K Hefty Final ID Project

7/26/2019 K Hefty Final ID Project

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EdTech 503: ID Project | Page 0

Lets PlayBall!!Excel, Baseball & Statistics

Final ID Project

i "e#ty

EdTech 503: Instr$ctional Design

Boise %tate &ni'ersity

($g$st )* +0)3


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Table of Contents

Reflection Paper 3

Part 1 Topic 5

1a. Goal Statement 5

1b. Audience Description 5

1c. Rationale 5

Part 2 Analysis Report 7

2a. Description of eed 7

2a1. eeds Assessment Sur!ey 7

2a2. eeds Assessment Results "

2b. Description of #earnin$ %onte&t 12

2b1. #earnin$ %onte&t Description 12

2b2. Transfer %onte&t Description 12

2c. Description of #earners 13

2d. Tas' Analysis (lo)c*art 1+

Part 3 Plannin$ 15

3a. #ist of ,nstructional -becti!es 15

3b. -becti!es /atri& Table 17

3c. AR%S Table 20

Part + ,nstructor Guide 22

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+a. ,nstructor Guide 22

Part 5 #earner %ontent 2

5a. #earnin$ /aterials 2

5b. Assessment /aterials 27

5c. Tec*nolo$y Tool Rationale 2"

Part (ormati!e !aluation Plan 2

a. &pert Re!ie) Plan 2

b. -ne4to4-ne Re!ie) Plan 2

c. Small Group !aluation Plan 30

d. (ield Trial Plan 31

Part 7 (ormati!e !aluation Report 32

7a. !aluation Sur!ey 32

7b. Report of &pert Re!ie) 33

7c. Desi$ners Response to Re!ie) 3+

Part " Standards Grid 35

". A%T Standards Grid 35

Appendices +3

Appendi& A6 Rubrics +3

Appendi& 6 /icrosoft &cel &amples ++

Appendi& %6 ,nnin$ %*ec'list +5

Appendi& D6 References +

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Reflective Synthesis Paper

a'in$ re8uires $reat attention to detail. (irst9 t*e ba'er must decide on )*at t*ey

)ant to ba'e9 t*en t*ey *a!e to decide )*ic* recipe t*ey )ould li'e to use. T*erecan be multiple options for t*e same product but t*e ba'er *as to loo' at t*e needs

of )*o *e is ba'in$ for. Suppose t*e ba'er )ants to ma'e blueberry muffins for

c*ildren. ,s anyone aller$ic to nuts or e$$s or $luten: T*e ans)ers to t*ese

8uestions )ill determine )*ic* recipe t*e ba'er uses. After decidin$ on )*ic*

recipe to use9 t*e ba'er )ill carefully assemble all t*eir in$redients. a'in$

re8uires precise attention to detail. T*e in$redients must be assembled in t*e

correct order )it* t*e correct amount and for a precise amount of time. A $ood

ba'er follo)s t*e steps of analy;e9 de!elop9 and e!aluate. (ailin$ to do any of

t*ese steps could be disastrous.

Details9 its all about t*e details< T*at is *o) , )ould summari;e ,nstructional

Desi$n. An ,nstructional Desi$ner is similar to a ba'er= bot* must follo)s t*e

steps of analy;e9 desi$n9 and e!aluate. A $ood desi$ner starts )it* an analysis of

)*at s*e )ants to accomplis* > a $oal. T*e desi$ner in education )ill consult

)it* subect matter e&perts or different departments to de!elop t*e ultimate end

$oal. A $ood desi$ner must also start )it* e!aluatin$ prere8uisite s'ills and any

restrictions before c*oosin$ t*e best ?recipe@ to follo). ust as a ba'er assembles

*er in$redients before be$innin$9 t*e ,nstructional Desi$ner prepares *er learnin$

obecti!es. Bit* precise attention to detail9 t*e ,nstructional Desi$ner carefullyand met*odically be$ins to assemble *er proect. -r$ani;ation is often t*e 'ey to

success in bot* ,nstructional Desi$n and ba'in$.

!aluation is t*e 'ey to bot* ba'in$ and ,nstructional Desi$n. -nce t*e muffins

*a!e ba'ed for t*e set amount of time9 t*e ba'er must c*ec' t*em. Did t*ey ba'e

lon$ enou$*: Did t*ey ba'e for too lon$: Co) do t*ey taste: Bas t*e end result

)*at )as e&pected or *oped for: A desi$ner *as to as' *erself similar 8uestions.

ltimately9 is t*e end result )*at )as *oped for: ,f not9 bot* t*e ba'er and t*e

,nstructional Desi$ner must loo' bac' and find t*e error. (or ba'in$9 if all t*e

steps )ere follo)ed correctly t*ere are ot*er factors suc* as ele!ation9 in$redient!ariations or brands of o!en t*at can effect ba'in$ time. A $ood desi$ner must also

ma'e sure t*at enou$* time )as allo)ed for *er product to *a!e fully de!eloped.

Personally9 , *a!e been astounded by t*e ,nstructional Desi$n process. As ,

de!eloped my o)n ,nstructional Desi$n proect9 , *a!e made a $reat many



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mista'es. /y ori$inal proect )as too broad in bot* scope and desi$n9 especially

for a t)o to t*ree *our proect. , needed to scale it )ay bac' and $et more focused.

