AHP - Danh Gai Bai Giang

Tp ch Khoa hc HQGHN: Nghin cu Gio dc, Tp 31, S 1 (2015) 13-27

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M hnh TOPSIS-AHP s dng b tiu ch ICT Newhouse nh gi bi ging vi tr gip ra quyt nh thng minh

Phm Vn Hi*,1, Nguyn Th M Lc2 1Vin Cng ngh Thng tin-Truyn Thng, Trng i hc Bch khoa H Ni

2Trng i hc Gio dc, i hc Quc Gia H Ni

Nhn ngy 22 thng 4 nm 2014 Chnh sa ngy 29 thng 5 nm 2014; chp nhn ng ngy 26 thng 3 nm 2015

Tm tt: Trong nhng nm gn y, vi s pht trin nhanh chng ca khoa hc cng ngh kt hp o to truyn thng, E-learning hin v ang ph bin trong cc trng i hc hin nay. Trong qu trnh nghin cu v ging dy, vic nh gi bi ging v bi ging in t trn mng theo phng php truyn thng bng cch xc nh cc tiu ch nh gi c trng s l nh nhau thng gp nhng hn ch i vi cc tiu ch c mc quan trng khc nhau. Theo phng php nh gi bi ging truyn thng, cc s liu c thng k t cc chuyn gia a ra di dng thng k trung bnh kt qu ca cc chuyn gia s b hn ch. Nghin cu ny a ra cc phng php tch hp ra quyt nh nh gi bi ging trc tuyn vi m hnh nhiu chuyn gia cng tham gia nh gi bi ging ng thi. M hnh xut s dng cc k thut tch hp ra quyt nh TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) v AHP (Analytic Hierachy Process) da trn b tiu ch ICT Newhouse kt hp cc tri thc t chuyn gia a ra quy trnh nh gi bi ging. nh gi m hnh trn, chng ti biu din v d minh ha v ci t chng trnh vi thc nghim thc tin nh gi bi ging trc tuyn. Kt qu thc nghim cho thy m hnh xut nh gi bi ging vi nh gi ng th hin cc tc ng a chiu nh hng tch cc ca chuyn gia trong m hnh nh gi bi ging. nh gi bi ging theo m hnh xut s gip cho ngi qun l ra quyt nh ng n vi a tiu ch mc ch.

T kha: TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), AHP (Analytic Hierachy Process), nh gi bi ging, tr gip ra quyt nh.

1. Gii thiu

Trong ging dy v o to, nh gi bi ging tr thnh mt yu t quan trng trong qu trnh nh gi cht lng hc tp. tr gip cho cng tc nh gi cht lng bi ging, nhm nghin cu v xy dng mt h

_______

Tc gi lin h. T: 84-1293727555

Email: [email protected]

tr gip quyt nh h tr nhm chuyn gia kt hp vi cc k thut ra quyt nh l TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) [12,13] v AHP (Analytic Hierachy Process) [7,9-11]. Vi cc kt qu cng trnh nghin cu ca cc tc gi Alya nm 2014 v cc nhm tc gi cng b nm 2013-2014 [18-21], cc m hnh TOPSIS-AHP cng p dng nh gi c s gio dc trong qun l gio dc. Hu ht cc

P.V. Hi, N.T.M. Lc / Tp ch Khoa hc HQGHN: Nghin cu Gio dc, Tp 31, S 1 (2015) 13-27

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nghin cu ny cha cp n mc nh gi nh tch cc hay tiu cc t cc ch th. im mi ca m hnh TOPSIS-AHP l m hnh tch hp gia TOPSIS v AHP nh gi bi ging tr gip quyt nh nhm cho php nhiu chuyn gia cng tham gia nh gi v tch hp vi k thut AHP vi b tiu ch ICT Newhouse cho php ngi ra quyt nh cui cng xc nh mc nh gi tch cc ca cc chuyn gia.

Cc nghin cu truyn thng thng da trn kinh nghim ca cc chuyn gia ging dy, nh qun l gio dc th c rt nhiu cc yu t nh hng, tc ng n vic nng cao cht lng cc bi ging [3, 16]. i vi cc chuyn gia v ngi c kinh nghim ging dy, vic nh gi mt bi ging v nhng t vn nhm nng cao cht lng bi ging trc tuyn cng l mt thch thc ln. Cc bi ging in t ngy cng c cc gio vin trong nh trng s dng nh mt cng c nhm nng cao hiu qu ging dy [14]. Xy dng h thng tr gip nh gi bi ging v a ra nhng gi hoc li khuyn hp l nhm nng cao cht lng ca bi ging phc v cho cng tc bin son bi ging cho cc trng i hc v trung hc ph thng hin nay. Vi phng php nh gi truyn thng bi ging, kt qu chuyn gia thng c cng trung bnh hoc s dng phng php thng k. y l nhc im ca c phng php nh gi truyn thng v ngi ra quyt nh khng phn bit c r mc nh hng tch cc ca cc chuyn gia khi tham gia nh gi bi ging. Mt khc cc tiu ch nh gi bi ging theo phng php nh gi truyn thng thng thng c cc im nh gi hoc trng s c coi l bng nhau. Nghin cu xut m hnh TOPSIS-AHP a ra cc nh bi ging da vo cc yu tt nh gi tch cc hoc khng tch cc ca cc chuyn gia. B tiu ch nh gi bi ging - ICT Newhouse c xp theo cu trc ca AHP gip cho ngi ra quyt nh nh gi bi ging c s cn nhc so snh da theo cc trng s

ca tng tiu ch nh gi bi ging ra quyt nh ng n hn.

