A survey of educational data - TechyLib\nA survey of educational data\n20 Νοε 2013 (πριν από 4 χρόνια και 5 μήνες)\nΑγαπημένα Αναφορά Κατέβασμα (.PDF 738KB)\nR Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nA A s su ur rv ve ey y o of f e ed du uc ca at ti io on na al l d da at ta a-m mi in ni in ng g r re es se ea ar rc ch h\nE Ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g ( (E ED DM M) ) i is s a an n e em me er rg gi in ng g d di is sc ci ip pl li in ne e t th ha at t f fo oc cu us se es s o on n a ap pp pl ly yi in ng g d da at ta a\nm m mi i in n ni i in n ng g g t t to o oo o ol l ls s s a a an n nd d d t t te e ec c ch h hn n ni i iq q qu u ue e es s s t t to o o e e ed d du u uc c ca a at t ti i io o on n na a al l ll l ly y y r r re e el l la a at t te e ed d d d d da a at t ta a a... T T Th h he e e d d di i is s sc c ci i ip p pl l li i in n ne e e f f fo o oc c cu u us s se e es s s o o on n n a a an n na a al l ly y yz z zi i in n ng g g\neducational d d da a at t ta a a t t to o o d d de e ev v ve e el l lo o op p p m m mo o od d de e el l ls s s f f fo o or r r i i im m mp p pr r ro o ov v vi i in n ng g g l l le e ea a ar r rn n ni i in n ng g g e e ex x xp p pe e er r ri i ie e en n nc c ce e es s s a a an n nd d d i i im m mp p pr r ro o ov v vi i in n ng g g\ninstitutional effectiveness. A l li it te er ra at tu ur re e r re ev vi ie ew w o on n e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g f fo ol ll lo ow ws s, which covers\nt t to o op p pi i ic c cs s s s s su u uc c ch h h a a as s s s s st t tu u ud d de e en n nt t t r r re e et t te e en n nt t ti i io o on n n a a an n nd d d a a at t tt t tr r ri i it t ti i io o on n n,,, p p pe e er r rs s so o on n na a al l l r r re e ec c co o om m mm m me e en n nd d de e er r r s s sy y ys s st t te e em m ms s s w w wi i it t th h hi i in n n e e ed d du u uc c ca a at t ti i io o on n n,,,\na a an n nd d d h h ho o ow w w d d da a at t ta a a m m mi i in n ni i in n ng g g c c ca a an n n b b be e e u u us s se e ed d d t t to o o a a an n na a al l ly y yz z ze e e c c co o ou u ur r rs s se e e m m ma a an n na a ag g ge e em m me e en n nt t t s s sy y ys s st t te e em m m d d da a at t ta a a... G G Ga a ap p ps s s i i in n n t t th h he e e c c cu u ur r rr r re e en n nt t t\nl li it te er ra at tu ur re e a an nd d o op pp po or rt tu un ni it ti ie es s f fo or r f fu ur rt th he er r r re es se ea ar rc ch h a ar re e p pr re es se en nt te ed d..\nK K Ke e ey y yw w wo o or r rd d ds s s: : : e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a m m mi i in n ni i in n ng g g,,, a a ac c ca a ad d de e em m mi i ic c c a a an n na a al l ly y yt t ti i ic c cs s s,,, l l le e ea a ar r rn n ni i in n ng g g a a an n na a al l ly y yt t ti i ic c cs s s,,, i i in n ns s st t ti i it t tu u ut t ti i io o on n na a al l l\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 1 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nThere is pressure in h hi ig gh he er r e ed du uc ca at ti io on na al l i in ns st ti it tu ut ti io on ns s t to o p pr ro ov vi id de e u up p-to-d da at te e i in nf fo or rm ma at ti io on n o on n\ninstitutional effectiveness (C C.. R Ro om me er ro o & & V Ve en nt tu ur ra a,, 2 20 01 10 0). Institutions are also i in nc cr re ea as si in ng gl ly y h he el ld d\naccountable for student success ( (Campbell & Oblinger, 2007). O On ne e r re es sp po on ns se e t to o t th hi is s p pr re es ss su ur re e i is s\nfinding new w wa ay ys s t to o a ap pp pl ly y a an na al ly yt ti ic ca al l and data mining methods t to o e ed du uc ca at ti io on na al ll ly y r re el la at te ed d d da at ta a..\nEven though data mining g g ( ( (D D DM M M) ) ) h h ha a as s s b b be e ee e en n n a a ap p pp p pl l li i ie e ed d d i i in n n n n nu u um m me e er r ro o ou u us s s i i in n nd d du u us s st t tr r ri i ie e es s s a a an n nd d d s s se e ec c ct t to o or r rs s s,,, t t th h he e e\na ap pp pl li ic ca at ti io on n o of f D DM M t to o e ed du uc ca at ti io on na al l c co on nt te ex xt ts s i is s l li im mi it te ed d (Ranjan & Malik, 2007).. R Re es se ea ar rc ch he er rs s h ha av ve e\nf f fo o ou u un n nd d d t t th h ha a at t t t t th h he e ey y y c c ca a an n n a a ap p pp p pl l ly y y d d da a at t ta a a m m mi i in n ni i in n ng g g t t to o o r r ri i ic c ch h h e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a s s se e et t ts s s t t th h ha a at t t c c co o om m me e e f f fr r ro o om m m c c co o ou u ur r rs s se e e\nm m ma a an n na a ag g ge e em m me e en n nt t t s s sy y ys s st t te e em m ms s s s s su u uc c ch h h a a as s s A A An n ng g ge e el l l,,, B B Bl l la a ac c ck k kb b bo o oa a ar r rd d d,,, W W We e eb b bC C CT T T,,, a a an n nd d d M M Mo o oo o od d dl l le e e... T T Th h he e e e e em m me e er r rg g gi i in n ng g g f f fi i ie e el l ld d d o o of f f\ne ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g ( (E ED DM M) ) e ex xa am mi in ne es s t th he e u un ni iq qu ue e w wa ay ys s o of f a ap pplying d da at ta a m mi in ni in ng g methods to\ns so ol lv ve e e ed du uc ca at ti io on na al ll ly y r re el la at te ed d p pr ro ob bl le em ms s..\nThe recent l li it te er ra at tu ur re e r re el la at te ed d t to o e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g ( (E ED DM M) ) i is s p pr re es se en nt te ed d. Educational\nd d da a at t ta a a m m mi i in n ni i in n ng g g i i is s s a a an n n e e em m me e er r rg g gi i in n ng g g d d di i is s sc c ci i ip p pl l li i in n ne e e t t th h ha a at t t f f fo o oc c cu u us s se e es s s o o on n n a a ap p pp p pl l ly y yi i in n ng g g d d da a at t ta a a m m mi i in n ni i in n ng g g t t to o oo o ol l ls s s a a an n nd d d t t te e ec c ch h hn n ni i iq q qu u ue e es s s\nto educationally related data (B Ba ak ke er r & & Y Ya ac ce ef f,, 2 20 00 09 9). Researchers within EDM f fo oc cu us s o on n t to op pi ic cs s\nr ra an ng gi in ng g f fr ro om m u us si in ng g d da at ta a m mi in ni in ng g t to o i im mp pr ro ov ve e i in ns st ti it tu ut ti io on na al l e ef ff fe ec ct ti iv ve en ne es ss s t to o a ap pp pl ly yi in ng g d da at ta a m mi in ni in ng g in\ni im mp pr ro ov vi in ng g s st tu ud de en nt t l le ea ar rn ni in ng g p pr ro oc ce es ss se es s. There is a wide range o of f t to op pi ic cs s w wi it th hi in n e ed du uc ca at ti io on na al l d da at ta a\nm mi in ni in ng g,, s so o t th hi is s p pa ap pe er r w wi il ll l f fo oc cu us s e ex xc cl lu us si iv ve el ly y o on n w wa ay ys s t th ha at t d da at ta a m mi in ni in ng g i is s u us se ed d t to o i im mp pr ro ov ve e s st tu ud de en nt t\ns su uc cc ce es ss s a an nd d p pr ro oc ce es ss se es s d di ir re ec ct tl ly y r re el la at te ed d t to student learning. For example, s st tu ud de en nt t s su uc cc ce es ss s a an nd d\nretention, personalized r r re e ec c co o om m mm m me e en n nd d de e er r r s s sy y ys s st t te e em m ms s s,,, a a an n nd d d e e ev v va a al l lu u ua a at t ti i io o on n n o o of f f s s st t tu u ud d de e en n nt t t l l le e ea a ar r rn n ni i in n ng g g w w wi i it t th h hi i in n n c c co o ou u ur r rs s se e e\nmanagement systems (CMS) a ar re e a al ll l t to op pi ic cs s w wi it th hi in n t th he e b br ro oa ad d f fie el ld d o of f e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g..\nResearchers intere es st te ed d i in n e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g e es st ta ab bl li is sh he ed d t th he e J Jo ou ur rn na al l o of f E Ed du uc ca at ti io on na al l\nData Mining ( (2 20 00 09 9) ) a an nd d a a y ye ea ar rl ly y i in nt te er rn na at ti io on na al l c co on nf fe er re en nc ce e that began in 2008. T Th he e EDM\nliterature d dr ra aw ws s f fr ro om m s se ev ve er ra al l r re ef fe er re en nc ce e d di is sc ci ip pl li in ne es s i in nc cl lu ud di in ng g d da at ta a m mi in ni in ng g,, l le ea ar rn ni in ng g t th he eo or ry y, data\nvis su ua al li iz za at ti io on n,, m ma ac ch hi in ne e l le ea ar rn ni in ng g a an nd d p ps sy yc ch ho om me et tr ri ic cs s (Baker & Yacef, 2009). S So om me e o of f t th he e e ea ar rl li ie es st t\nworks are published in the C Co on nf fe er re en nc ce e o on n A Ar rt ti if fi ic ci ia al l I In nt te el ll li ig ge en nc ce e i in n Education,, a an nd d t th he e\nI In nt te er rn na at ti io on na al l J Jo ou ur rn na al l o of f A Ar rt ti if fi ic ci ia al l I In nt te el ll li ig ge en nc ce e i in n E Ed du uc ca at ti io on n. Interestingly,, a ar rt ti if fi ic ci ia al l i in nt te el ll li ig ge en nc ce e\ni i is s s a a a l l la a ar r rg g ge e e p p pa a ar r rt t t o o of f f d d da a at t ta a a m m mi i in n ni i in n ng g g,,, w w wh h hi i ic c ch h h i i is s s w w wh h hy y y w w we e e s s se e ee e e e e ea a ar r rl l ly y y e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a m m mi i in n ni i in n ng g g p p pa a ap p pe e er r rs s s i i in n n\na ar rt ti if fi ic ci ia al l i in nt te el ll li ig ge en nc ce e r re el la at te ed d p pu ub bl li ic ca at ti io on ns.\nT Th he e p pu ur rp po os se e o of f t th hi is s p pa ap pe er r i is s t to o p pr ro ov vi id de e a survey of e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g research.\nSp p pe e ec c ci i if f fi i ic c c a a ap p pp p pl l li i ic c ca a at t ti i io o on n ns s s o o of f f e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a m m mi i in n ni i in n ng g g a a ar r re e e d d de e el l li i in n ne e ea a at t te e ed d d,,, w w wh h hi i ic c ch h h i i in n nc c cl l lu u ud d de e e s s st t tu u ud d de e en n nt t t r r re e et t te e en n nt t ti i io o on n n\na an nd d a at tt tr ri it ti io on n,, p pe er rs so on na al l r re ec co om mm me en nd de er r s sy ys st te em ms s,, a an nd d o ot th he er r d da at ta a m mi in ni in ng g s st tu ud di ie es s w wi it th hi in n c co ou ur rs se e\nmanagement systems. T Th he e p pa ap pe er r c co on nc cl lu ud de es s w wi it th h i id de en nt ti if fy yi in ng g ga ap ps s i in n t th he e c cu ur rr re en nt t l li it te er ra at tu ur re e and\nr re ec co om mm me en nd da at ti io on ns s f fo or r f fu ur rt th he er r r re es se ea ar rc ch h.\nB BA AC CK KG GR RO OU UN ND D O OF F D DA AT TA A M MI IN NI IN NG G\nBig data i i is s s a a a t t te e er r rm m m t t th h ha a at t t d d de e es s sc c cr r ri i ib b be e es s s t t th h he e e g g gr r ro o ow w wt t th h h o o of f f t t th h he e e a a am m mo o ou u un n nt t t o o of f f d d da a at t ta a a t t th h ha a at t t i i is s s a a av v vailable to an\no o or r rg g ga a an n ni i iz z za a at t ti i io o on n n a a an n nd d d t t th h he e e p p po o ot t te e en n nt t ti i ia a al l l t t to o o d d di i is s sc c co o ov v ve e er r r n n ne e ew w w i i in n ns s si i ig g gh h ht t ts s s w w wh h he e en n n a a an n na a al l ly y yz z zi i in n ng g g t t th h he e e d d da a at t ta a a... IBM suggests\nb b bi i ig g g d d da a at t ta a a s s sp p pa a an n ns s s t t th h hr r re e ee e e d d di i if f ff f fe e er r re e en n nt t t d d di i im m me e en n ns s si i io o on n ns s s,,, w w wh h hi i ic c ch h h i i in n nc c cl l lu u ud d de e e v v vo o ol l lu u um m me e e,,, v v ve e el l lo o oc c ci i it t ty y y,,, a a an n nd d d v v va a ar r ri i ie e et t ty y y (IBM,\n2012)... O O Or r rg g ga a an n ni i iz z za a at t ti i io o on n ns s s h h ha a av v ve e e a a a c c ch h ha a al l ll l le e en n ng g ge e e o o of f f s s si i if f ft t ti i in n ng g g t t th h hr r ro o ou u ug g gh h h a a al l ll l l o o of f f t t th h ha a at t t i i in n nf f fo o or r rm m ma a at t ti i io o on n n,,, a a an n nd d d n n ne e ee e ed d d\ns so ol lu ut ti io on ns s t to o d do o s so o.. D Da at ta a m mi in ni in ng g c ca an n a as ss si is st t o or rg ga an ni iz za at ti io on ns s w wi it th h u un nc co ov ve er ri in ng g u us se ef fu ul l i in nf fo or rm ma at ti io on n i in n\norder to guide decision-making ( (Kiron, Shockley y,, K Kr ru us sc ch hw wi it tz z,, F Fi in nc ch h,, & & H Ha ay yd do oc ck k,, 2 20 01 12 2). Data\nmining is a s s se e er r ri i ie e es s s o o of f f t t to o oo o ol l ls s s a a an n nd d d t t te e ec c ch h hn n ni i iq q qu u ue e es s s f f fo o or r r u u un n nc c co o ov v ve e er r ri i in n ng g g h h hi i id d dd d de e en n n p p pa a at t tt t te e er r rn n ns s s a a an n nd d d r r re e el l la a at t ti i io o on n ns s sh h hi i ip p ps s s\namong data (Dunham, 2003). D Da at ta a m mi in ni in ng g i is s a al ls so o o on ne e s st te ep p i in n a an n o ov ve er ra al ll l k kn no ow wl le ed dg ge e d di is sc co ov ve er ry y\np pr ro oc ce es ss s,, w wh he er re e o or rg ga an ni iz za at ti io on ns s w wa an nt t t to o discover new information from t th he e d da at ta a i in n o or rd de er r t to o a ai id d i in n\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 2 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\ndecision-m m ma a ak k ki i in n ng g g p p pr r ro o oc c ce e es s ss s se e es s s... K K Kn n no o ow w wl l le e ed d dg g ge e e d d di i is s sc c co o ov v ve e er r ry y y a a an n nd d d d d da a at t ta a a m m mi i in n ni i in n ng g g c c ca a an n n b b be e e t t th h ho o ou u ug g gh h ht t t o o of f f a a as s s t t to o oo o ol l ls s s for\ndecision-making and organiza at ti io on na al l e ef ff fe ec ct ti iv ve en ne es ss s.. The c co om mp pl le ex xi it ty y o of f d da at ta a m mi in ni in ng g has led the\ndata analytics community t to o e es st ta ab bl li is sh h a a s st ta an nd da ar rd d p pr ro oc ce es ss s f fo or r d da at ta a m mi in ni in ng g a ac ct ti iv vi it ti ie es s..\nT Th he e C Cr ro os ss s I In nd du us st tr ry y S St ta an nd da ar rd d P Pr ro oc ce es ss s f fo or r D Da at ta a M Mi in ni in ng g ( (C CR RI IS SP P-D DM M) ) i is s a a l li if fe e c cy yc cl le e p pr ro oc ce es ss s\nfor developing and a an na al ly yz zi in ng g d da at ta a m mi in ni in ng g m mo od de el ls s (Leventhal, 2010).. T Th he e C CR RI IS SP P-DM process is\ni i im m mp p po o or r rt t ta a an n nt t t b b be e ec c ca a au u us s se e e i i it t t g g gi i iv v ve e es s s s s sp p pe e ec c ci i if f fi i ic c c t t ti i ip p ps s s a a an n nd d d t t te e ec c ch h hn n ni i iq q qu u ue e es s s o o on n n h h ho o ow w w t t to o o m m mo o ov v ve e e f f fr r ro o om m m u u un n nd d de e er r rs s st t ta a an n nd d di i in n ng g g t t th h he e e\nb bu us si in ne es ss s d da at ta a t th hr ro ou ug gh h d de ep pl lo oy ym me en nt t o of f a a d da at ta a m mi in ni in ng g m mo od de el l.. C CR RI IS SP P-DM has s si ix x p ph ha as se es s,, which\ni i in n nc c cl l lu u ud d de e e b b bu u us s si i in n ne e es s ss s s u u un n nd d de e er r rs s st t ta a an n nd d di i in n ng g g,,, d d da a at t ta a a u u un n nd d de e er r rs s st t ta a an n nd d di i in n ng g g,,, d d da a at t ta a a p p pr r re e ep p pa a ar r ra a at t ti i io o on n n,,, m m mo o od d de e el l li i in n ng g g,,, e e ev v va a al l lu u ua a at t ti i io o on n n,,, a a an n nd d d\ndeployment (Leventhal, 2010).. T Th he e b be en ne ef fi it ts s o of f CRISM-DM are that it is non-p pr ro op pr ri ie et ta ar ry y a an nd d\ns so of ft tw wa ar re e v ve en nd do or r n ne eu ut tr ra al l,, a an nd d p pr ro ov vi id de es s a a s so ol li id d f fr ra am me ew wo or rk k f fo or r g gu ui id da an nc ce e i in n d da at ta a m mi in ni in ng g (Leventhal,\n2010)... T T Th h he e e m m mo o od d de e el l l a a al l ls s so o o i i in n nc c cl l lu u ud d de e es s s t t te e em m mp p pl l la a at t te e es s s t t to o o a a ai i id d d i i in n n a a an n na a al l ly y ys s si i is s s... T T Th h hi i is s s p p pr r ro o oc c ce e es s ss s s i i is s s u u us s se e ed d d i i in n n a a a n n nu u um m mb b be e er r r o o of f f\neducational data mining studies ( (Luan, 2002; Vialardi et al., 2011; Y.