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A Unified Instructional Strategy Jayasurya Venugopalan, Wipro Ltd, Karnataka, India Annapoorna Gopal, Wipro Ltd., Karnataka, India Abstract: Direct learning methods have been the traditional forms of learning from time immemorial. The late 60’s saw the rise of inquiry based and experiential learning models which have attained some degree of success. More recently neuroscience based learning models have become prevalent. The paper attempts to arrive at a new model for instructional approach which integrates direct learning, experiential learning and cognitive neuro-scientific learning principles to arrive at the Unified Instruc- tional Strategy. Due importance is given to the architecture of human memory. The semantic declarative and procedural aspects of long term memory are considered so as to more efficiently associate new learning to existing learning, thus cementing this into long term memory. The methodology involves a 5 stage approach: (i) Review of learning already present in participant memory. (ii) Introduction of new concepts linking them to known concepts (iii) Introduction of new principles and procedures and relating them to the concepts learnt. (iv) Give a wider perspective to the concepts and principles /procedures learnt (v) Expose the participants to a problem solving situation which applies the new learning. This 5 fold approach to instructional strategy will help participants grasp the subject better and enable its storage in long term memory. Keywords: Direct Learning, Experiential Learning, Inquiry Based Learning, Neuro-Scientific Learning, Unified Instructional Strategy, Long Term Memory, Concepts, Principles, Procedures, Problem Solving Introduction T HE CONCEPTS OF direct, experiential and problem solving methods of learning are well known and have been implemented in diverse environments. Neuroscientific methods too have been investigated over the last few years and have been used to fuse learning with human memory architecture. The approach outlined in this paper integrates and unifies direct, experiential and neuroscientific methods to evolve an instruc- tional strategy framework which is adaptable and effective. It would enable and equip the learner to acquire knowledge and to leverage it to the greatest advantage. Learning Models and their Evolution The importance of learning models in any form of learning is extremely significant. The most frequently used learning models are: 1. Direct Learning Model 2. Experiential Learning Model 3. Inquiry Based Learning Model 4. Problem Based Learning Model 5. Neuroscience Based Learning Model The International Journal of Learning Volume 17, Number 2, 2010, http://www.Learning-Journal.com, ISSN 1447-9494 © Common Ground, Jayasurya Venugopalan, Annapoorna Gopal, All Rights Reserved, Permissions: [email protected]

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A Unified Instructional StrategyJayasurya Venugopalan, Wipro Ltd, Karnataka, IndiaAnnapoorna Gopal, Wipro Ltd., Karnataka, India

Abstract: Direct learning methods have been the traditional forms of learning from time immemorial.The late 60’s saw the rise of inquiry based and experiential learning models which have attained somedegree of success. More recently neuroscience based learning models have become prevalent. Thepaper attempts to arrive at a new model for instructional approach which integrates direct learning,experiential learning and cognitive neuro-scientific learning principles to arrive at the Unified Instruc-tional Strategy. Due importance is given to the architecture of human memory. The semantic declarativeand procedural aspects of long term memory are considered so as to more efficiently associate newlearning to existing learning, thus cementing this into long term memory. The methodology involvesa 5 stage approach: (i) Review of learning already present in participant memory. (ii) Introduction ofnew concepts linking them to known concepts (iii) Introduction of new principles and procedures andrelating them to the concepts learnt. (iv) Give a wider perspective to the concepts and principles/procedures learnt (v) Expose the participants to a problem solving situation which applies the newlearning. This 5 fold approach to instructional strategy will help participants grasp the subject betterand enable its storage in long term memory.

Keywords: Direct Learning, Experiential Learning, Inquiry Based Learning, Neuro-Scientific Learning,Unified Instructional Strategy, Long Term Memory, Concepts, Principles, Procedures, Problem Solving

Introduction

THE CONCEPTS OF direct, experiential and problem solving methods of learningare well known and have been implemented in diverse environments. Neuroscientificmethods too have been investigated over the last few years and have been used tofuse learning with human memory architecture. The approach outlined in this paper

integrates and unifies direct, experiential and neuroscientific methods to evolve an instruc-tional strategy framework which is adaptable and effective. It would enable and equip thelearner to acquire knowledge and to leverage it to the greatest advantage.

