Student Performance in Online Quizzes as a Function of Time in Undergraduate Financial Management Courses


 Ezra Robbins
 3 years ago
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1 Student Performance n Onlne Quzzes as a Functon of Tme n Undergraduate Fnancal Management Courses Olver Schnusenberg The Unversty of North Florda ABSTRACT An nterestng research queston n lght of recent technologcal developments s an nvestgaton of the relatonshp between the tme remanng to complete onlne quzzes and quz scores. The data consst of over 4,000 ndvdual quz scores for sx sectons of Fnancal Management at The Unversty of North Florda taught between the Summer of 2004 and the Summer of Over 50% of the tme, students take onlne quzzes when they have less than 10% of the total tme allocated for the quz remanng. Moreover, students reduce the tme avalable to them for later quzzes as the semester progresses. The most successful students take the quzzes shortly after the materal has been covered n class. Regresson analyss reveals a strong postve relatonshp between the tme remanng untl the quz deadlne and the quz score. For every addtonal 10% of the total tme avalable to take a quz, the quz score ncreases by approxmately 1.1 ponts, on average. Also, students perform better for hgher number quzzes, partcularly f they allow themselves a large amount of tme to take the quz. In addton, students wth ether a low prevous average or a falng average contnue to perform poorly, partcularly f they allow themselves relatvely lttle tme to complete a quz. Fourth, the relatonshp between the prevous amount of tme students budgeted to take a quz and the current quz score s postve and margnally sgnfcant. However, students who budgeted less tme for quzzes early n the semester beneft on the last quz by earnng a hgher quz score. Ths s partcularly true for students who do not allow themselves a lot of tme to take the current quz. Lastly, students who allow themselves the least amount of tme to take a quz could ncrease ther quz scores by about 12 ponts for every addtonal percentage pont of avalable tme they budget for themselves to take the quz. The results reported here are nterestng not only for Fnancal Management courses at The Unversty of North Florda, but offer some nterestng mplcatons for Fnancal Management courses across the country and for projects n any other class. Keywords: Onlne Quz, Fnancal Managemen Tme, Student Performance Student Performance, Page 1
2 Purpose and Motvaton Technologcal teachng and assessment ads such as the Blackboard System have become commonplace n academa. Students these days are capable of usng the Web to obtan learnng materals and to complete tasks for a gven course. Smth and Rupp (2004), for example, report that 80 percent of ther student sample consder themselves to be ether ntermedate or advanced computer users. Descrptons of usage of varous technology (hardware, software, etc.) n the classroom are ample n recent years. Edlng (2000) and Webb (2001) provde two examples of how technology can enhance the classroom envronment. Possbly as a result of developng student sklls n managng technologcal ads n the classroom, there s some evdence that tradtonal and webasssted methods of teachng produce no dfferent results, at least n terms of student grades (see, for example, Prluck [2004] and Dellana, Collns, and West [2000]), whch may leave webasssted or even onlne courses as costeffectve alternatves to the tradtonal methods of teachng. Nevertheless, Serwatka (2003) ponts out that subjectve testng s problematc n an onlne settng, partly because t s dffcult to dentfy who s takng the test. Research also ndcates that seatng n partcularly large classes affects student grades. Benedct and Hoag (2004) fnd that students who st n the back have a 23 percent ncreased probablty of recevng Ds or Fs. Onlne courses do not face ths ssue and webasssted courses may mtgate ths ssue, although t remans unclear whether nformaton s lost wthout facetoface communcaton between nstructor and student. Gven the contnued research nto webasssted and onlne courses, contnued research nto the effects of webasssted learnng on student outcomes s therefore mportant and necessary. Whether students learn equally well n a webasssted course undoubtedly affects course and program outcomes, a crteron that has receved great attenton from the Assocaton to Advance Collegate Schools of Busness (AACSB). 