-h h.. W Wa an ng g & & L Li ia ao o,, 2 20 01 11 1),\nb bu ut t m ma ay y n no ot t b be e e ex xp pl li ic ci it tl ly y s st ta at te ed d a as s s su uc ch h..\nD D Da a at t ta a a m m mi i in n ni i in n ng g g h h ha a as s s i i it t ts s s r r ro o oo o ot t ts s s i i in n n m m ma a ac c ch h hi i in n ne e e l l le e ea a ar r rn n ni i in n ng g g,,, a a ar r rt t ti i if f fi i ic c ci i ia a al l l i i in n nt t te e el l ll l li i ig g ge e en n nc c ce e e,,, c c co o om m mp p pu u ut t te e er r r s s sc c ci i ie e en n nc c ce e e,,,\nand statistics (Dunham, 2003)... T T Th h he e er r re e e a a ar r re e e a a a v v va a ar r ri i ie e et t ty y y o o of f f d d di i if f ff f fe e er r re e en n nt t t d d da a at t ta a a m m mi i in n ni i in n ng g g t t te e ec c ch h hn n ni i iq q qu u ue e es s s a a an n nd d d\na a ap p pp p pr r ro o oa a ac c ch h he e es s s,,, s s su u uc c ch h h a a as s s c c cl l lu u us s st t te e er r ri i in n ng g g,,, c c cl l la a as s ss s si i if f fi i ic c ca a at t ti i io o on n n,,, a a an n nd d d a a as s ss s so o oc c ci i ia a at t ti i io o on n n r r ru u ul l le e e m m mi i in n ni i in n ng g g... E E Ea a ac c ch h h o o of f f t t th h he e es s se e e\na a ap p pp p pr r ro o oa a ac c ch h he e es s s c c ca a an n n b b be e e u u us s se e ed d d t t to o o q q qu u ua a an n nt t ti i it t ta a at t ti i iv v ve e el l ly y y a a an n na a al l ly y yz z ze e e l l la a ar r rg g ge e e d d da a at t ta a a s s se e et t ts s s t t to o o f f fi i in n nd d d h h hi i id d dd d de e en n n m m me e ea a an n ni i in n ng g g a a an n nd\npatterns. Da a at t ta a a m m mi i in n ni i in n ng g g i i is s s a a an n n e e ex x xp p pl l lo o or r ra a at t to o or r ry y y p p pr r ro o oc c ce e es s ss s s,,, b b bu u ut t t c c ca a an n n b b be e e u u us s se e ed d d f f fo o or r r c c co o on n nf f fi i ir r rm m ma a at t to o or r ry y y i i in n nv v ve e es s st t ti i ig g ga a at t ti i io o on n ns s s\n(B Be er rs so on n,, S Sm mi it th h,, & & T Th he ea ar rl li in ng g,, 2 20 01 11 1).. I It t i is s d di if ff fe er re en nt t f fr ro om m o ot th he er r s se ea ar rc ch hi in ng g a an nd d a an na al ly ys si is s t te ec ch hn ni iq qu ue es s\nin that data mining is highly y y e e ex x xp p pl l lo o or r ra a at t to o or r ry y y,,, w w wh h he e er r re e e o o ot t th h he e er r r a a an n na a al l ly y ys s se e es s s a a ar r re e e t t ty y yp p pi i ic c ca a al l ll l ly y y p p pr r ro o ob b bl l le e em m m-driven and\nW W Wh h hi i il l le e e d d da a at t ta a a m m mi i in n ni i in n ng g g h h ha a as s s b b be e ee e en n n a a ap p pp p pl l li i ie e ed d d i i in n n a a a v v va a ar r ri i ie e et t ty y y o o of f f i i in n nd d du u us s st t tr r ri i ie e es s s,,, g g go o ov v ve e er r rn n nm m me e en n nt t t,,, m m mi i il l li i it t ta a ar r ry y y,,,\nr r re e et t ta a ai i il l l,,, a a an n nd d d b b ba a an n nk k ki i in n ng g g,,, d d da a at t ta a a m m mi i in n ni i in n ng g g h h ha a as s s n n no o ot t t r r re e ec c ce e ei i iv v ve e ed d d m m mu u uc c ch h h a a at t tt t te e en n nt t ti i io o on n n i i in n n e e ed d du u uc c ca a at t ti i io o on n na a al l l c c co o on n nt t te e ex x xt t ts (Ranjan\n& Malik, 2007). E Ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g i is s a a f fi ie el ld d o of f s st tu ud dy y t th ha at t a an na al ly yz ze es s a an nd d a ap pp pl li ie es s d da at ta a m mi in ni in ng g\nto solve educationally-r r re e el l la a at t te e ed d d p p pr r ro o ob b bl l le e em m ms s s... A A Ap p pp p pl l ly y yi i in n ng g g d d da a at t ta a a m m mi i in n ni i in n ng g g t t th h hi i is s s w w wa a ay y y c c ca a an n n h h he e el l lp p p r r re e es s se e ea a ar r rc c ch h he e er r rs s s a a an n nd d d\np p pr r ra a ac c ct t ti i it t ti i io o on n ne e er r rs s s d d di i is s sc c co o ov v ve e er r r n n ne e ew w w w w wa a ay y ys s s t t to o o u u un n nc c co o ov v ve e er r r p p pa a at t tt t te e er r rn n ns s s a a an n nd d d t t tr r re e en n nd d ds s s w w wi i it t th h hi i in n n l l la a ar r rg g ge e e a a am m mo o ou u un n nt t ts s s o o of f f\nB BA AC CK KG GR RO OU UN ND D O OF F E ED DU UC CA AT TI IO ON NA AL L D DA AT TA A M MI IN NI IN NG G\nT Th he er re e a ar re e d di if ff fe er re en nt t w wa ay ys s t th ha at t e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g is defined. C Ca am mp pb be el ll l a an nd d O Ob bl li in ng ge er r\n(2007) defined a ac ca ad de em mi ic c a an na al ly yt ti ic cs s a as s t th he e u us se e o of f s st ta at ti is st ti ic ca al l t te ec ch hn ni iq qu ue es s a an nd d d da at ta a m mi in ni in ng g i in n w wa ay ys s\nthat will help faculty and advisor rs s b be ec co om me e m mo or re e p pr ro oa ac ct ti iv ve e i in n i id de en nt ti if fy yi in ng g a at t-r ri is sk k s st tu ud de en nt ts s a an nd d\nr re es sp po on nd di in ng g a ac cc co or rd di in ng gl ly y.. I In n t th hi is s w wa ay y,, t th he e r re es su ul lt ts s of d da at ta a m mi in ni in ng g c ca an n b be e u us se ed d t to o i im mp pr ro ov ve e s st tu ud de en nt t\nretention. A A Ac c ca a ad d de e em m mi i ic c c a a an n na a al l ly y yt t ti i ic c cs s s f f fo o oc c cu u us s se e es s s o o on n n p p pr r ro o oc c ce e es s ss s se e es s s t t th h ha a at t t o o oc c cc c cu u ur r r a a at t t t t th h he e e d d de e ep p pa a ar r rt t tm m me e en n nt t t,,, u u un n ni i it t t,,, o o or r r c c co o ol l ll l le e eg g ge e e\nand d d u u un n ni i iv v ve e er r rs s si i it t ty y y l l le e ev v ve e el l l... T T Th h hi i is s s t t ty y yp p pe e e o o of f f a a an n na a al l ly y ys s si i is s s d d do o oe e es s s n n no o ot t t f f fo o oc c cu u us s s o o on n n t t th h he e e d d de e et t ta a ai i il l ls s s o o of f f e e ea a ac c ch h h i i in n nd d di i iv v vi i id d du u ua a al l l c c co o ou u ur r rs s se e e,,,\ns so o i it t c ca an n b be e s sa ai id d t th ha at t a ac ca ad de em mi ic c a an na al ly yt ti ic cs s h ha as s a a m ma ac cr ro o p pe er rs sp pe ec ct ti iv ve e.. A Ac ca ad de em mi ic c a an na al ly yt ti ic cs s c ca an n b be e\nconsidered a sub-f fi ie el ld d o of f e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g..\nBaker and Yac c ce e ef f f ( ( (2 2 20 0 00 0 09 9 9) ) ) d d de e ef f fi i in n ne e ed d d E E ED D DM M M a a as s s “ “ “a a an n n e e em m me e er r rg g gi i in n ng g g d d di i is s sc c ci i ip p pl l li i in n ne e e,,, c c co o on n nc c ce e er r rn n ne e ed d d w w wi i it t th h h\nd d de e ev v ve e el l lo o op p pi i in n ng g g m m me e et t th h ho o od d ds s s f f fo o or r r e e ex x xp p pl l lo o or r ri i in n ng g g t t th h he e e u u un n ni i iq q qu u ue e e t t ty y yp p pe e es s s o o of f f d d da a at t ta a a t t th h ha a at t t c c co o om m me e e f f fr r ro o om m m e e ed d du u uc c ca a at t ti i io o on n na a al l l s s se e et t tt t ti i in n ng g gs s s,,,\na a an n nd d d u u us s si i in n ng g g t t th h ho o os s se e e m m me e et t th h ho o od d ds s s t t to o o b b be e et t tt t te e er r r u u un n nd d de e er r rs s st t ta a an n nd d d s s st t tu u ud d de e en n nt t ts s s,,, a a an n nd d d t t th h he e e s s se e et t tt t ti i in n ng g gs s s w w wh h hi i ic c ch h h t t th h he e ey y y l l le e ea a ar r rn n n i i in n n” ” ”\n(Baker & Yacef, 2009, p. 1). Th he ei ir r d de ef fi in ni it ti io on n d do oe es s n no ot t m me en nt ti io on n d da at ta a m mi in ni in ng g,, l le ea av vi in ng g r re es se ea ar rc ch he er rs s\nopen to exp pl lo or ri in ng g a an nd d d de ev ve el lo op pi in ng g o ot th he er r a an na al ly yt ti ic ca al l m me et th ho od ds s t th ha at t c ca an n b be e a ap pp pl li ie ed d t to o e ed du uc ca at ti io on na al ll ly y\nr r re e el l la a at t te e ed d d d d da a at t ta a a... A A Al l ls s so o o,,, m m ma a an n ny y y e e ed d du u uc c ca a at t to o or r rs s s w w wo o ou u ul l ld d d n n no o ot t t k k kn n no o ow w w h h ho o ow w w t t to o o u u us s se e e d d da a at t ta a a m m mi i in n ni i in n ng g g t t to o oo o ol l ls s s,,, t t th h hu u us s s t t th h he e er r re e e i i is s s a a a\nn n ne e ee e ed d d t t to o o m m ma a ak k ke e e i i it t t e e ea a as s sy y y f f fo o or r r e e ed d du u uc c ca a at t to o or r rs s s t t to o o c c co o on n nd d du u uc c ct t t a a ad d dv v va a an n nc c ce e ed d d a a an n na a al l ly y yt t ti i ic c cs s s a a ag g ga a ai i in n ns s st t t d d da a at t ta a a t t th h ha a at t t p p pe e er r rt t ta a ai i in n ns s s t t to o o\nthem (such as on nl li in ne e C CM MS S d da at ta a,, e et tc c..) ).. O On ne e o of f t th he e a ad dv va an nt ta ag ge es s t to o t th he ei ir r r re es se ea ar rc ch h i is s t th ha at t i it t p pr ro ov vi id de es s a a\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 3 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nb br ro oa ad d r re ep pr re es se en nt ta at ti io on n o of f t th he e E ED DM M f fi ie el ld d s so o f fa ar r b by y d di is sc cu us ss si in ng g t th he e p pr ro om mi in ne en nt t p pa ap pe er rs s i in n t th he e f fi ie el ld d.\nHowever, their research u us se ed d t th he e n nu um mb be er r o of f a ar rt ti ic cl le e c ci it ta at ti io on ns s a as s a a w wa ay y t to o e ev va al lu ua at te e g gr ro ow wt th h o of f\nE E ED D DM M M... P P Pe e er r rh h ha a ap p ps s s f f fu u ut t tu u ur r re e e r r re e es s se e ea a ar r rc c ch h h c c ca a an n n u u us s se e ed d d a a a b b br r ro o oa a ad d de e er r r p p pe e er r rs s sp p pe e ec c ct t ti i iv v ve e e w w wh h he e en n n e e ev v va a al l lu u ua a at t ti i in n ng g g t t th h hi i is s s d d di i is s sc c ci i ip p pl l li i in n ne e e’ ’ ’s s s\nIn evaluating t t th h he e e a a ab b bo o ov v ve e e t t tw w wo o o d d de e ef f fi i in n ni i it t ti i io o on n ns s s,,, e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a m m mi i in n ni i in n ng g g i i is s s a a a b b br r ro o oa a ad d de e er r r t t te e er r rm m m t t th h ha a at t t\nfocuses o on n n ne ea ar rl ly y a an ny y t ty yp pe e o of f d da at ta a i in n e ed du uc ca at ti io on na al l i in ns st ti it tu ut ti io on ns s,, w wh hi il le e a ac ca ad de em mi ic c a an na al ly yt ti ic cs s is\nspecific to d da at ta a r re el la at te ed d t to o i in ns st ti it tu ut ti io on na al l e ef ff fe ec ct ti iv ve en ne es ss s and student retention issues. As noted earlier,\nt th he e d di is sc ci ip pl li in ne e r re el li ie es s o on n s se ev ve er ra al l r re ef fe er re en nc ce e d di is sc ci ip pl li in ne es s a an nd d i in n t th he e future, t th he er re e w wi il ll l b be e additional\ngrowth in th he e i in nt te er rd di is sc ci ip pl li in na ar ry y n na at tu ur re e o of f E ED DM M.. As the discipline grows, r re es se ea ar rc ch he er rs s w wi il ll l need to\nr r re e ef f fi i in n ne e e t t th h he e e s s sc c co o op p pe e e a a an n nd d d d d de e ef f fi i in n ni i it t ti i io o on n ns s s o o of f f E E ED D DM M M... A A At t t t t th h hi i is s s e e ea a ar r rl l ly y y s s st t ta a ag g ge e e,,, i i it t t w w wo o ou u ul l ld d d b b be e e h h he e el l lp p pf f fu u ul l l t t to o o h h ha a av v ve e e a a a more\nthorough t ta ax xo on no om my y o of f t th he e d di if ff fe er re en nt t a ar re ea as s o of f s st tu ud dy y w wi it th hi in n E ED DM M,, e ev ve en n t th ho ou ug gh h a a b ba as si ic c t ta ax xo on no om my y\nh ha as s a al lr re ea ad dy y b be ee en n e es st ta ab bl li is sh he ed d b by y r re es se ea ar rc ch he er rs s (Baker & Yacef, 2009). O On ne e d dr ra aw wb ba ac ck k t to o B Ba ak ke er r a an nd d\nY Ya ac ce ef f’ ’s s t ta ax xo on no om my y ( (2 20 00 09 9) ) i is s t th ha at t i it t d do oe es s n no ot t a ad dd dr re es ss s a as sp pe ec ct ts s o of f t th he e c cl lu us st te er ri in ng g d da at ta a m mi in ni in ng g t ta as sk k..\nPe er rh ha ap ps s f fu ut tu ur re e r re es se ea ar rc ch h c co ou ul ld d e ex xp pa an nd d o on n t th he e c cl lu us st te er ri in ng g a as sp pe ec ct ts s o of f E ED DM M..\nThe scope of ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g includes areas s t th ha at t d di ir re ec ct tl ly y i im mp pa ac ct t s st tu ud de en nt ts s.. F Fo or r\ne ex xa am mp pl le e,, m mi in ni in ng g c co ou ur rs se e c co on nt te en nt t a an nd d the e d de ev ve el lo op pm me en nt t o of f r re ec co om mm me en nd de er r s sy ys st te em ms s ( (t to o b be e discussed\nl la at te er r i in n t th hi is s p pa ap pe er r) ).. O Ot th he er r a ar re ea as s w wi it th hi in n E ED DM M i in nc cl lu ud de e a an na al ly ys si is s o of f e ed du uc ca at ti io on na al l p pr ro oc ce es ss se es s i in nc cl lu ud di in ng g\na ad dm mi is ss si io on ns s,, a al lu um mn ni i r re el la at ti io on ns s,, a an nd d c co ou ur rs se e s se el le ec ct ti io on ns s. Furthermore, applications o of f s sp pe ec ci if fi ic c d da at ta a\nmining tec c ch h hn n ni i iq q qu u ue e es s s s s su u uc c ch h h a a as s s w w we e eb b b m m mi i in n ni i in n ng g g,,, c c cl l la a as s ss s si i if f fi i ic c ca a at t ti i io o on n n,,, a a as s ss s so o oc c ci i ia a at t ti i io o on n n r r ru u ul l le e e m m mi i in n ni i in n ng g g,,, a a an n nd d d m m mu u ul l lt t ti i iv v va a ar r ri i ia a at t te e e\nstatistics a ar re e a al ls so o k ke ey y t te ec ch hn ni iq qu ue es s a ap pp pl li ie ed d t to o e ed du uc ca at ti io on na al ll ly y r re el la at te ed d d da at ta a (C Ca al ld de er rs s & & P Pe ec ch he en ni iz zk ki iy y,,\n2012). These data mining m me et th ho od ds s are largely exploratory techniques that c ca an n b be e u us se ed d f fo or r\np pr re ed di ic ct ti io on n a an nd d f fo or re ec ca as st ti in ng g o of f l le ea ar rn ni in ng g and institutional improvement needs. A Al ls so o,, t th he e t te ec ch hn ni iq qu ue es s\nc c ca a an n n b b be e e u u us s se e ed d d f f fo o or r r m m mo o od d de e el l li i in n ng g g i i in n nd d di i iv v vi i id d du u ua a al l l d d di i if f ff f fe e er r re e en n nc c ce e es s s i i in n n s s st t tu u ud d de e en n nt t ts s s a a an n nd d d p p pr r ro o ov v vi i id d de e e a a a w w wa a ay y y t t to o o r r re e es s sp p po o on n nd d d t t to o o\nt th ho os se e d di if ff fe er re en nc ce es s t th hu us s i im mp pr ro ov ve e s st tu ud de en nt t l le ea ar rn ni in ng g (Corbett, 2001). A Al lt th ho ou ug gh h,, o on ne e q qu ue estion is how\ndo institutions a ad do op pt t e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g t to o i im mp pr ro ov ve e i in ns st ti it tu ut ti io on na al l e ef ff fe ec ct ti iv ve en ne es ss s? ?