Learning Models and their EvolutionThe importance of learning models in any form of learning is extremely significant. Themost frequently used learning models are:

1. Direct Learning Model2. Experiential Learning Model3. Inquiry Based Learning Model4. Problem Based Learning Model5. Neuroscience Based Learning Model

The International Journal of LearningVolume 17, Number 2, 2010, http://www.Learning-Journal.com, ISSN 1447-9494© Common Ground, Jayasurya Venugopalan, Annapoorna Gopal, All Rights Reserved, Permissions:[email protected]

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Direct Learning Model was the first to evolve and it concentrated on direct instruction fromfaculty to learners . However, the subsequent Experiential and Inquiry-Based models paidmore attention to learning by doing and faculty student interaction. (“Inquiry Based Learning”;Kahn & O’Rourke, 2005). The Problem Based Learning Model on the other hand emphasizedon learners solving real life problems to acquire knowledge. (“Problem Based Learning”;Venkatesan & Fragomeni, 2008). Of late, the Neuroscience Based Learning Model has in-troduced learning techniques based on the architecture of human memory and brain (Byrnes,2001).

Architecture of Memory and LearningMany models of memory have been proposed and Dr Milton J. Dehn has evolved an elegantintegrated Model of Memory based on existing memory models, which we shall use in thispaper.

Fig 1: Integrated Model of Memory (Dehn, 2008, pp 51)

As seen in the diagram the components of this integrated memory model are:

1. Short-Term Memory: Visuospatial and Phonological2. Working Memory3. Long-Term Memory

Short-term memory stores verbal (also known as phonological) and visuospatial informationobtained typically through the auditory and visual senses. It can automatically encode thisinformation into long-term memory, bypassing working memory. When needed short-termmemory also activates long-term memory structures.

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Working Memory acts on both short-term memory and long-term memory information.Its operations include encoding information into long-term memory, association of memory,transforming information, searching, chunking and creating new memory representations.It basically helps the brain to process information and store what has been processed.

Long-Term Memory is composed of:

1. Semantic Memory and2. Episodic Memory

Semantic memory can be Declarative or Procedural memory. Declarative memory storesfacts, concepts, principles and rules, organized according to classifications, associations andmeaning. These are stored as semantic structures which form a network or schema. Aslearning occurs schemas are changed and connections between related schemas are madestronger. On the other hand, procedural memory is a record of the various steps required tocomplete a task. For successful learning, semantic memory must be well organized for bothdeclarative and procedural knowledge.

Episodic memory is primarily visual and contextual, and is focused on specific events orepisodes.

Long-term memory can also be classified into explicit and implicit memory.Much of the long-term content in working memory is brought by automatic activation,

directly initiated by short-term memory. As knowledge and skills become entrenched inlong-term memory, less processing is required (Lewis-Peacock & Postle, 2008)

When automated activation and retrieval and processing are insufficient for a task, workingmemory initiates a search for retrieving as well as for active restructuring and recoding. Toachieve this working memory operates on the semantic memory structures in long-termmemory. (Dehn, 2008; Anderson, Reder & Lebiere, 1996).

Direct Learning vs Experiential LearningDirect Learning Methods have been traditionally used for learning from the onset of education.However in the late 60s inquiry based and experiential learning models evolved and startedbecoming popular.

Of late, inquiry and experiential based learning were felt inadequate for present learningdemands. Another opposing school of thought, however, maintained that motivational levelscan be triggered and sustained only through inquiry, experiential and problem based learning.Let us first investigate these two proponent theories before postulating a probable solution.

Learning involves both short-term and long-term memories. Our long-term memory hasa huge knowledge base that is central to all our cognitive activities. The works of De Grooton chess expertise, Chase and Simon, and Egan & Schwartz1, all suggest that expert problemsolvers obtain their skill by using the large amount of experience stored in their long-termmemory and then rapidly determining the best procedures for solving problems. When aperson has huge amounts of strongly linked information in long-term memory he becomesan expert. This is because the associated information in his long-term memory enables him

1 De Groot was a chess master and psychologist who conducted some famous experiments in chess in the 50s and60s. Chase and Simon as well as Egan and Schwartz were psychologists who studied behavior of memory in chessgames and positions in the 1970s.

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to quickly recognize the characteristics of a situation , even if it is new, and enables him todetermine how to resolve the problem encountered..

The objective of any instruction is to meaningfully alter long-term memory. If nothingchanges in long-term memory, nothing has been learned. The architecture of long-termmemory guides us how to conduct instruction optimally.