i vi cc nghin cu nc ngoi, nhm cc tc gi Edward L. [2] v nhm tc gi Nadzeya Kalbaska [5] a ra cc lun im nhn xt, nh gi cc bi ging trong o to trc tuyn. Tuy nhin cc nghin cu ny ch ra cc c im, ni dung tng quan trong qu trnh nh gi, nhn xt bi ging trc tuyn. Trong nm 2013, nhm cc tc gi Elaine v Yasira [3, 4] nu cc tiu ch v c im thit k, xy dng bi ging trc tuyn. Cc nghin cu ny gip cho hc liu v thit k bi ging hng tip cn E-learning. Trong nghin cu gn y, Tin s Paul Newhouse [1] - Trng i hc Ty c ch ra c mi quan h v nhng tc ng ca cng ngh thng tin (B tiu ch ICT Newhouse) n cng tc ging dy trong cc trng hc nc c. Theo quan im ca ng, vic nh gi v phn loi nhng tc ng tch cc ca ICT n hc tp v ci thin kt qu hc tp ca sinh vin. Da vo b tiu ch ny, chng ti xy dng m hnh nghin cu tch hp cc k thut ca tr gip quyt nh nh gi bi ging, nng cao cht lng bi ging trc tuyn trong cc trng i hc, trung hc chuyn nghip v ph thng trung hc. Tc gi c nhng kt qu nghin cu s dng cc k thut tch hp ra quyt nh v AHP (Analytic Hierachy Process) [15,17] gii quyt cc vn khng c cu trc. Kh nng tch hp cc k thut trong m hnh nh gi bi ging l hng gii quyt mi hin nay.

Bi bo ny a ra mt m hnh s dng cc thut ton TOPSIS v AHP da trn b tiu ch ICT Newhouse kt hp cc tri thc t chuyn gia a ra quy trnh nh gi bi ging kt hp vi vic s dng tri thc ca cc chuyn gia. nh gi m hnh trn, chng ti p dng m hnh thng qua v d v ci t

P.V. Hi, N.T.M. Lc / Tp ch Khoa hc HQGHN: Nghin cu Gio dc, Tp 31, S 1 (2015) 13-27 15

chng trnh nh gi bi ging trc tuyn. M hnh xut c ci t th nghim v thng k cc kt qu ca chuyn gia nh gi. Kt qu thc nghim cho thy m hnh xut nh gi bi ging vi nh gi ng th hin cc tc ng a chiu nh hng tch cc ca chuyn gia trong m hnh nh gi bi ging.

Cu trc bi bo gm 6 phn nh sau: Phn 2 gii thiu b tiu ch ICT Newhouse cho nh gi bi ging trc tuyn. xut m hnh tch hp TOPSIS-AHP c a ra trong phn 3. V d da vo m hnh xut c trnh by vo phn 4. Phn 5 trnh by mt s kt qu thc nghim vi mt s b d liu m phng minh ha cho m hnh. Kt lun v nh hng pht trin c tho lun phn 6.

2. B tiu ch ICT Newhouse vi cc k thut TOPSIS v AHP nh gi bi ging trc tuyn

Tin s Paul Newhouse [1] - Trng i hc Ty c ch ra c mi quan h v nhng tc ng ca cng ngh thng tin (B tiu ch ICT Newhouse) n cng tc ging dy trong cc trng hc nc c. Theo quan im ca ng, vic nh gi v phn loi nhng tc ng tch cc ca ICT n hc tp thng qua cc bi ging trc tuyn ci thin kt qu hc tp ca sinh vin. Theo ng, c chn tc ng tch cc m ICT mang n nhng ci thin r rt trong phng php hc tp ca sinh vin, l:

1. Kh nng kho st thc t v xy dng kin thc

2. Thc y hc tp tch cc v nh gi xc thc

3. Thu ht sinh vin bi cc ng lc v thch thc

4. Cung cp cc cng c tng nng sut hc 5. Cung cp cng c h tr t duy cao 6. Tng tnh c lp ca ngi hc 7. Tng cng s hp tc v cng tc 8. Thit k chng trnh hc cho ngi hc 9. Khc phc khuyt im th cht Vi cc tc ng ICT Newhouse ny, chng

ti la chn mt s cc tiu ch kt hp vi cc k thut tr gip quyt nh v suy din da vo c s tri thc nh gi nhng tc ng ca bi ging thng qua nhng thut ton: 1) To quyt nh nhm, chn la nhng nh gi tt nht t cc chuyn gia; 2) nh gi bi ging bi mt lot cc tc ng ICT. Mc tiu chung ca cc nh qun l gio dc nng cao cht lng bi ging, bo co a ra nhng phng php nh gi bi ging, t a ra nhng t vn, gi gip nng cao cht lng ca bi ging phc v tt hn trong cng tc ging dy trong trng i hc v trung hc ph thng.