\nI I In n n o o or r rd d de e er r r f f fo o or r r e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a m m mi i in n ni i in n ng g g t t to o o b b be e e s s su u uc c cc c ce e es s ss s sf f fu u ul l l,,, i i it t t i i is s s c c cr r ri i it t ti i ic c ca a al l l t t to o o h h ha a av v ve e e a a a s s so o ol l li i id d d d d da a at t ta a a\nwarehousing strategy. G Gu ua an n e et t a al l.. ( (2 20 00 02 2) ) d di is sc cu us ss se ed d h ho ow w i im mp po or rt ta an nt t i it t i is s t to o h ha av ve e m me ea an ni in ng gf fu ul l\ni in nf fo or rm ma at ti io on n a av va ai il la ab bl le e f fo or r d de ec ci is si io on n-m ma ak ke er rs s w wi it th hi in n h hi ig gh he er r e ed du uc ca at ti io on na al l i in ns st ti it tu ut ti io on ns s.. It is a challenge\nto get the information that d de ec ci is si io on n m ma ak ke er rs s n ne ee ed d q qu ui ic ck kl ly y a an nd d e ef ff fi ic ci ie en nt tl ly y.. S So om me e o of f t th he e p pr ri im ma ar ry y\ndrivers of in n ni i it t ti i ia a at t ti i in n ng g g d d da a at t ta a a w w wa a ar r re e eh h ho o ou u us s se e e p p pr r ro o oj j je e ec c ct t ts s s i i in n nc c cl l lu u ud d de e e i i in n nc c cr r re e ea a as s se e ed d d c c co o om m mp p pe e et t ti i it t ti i iv v ve e e l l la a an n nd d ds s sc c ca a ap p pe e e,,, and\ni i in n nc c cr r re e ea a as s se e ed d d r r re e es s sp p po o on n ns s si i ib b bi i il l li i it t ti i ie e es s s o o of f f r r re e ep p po o or r rt t ti i in n ng g g t t to o o e e ex x xt t te e er r rn n na a al l l s s st t ta a ak k ke e eh h ho o ol l ld d de e er r rs s s s s su u uc c ch h h a a as s s p p pa a ar r re e en n nt t ts s s,,, b b bo o oa a ar r rd d d m m me e em m mb b be e er r rs s s,,,\nl le eg gi is sl la at to or rs s a an nd d c co om mm mu un ni it ty y l le ea ad de er rs s (Guan, Nunez, & Welsh, 2002).\nEducational data mining c ca an draw u up po on n i id de ea as s f fr ro om m o or rg ga an ni iz za at ti io on na al l d da at ta a m mi in ni in ng g..\nO O Or r rg g ga a an n ni i iz z za a at t ti i io o on n na a al l l d d da a at t ta a a m m mi i in n ni i in n ng g g ( ( (O O OD D DM M M) ) ) f f fo o oc c cu u us s se e es s s o o on n n a a as s ss s si i is s st t ti i in n ng g g o o or r rg g ga a an n ni i iz z za a at t ti i io o on n ns s s w w wi i it t th h h s s su u us s st t ta a ai i in n ni i in n ng g g\ncompetitive advantage (N Ne em ma at ti i & & B Ba ar rk ko o,, 2 20 00 04 4).. T Th he e k ke ey y d di if ff fe er re en nc ce e b be et tw we ee en n D DM M a an nd d O OD DM M i is s\nt th ha at t O OD DM M r re el li ie es s o on n o or rg ga an ni iz za at ti io on na al l t th he eo or ry y a as s a a r re ef fe er re en nc ce e d di is sc ci ip pl li in ne e (N Ne em ma at ti i & & B Ba ar rk ko o,, 2 20 00 04 4).\nO O Or r rg g ga a an n ni i iz z za a at t ti i io o on n ns s s t t th h ha a at t t t t tr r ra a an n ns s sf f fo o or r rm m m t t th h he e ei i ir r r d d da a at t ta a a i i in n nt t to o o u u us s se e ef f fu u ul l l i i in n nf f fo o or r rm m ma a at t ti i io o on n n a a an n nd d d k k kn n no o ow w wl l le e ed d dg g ge e e,,, a a an n nd d d d d do o o s s so o o\ne ef ff fi ic ci ie en nt tl ly y,, s sh ho ou ul ld d g ga ai in n t tr re em me en nd do ou us s b be en ne ef fi it ts s s su uc ch h a as s e en nh ha an nc ce ed d d de ec ci is si io on n-m ma ak ki in ng g,, i in nc cr re ea as se ed d\ncompetitiveness, and poten nt ti ia al l f fi in na an nc ci ia al l g ga ai in ns s (Nemati & Barko, 2004). T Th he er re ef fo or re e,, t th he e E ED DM M\nf fi ie el ld d d dr ra aw ws s u up po on n o or rg ga an ni iz za at ti io on na al l t th he eo or ry y a as s w we el ll l.. T Th hi is s i is s a an n i im mp po or rt ta an nt t r re el la at ti io on ns sh hi ip p b be ec ca au us se e t th he e\nf f fo o oc c cu u us s s o o of f f r r re e es s se e ea a ar r rc c ch h h w w wi i it t th h hi i in n n E E ED D DM M M c c ca a an n n e e ex x xa a am m mi i in n ne e e p p ph h he e en n no o om m me e en n na a a a a at t t d d di i if f ff f fe e er r re e en n nt t t l l le e ev v ve e el l ls s s o o of f f a a an n na a al l ly y ys s si i is s s,,, f f fr r ro o om m m\ns so oc ci ie et ta al l,, o or rg ga an ni iz za at ti io on na al l,, u un ni it t,, o or r i in nd di iv vi id du ua al l l le ev ve el l..\nT T Th h he e e t t ty y yp p pe e e o o of f f r r re e es s se e ea a ar r rc c ch h h d d do o on n ne e e w w wi i it t th h hi i in n n E E ED D DM M M f f fo o oc c cu u us s se e es s s p p pr r ri i im m ma a ar r ri i il l ly y y o o on n n q q qu u ua a an n nt t ti i it t ta a at t ti i iv v ve e e a a an n na a al l ly y ys s se e es s s,,, w w wh h hi i ich\ni i is s s n n ne e ec c ce e es s ss s sa a ar r ry y y b b be e ec c ca a au u us s se e e d d da a at t ta a a m m mi i in n ni i in n ng g g e e em m mp p pl l lo o oy y ys s s s s st t ta a at t ti i is s st t ti i ic c cs s s,,, m m ma a ac c ch h hi i in n ne e e l l le e ea a ar r rn n ni i in n ng g g,,, a a an n nd d d a a ar r rt t ti i if f fi i ic c ci i ia a al l l i i in n nt t te e el l ll l li i ig g ge e en n nc c ce e e\nt t te e ec c ch h hn n ni i iq q qu u ue e es s s... M M Ma a an n ny y y o o of f f t t th h he e e s s st t tu u ud d di i ie e es s s p p pr r re e es s se e en n nt t te e ed d d i i in n n t t th h hi i is s s l l li i it t te e er r ra a at t tu u ur r re e e r r re e ev v vi i ie e ew w w a a ar r re e e c c ca a as s se e e s s st t tu u ud d di i ie e es s s w w wh h he e er r re e e d d da a at t ta a a\nm mi in ni in ng g p pr ro oj je ec ct ts s w we er re e d do on ne e a at t a a s sp pe ec ci if fi ic c i in ns st ti it tu ut ti io on n,, w wi it th h a a s si in ng gl le e i in ns st ti it tu ut ti io on n’ ’s s d da at ta a.. Q Qu ua al li it ta at ti iv ve e\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 4 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nt t te e ec c ch h hn n ni i iq q qu u ue e es s s s s su u uc c ch h h a a as s s i i in n nt t te e er r rv v vi i ie e ew w ws s s a a an n nd d d d d do o oc c cu u um m me e en n nt t t a a an n na a al l ly y ys s si i is s s a a ar r re e e a a al l ls s so o o u u us s se e ed d d t t to o o s s su u up p pp p po o or r rt t t c c ca a as s se e e s s st t tu u ud d di i ie e es s s i i in n n\nE E ED D DM M M... T T Th h he e e d d do o om m mi i in n na a an n nt t t r r re e es s se e ea a ar r rc c ch h h p p pa a ar r ra a ad d di i ig g gm m m i i is s s q q qu u ua a an n nt t ti i it t ta a at t ti i iv v ve e e,,, w w wi i it t th h h r r re e es s su u ul l lt t ts s s c c co o om m mi i in n ng g g i i in n n t t th h he e e f f fo o or r rm m m o o of f f\npredictions, clusters or classifica at ti io on ns s,, o or r a as ss so oc ci ia at ti io on ns s.. T Th he e d dr ra aw wb ba ac ck k w wi it th h s so om me e o of f t th he e e ex xi is st ti in ng g\nc c ca a as s se e e s s st t tu u ud d di i ie e es s s i i is s s t t th h ha a at t t t t th h he e e r r re e es s su u ul l lt t ts s s a a ar r re e e n n no o ot t t n n ne e ec c ce e es s ss s sa a ar r ri i il l ly y y g g ge e en n ne e er r ra a al l li i iz z za a ab b bl l le e e t t to o o o o ot t th h he e er r r i i in n ns s st t ti i it t tu u ut t ti i io o on n ns s s... T T Th h hi i is s s m m me e ea a an n ns s s\nt t th h ha a at t t t t th h he e e r r re e es s su u ul l lt t ts s s a a ar r re e e h h hi i ig g gh h hl l ly y y a a as s ss s so o oc c ci i ia a at t te e ed d d w w wi i it t th h h a a a s s sp p pe e ec c ci i if f fi i ic c c i i in n ns s st t ti i it t tu u ut t ti i io o on n n a a at t t a a a s s sp p pe e ec c ci i if f fi i ic c c t t ti i im m me e e... Research in\nE ED DM M s sh ho ou ul ld d e ex xa am mi in ne e w wa ay ys s f fo or r d da at ta a m mi in ni in ng g r re es su ul lt ts s t to o b be e m mo or re e g ge en ne er ra al li iz za ab bl le e..\nA AP PP PL LI IC CA AT TI IO ON NS S O OF F D DA AT TA A M MI IN NI IN NG G\nA r re ev vi ie ew w o of f r re el la at te ed d l li it te er ra at tu ur re e i in n e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g follows. It f fo oc cu us se es s o on n h ho ow w d da at ta a\nm mi in ni in ng g i is s u us se ed d f fo or r i im mp pr ro ov vi in ng g s st tu ud de en nt t s su uc cc ce es ss s a an nd d p pr ro oc cesses directly related t to o s st tu ud de en nt t l le ea ar rn ni in ng g..\nE Ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g r re es se ea ar rc ch h e ex xa am mi in ne es s d di if ff fe er re en nt t w wa ay ys s t th ha at t c co ou ur rs se e m ma an na ag ge em me en nt t s sy ys st te em ms s\n( ( (C C CM M MS S S) ) ) d d da a at t ta a a c c ca a an n n b b be e e m m mi i in n ne e ed d d t t to o o p p pr r ro o ov v vi i id d de e e n n ne e ew w w p p pa a at t tt t te e er r rn n ns s s o o of f f s s st t tu u ud d de e en n nt t t b b be e eh h ha a av v vi i io o or r r... R R Re e es s su u ul l lt t ts s s c c ca a an n n a a as s ss s si i is s st t t f f fa a ac c cu u ul l lt t ty y y\nand staff with improving lear r rn n ni i in n ng g g a a an n nd d d s s su u up p pp p po o or r rt t ti i in n ng g g e e ed d du u uc c ca a at t ti i io o on n na a al l l p p pr r ro o oc c ce e es s ss s se e es s s,,, w w wh h hi i ic c ch h h i i in n n t t tu u ur r rn n n i i im m mp p pr r ro o ov v ve e e\nS St tu ud de en nt t R Re et te en nt ti io on n a an nd d A At tt tr ri it ti io on n\nR Re es se ea ar rc ch h h ha as s s sh ho ow wn n t th ha at t d da at ta a m mi in ni in ng g c ca an n b be e u us se ed d t to o d di is sc co ov ve er r a at t-r ri is sk k s st tu ud de en nt ts s a an nd d h he el lp p\ni in ns st ti it tu ut ti io on ns s b be ec co om me e m mu uc ch h m mo or re e p pr ro oa ac ct ti iv ve e in identifying and responding to t th ho os se e s st tu ud de en nt ts s (Luan,\n2002). Luan (2002) a a ap p pp p pl l li i ie e ed d d d d da a at t ta a a m m mi i in n ni i in n ng g g a a as s s a a a w w wa a ay y y t t to o o p p pr r re e ed d di i ic c ct t t w w wh h ha a at t t t t ty y yp p pe e es s s o o of f f s s st t tu u ud d de e en n nt t ts s s w w wo o ou u ul l ld d d d d dr r ro o op p p\no ou ut t o of f s sc ch ho oo ol l,, a an nd d t th he en n r re et tu ur rn n t to o s sc ch ho oo ol l l la at te er r o on n.. H He e a ap pp pl li ie ed d c cl la as ss si if fi ic ca at ti io on n a an nd d r re eg gr re es ss si io on n t tr re ee es s\n(C&RT) – a a s sp pe ec ci if fi ic c d da at ta a m mi in ni in ng g t te ec ch hn ni iq qu ue e – t to o e ed du uc ca at ti io on na al l d da at ta a i in n o or rd de er r t to o p pr re ed di ic ct t w wh hi ic ch h\ns s st t tu u ud d de e en n nt t ts s s a a ar r re e e u u un n nl l li i ik k ke e el l ly y y t t to o o r r re e et t tu u ur r rn n n t t to o o s s sc c ch h ho o oo o ol l l... I I In n n t t th h hi i is s s c c ca a as s se e e s s st t tu u ud d dy y y,,, L L Lu u ua a an n n a a ap p pp p pl l li i ie e ed d d b b bo o ot t th h h q q qu u ua a an n nt t ti i it t ta a at t ti i iv v ve e e a a an n nd d d\nqualitative research t t te e ec c ch h hn n ni i iq q qu u ue e es s s t t to o o u u un n nc c co o ov v ve e er r r s s st t tu u ud d de e en n nt t t s s su u uc c cc c ce e es s ss s s f f fa a ac c ct t to o or r rs s s... T T Th h hi i is s s r r re e es s se e ea a ar r rc c ch h h i i is s s i i im m mp p po o or r rt t ta a an n nt t t\nb be ec ca au us se e i it t d de em mo on ns st tr ra at te ed d t th he e s su uc cc ce es ss sf fu ul l a ap pp pl li ic ca at ti io on n o of f d da at ta a m mi in ni in ng g t to oo ol ls s t to o a as ss si is st t in student\nr r re e et t te e en n nt t ti i io o on n n e e ef f ff f fo o or r rt t ts s s... A A As s s n n no o ot t te e ed d d e e ea a ar r rl l li i ie e er r r,,, t t th h he e e c c ca a as s se e e s s st t tu u ud d dy y y m m me e et t th h ho o od d d f f fo o or r r E E ED D DM M M m m ma a ay y y o o of f ft t te e en n n p p pr r ro o od d du u uc c ce e e r r re e es s sults that\na a ar r re e e n n no o ot t t g g ge e en n ne e er r ra a al l li i iz z za a ab b bl l le e e... H H Ho o ow w we e ev v ve e er r r,,, t t th h he e e p p pr r ro o oc c ce e es s ss s s b b by y y w w wh h hi i ic c ch h h r r re e es s se e ea a ar r rc c ch h he e er r rs s s a a ap p pp p pl l ly y y t t th h he e e d d da a at t ta a a m m mi i in n ni i in n ng g g can be\ng g ge e en n ne e er r ra a al l li i iz z ze e ed d d a a an n nd d d u u us s se e ed d d i i in n n o o ot t th h he e er r r c c co o on n nt t te e ex x xt t ts s s... I I It t t i i is s s s s si i im m mp p pl l ly y y t t th h he e e r r re e es s su u ul l lt t ts s s o o of f f t t th h he e e d d da a at t ta a a m m mi i in n ni i in n ng g g m m mo o od d de e el l ls s s t t th h ha a at t t\nmay not be generalized.\nI In n a a r re el la at te ed d s st tu ud dy y,, L Li in n ( (2 20 01 12 2) ) a ap pp pl li ie ed d d da at ta a m mi in ni in ng g a as s a a w wa ay y t to o i im mp pr ro ov ve e s st tu ud de en nt t r re et te en nt ti io on n\ne e ef f ff f fo o or r rt t ts s s... L L Li i in n n ( ( (2 2 20 0 01 1 12 2 2) ) ) w w wa a as s s a a ab b bl l le e e t t to o o g g ge e en n ne e er r ra a at t te e e p p pr r re e ed d di i ic c ct t ti i iv v ve e e m m mo o od d de e el l ls s s b b ba a as s se e ed d d o o on n n i i in n nc c co o om m mi i in n ng g g s s st t tu u ud d de e en n nt t ts s s’ ’ ’ d d da a at t ta a a... T T Th h he e e\nm mo od de el ls s w we er re e a ab bl le e t to o p pr ro ov vi id de e s sh ho or rt t-t te er rm m a ac cc cu ur ra ac cy y f fo or r p pr re ed di ic ct ti in ng g w wh hi ic ch h t ty yp pe es s o of f s st tu ud de en nt ts s w wo ou ul ld d\nbenefit f fr ro om m s st tu ud de en nt t r re et te en nt ti io on n p pr ro og gr ra am ms s o on n c ca am mp pu us s.. T Th he e r re es se ea ar rc ch h s st tu ud dy y f fo ou un nd d t th ha at t c ce er rt ta ai in n\nm ma ac ch hi in ne e l le ea ar rn ni in ng g a al lg go or ri it th hm ms s c ca an n p pr ro ov vi id de e u us se ef fu ul l p pr re ed di ic ct ti io on ns s o of f s st tu ud de en nt t r re et te en nt ti io on n ( (Lin, 2012).\nR Re es se ea ar rc ch he er rs s a at t B Bo ow wi ie e S St ta at te e U Un ni iv ve er rs si it ty developed a system b ba as se ed d o on n d da at ta a m mi in ni in ng g that\nsupports and improves retention (Chacon, Spicer, & Valbuena, 2012). Their sys st te em m h he el lp ps s t th he e\ni in ns st ti it tu ut ti io on n i id de en nt ti if fy y a an nd d r re es sp po on nd d t to o a at t-r ri is sk k s st tu ud de en nt ts s.. T Th he ei ir r r re es se ea ar rc ch h c co on nt tr ri ib bu ut te es s m me ea an ni in ng gf fu ul ll ly y t to o t th he e\nEDM literature b be ec ca au us se e i it t d de em mo on ns st tr ra at te es s a successful implementation and use o of f d da at ta a m mi in ni in ng g..\nT T Th h he e ei i ir r r w w wo o or r rk k k i i is s s h h hi i ig g gh h hl l ly y y r r re e ep p pr r re e es s se e en n nt t ta a at t ti i iv v ve e e o o of f f t t th h he e e d d di i is s sc c ci i ip p pl l li i in n ne e e i i in n n t t th h ha a at t t i i it t t f f fo o ol l ll l lo o ow w ws s s a a a s s st t tr r ri i ic c ct t t d d da a at t ta a a m m mi i in n ni i in n ng g g p p pr r ro o oc c ce e es s ss s s\nand is quantitative. C Ch ha ac co on n e et t a al l..’ ’s s (2012) r re es se ea ar rc ch h s su up pp po or rt ts s o ot th he er r w wo or rk k d do on ne e i in n a ap pp pl ly yi in ng g d da at ta a\nm mi in ni in ng g t to o s st tu ud de en nt t r re et te en nt ti io on n i is ss su ue es s,, s su uc ch h a as s L Li in n ( (2 20 01 12 2) ) a an nd d L Lu ua an n ( (2 20 01 12 2) ),, a al ll l w wi it th h s su uc cc ce es ss sf fu ul l\nresults. T T Th h he e e w w wo o or r rk k k b b by y y C C Ch h ha a ac c co o on n n e e et t t a a al l l... g g go o oe e es s s o o on n ne e e s s st t te e ep p p f f fu u ur r rt t th h he e er r r t t th h ha a an n n L L Li i in n n a a an n nd d d L L Lu u ua a an n n,,, b b be e ec c ca a au u us s se e e t t th h he e e\nr r re e es s se e ea a ar r rc c ch h he e er r rs s s w w we e er r re e e a a ab b bl l le e e t t to o o d d de e ev v ve e el l lo o op p p a a an n nd d d i i im m mp p pl l le e em m me e en n nt t t t t th h he e ei i ir r r s s so o ol l lu u ut t ti i io o on n n i i in n n a a a p p pr r ro o od d du u uc c ct t ti i io o on n n e e en n nv v vi i ir r ro o on n nm m me e en n nt t t...