-nce , simplified t*e o!erall scope , )as able to focus on t*e details. , also needed

to re!ise my $oals multiple times. T*e more detailed , $ot9 t*e more focused t*e

proect became. , learned a lot about ,nstructional Desi$n t*rou$* t*is process9especially t*rou$* my errors.

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Part 1 Topic: Microsoft Excel, Statistics and Baseball

1a. earnin! "oal

After t)o to t*ree *ours of researc* on t*e ,nternet and direct instruction9 students)ould utili;e &cel spreads*eets to be able to create and interpret a statistical

correlation proect relatin$ )innin$ to t*e offensi!e statistics of t*e Seattle

/ariners o!er a defined period of time.

1b. #$dience %escription

T*e learners of t*is ,nstructional Desi$n proect )ill be 7 t*$rade students in t*e

ad!anced al$ebra course )*o *a!e pre!iously ta'en t*e ad!anced pre4al$ebra

course. ,nstruction )ill ta'e place in t*e computer lab meetin$ on t*ree

consecuti!e Bednesdays9 durin$ desi$nated ?computer@ time9 for an *our eac*time.

1c. Rationale

, *a!e a 7t*$rade son )*o lo!es mat* and sports. -!er 20 years a$o , tau$*t

middle sc*ool mat* and remember doin$ a ?baseball proect@ t*at t*e students ust

lo!ed. ut 20 years a$o )e did !irtually e!eryt*in$ by *and. T*e students *ad to

brin$ in p*ysical ne)spapers and loo' at t*e bo& scores to find t*e data to calculate

battin$ a!era$es for t*e Seattle /ariners. T*e students )ould record all t*is

information on )or's*eets and9 by *and9 calculate all t*e data and $enerate !isual

representations. , )ondered *o) different it )ould be to update t*is proect )it*

tec*nolo$y. , 8uic'ly reali;ed t*at t*e computations and $rap*s could be done

)it* /icrosoft &cel and t*e students could spend more time analy;in$ t*e

compilation of data and loo'in$ for correlations. /y sons sc*ool pro!ided t*e

perfect opportunity to try t*is out.

(or t*is proect9 bot* supplanti!e and $enerati!e strate$ies )ill be utili;ed. T*e

o!erall strate$y of t*is instruction )ill be a blend of appro&imately 20E

supplanti!e and "0E $enerati!e instruction. T*e instruction )ill be primarilyprocedural9 )*ic* )ill re8uire a more structured approac* to learnin$ and

instruction. Researc* and data analysis )ill *a!e a more $enerati!e instructional

approac*. T*ere )ill be opportunities for creati!ity for t*e students $rap*ical

representations and final product. (or many of t*e steps it )ill be critical t*at t*ey

complete eac* step in a precise manner in order to correctly calculate t*e data.



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Procedural )ill be t*e maor instructional strate$y. #earners )ill be follo)in$ a

specific set of steps needed in order to be able to create t*eir $rap*s usin$

/icrosoft &cel. T*e learner )ill reac* a decision points alon$ t*e )ay and )ill

need to c*oose t*e correct branc* of t*e procedure to follo). At t*ese decisionpoints9 t*e instructor )ill utili;e Problem Sol!in$ ,nstruction. T*ere )ill be a fe)

places )*ere t*e learner can complete steps out of order )it*out impactin$ t*e

final outcome. ,n order for learners to reac* t*e instructional $oal9 t*ey )ill need to

do more t*an recall t*e steps of t*e procedure t*ey )ill need to apply t*e

procedures to create somet*in$ ne).

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P#RT &: #nalysis Report&a. %escription of 'eed

&a1. 'eeds #ssess(ent S$rvey

T*e follo)in$ is a list of 8uestions presented by Sur!ey /on'ey at6*ttps6FF))).sur!eymon'ey.comFsF37HI . , sent out t*is sur!ey to all 2 of my

sons classmates. 2+ out of 2 responded.

T*ese 8uestions )ere de!eloped to analy;e t*e s'ill set of t*e students )*o )ill be

participatin$ in t*e proect. T*is sur!ey co!ers t*e students familiarity )it*

tec*nolo$y9 baseball and statistics.

Baseball Statistics ) Excel S$rvey *$estions

1. Ca!e you e!er used /icrosoft &cel before:

2. Co) comfortable are you )it* /icrosoft &cel:

3. Do you 'no) *o) to do researc* on t*e ,nternet:

+. Co) comfortable are you )it* doin$ researc* on t*e internet:

5. Are you familiar )it* aseball:

. Do you 'no) *o) to calculate a battin$ a!era$e:

7. Do you 'no) *o) to read a ?bo& score@ for baseball:

". B*ic* of t*e follo)in$ $rap*s are you familiar )it*: %ircle or Pie Grap*9

ar Grap*9 #ine Grap*9 Scatterplots

. Do you understand *o) to calculate t*e mean of data:

10. Do you understand *o) to calculate t*e median of data:

11. %an you $enerate a formula for calculatin$ t*e mean:

12. Do you 'no) )*at a mat*ematical correlation is:13. ,n your o)n )ords9 )*at do you t*in' a mat*ematical correlation is:

1+. B*at is a trend: ,n mat*: ,n baseball:

15. B*ic* of t*e follo)in$ do you t*in' could be related: attin$ a!era$es

and )innin$ percenta$e: attin$ a!era$es and losin$ percenta$e:

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&a&. 'eeds #ssess(ent Res$lts

T*e first 8uestion sur!eyed t*e students familiarity )it* &cel. 100E of t*e

respondents ans)ered t*at t*ey *ad used &cel. Juestions 2 and 11 also related to

t*e usa$e of &cel. Alt*ou$* a lar$e portion of t*e respondents felt some)*at to!ery comfortable )it* &cel9 not as many as , e&pected )ere able to $enerate a

formula.

