The Effecs of Simulaion-based Learning on Engineering Workshop Pracice Linda FANG, Mya Mya THWIN, Mariner KWOK, Hock Soon TAN, Kim Cheng TAN, Temasek Engineering School, Temasek Polyechnic, 21 Tampines 1, Singapore 529757, Republic of Singapore and Caroline KOH, Psychological Sudies Deparmen, Naional Insiue of Educaion, Nanyang Technological Universiy, 1 Nanyang Walk, Singapore 637616, Republic of Singapore ABSTRACT This qualiaive sudy on he effecs of Simulaion-based learning () on Machining Technology workshop pracice involved wo workshop groups ha had infused ino heir curriculum and wo workshop groups ha received normal insrucion. The research quesion was How did help o prepare paricipans for workshop pracice? The sub-quesions were as follows: i. Were he workshop groups more familiar wih he workshop asks? ii. Were hey more responsive o heir insrucor s quesions? iii. Were hey able o work more independenly? iv. Were hey able o work faser? v. Were hey easier o each? Each workshop group was observed hrice. In addiion o he daa colleced using he Pracice Observaion Toolki for Groups, here were observaion noes and saff inerviews. Personal daa of 16 and 18 non- paricipans, usage of modules and wrien commens from he paricipans were also colleced. While he paricipans seemed more prepared for workshop pracice, were able o visualize machine pars, worked faser and were easier o each, he posiive effecs of varied from srong o marginal. Keywords: Posiive effecs of Simulaion-based learning, ransfer of learning, Engineering workshop pracice INTRODUCTION Educaional simulaions provide a variey of selecively ineracive, selecively represenaional environmens ha can provide highly effecive learning experiences [1, p. 270]. Compuer simulaions can help sudens undersand and visualize heoreical problems, allowing hem o pracice, be assessed and measured for undersanding of he heory and applicaion [2]. Effecive learning requires ransfer, where curren learning is applied or adaped o similar or novel siuaions [3]. I is assumed ha when learners are able o perform a ask in a simulaed environmen, hey would evenually assimilae he necessary skills and conceps over ime [4]. Simulaion-based e-learning is supposed o help learners move seamlessly from learning-by-doing o improved real job performance [5]. However, here could be a gap beween he simulaor and operaional performance [6] or he real-world performance canno be fully refleced [7]. There have been sudies on he ransfer performance of differen arge groups in a simulaion of a chemical plan [8], he ransfer of spaial knowledge in virual environmen raining [9], he applicaion of knowledge in flexible siuaions [10], and he performance of medical sudens in pracical ess [11]. However, here are no sudies ha look a ransfer in Machining Technology workshop pracice. Temasek Engineering School explored he use of in he 2008 for Machining Technology, a subjec aken by year wo semeser one Mecharonics sudens. During he Ocober 2008 semeser, hree ou of five classes in he cohor had infused in heir curriculum. I was hoped ha could suppor learning in he classroom and prepare sudens for workshop pracice. See Figure 1 for he concepual framework. Faciliaes learning Classroom Insrucion Machining Technology Infusion of Figure 1. Concepual Framework for he Infusion of The research quesion was How did help o prepare paricipans for workshop pracice? The sub-quesions were as follows: i. Were he workshop groups more familiar wih he workshop asks? ii. Were hey more responsive o heir insrucor s quesions? iii. Were hey able o work more independenly? iv. Were hey able o work faser? v. Were hey easier o each? This sudy was par of a larger sudy on he effeciveness of for Machining Technology. I was designed o complemen he sudy on he effecs of during workshop pracice a he individual level. LITERATURE REVIEW Prepares sudens for workshop pracice Workshop Pracice Compuer-based echnical raining can be designed o each facs, conceps, processes and procedures and principles o faciliae memory and applicaion of lessons [12]. The virual environmen has much poenial for learning [13] and raining [14]. Virual producs and virual laboraories have been used exensively in he eaching of Engineering [15-19]. Virual producs can be offered on a sand alone basis or embedded in virual laboraories. While virual producs allow users be