H h tr ra quyt nh - Decision Support Systems (DSS) l mt h thng h tr bng my tnh c th thch nghi, linh hot v tng tc ln nhau, c bit c pht trin h tr gii quyt mt vn qun l khng c cu trc nhm ci tin vic ra quyt nh ng n. [6,8] Nghin cu ny a ra cc phng php nh gi bi ging da trn b tiu ch ICT New house. Hng tip cn nghin cu ny bao gm cc bc:

1. Tch hp cc thut ton TOPSIS v AHP kt hp cc kin tham kho t chuyn gia xy dng mt m hnh nh gi chung cho bi ton [11-13].

2. Vn dng cc k thut tr gip quyt nh trong nh gi v t vn bi ging.

Bng 1 so snh vic nh gi cht lng bi ging bng phng php truyn thng vi s dng cng ngh thng tin:


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Bng 1. So snh gia phng php nh gi truyn thng vi phng php s dng CNTT

So snh Phng php truyn thng S dng CNTT Cch thc nh gi

nh gi trc tip da vo ch quan ca con ngi Cho im, ly kt qu trung bnh ca hi ng nh gi

Da trn cc tp lut, s kin v d liu thng k Da trn cc thut ton tnh ton, ra quyt nh c cu trc.

u im D dng thc hin theo phng php truyn thng

Cho kt qu u ra l mt vi tp d liu u vo ln, phc tp Gii quyt c so snh cc tiu ch vi cc trng s khc nhau C m hnh nh gi do cc chuyn gia tip cn ph hp, nhanh thc hin trn mng hoc cng c phn mm

Nhc im nh hng bi tm l v tnh ch quan ca ngi tham gia nh gi Cc trng s tiu ch nh gi l nh nhau Cc kt qu nh gi, thng k da vo tnh trung bnh cho nn vic xem tiu ch no mnh v chuyn gia ph hp khng thc hin c

Cn phi xy dng cc chng trnh phn mm v cng c nh gi trn mng

3. M hnh TOPSIS-AHP s dng b tiu ch ICT Newhouse nh gi bi ging M hnh TOPSIS-AHP s dng b tiu ch ICT Newhouse nh gi bi ging nh Hnh 1:

Hnh 1. M hnh TOPSIS-AHP s dng nh gi bi ging trc tuyn.

D liu u vo (Bi ging) (1)

B tin x l

B nh gi

B ghi nhn s liu t

chuyn gia (3)

B tnh ton

(TOPSIS) (4)

B chuyn i mc quan trng

(5)

B nh gi i tng

(AHP) (6)

C s d liu (2)

D liu u ra (Kt qu nh gi)

(7)


M t cc bc trong m hnh xut nh sau:

Bc 1: Xem v hin th bi ging trc tuyn h thng. Bi ging trc tuyn l tp ti liu dng vn bn word, Excel, text, pdf, multimedia, pptv.v, bin son bi cc ging vin/ gio vin

Bc 2: Thu thp nhng nh gi ca chuyn gia v i tng (Bi ging), nhng nh gi v mc hn km nhau gia cc tc ng ICT n bi ging.

Bc 3: Tin x l d liu nhm ly ra nhng nh gi thch hp t cc chuyn gia. S dng gii thut TOPSIS tm ra mt nh gi ti u nht t danh sch cc chuyn gia tham gia nh gi bi ging.

Bc 4: Chuyn i thnh cc mc quan trng t b s liu nh gi thu c ca chuyn gia c chn

Bc 5: p dng thut ton AHP a ra mc no l ph hp nht vi bi ging ang xem xt (mc nh gi bi ging)

Trong : 1. D liu u vo: bao gm bi ging

Online hoc Offline cn c nh gi. 2. C s tri thc: thu thp cc tri thc

chuyn gia, ging vin c kinh nghim. 3. B ghi nhn s liu t chuyn gia: Nhn

cc s liu l cc gi tr nhp vo - tng ng vi tng tiu ch trong c s d liu t cc chuyn gia.

4. B tnh ton bng TOPSIS: Gii thut tnh ton bng TOPSIS a ra th t sp xp v nh gi cc s liu nhp vo ca cc chuyn gia

5. B chuyn i mc quan trng: Tnh ton v chuyn i s liu t c ch nhn s liu t chuyn gia thnh cc mc quan trng tng ng.

6. Thut ton nh gi i tng (bi ging) AHP: S dng thut ton AHP nh gi bi ging

7. D liu u ra: l mt nh gi ph hp nht cho bi ging

Chuyn gia khi tham gia nh gi mt bi ging l nhng ngi c kinh nghim v ging dy. thu thp c cc s liu nh gi t cc chuyn gia trong khi tham gia nh gi bi ging, ngi ra quyt nh da vo 9 tiu ch ICT Newhouse cp trn chn cc tiu chun nh gi. Cc chuyn gia s xem xt tng tiu ch v a ra nhng nh gi c nhn ca mnh i vi tng tiu ch. Mi tiu ch tham gia nh gi s nhn mt gi tr bng s (Thang im 9).