\nB Bo ow wi ie e S St ta at te e U Un ni iv ve er rs si it ty y u us se es s t th he e s sy ys st te em m t to o a aid in student retention efforts.\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 5 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nD D Da a at t ta a a m m mi i in n ni i in n ng g g w w wa a as s s u u us s se e ed d d t t to o o a a as s ss s se e es s ss s s t t th h he e e e e ef f ff f fi i ic c ca a ac c cy y y o o of f f a a a w w wr r ri i it t ti i in n ng g g c c ce e en n nt t te e er r r i i in n n a a an n n e e ef f ff f fo o or r rt t t t t to o o a a an n na a al l ly y yz z ze e e\ns st tu ud de en nt t a ac ch hi ie ev ve em me en nt t a an nd d s st tu ud de en nt t p pr ro og gr re es ss s t to o t th he e n ne ex xt t g gr ra ad de e (Y Ye ea at ts s,, R Re ed dd dy y,, W Wh he ee el le er r,, S Se en ni io or r,, & &\nMurray, 2010). T T Th h he e ei i ir r r w w wo o or r rk k k d d de e em m mo o on n ns s st t tr r ra a at t te e ed d d t t th h he e e a a ab b bi i il l li i it t ty y y t t to o o a a as s ss s se e es s ss s s a a a s s sp p pe e ec c ci i if f fi i ic c c e e ed d du u uc c ca a at t ti i io o on n na a al l l s s su u up p pp p po o or r rt t t\nprocess, i.e., the writing center, i i in n n a a an n n e e ef f ff f fo o or r rt t t t t to o o i i im m mp p pr r ro o ov v ve e e i i in n ns s st t ti i it t tu u ut t ti i io o on n na a al l l e e ef f ff f fe e ec c ct t ti i iv v ve e en n ne e es s ss s s... T T Th h he e ei i ir r r r r re e es s se e ea a ar r rc c ch h h\napproach used a combination o o of f f q q qu u ua a an n nt t ti i it t ta a at t ti i iv v ve e e w w wo o or r rk k k a a an n nd d d c c ca a as s se e e s s st t tu u ud d dy y y a a an n na a al l ly y ys s si i is s s... T T Th h he e e m m mi i ix x xe e ed d d-methods\na a ap p pp p pr r ro o oa a ac c ch h h t t to o o d d da a at t ta a a m m mi i in n ni i in n ng g g w w wa a as s s h h he e el l lp p pf f fu u ul l l i i in n n u u un n nd d de e er r rs s st t ta a an n nd d di i in n ng g g m m mu u uc c ch h h m m mo o or r re e e a a ab b bo o ou u ut t t t t th h he e e w w wa a ay y ys s s d d da a at t ta a a m m mi i in n ni i in n ng g g\nc c ca a an n n b b be e e u u us s se e ed d d i i in n n a a an n n a a ac c ct t tu u ua a al l l i i im m mp p pl l le e em m me e en n nt t ta a at t ti i io o on n n... T T Th h he e ei i ir r r r r re e es s se e ea a ar r rc c ch h h r r re e es s su u ul l lt t ts s s w w we e er r re e e n n no o ot t t s s su u ur r rp p pr r ri i is s si i in n ng g g i i in n n t t th h ha a at t t i i it t t\nfound s st tu ud de en nt ts s w wh ho o a at tt te en nd d w wr ri it ti in ng g c ce en nt te er rs s t te en nd d t to o d do o b be et tt te er r i in n t th he ei ir r c cl la as ss se es s.. T Th he e r re es se ea ar rc ch h b by y\nYeats et al. (2010) t to oo ok k a a d di if ff fe er re en nt t a ap pp pr ro oa ac ch h t to o analyzing student achievement i in n t th ha at t i it t m ma ad de e t th he e\nc co on nn ne ec ct ti io on n b be et tw we ee en n w wr ri it ti in ng g c ce en nt te er r a at tt te en nd da an nc ce e a an nd d s st tu ud de en nt t g gr ra ad de es s.. I It t d di id d n no ot t m ma ak ke e t th he e l li in nk k t to o\ns s st t tu u ud d de e en n nt t t r r re e et t te e en n nt t ti i io o on n n i i is s ss s su u ue e es s s,,, b b bu u ut t t a a a f f fu u ut t tu u ur r re e e s s st t tu u ud d dy y y c c co o ou u ul l ld d d e e ex x xa a am m mi i in n ne e e t t th h he e e r r re e el l la a at t ti i io o on n ns s sh h hi i ip p p b b be e et t tw w we e ee e en n n t t th h he e es s se e e t t th h hr r re e ee e e\nc co on nc ce ep pt ts s: : w wr ri it ti in ng g c ce en nt te er r a at tt te en nd da an nc ce e,, s st tu ud de en nt t g gr ra ad de es s,, a an nd d r re et te en nt ti io on n..\nI In n a an no ot th he er r s st tu ud dy y,, t th hr re ee e d di if ff fe er re en nt t d da at ta a m mi in ni in ng g t te ec ch hn ni iq qu ue es s w we er re e u us se ed d t to o d de et te er rm mi in ne e\np pr re ed di ic ct to or rs s o of f s st tu ud de en nt t r re et te en nt ti io on n.. Y Yu u,, D Di iG Ga an ng gi i,, J Ja an nn ne es sc ch h-P Pe en nn ne el ll l a an nd d K Ka ap pr ro ol le et t ( (2 20 01 10 0) ) a ap pp pl li ie ed d\nc c cl l la a as s ss s si i if f fi i ic c ca a at t ti i io o on n n t t tr r re e ee e es s s,,, m m mu u ul l lt t ti i iv v va a ar r ri i ia a at t te e e a a ad d da a ap p pt t ti i iv v ve e e r r re e eg g gr r re e es s ss s si i io o on n n s s sp p pl l li i in n ne e es s s ( ( (M M MA A AR R RS S S) ) ),,, a a an n nd d d n n ne e eu u ur r ra a al l l n n ne e et t tw w wo o or r rk k ks s s to\neducational data w wh hi ic ch h r re es su ul lt te ed d i in n f fi in nd di in ng g t tr ra an ns sf fe er rr re ed d h ho ou ur rs s,, r re es si id de en nc cy y,, a an nd d e et th hn ni ic ci it ty y a as s c cr ri it ti ic ca al l\nelements in retention efforts (Y Yu u,, D Di iG Ga an ng gi i,, J Ja an nnasch-Pennell, & Kaprolet, 2010) ). Through this\nr r re e es s se e ea a ar r rc c ch h h,,, t t th h he e ey y y a a al l ls s so o o d d di i is s sc c co o ov v ve e er r re e ed d d t t th h ha a at t t e e ea a as s st t t c c co o oa a as s st t t s s st t tu u ud d de e en n nt t ts s s t t te e en n nd d d t t to o o s s st t ta a ay y y e e en n nr r ro o ol l ll l le e ed d d l l lo o on n ng g ge e er r r t t th h ha a an n n t t th h he e ei i ir r r w w we e es s st t t\ncoast counterparts do.\nA Ac ca ad de em mi ic c p pe er rf fo or rm ma an nc ce e a an nd d s st tu ud de en nt t s su uc cc ce es ss s can be predicted by using d da at ta a m mi in ni in ng g\ntech h hn n ni i iq q qu u ue e es s s... O O On n ne e e r r re e es s se e ea a ar r rc c ch h h t t te e ea a am m m u u us s se e ed d d d d da a at t ta a a m m mi i in n ni i in n ng g g t t to o o c c cl l la a as s ss s si i if f fy y y s s st t tu u ud d de e en n nt t ts s s i i in n nt t to o o t t th h hr r re e ee e e g g gr r ro o ou u up p ps s s a a as s s e e ea a ar r rl l ly y y a a as s s\nthey could in the academic year ( (Vandamme, Meskens, & Superby, 2007).. T Th he e t th hr re ee e g gr ro ou up ps s\nincluded low-r ri is sk k,, m me ed di iu um m r ri is sk k,, a an nd d h hi ig gh h-r ri is sk k s st tu ud de en nt ts s.. T Th he e a au ut th ho or rs s u us se ed d s se ev ve er ra al l d da at ta a m mi in ni in ng g\nt t te e ec c ch h hn n ni i iq q qu u ue e es s s i i in n nc c cl l lu u ud d di i in n ng g g n n ne e eu u ur r ra a al l l n n ne e et t tw w wo o or r rk k ks s s,,, r r ra a an n nd d do o om m m f f fo o or r re e es s st t ts s s,,, a a an n nd d d d d de e ec c ci i is s si i io o on n n t t tr r re e ee e es s s... T T Th h he e e s s st t tu u ud d de e en n nt t t in the high\nr r ri i is s sk k k g g gr r ro o ou u up p p h h ha a ad d d a a a h h hi i ig g gh h h p p pr r ro o ob b ba a ab b bi i il l li i it t ty y y o o of f f f f fa a ai i il l li i in n ng g g o o or r r d d dr r ro o op p pp p pi i in n ng g g o o ou u ut t t o o of f f s s sc c ch h ho o oo o ol l l... T T Th h he e es s se e e t t ty y yp p pe e es s s o o of f f s s st t tu u ud d di i ie e es s s a a ar r re e e\ni im mp po or rt ta an nt t i in n t th ha at t t th he ey y g gi iv ve e f fa ac cu ul lt ty y a an nd d s st ta af ff f a a w wa ay y t to o i id de en nt ti if fy y t th he e a at t-r ri is sk k s st tu ud de en nt ts s i in n a a p pr ro oa ac ct ti iv ve e\nway, because “o on nc ce e a a s st tu ud de en nt t d de ec ci id de es s t to o l le ea av ve e,, i it t i is s h ha ar rd d t to o c co on nv vi in nc ce e t th he em m t to o s st ta ay y” (discussion\nwith D Di ir re ec ct to or r o of f I In ns st ti it tu ut ti io on na al l E Ef ff fe ec ct ti iv ve en ne es ss s at Norwich University).\nIn a related study, r re es se ea ar rc ch he er rs s e ex xa am mi in ne ed d w wh he et th he er r t th he e d de em mo og gr ra ap ph hi ic c b ba ac ck kg gr ro ou un nd d o of f\ns st tu ud de en nt ts s h ha ad d a an ny y i in nf fl lu ue en nc ce e o on n t th he ei ir r p pe er rf fo or rm ma an nc ce e (Yorke et al., 2005). R Re es su ul lt ts s f fr ro om m t th he e s st tu ud dy y\na ap pp pe ea ar re ed d i in nc co on nc cl lu us si iv ve e,, p po ot te en nt ti ia al ll ly y b be ec ca au us se e of the type of analysis they did. I In nt te er re es st ti in ng gl ly y,, t th he e\nf fi ie el ld d o of f e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g i is s c co on nc ce er rn ne ed d w wi it th h a an na al ly yt ti ic cal m me et th ho od ds s,, a an nd d n no ot t n ne ec ce es ss sa ar ri il ly y j ju us st t\ndata mining methods. Y Yo or rk ke e e et t a al l.. (2005) u us se ed d M Mi ic cr ro os so of ft t E Ex xc ce el l f fo or r t th he ei ir r a an na al ly ys si is s a an nd d mining\ndata. The probl l le e em m m w w wi i it t th h h t t th h hi i is s s a a ap p pp p pr r ro o oa a ac c ch h h i i is s s t t th h ha a at t t t t th h he e ey y y d d di i is s sc c cu u us s ss s s m m mi i in n ni i in n ng g g t t th h he e e d d da a at t ta a a w w wi i it t th h ho o ou u ut t t r r re e ea a al l ll l ly y y a a ap p pp p pl l ly y yi i in n ng g g\nd d da a at t ta a a m m mi i in n ni i in n ng g g t t te e ec c ch h hn n ni i iq q qu u ue e es s s... I I It t t i i is s s c c cl l le e ea a ar r r t t th h ha a at t t r r re e es s se e ea a ar r rc c ch h he e er r rs s s s s sh h ho o ou u ul l ld d d e e ex x xe e er r rc c ci i is s se e e m m mo o or r re e e c c ca a au u ut t ti i io o on n n w w wh h he e en n n u u us s sing the\nphrase data mining, especially w wh he en n t th he ey y a ar re e n no ot t r re ef fe er rr ri in ng g t to o d da at ta a m mi in ni in ng g t te ec ch hn ni iq qu ue es s.. The\ndrawback with the research Y Yo or rk ke e e et t a al l.. ( (2 20 00 05 5) ) used these phrases, but never a ap pp pl li ie ed d a an ny y\nc c cl l la a as s ss s si i if f fi i ic c ca a at t ti i io o on n n,,, r r re e eg g gr r re e es s ss s si i io o on n n,,, o o or r r o o ot t th h he e er r r d d da a at t ta a a m m mi i in n ni i in n ng g g t t te e ec c ch h hn n ni i iq q qu u ue e e... T T Th h hi i is s s p p pa a ar r rt t ti i ic c cu u ul l la a ar r r r r re e es s se e ea a ar r rc c ch h h d d de e em m mo o on n ns s st t tr r ra a at t te e es s s\nt th ha at t r re es se ea ar rc ch he er rs s c ca an n s st ti il ll l c co on nd du uc ct t d da at ta a a an na al ly ys se es s b by y u us sing Excel, but r re es se ea ar rc ch he er rs s s sh ho ou ul ld d n no ot t\nm mi is sl le ea ad d t th he e r re ea ad de er r w wh he en n d de es sc cr ri ib bi in ng g t th he ei ir r a ap pp pr ro oa ac ch h.. C Co on nt tr ra ar ry y t to o t th he e Y Yo or rk ke e e et t a al l.. ( (2 20 00 05 5) ) s st tu ud dy y,, a\ndifferent research team n n no o ot t te e ed d d t t th h ha a at t t d d de e em m mo o og g gr r ra a ap p ph h hi i ic c c c c ch h ha a ar r ra a ac c ct t te e er r ri i is s st t ti i ic c cs s s a a ar r re e e n n no o ot t t s s si i ig g gn n ni i if f fi i ic c ca a an n nt t t p p pr r re e ed d di i ic c ct t to o or r rs s s o o of f f\nstudent satisfaction or success (T Th ho om ma as s & & G Ga al la am mb bo os s,, 2 20 00 04 4). T Th he e r re es su ul lt ts s s se ee em m t to o r re ep po or rt t d di if ff fe er re en nt t\nf fi in nd di in ng gs s r re el la at te ed d t to o s st tu ud de en nt t s sa at ti is sf fa ac ct ti io on n o or r t th he e p pr re ed di ic ct ti io on n o of f s st tu ud de en nt t s su uc cc ce es ss s.. O On ne e c ca an n conclude\nt th he er re e a ar re e s si ig gn ni if fi ic ca an nt tl ly y m mo or re e f fa ac ct to or rs s t th ha at t i in nf fl lu uence students’ success t th ha an n w wh ha at t h ha as s b be ee en n s st tu ud di ie ed d\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 6 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nPe er rs so on na al l L Le ea ar rn ni in ng g E En nv vi ir ro on nm me en nt ts s a an nd d R Re ec co om mm me en nd de er r S Sy ys st te em ms s\nPer r rs s so o on n na a al l l l l le e ea a ar r rn n ni i in n ng g g e e en n nv v vi i ir r ro o on n nm m me e en n nt t ts s s ( ( (P P PL L LE E Es s s) ) ) a a an n nd d d p p pe e er r rs s so o on n na a al l l r r re e ec c co o om m mm m me e en n nd d da a at t ti i io o on n n s s sy y ys s st t te e em m ms s s ( ( (P P PR R RS S S) ) )\na a al l ls s so o o d d di i ir r re e ec c ct t tl l ly y y r r re e el l la a at t te e e t t to o o e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a m m mi i in n ni i in n ng g g... P P Pe e er r rs s so o on n na a al l li i iz z ze e ed d d l l le e ea a ar r rn n ni i in n ng g g e e en n nv v vi i ir r ro o on n nm m me e en n nt t ts s s f f fo o oc c cu u us s s o o on n n\np p pr r ro o ov v vi i id d di i in n ng g g t t th h he e e v v va a ar r ri i io o ou u us s s t t to o oo o ol l ls s s,,, s s se e er r rv v vi i ic c ce e es s s,,, a a an n nd d d a a ar r rt t ti i if f fa a ac c ct t ts s s s s so o o t t th h ha a at t t t t th h he e e s s sy y ys s st t te e em m m c c ca a an n n a a ad d da a ap p pt t t t t to o o students’\nlearning needs on the fly (M Mö öd dr ri it ts sc ch he er r,, 2 20 01 10 0). Much of t th he e w wo or rk k d do on ne e r re el la at te ed d t to o r re ec co om mm me en nd de er r\nsystems is quantitative a a an n nd d d i i is s s w w wi i id d de e el l ly y y u u us s se e ed d d i i in n n e e eC C Co o om m mm m me e er r rc c ce e e... F F Fo o or r r e e ex x xa a am m mp p pl l le e e,,, A A Am m ma a az z zo o on n n...c c co o om m m u u us s se e es s s\nr re ec co om mm me en nd de er r s sy ys st te em ms s i in n o or rd de er r t to o c cu us st to om mi iz ze e t th he e b br ro ow ws si in ng g e ex xp pe er ri ie en nc ce e f fo or r e ea ac ch h u us se er r..\nRecommendations display re el la at te ed d p pr ro od du uc ct ts s t th ha at t a a c co on nsumer might purchase. N Ne et tf fl li ix x a al ls so o\ne e em m mp p pl l lo o oy y ys s s r r re e ec c co o om m mm m me e en n nd d de e er r r s s sy y ys s st t te e em m ms s s t t to o o h h he e el l lp p p i i it t ts s s s s su u ub b bs s sc c cr r ri i ib b be e er r rs s s f f fi i in n nd d d t t th h he e e t t ty y yp p pe e es s s o o of f f m m mo o ov v vi i ie e es s s t t th h ha a at t t t t th h he e ey y y w w wi i il l ll l l\nR R Re e ec c co o om m mm m me e en n nd d de e er r r s s sy y ys s st t te e em m ms s s m m mu u us s st t t b b be e e a a ad d da a ap p pt t te e ed d d w w wh h he e en n n t t th h he e ey y y a a ar r re e e u u us s se e ed d d i i in n n e e ed d du u uc c ca a at t ti i io o on n na a al l l c c co o on n nt t te e ex x xt t ts s s\nbecause the recommendations s sh ho ou ul ld d c co oi in nc ci id de e w wi it th h e ed du uc ca at ti io on na al l o ob bj je ec ct ti iv ve es s.. T Th he e r re ea as so on n i is s t th ha at t i it t\ni i is s s n n no o ot t t p p po o os s ss s si i ib b bl l le e e t t to o o a a ap p pp p pl l ly y y e e ex x xi i is s st t ti i in n ng g g r r re e ec c co o om m mm m me e en n nd d de e er r r s s sy y ys s st t te e em m ms s s d d di i ir r re e ec c ct t tl l ly y y t t to o o e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a b b be e ec c ca a au u us s se e e t t th h he e ey y y\nare highly domain dependent (S Sa an nt to os s & & B Bo ot ti ic ca ar ri io o,, 2 20 01 10 0).. T Th he er re e a ar re e t tw wo o s si ig gn ni if fi ic ca an nt t c ch ha al ll le en ng ge es s\nw wi it th h r re es sp pe ec ct t t to o a ap pp pl ly yi in ng g r re ec co om mm me en nd de er r s sy ys st te em ms s i in n a an n e ed du uc ca at ti io on na al l c co on nt te ex xt t.. F Fi ir rs st t,, t th he e s sy ys st te em m m mu us st t\na a at t tt t te e em m mp p pt t t t t to o o u u un n nd d de e er r rs s st t ta a an n nd d d o o or r r d d de e et t te e er r rm m mi i in n ne e e t t th h he e e n n ne e ee e ed d ds s s o o of f f l l le e ea a ar r rn n ne e er r rs s s... S S Se e ec c co o on n nd d d,,, t t th h he e er r re e e s s sh h ho o ou u ul l ld d d b b be e e s s so o om m me e e w w wa a ay y y f f fo o or r r\nf fa ac cu ul lt ty y m me em mb be er rs s t to o c co on nt tr ro ol l r re ec co om mm me en nd da at ti io on ns s f fo or r t th he ei ir r l le ea ar rn ne er rs s (S Sa an nt to os s & & B Bo ot ti ic ca ar ri io o,, 2 20 01 10 0).