familiar wih new producs when hey inerac wih visual, selecively accurae represenaions of acual producs wihou he physical resricions of realiy [1, p. 5], virual laboraories presen siuaions where producs are acually used, however a he expense of fideliy [1]. The effeciveness of has been evaluaed in differen way, for insance, by comparing effec size of experimenal and conrol groups [20], relaing ime spen on o he achievemen of sandardized learning oucomes [21], conrasing pre-es and pos-es scores [10], comparing iniial and final assessmen checklis scores [11], and evaluaing performance in se asks [9]. Transfer of learning has muliple definiions and inerpreaions. According o Eddy and Tannenbaum [22, p. 164] cogniive psychologiss consider ransfer as he applicaion of learning from a learned ask o a differen ask while insrucional designers consider i as he applicaion of learning in siuaions differen from where learning ook place. Leberman, McDonald and Doyle [23] aribue he differences o he learning approaches, wheher i is formal discipline, behavioral, cogniive and allied or conexual socio-culural approaches. Haskell [3] caegorized ransfer a six differen levels: simple learning i.e. non-specific and applicaion ransfer (levels one and wo); applicaion of learning i.e. conex ransfer (level hree); near ransfer (level four); and far ransfer i.e. far and creaive ransfer (levels five and six respecively). He also idenified 14 differen kinds of ransfer e.g. conen-o-conen ransfer, procedural-o-procedural ransfer, declaraive-o procedural ransfer, procedural-o-declaraive ransfer, sraegic ransfer, condiional ransfer, heoreical ransfer, general or nonspecific ransfer, lieral ransfer, verical ransfer, laeral ransfer, reverse ransfer, proporional ransfer and relaional ransfer. Transfer is considered posiive when learning in one conex improves learning or performance in anoher conex [23, p. 4]. Temasek Polyechnic s Sraegic and Qualiy Developmen Deparmen [24] learning oucomes for he cogniive domain are based on Bloom s Taxonomy [25], which are knowledge, comprehension, applicaion of conceps and principles o new siuaions, analysis and synhesis and evaluaion. For he psychomoor domain, learning oucomes are based on Simpson s classificaion [26], which are percepion, se, guided response, mechanism, complex over response, adapaion and originaion. Machining Technology sudens are expeced o demonsrae heir undersanding of he differen applicaions of he ypes of convenional machines, he machine parameers, and he differen work holding devices as well as operae hem [27]. A wrien pos-inervenion es had showed ha helped improve higher-order le arning, demonsraing ransfer in he cogniive domain [28, 29]. METHODOLOGY Machining Technology subjec was augh in a four hour blocks weekly. Two hours of classroom insrucion followed wo hours of workshop pracice, which were fully guided. The firs seven weeks were designed o help sudens use convenional machine and basic bench-fiing ooling for assembly work. The aciviies suppored wo individual projecs which were he fabricaion of a pen holder and a meal box. The former required urning, milling, drilling while he laer involved shearing, bending, drilling and bench work for shee meal. The lessons were designed as virual objecs and packaged as one projec and four eaching modules. The eaching modules, namely Turning, Shee Meal, Milling and Drilling offered differen levels of learning. Know he Machine provided an inroducion o he machine pars and funcions, and a shor MCQ online quiz o help sudens evaluae how much hey had learn. Explore he Machine provided a preview of how each machine works, while Work on he Machine provided guided pracice on a virual machine followed by a simulaion es which required sudens o repea he procedure wihou any guidance. The Projec Work module demonsraed he use of a combinaion of differen machines o suppor he wo projecs. was used in class. The Machining Technology uor inroduced he maerials hough he use of he Drilling module in week one. Sudens were allocaed 30 minues jus before heir workshop pracice and learn from he Turning, Shee Meal and Milling modules as each process was inroduced in weeks wo, four and six respecively. They were also encouraged o access he maerials ouside class ime. The sudy involved four randomly seleced workshop groups from wo and wo non- classes. There were sufficien similariies in group composiion for comparison beween he and non- workshop groups despie he variaion in naionaliies and educaional backgrounds. The workshop group size ranged from eigh o 10 paricipans. The raio of paricipans wih qualificaions from he Insiue of Technical Educaion (ITE) o hose wih General Cerificae of Educaion (GCE) O level qualificaions was similar for he and non- workshop groups. The mixed and non- workshop groups had he same number of s and inernaional sudens, and a similar raio of paricipans wih ITE o GCE O level qualificaions. Those wih ITE and GCE O level qualificaions were s, while hose wih inernaional qualificaions were inernaional sudens and one who compleed his GCE O levels a an inernaional school in Malaysia. See Table 1. Table 1: Deails of and non- Workshop Groups Enry Qualificaions Number Ave Ave Ave Age GPA Login 8 22.6 2.76 85.9 Workshop Gp - ITE 6 22.5 2.55 92.8 - GCE O 2 23.0 3.41 65.0 Mixed Workshop 8 19.4 3.16 103.5 Gp - ITE 3 19.8 2.75 74.0 - GCE O 3 19.7 3.20 105.7 - Inernaional 2 18.6 3.71 144.5 Boh Groups Workshop 16 21 2.96 94.7 Non- Workshop Gp 10 21.4 2.91 - ITE 7 22.0 2.81 - GCE O 2 21.0 2.84 - Inernaional 1 18.0 3.77 Non- Mixed 8 22.1 2.76 Workshop Gp - ITE 4 23.0 2.71