1 The purpose of ths study s to nvestgate the relatonshp between the tme remanng to complete onlne quzzes and the quz score for sx sectons of Fnancal Management Courses at The Unversty of North Florda. Gven the ncreased focus of webasssted learnng n academa and the focus on outcomes by the AACSB, such an nvestgaton s warranted. However, an nvestgaton of webasssted testng methods s also mportant because t may gan nsght nto whether students retan and apply knowledge, whether students budget ther tme more effectvely as the semester progresses, and whether anxety s reduced or elmnated as addtonal onlne quzzes are taken. These factors are dscussed below. The nature of the Fnancal Management course s hghly cumulatve, and t s mportant to nvestgate whether students retan and apply the knowledge learned throughout the semester and whether a webasssted testng approach s suffcently studentcentered to be used n ntroductory fnance courses n order to satsfy AACSB expectatons and requrements. Recent studes, such as the ones by Taylor et al (2004) and Doyle and Wood (2005) pont out that the AACSB has ncreased ts focus on student outcomes and a studentcentered approach. If students retan the knowledge learned early n the semester and demonstrate that knowledge through onlne quz performance throughout the semester, then webasssted testng may be a vable alternatve to classroom testng. Another nterestng aspect of nvestgatng the relatonshp between the tme a quz s taken and quz performance s whether students budget ther tme more effectvely as the 1 For a more detaled dscusson, see Taylor, Humphreys, Sngley, and Hunter (2004) and Doyle and Wood (2005). Student Performance, Page 2
3 semester progresses and learn from ther prevous mstakes. That s, f a student decdes to take a quz at the last possble mnute and s unable to complete the quz, wll that student correct hs or her mstake on a subsequent quz and take that quz earler? Such a fndng would ndcate that a webasssted testng approach s studentcentered and would not dsadvantage the student by separatng the testng envronment from the classroom. It s also possble that webbased testng reduces students test anxety. Burns (2004) fnds that grade expectatons by students can ncrease anxety at the tme of the fnal exam, whch may n turn affect the actual grade the student receves. Based on ths research, we suspect that students takng quzzes outsde of the classroom wll experence less anxety than they do wth a tradtonal testng format. Nonetheless, to the extent that students stll experence anxety and dread takng onlne quzzes, t s possble that students wll postpone takng an onlne quz untl the last possble mnute, whch may negatvely affect quz grades. Whle ths has not been tested n prevous research, a fndng that less remanng tme to complete a quz wll result n lower performance would confrm ths delberaton. Conversely, Jadal (1999) suggests that student performance may ncrease as students focus more on the task at hand because of the new technology. Perhaps the most nterestng aspect of nvestgatng the relatonshp between avalable tme and quz performance s the fact that such a relatonshp may gan nsght nto student performance on other, subjectve, projects, such as research projects and essays. For example, a fndng that quz performance s hghly postvely correlated to tme avalablty would ndcate that students who complete other projects early perform better, on average, than those who wat untl the last mnute to complete a project. The remander of ths paper s organzed as follows. Secton 2 presents a descrpton of the setup of Fnancal Management courses at The Unversty of North Florda (UNF). Expected fndngs and related lterature are dscussed n Secton 3. Secton 4 presents the data and methodology. Results are dscussed n Secton 5. Secton 6 concludes. A Descrpton of Onlne Quzzes n the Fnancal Management Course at UNF The present study nvestgates the relatonshp between avalable tme to complete a quz and quz score for Fnancal Management (FM) undergraduate courses at The Unversty of North Florda (UNF). FM courses at UNF are capped at about 180 students per secton. We nvestgate the tmeperformance relatonshp for sx sectons of FM, ncludng the Summer of 2004 (one secton), the Fall Semester 2004 (two sectons), the Sprng Semester 2005 (two sectons), and the Summer 2005 (one secton). Two professors at UNF taught the FM sectons over ths tme perod. In each of the FM sectons, the professors provded students wth nclass examnatons. In addton, students had to complete eght quzzes throughout the semester that were posted on Blackboard. Students had one work week to complete the quz, wth the quz becomng avalable on Blackboard on a Monday mornng at 8:00 am and remanng avalable to students untl the followng Saturday at 11:00 pm (Fall Semester 2004) or 10:00 pm (Sprng Semester 2005). Students were nformed about ths procedure twce durng the frst week of classes. In addton, the tmng of the quzzes and the quz schedule was publshed n the syllabus. Lastly, an announcement for the quz was posted on Blackboard once a quz was posted. The format of the quzzes was multple choce, wth fve to sx questons focusng on one partcular chapter. Student Performance, Page 3
