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AD-A023 066
LEARNING GUIDELINES AND ALGORITHMS FOR TYPES OFTRAINING OBJECTIVES
James A. Aagard, et al
Training analysis and Evaluation Group (Navy)
Orlando, Florida
March 1976
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I. REPORT NUMBER 12. GOVT ACCESSION NO 3. RECIPIENT'S CATALOG NUMBER
TAEG Report No. 234. TITLE (end Subtitle) S. TYPE OF REPORT & PERIOD COVERED
LEARNING GUIDELINES AND ALGORITHMS FOR TYPES OF Feb 1974 - Mar 1976TRAINING OBJECTIVES Final Report
6. PERFORMING ORG. REPORT NUMBER
7. AUTHOR(a) S. CONTRACT OR GRANT NUMBER(a)
James A. Aagard, Ph.O. and Richard Braby, Ed.D.
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Training Analysis and Evaluation Groupnrlandne Ft .R1_
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March 197613. NUMBER OF PAGES
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18. SUPPLEMENTARY NOTES
19. KEY WORDS (Continue on reverse side If neceaesry and identify by block number)
Learning GuidelinesLearning AlgorithmsLearning PrinciplesClasses of TasksInstructional System Development
20 ABSTRACT (Continue on reverse side If necessary end Identify by block number)
Training strategies are presented for 11 common classes of trainingobjectives. These classes are: (1) recalling bodies of knowledge, (2)using verbal information, (3) rule learning and using, (4) decisionmaking, (5) detecting, (6) classifying, (7) identifying symbols, (8)voice communicating, (9) recalling procedures and positioning movement,10t) steering and guiding, continuous movement, and (11) performing
qrross motor skills.
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20. ABSTRACT (continued)
The training strategy for each class of instructional objectives ismade up of three parts. The first is a definition of the class and adescription of the uniqueness of each class. The second is a set oflearning guidelines, consisting of a series of statements which prescribespecific learning elements to be built into the design of a trainingsystem. These guidelines are based mostly on learning theýory and somewhaton practical experience. They represent information available forprescribing general solutions for a class of training problems. Thethird part of each strategy is a learning algorithm. The algorithm isexpressed as a flow chart of a sequence (or system) of learning events.It represents a logical arrangement of the events called Tor in thelearning guidelines.
These guikelines and algorithms may be used by training systemdesigners as guidance in (1) specifying learning events and activities,(2) selecting instructional delivery vehicles, (3) designing instructionalmaterials, (4) evaluating existing instructional materials, and (5)recording field experience for use in improving the guidelines andalgorithms.
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TAEG Report No. 23
LEARNING GUIDELINES AND ALGORITHMS FORTYPES OF TRAINING OBJECTIVES
James A. Aagard, Ph.D.Richard Braby, Ed.D.
Training Analysis and Evaluation Group
March 1976
A... i, ; tl ,,; " '
GOVERNMENT RIGHTS IN DATA STATEMENT , ;.
Reproduction of this publication in wholeor in part is permitted for any purposeof the United States Government. ,,....
ALFRED F. SMODE, Ph.D., Director, B. G. STONE, APT, USN
Traininrc Analysis and Evaluation Group Assistant Chief of Staff"Research and Program DevelopmentChief of Naval Education and Training
TAEG Report No. 23
TABLE '.Y ON)TNTS
Section Page
FOREWORD ................... ............................ 4
INTRODUCTION ......... ......................... 7
Purpose and Use of the Report ........ ............. 7Background ............ ....................... 8Organization of the Report ....... ............... 9
II LEARNING GUIDELINES AND ALGORITHMS .............. . .11
A. Recalling Bodies of Knowledge ... ............ ... 17B. Using Verbal Infor'mation ..... .............. ... 23C. Rule Learning and Using ..... .............. ... 27D. Making Decisions ...... .................. ... 32E. Detecting ........ ..................... .... 39F. Classifying ................................ 7G. Identifying Symbols .......... ................ 51H. Voice Communicating .......... ................ 55I. Recalling Procedures and Positoninc Movement . . 6J. Guiding and Steering, Continuo,; Movement .... r9AK. Performing Gross Motor Skills .............. ..
I RECOMFvIDAT O01S .......... ....................
E .- . .:r, • , . . . .... ............ . .. .. . . . . ....... . .. ....
GL•';• ?Y.N'
TAEG Report No. 23
LIST OF ILLUSTRATTnOs
Figure pg
1 Learning Algorithm for Recalling Bodies of Knowledge 19
2 Learning Algorithm for Using Verbal Information ........ 25
3 Learning Algorithm for Rule Learning and Using ........ 99
4 Learning Algorithm for Making Decisions ............. ..35
5 Learning Algorithm for Detecting .... ............. .. 42
6 Learning Algorithm for Classifying ...... ............ 49
7 Learning Algorithm for Identifying Symbols ............ 53
8 Learning Algorithm for Voice Commiunicating ........... 57
9 Learning Algorithm for Recalling Procedures andPositioning Movement ........ ................... .. 64
10 Learning Algorithm for Guiding and Steering, CotntinuousMovement ........... ......................... ..70
11 Lea-ning Algorithm for Perforrminq Gross Motor Skills . . . 75
LIST OF TABLES
Table Page
i Eleven Types of Elemental Learning Tasks ........... .. 12
2 Algorithm Symbols and Meanings ..... .............. .15
TAEG Report No. 23
FOREWORD
The guidelines and algorithms of this reoort are intended to teused by experienced professional training system designers and ne>swho will be tasked with the planning, design, and utilizatior cý tr,3irinosystems. These professionals should be versed 'n the osychobcz:'v -flearning and be acquainted with the terminoloqy.
A simplified version of these guidelines has been oublished •eparateyby the Navy for personnel inexperienced in the application of the psychoi-ogy of learning. The translation of these quidelines was made by theCenter for Educational Technology, Florida State University. and theresulting nontechnical guidelines are presented ra a par t of 'Ih-,\'T106A, the Interservice Procedures for instructi"on Systems k.. • ...(August 1975).
These guidelines and algorithms are suopor'ed by varvir, a.....ns Ofempirical data, but all have at least a basic core of empirical supnort.The categories of tasks are neither comprehensive nor entire•• i-,eenden,of each other. Finally, it is important that these cuidelines andalgorithms should be used in conjunction with another report ( -Braby,Henry, Parrish, and Swope, 1975) which concerns job task cateqories,training media, and training cost factors to fonn the widest possiblebasis for decision making in the design of instructionia programs.
TAEG Report No. 23
ACKNOWLEDGMENTS
The authors wish to thank members ef the Center for EducationalTechnology at Florida State University for encouraging the deveopmentof the guidelines and algorithms and for suggestions on simplifying theguidelines. Their suggestions grew out of their editing a draft ofthese guidelines for incorporation in the Interservice Procedures forInstructional Systems Development. This effort was directed by RobertK. Branson, Gail T. Rayner, J. Lamarr Cox, and Wallace H. Hanwium.
Appreciation is also expressed to Gene S. Micheli for valuablesuggestions and inputs to this report.
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- j TAEG Report No. 23
SECTION I
INTRODUCTION
In the process of designing training systems, professionals havebeen inconsistent in integrating available knowledge and principles onhow people learn. Frequently, the translation of psychological learningprinciples into practices useful for the classroom has not been accomplished,much to the detriment of the instructional program. Since siqnificanttraining gains can be made through the application of these principles,guilelines which assist the designer in the translatioe nf bas C conceptsof learning into descriptions of specific action to be4 aken h,. needed.To solve this problem, the development of standard uice-lines f",r t)"structuring of training materials is being seriously examined.
PURPOSE AND USE OF THE REPORT
This report summarizes in a simple, redily usable format, thepsychological learning principles applicable to the traininq of comonmilitary job tasks. It provides guidance for training system designcrsin defining basic learning events which reflect research findings on howpeople learn specific types of tasks. The use of algorithms (in theform of flow charts) to display learning guidelines in a manner thatemphasizes the flow of events and the combining and sequencinq of learningguidelines in the design of a training program is aiso demonstrated.
These learning guidelines and algorithms were used in the develop-ment of the Instructional Delivery System Selection Charts in the basicTraining Effectiveness, Cost Effectiveness Prediction (TECEP) report(Braby, et al., 1975). As such, this report serves as background informa-tion on the TECEP technique and also serves as an aid in carrying outvarious steps in the TECEP technique.
The learning guidelines and algorithms presented are expiessed innontechnical language. They have been developed from the more formalbase of theory so that principles of learning might be -ore widelyunderstood and used in the design of training systems.
Certain constraints must be considered in the uti7,zation of theguidelines and algorithms. First, these guidelines are general approaches.Their relevance to given training settinrs -,nust be carefully ascertained.The task categories and related guideýines are not at 7 level that wiVaccommodate any training setting. In ,it may not t..possible to match a given job task with a defined task category. I,other instances, it may not be practical to fully --ie-.ent every learning:jideIi ne. In these situations, the training system designer should use
the quidelines that do apply to the given trnairirl situ tion.
TAEG Report No. 23
It should be noted that the algorithms representing the learningguidelines are not the product of empirical research but are the productof rational study. While each of the guidelines can be supported withexperimental evidence, the algorithms based on the composite of theseguidelines have not been validated; such validation is beyond the scopeof the present study. Innovative training methods, based on the guidelinesand algorithms, should be tried in pilot studies, evaluated, and modifieduntil they function properly before applying them widely throughout theNaval Training Command.
BACKGROUND
Various attempts have been made t9 translate specific principlesand concepts into general guidelines for training system design. Mosthave fallen short in that they have not adequately attended to the fullrange of tasks that occur in military or civilian training programs.These previous efforts have been less than satisfactory for use in thedesign of military training programs. Several of the more siqnificantefforts, however, are worthy of note and are described next. B. F.Skinner (1954) transformed a series of principles of learning into a setof rules for writing and using programmed texts. By following theserules or guidelines, educators were able to write arogrammed lessonsbased on the principles. These rules were subsequently refined (Hollanl,1960) as a base of experience accumulated in programmed learning.