- GCE O 2 18.7 2.49 - Inernaional 2 23.8 3.13 Boh Non- Workshop Gps 18 21.7 2.84 Their echnical raining backgrounds prior o joining Temasek Polyechnic ranged widely. Those wih inernaional qualificaions had an academic background and none or hardly any echnical raining. Those wih GCE O level qualificaions had an academic background wih varying exposure o Design Technology. Those wih ITE Elecrical-IT qualificaions had pracice-based raining no relaed o Machining Technology. Those wih ITE Mechanical qualificaions had pracice-based raining relaed o machining echnology. See Char 1. No. of paricipans 10 8 6 4 2 0 Mixed Workshop groups Non- Char 1. Profile of workshop groups Non- Mixed Inernaional GCE "O" Elecrical - IT Mechanical As workshop pracice was fully guided, he workshop insrucor would demonsrae he use of he machines before allowing paricipans o work on individual machines. To ensure ha he mehod of insrucion was consisen, he wo insrucors were briefed on he insrucional maerials, key poins of he demonsraion, he ypes of quesions o ask and wha o observe during he session. Each group was observed for heir Turning, Shee Meal and Milling workshop pracice sessions in weeks wo, four and six respecively. All observaions sessions were video-aped. A he beginning of each session, he paricipans were reassured ha ha he daa recording of he observaion session had no bearings on heir workshop pracice grades. The firs insrumen used was he Pracice Observaion Toolki for Groups, which was specially designed by a domain exper. He firs analyzed he course book and eaching noes, observed several workshop pracice sessions and had exensive discussions wih he workshop insrucors before developing he workshop pracice learning model ha focused on ineraciviy, work pace and independence (see Figure 2). I n e W o r a c Commun r k i v i ca P i y i on Group Checklis a c e I n d e p e n d e n Figure 2. Model of Workshop Pracice He hen idenified 11 iems ha could possibly capure, idenify c e or reflec he effecs of as he workshop progressed and caegorized hem as follows: i. Familiariy wih workshop asks: engages in discussion on opics relaed o workshop pracice; checks wih insrucor and peers ii. Responsiveness o insrucor: responds o insrucor s quesions iii. Abiliy o work independenly: works independenly; checks wih insrucion shee; seeks assisance from peers and relies on hem for help; clarifies repeaedly wih insrucor iv. Pace of Work: complees all asks ahead of schedule, wihin or beyond schedule. These indicaors formed he basis of he form for he Pracice Observaion Toolki for Groups. Daa was collaed by occurrences. The workshop insrucors and domain exper also ook observaion noes. The second insrumen was an unsrucured, open-ended inerview for saff. I focused on he behavior of he paricipans in he workshop and wheher hey easier o each. The domain exper and his assisan were inerviewed ogeher on Dec 3, 2008 for 30 minues while he wo workshop insrucors were inerviewed ogeher on Dec 9, 2008 for abou 45 minues. In addiion, personal daa, log in daa, es scores and wrien commens from he paricipans were also colleced. These were used o build a profile of each workshop group. The observaion forms and noes were saved in Microsof 2003 Excel and Word files respecively while he inerviews were ranscribed and sored in Microsof 2003 Word files. The observaion daa were compared agains he observer s noes, inerview ranscrips, paricipan s personal daa, heir commens, logins and es scores. FINDINGS The number of log-ins o he modules in Table 1 indicaed ha he paricipans were using. In addiion, 87.5% of he paricipans wroe ha had prepared hem in erms of wha o expec in he workshop, and had helped hem undersand he pars of he machine and learn how o operae he machines. The daa presened was based on he summaion of he paricipans observed over hree sessions aking ino accoun he absenees: 22 for he workshop group (wo absenees), 23 for he mixed workshop group (one absenee), 30 for he non- workshop group, and 21 for he non- mixed workshop group (hree absenees). Familiariy wih Workshop Tasks Indicaors on how well prepared paricipans for heir workshop pracice were as follows: he need o discuss workshop pracice maers and check wih heir insrucor and workshop group members. Table 2 shows he average percenages for heir need o discuss workshop-relaed maers. Table 2. Need for Discussion Workshop groups Discussed workshop Checked wih Checked wih maers Insrucor Peers Boh 80.0% 22.2 % 22% 77.3% 18.2% 9.1% Mixed 82.6% 26.1% 34.8%