4 Students had advance knowledge of the chapters covered n the quz. In general, nclass coverage of the chapter ended on ether the Monday or the Wednesday of the week durng whch the quz was posted. Importantly, students were nformed several tmes n class that the quzzes would lterally dsappear at the expraton tme. For example, students were aware that they could not log onto Blackboard at 9:59 pm durng the Sprng Semester of 2005, as the quz would dsappear at 10:00 pm and they would be unable to complete the quz. Addtonal formattng optons for quzzes and tests are avalable on Blackboard. For the quzzes n the FM sectons nvestgated here, the questons were presented to students n a randomzed order. Furthermore, students could not backtrack (.e., once they answered a queston, they could not change the answer) and were not allowed to take a quz multple tmes. Ths nformaton was communcated to students n class and was ncluded wth the drectons for each quz. These drectons are vsble to students when they take a quz on Blackboard. Students were nether encouraged nor dscouraged to work together on the quzzes. However, students were not prohbted from workng together f they chose to. Expected Fndngs and Revew of Related Lterature Throughout the semester, we expect that students who wat to take the quz untl shortly before the quz expres on Blackboard wll perform more poorly than those who decde to take a quz early, for several reasons. Frs early n the semester, students may have a dffcult tme assessng how long t wll take them to complete a quz. Consequently, f a student wats untl shortly before the quz expres, he or she may msjudge the tme necessary to work the quz and be unable to complete t. Second, students who wat untl the last mnute to take the quz wll not have been exposed to the materal n class for several days, whereas those that decde to take the quz rght after the last lecture for that chapter wll be closer to the materal covered on the quz. Thus, we hypothesze: H1: Students who have more avalable tme to take the quz wll perform better than those who have less avalable tme to take the quz. As the semester progresses and addtonal quzzes are taken, t s possble that students wll change ther study habts, whch may result n ndvdual students takng quzzes earler than prevous quzzes and n mproved quz performance. Conversely, quz grades throughout the semester may decrease, as the materal s cumulatve and becomes more dffcul and as students become overly confdent as a result of good performance on prevous quzzes. There are several reasons to beleve that ndvdual students grades may ncrease as addtonal quzzes are taken throughout the semester. Frs students probably start workng together to take quzzes. Young, Klemz, and Murphy (2003), for example, fnd that encouragng supportve class behavors can ncrease selfreport performance and the course grade. Whle t s possble that some students perceve workng together on quzzes as cheatng, Wes Ravenscrof and Shrader (2004) fnd that the relatonshp between moral judgment scores and actual cheatng behavor s nsgnfcan leadng us to beleve that students wll work together on quzzes even f they beleve such behavor consttutes cheatng. 2 Second, students may budget ther tme more effectvely as the semester progresses and may refran from takng quzzes at the last mnute even f they have prevously done so. 2 A smlar fndng s reported by Chapman et al (2004), who fnd that busness students cheat more than ther peers n other dscplnes. Student Performance, Page 4
5 Rabnowtz (2001), for nstance, suggests that students budget ther tme and learn from ther mstakes as a successful learnng strategy. Thrd, students may adjust and ncrease ther study tme and habts as they learn what s requred to acheve a better grade throughout the semester; Okpala, Okpala, and Ells (2000) fnd that academc achevement s postvely related to academc effcacy and habt varables, although study tme by tself s not an explanatory varable. Furthermore, Pope and Ma (2004) argue that students care about gradersk, the potental for the loss of ponts on examnatons, quzzes, and other assgnments. Consequently, students are motvated to acheve a hgher grade. Another reason why ndvdual students grades may ncrease as the semester progresses s that students may learn how to manage nterruptons better. FM students at UNF can take onlne quzzes on ther home computer, n the lbrary, at a frends house, etc. As the semester progresses, students