\nE Ex xi is st ti in ng g r re ec co om mm me en nd de er r s sy ys st te em ms s i in n t th he e e ed du uc ca at ti io on na al l d do om ma ai in n t ty yp pi ic ca al ll ly y d do o n no ot t a ad dd dr re es ss s these\nconcerns, which open up add d di i it t ti i io o on n na a al l l r r re e es s se e ea a ar r rc c ch h h o o op p pp p po o or r rt t tu u un n ni i it t ti i ie e es s s f f fo o or r r t t th h he e e E E ED D DM M M r r re e es s se e ea a ar r rc c ch h h c c co o om m mm m mu u un n ni i it t ty y y...\nH Ho ow w c ca an n r re es se ea ar rc ch he er rs s a an nd d e ed du uc ca at ti io on na al l a ad dm mi in ni is st tr ra at to or rs s u us se e d da at ta a m mi in ni in ng g t to o p pr re ed di ic ct t s st tu ud de en nt t\nperformance? One r re es se ea ar rc ch h t te ea am m examined this issue by applying rec co om mm me en nd de er r s sy ys st te em ms s i in n a an n\ne ef ff fo or rt t t to o i im mp pr ro ov ve e s st tu ud de en nt t p pr re ed di ic ct ti io on n r re es su ul lt ts s (Thai-Nghe, Drumond, Krohn-G Gr ri im mb be er rg gh he e,, & &\nSchmidt-Thieme, 2010). T Th hi is s p pa ar rt ti ic cu ul la ar r r re es se ea ar rc ch h s st tu ud dy y i is s o on ne e o of f t th he e m mo or re e q qu ua an nt ti it ta at ti iv ve el ly y r ri ig go or ro ou us s\narticles, probably more a a ap p pp p pr r ro o op p pr r ri i ia a at t te e e f f fo o or r r c c co o om m mp p pu u ut t te e er r r s s sc c ci i ie e en n nc c ce e e s s st t tu u ud d dy y y,,, b b be e ec c ca a au u us s se e e i i it t t f f fo o oc c cu u us s se e es s s o o on n n u u un n nd d de e er r rl l ly y yi i in n ng g g\na al lg go or ri it th hm ms s a an nd d m me et th ho od ds s t to o i im mp pr ro ov ve e r re ec co om mm me en nd de er r s sy ys st te em ms s.. However, th he e v va al lu ue e o of f t th hi is s s st tu ud dy y i is s\nt t th h ha a at t t i i it t t p p pr r ro o ov v vi i id d de e es s s a a an n n a a an n na a al l ly y ys s si i is s s o o of f f w w wh h hi i ic c ch h h a a an n na a al l ly y yt t ti i ic c ca a al l l m m me e et t th h ho o od d ds s s a a ar r re e e m m mo o or r re e e a a ac c cc c cu u ur r ra a at t te e e w w wh h he e en n n p p pr r re e ed d di i ic c ct t ti i in n ng g g\nR R Re e ec c co o om m mm m me e en n nd d da a at t ti i io o on n ns s s f f fo o or r r f f fu u ur r rt t th h he e er r r l l le e ea a ar r rn n ni i in n ng g g e e ex x xe e er r rc c ci i is s se e es s s w w we e er r re e e m m ma a ad d de e e b b ba a as s se e ed d d o o on n n a a a s s st t tu u ud d de e en n nt t t’ ’ ’s s s w w we e eb b b\nbrowsing behavior a an nd d i im mp pr ro ov ve ed d s st tu ud dent achievement.. A A d da at ta a m mi in ni in ng g m mo od de el l w wa as s e es st ta ab bl li is sh he ed d t th ha at t\na an nn no ot ta at te ed d b br ro ow ws si in ng g e ev ve en nt ts s w wi it th h c co on nt te ex xt tu ua al l f fa ac ct to or rs s,, t to o p pr ro od du uc ce e n ne ew w i in nd di iv vi id du ua al li iz ze ed d content\nrecommendations s sp pe ec ci if fi ic ca al ll ly y f fo or r c co ou ur rs se e m ma an na ag ge em me en nt t s sy ys st te em ms s (F.-H H.. W Wa an ng g,, 2 20 00 08 8). The results\nshowed that data mining can d d de e el l li i iv v ve e er r r h h hi i ig g gh h hl l ly y y p p pe e er r rs s so o on n na a al l li i iz z ze e ed d d c c co o on n nt t te e en n nt t t,,, b b ba a as s se e ed d d o o on n n b b br r ro o ow w ws s si i in n ng g g h h hi i is s st t to o or r ry y y a a an n nd d d\nh h hi i is s st t to o or r ry y y o o of f f s s st t tu u ud d de e en n nt t t a a ac c ch h hi i ie e ev v ve e em m me e en n nt t t... T T Th h hi i is s s a a al l ls s so o o i i im m mp p pr r ro o ov v ve e ed d d s s st t tu u ud d de e en n nt t t l l le e ea a ar r rn n ni i in n ng g g b b be e ec c ca a au u us s se e e s s st t tu u ud d de e en n nt t ts s s c c co o ou u ul l ld d d\nm mo ov ve e t th hr ro ou ug gh h t th he e m ma at te er ri ia al l a at t t th he ei ir r o ow wn n p pa ac ce e.. T Th he e researchers also discovered t th ha at t t th he e c co on nt te ex xt tu ua al l\nbr r ro o ow w ws s si i in n ng g g m m mo o od d de e el l l i i is s s m m mu u uc c ch h h m m mo o or r re e e e e ef f ff f fe e ec c ct t ti i iv v ve e e t t th h ha a an n n u u us s si i in n ng g g a a as s ss s so o oc c ci i ia a at t ti i io o on n n r r ru u ul l le e e m m mi i in n ni i in n ng g g m m mo o od d de e el l ls s s...\nD D Da a at t ta a a m m mi i in n ni i in n ng g g w w wa a as s s u u us s se e ed d d i i in n n o o on n ne e e s s st t tu u ud d dy y y a a as s s a a a w w wa a ay y y t t to o o a a an n na a al l ly y yz z ze e e u u us s se e er r rs s s’ ’ ’ p p pr r re e ef f fe e er r re e en n nc c ce e es s s i i in n n i i in n nt t te e er r ra a ac c ct t ti i iv v ve e e\nm m mu u ul l lt t ti i im m me e ed d di i ia a a l l le e ea a ar r rn n ni i in n ng g g s s sy y ys s st t te e em m ms s s... T T Th h he e e d d da a at t ta a a m m mi i in n ni i in n ng g g c c cl l lu u us s st t te e er r ri i in n ng g g t t te e ec c ch h hn n ni i iq q qu u ue e e w w wa a as s s u u us s se e ed d d t t to o o p p pl l la a ac c ce e e s s st t tu u ud d dents\ni in nt to o f fo ou ur r m ma ai in n g gr ro ou up ps s b ba as se ed d o on n t th he ei ir r p pr re ef fe er re en nc ce es s a an nd d c co om mp pu ut te er r e ex xp pe er ri ie en nc ce e (C Ch hr ry ys so os st to om mo ou u,, C Ch he en n,,\n& Liu, 2009). Although t th he e r re es se ea ar rc ch he er rs s u us se ed d s st tu ud de en nt t p pr re ef fe er re en nc ce es s a as s a a v va ar ri ia ab bl le e a an nd d d de et te er rm mi in ne ed d\nt t th h ha a at t t c c co o om m mp p pu u ut t te e er r r e e ex x xp p pe e er r ri i ie e en n nc c ce e e a a as s s a a a f f fa a ac c ct t to o or r r t t th h ha a at t t i i in n nf f fl l lu u ue e en n nc c ce e es s s p p pr r re e ef f fe e er r re e en n nc c ce e es s s,,, i i it t t i i is s s u u un n nk k kn n no o ow w wn n n w w wh h ha a at t t o o ot t th h he e er r r t t ty y yp p pe e es s s\no of f f fa ac ct to or rs s m mi ig gh ht t i in nf fl lu ue en nc ce e p pr re ef fe er re en nc ce es s i in n a an n o on nl li in ne e l le ea ar rn ni in ng g e en nv vi ir ro on nm me en nt t.. F Fu ut tu ur re e r re es se ea ar rc ch h c co ou ul ld d\ne e ex x xa a am m mi i in n ne e e a a ad d dd d di i it t ti i io o on n na a al l l f f fa a ac c ct t to o or r rs s s o o or r r d d de e em m mo o og g gr r ra a ap p ph h hi i ic c cs s s t t th h ha a at t t c c co o on n nt t tr r ri i ib b bu u ut t te e e t t to o o s s st t tu u ud d de e en n nt t t p p pr r re e ef f fe e er r re e en n nc c ce e es s s,,, s s su u uc c ch h h a a as s s a a ag g ge e e,,,\ngender, or ethnicity.\nD D Da a at t ta a a m m mi i in n ni i in n ng g g w w wa a as s s u u us s se e ed d d i i in n n a a an n no o ot t th h he e er r r s s st t tu u ud d dy y y t t to o o p p pr r ro o ov v vi i id d de e e l l le e ea a ar r rn n ne e er r rs s s w w wi i it t th h h m m ma a an n ny y y r r re e ec c co o om m mm m me e en n nd d da a at t ti i io o ons\nt t to o o h h he e el l lp p p t t th h he e em m m l l le e ea a ar r rn n n m m mo o or r re e e e e ef f ff f fe e ec c ct t ti i iv v ve e el l ly y y a a an n nd d d e e ef f ff f fi i ic c ci i ie e en n nt t tl l ly y y... A A A m m me e et t th h ho o od d do o ol l lo o og g gy y y c c ca a al l ll l le e ed d d f f fr r re e eq q qu u ue e en n nt t t i i it t te e em m ms s se e et t t\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 7 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nmining was used to m m mi i in n ne e e l l le e ea a ar r rn n ne e er r r b b be e eh h ha a av v vi i io o or r r p p pa a at t tt t te e er r rn n ns s s i i in n n a a an n n o o on n nl l li i in n ne e e c c co o ou u ur r rs s se e e a a an n nd d d s s su u ub b bs s se e eq q qu u ue e en n nt t tl l ly y y,,, provide\nl le ea ar rn ne er rs s w wi it th h d di if ff fe er re en nt t l le ev ve el ls s o of f r re ec co om mm me en nd da at ti io on ns s r ra at th he er r t th ha an n s si in ng gl le e o on ne es s t th ha at t a ar re e p pr ro od du uc ce ed d f fr ro om m\nother recommender systems (H Hu ua an ng g,, C Ch he en n,, & & C Ch he en ng g,, 2 20 00 07 7).. T Th hi is s s sy ys st te em m a as ss si is st te ed d l le ea ar rn ne er rs s b by y\np pr ro ov vi id di in ng g t th he em m w wi it th h h hi ig gh hl ly y i in nd di iv vi id du ua al li iz ze ed d r re ec co om mm me en nd da at ti io on ns s f fo or r i im mp pr ro ov ve ed d l le ea ar rn ni in ng g e ef ff fi ic ci ie en nc cy y..\nA A n ne ew we er r s st tr re ea am m o of f r re es se ea ar rc ch h f fo oc cu us se es s o on n m mo ob bi il le e l le ea ar rn ni in ng g e en nv vi ir ro on nm me en nt ts s.. A A s st tu ud dy y b by y Su,\nT T Ts s se e en n ng g g,,, L L Li i in n n,,, a a an n nd d d C C Ch h he e en n n ( ( (2 2 20 0 01 1 11 1 1) ) ) a a ap p pp p pl l li i ie e ed d d d d da a at t ta a a m m mi i in n ni i in n ng g g t t to o o h h he e el l lp p p p p pr r ro o ov v vi i id d de e e f f fa a as s st t t,,, d d dy y yn n na a am m mi i ic c c,,, p p pe e er r rs s so o on n na a al l li i iz z ze e ed d d\nl le ea ar rn ni in ng g c co on nt te en nt t t to o m mo ob bi il le e u us se er rs s.. Mo ob bi il le e d de ev vi ic ce es s h ha av ve e v ve er ry y d di if ff fe er re en nt t r re eq qu ui ir re em me en nt ts s f fo or r m ma an na ag gi in ng g\nc co on nt te en nt t t th ha an n s st ta an nd da ar rd d P PC Cs s a an nd d w we eb b b br ro ow ws se er rs s (Su, Tseng, Lin, & Chen, 2011).. T Th he ey y u us se e d da at ta a s su uc ch h\nas network conditions, h h ha a ar r rd d dw w wa a ar r re e e c c ca a ap p pa a ab b bi i il l li i it t ti i ie e es s s,,, a a an n nd d d t t th h he e e u u us s se e er r r’ ’ ’s s s p p pr r re e ef f fe e er r re e en n nc c ce e es s s f f fr r ro o om m m t t th h he e ei i ir r r d d de e ev v vi i ic c ce e e... W W Wh h hi i il l le e e\nt t th h hi i is s s p p pa a ar r rt t ti i ic c cu u ul l la a ar r r s s st t tu u ud d dy y y i i is s s e e ex x xt t tr r re e em m me e el l ly y y t t te e ec c ch h hn n ni i ic c ca a al l l,,, i i it t t d d de e em m mo o on n ns s st t tr r ra a at t te e es s s h h ho o ow w w m m mo o ob b bi i il l le e e l l le e ea a ar r rn n ni i in n ng g g e e en n nv v vi i ir r ro o on n nm m me e en n nt t ts s s\ncan benefit from data mining.\nEDM A AN ND D C CO OU UR RS SE E M MA AN NA AG GE EM ME EN NT T S SY YS ST TE EM MS S\nA large number of re es se ea ar rc ch he er rs s w wi it th hi in n E ED DM M f fo oc cu us s d di ir re ec ct tl ly y o on n c co ou ur rs se e m ma an na ag ge em me en nt t s sy ys st te em ms s\na a an n nd d d h h ho o ow w w t t th h he e ey y y c c ca a an n n b b be e e i i im m mp p pr r ro o ov v ve e ed d d t t to o o s s su u up p pp p po o or r rt t t s s st t tu u ud d de e en n nt t t l l le e ea a ar r rn n ni i in n ng g g o o ou u ut t tc c co o om m me e es s s a a an n nd d d s s st t tu u ud d de e en n nt t t s s su u uc c cc c ce e es s ss s s... O O On n ne e e\nr re es se ea ar rc ch h t te ea am m d de ev ve el lo op pe ed d a a s si im mp pl li if fi ie ed d d da at ta a m mi in ni in ng g t to oo ol lk ki it t t th ha at t o op pe er ra at te es s w wi it th hi in n t th he e c co ou ur rs se e\nmanagement s sy ys st te em m a an nd d a al ll lo ow ws s n no on n-e ex xp pe er rt t u us se er rs s t to o g ge et t d da at ta a m mi in ni in ng g i in nf fo or rm ma at ti io on n f fo or r t th he ei ir r c co ou ur rs se es s\n(G Ga ar rc cí ía a,, R Ro om me er ro o,, V Ve en nt tu ur ra a,, & & d de e C Ca as st tr ro o,, 2 20 01 11 1). In addition, a t to oo ol lk ki it t a al ll lo ow ws s t te ea ac ch he er rs s t to o\nc co ol ll la ab bo or ra at te e w wi it th h e ea ac ch h o ot th he er r a an nd d s sh ha ar re e r re es su ul lt ts s.. T Th hi is s r re es se ea ar rc ch h i is s i im mp po or rt ta an nt t b be ec ca au us se e m mo os st t d da at ta a\nm m mi i in n ni i in n ng g g t t to o oo o ol l ls s s a a ar r re e e c c co o om m mp p pl l li i ic c ca a at t te e ed d d a a an n nd d d r r re e eq q qu u ui i ir r re e e d d de e ee e ep p p e e ex x xp p pe e er r rt t ti i is s se e e i i in n n d d da a at t ta a a m m mi i in n ni i in n ng g g t t to o oo o ol l ls s s,,, m m me e et t th h ho o od d ds s s a a an n nd d d\np pr ro oc ce es ss se es s,, s st ta at ti is st ti ic cs s,, a an nd d m ma ac ch hi in ne e l le ea ar rn ni in ng g a al lg go or ri it th hm ms s.. T Th hi is s s st tu ud dy y f fo ol ll lo ow ws s a a t ty yp pi ic ca al l d da at ta a m mi in ni in ng g\nprocess, thus it is quanti it ta at ti iv ve e.. T Th he e data mining process usually follows a pre-p pr ro oc ce es ss si in ng g p ph ha as se e,,\nt th he en n a an n a ap pp pl li ic ca at ti io on n o of f s sp pe ec ci if fi ic c d da at ta a m mi in ni in ng g t te ec ch hn ni iq qu ue es s,, a an nd d t th he en n a a p po os st t-p pr ro oc ce es ss si in ng g p ph ha as se e.. The\nr re es se ea ar rc ch h a an nd d a ap pp pl li ic ca at ti io on n c co on nt tr ri ib bu ut ti io on ns s w wi il ll l a al ll lo ow w n no on n-t te ec ch hn ni ic ca al l f fa ac cu ul lt ty y t to o e en ng ga ag ge e i in n e ed du uc cational\nd da at ta a m mi in ni in ng g a ac ct ti iv vi it ti ie es s.. I It t i is s c cl le ea ar r t th ha at t a ad dd di it ti io on na al l is needed in this area to m ma ak ke e e ed du uc ca at ti io on na al l d da at ta a\nm mi in ni in ng g t to oo ol ls s m mo or re e a ac cc ce es ss si ib bl le e t to o n no on n-technical users.