Juestions 3 and + related to usin$ t*e internet. 100E students 'ne) *o) to do

researc* on t*e internet )*ile only "3E felt !ery comfortable )it* doin$ so. o

one indicated t*ey )ere not comfortable.

Juestions 59 9 and 7 related to t*e students familiarity )it* baseball. , *onestly

)as !ery surprised by t*ese results. , e&pected all of t*e students to be muc* more

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familiar )it* baseball. -!er *alf of t*e respondents stated t*ey did not 'no) *o)

to calculate a battin$ a!era$e or read a bo& score. ased on t*ese results9 it is

apparent t*at some basic re!ie) of baseball9 battin$ a!era$e9 and bo& scores )ill

be re8uired.

Juestions "9 9 10 relate to statistics. T*e o!er)*elmin$ maority of students )ere

familiar )it* common statistical representations suc* as circle $rap*s9 bar $rap*s9

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line $rap*s and scatterplots. All of t*e students indicated t*at t*ey could calculate

t*e mean and t*e median.

Juestions 12 K 13 relate to correlations. Juestion 13 )as open ended. T*e

students )ere e!enly split )*et*er or not t*ey could define correlation. Co)e!er9

$i!en t*e number of respondents t*at indicated t*ey )ere not sure9 it is apparent

t*at t*is must be part of t*e instruction time. (or t*e open ended 8uestion9 only

about *alf t*e students responded. Let9 t*e students t*at did respond )ere able to

correctly state a correlation as a relations*ip. ,t is muc* more t*an ust a

relations*ip but t*is is a $reat startin$ point.

Juestion 1+ K 15 relate to trend analysis. Juestion 1+ )as open ended and as'ed

respondents )*at t*ey t*ou$*t a trend )as in mat* or baseball. About a t*ird of

t*e students s'ipped t*is. T*e maority of t*e respondents correctly stated t*at a

trend is a pattern t*at repeats. , found it !ery interestin$ t*at t*e maority of

students identified a relations*ip bet)een battin$ a!era$es and )innin$ but t*e

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same number did not relate battin$ a!era$es and losin$. , am not sure )*y t*is is.

, t*in' t*is )ill be !ery interestin$ to disco!er.

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&b. %escription of earnin! Context

St. #ouise is a pri!ate %at*olic sc*ool for $rades pre4'inder$arten t*rou$* ei$*t9

stressin$ a traditional9 disciplined approac* to learnin$. (ounded in 11 by t*e

Sisters of St. osep*9 St. #ouise is no) one of 73 sc*ools in t*e %at*olic

Arc*diocese of Seattle. St. #ouis dra)s students from t*e $reater Seattle astside

4communities of elle!ue9 ,ssa8ua*9 Sammamis*9 Redmond9 Boodin!ille9 Renton9

e)castle9 Seattle9 Hir'land9 %arnation9 (all %ity9 and ort* end. St. #ouise

Paris* Sc*ool is state4certified and accredited.

Affiliation6 Roman %at*olic

+0 students

31E t*nic /inorities

"E of students are %at*olic

/a&imum class si;e6 2 students in $rades H4"= 1" in Pre4H

100E Graduation rate

(ully e8uipped Science #ab9 Art Room9 and %omputer #ab

&b1. earnin! Context

T*e students )ill be t*e ad!anced 7t*$rade mat* students from St. #ouise. T*ere

are 2 students in t*e ad!anced mat* pro$ram. ,nstruction )ill ta'e place in t*e

computer lab meetin$ on t*ree consecuti!e Bednesdays9 durin$ desi$nated

?computer@ time9 for an *our eac* time. T*e computer lab is e8uipped )it* 2

computers9 a proector and a )*ite board. All computers *a!e /icrosoft &cel and

internet access.

&b.& Transfer ContextStudents s*ould be able to use t*e 'no)led$e t*ey $ain from t*is proect

immediately. Alt*ou$* t*e students )ill *a!e pre!iously )or'ed )it* &cel and

basic statistical formulas9 t*is s*ould $reatly e&pand t*eir 'no)led$e of bot*. T*e

students )ill need to $enerate a basic formula for mean and utili;e t*e

correspondin$ &cel function to !alidate as )ell as to e!aluate multiple

calculations more 8uic'ly. T*e $oal is t*at t*ey )ill de!elop t*e relations*ip



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bet)een statistical e8uations and t*e e8uations needed for &cel. sin$ t*ese

relations*ips9 students s*ould be able to $enerate multiple &cel function e8uations

used in ot*er classes Mi.e. science or mat*N. Students s*ould also $ain a better

understandin$ of *o) $rap*s are created )it* &cel and *o) to interpret and

analy;e data for trends and correlations. Trend analysis applies to a lot more t*anust sports. Students s*ould be analy;in$ multiple situations. Students s*ould be

able to apply t*is ne) 'no)led$e to assist t*em )it* future proects.

