of systems in which we work and live: We live in a network of complex systems where cause and effect are not closely related as in simple systems. In a system made up of many interacting feedback loops, causes may lie far back in time. Besides, policies to yield better results may not be obvious. So, students should come out of a systems education with an appreciation for how mental models alone can lead one astray in multiple-loop systems. Students should also look for the source of their troubles first in their own actions rather than blaming others and should be exposed to the dynamics of goal collapse in models so that they can relate the process to their own lives. They should also study the fundamental conflicts between short-term and long-term goals in the context of system dynamics models and have the opportunity to relate lessons to their communities and nations.

In order to gain the systems thinking systems education students must get actively involved and relate what they are learning to systems they already now in families and school for a deeper understanding. System dynamics modelling refers to learning by doing and learning through being surprised by the mistakes one makes.

Systems Thinking

by aysekok @ 2008-10-03 – 18:56:50

Thinking is considered to be an individual concept. Although the term 'systems thinking' is a paradox it can be defined at the individual level the thinking of one individual about the whole, multi-actors system. At the group level, it refers to the collective thinking of a group about a larger multi-actors system. Systems thinking is often associated with system dynamics whereas systems refer to intercations, interelationships, and interdependencies that are technical, socal, temporal and multi-level according to a MIT based research study (Davidz, Nightingale, Rhodes). According to this study, the potential enablers of systems thinking are:

- Working in a role requiring systems thinking
- Systems education paired with practical experience
- Strong communication skills
- Undergrad degree outside of engineering
- Encountering serious problems requiring systems thinking
- Holding jobs in multiple disciplines]- Technical depth
-Participation in professional societies
- Broad range of interests
- Training courses

Some barriers entail the silo activities whereras potential precursors are the unwillingness for systems thinking, the personality traits, not being born as a systems thinker. It is interesting to note that the natural dispositions to systems thinking is triggered and that systems thinkers are born rather than taught. So, some age-children may be most open to systems thinking.

I think that although systems thinking- according to the stud- cannot be taught we may emphasize in our schools more on this topic as it seems to be a crucial skill for the 21st century.

lock;margin:12px 0 3px 0;text-decoration:underline;" href="http://www.slideshare.net/pthuyduong/systems-thinking-introduction?type=powerpoint" title="Systems Thinking Introduction">Systems Thinking Introduction

View SlideShare presentation or Upload your own. (tags: systems-thinking systems thinking)

The Cognitive and Social Impact of Technology

by aysekok @ 2008-10-03 – 17:46:01

Today, I had the chance to listen to G. Siemens' podcast about the cognitive and social impact of technology. He mainly focuses on the following questions:

- What does technology allow us to do?

Technology allows us to think. They enable us to extend ourselves from our limitations and to extend ourselves onto a network of tools that can address the weaknesses that we have inherent in our human mind. Technology also allows us to know. It allows to be intelligent. We are cognitive through technology. It also allows us to feel, act, share, to be or to become. Any new technology carries the patterns f prior reasoning. This is evident in the use of technologies within the classrooms. New technologies are embedded within the mindset of use of prior technologies. Recently, there is a break from centralized thinking, from who is an authority or an expert. Some other recent changes are:

We have incredible gain of control over virtually every information interaction. Paradoxically, this may result in a loss of control as everyone may try to control the information creation and hence be overwhelmed by information overload.

• There is a breakdown of geographical distances to understand what it means to know. Networked connectivism enable us to have friends geographically dispersed.
• We also live in a multi-perspective world where every single perspective is balanced by at least two more perspectives.
• Cognitively, we are also distributed. We don’t think alone, we think in social interactions, in social spaces.
• We are also becoming collective via collaborative web sites, blogs, wikis. So, it is not what you know that is important rather to what resources/people one is connected. We pull together different pieces from the network participants.

- How does technology affect the process of socialization?

There are two main type identities with regard to the online realm: Identity that we reveal via social networking websites such as Facebook and the identity revealed by our actions via websites. The trails that we leave behind form who we are. When these structures are pulled together the real value is provided.
Problem solving and teaching about a specific subject can occur via ongoing participation in the online environment. Content is just a commodity due to the explosion of free online resources. Our ability for distributed cognition and our ability to interact, collaborate, share and influence far exceed the recent structure of education.

- What does it mean to be human?