4. V d minh ha m phng m hnh TOPSIS-AHP nh gi bi ging

Cc bc sau y m t qu trnh x l m hnh xut nh gi bi ging:

Bc 1: Xc nh cc d liu u vo v d liu bi ging cn nh gi

u vo: Bi ging mn hc cn nh gi. Cc tiu ch trong b 9 tiu ch tc ng ICT Newhouse trong Bng 2.a s dng nh gi bi ging.

Bc 2: Thu thp kin nh gi t cc chuyn gia.

Trng hp c 1 chuyn gia tham gia nh gi bi ging th b s liu nh gi ca chuyn gia s ng thi l b s liu chun (B qua bc tin x l d liu).

Trng hp c t 2 chuyn gia tr ln, ta s tin hnh thm 1 bc tin x l d liu ly c mt b s liu nh gi tt nht. Gi s y ta c 5 chuyn gia l A1, A2, A3, A4, A5 v cc 9 tiu ch tc ng ICT l X1, X2, X3 X9.


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im s nh gi c cho theo thang im 9. Tc l: ng vi mi tiu ch tc ng ICT, mc hn (km) cng cao v tc ng, im s c chm cho tiu ch cng gn n 9.

V d: Chuyn gia A1 sau khi xem xt bi ging trn nh gi im s nh sau: A1 (6/5/5/4/3/5/4/3/2) tc l:

Mc tc ng tiu ch 1: Kh nng kho st thc t v xy dng kin thc l 6

Mc tc ng tiu ch 2: Thc y hc tp tch cc v nh gi xc thc l 5

.

Mc tc ng tiu ch 9: Khc phc khuyt im th cht l 2

Cc kin t cc chuyn gia c thu thp bng s liu m t Bng 2.b nh sau:

Bng 2.a. B 9 tiu ch ICT Newhouse

K hiu ngha X1 Kh nng kho st thc t v xy dng kin thc X2 Thc y hc tp tch cc v nh gi xc thc X3 Thu ht sinh vin bi cc ng lc v thch thc X4 Cung cp cc cng c tng nng sut hc X5 Cung cp cng c h tr t duy cao X6 Tng tnh c lp ca ngi hc X7 Tng cng s hp tc v cng tc X8 Thit k chng trnh hc cho ngi hc. X9 Khc phc khuyt im th cht

Bng 2.b. B s liu thu thp t cc chuyn gia nh gi mc hn (km) gia cc tc ng ICT

X1 X2 X3 X4 X5 X6 X7 X8 X9 A1 6 5 5 4 3 5 4 3 2 A2 5 6 5 5 3 4 4 3 3 A3 4 5 4 4 3 4 5 3 2 A4 6 4 6 5 4 3 3 4 3 A5 5 5 4 4 5 3 3 4 3 Trng s 0.2 0.2 0.2 0.1 0.1 0.05 0.05 0.05 0.05

g B trng s trn, c cc chuyn gia

phn tch a ra, h s quyt nh xem trong s 9 tc ng ca ICT - th tc ng no c nh hng mnh m nht n vic hc tp ca sinh vin. Tng gi tr trng s cho 9 tiu ch tc ng ICT bng 1.

Bc 3: X l d liu thu c t bng trn bng phng php TOPSIS

1. Chun ha cc gi tr (Bng 3) 2. Tnh gi tr theo trng s (Bng 4) 3. Cc gii php l tng:

= (0.0087, 0.0094, 0.0102, 0.0051, 0.0073, 0.0033, 0.0033, 0.0034, 0.0043)

= (0.0058, 0.0063, 0.0068, 0.0041, 0.0044, 0.0020, 0.0020, 0.0025, 0.0029)

4. Tnh khong cch n cc gii php l tng = (0.0042, 0.0039, 0.0059, 0.0039, 0.0045) = (0.0040, 0.0043, 0.0022, 0.0051, 0,0040)

5. o tng t n gii php l tng = (0.4878, 0.5244, 0.2716, 0.5667, 0.4706)


Bng 3. Chun ha cc gi tr s dng TOPSIS

X1 X2 X3 X4 X5 X6 X7 X8 X9 A1 0.0435 0.0394 0.0424 0.0408 0.0441 0.0667 0.0533 0.0508 0.0571 A2 0.0362 0.0472 0.0424 0.0510 0.0441 0.0533 0.0533 0.0508 0.0857 A3 0.0290 0.0394 0.0339 0.0408 0.0441 0.0533 0.0667 0.0508 0.0571 A4 0.0435 0.0315 0.0508 0.0510 0.0588 0.0400 0.0400 0.0678 0.0857 A5 0.0362 0.0394 0.0339 0.0408 0.0735 0.0400 0.0400 0.0678 0.0857 Trng s 0.2 0.2 0.2 0.1 0.1 0.05 0.05 0.05 0.05