Other attempts have been madr ('1951r, 19. Sheffield, 1961;Lumsdaine, 1964; Ellis, 1972) to translate specific principles derivedfrom learning theory into guidelines for desigrino 'riining systems forspecific types of learning tasks. A noteworthy vFforz in this regard wasmade by Willis and Peterson (1961) in which they analyzed the principlesapplicable to training of nne major iearnini therists ind identified alist of learning principles comron to them i 1. Fifty-one guidelineswere developed from these common concepts and these were matched with 19types of Navy training task:. These Sets of guidelines were intended tobe used as checklists for the design and use o' t-aininn devices.However, the guidelines were e;,pressed in lar'>•ce that was too technicaland abstract to be useful for most instructio-a' des-gners 7nd they didnot deal with all of the important issues related to -he des'gn oflearning sequences.
One of the most widely-read attempts to translate learning theoryinto design g'uidelines is that of Gagn6 (i965) 7Tght types of learningwere identified and the conditions of lea'ý-nina fnr each ty•e described.This work was later refined by Gagne and Briggs (797d) who identifiedfive broad cateqories of learninq outcomes and descibed the learninanrincioles associated with these types of learning. in both stddies,:e `: s c 'i-tions of learninq were written in t'e 'anguage o the educatorr"d tne -esigner of training prograc s and not •n the technica7 language
) TAEG Report No. 23
of theory. However, Gagne's taxonomy of learning classes cannot beeasily applied to the broad range of military job tasks.
A more comprehensive guide is needed to translate learning principlesinto leai-ning events for military training. The TECEP technique (Braby,et al., 1975) was developed by TAEG to provide the Navy training establish-metit with learning principles appropriate to Navy job tasks and to outlinea method of choosing cost-effective instructional delivery systems thatsupport the use of these learning principles. The TECEP techniqueincorporates the use of learning guidelines based in part on those usedby Willis and Peterson (1961) and by Gagn9 (1965). Additionally, algorithrswere developed to make clear the combining and sequencing of the guidelines.In the TECEP technique (1) common classes of training tasks are defined,(2) a set of learning guidelines and an algorithm are presented for eachclass of training tasks, (3) some instructional delivery systems capableof carrying out each set of learning guidelines and algorithms areidentified, and (4) a cost model is provided for use in projecting thecost of using each instructional design alternative in a specific trainingsetting. Design decisions are based on estimates of both the cost andeffectiveness of the various approaches.
ORGANIZATION OF THE REPORT
In addition to this Introduction, two additional sections arepresented in this report. Section II presents descriptions of 11 basictypes of learning tasks with learning guidelines and an algorithm foreach. Directions for the interpretation and use of the algorithrmsare also presented. Section III contains recornendations for trainingsystem designers concerning the application of the concepts presented inthe report. A glossary of some technical terms used in the guidelinesand algorithms is appended. References are also cited which support theconcepts in the learning guidelines.
TAEG Report No. 23
SECTION I1
LEARNING GUIDELINES AND ALGORITHMS
Learning strategies are presented for 11 types of common militaryt-aining tasks. Each strategy contains (1) a description of the type ofjob tasks to which the strategy can be applied, (2) learning guidelines(general principles) that will produce the most efficient student learningof these tasks, and (3) an algorithm which combines and sequences theguidelines into a flow of events.
This approach assumes that human learning of specific job tasks canbe prescribed using generic classes of learning events and job taskcategories. By limiting the~number of classes to be considered, theprocess of prescribing solutions is simplified. However, it should terecognized that a high degree of artificiality is inherent in this typeof classification scheme. Subtle variations in both job structure andappropriate learning activity are not accommodated. Also skilled perform-ance of a job task usually requires the perfon-mer to respond with complexbehavior that cuts across the classes in simple classification schemes.Since the guidelines and algorithms presented in this section are basicprescriptions, the training system designer should adapt these solutionsinto more sensitive responses to the specific requirements of the learningsetting.
The guidelines and algorithms can be applied most directly to theearly phases of training. After mastering the elemental tasks, thestudent proceeds to combine difforent types of .!.Tmental tasks intoperformance segments, phases of a mission, and full mission performance.While individual guidelines are still valid at these higher levels ofiearring, the application of the algorithms will not necessarily beapý opriate. The guidelines and algorithms should be used with thesecautions in mind.
Table I describes the 11 types of tasks for which learning guidelinesand algorithms are provided. By matching the general characteristics ofa training objective with the action verbs, behavioral attributes, andexampnles listed in table 1, the appropriate guidelines and algorithmsca usually be identified. Where a clear match cannot be made, a singleappropriate TECEP learning strategy may not exist but a combination ofseveral may be required. In these instances the designer may find itnecessary to build frum the guidelines 4nd algorithms in this report alearning strat ngy that rieets his specific training requirements.
The glossary appended to this report defi e; the technical termsused in both the learning guidelines %nud the algorithms. The different•'inds of symbols in the aigorit•mis are uspd as ty-Yes of instructions.The meaning of each symbol is described in table 2.
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TAEG Report No. 23
TABLE I. [LEF'FN TTNIE Or El F 'INIAt I ,1 AIR1 1r i 1. AMf,,
NAMES OF CHARACTFRISTICS Of TRAINING OBJECTIVF WITHIN TAh (All iSL EA RN IN G j .. . ... .. . .. . .. .. . . ... ... .. ... .. . . . .. . .. . . . .
TASKS I ACTION___ VERBS - .LdAVIORAL ATTRI[BUTES -XA --- 'L I IS
1. RECALLING Answer I. Concerns verbal or 1. Recald ing equipimet neoimn-BODIES OF Define symbolic learning. claturo or functinns.KNOWLEDGE Express 2. Concerns acquisition and 2. RecallirmI system tun t i on-,
Inform lonq-term maintenance of such as the complex rela-Select knowledge so that it can tinns between the systtm's !
be recalled, input and output.3. Recallinq phy.,ical laws,
such as flhr','s law.4. Recallino spec ifi(: radio
frequertc ivt, and Ot her
------- -------- discrete .acts.
2. USING Apply 1. Concerns the practical 1. Based on academic knrwe,1m;c.VERBAL Arrange application of d(htet:r';' which equipment tcINFORMA- Choose information. use f ,, 'pecific realTION Compdme 2. Generally follows the world task.
Determine initial learning of 2. lased on an academic ,nowl-information through the edge of the rystem. compareuse of the guidelines alternative modes of opera-for Recalling Bodies tion of a piece of equipmentof Knowledge. and determine the aporopri-
3. Limited uncertainty of ate mode for a specific realoutcome. world situation.
4. Usually little thought 3. Base, on memorized knewledqeof other alternatives,. of radio frequencies. ch(oose
the correct frequency in aspecifir real wnrl(C situa- "
_________ -_____ ion.
3. RULE Choose 1. Choosing a course of 1. Applying the "rules of theLEARNING Conclude action based on apply- road."AND Deduce ing known rules. 2. Solving mathemitical equa-USING Predict 2. Frequently involves tions (both choosing correct
Propose "If... Then" situations. equtior ind the mechanicsSelect 3. The rules are not no •olving the equation).Specify questioned, the decision 3. Carrying nut military
focuses on whether the protocol.correct rule is being V. Selecting proper fireapplied. extinquisher for different
type fires.5. Usinou correc,-t gramnmar in
novel situation, covered
4. MAKING Choose 1. Choosing a course of 1. Choosing frequencies toDECISIONS Design action when alternatives search in an FCM -Xerrh plan.
Diagnose a-e( unspecified or 2. Chm'sinoi tor-ieo srttingsDevelop unknown, during a torp'nio• itott.
Evaluate 2. A succE;s ful course of 3. Assigning wemiýon based onForecast action i,, not readily threat ovalt;aticn.Fornulate apparent. 4. Choosing tactics in com-Organize 3. The penalties for unsuc- bat - wide ranqe of options.Select cessful courses of 5. Choosing a diaqnostic
action are not readily stratpey in dealinq with aapparent. N., malfunction in a complex
4. The relative value of piere of eoinirtrnt.
be cons ido r-el - includ- nvl',,i, .'1 5' jii gr[ 'l i t-inq pos.,ible trarle oft', ing 91 f ri i t i l point in
I ~ ~ 5 fre'iurntly involve-s 01,," i•I,,u
; forced met io', " 'on
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TAEG Report No. 23
TABLE 1. ELEVEN TYPES OF ELEMENTAL LEARNING TASKS (continued)
NAMES OF CHARACTERISTICS OF TRAINING OBJECTIVES WITHIN TASK CATEGORIESLEARNINGTASKS ACTION
VERBS BEHAVIORAL ATTRIBUTES EXAMPLES
5. DETECTING Detect 1. Vigilance - detect a few i. Detecting sonar returnsDistin- cups embedded in a large from a submarine target.guish block o' time. 2. Visually detecting the
"monitor 2. Low threshold cues; periscope of a snorkelingsignal to noise ratio submarine dur-nq daytimemay be very low- early operations in a sea stateawareness of small cues. of three.
3. Scan for a wide range of 3. Detecting. through apcues for a giver "target" change in sound, a bearingand for difFerent types starting to burr, out n aof "targets." power generator.
5. CLASSIFY- identlfy 1. pattern recognition aP- 1. Classifying a sonar target as:NG Pecog- proach of identification "sub" or "non-sub."
nize - not oroblen' solvino. 2. Visually classifying aDi'er- 2. Classi'ication by non- flying aircraft as "friend'entiate verbal characteristics, or "enevy" or as an ,'
Classify 3. Status determination - 3. Deterrinino that ar identi-ready to start. fied noise is 3 wheel bearin;
4. rýbect to be classified failure, not a water pXuocan be viewed from many failure by rating tre oualit÷oerspectives or in many o0 the noise - rot by the'orvs. Problem solvino approach.
" :'H'T7Y- identify 1. 'nvolves the recognition 1. Readinc elect-onrc symbols,%C Oead of symbols. on a schemaLic drawing.
S"vBCLS T7an- 2. Symbcls to be identified 2. Identifyinc nap s'yibtos.
scribe 'vvicaliv aee of low 2. ?eadirg and tra,!crtb-cmeaningfulness to symbols or a tazticaluntrained Persons. status board.
3. dentif.cation, not 4. identi'yin• s,'-zolS
interpr-etation, is weathe' man.eI'ohasized.n. nvoives storing oueues
of srybolic informationand related meaninos.