Working memory has two major characteristics:

1. It can process only for a limited period of time.2. It has limited capacity.

Information in working memory if not rehearsed is lost within 30 seconds and its capacityis limited to only a very small number of elements . Information in long-term memory canbe activated and accessed by working memory. Moreover while accessing this informationin long-term memory, the capacity limitations of working memory are not applicable.

If we ask novice learners to find solutions for problems using unguided or minimallyguided instruction mechanisms, they will not have sufficient relevant information in long-term memory. So the capacity limitations of working memory will apply and problem solvingwill become quite difficult.

To build any set of skills or expertise the learning must be embedded in long term memory.To do this we need to have instructional learning designs which give quite a considerableamount of direct guidance (Kirschner et al., 2006).

This is what the advocates of direct learning state.Let us now turn to the opposing school of thought, which is the proponent of inquiry based

experiential and problem solving learning with minimal guidance. Kuhn (2007) says thatlearning should emphasize more on the subject matter that students learn and the relationbetween a particular student’s inclinations and the specific content required to be learnt.Motivation does not reside within the individual but is in the interaction between the indi-vidual and content. Inquiry based or learning by doing is irreplaceable. Students need toacquire complex skills and competencies nowadays. To learn what professionals do and howthey do it, students should engage themselves , in however rudimentary a way, in a handson approach. This means that supervision or guidance must be minimal for students to learnon their own.

Reconciling the Two SchoolsHow then do we reconcile these two approaches? Are they divergent or can they be unifiedin a holistic way?

Kirschner et al (2006) says that for learning to happen it must be stored in long-termmemory. At the same time Kuhn (2007) and others say that motivation is enabled only whenstudents learn on their own and by practice acquire the skills needed of them.

The problem then reduces to imparting learning which can be stored in long-term memory.It is apparent that the experiential approach to learning is ideally suited for adult learners as:

1. They already have a considerable store of knowledge and experiences2. These groups are motivated more by the experiential approach

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It must be agreed that learning happens only when the student is left to think and reason outon his own. Instructional design then is of paramount importance. The learning has to besuch that the learner acquires sufficient knowledge in long-term memory before embarkingon self discovery and learning by doing.

These learning processes have to be interspersed judiciously, with guided instruction onone hand building up long-term memory followed by experiential learning which helps tosink in the learning further into long-term memory. This is not enough. We have to scalethe learning content in such a way that the learner navigates from the basic to the complexin a natural manner, so that his learning goes into long-term.

Instructional StrategiesBefore discussing the Unified Instructional Strategy Model, let us first summarize the variousinstructional strategies which have been employed in learning.

Types of Organizational Instructional StrategyThe important types of organizational instructional strategies are (Smith & Ragan, 2005):

1. Declarative Knowledge Instruction Strategy2. Concept Learning Instructional Strategy3. Procedure Learning Instructional Strategy4. Principle Learning Instructional Strategy5. Problem Solving Learning Instructional Strategy

Declarative Knowledge

Declarative knowledge can be categorized into three different subtypes.

1. Knowledge Acquisition of Labels and Names:2. Knowledge Acquisition of Facts and Lists3. Learning of organized discourse

Knowledge of labels/names involves learners connecting two elements in declarative memory.Though meaning of the elements need not be necessarily known, linking becomes difficultwithout knowing the meaning.

A fact is a statement which normally describes a relationship between two or more concepts.For example: A dog is a household animal This links dogs to the category of household an-imals.

A list is a set of items which has to be remembered in toto. Facts and lists must be integratedwith prior knowledge in memory. As the semantic tree becomes larger and more complexit becomes easier to add new declarative knowledge by linking, elaborating and organizing.

Learning of organized discourse involves the comprehension of a line of reasoning likein a passage in a book.

(Scott, “Teaching Declarative Knowledge”) (Smith , 2006)

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Concept Learning

“A concept can be defined as a set of specific objects, events or symbols which are groupedtogether because of their shared characteristics and which can be referenced by a commongroup name or symbol “(Merrill and Tennyson.1977).

Concepts can be both concrete and abstract. Dog is a concrete concept whereas happinessis abstract . A learner who has acquired a new concept is able to use it to identify instancesof that concept he may not have been exposed to earlier. Similarly concept learners can illus-trate concepts learnt with their own examples and apply them appropriately.