&c. %escription of earners

T*ere )ill be 2 students in t*e ad!anced 7 t*$rade al$ebra course. ac* of t*e

students *as pre!iously ta'en ad!anced mat* and )as retested before enterin$ 7 t*

$rade ad!anced mat*. All of t*e students *a!e demonstrated a *i$* le!el of

proficiency )it* pre4al$ebra. Accordin$ to my sur!ey9 100E of t*e students are

familiar )it* /icrosoft &cel9 na!i$atin$ t*e internet9 mean and mode. T*e areaof $reatest concern in!ol!es baseball.

,t is apparent t*at some basic re!ie) of *o) baseball statistics are calculated isnecessary. Calf of t*e respondents do not 'no) *o) a battin$ a!era$e is

calculated and o!er *alf of t*e respondents do not 'no) *o) to read a bo& score.

Alt*ou$* t*e maority of students indicated familiarity )it* baseball9 t*is is not a

necessary component.

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&d. Tas+ #nalysis lo-chart

Prere$isite S+ills



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P#RT / Plannin!

/a. ist of 0nstr$ctional b2ectives

1N #earner )ill be able to open /icrosoft &cel and open a ne) blan'

spreads*eet )it*in 5 minutesaN Start F All Pro$rams F /icrosoft -fficeF&cel

bN (ile F e) F lan' Bor'boo' F %reate

2N #earner )ill na!i$ate t*e internet9 find credible sources for data.

aN (or e&ample6 *ttp6FF))).baseball4reference.comFteamsFSAFbatteam.s*tml

3N #earner )ill input statistical data into /icrosoft &cel successfully.

aN /et*od 16 Select F %opy F Paste

iN Select upper left column *eadin$ F Dra$ to lo)er ri$*t data point

iiN Ri$*t %lic' F %opy

iiiNReturn to /icrosoft &cel Tab

i!N Select upper left cell

!N Ri$*t %lic' F Paste

bN /et*od 26 %SI

iN %lic' t*e %SI lin' abo!e t*e data

iiN Select upper left *eader ro) F Dra$ to lo)er ri$*t data point

iiiNRi$*t %lic' F %opy

i!N Return to /icrosoft &cel Tab

!N Select upper left cell

!iN Ri$*t %lic' F Paste

+N #earner )ill apply and utili;e t*eFxMfunctionN tab in &cel.

aN %reate a Bin E %olumn

iN Select t*e cell immediately to t*e ri$*t of t*e last data column *eader

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iiN Type Bin E

iiiNSelect t*e cell immediately belo) t*e Bin E cell

i!N Type t*e formula for Bin E ?OR-DMBin %olumnF1stnon4*eader

ro)QFMBin %olumnF1st

non4*eader ro)Q #oss %olumnF1st

non4*eaderro)QN93N

!N Select t*e cell containin$ t*e formula abo!e F Select t*e bottom ri$*t

corner of t*is cell F Dra$ to last ro) )it* data Mt*is )ill replicate t*e

formulaN

5N #earner )ill transform ra) data in &cel into !isual representations Mi.e.

$rap*sN.aN Select t*e columns to be $rap*ed Mfor e&ample Lear9 attin$ A!era$e9 Bin

EN

bN Grap* Type 16 ,nsert F Scatter F Scatter )it* smoot* lines and mar'ers

cN Grap* Type 26 ,nsert F %olumn F Stac'ed column in 34D

N #earner )ill analy;e data9 as )ell as $rap*s9 to locate trends.

7N #earner )ill be able to apply analysis to formulate a t*eory or possible

reasonin$ be*ind trends.

"N #earner )ill de!elop a mat*ematical correlation coefficient usin$ t*e &cel

function.

aN (ormulas F /ore (unctions F Statistical F %-RR#

bN Select Array 1 Mattin$ A!era$eN

cN Select Array 2 MBin EN

N #earner )ill mana$e time )isely in order to meet deadlines.

10N #earner )ill be able to sa!e t*eir spreads*eet as it pro$resses at t*e end of

e!ery class period9 by sa!in$ t*e file to a flas* dri!e.

aN (ile F Sa!e As F &cel Bor'boo' F %omputer F (las* Dri!e F desired

folderFfilenameQ

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/b. M#TR03 B4ECT05ES

T#BE:

earnin!

b2ectives 6a7

Bloo(8s

Taxono(y

Classification6b7

or(at of

#ssess(ent 6c7

%escription of

test for( 6d7

Sa(ple ite(s

6e7

1.0 Application Performance -bser!ation

)it* c*ec'list

#earners )ill

open &cel and

preparea ne)

spreads*eet

)it*in t*ree

minutes

2.0 %ompre*end9

Analysis9

Synt*esi;e

Performance Apply Students )ill

ocateat least

one credible

)ebsite to

research and

!enerate

/ariners

statistical data3.0 Application Performance -bser!ation

)it* c*ec'list

#earners )ill

prepareand

transfer

statistical data

into &cel

successfully

+.0 Application Performance %omputer4based

obser!ation

#earners )ill

co(p$te

correlations$tili9in!t*e

F(x)function

tabQ feature in

&cel



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5.0 Hno)led$e9

%ompre*end9

Application9

Synt*esi;e

Performance %omputer4based

obser!ation

#earner )ill

convertand

transfor(ra)

data in &cel to

!enerateandprod$ce!isual

representations

Mi.e. $rap*sN.