1'OCE Advise 1. Sneaking and listening 1. cficer oino C',a CersCOM"U•2- Answer in soecialized terse ant receivino 'e::"c ..AN'G Lornuni- lanauaqcs. 2. Scna- operate,- :ass-• 0.2
cate 2. O')te.i involves the use itr-ation c;er cO-7.l,-Converse o0 a soecific message cation ret.Direct model. Standart 3. Instructiors bv S:'Exoress vocabulary and format, operator to oilot in:'st-uct 3. Also concerns clarity Co , antinc airc-.3:.interview v'oice. enuncaetion,List speed.Order a. -iTinq Oc verbalizationDeport is usual!y c-;ttca. -Speak when to oass i"-o-at~cn.
5. Typically cnaracte.-zedby redundanc, " te.'sof in'cr"atio.ý ýcotert.
6. Involves extensive •sec, 0-evicjsl! o,,e-lea-te
,,qtta, s'.i'ls, o)r ýercin1A O.Jewjc v-ned te-'erir :-':r-:. N" Reproduced from
7. asL may ne diffiwiolV d best available copy.t, oresence ..' :s.
13Best Available Copy
TAEG Report No. 23
TABLE 1. ELEVEN TYPES Of ELEvE*4TAL LEARNING TASKS (continued)
NAMES OF CHARACTERISTICS OF TRAINING OBJECTIVES WTTH% 7AS, C47EGORlESLEARNING -
TASKS ACTIONVERBS BEHAVIORAL ATTRIBJTES EXAVPLES _
9. RECALL- Activate 1. Concerns the chaining or 1. Pecallinc ecuipmentING Adjust sequencing of events. - assemblv and disassemiblyPROCE- Align 2. Includes both the cognl- procedures.DURES. Assemble tive and motor aspects 2. Recallino the cveraticnPOSITION- Calibrate of equipment set-up and and check out proceduresING Oisassem- operatina procedures. for a piece of ecjimentMOVEMENT ble 3. Procedural check lists (!cockw;t check hists.
IfSDect are frequently used as 3. Followira equintnent turn-on.Operate job aids. prccedu"e - a, i• orService motor bekav'-,.
O. GUIDING Control 1. Trocking. dynamic con- I. Subrarine bow and sternAND Guide trol: a verceotual-moto- plane oDerators aintainWcSTEERING, Maneuver skill involvinq cortinu- a consta~t cur.se. orCONTINU- Regulate ous pursuit of 3 target aknlc chýnes ýn cou-'e ýrOUS Steer or keeoine dials at a det1h.MOVEMENT Track certain reading suCh as 2. TaVk d-veý 'C7O1*rc a
maintaining constant road.turn rates. etc. 3. Sonar operate, keepinc tke
2. Coonsatory roveents cvrsor o- a rcnar t~rnet.based on eedback fro-n . ;;r-to-air cunnern - taroetdisplays. trackirc.
3. Skill in trackl'n 5. Aircraft vilctinc sict asrequires Smooth muscle visual'y I^*- -CW acoordination oatter's - courd patn.lack of overcontrol. 6. w'ers-ar 'cld•r a co.rse
4. Involves estinatinf, wit r or -at--icchances in positions. ccw"os5.velocities. accelera-tVons. etc.
S. involves knowledqe nfdisolay-controlrelationships.
"PERFORm- Carry i. Perceotual - mrotOr I. fr' a -eelirc :osit•c-.ING Creed behavior - ermhasis on trow.a, T ¢c'•ertatzGROSS Fall rotor. PrW, um on hand crerade z: 7ete- orMOTOR 'urn manual dexterity. occa- target wittir e'ec-%eSKILLS Lift sionally strength and casualty radijs E,'"' s
Run endurance, acceptable tecnnizwe.Swin 2. Reoetitive mechanical 2. iearin; a utility !acket.Throw skill. utility trcusers, cO'bat :•:
3. Standardized behavico. and 3r-ed wlth mlf -i'*e.little room for varia- traverse "5 -ete, 'rn e:tion or innovation. water -,simn correct Ic--.
"4. Auto-atic behavior - D 3e--orstrate te _•erererlow level c, attert~c- tc:hrluoe 'C, '. -aa,-e
oneratce. Kinesthet~c o:er :e,'-.
tekav~c', te• c'C creec•2-c
S. %atice C', boredy -ay at n;ckt a'-oss ::c-beco-e a factcr ýre- terra- a'-e x th aski2• is oe.';"-ec :ve' i•
an extended •eoe.-' S. Dccst'ae :he :'e-e.-ti!e 0" at a r.:id 'ate. tehnic:e c' c'-:s. ne tCoe-a-ces. stertinc Ire- ceac
harng zalr~s toward 'ace
___ C_ _ e_ _ Dositicr.
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TAEG Report No. 23
TABLE 2. ALGORITHM SYMBOLS AND MEANINGS
Symbol Meaning
A decision or branch point-divides the flow into 2 ormore paths.
Informatonor Ipformatlon or directions for
Direction program designer or rtudent.
Student Represents studenW responses.0 ,either a, answer rr movement
Action to a new block in the flow.
NA special sequence of events notSub-routine presented in the flow, such as
a oretpst.
A file of rules, exercises, orstudent scores; any of theseitems can be called up asrequired.
0 A technique for connecting theReference student action lines on two pagesConnector of a flow chart (or algorithm).
START A syrbol for starting a flow orstopping the various paths of
or that flow.STOP
TAEG ReDort No. 23
The 11 learning strategies are presented in the remainder of thissection. They appear in the order listed in table 1. Since each strategyS-deflned in operationd' terms, it may at times be necessary to refer to
t-ýNle I and the glossary for clarification of key words.
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TAEG Report No. 23
A. RECALLING BODIES OF KNOWLEDGE
This category encompassi-- the learning, recognizing, and recallingof the verbal informatio, ne 1.ed to function in an operational setting.It includes knowledge of equipment nomenclature, functions, configurations,locations, control inputs, output displays, and the complex relationshipsbetween inputs, outputs, and possible equipmernt malfunctions. Mostacademic training is of this kind, and therefore students learning thesetasks have been readily accessible as subjects for investigators studyingthe learning and recall of verbal information. The following guidelines;7ý, :! : o a •.-!-tnn ef the findings of this research. The algorithm
vrsssiin1r: n',*- i,;%la es is presented in figure
1. ctajecti,&;s of tta'r. to '-.. :-udent at thebirlnnirq of tho trani,• ercio;.
2. Orrýýiii< the learning n,ýwa-; i.Al to rieet the stated objectives.Organ" ze tr, i:a;^jurjd imtort•int cuP comnonlants ik-t ;*A :ds, formulas,or phrases) withIn :."C bo.y of facts o0. p;c•-:h'.
3, Pro)vide some w:..up exerCises i*r-ediateiv rrior to testing'or recalling bodief of' ýnowledqs.
Mz..:e le'-'ning tasks relevant; i.e., similar to real-life tasksrthat toc st',t will Le perforr,ýng on the job,
S. Cimpare direct l y the names or other dica that are similar, orseparate their presni..t'on by as much tiri w possible to avoid confusion.
6. Make svre the 3tudents can , th., difference between two ormore salient cue, that are difficult to d, Ainguish in the operationalcortvt bEfore ,ssoiatir. each with ; -:ponse during training.
V3. Ps_ mnemonics (assoi-t)r; ýe' , ces) which will cause an affectiverea,:tionn 'the student to aid -tica":•i .enever possible.
8. 6.e mtiemonics whtrl ." i'K : . in the association of the cue andDonsa teis in the rec&ll ;,a;as or principles. Provide directions
..e stiddent to develop his ow0 inemonics if he can and wants to dro
9. F. r fea:'-ures if the real-world job set.ting to be usedto trigger t fs rec-,! l of associated cues w,,hich, in turn, wi-lcall to mird the K,,. .ae >,a needs to perr-r his joý.
10. Select attention--. -'`.' cuss to us2 throughout the Iearning
events. Select learning act-iviti- 't rsouire stude invo veimsn.
3 st Avai !e cony
TAEG Report No. 23
11. Guide (or prompt) the student's response, especially in theearly phase of training. Later in training, remove guides to match thelevel of guides (or prompts) in the operational setting.
12. Arrange for practice of recalling the verbal information byproviding retrieval tests very similar to the tests that the studentwill encounter in the operational setting.
13. Require the student to make an overt response which will showhis recall of the facts or principles which, in turn, will enable measure-ment of his response.
14. Arrange for knowledge of results (KOR) to follow both correctand incorrect responses. Also arrange for positive reinforcement to beinterspersed throughout the training following correct recall of facts.
15. Schedule KOR to be presented immediately after a response formaximum effect of KOR.
16. Change the order of presenting facts and principles duringpractice so that each item in the list of information will be learnedequally well.
17. Practice should be distributed (interspersed with rest periods)during training periods especially with (1) the learning of large bodiesof facts or (2) complex information. This is particularly useful withslow le'arners.
18. Individualize instruction to the extent possible. In orderfor slow learners to reach the same criterion as fast learners, arrangefor slow learners to have a higher total number of reinforcements ofcorrect responses than the Yast learners.
19. Arrange for the student io compare the program's stated objectiveswith his status in meeting these objectives (use periodically).
20. Test to determine if the student is able to correctly recallkey features of the job setting which serve as cues to him in recallingthe knowledge he needs in performing his job.
21. Prevent decay of recall by:
a. Increasing the meaningfulnes' of the material to be learned(relating it to the student's operational environment) and by relatingthe organized facts or principles to each other.
b. Requiring the student to overlearn the origi~ial materialv'• eential orocedure to reduce forgetting).