\nC C Co o ou u ur r rs s se e e m m ma a an n na a ag g ge e em m me e en n nt t t s s sy y ys s st t te e em m ms s s s s su u uc c ch h h a a as s s o o op p pe e en n n s s so o ou u ur r rc c ce e e M M Mo o oo o od d dl l le e e c c ca a an n n b b be e e m m mi i in n ne e ed d d f f fo o or r r u u us s sa a ag g ge e e d d da a at t ta a a t t to o o\nfind intere es st ti in ng g p pa at tt te er rn ns s a an nd d t tr re en nd ds s i in n s st tu ud de en nt t o on nl li in ne e b be eh ha av vi io or r.. A s sy ys st te em ma at ti ic c m me et th ho od d f fo or r a ap pp pl ly yi in ng g\nd da at ta a m mi in ni in ng g t te ec ch hn ni iq qu ue es s t to o M Mo oo od dl le e u us sa ag ge e d da at ta a was established (C Cr ri is st tó ób ba al l R Ro om me er ro o,, V Ve en nt tu ur ra a,, & &\nGarcía, 2008). The benefit to m m mi i in n ni i in n ng g g u u us s sa a ag g ge e e d d da a at t ta a a i i is s s t t th h ha a at t t i i it t t c c co o on n nt t ta a ai i in n ns s s d d da a at t ta a a a a ab b bo o ou u ut t t e e ev v ve e er r ry y y u u us s se e er r r a a ac c ct t ti i iv v vi i it t ty y y,,,\ns su uc ch h a as s t te es st ti in ng g,, q qu ui iz zz ze es s,, r re ea ad di in ng g,, a an nd d d di is sc cu us ss si io on n p po os st ts s.. R Ro om me er ro o e et t a al l.. ( (2 20 00 08 8) ) d di is sc cu us ss s t th he e\nimportance of pre-p p pr r ro o oc c ce e es s ss s si i in n ng g g t t th h he e e d d da a at t ta a a a a an n nd d d t t th h he e en n n d d di i is s sc c cu u us s ss s s s s sp p pe e ec c ci i if f fi i ic c cs s s o o on n n h h ho o ow w w t t to o o a a ap p pp p pl l ly y y d d da a at t ta a a m m mi i in n ni i in n ng g g\ntechniques to Moodle data. T Th he ei ir r r re es se ea ar rc ch h r re es su ul lt ts s d de em mo on ns st tr ra at te ed d h ho ow w s st tr ra ai ig gh ht tf fo or rw wa ar rd d i it t i is s t to o m mi in ne e\nd d da a at t ta a a,,, e e ev v ve e en n n i i if f f a a a r r re e ea a ad d de e er r r d d do o oe e es s s n n no o ot t t h h ha a av v ve e e m m mu u uc c ch h h e e ex x xp p pe e er r ri i ie e en n nc c ce e e i i in n n t t th h hi i is s s a a ar r re e ea a a... T T Th h he e e a a au u ut t th h ho o or r rs s s a a al l ls s so o o u u us s se e e b b bo o ot t th h h K K Ke e ee e el l l\nand Weka a a as s s t t th h he e ei i ir r r d d da a at t ta a a m m mi i in n ni i in n ng g g s s so o of f ft t tw w wa a ar r re e e p p pa a ac c ck k ka a ag g ge e es s s... T T Th h he e es s se e e s s so o of f ft t tw w wa a ar r re e e p p pr r ro o og g gr r ra a am m ms s s a a ar r re e e o o op p pe e en n n s s so o ou u ur r rc c ce e e a a an n nd d d\na ar re e b bu ui il lt t o on n t th he e J Ja av va a l la an ng gu ua ag ge e,, s so o t th he ey y a ar re e e ex xt te en nd da ab bl le e a as s w we el ll l..\nD D Da a at t ta a a m m mi i in n ni i in n ng g g c c ca a an n n b b be e e u u us s se e ed d d i i in n n s s su u uc c ch h h a a a w w wa a ay y y a a as s s t t to o o c c cu u us s st t to o om m mi i iz z ze e e l l le e ea a ar r rn n ni i in n ng g g a a ac c ct t ti i iv v vi i it t ti i ie e es s s f f fo o or each\nindividual student. Data mining w wa as s u us se ed d t to o a ad da ap pt t l le ea ar rn ni in ng g e ex xe er rc ci is se es s b ba as se ed d o on n s st tu ud de en nt ts s’ ’ p pr ro og gr re es ss s\nt th hr ro ou ug gh h a a c co ou ur rs se e o on n E En ng gl li is sh h l la an ng gu ua ag ge e i in ns st tr ru uc ct ti io on n (Y.-h. Wang & Liao, 2011).. I In ns st te ea ad d o of f h ha av vi in ng g\ns s st t ta a at t ti i ic c c c c co o ou u ur r rs s se e e c c co o on n nt t te e en n nt t t,,, t t th h he e e c c co o ou u ur r rs s se e e a a ad d da a ap p pt t ts s s t t to o o s s st t tu u ud d de e en n nt t t l l le e ea a ar r rn n ni i in n ng g g,,, t t ta a ak k ki i in n ng g g h h hi i im m m o o or r r h h he e er r r t t th h hr r ro o ou u ug g gh h h t t th h he e e c c co o ou u ur r rs s se e e\nat his or her own pace.. T Th hi is s w wa as s a an n e ef ff fo or rt t t to o c cr re ea at te e s si ig gn ni if fi ic ca an nt t a an nd d o op pt ti im ma al l l le ea ar rn ni in ng g e ex xp pe er ri ie en nc ce es s\nf f fo o or r r e e ea a ac c ch h h s s st t tu u ud d de e en n nt t t,,, a a an n nd d d w w wa a as s s a a a s s su u uc c cc c ce e es s ss s s... T T Th h hi i is s s r r re e es s se e ea a ar r rc c ch h h c c co o ou u ul l ld d d b b be e e a a ap p pp p pl l li i ie e ed d d t t to o o o o ot t th h he e er r r t t ty y yp p pe e es s s o o of f f c c co o ou u ur r rs s se e es s s\nw w wh h he e er r re e e s s st t tu u ud d de e en n nt t ts s s b b be e eg g gi i in n n a a a c c co o ou u ur r rs s se e e w w wi i it t th h h v v va a ar r ry y yi i in n ng g g l l le e ev v ve e el l ls s s o o of f f c c co o om m mp p pe e et t te e en n nc c cy y y,,, e e e...g g g...,,, a a a c c co o om m mp p pu u ut t te e er r r p p pr r ro o og g gr r ra a am m mm m mi i in n ng g g\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 8 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nData mining was used t t to o o a a as s ss s se e es s ss s s c c co o om m mp p pl l le e ex x x s s st t tu u ud d de e en n nt t t b b be e eh h ha a av v vi i io o or r rs s s w w wi i it t th h h r r re e es s sp p pe e ec c ct t t t t to o o a a a t t th h hr r re e ee e e-week\np p pr r ro o og g gr r ra a am m mm m mi i in n ng g g a a as s ss s si i ig g gn n nm m me e en n nt t t... B B Bl l li i ik k ks s st t te e ei i in n n ( ( (2 2 20 0 01 1 11 1 1) ) ) f f fo o ou u un n nd d d r r re e es s su u ul l lt t ts s s t t th h ha a at t t s s sh h ho o ow w we e ed d d d d di i if f ff f fe e er r re e en n nt t t t t ty y yp p pe e es s s o o of f f student\np p pr r ro o og g gr r ra a am m mm m mi i in n ng g g b b be e eh h ha a av v vi i io o or r rs s s i i in n n a a an n n o o on n nl l li i in n ne e e c c co o ou u ur r rs s se e e... T T Th h he e es s se e e l l lo o og g g f f fi i il l le e es s s c c co o on n nt t ta a ai i in n ne e ed d d d d di i if f ff f fe e er r re e en n nt t t t t types of events as\ne ea ac ch h s st tu ud de en nt t c co om mp pl le et te ed d t th he em m.. T Th he e e ev ve en nt ts s i in nc cl lu ud de ed d c co od di in ng g a an nd d n no on n-c co od di in ng g a ac ct ti iv vi it ti ie es s i in n t th he e o on nl li in ne e\ncourse. This quantitative data m m mi i in n ni i in n ng g g r r re e es s se e ea a ar r rc c ch h h h h he e el l lp p pe e ed d d d d di i is s sc c co o ov v ve e er r r d d di i if f ff f fe e er r re e en n nt t t p p pr r ro o og g gr r ra a am m mm m mi i in n ng g g s s st t tr r ra a at t te e eg g gi i ie e es s s\nu us se ed d b by y s st tu ud de en nt ts s,, a an nd d d de ev ve el lo op pe ed d t th hr re ee e p pr ro og gr ra am mm ming behavior profiles: copy-a an nd d-pasters, mixed-\nmode, and self-sufficients (B Bl li ik ks st te ei in n,, 2 20 01 11 1).\nI I In n n m m ma a an n ny y y o o on n nl l li i in n ne e e c c co o ou u ur r rs s se e es s s,,, d d di i is s sc c cu u us s ss s si i io o on n n b b bo o oa a ar r rd d d p p po o os s st t ts s s a a ar r re e e a a an n n i i im m mp p po o or r rt t ta a an n nt t t p p pa a ar r rt t t o o of f f t t th h he e e l l le e ea a ar r rn n ni i in n ng g g\ne e ex x xp p pe e er r ri i ie e en n nc c ce e e... O O On n ne e e r r re e es s se e ea a ar r rc c ch h h t t te e ea a am m m u u us s se e ed d d d d da a at t ta a a m m mi i in n ni i in n ng g g a a as s s a a a s s st t tr r ra a at t te e eg g gy y y f f fo o or r r a a as s ss s se e es s ss s si i in n ng g g a a as s sy y yn n nc c ch h hr r ro o on n no o ou u us s s\nd d di i is s sc c cu u us s ss s si i io o on n n f f fo o or r ru u um m ms s s b b be e ec c ca a au u us s se e e i i it t t w w wa a as s s c c ch h ha a al l ll l le e en n ng g gi i in n ng g g t t to o o m m ma a an n nu u ua a al l ll l ly y y a a as s ss s se e es s ss s s t t th h he e e q q qu u ua a al l li i it t ty y y o o of f f t t th h he e e postings by\neach student (D Dr ri in ng gu us s & & E El ll li is s,, 2 20 00 05 5).. T Th he ei ir r r re es se ea ar rc ch h a at tt te em mp pt ts s t to o a an ns sw we er r t th he e q qu ue es st ti io on n o of f w wh ha at t\nk k ki i in n nd d d o o of f f i i in n nf f fo o or r rm m ma a at t ti i io o on n n i i is s s e e em m mb b be e ed d dd d de e ed d d i i in n n o o on n nl l li i in n ne e e d d di i is s sc c cu u us s ss s si i io o on n n g g gr r ro o ou u up p ps s s... T T Th h he e e d d da a at t ta a a m m mi i in n ni i in n ng g g r r re e es s su u ul l lt t ts s s were used\nt t to o o a a as s ss s se e es s ss s s s s st t tu u ud d de e en n nt t t p p pr r ro o og g gr r re e es s ss s s i i in n n a a an n n o o on n nl l li i in n ne e e c c co o ou u ur r rs s se e e... O O On n ne e e d d dr r ra a aw w wb b ba a ac c ck k k w w wi i it t th h h t t th h hi i is s s a a ap p pp p pr r ro o oa a ac c ch h h i i is s s t t th h ha a at t t n n no o on n n-\nt t te e ec c ch h hn n ni i ic c ca a al l l f f fa a ac c cu u ul l lt t ty y y w w wo o ou u ul l ld d d n n no o ot t t k k kn n no o ow w w h h ho o ow w w t t to o o a a ap p pp p pl l ly y y d d da a at t ta a a m m mi i in n ni i in n ng g g t t to o o g g ge e et t t r r re e es s su u ul l lt t ts s s f f fo o or r r t t th h he e ei i ir r r s s st t tu u ud d de e en n nt t ts s s,,, t t th h hu u us s s\nt th he er re e i is s a a n ne ee ed d t to o c cr re ea at te e t to oo ol ls s t th ha at t a ar re e a ac cc ce es ss si ib bl le e t to o non-t te ec ch hn ni ic ca al l f fa ac cu ul lt ty y m me em mb be er rs s..\nL L Li i ik k ke e e B B Bl l li i ik k ks s st t te e ei i in n n ( ( (2 2 20 0 01 1 11 1 1) ) ),,, D D Dr r ri i in n ng g gu u us s s a a an n nd d d E E El l ll l li i is s s ( ( (2 2 20 0 00 0 05 5 5) ) ) a a an n na a al l ly y yz z ze e e s s st t tu u ud d de e en n nt t t b b be e eh h ha a av v vi i io o or r r b b by y y a a ap p pp p pl l ly y yi i in n ng g g\nd d da a at t ta a a m m mi i in n ni i in n ng g g t t te e ec c ch h hn n ni i iq q qu u ue e es s s... W W Wh h hi i il l le e e t t th h he e e f f fo o or r rm m me e er r r e e ex x xa a am m mi i in n ne e es s s p p pr r ro o og g gr r ra a am m mm m mi i in n ng g g a a ac c ct t ti i iv v vi i it t ty y y b b be e eh h ha a av v vi i io o or r r,,, t t th h he e e l l la a at t tt t te e er r r\ne ex xa am mi in ne es s d di is sc cu us ss si io on n b bo oa ar rd d b be eh ha av vi io or r.. The analysis is different based upon t th he e t ty yp pe e o of f t ta as sk k o or r\nactivity. F F Fo o or r r e e ex x xa a am m mp p pl l le e e,,, t t th h he e e D D DM M M a a an n na a al l ly y ys s si i is s s p p pr r ro o og g gr r ra a am m mm m mi i in n ng g g t t ta a as s sk k ks s s i i in n n a a a c c co o ou u ur r rs s se e e m m ma a an n na a ag g ge e em m me e en n nt t t s s sy y ys s st t te e em m m i i is s s\ng go oi in ng g t to o b be e d di if ff fe er re en nt t t th ha an n t th he e D DM M a an na al ly ys si is s f fo or r d di is sc cu us ss si io on n b bo oa ar rd ds s.. E Ea ac ch h d da at ta a m mi in ni in ng g t ta as sk k i is s\nusually very specific and is u us se ed d w wi it th h a a s sp pe ec ci if fi ic c d da at ta a s se et t.. However, m ma ay y b be e m mo or re e important to\nf fi in nd d w wa ay ys s o of f a ap pp pl ly yi in ng g d da at ta a m mi in ni in ng g t to o e ex xa am mi in ne e s st tu ud de en nt ts s’ ’ b be eh ha av vi io or r i in n a a b br ro oa ad de er r s se en ns se e,, r ra at th he er r t th ha an n\na an na al ly yz zi in ng g a a s si in ng gl le e a as sp pe ec ct t o of f t th he ei ir r b be eh ha av vi io or r w wi it th hi in n t th he e C CM MS S..\nIn an o o on n nl l li i in n ne e e e e ed d du u uc c ca a at t ti i io o on n na a al l l e e en n nv v vi i ir r ro o on n nm m me e en n nt t t,,, l l le e ea a ar r rn n ne e er r r e e en n ng g ga a ag g ge e em m me e en n nt t t i i is s s a a an n n i i im m mp p po o or r rt t ta a an n nt t t a a as s sp p pe e ec c ct t t o o of f f\nstudent success. S S St t tu u ud d de e en n nt t ts s s’ ’ ’ e e en n ng g ga a ag g ge e em m me e en n nt t t w w wi i it t th h h t t th h he e e c c co o ou u ur r rs s se e e c c co o on n nt t te e en n nt t t c c ca a an n n b b be e e a a an n na a al l ly y yz z ze e ed d d u u us s si i in n ng g g d d da a at t ta a a\nm mi in ni in ng g t te ec ch hn ni iq qu ue es s t to o d de et te er rm mi in ne e i if f t th he er re e a ar re e d di is se en ng ga ag ge ed d l le ea ar rn ne er rs s (C Co oc ce ea a & & W We ei ib be el lz za ah hl l,, 2 20 00 09 9).\nT T Th h he e er r re e e w w we e er r re e e s s se e ev v ve e er r ra a al l l f f fa a ac c ct t to o or r rs s s t t th h ha a at t t w w we e er r re e e r r re e ev v ve e ea a al l le e ed d d t t th h ha a at t t c c co o on n nt t tr r ri i ib b bu u ut t te e e t t to o o p p pr r re e ed d di i ic c ct t ti i in n ng g g s s st t tu u ud d de e en n nt t t\nd d di i is s se e en n ng g ga a ag g ge e em m me e en n nt t t,,, w w wh h hi i ic c ch h h i i in n nc c cl l lu u ud d de e ed d d t t th h he e e s s sp p pe e ee e ed d d a a at t t w w wh h hi i ic c ch h h s s st t tu u ud d de e en n nt t ts s s r r re e ea a ad d d t t th h hr r ro o ou u ug g gh h h t t th h he e e p p pa a ag g ge e es s s, and the\nl le en ng gt th h o of f t ti im me e s sp pe en nt t o on n p pa ag ge es s.. A Ad dd di it ti io on na al ll ly y,, t th he ei ir r s st tu ud dy y a al ls so o d de et te er rm mi in ne ed d t th ha at t w wh he en n s st tu ud de en nt ts s f fi ir rs st t\nl l lo o og g go o on n n t t to o o a a an n n o o on n nl l li i in n ne e e c c co o ou u ur r rs s se e e,,, t t th h he e ei i ir r r b b be e eh h ha a av v vi i io o or r r i i is s s q q qu u ui i it t te e e e e er r rr r ra a at t ti i ic c c,,, p p pr r ro o ob b ba a ab b bl l ly y y b b be e ec c ca a au u us s se e e t t th h he e e s s st t tu u ud d de e en n nt t t i i is s s l l le e ea a ar r rn n ni i in n ng g g\nh ho ow w t to o u us se e t th he e c co ou ur rs se e e en nv vi ir ro on nm me en nt t i it ts se el lf f.. T Th he er re ef fo or re e,, a an n a an na al ly ys si is s s sh ho ou ul ld d t ta ak ke e i in nt to o a ac cc co ou un nt t this\nt ty yp pe e o of f b be eh ha av vi io or r w wh he en n p pr ro od du uc ci in ng g d da at ta a m mi in ni in ng g m mo od de el ls s..\nO O On n ne e e p p po o ot t te e en n nt t ti i ia a al l l d d dr r ra a aw w wb b ba a ac c ck k k t t to o o t t th h he e e u u us s se e e o o of f f o o on n nl l li i in n ne e e c c co o ou u ur r rs s se e e m m ma a an n na a ag g ge e em m me e en n nt t t s s sy y ys s st t te e em m ms s s i i is s s t t th h ha a at t t s s st t tu u ud d de e en n nt t ts s s\ncan manipulate the system and av v vo o oi i id d d l l le e ea a ar r rn n ni i in n ng g g... G G Ga a am m mi i in n ng g g i i is s s t t th h he e e i i id d de e ea a a t t th h ha a at t t s s st t tu u ud d de e en n nt t ts s s a a at t tt t te e em m mp p pt t t t t to o o\ncircumvent properties o o of f f t t th h he e e s s sy y ys s st t te e em m m i i in n n o o or r rd d de e er r r t t to o o m m ma a ak k ke e e p p pr r ro o og g gr r re e es s ss s s,,, w w wh h hi i il l le e e a a av v vo o oi i id d di i in n ng g g l l le e ea a ar r rn n ni i in n ng g g\n(M Mu ul ld dn ne er r,, B Bu ur rl le es so on n,, V Va an n d de e S Sa an nd de e,, & & V Va an nl le eh hn n,, 2 20 01 11 1). Some researchers are i in nv ve es st ti ig ga at ti in ng g w wh ha at t\nc c ca a an n n b b be e e d d do o on n ne e e t t to o o m m mi i in n ni i im m mi i iz z ze e e g g ga a am m mi i in n ng g g,,, a a an n nd d d t t to o o m m ma a ak k ke e e s s su u ur r re e e t t th h ha a at t t s s st t tu u ud d de e en n nt t ts s s c c co o on n nt t ti i in n nu u ue e e l l le e ea a ar r rn n ni i in n ng g g... M M Mu u ul l ld d dn n ne e er r r e e et t t\nal. ( ( (2 2 20 0 01 1 11 1 1) ) ) u u us s se e ed d d d d da a at t ta a a m m mi i in n ni i in n ng g g t t te e ec c ch h hn n ni i iq q qu u ue e es s s i i in n nc c cl l lu u ud d di i in n ng g g B B Ba a ay y ye e es s si i ia a an n n m m me e et t th h ho o od d ds s s ( ( (N N Na a aï ï ïv v ve e e B B Ba a ay y ye e es s s) ) ) a a an n nd d d f f fo o ou u un n nd d d\nthat students, r r ra a at t th h he e er r r t t th h ha a an n n t t th h he e e a a as s ss s si i ig g gn n nm m me e en n nt t t o o or r r p p pr r ro o ob b bl l le e em m m,,, w w wa a as s s a a a b b be e et t tt t te e er r r p p pr r re e ed d di i ic c ct t to o or r r o o of f f g g ga a am m mi i in n ng g g... T T Th h he e ey y y a a al l ls s so o o\np p pr r ro o ov v vi i id d de e ed d d n n nu u um m me e er r ro o ou u us s s r r re e ec c co o om m mm m me e en n nd d da a at t ti i io o on n ns s s f f fo o or r r d d di i is s sc c co o ou u ur r ra a ag g gi i in n ng g g g g ga a am m mi i in n ng g g... T T Th h he e es s se e e i i in n nc c cl l lu u ud d de e e s s su u up p pp p pl l ly y yi i in n ng g g e e ex x xt t tr r ra a a o o or r r\ns su up pp pl le em me en nt ta al l e ex xe er rc ci is se es s,, o or r t th he e u us se e o of f a an n i in nt te el ll li ig ge en nt t a ag ge en nt t t th ha at t d di is sp pl la ay ys s d di is sa ap pp pr ro ov va al l i if f g ga am mi in ng g i is s\ndetected within the system.