.0 %ompre*end9

Analy;e9

!aluate


obser!ation

#earner )ill

describeand

disc$ssdata and

$rap*s in order

to correlate,

reco!ni9e and

interprettrends7.0 Synt*esis9

!aluate9

Analy;e


obser!ation

#earner )ill be

able to

interpretand

reco!ni9eor

ded$cepatterns

be*ind t*e

trends and be

able to !enerate

a t*eory orpossible

reasonin$

be*ind trends

".0 Analy;e Performance -bser!ation #earner )ill

!eneratea

mat*ematical

correlation

usin$ t*e &cel

function.

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.0 Application Performance -bser!ation

)it* c*ec'list

#earner )ill

participateand

sho-$ood time

mana$ement

s'ills time inorder to meet

deadlines.

10.0 Application Performance -bser!ation

)it* c*ec'list

#earner )ill be

able to

de(onstrate

t*eir ability to

properly sa!e

t*eir

spreads*eets

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Part / C: #RCS Table

#TTE'T0'

#.1. Percept$al #ro$sal

T*e instructor )ill s*o) a s*ort *i$*li$*ts clip of t*e Seattle /ariners.

#.&. 0n$iry #ro$sal

T*e instructor )ill s*o) t*e Seattle /ariners ?post season@ record and as' t*e

students why t*ey t*in' t*e /ariners rarely ma'e it to baseballs playoffs.

#./. 5ariability

Students )ill select 2 seasons9 of t*eir c*oice9 to analy;e.

REE5#'CE

R.1. "oal rientation

T*e instructor )ill use t*e sur!ey results to determine t*e students needs

R.&. Motive Matchin!

Students )ill be able to c*oose )*ic* )ebsites t*ey )ould li'e to use to collect

t*eir data. Students )ill also be $i!en a c*ec'list of responsibilities to *elp 'eep

t*em on trac'

R./. a(iliarity

Students are encoura$ed to relate t*eir personal e&periences )it* baseball suc* as

playin$ or )atc*in$ a $ame li!e or on t.!..

C'0%E'CE

C.1. earnin! Re$ire(ents

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Students )ill be $i!en all of t*e re8uirements and rubrics at t*e start of t*e proect.

C.&. S$ccess pport$nities

,nstruction )ill be in ?pieces@ to allo) students t*e opportunity to complete t*e

proect in s*ort sections and recei!e immediate feedbac'.

C./. Personal Control

Students )ill be able to select )*ic* 2 seasons t*ey )ould li'e to )or' )it* and

)*ic* )ebsites t*ey )ould li'e to use to collect t*eir data. Students may also

c*oose *o) t*ey )ould li'e to display t*eir data. Students may also elect to

e!aluate a team ot*er t*an t*e Seattle /ariners.

S#T0S#CT0'

S.1. 'at$ral Conse$ences

Students )ill need to follo) t*e re8uirements in order to complete subse8uent

steps.

S.&. Positive Conse$ences

T*e instructor )ill pro!ide feedbac' t*rou$*out eac* step of t*e proect. An

?innin$s@ c*art )ill be displayed to s*o) eac* student *o) muc* of t*e proectt*ey *a!e completed.

S./. E$ity

ac* student )ill *a!e clear e&pectation and obecti!es from t*e be$innin$. T*e

instructor )ill pro!ide re$ular feedbac' on eac* step of t*e proect.

EdTech 503: ID Project | Page +3


25/51

P#RT : 0'STR;CTR ";0%E

0'TR%;CT0'

#ctive #ttention ,nstructor )ill s*o) *i$*li$*t !ideos of t*e Seattle /ariners

Msee #earner /aterialsN.

Establish P$rpose Students )ill be learnin$ *o) to use /icrosoft &cel to

create and present a statistical correlation relatin$ t*e )innin$ record of t*e Seattle

/ariners to t*eir offensi!e statistics for a defined period of time9 2 seasons9 of t*e

students c*oice.

#ro$se 0nterest ) Motivation ,nstructor )ill lead a classroom discussion about

baseball in $eneral and as' students to t*eori;e )*at any baseball team needs to do

to *a!e a )innin$ season.

Previe- the earnin! #ctivity Students s*ould be pro!ided )it* a c*ec'list for

t*e proect in baseball style innin$s Mor stepsN to create t*eir proect Msee

Appendi&N. ,nstructor )ill model9 usin$ t*e )*ite board and proector9 *o) to put

a simple set of " data points into /icrosoft &cel and $enerate a $rap*. T*e

instructor )ill t*en lead a discussion of )*et*er or not t*at )as a sufficient amount

of data to disco!er a ?correlation@ or a ?trend.@

B%D/7

1.D %esi!n

1.1 0nstr$ctional Syste(s %esi!n

1.1.a tili;e and implement desi$n principles )*ic* specify optimal

conditions for learnin$.