State:* Jbjectives*Organization of Program*Type of Assessment*Show how this knowledge will
be used on the Job
(*)(1 )(2)(4)(18)
wan the Coerriespod to gui eln numer o hs STOP
Testcfeso
select first/flextfact fromt set
Preset _th 14AIIE of the fact~ in'
sucht ah wY that~ ditI asoiatewit KE ,IORDS do thei defin witio
ofdi dfnn the fat soiat.e o the~ fý t
WOD Usth th~e etr dd refinition
Use moderate fvrrtion-lalen
wj A~ yor~trnw c whor eain poodi, TfKoweýCkortnud20_ gttn
2
*oe the MEY DemnS o etci t e fua neiiln
(4)een SPECIFIC ovor responoseettuon
THINGI re pneed otaloaon arndn Peod scrn atodicmntec'ianaeL orderPT nonexd mo ofes
o rganied in tostsi st
(16)0
rosontthat:
roj') Reqireovrt espns
((13)
Ovurin . Lerirjihoih foriton Pres2ing Roiria ofKowes (otiud
Yes More Po at
4 sets in tPoolI?D
No
Reinforce-moen t
Select tem tfro p o cl orwndactionse oreali rcresponer t :'d r eqnl: or* Disto fr ltributed practice
relea rtto peraion a t tas
FlrjurCue 1.o LerigA rthm fprtora settinging Bodirutue of Knwlde (cotined
(1)2? ' ~) 7h
TAEG Report No. 23
B. USING VERBAL INFORMATION
This task category involves recalling and applying previouslylearned facts and principles as needed in a job setting. It is a compon-ent of most jobs. In tha guidelines for this task category, attentionis focused on increasing the transfer of learning from the classroom tothe job. An example of using verbal information is that of a radaroperator faced with a tactical situation where a change in antennasearch mode might increase the probability of the detection of an expectedtarget. The operator recalls the various modes and their characteristicsand then chooses an appropriate mode. This involves the application ofprinciples and concepts, not the application of a fixed decision procedure.
The amount of empirical data which supports the guidelines for thetask category is meager. Uot much research has been accomplished on theapplication of knowledge in the operational setting. Traditionally, theemphasis has been on acquiring knowledge in the classroom with theassumption that if one has previously learned the knowledge he caneasily recall and apply it when required to do so on the job. But thisassumption is not always warranted. Students have considerable difficultyapplying in the operational setting that which they learn in a rotefashion.
The following guidelines apply to using verbal information. Thealgorithm representing these guidelines is presented in figure 2.
1. Insure that previously learned verbal information is organizedinto generalizations, unifyinQ concepts, and principles to promotetransfer as the first step in training how to use verbal information.
2. Give the learner practice in applyinq the generalizations andunifying concepts to tasks similar to those in the operational settingthat he will be encountering.
3. Provide knowledge of results as soon as the learner has madehis application; provide reinforcement for his correct applications.
4. Require that practice in applying the principles covers thewide variety of operational situations that- the student will be presentedwith on the job.
5. Provide examples of application; of morc abstract principles orgeneralizations that have been shown tote difficult to apply to theoperational setting.
6. Reinforce the student when he makes practical applications ofverbal I"foration.
L23
TAEG Report No. 23
7. Ensure practice until the student achieves job entry level ofskill.
8. Vary both the context of salient cues and the principles to beapplied during practice.
9. Provide for refresher training when there has been extendedabsence from the task or where such training is indicated by performanceon the job.
10. Give job sample tests ("dry runs") in the operational settingoccasionally to determine need for refresher training, where this ispractical to carry out.
11. Provide for individual training at student's own rate.
State:
9 Objectives0 ,irganization of Program0 Type of Assessment0 Relevance to operational setting
Noo
Organize information into:
"* generalizations"* unifying concepts"* principles
Require overt response
C UX ) Car s o d no g i e i e n z e o h s t s
stude nt ;k~iK Nor LSub-e~a 7ml
Pool of PracticalExercises: 1Logic for selecting
* repreentpeacblfmth9rpeetecoftgeneralizations, unifying fraypicpe nv
concepts or principles. from simple to complex
on-represen sthe transe Select and display * ensure full range of opera
on-rythe-o situation s first/next problem tional situations are
of examples 0 fo polsecd* inciude examples of (2)th rero rolm
abstract principles Overt Response in terms of principles and
required in opera.tionalthopr ina se ig.
appl prncipes.KOR(including correct
(1)(4)(5) (8) sltos
(I(3)
Yes
enforcement
2. K r~ii2 Ari~oith forU~ifq V roal n Criateion (crornntivc'd
c) TAEG Report No. 23
C. RULE LEARNING AND USING
This category of job task concerns the acouisition and applicationof established practices or fixed principles (rules) that serve asguides in selecting courses of action. These rules may be based oncurrent practices or on a knowledge of what normally happens in similarjob situations. Rules are frequently expressed as "if-then" statementsor directives not to be questioned by the user. The user merely concernshimself with whether the proper rule has been selected and is beingapplied correctly. There are many examples of rules that must be learnedand used. Typical examples include using rules-of-the-road in guiding aship through inland waterways, solving mathematical problems using therules for manipulating numbers, using correct protocol in displaying theflag in a formal ceremony, applying grammar rules in writing a sentence,ard writing a computer program according to the rules ofka specificprogramming language. Although rules are commonly used in selectingcourses of action, limited research has been performed on learning toapply rules. The learning guidelines are based on the available researchand general learning principles, where appropriate.
Guidelines for rule learning and-using are listed below. Thealgorithm-representing these guidelines is presented in figure 3.
1. Insure that the individual words which comprise the rule areunderstood before proceeding to rule learning.
2. Require that the student state the rule verbally. Thisverbal statement of the rule serves to cue the recall of the conceptsthat make up the rule and their arrangement within the rule (this usuallyshould be an informal statement of the rule).
3. Present examples showing when the rule applies and when itdoes not.
4. Use mnemonics (where possible) in the learning of difficult torecall rules and the application of these rules. Use cues from theoperational setting in the mnemonics to facilitate the recall of themnemonics.
5. Give the learner an opportunity to apply the rule in newsituations and give knowledge of results following each application.Provide reinforcement for correct applications of the rule.
6. Test the learner by requiripg him to state the relationshipsamong the concepts in new situations to insure that he understands therule.
7. Provide practice in applying the rules until the student achievessome stated criterion performance; i.e., until he learns the rules and
27
TAEG Report No. 23
learns to apply the rules across the range of situations he will find inthe operational job setting.
8. Reduce the frequency of reinforcement of correct applicationsat the end of training to a level'that exists in his job setting.
9. Relate the rules to be learned to the operational job settingin order to provide motivation for rule learning.
10. Provide for (1) individualized learning to allow for individualdifferences in learning and (2) periodic refresher training when thestudent has had an extended absence from performing the job.
11. Guide the student to discoyer a useful rule by having himrespond to a sequence of leading questions, if the student is having adifficult time understanding and applying a rule.
12. Arrange for slow learners to have a higher tot-! number ofreinforcements of correct responses than the fast learners.
28
DSTATE:
bjKtiv" - CtittrionOrgarizAtiort of pnnrar,
Me Pool Type Of assessairmt
For "st of M 0 Relevance to owationAl satt.,gF-106'TAT
e por each rule:
(9)'ISa pr requisite
4:orzepts
a"Ptest itms0 ranr of ex"les
oto6Aich vary In difficulty Dora of tion-exaMlits )r ) waot
cl very in difficulty the crtttl-oft C.T.im"monics teIC7
0 test Items lowich vary I"
difficulty, and apswm
t n
- remedial data on
iIexpected wrong ens.*rs0 .1dinted oulkstions 7 .
No
hat I#Ad 4
"';v -y toM 'Oil , 14 n-tng of the vlf. SAPIOCt fIr ".*.t utt 3
Awfolit" pr*-t t to 0"*"4.o it sý.J*.% caý rww iA
the Ot", c cwK#Vi% Pcý I" '41it t% Wi It.
kil 4
c It, 4-ýI v--d-
"scribefTrt
If -w4w,
toto dv- oo
Trst, 'to dete-l't 11 std"t caý ýtate,ul eb !If
c-r-p-.d. t"
,loure 3. Learning Aigorith-m for Pule Lear no- and Usingn 41
Present job oriented examples of:0 ~ rule O"lles*p Am not applicableresent - we" cs. if required. EmpMsize cues frow job Setting.
(3) (4)
TestN!w Man Present noval situation repvS"ting a jw talk WWI. the
rule(%, ney or may not be wW. Require student to stateWhich rule applies and to recall that rule.
Student recalls and -. ;'.a.
Was NoS'Llde". S.0,COirrecir (Orly fc, the st.4*"t na-Ing
sllrious 411"IC."Ity: PlDtAtodq0titICIIS tI.It Wilt tint !ýA-k-
I" in Nis j4de"I fol a, Vf1wit"e.
< f
105t" ;tvd"f present %Oýy the ruleI# 4.01or '&to for imawoortatOa explain thr relatIOWIP an"t1w concept in the rule.
(6)
M
40Itod"tccwrvct? Wnly ?ý,r stud"Its kAvt-, wfo,ý
jffflcuý'.Y: 0-ted t"'.
9040 too learn" in W% s A;-ý, 'C'
an wf-de"lanlin I t, ýe 47 e
110 "an Cont.1140 wlt
CrIter ,,n I . CIPSMA09*1Y CO-OKtb"M ýqt 4t -It
? 4.41 tc,
(7)
Y..
ReivfGýCe""t
Vlert. Itle"Ies,
Nr
z
- 1ý1"
Learning Algorithm Tor Rule 1,-,rning and Using (continued)
111) -
2
"res t status of student
Selection criteria:SelectionSelect prwl ele f ron. a j
0 Select problems for eachrule fron. a job example.or c r e
Selo-ct and display 0 For each rule sa-,iple fror,
first/next practical range of easy to difficull-
Rule problvn on any rile in problers.Pool 9 Continue to sample data on
the pool. Student rules until "X" consecutive.< recalls correct rule ly correct answer cre ob-
Ii and applies it. tained for a tpecific ruleat the Muired difficultylevel to ,Patch tneoperatiOn4l setting. j
Periodic KOR J (3)(7)Rest
NoCorreti:7
Y es
Reinforc ".iit grad-uallý -Nuced toleve) that exists onthe
6-
No crileron
ret?(7)
beer,
>
Yes
Reinforcemoent
2)_
:,-lend at i on fortraining.