Bng 4. Gi tr ca cc tiu ch ICT c tnh theo trng s

X1 X2 X3 X4 X5 X6 X7 X8 X9 A1 0.0087 0.0079 0.0085 0.0041 0.0044 0.0033 0.0027 0.0025 0.0029 A2 0.0072 0.0094 0.0085 0.0051 0.0044 0.0027 0.0027 0.0025 0.0043 A3 0.0058 0.0079 0.0068 0.0041 0.0044 0.0027 0.0033 0.0025 0.0029 A4 0.0087 0.0063 0.0102 0.0051 0.0059 0.0020 0.0020 0.0034 0.0043 A5 0.0072 0.0079 0.0068 0.0041 0.0073 0.0020 0.0020 0.0034 0.0043 Trng s 0.2 0.2 0.2 0.1 0.1 0.05 0.05 0.05 0.05

f

Theo kt qu trn th mc nh gi tch cc (t tt nht n km nht) ca cc chuyn gia s l A4 > A2 > A1 > A5 > A3 (0.5567 > 0.5244 > 0.4878 > 0.4706 > 0.2716)

D thy, nu ly kt qu nh gi ca chuyn gia A4 s cho ta mt nh gi tch cc nht. Nhng khng phi lc no tch cc nht cng l tt nht. bi ton hp l v ph hp vi a s nh gi t cc chuyn gia, ta s chn

nh gi ca chuyn gia A1 (nh gi nh hng ca 9 tiu ch tc ng ICT mc va phi).

Bc 4: Thit lp cc ma trn nh hng a/Thit lp ma trn nh hng gia cc yu

t vi nhau T s liu thu c ca chuyn gia A1 ta c

nh sau:

Bng 5. B s liu nh gi tc ng ICT ca chuyn gia A1

X1 X2 X3 X4 X5 X6 X7 X8 X9 A1 6 5 5 4 3 5 4 3 2

Chuyn thnh m trn so snh gia cc tiu ch (tc ng ICT) nh sau:

Bng 6. Ma trn so snh gia cc tiu ch ICT

X1 X2 X3 X4 X5 X6 X7 X8 X9 X1 1 1 1 2 2 1 2 2 3 X2 1 1 1 1 2 1 1 2 3 X3 1 1 1 1 2 1 1 2 3 X4 1/2 1 1 1 1 1 1 1 2 X5 1/2 1/2 1/2 1 1 1/2 1 2 3 X6 1 1 1 1 2 1 1 2 3 X7 1/2 1 1 1 1 1 1 1 2 X8 1/2 1/2 1/2 1 1/2 1/2 1 1 1 X9 1/3 1/3 1/3 1/2 1/3 1/3 1/2 1 1

g


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Cng thc chuyn i mc quan trng t s liu nh gi

aij = vi si, sj l im s nh gi ca tiu

ch Xi, Xj Vi gi tr ca ma trn c tnh nh sau:

Bng 7. V d v cch i mc quan trng t b s liu nh gi

X1 X2 X3 X4 X5 X1 1 1 1 2 2 X2 1 1 1 1 2 X3 1 1 1 1 2 X4 1/2 1 1 1 1 X5 1/2 1/2 1/2 1 1

Gi tr hng X3 ct X4 s l thng s ca X3/X4 = 5/4 = 1,25 ~ 1.

(Theo gii thut AHP do Satty [9] xut, mc so snh quan trng ca tng tiu ch l mt s nguyn - hoc nghch o ca mt s nguyn nn cc gi tr c lm trn)

b/Thit lp ma trn nh hng gia cc la chn mc nh gi vi tng tiu ch:

Mc nh gi bao gm c 5 mc: Bng 8. Mc nh gi cht lng bi ging

Mc nh gi K hiu ngha Rt tt M1 nh gi cht lng cao nht

Tt M2 nh gi cht lng cao

Kh tt M3 nh gi bi ging kh

Bnh thng M4 nh gi bi ging chp nhn c

Km M5 nh gi bi ging ny cha c

So snh ma trn gia cc kt qu nh gi i vi tng yu t ICT (tng cng ta phi thit lp cc ma trn ng vi 9 tiu ch ICT)

Vi tiu ch th nht (X1), chuyn gia nh gi s cho im quan trng nh sau:

Rt tt: 7 Tt: 5 Kh tt: 3 Bnh thng : 2 Km: 1 p dng cng thc chuyn i quan

trng, ta c ma trn sau:

Bng 9. Ma trn so snh gia cc mc nh gi i vi Tiu ch X1

Tiu ch X1 M1 M2 M3 M4 M5 M1 1 1 1 3 7 M2 1 1 2 3 5

M3 1 1/2 1 2 3 M4 1/3 1/3 1/2 1 2 M5 1/7 1/5 1/3 1/2 1

m bo vi mi tiu ch khc nhau, cc ma trn so snh a ra kt qu thit lp quan trng vi 8 tiu ch cn li. Cc ma trn kt qu trnh by di bng nh sau:

Bc 5: S dng thut ton AHP gii quyt bi ton

p dng cng thc tnh vector ring (9) ta i tm cc vector ring ng vi 10 ma trn va c thit lp.