Concept Learning involves generalization and discrimination. Discrimination is to ensurethat members of other similar groups are distinguished from the concept under study. Forexample cows should not be classified under dogs, this requires discrimination.

Concepts are stored in semantic long-term memory as productions. For example theconcept of a square may be stored thus:IF the figure is a parallelogram

And each side is equalAnd each internal angle is a right angle

THEN the figure is a square (Smith, 2005; “Concept Learning”):

Procedure Learning

Procedures are typically defined without ambiguity, where all steps are included and eachstep is clear. Procedures can be simple or complex. In a complex procedure there are manydecision points, at which the learner must decide which of two or more situations exist andcorrespondingly choose the next step in the procedure.

Instruction by which the learners understand the principles relating the relevant conceptsof a task and apply the procedure to accomplish the task would be very effective in forgingthe association between the procedure in long-term procedural memory and the conceptsand principles in declarative memory. Instructional strategies should explain the procedurein the context of the underlying principle so that information is more easily learnt.

The learner must understand the concepts before learning the procedure . Procedures alsorequire that productions be learnt. The following is an illustrative format:

IF the scenario possesses unique features A,, B or C usually understood as concepts,THEN apply procedure P1 (Smith, 2005; Wilson, 1995).

Principle Learning

Principles describe the relationship between two or more concepts. These relationships canbe represented by if-then or cause-effect relationships. Knowing a principle helps the learnerto explain what has happened and also how to control the effects of variabes involved in theprinciple on each other.

Principles are a type of declarative knowledge. Learning a principle also implies theability to apply the principle in a spectrum of scenarios which the learner has not been exposedto earlier.. The cognitive processes of the application of principles can be represented asproductions. Principle learning is central to problem solving. To find and solve problems in

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a domain, learners must have acquired a large number of principles that explain the relation-ships between critical concepts in that domain.

Information analysis for principles is somewhat different from that of procedures Someexamples of the processes of human cognition involving principles are shown:1. IF the situation described involves key concept X

And if the situation involves key concept YTHEN rule Q applies in the case. (Concept Recognition) Here Q is a principle.

2. IF concept X changes in direction D1 with magnitude M1THEN concept Y will change in direction D2 with magnitude M2.This principle explains the relationship of the two concepts. (Smith, 2005; “Principle

Learning”).

Problem Solving Learning

Problem solving is the ability to combine uniquely principles, procedures, and declarativeknowledge previously learnt, to solve problems never encountered before . This yields newlearning as learners are able to tackle problems of similar nature more easily in the future.The key factor behind problem solving in is the knowledge of principles and proceduralrules in a specific domain and how these relate to each other.

The first stage of problem-solving is problem representation. This needs problem decom-position and identifying the appropriate problem schemata. A skilled problem solver mapsthe current to a previous problem situation. The learner maps the attributes of the currentproblem to the important features of the problem stored in long-term memory. If this mappingis through meaningful conceptual links, this would facilitate easy problem solving (Savery,2006)

The next stage of problem-solving is Solution Planning. This involves searching, picking,combining and serializing the relevant knowledge. Then comes Solution implementationwhere learners identify and apply appropriate principles to find a solution.

Finally in Solution evaluation the learner verifies that the solution is correct (Smith, 2005;Sergienko, 2002; Zhang).

Instructional Design and StrategyFor Instructional Design of any course, there must be:

1. Needs analysis2. Analysis of learners and learner characteristics3. Determination of Pre requisites4. Formation of Learning Objectives and Designing assessments5. Instructional Strategy6. Implementation and Evaluation

Needs, learners and their characteristics analysis are first completed. Then, prerequisiteanalysis is performed. This is followed by the framing of the learning objectives and thedesign of assessments for evaluating learner performance. Next comes, instructional strategydesign and implementation and finally its evaluation for efficacy.

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Our main focus is on the design of a model for Unified Instructional Strategy integratingall relevant types of instructional strategies in conjunction with the integrated architectureof human memory and learning.