C top
con 1:1 nuedi r P 3 ýjg Algfj,'th-,,, for 'Rule LearnlnC ;,Ijld Usi,19
31,
TAEG Report No. 23
D. MAKING DECISIONS
Decision making is defined here as the application of a specificdecision model, thuught to be useful in diagnosing equipment malfunctions,choosing tactics in Fleet operations, and in planning where severalalternatives must be considered, each with an unknown probability ofsuccess. The decision model combines the following factors: perceptionof the problem, identification of alternative solutions, evaluation ofthese al.ernatives and selection of the apparent best solutions. There-fore, the guidelines and algorithm presented here support learning touse this decision model.
The decision-making guidelines presented here are based upon themost fashionable practices in existing decision-making training programs.
The following guidelines apply to decision making training. Thealgorithm representing these guidelines is presented in figure 4.
I. Ensure that the student acquires the knowledge required to:
a. identify the problem,
b. generate reasonable solutions,
c. evaluate these solutions.
2. Decrease student anxiety to a low level, particularly in theearly stages of training, where student anxiety is high and where complexdecisions are to be made.
3. Give the student examples of these two types of actions whichare tc be avoided when making a decisicn:
a. The tendency to make a "favorite" decision or use a"favorite" solution regardless of the real nature of the problem.
b. The tendency to generalize problems or view several typesof problems as if they were ell the same when, in fact, they are quitedifferent.
Give examples of these undesirable responses in decision making.
4. Teach a decision-mdking strategy; the following strategy issuggested:
a. Upon becoming aware of the problem, define it.
b. Be alert for the availability of relevant information andcollect such data.
32
TAEG Report No. 23
c. Develop alternative solutions.
(1) State alternative solutions,
(2) Combine alternative solutions,
(3) Compare alternative solutions.
d. Ev'luate alternative solutions.
(1) List the probable consequences of each alternativesolution,
(2) Rank each alternative solution according to desir-ability of consequences.
e. Choose course of action based on a desired solution.
f. Execute the chosen course of action.
5. Vary the setting of the significant cues of the decision-making learning task. Provide both basic and advanced problerms to besolved with a wide range of problem difficulty at each level of trainingfor the operational tasks.
6. Insure the overlearning of decision-making skills in laterstages of training if the student will be required to perform understress in the real world.
7. Present the student with a realistic data load (i.e., realisticamount of significant data) plus operational distractors in real timetoward the end of training.
8. Provide the student with access to potentially relevant dataduring practice. In the final stage of training, the data available tohim should be limited to that expected in the real world situations inwhich he will be working.
9. Provide the student with answers to the five following questionsafter his decisions in practice problems. These answers serve as knowl-edge of retults (KOR).
a. Predictability? (Were problems mistakenly viewed as ifthey were all the same in reaching solutions?)
b. Persistence? (Was usc made of a "favorite" solution whenit was inappropriate?)
c. Timeliness? (Wes this the appropriate time to execute
this particular decision?)
33
TAEG Report No. 23
d. Completeness? (Was all of the a',alable informationconsidered?)
e. Consistency? (Was the solution compatible and relevant tothe available information?)
Give KOR with respect to the above five criteria each time the studentmakes a decision and, if possible, provide the simulated consequences ofthe decision as compared to alternative solutions.
START
Make relevant to oPeraitional setting.
!he~re to:rasd"SO
cnrae rieaionabesltos
Adni luater oethes fors the foutot-es.
so te hniave anolletge that Suareo~ o nwc'e udl~~
" deti v te nt Tobler.b e~n~t e
yAlert student to avoid using favoritetsolutions anI1 viewing different types
of problems as if they were the sametype -give example
((3)
.1 ý rInes~ iol,
Selet a)ororiae stden Dr~reiWsý rN,
2
Student'dentiffes;denti -
iesSt-den
tyou datadata
more ýat reouireed Present
develc-. requireJY's
s soolution? Yes data
(4b) (8)
!40
Direct student to synthesize (re':itearw combine) useful solutions.
(40 S,tudent identifies what fie considers
+
,t,,d
Met be uselta be usefL;l solutiorsent n'
Does Yesstudent Yeswant KOR at
thistime?
NotoKN %n
adeizuate i ril-wi tit,%olutions, to, -it i on-,
Direct student to analyze protable conseotiencesof each ddequate solution; rink these solutiors.
(4d) ýtuder* ranks utefil
Croesstudertstudenz Yes ranked ',Otiorsw3rit KOR at y
this ccrsiste-ýtw;
Yes
j T",r
Oirecrec stuen t
(9()
select BEST solution.(4e)
ieiae KOR KR-h-ac
thehe dtshate diffictlty.of t bin st sholutid bes S cr~tevc I rs
thCreitrquew proble. Give feiback in ter of crito.rla forchoositn9 best $Olit'on, and oo~ssblt- conse-auenos. Analyze;tIudent actio)n Inl terms if: predictability, persistence.timlne1ss. completen~ess, and consistercy.
(9)
hi h , student out of be/ wwhen he"* choose$ not to use t
/ ~Immediate KOR
* scorrectly solves roblems ofrthe designated difficulty./ ~~~Data availat'le at this stage / .)
/ ~of training should be criterion • OJPresentSlimited to thAt expec,•ted in /r derforr-ame been status to
*C"rf the real worl% situations in / ,cri~eveý: / studentSw~~~hich the studcent will be /"
\ •~~.orking./Sssatisfies the overall L criteria
Sf%- decision strategy IYes*satisfieý overlearnlng
• rcriteria
•:!• ;re • n. Le rnin-j l.r it? 'or D',k ecisions (coT'nti ued
TAEG Report No. 23
E. DETECTING
This task concerns the act of becoming alert to the presence of asignal that could be of special interest in the performance of a job ormission. Detecting is essentially a matter of becoming aware of certaincues, including those almost hidden in distracting backgrounds, and itstops short of verifying the nature of the signals. In many practicalsituations after a signal is detected it is immediately classified. Theearly detection of targets is usually a significant part of any tacticaltask. Examples include an operator becoming alert to the presence oftargets on a radar or sonar display, a mechanic becoming alert to slightchanges in the functioning of a piece of equipment signaling an emeigingmalfunction, and a pilot visually scanning through the wirdow of hisaircraft and spotting another aircraft sharing his airspace. In thesedetection tasks, involving long period& of time between the appearanceof significant signals, maintaining vigilance is an important part ofperformance.
The following guidelines apply to detecting. The algorithm reoresent-ing these guidelines is presented in figure 5.
1. Train the student to use systematic overall search proceduresutilizing his appropriate senses. Use models of correct behavior, whereneeded.
2. Present signals from the full range of types of signals.Include the various signal sources that the student will encounter onthe job and the different patterns of each signal source.
3. Train the student to use techniques of vigilance to:
a. establish a mental set to search. Use instructions toestablish this set and reinforce the student when he achieves a properset.
b. constantly monitor internal biological cues in order todetermine own vigilance level (state of alertness).
c. use, where appropriate, peripheral vision in scanning;ie., to rely on detections made from the side of direct line of sight.
4. Train the student in detection skills according to the followingschedule:
a. Early in training use:
(1) high signal density - more frequent than in the.EltAtional task,
39
TAEG Report No. 23
(2) signals that have a high signal-to-noise ratio,
(3) different amounts of time between signal presentations,
(4) hiqh response rate from the learner,
(5) immediate and continuous knowledge of results (KOR),
(6) reward for responding to any real signal.
b. During the intermediate stage of training use:
(1) a lower signal density,
(2) lower signal-to-doise ratios,
(3) different amounts of time between signal presentations,
(4) KOR on an intermittent time schedule,
(5) specific vigilance techniques; i.e., mental set tosearch and monitor internal cues to state of alertness.
(6) intermittent reward for responding to real signals,
c. In advanced state of training use:
(1) low signal density; i.e., operational density orminimum number suited to training program,
(2) a signal-to-noise ratio comparable to the operaticnallevel,
(3) signals presented within different time intervals,
(4) KOR on a schedule equivalent to that found in thejob setting (describe realistic consequences for signals missed),
(5) vigilance techniques which are appropriate to the
job setting,
(6) operational level of reward following correct detection.
5. Train the student to use a cue detected by one sense (such ashearing) as a stimulus to search for and detect the existence of arelated cue in a second sense (such as sight) where it is possible todetect a target by more than one sense.
40
TAEG Report No. 23
6. Present the student with his status; i.e., progress towardsmeeting the trdining program objectives. Reward him for progresstoward these goals.
7. !Idividualize training. Keep student practicing at each phase(or level) of the learning task until the required level (or mastery) ofthe job perfcnnance is achieved.
41
START
State:0 Objectives9 Jrganization of Program
-Type of Assessmnt* Relevance to Operational Setting
you want Ye ecriterion C..assed? '-TOP
Present systematic serch procedures
9 Use model of correct behavior9 Using appropriate senses* Verify with a second sense, if
appropriate
Have student recall and demorstratesearch procedures
(*)(1) (S) / Student recalls and d~eo-trates
search predure, including use ofsccond sense modality, if appropriate
KOR
(6) •"procedures?