Vector ring ca ma trn so snh gia cc tiu ch (tc ng ICT)

w (0.1613, 0.1382, 0.1382, 0.1049, 0.0941, 0.1382, 0.1049, 0.0714, 0.0488)

Vector ring ca cc ma trn so snh gia cc la chn (mc nh gi) tng ng vi 9 tc ng ICT (Bng 11).

Vector u tin W = [w][w1 w2 w3 w9] = (0.252, 0.258, 0.239, 0.160, 0.091). Tc l kh nng bi ging c nh gi mc rt tt l 25%, mc tt l 26%, mc kh tt l 24%, mc bnh thng l 16%, mc km l 9%. Nh vy ta c th nh gi c bi ging ny mc tt.


Bng 10. Ma trn so snh gia cc mc nh gi i vi cc tiu ch Xi

Tiu ch tc ng ICT Ma trn X1 Kh nng kho st thc t v xy dng kin thc

X1 M1 M2 M3 M4 M5 M1 1 1 1 3 7 M2 1 1 2 3 5 M3 1 1/2 1 2 3 M4 1/3 1/3 1/2 1 2 M5 1/7 1/5 1/3 1/2 1

X2 Thc y hc tp tch cc v nh gi xc thc

X2 M1 M2 M3 M4 M5 M1 1 1 2 3 5 M2 1 1 2 2 3 M3 1/2 1/2 1 2 3 M4 1/3 1/2 1/2 1 2 M5 1/5 1/3 1/3 1/2 1

X3 Thu ht sinh vin bi cc ng lc v thch thc

X3 M1 M2 M3 M4 M5 M1 1 1 1 3 5 M2 1 1 1 3 3 M3 1 1 1 3 5 M4 1/3 1/3 1/3 1 1 M5 1/5 1/3 1/5 1 1

X4 Cung cp cc cng c tng nng sut hc

X4 M1 M2 M3 M4 M5 M1 1 1 1 1 2 M2 1 1 1 1 2 M3 1 1 1 2 2 M4 1 1 1/2 1 1 M5 1/2 1/2 1/2 1 1

X5 Cung cp cng c h tr t duy cao

X5 M1 M2 M3 M4 M5 M1 1 1 1/2 1 2 M2 1 1 1 1 3 M3 2 1 1 1 3 M4 1 1 1 1 2 M5 1/2 1/3 1/3 1/2 1

X6 Tng tnh c lp ca ngi hc

X6 M1 M2 M3 M4 M5 M1 1 1 1 1 2 M2 1 1 1 1 2 M3 1 1 1 2 2 M4 1 1 1/2 1 1 M5 1/2 1/2 1/2 1 1

X7 Tng cng s hp tc v cng tc

X7 M1 M2 M3 M4 M5 M1 1 1 1/2 1/2 1 M2 1 1 1 1 2 M3 2 1 1 1 2 M4 2 1 1 1 3 M5 1 1/2 1/2 1/3 1


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X8 Thit k chng trnh hc cho ngi hc

X8 M1 M2 M3 M4 M5 M1 1 1 1 1 2 M2 1 1 1 1 3 M3 1 1 1 1 3 M4 1 1 1 1 3 M5 1/2 1/3 1/3 1/3 1

X9 Khc phc khuyt im th cht

X9 M1 M2 M3 M4 M5 M1 1 1 2 2 3 M2 1 1 2 3 3 M3 1/2 1/2 1 2 3 M4 1/2 1/3 1/2 1 1 M5 1/3 1/3 1/3 1 1

Bng 11. Gi tr vector ring ng vi cc ma trn so snh khi nh gi

w1 0.3041, 0.3266, 0.2060, 0.1066, 0.0568 w2 0.3399, 0.2830, 0.1867, 0.1203, 0.0700 w3 0.2899, 0.2618, 0.2899, 0.0873, 0.0711 w4 0.2232, 0.2232, 0.2563, 0.1691, 0.1282 w5 0.1882, 0.2344, 0.2693, 0.2162, 0.0919 w6 0.2232, 0.2232, 0.2563, 0.1691, 0.1282 w7 0.1439, 0.2182, 0.2506, 0.2718, 0.1155 w8 0.2152, 0.2334, 0.2334, 0.2334, 0.0844 w9 0.2916, 0.3163, 0.1924, 0.1079, 0.0918

f

5. Kt qu thc nghm

5.1. Thc nghim

Chng trnh thc nghim vi m hnh th nghim nh gi bi ging gia cc ging vin, sinh vin S phm K thut, Cng ngh Thng tin Trng i hc Bch khoa H Ni t thng 6 nm 2013 n thng 6 nm 2014. Trong qu trnh nh gi bi ging, chuyn gia/ging vin la chn cc hc phn - bi ging bao gm text, html, pdf, ppt,v.v. Hnh 2 m t cc bc trong thc nghim nh gi bi ging.