may adjust the settng n whch they take quzzes n order to mnmze nterruptons. Speer, Valacch, and Vessey (1999) and Speer, Vessey, and Valacch (2003) fnd that nterruptons mprove decsonmakng on smple tasks and lower performance on complex tasks. Moreover, the authors report that the frequency of nterruptons and the dssmlarty of content between the prmary and nterrupton tasks was found to exacerbate that effect for complex tasks. To the extent that FM quzzes are complex tasks and that nterruptons whle takng the quz are not related to the class materal, students who manage to reduce nterruptons throughout the semester should perform better as the semester progresses. Yet another reason why students may perform better on FM quzzes later n the semester s that those students who are not famlar wth the technology early n the semester may become used to t as the semester progresses. Stoel and Lee (2003) fnd that experence wth technology postvely nfluences perceved ease of use, and perceved ease of use n turn postve nfluences atttudes toward the technology and ts usage. The arguments above lead to the followng hypotheses: H2: As ndvdual students take addtonal quzzes throughout the semester, ther quz score ncreases, especally f ther quz average s low and f they have a falng quz average. H3: Indvdual students who wated untl the last mnute to take quzzes early n the semester wll adjust ther study habts to take quzzes earler as the semester progresses, resultng n a hgher quz score. A counterargument to H2 and H3 above s presented by Chrstensen, Fogarty, and Wallace (2002), who fnd that the more conservatve a student s selfeffcacy s, the hgher subsequent exam scores and the fnal course grade wll be. Ths mples that more optmstc students wll perform worse on subsequent quzzes and more pessmstc students wll perform better on subsequent quzzes. Consequently, whle students who perform poorly early n the semester may adjust ther study habts to ncrease ther grades, those who perform well early n the semester may let ther study habts deterorate, leadng to reduced quz scores. Ths s also supported by Krohn and O Connor (2005), who fnd that students respond to hgher mdterm scores by reducng the number of hours they subsequently allocate to studyng for the course. Regardng H3, Conte, Matheu, and Landy (1998) suggest that tme urgency (whch ncludes an ncreasng concern wth the passage of tme) may be dffcult to alter through tranng and may thus have a predctable effect on performance. In the current study, ths study suggests that students may not adjust the avalable tme they allocate themselves to complete a quz as the semester progresses, thereby negatng H3. Student Performance, Page 5
6 Data and Methodology For each secton taught n the Fall of 2004 (2 sectons) and the Sprng of 2005 (2 sectons), quz scores were collected for each student for each of the eght quzzes gven n each secton of FM at UNF. Ths resulted n an ntal sample of 4,512 quz scores for 564 students. At UNF, the admnstraton automatcally deletes students from the Blackboard system f they wthdraw from the course. Consequently, the sample presented here s subject to survvorshp bas, as only the students that completed the course are analyzed. We beleve ths to be an approprate sample for analyzng the relatonshp between quz scores and tme avalablty, as those students that wthdraw from the course mght not have taken the course serously or mght have outsde nfluences (whch caused them to wthdraw from the course) affectng the tme at whch they take the quzzes. Furthermore, several students ether dd not take the quz at all (resultng n a quz score of zero) or sgned on too late to answer even one queston (also resultng n a quz score of zero). Many of the students who dd not take the quz at all also never completed any other assgnment and later wthdrew from the course. Snce these observatons may serously bas our results n favor of fndng a postve relatonshp between quz scores and tme avalablty, and snce our focus here s on the relatonshp between tme management of students and quz performance for students who are actually attemptng to complete an assgnmen they were elmnated from the sample, leavng a total sample of 4,001 quz scores. 