Design of the Unified Instructional Strategy ModelThe design of the model for Unified Instructional Strategy involves a five stage approach:

1. Review of relevant learning already present in the long-term memory of the learner2. Introduction of new concepts and associating them to already existing schemata in se-

mantic memory3. Introduction of new principles and associating them with learner’s existing knowledge

schemata and introduction of new procedures and their association.4. Exposure of a wider perspective to concepts, principles and procedures through a wide

range of illustrative scenarios enhanced by experiential and inquiry based learning, thusstrengthening and deepening long-term memory schemata

5. Exposure of learners to problem-solving situations which apply the concepts, principlesand procedures in the new learning, which ensures learning is cemented in long-termmemory

Let us now consider each stage of the model. Together we illustrate with a case study howour model can be applied to each stage.

Our case study is on computer networking to comprehend how an Ethernet Network op-erates and to study its applications.

Prerequisite:(as relevant to the learning objectives):How a computer functions

Learning Objectives of the Case Study:

1. Describe the properties of a Network Interface Card (NIC)2. Comprehend the Ethernet Address format and the IP Address of NIC3. List the fields in the Ethernet frame4. Comprehend and apply how the Ethernet Address and IP address are mapped5. Describe and Study the use of Address Resolution Protocol (ARP)6. Comprehend how systems in one network and across different networks communicate

through the NIC.

Stage 1: ReviewIn any instruction design the introduction should prepare the learners by stimulating theirattention and making available relevant memory schemas in working memory. This existingknowledge makes the new information easier to grasp. The learners should have a clear ideaof the learning objectives, their purpose and usefulness. Side by side the learning activitiesshould be previewed.

Judicious review should make available for working memory the schemata which will beused to correlate and associate the new learning so as to extend them with the fresh concepts,

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principles and procedures learnt. The review process is extremely important in aiding andenhancing learning. It would be more efficacious if at the appropriate points in the instructiona strategy for refreshing the relevant schema is used. With reference to our Case Study andthe pre-requisite of how a computer functions, consider this chunk of long-term memoryschema:

Fig 2: Schema in Long –Term Memory

Fig. 2 depicts how people communicate by talking and messaging using mobiles. It also il-lustrates the fact that people typically communicate data through wired networks. All learnershaving the prerequisites would already be knowing this, they only need to be reminded ofit.

By review if this structure is activated, the working memory will have access to it. So itbecomes much easier to link in the new learning regarding Ethernet communication to theexisting knowledge available as an activated chunk.

Stage 2: Introduction of New ConceptsThe second stage of our Unified Instructional Strategy is the introduction of new concepts.A concept as defined earlier is a set of objects, events or symbols which have an association.New concepts should always be introduced in the context of existing concepts and principles.

Considering our Ethernet Case Study the concepts which would need to be learnt are:

Ethernet Frame, Ethernet Address, Fields of Ethernet Frame, IP Address, ARP(AddressResolution Protocol), unicast, multicast and broadcast framesSuppose we want to introduce the concept of a message as an Ethernet frame.First, we could review the existing knowledge of a frame by showing images or discuss-ing a photograph or door frame.Once the learner recognizes that a frame acts as a container, he or she can be exposedto the concept of a message and how messages may be sent on mobiles or throughcomputers on Ethernet.

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Then the fact that the message needs to be put in a container is driven home, like a letterin an envelope or the data in an Ethernet Frame.Then we would like to expose the learner to the fields of an Ethernet frame includingthe address fields in the frame.To do this we could recall that a letter has an envelope which contains the destinationaddress, the source address (From Address) and the message itself.Similarly the Ethernet Frame has the destination address, the source address in theheader or initial part of the frame and the messsage in the body of the frame.When concepts are introduced in this manner it becomes easy for the learner to associatethis into his or her existing schemata as illustrated in Fig 3. The colored ellipses andboxes are concepts which learners already know and recalled through review. The whiteellipses and boxes are the new learning of Ethernet networks which is associated to theexisting learning.The remaining concepts can be introduced in similar fashion.

Fig 3: Introducing and Linking a Concept using an Ethernet Frame as Example

Needless to say concepts can be introduced and associated with a combination of direct andexperiential learning techniques (Lewis, 2003).

Stage 3: Introduction of New Principles and ProceduresPrinciples relate two or more concepts, and are depicted by IF THEN or Cause and Effectrelationships.

For our case study on Ethernet networks the principles which would need to be coveredare:

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1. A Network Interface Card (NIC) will accept a unicast frame only if the destination ad-dress in frame is same as the NIC’s Ethernet address.

2. All systems in same Network will have the same prefix in the IP Address.3. The IP packet with the application message will be encapsulated in a Frame.4. If a system finds the destination IP address in its ARP cache it will use the corresponding

Ethernet address as the destination address field in its frame, else it will broadcast anARP and wait for the reply.