Boh Non- 92.6% 10.5 % 46.4% Non- 90.0% 6.7% 50.0% Non- Mixed 95.2% 14.3% 42.9% The workshop groups needed o communicae less (80.0%) han he non- workshop groups (92.6%) abou workshop maers. The non- workshop groups were mos acively involved in discussion, and seemed more ineracive and lively paricularly during he demonsraion sessions. The workshop groups communicaed more ofen wih heir insrucor (22.2%) han he non- workshop groups (10.5%). The non- workshop groups communicaed wice as ofen (46.4%) wih heir group members compared o he workshop groups (22%). They ofen asked for exra informaion and clarificaion and communicaed more wih heir peers (46.4%) han he insrucor (10.5%). The workshop insrucors noiced ha as he inernaional sudens generally mingled well wih s in heir group, hey would clarify heir doubs wih hem. If he s had doubs, hey would ask heir insrucor. Perhaps ha migh have been he reason for mixed workshop group s high checking wih insrucor percenage (26.1%) and a relaive high checking wih peers percenage (34.8%). Responsiveness o Workshop Insrucor The second indicaor of preparedness for workshop pracice was he paricipans responsiveness o he workshop insrucor s quesions. Table 3 shows he response raes by workshop groups. Table 3. Responsive ness o Insrucor s Quesions Workshop Groups Responded o Insrucor s Quesions Boh 35.4% 27.3% Mixed 43.5% Boh Non- 61% Non- 60.0% Non- Mixed 61.9% On average, he groups responded less o he insrucor's quesions compared o he non- groups. However, he insrucors noiced ha some paricipans were able o visualize machine pars and provide correc answers. Boh and non- workshop groups were able o answer he insrucor s quesions correcly. Abiliy o Work Independenly Independence was deermined by he following: he abiliy o work independenly, he need o refer o he insrucion shee, he level of dependence on workshop group peers o explain and assis and he need o clarify wih he insrucor. See Table 4. Table 4. Level of Independence W orkshop Worked Required Depended Clarified Groups Independenly Insrucion on peers repeaedly shee wih insrucor Boh 42.3% 62.2% 11.3% 6.7% 45.5% 59.1% 18.2% 9.1% Mixed 39.1% 65.2% 4.3% 4.3 % Boh Non- Non- Non- Mixed 39.0% 72.6% 12.1% 8.1% 40.0% 83.3% 10.0% 6.7% 38.1% 61.9% 14.3% 9.5% The workshop insrucors noiced ha he workshop group preferred individual work, he non- mixed group preferred working wih each oher while hose in he non- workshop group someimes preferred o work as group and a oher imes, individually. Generally, he workshop groups were more ask-oriened and were more independen (42.3%) compared o he non- workshop groups (39%) who ended o move around, alk and discuss while working on he machines. The workshop group was he mos independen (45.5%). The mixed group was marginally more independen (39.1%) han he non- mixed workshop group (38.1%) bu marginally less independen han he non- workshop group (40%). In general, he non- workshop groups looked a he insrucion shee more ofen (72.6%). However here was no specific paern as o which comparaive pair of workshop groups looked more a he insrucion shees. The workshop group looked a he workshop insrucion leas (59.1%) while he non- workshop group looked a i he mos (83.3%) However, he mixed workshop group needed o look a he insrucion more (65.2%) han he non- mixed group (61.9%). The workshop groups depended less on heir peers for help (11.3%) compared o he non- workshop groups (12.1%), However, he workshop group depended more on heir peers for help (18.2%) compared o he non- workshop group who required he leas assisance from heir peers (10%). The mixed group required he leas help (4.3%) compared o he non- mixed workshop group (14.3%). The groups seemed o need less repeaed clarificaion (6.7%) wih he insrucor han he non- groups (8.1%). However, he workshop group referred more o he insrucion (9.1%) han heir non- counerpars (6.7%). The mixed workshop group required he leas clarificaion (4.3%) while he non- mixed workshop groups required he mos (9.5%). Pace of Work The working pace differed among he workshop groups. The insrucors fel ha he workshop group was he bes in erms of overall performance followed by he