3 Blackboard was used to dentfy the tme at whch a student completed a gven quz. Each of the 4,001 quz scores was manually recorded together wth the tme at whch the quz was completed. Ths tme was then used to compute the tme stll avalable to take the quz at the tme a student completes the quz. Ths avalable tme was then expressed as a fracton of the total tme avalable to take the quz. For example, f a student n the Sprng Semester of 2005 completed a quz at 5 p.m. on Saturday, then she would stll have had fve hours to take the quz once she completed snce the quz expred at 10 p.m. From Monday at 8 a.m. to Saturday at 10 p.m. s a total of 134 hours to take the quz. 4 Thus, the fracton of tme stll avalable for ths student to take the quz once she completed t was 5/134 = Fgure 1 presents the dstrbuton of avalable tme to take the quzzes once the quzzes are completed for all sx sectons of FM, n fractons of total tme avalable to take the quz. From Fgure 1, over 50% of the tme, students choose to take a quz when they have between 0 and 10% of the total tme avalable to them remanng! Interestngly, the next most frequent class occurs when students have between 20 and 30% of the total tme remanng to take the quz. Ths occurs 14.2% of the tme. Ths s not surprsng, and ndcates that some students choose to wat to take a quz untl the materal s covered n class. The next two most frequent classes are 10 to 20% and 50 to 60% of the tme, wth frequences of 9.5% and 9.0%, respectvely. Interestngly, students take the quz very early, wth 90 to 100% of the total tme avalable remanng. Ths consttutes only 1.2% of the total. 3 Note that ths sample does nclude quz scores of zero by students who answered all questons. Moreover, t ncludes quz scores other than zero of students who ran out of tme whle takng the quz. We also repeated the analyss by ncludng all 4,512 observatons, and the results were smlarly pronounced. 4 Two unusual quzzes should be mentoned. Quzzes 3 and 4 n the two secton n the Fall Semester of 2004 had a total tme of 303 and 207 hours to complete the quz, respectvely. Ths occurred because of class cancellatons and quz extensons. These extensons were communcated to the students 1) va emal, 2) through a Blackboard announcemen and 3) va a class announcement. Student Performance, Page 6
7 Fgure 1. Avalable Tme Remanng to Take a Quz n Sx Sectons of FM at UNF Between Summer 2004 and Summer Number of Students Fracton of Total Tme Remanng to Complete a Quz Fgure 2 shows the dstrbuton of remanng avalable tme to complete the quz by quz number. The Fgure clearly shows that students allow themselves more tme early n the semester to complete a quz. Ths makes sense, as students become used to the quzzes and are better able to assess the tme needed to complete a quz as the semester progresses. Interestngly, the tme fracton appears to level off at about quz number 4, ndcatng that students have determned the optmal tme to take a quz and see no reason to change t agan. A notable excepton s quz number 8, whch students seem to take farly early, almost as early as the frst quz, on average. A possble explanaton for ths s that quz 8 was one of the last assgnments left to complete by students; students may thus choose to take the quz early to complete the semester. Fgure 2. Avalable Tme Remanng to Take a Quz n Sx Sectons of FM at UNF Between Summer 2004 and Summer 2005, by Quz Number. Fracton of Total Tme Remanng Quz Number Student Performance, Page 7
8 Table 1 shows the descrptve statstcs for the 4,001 quz scores. As shown n the Table, the quz average across the four sectons s 72.84, wth a standard devaton of ponts. As would be expected, quz scores range from 0 to 100%. Table 1 also shows that students tend to take quzzes n the late afternoon, fnshng them around 4:30 p.m., on average. The standard devaton for the tme at whch quzzes are taken s a relatvely hgh 4.7 hours, confrmng that students lterally take quzzes around the clock, as ndcated by the mnmum and maxmum. Table 1. Descrptve Statstcs for 4,001 a Quz Scores n FM at UNF. Mean Std. Dev. Mnmum Maxmum Score Hour Avg. Tme (Hours) c b Avg. Tme (Fracton of Total) d Notes to Table 1: a A total of 4,512 quz scores were avalable. To avod an upward bas n the relatonshp between tme avalablty and quz score, those observatons where the student dd not take a quz at all or sgned on too late to complete even one queston on the quz (resultng n a score of zero) were deleted. b In the Fall Semester of 2004, students had from 8 a.m. on Monday to 11 p.m. on the followng Saturday to take a quz (a total of 134 hours avalable). In the Sprng Semester of 2005, students had from 8 a.m. to 10 p.m. on the followng Saturday to take a quz (a total of 135 hours). Quzzes 3 and 4 n the Fall Semester of 2004 were extended due to cancelled classes, resultng n a total avalable tme of 303 hours and 207 hours, respectvely. c Ths s the average tme a student would stll have had to complete a quz at the tme he or she fnshes takng the quz. d Computed as the average tme (n hours) dvded by the total amount of tme a student had to complete the quz. The average tme that remans to take the quz after students fnsh takng them s hours, on average. Ths means that the average student takes the quz on the day before s expres. However, the standard devaton for the average avalable tme s also very wde, wth hours. Moreover, the mnmum of 0 ndcates that sometmes students run out of tme when takng a quz, and the maxmum of hours ndcates that some students take the quz very early. 