5. A system receiving a broadcast ARP will reply with its Ethernet address to sender onlyif the IP address in the ARP broadcast frame corresponds to its own IP address.

6. If the destination IP address has a prefix different from that of the sending system itsends the frame to the gateway router on the network.

The first principle underlying the receipt of Ethernet frames by a NIC can be stated thus:

A computing system in an Ethernet network will receive and process a frame only ifthe destination address in frame matches the address of the Network card in the com-puting system receiving the frame.

So the concepts which must be known to understand this principle are:

1. Computer systems communicate on Ethernet networks by sending Ethernet frameswhich have the destination and source address.

2. Every computing system on an Ethernet network has a network card which receivesand transmits Ethernet frames. It has a fixed Ethernet address.

3. An Ethernet card receiving frames will process only those whose destination addressesis same as card’s own address.

This principle will get associated as a production in memory by the following:

IF the network card in a computing system receives an Ethernet frameAND IF the destination address in frame is equal to the ethernet address of the

cardTHEN it will process the frameELSE it will discard the frame.

Here we have for simplicity assumed that all frames are unicast. This method of presentingconcepts and principles, associating them in the way described mimics the way informationis stored in memory. So the learner will find it very easy to absorb such learning and recallwhen needed.

Learning of procedures is also equally important. Procedures are stored as a series of stepsin procedural memory. The procedure may have decision steps too. Hence a procedureconsists of recognition of the occurrence of a concept or concepts in a scenario and applyingthe appropriate procedural steps.

Our case study would involve the learning of the following procedures.

1. How to determine Ethernet address using Address Resolution Protocol (ARP) Cache.2. How to connect the systems to switch

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3. How to connect more than 1 switch4. How to test the connectivity between the systems5. How to troubleshoot

Let us consider the first procedure of how to determine the Ethernet address using the ARPcache . Typically every Network Card has an Ethernet address as well as a logical IP address.When a system wants to transmit a message it determines the destination IP address first.Then it searches for the Ethernet address in a cache called an Address Resolution Protocol(ARP) cache.

So the procedure may be depicted thus:IF a system wants to send a message to a destination:

1. Get the IP address of destination2. Look up the ARP cache for the IP Address and corresponding Ethernet address of

destination.3. IF found use the Ethernet address as destination address and own NIC Ethernet address

source address

Form the frame with message.Transmit the frame.ELSE broadcast an ARP request and wait for reply.

It is extremely important the learning be logically presented as concepts, principles andprocedures, which will immensely enhance learner absorption and retention.

Stage 4: Give Wider Perspectives to the Concepts andPrinciples/Procedures LearntThe fourth stage is to give a broader base to the learner. To achieve this it is necessary todesign a range of experiential activities for the learner so that the knowledge he has acquiredis cemented into his long-term memory. This will also help in deepening the links and asso-ciations forged in the learner.

Experiential activities would be scenario based, and could be role plays/discussions/as-signments/laboratory/hands-on assignments as appropriate. There is no sacrosanct sequencingadvocated; it is the task of the instructional designer to determine the most optimum flowfor the learner.

It is important to make the learner view the concepts, principles and procedures fromdifferent angles.

Our case study could use the following for broadening the perspectives of the learners.

1. Demonstrate how to examine the IP and Ethernet address of system. Let participantscheck the IP/Ethernet address and verify.

2. Let participants connect to a switch and use ping command to check connectivity.3. Demonstrate how ARP functions using ARP command, and let the participants verify.4. Demonstrate with ethereal( a packet capturing tool) and let participants check IP address,

Ethernet address and ARP request and response.

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In the case study considered, assignments can be designed to make the learner reason whythe destination address should be the first field, what happens when a frame reaches a switch,why a logical IP Address and Ethernet address are both necessary, why should an ARP bebroadcast and so on. The intent here is to thoroughly analyze the knowledge gained be itconcepts, procedures or principles. Needless to say, analogies have to be drawn to priorknowledge.

It is the instructional strategy designer’s imagination which needs to be stretched to thelimit to produce content to make the learner truly appreciate and relate to his acquiredknowledge. The fruit of the instructional strategist’s design will be the strength and longevityof the structures created and linked in the long-term memory of the learner.