1.1.b ,dentify a !ariety of instructional systems desi$n models and apply at

least one model.

1.1.1 Analy;in$

1.1.1.a Brite appropriate obecti!es for specific content and outcome le!els.

1.1.1.b Analy;e instructional tas's9 content9 and conte&t.

1.1.2 Desi$nin$1.1.2.a %reate a plan for a topic of a content area Me.$.9 a t*ematic unit9 a te&t

c*apter9 an interdisciplinary unitN to demonstrate application of t*e

principles of macro4le!el desi$n.

1.1.2.b %reate instructional plans Mmicro4le!el desi$nN t*at address t*e needs

of all learners9 includin$ appropriate accommodations for learners )it*

special needs.

1.1.2.d ,ncorporate contemporary instructional tec*nolo$y processes in t*e

de!elopment of interacti!e lessons t*at promote student learnin$.

1.1.3 De!elopin$

1.1.3.a Produce instructional materials )*ic* re8uire t*e use of multiple

media Me.$.9 computers9 !ideo9 proectionN.

1.1.3.b Demonstrate personal s'ill de!elopment )it* at least one6 computer

aut*orin$ application9 !ideo tool9 or electronic communication application.

1.1.+ ,mplementin$

1.1.+.a se instructional plans and materials )*ic* t*ey *a!e produced in

conte&tuali;ed instructional settin$s Me.$.9 practice9 field e&periences9trainin$N t*at address t*e needs of all learners9 includin$ appropriate

accommodations for learners )it* special needs.

1.1.5 !aluatin$

EdTech 503: ID Project | Page ,)


43/51

1.1.5.a tili;e a !ariety of assessment measures to determine t*e ade8uacy

of learnin$ and instruction.

1.1.5.b Demonstrate t*e use of formati!e and summati!e e!aluation )it*in

practice and conte&tuali;ed field e&periences.

1.1.5.c Demonstrate con$ruency amon$ $oalsFobecti!es9 instructional

strate$ies9 and assessment measures.

1./ 0nstr$ctional Strate!ies

1.3.a Select instructional strate$ies appropriate for a !ariety of learner

c*aracteristics and learnin$ situations.

1.3.b ,dentify at least one instructional model and demonstrate appropriate

conte&tuali;ed application )it*in practice and field e&periences.

1.3.c Analy;e t*eir selection of instructional strate$ies andFor models as

influenced by t*e learnin$ situation9 nature of t*e specific content9 and type

of learner obecti!e.

1.3.d Select moti!ational strate$ies appropriate for t*e tar$et learners9 tas'9

and learnin$ situation.

1. earner Characteristics

1.+.a ,dentify a broad ran$e of obser!ed and *ypot*etical learner

c*aracteristics for t*eir particular areaMsN of preparation.

1.+.b Describe andFor document specific learner c*aracteristics )*ic*

influence t*e selection of instructional strate$ies.

1.+.c Describe andFor document specific learner c*aracteristics )*ic*

influence t*e implementation of instructional strate$ies.

&.D %evelop(ent

2.0.1 Select appropriate media to produce effecti!e learnin$ en!ironments

usin$ tec*nolo$y resources.

2.0.2 se appropriate analo$ and di$ital producti!ity tools to de!elop

instructional and professional products.

2.0.3 Apply instructional desi$n principles to select appropriate

tec*nolo$ical tools for t*e de!elopment of instructional and professional

products.

EdTech 503: ID Project | Page ,+


44/51

2.0.+ Apply appropriate learnin$ and psyc*olo$ical t*eories to t*e selection

of appropriate tec*nolo$ical tools and to t*e de!elopment of instructional

and professional products.

2.0.5 Apply appropriate e!aluation strate$ies and tec*ni8ues for assessin$

effecti!eness of instructional and professional products.

2.0. se t*e results of e!aluation met*ods and tec*ni8ues to re!ise and

update instructional and professional products.

2.0.7 %ontribute to a professional portfolio by de!elopin$ and selectin$ a

!ariety of productions for inclusion in t*e portfolio.

&.1 Print Technolo!ies

2.1.3 se presentation application soft)are to produce presentations and

supplementary materials for instructional and professional purposes.

2.1.+ Produce instructional and professional products usin$ !arious aspects

of inte$rated application pro$rams.

&./ Co(p$terBased Technolo!ies

2.3.2 Desi$n9 produce9 and use di$ital information )it* computer4based

tec*nolo$ies.

/.D ;tili9ation

/.1 Media ;tili9ation3.1.1 ,dentify 'ey factors in selectin$ and usin$ tec*nolo$ies appropriate for

learnin$ situations specified in t*e instructional desi$n process.

3.1.2 se educational communications and instructional tec*nolo$y

MS/TSN resources in a !ariety of learnin$ conte&ts.

/./ 0(ple(entation and 0nstit$tionali9ation

3.3.1 se appropriate instructional materials and strate$ies in !arious

learnin$ conte&ts.