H thng phn tch v tnh ton, a ra xp hng (hoc nh gi) v cc s liu thu thp c, nhm tm ra chuyn gia c mc nh gi tch cc c ch s nh gi

tt nht. Hnh 4 m t trng s nh gi tch cc ca chuyn gia 2.

i vi nh gi a chiu theo mc tch cc hoc tiu cc ca cc chuyn gia, ngi chuyn gia c b ch s nh gi tt nht c th c la chn nh sau:

Chuyn gia c nh gi tch cc nht (b s liu cao nht)

Chuyn gia c nh gi mc trung bnh (gi tr trung bnh ca xp hng)

Ngi ra quyt nh c th la chn kt qu ca chuyn gia c nh hng nh gi tch cc hoc trung bnh tip tc nh gi bi ging theo gii thut AHP m t kt qu nh Hnh 5.

d


Hnh 2. Giao din chn bi ging nh gi.

Hnh 3 m t 06 chuyn gia tham gia vo h thng nh gi bi ging

Hnh 3. nh gi bi ging s dng m hnh TOPSIS.


24

Hnh 4. Giao din xp hng chuyn gia theo TOPSIS.

Hnh 5. Giao din hin th kt qu nh gi bi ging.

5.2. Kt qu v tho lun

Trong qu trnh thc nghim vi m hnh xut trn, nm chuyn gia l ging vin, gio vin tham gia nh gi bi ging trc tuyn trn mng vo thng 4 nm 2014 ti Trng i hc Bch khoa H Ni. Kt qu m hnh TOPSIS-AHP nh gi bi ging biu din theo Hnh 6.

Kt qu m phng ca m hnh TOPSIS-AHP xut nh gi bi ging cho 4 hc phn mn hc trin khai ti Trng i hc Bch khoa H Ni ch ra cc tc ng tch cc hoc khng tch cc ca tng chuyn gia da trn b tiu ch ICT Newhouse. Hnh 4 cho thy chuyn gia 3 c mc nh hng tch cc n cc hc phn h tr gip quyt nh v phn tch-thit k h thng thng tin. Trong khi , chuyn gia 3 phn nh cch nh gi khng tch

cc ca cc hc phn mn hc: H c s tri thc, h tr gip quyt nh v phn tch v TKHTTT. ng thi, chuyn gia 2 i vi nh hng khng tch cc i vi hc phn h c s tri thc v chuyn gia 4 i vi hc phn tr tu nhn to. Kt qu nh gi gip ngi ra quyt nh la chn chuyn gia c cch nh gi tch cc thc hin m un nh gi AHP a ra bi ging nh gi cc cp : tt, kh, trung bnh, khng t.

So snh vi cch nh gi truyn thng, kt qu nh gi s dng m hnh TOPSIS-AHP a ra cc nh gi tch cc hoc khng tch cc ca cc chuyn gia m theo cch nh gi truyn thng khng c. Mt khc, b tiu ch nh gi bi ging - ICT Newhouse c xp theo cu trc ca AHP gip cho ngi ra quyt nh nh gi bi ging c s cn nhc so snh


thng qua s dng cc trng s ca tng tiu ch nh gi bi ging c ng n hn. Vi cch nh gi ny, kt qu nghin cu a

ra m hnh nh gi kt hp vi nh gi truyn thng a ra cc khuyn co bi ging trc tuyn nng cao cht lng dy v hc.

Hnh 6. Kt qu nh gi ca cc chuyn gia vi 4 hc phn bi ging.

6. Kt lun Bi bo ny a ra mt m hnh TOPSIS-

AHP da trn b tiu ch ICT Newhouse kt hp cc tri thc t chuyn gia a ra quy trnh nh gi. Kt qu thc nghim cho thy m hnh xut nh gi bi ging vi nh gi ng th hin cc tc ng a chiu nh hng tch cc ca chuyn gia trong m hnh nh gi bi ging. Phng php nh gi ny kt hp vi nh gi truyn thng s a ra nh gi ng n cho cc bi ging trc tuyn - ngun hc liu m cho h E-learning hin nay.

M rng m hnh nghin cu ny, chng ti tip tc m rng m hnh TOPSIS-AHP kt hp vi suy din t ng v bn t ng t vn cho cc ging vin, gio vin chun b ni dung bi ging tt nht cho phng thc o to truyn thng v o to trc tuyn. C s tri thc s xy dng lu tr cc tri thc chuyn gia nhm gim thiu cc chi ph dch v v nng cao cht lng t vn cho ging dy v hc tp.

Li cm n

Cng trnh nghin cu c h tr ti chnh t ti m s: QGT.13.15 ca HQGHN. Nhm tc gi trn trng cm n chuyn gia phn bin, Ban bin tp c cc ng gp nng cao cht lng bi bo ny. ng thi, nhm tc gi xin cm n cc ging vin, gio vin v sinh vin Trng i hc Bch khoa H Ni, Trng i hc Gio dc, i hc Quc gia H Ni tham gia ly s liu, thc nghim cho chng trnh th nghim - nghin cu ny.