Stage 5: Expose the Participants to a Problem Solving Situation whichApplies the New LearningThe fifth and final stage is to expose the learners to a problem solving situation which makesthem apply their learning. This could be one problem scenario or more.

The essence of this stage is to crystallize the knowledge gained in the previous four stagesby exposing learners to a practical situation which makes them appropriately recall and applythe knowledge acquired. This problem solving exercise clarifies any knowledge in thelearner’s mind which is a bit fuzzy. The role of the instructor in guiding the learners is ofparamount importance.

Now for our case study introduce problems in the network like faulty network card, orfaulty Port of switch or faulty switch and let learners troubleshoot and diagnose the problem.

In the problem solving scenario of troubleshooting the faulty network the fault generatedcould be faulty IP addressing or problem in the cable or problem in the Network Card orcombinations of these. Troubleshooting, diagnosing and rectifying the problem in the networkusing a logical sequence of identifying the concepts, principles and procedures studied forapplication to the problem resolution helps to make the learner’s learning much more concreteand lasting in long-term memory. Collobaration with other learners in a group in the problemsolving exercise also enhances learning.

Session Conclusion and SummaryHave a group discussion to discuss the learning and share ideas and comments and theproblems typically faced and solved and how the principles and concepts learnt helped themto solve the problem to embed learning into long-term Memory.

ConclusionThe Unified Instructional Strategy marries direct learning, inquiry based and experientiallearning with the architecture of human memory into an integrated instructional model whichserves as a powerful means to impart learning. The Framework helps cement and merge newknowledge seamlessly into existing learning.

Moreover, this embedded and strongly associated learning is fused into long-term memorythrough a range of associations. Hence learners will be able to recognize, tackle and resolvehitherto unencountered problems by drawing on their rich repertoire of knowledge. This

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model is however no philosopher’s stone; it requires a lot of thought and effort from the in-structional strategy designer.

We are of the strong opinion that our unified model for instructional strategy can proveto be a very powerful and efficient methodology for learning.. It can be utilized to dramaticallyincrease the absorption power and competency gains of the learner. We are in the processof implementing this model in our organization.

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Relevance of Neuroscientific Research. New York: The Guilford Press.Concept Learning (n.d.). Retrieved from http://dspc11.cs.ccu.edu.tw/ml93/lecture3-concept-learning.pdfDehn, M. J. (2008). Working Memory and Academic Learning: Assessment and Intervention. New

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Labhrainn, I., Fallon, H. (Eds), Handbook of Enquiry & Problem Based Learning.Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why Minimal Guidance during Instruction Does

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About the AuthorsJayasurya VenugopalanJayasurya Venugopalan graduated from IIT Madras, with a B.Tech (Electronics) and sub-sequently did his MS from BITS Pilani. He has a total work experience of 29 years , the first9 years as an Instrument Engineer in a paper manufacturing industry. Subsequently he wasin the academic profession teaching in the computer Science Department of several engin-eering colleges. Before joining Wipro Technologies in 1999 he was the Asst. Prof and HODof the CSE Dept of BMS College of Engineering, a premier engineering college in Bangalore.In Wipro he has been with the Training Division called Talent Transformation and has beenconducting courses both instructor led and online in various topics in Networking, NetworkManagement and Operational Support Systems. Over the last year he has been associatedwith the School of Talent Transformers within Talent Transformation where he is activelydoing research in curriculum development and Teaching methodologies.

Dr. Annapoorna GopalDr. Annapoorna Gopal has completed her research in the area of Human Resources fromSIBM, Pune, India. She heads the School for Talent Transformers at Wipro and is workingwith Wipro for the last nine years. Prior to this she was associated as a Senior Faculty in thePost Graduate Department of Christ College, Bangalore.At Wipro Annapoorna has adornedmultiple roles both in the delivery and managerial capacities alike. She has contributed tothe development of competency on Rational software development tools, managed the as-sessment center, introduced different teaching methodologies with specialization in the “caseBased Approach to Training”, championed Distributed Learning projects and has designedand delivered a course on Wipro Values. As the head of Academic Initiatives Annapoornatook care of the Wipro Academy of Software Excellence which is the country’s largest work-integrated collaborative learning program. In her current role, Annapoorna and her teamwork towards enabling Talent Transformation at Wipro move up the value chain. She haspublished several papers and is a regular contributor of articles in the press

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