Yes,
Reinforc er ryi.-2 c>: ce hnettc
•, Programming Logic:j ... ... I Detection Dr•lDirections for Detection Drill Early in Training
Po finas-Ery inTheining * high signal density
Include: aiigh signal to noise ratio* different signal I
sources experienced * Repeat sare signal sourceon-the-job Present until criterion perfo,mance
first/next i., achieved*different patterns signal a
representing each Variable irtervalsignal source Student attempts to schedule for signal
detect within tirv presentation* realistic range of limits
Sratios for each
type of sig~ml XOR a reward for correct(Reinforce only if detections and ane
correWt) real signal
'(2) (4a (4a;
Criterion for Detection Yes
Drill - Early in Training (7)
Required: Has
"9 "X" probability of detection crierion NO"*Y false detection rate b* Detection within tire limits* use second sense modality,
if appropriate
(5) (7)
o Present stude.t with his status --
progress tc-,ýrd cb4ecti esr Reinforce.ent
(6) 0 C,
•iu•5. t.•~r'•irg A~ghor<th for Lnetecti•, (conftinued)
1xiautiont to vlqilf'ce tlalmtel. At? toto entire tretais IrPu
* Pr..int tostrwitions. ai Pkk for stiftat to noo In itstabl tsh;..
to MSCh
*~~~~~~oI in.titrcjlt.m twtio -SOv: ,tt
pntit't 1"eiotleft, a", mootl for b"otet to via 1-ot" ftt$
ypief1te, toot v ao** 1*ye~ blot'v I 0j
ftvest~ ecal I't~clem' aftdod troit s* o(I1
molsoroal cos
3
Directions fcr rgarif oi:" seet~l rl- Detection Drill--Intersiediate
Pol fSinasintermiediate Sitage Stage of TrainingPoofSgasof Training *lower signal densityicue (4-b) i nclude lower signal to
*differenlt signal sources niertcexperienced on-the-job sinoise pra set edos
Presert' sgals prset d uon*different patterns represent- frtoxsinlvariable interval Schedule
ing each signal source irtietsgl*.:OR preSerted oli a variable,*realistic range ofinterval schedule
signal-to-floise ratios SuetPrfor each type of signal fom*ts require vigilance tec~niques
~Yarabl Intrva) * x signal Datterns andKOR sotircLs
(Reirftrc* CO ntermittently' roward
if corect)responding to'ary reil
f 4b)
* Detecion wihinetietedit
N())
* Present S ~ Yen~~ths Sau-Proteress firr Detecttves
of Ternarningf(4Kas
Reurd criterion NO
4
Directions for Detection Drill--AdvancedDetection Drill -- Stage of Training
Pool of SgasAdvanced Stageof training &A* low signal density (operaticnal
Include: density or minimum numberI suited for training)
i* different sitaml saurces d e- sexperienced ihi-the-job S decrease signal-to-noise ratio
S difr pto operational level
I different rsorce first/next * present signals according to asignal v&riablt interval schedule
* realistic range of signal- . pe". oetn stgto-noise ratios for ech Student per-I schedule KOR equivalent to
type of signal forms tasksetting
4f p require vigilance techniquesSRealistically Scheduled appropriate to the job setting
\ • KOR ,
, (Reinforce o*ly e randomize signal patterns
I f c orrect and sources
(2) (6) (4c)
SDetected? 0
Nextsignal
Criterion for DetectionDrill -- Advanced Stageof Training
Required:
* "x" probability or detection criterion"Y" false detectior rate / een met?
* Detection witlin time limits* Use second sense modality, if
appropriate
(5,Present:* Status
R peinforcer-ent
(6)
L Recomwendations for Scheduling an, -7irfor:r e
Trainina 2S
o.1
C TOP
j- Q -
TAEG Report No. 23
F. CLASSIFYING
This task involves assigning a name to detected signals based onidentifiable characteristics. Classifying frequently follows immediatelyafter detecting in the operational setting as if the two were a singleevent, although the two processes are fundamentally different. Classify-ing is closely related to the forming of concepts which has been extensivelystudied. In fact, to a large extent, the principles of learninq which areapplicable to concept formation also apply to classifying. Examplec ofclassifying in operational tasks include labeling a sonar signal as"submarine" or "nonsubmarine," naming an approaching aircraft when thedistinguishing features become visible, and determining that an increasinglylouder "grinding" noise is a bearing starting to disintegrate.
The following guidelines apply to classifying. The algorithmrepresenting these guidelines is presented in figure 6.
1. State clearly the behaviorial objectives to be achieved by thestudent. Organize learning material around critical cues (distinguishingfeatures of the objects) to achieve this desired behavior. Relate theobjectives to the student's future real-world assignments.
2. Train the student to properly differentiate features to beused in classifying. Make sure the student can observe the differencesbetween closely related features if these differences are important inthe classification task. (As an example, properly identify blue andblue-green as being different colors.)
3. Train the student to recognize the features of a pattern (cue) thatdistinguish this pattern from other patterns. Use cues that will bepresent in the student's job.
4. Emphasize distinctive cues which can be remembered in the formof mental pictures instead of abstract words. Teach the student totransform the distinctive features of cues into terms that he can readilyrecall.
5. Present examples of various classes in a single exercise.Towards the end of training, present examples of classes that appearvery similar in the operational setting.
6. Minimize the number of irrelevant cues in the early stages oflearning. Towards the end of training, increase the number of irrelevantcues to a maximum; i.e., corresponding to the real-life situation of thejob.
7. Reeinforce frequently in the early stages of Iearning patternrL-` !ý'rce `o~s o t9., rc 9
atting') towards the end of training.
47
/
TAEG Report No. 23
8. Ensure that the student practices making correct identificationsof the test objects.
9. F_:vide immediate knowledge of results (KOR) to insure correctterminal performance.
10. Provide a pause following KOR (e.g., 4-12 sec.) that is muchlonger than the pause between the response and KOR (e.g., ½ sec.). Thispause provides time for the student to sort out errors and to identifysalient cues of the pattern.
11, Sample from the extremes of the full range of examples ofputterns produced by a given object. Make the examples more similar astrc ning progresses. At the end of training, the similarities in theexamples should represent the similarities that exist in the realworld.
12. Provide a variety of examples of the pattern. Select examplesto sample the full range of variations in the pattern. Late in thelearning stage, build in distractors equivalent to those found in theoperational setting.
13. Provide self-paced training that can be adapted to the individualstudent's needs. Both rate and level of learning depend upon characteris-tics of the individual student.
14. Arrange for slow learners to have a higher number of reinforce-ments of correct responses than the fast learners.
15. Insure the development of a strong tendency for the student tolook for certain critical and distinctive cue patterns found in opera-tional tasks.
16. Require (where possible) the learner to correctly identify orcite new items as examples in each classification category.
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TAEG Report No. 23
G. IDENTIFYING SYMBOLS
This category deals with recognizing and interpreting graphiccharacters such as those used in engineering drawings, maps, and statusboards. Symbols serve as a brief code which must be decoded by theuser. Most symbols have low meaningfulness to the untrained person.Symbol recognition is related to paired-associate learning, which hasbeen the object of extensive research. The research literature support-ing the guidelines for identifying symbols is considerable.
The guidelines for identifyitg symbols follow. The algorithrm
representing these guidelines is presented in figure 7.
1. Relate training clearly to meaningful and job related tasks.
2. Show differences between similar individual features of syrbols.Do this before associating these symbols with identification responses.
3. Break up the total list of symbols into smeallr sets when anyof the following conditions exist:
a. A long list of symbols is to be learned,
b. Material is complex for students.
The size of the set for eich student should vary according to how mucheach of the factors departs from the normal situation for each condition.
4. Present the associate item (or meaning) iniuediately after thesymbol in time as the basis for this kind of training.
5. Randomize the order of the presentation of the symbols to thestudent so that all symbols will be learned equally well.
6. Use mnemonics (associating recall of symbols with imagery,rhymes or rhythms) for difficult to recall symbols. Provide mnemonicswhich will cause an affective reaction in the student. A-so providedirections for the student to develop his own mnemonics.
7. Allow for self-paced practice with knowledge of results (KOR).
S. Prevent decay c'.- recall by (1) requiring the student to overlearnthe or-iginal associations and (2) ensuring periodic refresher trairinu.
9. Test for correct identiFicaticn of s-7:-cl by -e2asuring over,'tperformarnce by the stu&,ent.
TAEG Report No. 23
10. Provide self-paced training that can be adapted to the individualstudent's needs. Both rateand level of learning depend upon the character-istics of the individual student.
11. Use immwdiate KOR and frequent reinforcement in the earlystages of training. In later stages of training, match the KOR atidreinforcement levels that exist in the operational setting.
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TAEG Report No. 23
H. VOICE COW4UNICATING
Voice communication is used here to mean a conversation betweenpeople in which standardized message formats are employed. A person hastypically been overtrained in speaking and listening as a part of everyday living. Certain conversation patterns must be changed in order toeffectively communicate within the military tactical environment. Inthis setting, messages must be brief and have a single meaning. Thetiming of when to pass the essential information is frequently critical.The task may be made more difficult due to the presence of backgroundnoise and other conversations on the communication circuit. '1frft,,enunciation is important. Most of the guidelines are based ppon generallearning principles. In addition, principles identified through analysisof voice communicating are used.
The following guidelines are presented for voice communicating.The algorithm representing these guidelines is presented in figure 8.
I. Present objectives of the learning program to the student.Organize material around objectives. Relate material to the operationalsetting of voice communication.
2. Present a brief overview of the learning program.
3. Break up the material into discrete voice connunication categoriesthat frequently occur in the job setting.
4. Identify similar cues (usually auditory) that frequently areconfused in voice communication tasks and test the student to see if hecan discriminate among them.
5. Point out critical cues and responses that are different fromthe student's habitual ("everyday" type) voice communication.
6. Teach the student to anticipate certain messages in a givenoperational setting - listen for certzii, words.
7. Teach voice communication procedures and terminology in generalusing Recalling Bodies of Knowledge Guidelines before presenting ademonstration of each specific procedure.
8. Demonstrate each voice procedure with a model performance;insure that the student observes the critical cues and responses in themodel's demonstration.
•. Req,'e the student to practice un'tji he d .... thecorrect performance. Have him conrentrate his practice on the parts hefinds difficult.
TAEG Report No. 23
10. Give specific knowledge pf results with each performance ofthe student; reinforce correct segents of performance.
'1. Provide rest periods at intervals within the training period.
12. Increase distractors and stress conditions equal to that inthe operational setting during the later stages of voice communicationtraining.
13. Practice voice communication procedures to the same.skilllevel that will be required In the operational setting.
14. Require student to overlearn correct voice cc-nunicationprocedures so that he can perform them correctly in a distracting,stressful environmental setting.
15. Reinforce the student for meeting the overlearning and opera-tional performance criteria.
16. Insure periodic refresher training where it is indicated bythe performance of the person on the Job.
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TAEG Report No. 23
I. RECALLING PROCEDURES AND POSITIONING MOVEMENT
This task category combines two quite different kinds of tasks.Recalling procedures is basically a mental skill, whereas positioningmerverft is a physical skill. They are combined in these guidelinessince they often occur together in the operational setting. They concerncarrying out routinized activity, executed as standard operating proceduresIn some predetermined-sequence. Relatively little judgment and analysisare required and a minimum of alternative behavior is involved. Controlsare manipulated in an identifiable procedural sequence. Motor movementsfor control positioning are, at tVe outset, within the response repertoireof the student; therefore, the emphasis is placed on recalling thesequeitial procedures and on the accuracy of the positioning movements.An example is the checkout of a piece, of communication equipment, using achecklist to determine if the equipment is operating within acceptabletolerances. These types of tasks are commno. and have often been studiedwith the goal of improving training efficiency.