\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 9 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nC CO ON NC CL LU US SI IO ON N A AN ND D F FU UT TU UR RE E W WO OR RK K\nE E Ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a m m mi i in n ni i in n ng g g ( ( (E E ED D DM M M) ) ) i i is s s a a an n n a a ar r re e ea a a f f fu u ul l ll l l o o of f f e e ex x xc c ci i it t ti i in n ng g g o o op p pp p po o or r rt t tu u un n ni i it t ti i ie e es s s f f fo o or r r r r re e es s se e ea a ar r rc c ch h he e er r rs s s\na an nd d p pr ra ac ct ti it ti io on ne er rs s.. T Th hi is s f fi ie el ld d a as ss si is st ts s h hi ig gh he er r e ed du uc ca at ti io on na al l i in ns st ti it tu ut ti io on ns s w wi it th h e ef ff fi ic ci ie en nt t a an nd d e ef ff fe ec ct ti iv ve e\nw w wa a ay y ys s s t t to o o i i im m mp p pr r ro o ov v ve e e i i in n ns s st t ti i it t tu u ut t ti i io o on n na a al l l e e ef f ff f fe e ec c ct t ti i iv v ve e en n ne e es s ss s s a a an n nd d d s s st t tu u ud d de e en n nt t t l l le e ea a ar r rn n ni i in n ng g g... D D Da a at t ta a a m m mi i in n ni i in n ng g g i i is s s a a a s s si i ig g gn n ni i if f fi i ic c ca a an n nt t t t t to o oo o ol l l\nf f fo o or r r h h he e el l lp p pi i in n ng g g o o or r rg g ga a an n ni i iz z za a at t ti i io o on n ns s s e e en n nh h ha a an n nc c ce e e d d de e ec c ci i is s si i io o on n n m m ma a ak k ki i in n ng g g a a an n nd d d a a an n na a al l ly y yz z zi i in n ng g g n n ne e ew w w p p pa a at t tt t te e er r rn n ns s s a a an n nd d d r r re e el l la a at t ti i io o on n ns s sh h hi i ip p ps s s\namong a large amount of data. A A broad sense of t th he e t ty yp pe es s o of f r re es se ea ar rc ch h c cu ur rr re en nt tl ly y b be ei in ng g c co on nd du uc ct te ed d\nin EDM was presented,,, f f fr r ro o om m m a a ap p pp p pl l ly y yi i in n ng g g d d da a at t ta a a m m mi i in n ni i in n ng g g f f fo o or r r u u un n nd d de e er r rs s st t ta a an n nd d di i in n ng g g s s st t tu u ud d de e en n nt t t r r re e et t te e en n nt t ti i io o on n n a a an n nd d d\nattrition t to o f fi in nd di in ng g n ne ew w w wa ay ys s o of f m ma ak ki in ng g p pe er rs so on na al li iz ze ed d l le ea ar rn ni in ng g r re ec co om mm me en nd da at ti io on ns s t to o e ea ac ch h\ni i in n nd d di i iv v vi i id d du u ua a al l l s s st t tu u ud d de e en n nt t t... M M Ma a an n ny y y o o op p pp p po o or r rt t tu u un n ni i it t ti i ie e es s s e e ex x xi i is s st t t t t to o o s s st t tu u ud d dy y y E E ED D DM M M f f fr r ro o om m m a a an n n o o or r rg g ga a an n ni i iz z za a at t ti i io o on n na a al l l u u un n ni i it t t o o of f f\nanalysis to individual course-l l le e ev v ve e el l ls s s o o of f f a a an n na a al l ly y ys s si i is s s... S S So o om m me e e w w wo o or r rk k k i i is s s s s st t tr r ra a at t te e eg g gi i ic c c i i in n n n n na a at t tu u ur r re e e a a an n nd d d s s so o om m me e e o o of f f t t th h he e e\nresearch is extremely t te ec ch hn ni ic ca al l.. O Ov ve er ra al ll l,, EDM d dr ra aw ws s u up po on n s se ev ve er ra al l r re ef fe er re en nc ce e d di is sc ci ip pl li in ne es s a an nd d\nc c co o on n nt t ti i in n nu u ue e es s s t t to o o g g gr r ro o ow w w w w wi i it t th h h t t th h he e e i i in n nt t tr r ro o od d du u uc c ct t ti i io o on n n o o of f f t t th h he e e J J Jo o ou u ur r rn n na a al l l o o of f f E E Ed d du u uc c ca a at t ti i io o on n na a al l l D D Da a at t ta a a M M Mi i in n ni i in n ng g g a a an n nd d d i i it t ts s s r r re e el l la a at t te e ed d d\na a an n nn n nu u ua a al l l c c co o on n nf f fe e er r re e en n nc c ce e e... T T Th h he e es s se e e w w we e er r re e e e e es s st t ta a ab b bl l li i is s sh h he e ed d d o o on n nl l ly y y i i in n n 2 2 20 0 00 0 08 8 8,,, w w wh h hi i ic c ch h h i i in n nd d di i ic c ca a at t te e es s s t t th h ha a at t t t t th h he e e d d di i is s sc c ci i ip p pl l li i ine is\ns s st t ti i il l ll l l i i in n n i i it t ts s s i i in n nf f fa a an n nc c cy y y... I I It t t w w wi i il l ll l l b b be e e e e ex x xc c ci i it t ti i in n ng g g t t to o o s s se e ee e e h h ho o ow w w E E ED D DM M M d d de e ev v ve e el l lo o op p ps s s o o ov v ve e er r r t t th h he e e c c co o om m mi i in n ng g g y y ye e ea a ar r rs s s...\nB Bi ie en nk ko ow ws sk ki i,, F Fe en ng g,, a an nd d M Me ea an ns s ( (2 20 01 12 2) ) p pr re es se en nt te ed d a a t th ho or ro ou ug gh h r re ep po or rt t o on n h ho ow w e ed du uc ca at ti io on na al l\nd da at ta a m mi in ni in ng g a an nd d l le ea ar rn ni in ng g a an na al ly yt ti ic cs s c ca an n e en nh ha an nc ce e t te ea ac ch hi in ng g a an nd d l le ea ar rn ni in ng g.. The autho or rs s o ou ut tl li in ne ed d\nc co om mp pe el ll li in ng g a av ve en nu ue es s f fo or r f fu ur rt th he er r r re es se ea ar rc ch h.. These included:\n• a focus on u u us s sa a ab b bi i il l li i it t ty y y a a an n nd d d i i im m mp p pa a ac c ct t t o o of f f p p pr r re e es s se e en n nt t ti i in n ng g g l l le e ea a ar r rn n ni i in n ng g g d d da a at t ta a a t t to o o i i in n ns s st t tr r ru u uc c ct t to o or r rs s s; ; ;\n• development of d d de e ec c ci i is s si i io o on n n s s su u up p pp p po o or r rt t t s s sy y ys s st t te e em m ms s s a a an n nd d d r r re e ec c co o om m mm m me e en n nd d da a at t ti i io o on n n s s sy y ys s st t te e em m ms s s t t th h ha a at t t m m mi i in n ni i im m mi i iz z ze e e\n• development of t t to o oo o ol l ls s s f f fo o or r r p p pr r ro o ot t te e ec c ct t ti i in n ng g g i i in n nd d di i iv v vi i id d du u ua a al l l p p pr r ri i iv v va a ac c cy y y w w wh h hi i il l le e e s s st t ti i il l ll l l a a ad d dv v va a an n nc c ci i in n ng g g e e ed d du u uc c ca a at t ti i io o on n na a al l l\ndata mining; and\n• development of m mo od de el ls s t th ha at t c ca an n b be e u us se ed d i in n m mu ul lt ti ip pl le e c co on nt te ex xt ts s.\nResearchers have n no ot t a ad dd dr re es ss se ed d h ho ow w d da at ta a m mi in ni in ng g can be applied to p pl la ag gi ia ar ri is sm m d de et te ec ct ti io on n..\nPlagiar ri is sm m i is s a a t to op pi ic c t th ha at t f fa ac cu ul lt ty y b be ec co om me e q qu ui it te e c co on nc ce er rn ne ed d w wi it th h. Thus, i it t b be eh ho oo ov ve es s u us s t to o d de ev ve el lo op p\np pr re ed di ic ct ti iv ve e c ca ap pa ab bi il li it ty y i in n p pl la ag gi ia ar ri is sm m-related issues.\nF Fu ut tu ur re e r re es se ea ar rc ch h c ca an n e ex xa am mi in ne e h ho ow w w wi id de es sp pr re ea ad d t th he e a ad do op pt ti io on n o of f e ed du uc ca at ti io on na al l d da at ta a m mi in ni in ng g\nmight be. Currently, it appea a ar r rs s s t t th h ha a at t t r r re e es s se e ea a ar r rc c ch h h i i in n n t t th h hi i is s s a a ar r re e ea a a i i is s s i i is s so o ol l la a at t te e ed d d a a an n nd d d w w we e e d d do o o n n no o ot t t k k kn n no o ow w w t t th h he e e e e ex x xa a ac c ct t t\ne e ex x xt t te e en n nt t t o o of f f h h ho o ow w w i i in n ns s st t ti i it t tu u ut t ti i io o on n ns s s m m mi i ig g gh h ht t t b b be e e u u us s si i in n ng g g d d da a at t ta a a m m mi i in n ni i in n ng g g f f fo o or r r e e en n nh h ha a an n nc c ci i in n ng g g s s st t tu u ud d de e en n nt t t l l le e ea a ar r rn n ni i in n ng g g o o or r r\ni im mp pr ro ov vi in ng g r re el la at te ed d e ed du uc ca at ti io on na al l p pr ro oc ce es ss se es s.. F Fu ur rt th he er rm mo or re e,, w we e d do o n no ot t k kn no ow w i if f t th he er re e a ar re e i in nt te en nt ti io on ns s t to o\na a ad d do o op p pt t t E E ED D DM M M o o or r r a a an n ny y y i i in n ni i it t ti i ia a at t ti i iv v ve e es s s w w wh h he e er r re e e i i in n ns s st t ti i it t tu u ut t ti i io o on n ns s s a a ar r re e e c c co o on n ns s si i id d de e er r ri i in n ng g g a a ad d do o op p pt t ti i in n ng g g a a an n n E E ED D DM M M s s st t tr r ra a at t te e eg g gy y y... I I It t t\nw w wo o ou u ul l ld d d b b be e e i i in n nt t te e er r re e es s st t ti i in n ng g g t t to o o d d de e et t te e er r rm m mi i in n ne e e i i if f f t t th h he e er r re e e a a ar r re e e b b ba a ar r rr r ri i ie e er r rs s s t t th h ha a at t t p p pr r re e ev v ve e en n nt t t i i in n ns s st t ti i it t tu u ut t ti i io o on n ns s s f f fr r ro o om m m e e es s st t ta a ab b bl l li i is s sh h hi i in n ng g g\nEDM initiatives. T Th he er re e a ar re e a a f fe ew w c ca as se e s st tu ud di ie es s o on n h ho ow w EDM is appl li ie ed d t to o a ad dm mi is ss si io on ns s and\ne e en n nr r ro o ol l ll l lm m me e en n nt t t,,, b b bu u ut t t f f fu u ur r rt t th h he e er r r w w wo o or r rk k k n n ne e ee e ed d ds s s t t to o o b b be e e d d do o on n ne e e b b be e ec c ca a au u us s se e e t t th h ho o os s se e e c c ca a as s se e e s s st t tu u ud d di i ie e es s s s s se e ee e em m m i i is s so o ol l la a at t te e ed d d f f fr r ro o om m m t t th h he e e\nmainstream EDM work.\nB B Ba a ak k ke e er r r,,, R R R...,,, & & & Y Y Ya a ac c ce e ef f f,,, K K K... ( ( (2 2 20 0 00 0 09 9 9) ) )... T T Th h he e e S S St t ta a at t te e e o o of f f E E Ed d du u uc c ca a at t ti i io o on n na a al l l D D Da a at t ta a a m m mi i in n ni i in n ng g g i i in n n 2 2 20 0 00 0 09 9 9: : : A A A R R Re e ev v vi i ie e ew w w and\nFuture Visions. J Jo ou ur rn na al l o of f E Ed du uc ca at ti io on na al l D Da at ta a M Mi in ni in ng g,, 1 1(1).\nB B Be e er r rs s so o on n n,,, A A A...,,, S S Sm m mi i it t th h h,,, S S S...,,, & & & T T Th h he e ea a ar r rl l li i in n ng g g,,, K K K... ( ( (2 2 20 0 01 1 11 1 1) ) )... A A An n n O O Ov v ve e er r rv v vi i ie e ew w w o o of f f D D Da a at t ta a a M M Mi i in n ni i in n ng g g T T Te e ec c ch h hn n ni i iq q qu u ue e es s s\nR Re et tr ri ie ev ve ed d N No ov ve em mb be er r 2 28 8,, 2 20 01 11 1,, f fr ro om m\nh ht tt tp p: :/ // /w ww ww w..t th he ea ar rl li in ng g..c co om m/ /t te ex xt t/ /d dm mt te ec ch hn ni iq qu ue es s/ /d dm mt te ec ch hn ni iq qu ue es s..h ht tm m\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 10 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nBlikstein, P. (2011). U U Us s si i in n ng g g l l le e ea a ar r rn n ni i in n ng g g a a an n na a al l ly y yt t ti i ic c cs s s t t to o o a a as s ss s se e es s ss s s s s st t tu u ud d de e en n nt t ts s s''' b b be e eh h ha a av v vi i io o or r r i i in n n o o op p pe e en n n-ended\nprogramming tasks... P P Pa a ap p pe e er r r p p pr r re e es s se e en n nt t te e ed d d a a at t t t t th h he e e P P Pr r ro o oc c ce e ee e ed d di i in n ng g gs s s o o of f f t t th h he e e 1 1 1s s st t t I I In n nt t te e er r rn n na a at t ti i io o on n na a al l l\nC C Co o on n nf f fe e er r re e en n nc c ce e e o o on n n L L Le e ea a ar r rn n ni i in n ng g g A A An n na a al l ly y yt t ti i ic c cs s s a a an n nd d d K K Kn n no o ow w wl l le e ed d dg g ge e e,,, B B Ba a an n nf f ff f f,,, A A Al l lb b be e er r rt t ta a a,,, C C Ca a an n na a ad d da a a...\nC C Ca a al l ld d de e er r rs s s,,, T T T...,,, & & & P P Pe e ec c ch h he e en n ni i iz z zk k ki i iy y y,,, M M M... ( ( (2 2 20 0 01 1 12 2 2) ) )... I I In n nt t tr r ro o od d du u uc c ct t ti i io o on n n t t to o o t t th h he e e s s sp p pe e ec c ci i ia a al l l s s se e ec c ct t ti i io o on n n o o on n n e e ed d du u uc c ca a at t ti i io o on n na a al l l d d da a at t ta a a\nmining. S SI IG GK KD DD D E Ex xp pl lo or r.. N Ne ew wsl., 13(2), 3-6 6.. d do oi i: : 1 10 0..1 11 14 45 5/ /2 22 20 07 72 24 43 3..2 22 20 07 72 24 45 5\nC C Ca a am m mp p pb b be e el l ll l l,,, J J J...,,, & & & O O Ob b bl l li i in n ng g ge e er r r,,, D D D... ( ( (2 2 20 0 00 0 07 7 7) ) )... A A Ac c ca a ad d de e em m mi i ic c c a a an n na a al l ly y yt t ti i ic c cs s s... W W Wa a as s sh h hi i in n ng g gt t to o on n n,,, D D DC C C: : : E E Ed d du u uc c ca a au u us s se e e...\nC C Ch h ha a ac c co o on n n,,, F F F...,,, S S Sp p pi i ic c ce e er r r,,, D D D...,,, & & & V V Va a al l lb b bu u ue e en n na a a,,, A A A... ( ( (2 2 20 0 01 1 12 2 2) ) )... A A An n na a al l ly y yt t ti i ic c cs s s i i in n n S S Su u up p pp p po o or r rt t t o o of f f S S St t tu u ud d de e en n nt t t R R Re e et t te e en n nt t ti i io o on n n a a an n nd d d\nS Su uc cc ce es ss s ( (R Re es se ea ar rc ch h B Bu ul ll le et ti in n 3 3,, 2 20 01 12 2 e ed d..) ).. L Lo ou ui is sv vi il ll le e,, C CO O: : E Ed du uc ca au us se e C Ce en nt te er r f fo or r A Ap pp pl li ie ed d\nC C Ch h hr r ry y ys s so o os s st t to o om m mo o ou u u,,, K K K...,,, C C Ch h he e en n n,,, S S S... Y Y Y...,,, & & & L L Li i iu u u,,, X X X... ( ( (2 2 20 0 00 0 09 9 9) ) )... I I In n nv v ve e es s st t ti i ig g ga a at t ti i io o on n n o o of f f U U Us s se e er r rs s s''' P P Pr r re e ef f fe e er r re e en n nc c ce e es s s i i in n n\nI In nt te er ra ac ct ti iv ve e M Mu ul lt ti im me ed di ia a L Le ea ar rn ni in ng g S Sy ys st te em ms s: : A A D Da at ta a M Mi in ni in ng g A Ap pp pr ro oa ac ch h.. I In nt te er ra ac ct ti iv ve e\nL Le ea ar rn ni in ng g E En nv vi ir ro on nm me en nt ts s,, 1 17 7(2), 151-163.\nC C Co o oc c ce e ea a a,,, M M M...,,, & & & W W We e ei i ib b be e el l lz z za a ah h hl l l,,, S S S... ( ( (2 2 20 0 00 0 09 9 9) ) )... L L Lo o og g g f f fi i il l le e e a a an n na a al l ly y ys s si i is s s f f fo o or r r d d di i is s se e en n ng g ga a ag g ge e em m me e en n nt t t d d de e et t te e ec c ct t ti i io o on n n i i in n n e e e-Learning\nenvironments. U Us se er r M Mo od de el li in ng g a an nd d U Us se er r - Adapted Interaction, 19( (4 4) ),, 3 34 41 1-385. doi:\n10.1007/s11257-009-9 90 06 65 5-5\nCorbett, A. T. (2001). C Co og gn ni it ti iv ve e C Co om mp pu ut te er r T Tutors: Solving the Two-S Si ig gm ma a P Pr ro ob bl le em m. Paper\np p pr r re e es s se e en n nt t te e ed d d a a at t t t t th h he e e P P Pr r ro o oc c ce e ee e ed d di i in n ng g gs s s o o of f f t t th h he e e 8 8 8t t th h h I I In n nt t te e er r rn n na a at t ti i io o on n na a al l l C C Co o on n nf f fe e er r re e en n nc c ce e e o o on n n U U Us s se e er r r M M Mo o od d de e el l li i in n ng g g 2 2 20 0 00 0 01 1 1...