3.3.2 ,dentify and apply tec*ni8ues for inte$ratin$ S/TS inno!ations in!arious learnin$ conte&ts.

3.3.3 ,dentify strate$ies to maintain use after initial adoption.

EdTech 503: ID Project | Page ,3


45/51

.D Mana!e(ent

(none specifically addressed in 503)

>.D Eval$ation

>.1 Proble( #nalysis5.1.1 ,dentify and apply problem analysis s'ills in appropriate sc*ool media

and educational tec*nolo$y MS/TN conte&ts Me.$.9 conduct needs

assessments9 identify and define problems9 identify constraints9 identify

resources9 define learner c*aracteristics9 define $oals and obecti!es in

instructional systems desi$n9 media de!elopment and utili;ation9 pro$ram

mana$ement9 and e!aluationN.

>.& Criterionreferenced Meas$re(ent

5.2.1 De!elop and apply criterion4referenced measures in a !ariety of S/T

conte&ts.

>./ or(ative and S$((ative Eval$ation

5.3.1 De!elop and apply formati!e and summati!e e!aluation strate$ies in a

!ariety of S/T conte&ts.

S!T " School edia # !ducational Technologies

#PPE'%03

#. "radin! R$bric

EdTech 503: ID Project | Page ,,


46/51

T*is s*ould be used for t*e o!erall rubric9 peer e!aluation and self4$radin$.

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/ost M40ENbuttons and lin's

)or' correctly

/any M"475ENof t*e buttons and

lin's )or'

correctly.

(e)er t*an 75Eof t*e buttons

)or' correctly.

-ri$inality Presentation s*o)s

considerable

ori$inality andin!enti!eness. T*e

content and ideas

are presented in a

uni8ue andinterestin$ )ay.

Presentation

s*o)s some

ori$inality andin!enti!eness.

T*e content and

ideas are

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Presentation

s*o)s an attempt

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142 cards.

Presentation is a

re*as* of ot*er

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little attempt at

ori$inal t*ou$*t.

ffecti!eness Proect includes all

material needed to$ain a comfortable

understandin$ of

t*e topic. ,t is a*i$*ly effecti!e

study $uide.

Proect includes

most materialneeded to $ain a

comfortable

understandin$ oft*e material but is

lac'in$ one or

t)o 'ey elements.,t is an ade8uate

study $uide.

Proect is missin$

more t*an t)o'ey elements. ,t

)ould ma'e an

incomplete study$uide.

Proect is lac'in$

se!eral 'eyelements and *as

inaccuracies t*at

ma'e it a poorstudy $uide.

Se8uencin$ of

,nformation

,nformation is

or$ani;ed in aclear9 lo$ical )ay.

,t is easy to

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of material t*atmi$*t be on t*e

ne&t card.

/ost information

is or$ani;ed in aclear9 lo$ical )ay.

-ne card or item

of information

seems out ofplace.

Some

information islo$ically

se8uenced. An

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seems out of

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T*ere is no clear

plan for t*eor$ani;ation of

information.

B. #dditional Exa(ples for Excel:

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C. Chec+list

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References

rtmer9 P.A.9 K e)by9 T.. M13N.e*a!iorism9 co$niti!ism9 constructi!ism6

%omparin$ critical features from an instructional desi$n perspecti!e.$erformance

%mpro&ement 'uarterly M+N9 50472. Retrie!ed from*ttp6FF))).ifets.infoFournalsF3U2Ftam.*tml

D. Randy Garrison and Terry Anderson M2003N.!*+earning in the ,-st .entury/

Framework for 1esearch and $ractice4#earnin$ in t*e 21st %entury6 A

(rame)or' for Researc* and Practice. e) Lor'9 L6 Routled$e.

Gustafson9 H. #.9 K ranc*9 R. /. M17N. R,% %learin$*ouse on ,nformation

and Tec*nolo$y9 Syracuse9 L. Retrie!ed from*ttps6FFfilebo&4!t4

edu.libpro&y.boisestate.eduFusersFlilin$"5FRS(FSiteFDesi$nE20PrinciplesUfilesFSur!eyof,D/odels+t*d.pdf

Cic'man9 #.9 K Reic*9 H. Mds.N. M200N.2ohn ewey between pragmatism and

constructi&ism. (ord*am ni!ersity Press. Retrie!ed from

*ttp6FFboo's.$oo$le.com.libpro&y.boisestate.eduF

onassen9 D.C.9 K #and 9 S./. M2000N. T*eotetical foundations of learnin$

en!ironments. /a*)a*9 6 #a)rence rlbaum Associates. Stano!ic*9 H. M1+N.

%onstructi!ism in readin$ education. ournal of Special ducation9 2"M3N9 25.

/er$el9 . M1"N. ,nstructional desi$n and learnin$ t*eory.1etrie&ed from

http/44membersiinetnetaulibproxyboisestateedu46aamcarthur4--7arch7,0087

files4+earning7Theories7of7%nstructional7esignpdf

Reiser9 R.9 M2001N. A *istory of instructional desi$n and tec*nolo$y6 Part ,,6 A

*istory of instructional desi$n.!ducational Technology 1esearch and

e&elopment 9:(,)9 5"40. Retrie!ed from

*ttp6FFedtec*.mrooms.or$Fplu$infile.p*pF770FmodUpa$eFcontentF2F Cistory4of4

,DUReiser.pdf

Smit*9 P. #. K Ra$an9 T. . M2005N. ,nstructional desi$n M3rd d.N. Dan!ers9 /A6

o*n Biley K Sons.