mixed group, he non- group and finally he non- mixed group. Table 5 shows he average compleion rae for each workshop group and he overall average for he and non- workshop groups. Table 5. Compleion rae for wor kshop asks Workshop Group Ahead schedule of Wihin schedule Behind schedule Boh 26.8% 73.3% 0% 31.8% 68.2% 0.0% S BL Mixed 21.7% 78.3 % 0.0% Non- 20.3% 60.7% 19.1% Non- 16.7% 50.0% 33.3% Non- Mixed 23.8% 71.4% 4.8% The overall work pace of he groups was generally faser han ha of he non- groups. For he compleion ahead of schedule sub-caegory, he groups were faser (26.8%) han he non- workshop (20.3%). The workshop group was he fases (31.8%) of all he groups. The non- mixed workshop group (comprising 50% or four paricipans from he ITE wih Mechanical raining) was marginally faser han he mixed group (comprising 25% or wo paricipans from ITE wih Mechanical raining). For he compleion wihin schedule sub-caegory, he workshop groups were generally faser (73.3%) han heir non- counerpars (60.7%). However, he workshop group had a higher compleion wihin schedule rae (68.2%) compared he non- workshop group (50%). The mixed group had he highes compleion wihin schedule rae (78.3%) followed by he non- mixed group (71.4%). For he compleion behind schedule sub-caegory, 19.1% from he non- workshop groups could no complee heir work wihin schedule; 33.3% from he non- workshop group and 4.8% from he non- mixed group. Easy o each Generally, he four workshop groups were easy o each. However, he groups were easier o each for Shee Meal in week four. The workshop insrucors noiced ha all inernaional sudens ne eded processes o be repeaed. DISCUSSION The effecs of on workshop pracice were derived by comparing he and non- workshop groups using a scale ranging from large, moderae, marginal, neural and negaive. The posiive effecs of near ransfer [3, 23] of ranged from large o marginal. Large Posiive Effec I could be inferred ha helped o familiarize paricipans wih workshop pracice asks as here was comparaively less need o discuss maers relaed o workshop pracice. The workshop groups were more ask-orienaed, and referred more o he insrucors han he non- workshop groups. This could be he resul of heir ransferring heir knowledge and comprehension of conceps from he lessons [25] o he workshop environmen. I also achieved he insrucional objecives of psychomoor domain for percepion (awareness) and se (menal readiness o ac) [26]. The need of he non- groups o discuss workshop maers could have been a sraegy ha hey used o compensae for he lack of insrucion, and mainly looked o heir peers o make sense of heir learning asks. Large -Moderae Posiive Effec seemed o provide an advanage in erms of work pace involving performance of a complex moor skill [26]. This could have involved procedure-o-procedure ransfer [3]. Overall, he workshop group performed beer han heir non- workshop group. The mixed group was somewha beer han he non- mixed group. The mixed non- group, wih wice he number of ITE paricipans, compleed heir asks ahead of ime; however a number could no complee heir work on ime. The ransfer of learning helped he group achieve he objecives in he guided, mechanism and complex over response caegories of he psychomoor domain [26]. Moderae Posiive Effec The groups were noiceably easier o each for Shee Meal (week 4) where here was cerainly procedure-o-procedure ransfer [3]. The workshop groups were able o visualize he machine pars, perhaps hrough he ransfer of heir visual memory of he machine pars [25] o he workshop environmen, meeing he percepion caegory in he psychomoor domain [26]. Marginal Posiive Effec The groups were marginally more independen, less relian on he insrucion shee, heir peers and insrucor. The mixed group seemed o rely more on heir insrucion shee and less on heir peers and insrucor compared o he group. Perhaps he preparaion helped familiarize hem wih he sequence. This helped achieve he percepion and se caegories for he psychomoor domain [26]. The non- group referred more o he insrucion shees, and perhaps because hey had discussed more wih each oher iniially, hey migh no have needed so much assisance from heir peers. CONCLUSION There were posiive effecs of on workshop pracice, alhough varied. The findings sugges ha he effec was large for all groups in he area of workshop preparaion, reducing he need o discuss wih heir peers. had a large o medium effec in erms of work pace. I was moderae in erms responsiveness, in heir abiliy o visualize he machine pars, ease in eaching hem, and marginal in erms of independence. As ransfer of learning appears in differen guises, furher work is required. Inerviewing groups immediaely afer each workshop pracice would verify he findings and help enhance he undersanding of ransfer in workshop pracice.
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