\nD D Dr r ri i in n ng g gu u us s s,,, L L L...,,, & & & E E El l ll l li i is s s,,, T T T... ( ( (2 2 20 0 00 0 05 5 5) ) )... U U Us s si i in n ng g g d d da a at t ta a a m m mi i in n ni i in n ng g g a a as s s a a a s s st t tr r ra a at t te e eg g gy y y f f fo o or r r a a as s ss s se e es s ss s si i in n ng g g a a as s sy y yn n nc c ch h hr r ro o on n no o ou u us s s\ndiscussion forums. C Co om mp pu ut te er rs s & & Education, 45, 141-160.\nDunham, M. (2003). D Da at ta a M Mi in ni in ng g: : I In nt tr ro od du uc ct to or ry y a an nd d A Ad dv va an nc ce ed d T To op pi ic cs s.. U Up pp pe er r S Sa ad dd dl le e R Ri iv ve er r,, N NJ J: :\nG G Ga a ar r rc c cí í ía a a,,, E E E...,,, R R Ro o om m me e er r ro o o,,, C C C...,,, V V Ve e en n nt t tu u ur r ra a a,,, S S S...,,, & & & d d de e e C C Ca a as s st t tr r ro o o,,, C C C... ( ( (2 2 20 0 01 1 11 1 1) ) )... A A A c c co o ol l ll l la a ab b bo o or r ra a at t ti i iv v ve e e e e ed d du u uc c ca a at t ti i io o on n na a al l l\na as ss so oc ci ia at ti io on n r ru ul le e m mi in ni in ng g t to oo ol l.. The Internet and Higher Education, 14( (2 2) ),, 7 77 7-88. doi:\n1 10 0..1 10 01 16 6/ /j j..i ih he ed du uc c..2 20 01 10 0..0 07 7..0 00 06 6\nG G Gu u ua a an n n,,, J J J...,,, N N Nu u un n ne e ez z z,,, W W W...,,, & & & W W We e el l ls s sh h h,,, J J J... ( ( (2 2 20 0 00 0 02 2 2) ) )... I I In n ns s st t ti i it t tu u ut t ti i io o on n na a al l l s s st t tr r ra a at t te e eg g gy y y a a an n nd d d i i in n nf f fo o or r rm m ma a at t ti i io o on n n s s su u up p pp p po o or r rt t t: : : t t th h he e e r r ro o ol l le e e\no of f d da at ta a w wa ar re eh ho ou us si in ng g i in n h hi ig gh he er r e ed du uc ca at ti io on n.. Campus-W Wi id de e I In nf fo or rm ma at ti io on n S Sy ys st te em ms s,, 1 19 9(5), 168-\nHuang, Y.-M., Chen, J.-N N..,, & & C Ch he en ng g,, S S..-C. (2007). A Method of Cross-L Le ev ve el l F Fr re eq qu ue en nt t P Pa at tt te er rn n\nMining for Web-B Ba as se ed d I In ns st tr ru uc ct ti io on n.. E Ed du uc ca at ti io on na al l T Te ec ch hn no ol lo og gy y & & S So oc ci ie et ty y,, 1 10 0(3), 305-319.\nI IB BM M.. ( (2 20 01 12 2) ).. W Wh ha at t i is s b bi ig g d da at ta a? ? R Re et tr ri ie ev ve ed d M Ma ay y 1 16 6t th h,, 2 20 01 12 2,, f fr ro om m http://www-\n0 01 1..i ib bm m..c co om m/ /s so of ft tw wa ar re e/ /d da at ta a/ /b bi ig gd da at ta a/ /\nK K Ki i ir r ro o on n n,,, D D D...,,, S S Sh h ho o oc c ck k kl l le e ey y y,,, R R R...,,, K K Kr r ru u us s sc c ch h hw w wi i it t tz z z,,, N N N...,,, F F Fi i in n nc c ch h h,,, G G G...,,, & & & H H Ha a ay y yd d do o oc c ck k k,,, M M M... ( ( (2 2 20 0 01 1 12 2 2) ) )... A A An n na a al l ly y yt t ti i ic c cs s s: : : T T Th h he e e\nWidening Divide. M MI IT T S Sl lo oa an n M Ma an na ag ge em me en nt t R Re ev vi ie ew w,, 5 53 3(2), 1-22.\nLeventha a al l l,,, B B B... ( ( (2 2 20 0 01 1 10 0 0) ) )... A A An n n i i in n nt t tr r ro o od d du u uc c ct t ti i io o on n n t t to o o d d da a at t ta a a m m mi i in n ni i in n ng g g a a an n nd d d o o ot t th h he e er r r t t te e ec c ch h hn n ni i iq q qu u ue e es s s f f fo o or r r a a ad d dv v va a an n nc c ce e ed d d\nanalytics. J Jo ou ur rn na al l o of f D Di ir re ec ct t,, D Da at ta a a an nd d D Di ig gi it ta al l M Ma ar rk ke et ti in ng g P Pr ra ac ct ti ic ce e,, 1 12 2( (2 2) ),, 1 13 37 7-153. doi:\nLin, S.-H H.. ( (2 20 01 12 2) ).. D Da at ta a m mi in ni in ng g f fo or r s st tu ud de en nt t r re et te en nt ti io on n m ma an na ag ge em me en nt t.. J.. C Co om mp pu ut t.. S Sc ci i.. C Co ol ll l..,, 2 27 7(4),\nLuan, J. (2002). D D Da a at t ta a a M M Mi i in n ni i in n ng g g a a an n nd d d K K Kn n no o ow w wl l le e ed d dg g ge e e M M Ma a an n na a ag g ge e em m me e en n nt t t i i in n n H H Hi i ig g gh h he e er r r E E Ed d du u uc c ca a at t ti i io o on n n - Potential\nApplications... P P Pa a ap p pe e er r r p p pr r re e es s se e en n nt t te e ed d d a a at t t t t th h he e e A A An n nn n nu u ua a al l l F F Fo o or r ru u um m m f f fo o or r r t t th h he e e A A As s ss s so o oc c ci i ia a at t ti i io o on n n f f fo o or r r I I In n ns s st t ti i it t tu u ut t ti i io o on n na a al l l\nR Re es se ea ar rc ch h,, T To or ro on nt to o,, O On nt ta ar ri io o,, C Ca an na ad da a..\nh ht tt tp p: :/ // /e er ri ic c..e ed d..g go ov v/ /E ER RI IC CW We eb bP Po or rt ta al l/ /d de et ta ai il l? ?a ac cc cn no o= =E ED D4 47 74 41 14 43 3\nM M Mö ö öd d dr r ri i it t ts s sc c ch h he e er r r,,, F F F... ( ( (2 2 20 0 01 1 10 0 0) ) )... T T To o ow w wa a ar r rd d ds s s a a a r r re e ec c co o om m mm m me e en n nd d de e er r r s s st t tr r ra a at t te e eg g gy y y f f fo o or r r p p pe e er r rs s so o on n na a al l l l l le e ea a ar r rn n ni i in n ng g g e e en n nv v vi i ir r ro o on n nm m me e en n nt t ts s s...\nP Pr ro oc ce ed di ia a C Co om mp pu ut te er r S Sc ci ie en nc ce e,, 1 1(2), 2775-2782. doi: 1 10 0..1 10 01 16 6/ /j j..p pr ro oc cs s..2 20 01 10 0..0 08 8..0 00 02 2\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 11 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nM M Mu u ul l ld d dn n ne e er r r,,, K K K...,,, B B Bu u ur r rl l le e es s so o on n n,,, W W W...,,, V V Va a an n n d d de e e S S Sa a an n nd d de e e,,, B B B...,,, & & & V V Va a an n nl l le e eh h hn n n,,, K K K... ( ( (2 2 20 0 01 1 11 1 1) ) )... A A An n n a a an n na a al l ly y ys s si i is s s o o of f f s s st t tu u ud d de e en n nt t ts s s'''\ng g ga a am m mi i in n ng g g b b be e eh h ha a av v vi i io o or r rs s s i i in n n a a an n n i i in n nt t te e el l ll l li i ig g ge e en n nt t t t t tu u ut t to o or r ri i in n ng g g s s sy y ys s st t te e em m m: : : p p pr r re e ed d di i ic c ct t to o or r rs s s a a an n nd d d i i im m mp p pa a ac c ct t ts s s... User\nModeling and User - A Ad da ap pt te ed d I In nt te er ra ac ct ti io on n,, 2 21 1(1-2), 99-13 35 5.. d do oi i: : 1 10 0..1 10 00 07 7/ /s s1 11 12 25 57 7-010-\nN N Ne e em m ma a at t ti i i,,, H H H...,,, & & & B B Ba a ar r rk k ko o o,,, C C C... ( ( (2 2 20 0 00 0 04 4 4) ) )... O O Or r rg g ga a an n ni i iz z za a at t ti i io o on n na a al l l D D Da a at t ta a a M M Mi i in n ni i in n ng g g ( ( (O O OD D DM M M) ) ): : : A A An n n I I In n nt t tr r ro o od d du u uc c ct t ti i io o on n n... I I In n n H H H...\nN Ne em ma at ti i & & C C.. B Ba ar rk ko o ( (E Ed ds s..) ),, Organizational Data Mining (pp. 1-8 8) ).. L Lo on nd do on n: : I Id de ea a G Gr ro ou up p\nR Ra an nj ja an n,, J J..,, & & M Ma al li ik k,, K K.. ( (2 20 00 07 7) ).. E Ef ff fe ec ctive educational process: a data-m mi in ni in ng g a ap pp pr ro oa ac ch h.. VINE:\nT Th he e J Jo ou ur rn na al l o of f I In nf fo or rm ma at ti io on n a an nd d K Kn no ow wl le ed dg ge e M Ma an na ag ge em me en nt t S Sy ys st te em ms s,, 3 37 7( (4 4) ),, 5 50 02 2-515.\nR R Ro o om m me e er r ro o o,,, C C C...,,, & & & V V Ve e en n nt t tu u ur r ra a a,,, S S S... ( ( (2 2 20 0 01 1 10 0 0) ) )... E E Ed d du u uc c ca a at t ti i io o on n na a al l l D D Da a at t ta a a M M Mi i in n ni i in n ng g g: : : A A A R R Re e ev v vi i ie e ew w w o o of f f t t th h he e e S S St t ta a at t te e e o o of f f t t th h he e e A A Ar r rt t t...\nS Sy ys st te em ms s,, M Ma an n,, a an nd d C Cy yb be er rn ne et ti ic cs s,, P Pa ar rt t C C: : A Ap pp pl li ic ca at ti io on ns s a an nd d R Re ev vi ie ew ws s,, I IE EE EE E T Tr ra an ns sa ac ct ti io on ns s\non, 40(6), 601-6 61 18 8.. d do oi i: : 1 10 0..1 11 10 09 9/ /t ts sm mc cc c..2 20 01 10 0..2 20 05 53 35 53 32 2\nR R Ro o om m me e er r ro o o,,, C C C...,,, V V Ve e en n nt t tu u ur r ra a a,,, S S S...,,, & & & G G Ga a ar r rc c cí í ía a a,,, E E E... ( ( (2 2 20 0 00 0 08 8 8) ) )... D D Da a at t ta a a m m mi i in n ni i in n ng g g i i in n n c c co o ou u ur r rs s se e e m m ma a an n na a ag g ge e em m me e en n nt t t s s sy y ys s st t te e em m ms s s: : :\nM Mo oo od dl le e c ca as se e s st tu ud dy y a an nd d t tu ut to or ri ia al l.. Computers & Education, 51(1), 368-3 38 84 4.. d do oi i: :\n1 10 0..1 10 01 16 6/ /j j..c co om mp pe ed du u..2 20 00 07 7..0 05 5..0 01 16 6\nS S Sa a an n nt t to o os s s,,, O O O... C C C...,,, & & & B B Bo o ot t ti i ic c ca a ar r ri i io o o,,, J J J... G G G... ( ( (2 2 20 0 01 1 10 0 0) ) )... M M Mo o od d de e el l li i in n ng g g r r re e ec c co o om m mm m me e en n nd d da a at t ti i io o on n ns s s f f fo o or r r t t th h he e e e e ed d du u uc c ca a at t ti i io o on n na a al l l d d do o om m ma a ai i in n n...\nP Pr ro oc ce ed di ia a C Co om mp pu ut te er r S Sc ci ie en nc ce e,, 1 1(2), 2793-2 28 80 00 0.. d do oi i: : 1 10 0..1 10 01 16 6/ /j j..p pr ro oc cs s..2 20 01 10 0..0 08 8..0 00 04 4\nSu, J.-m., Tseng, S.-s., Lin, H.-y y..,, & & C Chen, C.-h h.. ( (2 20 01 11 1) ).. A A p pe er rs so on na al li iz ze ed d l le ea ar rn ni in ng g c co on nt te en nt t\na a ad d da a ap p pt t ta a at t ti i io o on n n m m me e ec c ch h ha a an n ni i is s sm m m t t to o o m m me e ee e et t t d d di i iv v ve e er r rs s se e e u u us s se e er r r n n ne e ee e ed d ds s s i i in n n m m mo o ob b bi i il l le e e l l le e ea a ar r rn n ni i in n ng g g e e en n nv v vi i ir r ro o on n nm m me e en n nt t ts s s... User\nModeling and User - A Ad da ap pt te ed d I In nt te er ra ac ct ti io on n,, 2 21 1(1-2), 5-4 49 9.. d do oi i: : 1 10 0..1 10 00 07 7/ /s s1 11 12 25 57 7-010-9094-\nThai-N Ng gh he e,, N N..,, D Dr ru um mo on nd d,, L L..,, K Kr ro oh hn n-Grimberghe, A., & Schmidt-T Th hi ie em me e,, L L.. ( (2 20 01 10 0) )..\nR Re ec co om mm me en nd de er r s sy ys st te em m f fo or r p pr re ed di ic ct ti in ng g s st tu ud de en nt t p pe er rf fo or rm ma an nc ce e.. P Pr ro oc ce ed di ia a C Co om mp pu ut te er r S Sc ci ie en nc ce e,,\n1(2), 2811-2 28 81 19 9.. d do oi i: : 1 10 0..1 10 01 16 6/ /j j..p pr ro oc cs s..2 20 01 10 0..0 08 8..0 00 06 6\nT Th ho om ma as s,, E E.. H H..,, & & G Ga al la am mb bo os s,, N N.. ( (2 20 00 04 4) ).. W Wh ha at t S Sa at ti is sf fi ie es s S St tu ud de en nt ts s? ?: : M Mi in ni in ng g S St tu ud de en nt t-Opinion Data\nw wi it th h R Re eg gr re es ss si io on n a an nd d D De ec ci is si io on n T Tr re ee e A An na al ly ys si is s.. R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n,, 4 45 5(3), 251-\nV V Va a an n nd d da a am m mm m me e e,,, J J J... P P P...,,, M M Me e es s sk k ke e en n ns s s,,, N N N...,,, & & & S S Su u up p pe e er r rb b by y y,,, J J J... F F F... ( ( (2 2 20 0 00 0 07 7 7) ) )... P P Pr r re e ed d di i ic c ct t ti i in n ng g g A A Ac c ca a ad d de e em m mi i ic c c P P Pe e er r rf f fo o or r rm m ma a an n nc c ce e e b b by y y\nData Mining Methods. E Ed du uc ca at ti ion Economics, 15(4), 405-419.\nV V Vi i ia a al l la a ar r rd d di i i,,, C C C...,,, C C Ch h hu u ue e e,,, J J J...,,, P P Pe e ec c ch h he e e,,, J J J... P P P...,,, A A Al l lv v va a ar r ra a ad d do o o,,, G G G...,,, V V Vi i in n na a at t te e ea a a,,, B B B...,,, E E Es s st t tr r re e el l ll l la a a,,, J J J...,,, & & & O O Or r rt t ti i ig g go o os s sa a a,,, Á Á Á... ( ( (2 2 20 0 01 1 11 1 1) ) )...\nA A A d d da a at t ta a a m m mi i in n ni i in n ng g g a a ap p pp p pr r ro o oa a ac c ch h h t t to o o g g gu u ui i id d de e e s s st t tu u ud d de e en n nt t ts s s t t th h hr r ro o ou u ug g gh h h t t th h he e e e e en n nr r ro o ol l ll l lm m me e en n nt t t p p pr r ro o oc c ce e es s ss s s b b ba a as s se e ed d d o o on n n\nacademic performance. U Us se er r M Mo od de el li in ng g a an nd d U Us ser - A Ad da ap pt te ed d I In nt te er ra ac ct ti io on n,, 2 21 1(1-2), 217-248.\ndoi: 10.1007/s11257-0 01 11 1-9098-4\nWang, F.-H H.. ( (2 20 00 08 8) ).. C Co on nt te en nt t R Re ec co om mm me en nd da at ti io on n B Ba as se ed d o on n E Ed du uc ca at ti io on n-C Co on nt te ex xt tu ua al li iz ze ed d B Br ro ow ws si in ng g\nEvents for Web-B Ba as se ed d P Pe er rs so on na al li iz ze ed d L Le ea ar rn ni in ng g.. E Ed du uc ca at ti io on na al l T Te ec ch hn no ol lo og gy y & & S So oc ci ie et ty y,, 1 11 1(4),\nWang, Y.-h., & Liao, H.-C C C... ( ( (2 2 20 0 01 1 11 1 1) ) )... D D Da a at t ta a a m m mi i in n ni i in n ng g g f f fo o or r r a a ad d da a ap p pt t ti i iv v ve e e l l le e ea a ar r rn n ni i in n ng g g i i in n n a a a T T TE E ES S SL L L-based e-\nlearning system. E Ex xp pe er rt t S Sy ys st te em ms s w wi it th h A Ap pp pl li ic ca at ti io on ns s,, 3 38 8(6), 6480-6 64 48 85 5.. d do oi i: :\n1 10 0..1 10 01 16 6/ /j j..e es sw wa a..2 20 01 10 0..1 11 1..0 09 98 8\nY Ye ea at ts s,, R R..,, R Re ed dd dy y,, P P.. J J..,, W Wh he ee el le er r,, A A..,, S Se en ni io or r,, C C..,, & & M Mu ur rr ra ay y,, J J.. ( (2 20 01 10 0) ).. W Wh ha at t a a d di if ff fe er re en nc ce e a a w wr ri it ti in ng g\nc ce en nt tr re e m ma ak ke es s: : a a s sm ma al ll l s sc ca al le e s st tu ud dy y.. Education & Training, 52(6/7), 499-5 50 07 7.. d do oi i: :\n1 10 0..1 11 10 08 8/ /0 00 04 40 00 09 91 11 10 01 11 10 06 68 84 45 50 0\nY Y Yo o or r rk k ke e e,,, M M M...,,, B B Ba a ar r rn n ne e et t tt t t,,, G G G...,,, E E Ev v va a an n ns s so o on n n,,, P P P...,,, H H Ha a ai i in n ne e es s s,,, C C C...,,, J J Je e en n nk k ki i in n ns s s,,, D D D...,,, K K Kn n ni i ig g gh h ht t t,,, P P P...,,, ... ... ... W W Wo o oo o ol l lf f f,,, H H H... ( ( (2 2 20 0 00 0 05 5 5) ) )...\nMining Institutional Da a at t ta a as s se e et t ts s s t t to o o S S Su u up p pp p po o or r rt t t P P Po o ol l li i ic c cy y y M M Ma a ak k ki i in n ng g g a a an n nd d d I I Im m mp p pl l le e em m me e en n nt t ta a at t ti i io o on n n... Journal of\nH Hi ig gh he er r E Ed du uc ca at ti io on n P Po ol li ic cy y a an nd d M Ma an na ag ge em me en nt t,, 2 27 7(2), 285-298.\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 12 R Re es se ea ar rc ch h i in n H Hi ig gh he er r E Ed du uc ca at ti io on n J Jo ou ur rn na al l\nY Yu u,, C C.. H H..,, D Di iG Ga an ng gi i,, S S..,, J Ja an nn na as sc ch h-P Pe en nn ne el ll l,, A A..,, & & K Ka ap pr ro ol le et t,, C C.. ( (2 20 01 10 0) ).. A A d da at ta a m mi in ni in ng g a ap pp pr ro oa ac ch h f fo or r\ni id de en nt ti if fy yi in ng g p pr re ed di ic ct to or rs s o of f s st tu ud de en nt t r re et te en nt ti io on n f fr ro om m s so op ph ho om mo or re e t to o j ju un ni io or r y ye ea ar r.. Journal of\nData Science, 8, 307-3 32 25 5..\nEducational data-m mi in ni in ng g r re es se ea ar rc ch h,, P Pa ag ge e 13\nΠερισσότερα από τον χρήστη quiltamused\nFuture trends in data mining\nData Mining Applications for Space Mission Operations System Health Monitoring\nMCTS Self-Paced Training Kit (Exams 70-529). Microsoft .Net\nes. Big Picture: What a Web Site Doe got 50%? And what if ...\nhomelessness service integration: round 2, 2011 - Australian ...\nNational Guidelines for Water Recycling:\nPalm Harbor University High School Uniform Course Descriptions\nMUSIC, DEVOTIONS, AND MASHRIQU'L-ADHKAR\nKinematics of Machinery Through HyperWorks (History of ... - FTP ITB!\nEpistemology, cybernetics and uncertainty - Simon Fraser University\nU s e r ' s G u i d e\nP y G T K t u t o r i a l\nS-- - SH R GM F\nDownload - Australian Homelessness Clearinghouse\nnotesx - Google Code\nENVIRONMENTAL MANAGEMENT FRAMEWORK DOCUMENT