EdTech 503: ID Project | Page ,-
http://ocw.metu.edu.tr/file.php/118/Week_6/Ertmer-Newby-beh-cog-const.pdfhttp://ocw.metu.edu.tr/file.php/118/Week_6/Ertmer-Newby-beh-cog-const.pdfhttp://ocw.metu.edu.tr/file.php/118/Week_6/Ertmer-Newby-beh-cog-const.pdfhttp://www.ifets.info/journals/3_2/tam.htmlhttp://www.ifets.info/journals/3_2/tam.htmlhttp://books.google.com/books?id=UZOG5KEoiCQC&pg=PA33&dq=define-instructional-technology&lr=&as_brr=0&ei=ClahR5qoMY_-sQPyx-2bCg&sig=P3kU_P8ZfHHGAvedqg3rF2UG7gchttp://books.google.com/books?id=UZOG5KEoiCQC&pg=PA33&dq=define-instructional-technology&lr=&as_brr=0&ei=ClahR5qoMY_-sQPyx-2bCg&sig=P3kU_P8ZfHHGAvedqg3rF2UG7gchttp://books.google.com/books?id=UZOG5KEoiCQC&pg=PA33&dq=define-instructional-technology&lr=&as_brr=0&ei=ClahR5qoMY_-sQPyx-2bCg&sig=P3kU_P8ZfHHGAvedqg3rF2UG7gchttps://filebox-vt-edu.libproxy.boisestate.edu/users/liling85/ERSF/Site/Design%20Principles_files/SurveyofIDModels4thEd.pdfhttps://filebox-vt-edu.libproxy.boisestate.edu/users/liling85/ERSF/Site/Design%20Principles_files/SurveyofIDModels4thEd.pdfhttps://filebox-vt-edu.libproxy.boisestate.edu/users/liling85/ERSF/Site/Design%20Principles_files/SurveyofIDModels4thEd.pdfhttps://filebox-vt-edu.libproxy.boisestate.edu/users/liling85/ERSF/Site/Design%20Principles_files/SurveyofIDModels4thEd.pdfhttp://books.google.com.libproxy.boisestate.edu/http://books.google.com.libproxy.boisestate.edu/http://members.iinet.net.au.libproxy.boisestate.edu/~aamcarthur/11_March_2008_files/Learning_Theories_of_Instructional_Design.pdfhttp://members.iinet.net.au.libproxy.boisestate.edu/~aamcarthur/11_March_2008_files/Learning_Theories_of_Instructional_Design.pdfhttp://members.iinet.net.au.libproxy.boisestate.edu/~aamcarthur/11_March_2008_files/Learning_Theories_of_Instructional_Design.pdfhttp://ocw.metu.edu.tr/file.php/118/Week_6/Ertmer-Newby-beh-cog-const.pdfhttp://ocw.metu.edu.tr/file.php/118/Week_6/Ertmer-Newby-beh-cog-const.pdfhttp://www.ifets.info/journals/3_2/tam.htmlhttp://www.ifets.info/journals/3_2/tam.htmlhttp://books.google.com/books?id=UZOG5KEoiCQC&pg=PA33&dq=define-instructional-technology&lr=&as_brr=0&ei=ClahR5qoMY_-sQPyx-2bCg&sig=P3kU_P8ZfHHGAvedqg3rF2UG7gchttp://books.google.com/books?id=UZOG5KEoiCQC&pg=PA33&dq=define-instructional-technology&lr=&as_brr=0&ei=ClahR5qoMY_-sQPyx-2bCg&sig=P3kU_P8ZfHHGAvedqg3rF2UG7gchttps://filebox-vt-edu.libproxy.boisestate.edu/users/liling85/ERSF/Site/Design%20Principles_files/SurveyofIDModels4thEd.pdfhttps://filebox-vt-edu.libproxy.boisestate.edu/users/liling85/ERSF/Site/Design%20Principles_files/SurveyofIDModels4thEd.pdfhttps://filebox-vt-edu.libproxy.boisestate.edu/users/liling85/ERSF/Site/Design%20Principles_files/SurveyofIDModels4thEd.pdfhttp://books.google.com.libproxy.boisestate.edu/http://books.google.com.libproxy.boisestate.edu/http://members.iinet.net.au.libproxy.boisestate.edu/~aamcarthur/11_March_2008_files/Learning_Theories_of_Instructional_Design.pdfhttp://members.iinet.net.au.libproxy.boisestate.edu/~aamcarthur/11_March_2008_files/Learning_Theories_of_Instructional_Design.pdfhttp://members.iinet.net.au.libproxy.boisestate.edu/~aamcarthur/11_March_2008_files/Learning_Theories_of_Instructional_Design.pdf


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Lilma;9 H. M200"N. %onstructi!ism6 ,ts T*eoretical nderpinnin$s9 Iariations9 and

,mplications for %lassroom ,nstruction.!ducational ;ori

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K Hefty Final ID Project