Research on educational technologies suggests that it does not matter whether technology is used for teaching or not. What matter is that our tools carry different patterns from previous reasoning. Our tools still carry with them these prior concepts as if the teachers had still to control the information within the classroom environment. Technology can act as extension and technology can integrate with humanity. On the one hand, we have a return to humanity via the social tools. In way, we may return to the pre-Plato era where information is shared via storytelling. On the other hand, we may create techno-humans via nanotechnology. So, we are at a point where we can decide where humanity can go.

- How can we achieve a balance amidst these technological changes?

Education’s aim is to transform society and learners to higher ideals. We need to preserve the notions of deep understanding, being a human, contributing to others’ ideas. As stated by Harvard University the aim should be to educate unique learners as products of ideas and art. A conceptual revolution and tool-based revolution is ahead of us. Learning with collaborative tools out of classrooms should be acknowledged. As connections with other educators and learners can be formed the walls of the classroom become permeable.

When is Learning Effective?

by aysekok @ 2008-10-03 – 16:06:14

The effectiveness of learning is a complex issue as it may depend on various conditions, yet here are the main criterias according to the educational theorists:

- Principle of problem centeredness: Learning is effective when learners are engaged in solving real-world problems.
- Principle of learner activation: Learning is effective when existing learner knowledge is activated as a foundation for new knowledge and skills.
- Principle of demonstration: Learning is effective when desired knowledge applications and skills are demonstrated for learners.
- Principle of application: Learning is effective when learners are required to apply new knowledge and skills.
- Principle of integration: Learning is effective when new knowledge and skills are integrated into the learner’s world.

Although these may seem straightforward integrating all of these elements into the learning environment is a challenge!

Learning in the 21st Century

by aysekok @ 2008-10-02 – 17:58:11

While making research about my new paper I came across this link. According to Unesco's Learning Development Institute, the characteristics of the 21st century learning are as follows:

- When discussing the relationship between new pedagogies and the emerging new technologies equal consideration should be given to both technology and pedagogy. Pedagogy basically refers to the facilitation of learning among children. Yet, as because learning can be a life-long process it should refer to learning at any age. Besides, a learning landscape includes media landscape, socio-cultural organization landscape rather than the instructional landscape. So, the integrity, completeness and interconnectedness of all of these parts should be of concern.

- We should not assume that every new technology calls for different ways to facilitate human learning as learning is mainly determined by our minds. Technology extends the capacities of our cognitive functioning and hence should be considered as an evolving aspect of the human condition rather than as an independent phenomenon.

- To answer the questions of "What does it mean to learn in the 21st century?" we should take into consideration not only the growing human population, the need for peace to live together and the sustainability of resources but also the state of the development of the human consciousness.

So, human learning is a multi-faceted phenomenon which requires flexibility and openness. In order for technology to support learning we must accept the fact that everyone is both a learner and facilitator of the learning of others.

Recognizing our Cognition States

by aysekok @ 2008-10-02 – 17:16:27

Norman (1993) suggested there are two types of cognition:

- Experiental state: In this state, we perceive and react to events in an effortless way.

- Reflective state: This state relates to comparison, contrast, thought and decision-making.

Being essential for human performance these modes define whether reflective or experiental support should be provided for our interactions with technological artefacts. To exemplify, broadcast television cannot augment human reflection as it is watched in an experiental mode (Norman, 1993). On the other hand, video and television are reflective tools since the user can select what to watch and control the pace of the material (Norman, 1993). So, their use within the learning environments may further increase the power of learning.

Yet, apart from their importance in the area of technology and learning I think that we should develop a meta-awareness and be able to recognize in which state of cognition we are. Ideally, we should be able to reflect upon our experiences rather than just reacting passively to them. As emphasized in prior blog postings we are meaning-making creatures and without reflection we cannot find any meaning...

Knowledge Types

by aysekok @ 2008-10-01 – 17:41:27

When learning about a new subject make suer that you give some thought about what type of knowledge you gain based on the following criteria:

- Referential: This refers to the knowledge of symbols and meanings and is also as semantic knowledge.

- Factual: This refers to the knowledge about objects and relationships between objects within the world.

- Procedural: This knowledge about how to do things can either be classified in terms of rules, algorithms, procedures (explicit) or in terms of skills (implicit) that cannot easily be described verbally.

- Metacognitive: This refers to the learning strategies and entails what it means to lean something and how learning can be measured in terms of these different types of knowledge.

A blended model of all types of knowledge may make you eventually an expert