Guidelines for this behavior are listed below. The algorithmrepresenting these guidelines is presented in figure 9.
1. State clearly the behavioral objectives to be achieved.Describe how the learning materials are organized tn achieve this a(.iredbehavior. Relate the objectives to the student's future real-worldassignments.
2. Break the positioning movement task into appropriate parts andprovide subdivisions of organization for each procedure.
3. Divide the procedural steps into small parts if any of the
following conditions exist:
a. Students are of low ability,
b. The procedures are complex,
c. The entire procedure is lengthy.
4. Present a demonstration of each task performance (a positioningresponse to a checklist cue) on an observable model.
5. Show checklist cues and require the student to explain differencesin similar cues that serve as association devices for different proceduresthat have been confused in the past.
6. Use mnemonics which will cause an affective reaction in thestudent whenever possible 'o eid i4 the recall of the orocedures t, beee-ned for this task.
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TAEG Rep'rt No. 23
7. Use mnemonics (associating procedural steps with imagery,rhymes, or rhytlhms) to aid in recalling difficult to rewember steps."rovide directions for the student to develop hi; own mnemonics where heis able and willing to do it.
8. Direct the student to practice the following sequence ofevents to help him remember a chain of procedures.
a. When presented with each checklist item, explain (orperform) its corresponding procedural step.
b. Then when presented with a group of checklist items (asmany as the student c3M handle at once) explani or perform their correspond-ing procedural steps. The f'rst item of each group shouid overlap thelast item of the previously studied group of steps.
c. Then when presented with a single list of all ;f thechecklis• items in the entire procedure, explain (or perform) theircorresponding procedural steps.
9. Encourage students to mentally rehearse the prncedures calledfor by the steps in the checklist using mne-onlcs to aid in the reý:allof these procedures.
10. Ensure extensive practice early in the training by requiringthe learner to:
a. Understand the objective(s),
b. Observe the skilled performance of a model,
c. Strengthen the individual (or component) steps of thedesired movement by practicing these steps, obtaining knowledge ofresults (KOR) and by correcting performance errors.
d. Integrate the steps into a smooth sequence of positioningmovements by practicing the sequence of steDs.
11. Provide the following conditions for corresponding stages oft-raining:
a. Early in training use:
(1) immediate and frequent KOR,
(2) immediate and frequent reinfordenent,
(3) little or no oDerational distractors,
61
TAEG Report No. 23
(4) learning material broken-down into small, easilylearned parts,
-(5) items required to be learned which are relativelyeasy to acquire,
(6) guiding or prompting of responses.
b. Late in training:
(1) use delayed and Infrequent KOR,
(2) use delayed and Infrequent reinforcement,
(3) increase distractors to operational level,
(11 a given procedure will be required to be recalVý!(or performed) in response to the same cues as on the job.
(5) the level of complexity of the Procedural cues anddistractor cues should be the same as on the job. #A stressful conditionsequivalent to that in the. operational setting,
(6) eliminate guides or prompts (other than those providedin the operational setting).
12. Make the time interval following KOR much longer than the timeinterval between the response and KOR, to provide time for the studentto sort out errors.
13. Identify features of the operational environment which couldbe used as mediators to trigger the student's recall of checklist items.
14. Practice should be distributed; i.e., the timing of restperiods should be determined by:
a. need for rest as judged by the student.
b. requirements of the specific learning material as judgedby the instructor.
15. Arrange for exte-nsive repetition (overlearning) by the studentto take advantage of the internal feedback properties generated byperforming these +ypes of tasks (positicninc -ovemrent) accompanied byexternal feedback. Simple repetitive movements may become reinforcing;i.e., the student experiences feelngs in muscle and joints which he;dcntif4es as cues that he is Derfor•Tin,, the- task correctly.
69
TAEG Report No. 23
16. Arrange for slow learners to have _- higher numoer of reinforce-ments of correct responses than the fast learners.
17. Maximize the realism of checklist items and their correspondingprocedural responses.
18. Arrange for the student to compare the program objectives withhis current status in meetinn these objectives (use periodically).
19. Train the student to the operational criterion; i.e., insure"that acquisition of the procedural material will be to the level ofperformance required for on-the-job duties.
20. Prevent decay of recall by providing periodic refresher trainingfor infrequently used procedures.
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TAEG Report No. 23
J. GUIDING AND STEERING, CONTINUOUS MOVEMENT
This type of task concerns continuous physical response to aconstantly moving visual reference. Frequently it involves controllingthe path of a moving vehicle. Examples include maneuvering an automobiledown a road, visually aiming weapons during air-to-air combat, holding aship on course using a gyro compass. Many military jobs involve thistype of behavior. Because of the high cost of vehicle Control trainingperformed on the operational systems, how best to train this type ofbehavior has been carefully studied. Proprioceptive stimulation arisingin the muscles, tendons, and joints is normally present and is one ofthe primary sources of information used in controlling the force, extent,and duration of a movement. Perceptual discrimination skills are involved,including the detection of relevant cues (via sight, hearing, touch,etc.). Models of correct behavior are usually used in the training ofthis task. They serve as guides and criteria against which to evaluateone's own behavior. These models include rules, self-directions, andcues of adequate performance. As the student's skill increases incontinuous movement tasks, a high degree of internal control is developed;i.e., the routine tasks are performed smoothly with little consciouseffort, and conscious control governs increasingly larger blocks ofbehavior.
The following guidelines have been defined for training continuousmovement tasks. The algorithm representing these guidelines is presentedin figure 10.
1. State clearly the criterion behavior or objective to be achieved.Relate the objective to the student's future real-world assignments.Provide him with an overview of desired movements.
2. Break the task up into appropriate parts. (Use as criteria toS..ii. t'e size of these parts: ability of learner, complexity, and
length ot task.)
3. Ensure that the critical external cues are realistic and availableto the student continually during the performance of the task, particularlyduring the latter part of the training.
A. Provide trainina to scan by specific training of eye movementanQ where to focus for scanning.
5. Insure a high degree of realism in the operator's response intraining for continuous controlling tasks.
6. Demonstrate the desired task performance with a model.
i 658
TAEG Report No. 23
,P.-provide:- for extensive -practice to achieve skilled performance.Practice should contain (a) understanding skill objectives, (b) observingskilled performances, (c) practicing the task, (d) obtaining knowledge ofresults (KOR), and (e) scheduling periodic rest intervals.
8. Provide reinforcement contingent upon characteristics of thestudent's response so that by a process of "successive approximations"the final desired proficiency (withir acceptable tolerances) is produced.
9. Give KOR concerning discrete segments of student performance,especially during early stages of learning.
10. Give positive reinforcement after correct student performance;initially, immediately after each discrete segment of performance; towardthe end of training, after each mapeuver or couplete operation.
11. Practice on specific components when learning a complex task,as o0posed to practicing on the entire task at once.
12. Practice under the varied conditions that will exist in theoperational setting, if possible.
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TAEG Report No. 23
K. PERFORMING GROSS MOTOR SK!LLS
This category includes skills characterized by repetitive itoracts involaing it use of large muscles. It often includes chaining ofmovements ard a low level of attention by the skillf'il performer.Fatigue may become a factor in the performance of these skills when
S.. -fmed over an extended period of time. Examples include body mve••ents. in many athletic events such as running, swimming, and jumping. These
motor acts are controlled by various forms of internal and externalstimuli. Proprioceptive stimulation arising in tte muscles, tendons,and joints is a primary source of information used in directing thistype of skill. Perceptual discriminatien including t!e detecticn ofrelevant external cues is secorndary to successful zerf.other types of motor skills, conceptual models of correct behav-or areusually used as a performance guide and as a baseline for self-evaluation.A high degree of internal and unconscious control governs the diicrete•acts in this type of skilled behavior.
The guidelines for performing gross motor skills are liste0 below.The algorithm representing these guidelines is presented in figure 'I.
1. Orient student to the learning task by:
a. Stating the objectives,
b. Relating the objectives to the operational task he will bnperforming.
2. Teach the student to discriminate among similar cues withineach of these classes:
a. Objects in the job environment to which the performer mJstrespond with appropriate action (external cues).
b. Proprioceptive stimuli (internal cues).
3. Facilitate the student's undarstanding of the task by requiringhim to do the following:
a. Observe a demonstration of the task.
b. Observe the component parts uf the task as it is beirnzpresented,
c. Have the student describedan. amJ decorst rate the coponerlt,parts of the rotor task which he obServed.
TAEG Report No. 23
4. Require that the student practice with regard to the followingconsiderktions:
a. Practice a simple task in its entirety, or a complex taskin-parts and then in its entirety.
b. Practice under varied operational conditions. This isdone to help adapt the performance of this task to potential environmentalcMhanes in the 6perational setting.
c. Ensure that during practice the student:
(1) Understands the objectives of the skill while learning,
(2) Observes a skilled performance of the desired task asoften as necessary,
(3) Obtains feedback concerning his performance of thetask (immediate feedback early in training, and a level of feedbackappropriate to the operational setting later in training). Encouragethe student to respond to internal-feedback.
d. Distribute the practice; i.e., provide for rest intervals
during training.
5. Ensure that feedback of the 'ollowing kinds will be provided:
a. Evaluative--student learns what he is doing that is correctcr incorrect.
b. Comparative--student learns how his performance comparesto the objectives and standard of perforriance required in the operationalsetting.
6. Provide a pause of a few seconds after feedback has been givenfollowing performance of the motor skill to allow sorting out Of errorsmade during the training performance.
7. Shape the desired performance by reinforcing the student'sclosest approximation to the desired response.
8. Reduce frequency of reinforcement to the operational level asthe student approaches criterion performan-2,.
9. Require the student to overlearn desired perforruance.
10. Increase distractors towards the end of training to the level
73
TAEG Report No. 23
that the person will encounter in the operational setting.
11. Provide for refresher training when the skilled person has notperformed the motor skill for an extended period of time.