Ti liu tham kho

[1] Paul Newhouse, A Framework to Articulate the Impact of ICT on Learning in Schools - Western Australian Department of Education - December, 2002.

[2] Edward L Meyen, Ronald J Aust, Yvonne N Bui, Eugene Ramp, Sean J Smith, The Online Academy formative evaluation approach to


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evaluating online instruction, The Internet and Higher Education, Vol.5, No. 2 (2012) 89.

[3] Elaine Huber, Marina Harvey, Time to participate: Lessons from the literature for learning and teaching project evaluation in higher education, Studies in Educational Evaluation, December, Vol. 39, No. 4 (2013) 240.

[4] Yasira Waqar, The Impact of Learning Design on Student Learning in Technology Integrated Lessons, Article Procedia - Social and Behavioral Sciences, October, Vol. 93, No. 21 (2013) 1795.

[5] Nadzeya Kalbaska, Hee Andy Lee, Lorenzo Cantoni, Rob Law, UK travel agents evaluation of eLearning courses offered by destinations : An exploratory study, Article Journal of Hospitality, Leisure, Sport & Tourism Education, April, Vol. 12, No. 1 (April 2013) 7.

[6] S.L Alter, Decision Support System: Current Practices and Continuing Challenges, Reading, MA: Addison-Wesley, 1980.

[7] Bruce L. Golden, Edward A.Wasil, Patrick T.Harker (Eds.). The Analytic Hierarchy Process: Applications and Studies, Springer - Verlad Berlin . Heidelberg, 1989.

[8] E.Turban, E.A Jay, T.P. Liang, Decision Support Systems and Intelligent Systems, Decision Support Systems: An overview, 2007.

[9] T.L Saaty, The Analytic Hierarchy Process, Mc. Graw. Hill. New Jork, 1980.

[10] Saul L.Gass Decision Making Model Algorithms, John Wiley & Son, Inc. ISBN 0- 471-80963-2, 1985.

[11] Thomas L. Saaty, Decision making with the analytic hierarchy process, University of Pittsburgh, Pittsburgh, PA 15260, USA Int. J. Services Sciences, Vol. 1, No. 1 (2008) 8398.

[12] Alberto Vega, Juan Aguarn, Jorge Garca-Alcaraz, Jos Mara Moreno-Jimnez, Notes on Dependent Attributes in TOPSIS, Procedia Computer Science, Vol. 31 (2014) 308.

[13] Ibrahim A. Baky, Interactive TOPSIS algorithms for solving multi-level non-linear multi-objective decision-making problems, Applied Mathematical Modelling, Vol. 38, No. 4 (2014) 1417.

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[17] Hai Van. Pham, Khang D. Tran, Katsuari Kamei, Application s using Hybrid Decision Support Systems for selection of alternatives under uncertainty and risk, International Journal of Innovative Computing, Information and Control, Feb, Vol. 10, No. 1 (2014) 39.

[18] Mohammed F. Alya, Hazem A. Attiab Ayman M. Mohammed, Prioritizing Faculty of Engineering Education Performance by Using AHP-TOPSIS and Balanced Scorecard Approach. International Journal of Engineering Science and Innovative Technology (IJESIT), January, Volume 3, Issue 1 (2014) 11.

[19] Dipendra Nath Ghosh, Analytic Hierarchy Process and TOPSIS Method to Evaluate Faculty Performance in Engineering Education, UNIASCIT, Vol 1 (2) (2011) 63.

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Using ICT Newhouse Factors based TOPSIS-AHP Model to Evaluation Lectures with Intelligent Decision Supports

Phm Vn Hi1, Nguyn Th M Lc2 1School of Information Technology and Communication, Hanoi University of Science and Technology

2University of Education, Vietnam National University Hanoi

Abstract: In recent years, with the rapid development of science and technology combined with conventional training, E-learning has been recently become common. In research and teaching, evaluation lectures and online lectures based on the conventional evaluation method have some limitations in indentifion of factors weights. Based on the conventional evaluation, all statistic data collected from experts and calculated in an average are limited. This study aims to offer integrated decision support system (DSS) techniques in order to evaluate online lectures using a goup of experts. The propsed model uses an integatted DSS including TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) v AHP (Analytic Hierachy Process) based on ICT Newhouse factors, combined with knowledge-based experts to figure out a procedure of online lectures evaluation. To confirm the proposed model, we demonstrated an example and implemented experiments for the proposed model. Experimental results show that the propsed model has a variety of positive impact of experts participated in the evaluation. To evaluate lectures by using the proposed model, it is neccessary to make right decisions in multicriterial factors and for multipel purposes.

Keywords: TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), AHP (Analytic Hierachy Process), lecture evaluation, Decision Support Systems.

AHP - Danh Gai Bai Giang

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