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TAEG Report No. 23
SECTION III
RECOMMENDATIONS
The learning guidelines and algorithms presented in this reportmaybe used in carrying out the following steps in the design of trainingsystems-
1. Specifying learning events and activities. The guidelinesspecify the significant learning events and activities that should existin effective training.programs for specific types of tasks. Since thereis empirical support for the principles in these guidelines, trainingsystem designers should attempt to find practical ways to carry out allof the guidelines.
2. Selecting instructional delivery vehicles. Each type ofinstructional material is limited as to the functions it can perform.The training system designer should pick an instructional deliveryvehicle capable of carrying out the events specified in the guidelinesand algorithms. This is contrary to the usual practice where the deliveryvehicle is selected first and then the learning events are chosen to becompatible with the delivery vehicle.
3. Designing instructional materials. An instructional deliveryvehiclewhich has the capacity to sipport specified learning guidelines(see item 2) will only improve learning if the instructional materialsto be used in it are also designed to the same guidelines. Therefore,the type, sequence, and relationship of learning events in instructionalmaterials designed for such a system should be in 6ccordance with theappropriate guidelines and algorithms.
4. Evaluating existing instructional materials. It may be moreeconomical to use existing modules of instructional materials than tocreate new ones. If the modules are to be used in a system designedaccording to item 2, the guidelines and algorithms should serve ascriteria for determining if the modules are suitable or can be modifiedto bring them up to the required standard.
. ifying algorithms to store field experience. When instruc-tional material designed according to an algorithm is shown to be inadequatein tMh Field setting, then the algorithm as well as the instructionalmater"ial should be modified until the material proves useful for that
In this manner, algorithm- can'be used as the basis for describingP q-7enrrir, structure m• successful leirning materials for a specific
'>2, t i:'ut Ir j, ,•y Se(I ri , )'5o- r •, FiCCtinn Fl or theI desiqn of si! j1:r
TAEG Report No. 23
REFERENCES
Adams, J. A. "Mechanisms of Motor Responsing." In E. A. Bilodeau (Ed.)Acquisition of Skill. New York: Academic Press, 1966, pp. 369-397.
Braby, R. An Evaluation of Ten Techniques for Choosing InstructionalMedia. TAEG Report No. 8. December 1973. Training Analysis andva uation Group, Orlando, FL.
Braby, R., Henry, J. M., Parrish, Jr., W. F., and Swope, W. M. ATechnique for Choosing Cost-effective instructional Delivery Systems.TAEG Report-No. 16. April 1975. Training Analysis and EvaluatiorGroup, Orlando, FL.
Braby, R., Micheli, G. S., Morris, C. L., Jr., and Okraski, H. C.Staff Study on Cost and Train~'un Effectiveness of Proposed TrainingSystems. TAff eport_ No. 1. ?72. Training Analysis and EvaluationGroup, Orlando, FL.
Bugelski, B. R. An Introduction to the Principles of Psycholog.Indianapolis-" fhe Sobbs-Merr-Il Co. 1973, p7. .
Cofer, C. N. "Verbal Learning." In M. Marx (Ed.) Learninp Processes.New York: MacMillan and Company, Ltd. 1969. pp. 368-369.
English, B. A Student's Dictionary of Psychological Terms.Fourth E-ition. New rk: Harper and Brothers. -9-34.
Ellis, H. C. "Transfer and Retention." In M. Marx (Ed.) LearningProcesses. New York: MacMillan and Company, Ltd. 1969. p. 408.
Ellis, H. L.. Fundamentals of Human Learning and Cognition. Dubuque,Iowa: William C. Brown-Co. 1972. pp. 1 95, 113, 146, 200, 201,212.
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Cagne. R. i. The Conditions of, Learning. Niew York: Holt. Pinehart,and Winston. 1965. pp. 33-57.
/iaqne, R. M. and Briaqs, L. J. Princioles of Instructional Design.
New York. Holt, Rinehart, and Winston. 197?l. p. 140.
Glaser, R. Traininq Research and Education. University of PittsburgPress. 196?. p. 11.
aI, J. F. hne oscri y Leearn' , " L' Co.196;. pP. 134, 529.
TAEG Report No. 23
REFERENCES (continued)
Hilgard, E. R. and Bower, G. H. Theories of Learning. New York:Appleton, Century, Crofts Co. TT66. pp. 75, 77, 309, 546, 549.
Holland, J. G. "Teaching Machines: An Application of Principles from theLaboratory." In A. A. Lumsdaine and R. Glaser (Eds.) TeachingMachines and Programmed Learning: A Source Book. Washington, DC:National Educational Association. T960.
Interservice Procedures for Instructional Systems Development, Phase 1IIDevelop. NAVEDTRA 106A, 1 August 1975.
Kausler, D. H. Psychology of Verbal Learning and Memory. New York:Academic Press. 1974. p. 195.
Landa, L. N. Algorithmization in Leart,ing and Instruction. EnglewoodCliffs, New Jersey: Educational Techni6gy Publications. 1974.pp. 11, 90.
Lumsdaine, A. A. "Educational Technology, Programmed Learning, and Instruc-tional Sciences." In E. R. Hilgard (Ed.) Theories of Learning andInstruction. Chicago: University of Chicago Press. 1964.
Marx, M. "Learning Process." In M. Marx (Ed.) Learning Processes. NewYork: MacMillan and Company, Ltd. 1969. p. 29.
Miller, N. E. Graphic Communication and the Crisis in Education.Washington, DC: National Educational Association. 1957.
Pouitoii, B. C. "Tracking Behavior." In E. A. Bilodeau (Ed.) Acquisitionof Skill. New York: Academic Press. 1956. pp. 369, 375,391, 397.
Ruch, F. L. and Zimbardo, P. G. Psychology and Life. Glenview, Illinois:Scott, Foresman, and Co. 1971. pp. 206, 211, 213, 255, 518, 523.
Sheffield, F. D. "Theoretical Considerations in the Learning of ComplexSequential Tasks from Demonstration and Practice." In A. A. Lumsdaine
d Student Res pnse on Programmed Instruction. Washinatn.,' '-ioniT cad my of Sciences-National Research Council-
151 :,,1 o n 943. 1961.
r v o, R ... userr, J. , and Ferqusun, D. E. Behavior nd0~Prat i na A- ects of Tactical Decision Makinj in AAW and S.
T, ' )_ ~ VCF-N 1329---. 1964. N-avý-Trai-ning Devi ce Center, c! zIW#,c,:•I n~ tnn, NY.
TAEG Report No. 23
REFERENCES (continued)
Skinner, B. F. "The Science of Learning and the Art of Teaching."Harvard Educational Review. 1954. 24, pp. 86-94.
Warm, J. S. "Training for Vigilance: Some Suggestions for Research onthe Learnifig, Transfer and Retention, of Watchkeeping Skills:' InLearnino, Retention, and Transfer. NAVTRADEVCEN 68-C-0215-l,Vol. 2 of 2. Februar7yT971. Naval Training Device Center,Orlaiido, FL.
Willis, M. P. and Peterson, R. 0. Deriving Training Device Implicationsfrom Learning Theory Principles. Vols. I and II, NAVTRADEVCEN 784-1and -2. July 1961. Naval Training Device Center, Port Washington, NY.
N.
TAEG Report No. 23
GLOSSARY
Affective Reaction - A person's feelings or emotional response to someobject or person.
Algorithm (Landa) - A precise, generally comprehensible prescription forcarrying out a defined sequence of elementary operation in order tosolve any problem belonging to a certain class (or type).
Concept Formation - Classifying objects into groups on the basis ofcommon relationships in their patterns of cues.
Criterion (Cofer) - The degree of mastery to be reached in learning, whichis set by the instructor.
Distributed Practice (Ellis) - The introduction of rest intervals duringthe course of acquisition.
Facilitate (English) - Increased ease of performance, by aI - decrease in time2 - increase of output3 - decrease in sense of effort;
to make easier or less difficult.
Feedback (Ellis) - Cues that indicate whether a response is correct ornot and provides the learner with information about the correctnessof his responses.
Guides (Hilgard & Bower) - Environmental cues tha., Facilitate the discoveryof the correct responsc by the learner.
Instructional Delivery System (Braby, et al., 1975) - A system to accomplishhuman learning made up of the student and all the elements with whichhe interacts to achieve instructional goals.
KOR (Ruch & Zimbardo) and (Hall) - Knowledge of results--information as towhether the student has responded correctly; information the individualobtains about his actions.
Media - Those materials that store and present information to a student.
Mnemonics (Bugelski) - Memory aids or devices for facilitating the recallof learned material.
Overlearning (Hilgard & Bower) and (Cofer) - Further practice after meetingthe initial criterion for learning; continuing to practice beyondthe noint at which some arbitrary criterion is met. Continuationoi practice beyond some criterion of learning (or of mastery).
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TAEG Report No. 23
GLOSSARY (continued)
Positive Reinforcement (Ellis) - Any event that increases the likelihoodof a response when it is presented.
Predictability (Poulton) - Quality of being able to predict one event whenthe other is known.
Prompts (Kausler) and (Glaser) - Stimuli (usually words) known to elicit theresponse unit when given as a stimulus in a word association test;these elicit implicit associations to that prompt, one of which isthe to-be-recalled response unit. A variety oF stimulus materials whichcue the appropriate behavior.
Proprioceptive Cues - InternaV cues from the muscles and tendons indicatingtheir movement and position; cues that are aroused as a result ofmuscle movements.
Reinforcement (Ellis) - The process by which some response tendency
comes to be strengthened.
Salient - Prominent or conspicuous; important, striiking, remarkable.
Shaping (R,:,-h & Zimbardo) and (Marx) - A technique used in training in whichall responses that come close to the desired one are rewarded atfirst, then only the closest approximations, until the desiredresponse is attained; a procedure in which selective reinforcementis used to train the learner by means of successive approximationsin some new behavior.
Similar Cues (Ellis) - The number of elements that two cues have incomimon.
Stress (Ellis) - A state of the organism usually characterized as motiva-tioral (and or emotional). The task demands made upon an individuallearner.
Vigilance (Warm) and (Adams) - Human watchkeeping or monitoring behavior;observing a display for occasional critical signals; alertness for thedetection of critical signals when they occur.
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