5 When the remanng tme avalable to take a quz s expressed as a percentage of the total amount of tme avalable, the average student allows hm or herself 20% of the total tme allotted for the quz to complete t. As wth the tme remanng n hours, the standard devaton s very large, wth about 22%, and the range of avalable tme as a percentage of the total s from 0% to 99%. Table 2 shows the descrptve statstcs for the quzzes by secton, quz number, and decle. Panel A shows the descrptve statstcs by secton, Panel B shows the descrptves by quz number, and Panel C shows the descrptves by decle. As shown n Panel A of Table 2, classes taught n the Sprng Semester of 2005 (Sectons 446 and 452) performed better, on average, than classes taught n the Fall Semester of The average quz score n the Sprng Semester s about 75.0, whle the average score n the Fall Semester s only about Furthermore, students n the Sprng Semester allowed themselves more tme to complete the quzzes, wth an average fracton of avalable tme remanng of about 23% at quz completon. Conversely, for the Fall Semester classes, that fracton s only about 17%. 5 Recall that students had a total of 303 hours to take the thrd quz durng the Sprng 2005 semester. 6 Students n the Sprng Semester had addtonal materals avalable to them to prepare for the quzzes, such as practce quzzes and exams. Student Performance, Page 8
9 Panel A of Table 2 also reveals that the day classes (Sectons 434 and 446) whch begn before 5 p.m. complete the quzzes earler on the day a quz s taken than the nght classes (Sectons 440 and 452). The day classes complete the quzzes around 4 p.m., on average, whle the nght classes complete the quzzes closer to 5 p.m., on average. Statstcs for the 4,001 quzzes by quz number are shown n Panel B. There are several nterestng observatons to be gleaned from the table. Frs the average quz score tends to ncrease for hgher quz numbers. Whle quz 1 has the hghest average of almost 80, quzzes 2, 3, and 5 have averages n the md60s. Conversely, quzzes 6, 7, and 8 have averages n the mdto hgh70s, even though the chapter content of the quzzes s of a harder nature and ncorporates more cumulatve materal. Ths ndcates that students become more comfortable wth the materal as the semester progresses and are maybe more n tune wth the process of takng a quz. Panel B of Table 2 also shows a clearly dscernble decrease n the average tme avalable, expressed as a fracton of total tme avalable to take a quz, students allow themselves to take a quz; for quz 1, students allow themselves almost 27% of the total tme. However, ths fracton steadly decreases through quz 6, where ths fracton s only 15.4%. For quzzes 7 and 8, the average tme s 17.4% and 24.8%, respectvely. A possble explanaton for ths observaton s that students are antcpatng the end of the semester, and try to complete especally the last quz to be able to focus on fnals and projects n ther other classes. Panel C of Table 2 shows the statstcs by tme fracton decle. 7 As shown n Table 2, decle 1 has an average remanng avalable tme to complete a quz (once students are done takng the quz) of only 0.3% of the total avalable tme. For quzzes n the Sprng Semester of 2005, where students had 134 hours to complete a quz, ths translates to a tme of only 24 mnutes. Conversely, decle 10 has an average of 67.5%, whch translates to approxmately 90 hours and 30 mnutes, or almost four days. There are some other nterestng observatons n Panel C. Frs the hour of the day at students complete quzzes steadly decreases from decle 1, for whch students fnsh the quz at about 10 p.m., to decle 5, for whch students fnsh the quz around noon. For hgherorder decles, the tme stablzes between 3 and approxmately 5 p.m. Whle t s not surprsng that decle 1 students complete quzzes at such a late hour, t s surprsng that the tme would decreases between decles 2 and 5. However, nsofar students take the quz on the same day, ths result smply ndcates that an earler hour leaves students more tme (as ndcated by the hgher decle) to take the quz. Nevertheless, usng ths logc we would expect students to also take the quz at an even earler hour for decles 6 through 10, whch s not the case. What we do observe, however, s that the average quz score s farly steadly ncreasng as the decles ncrease. Interpretng these results smultaneously, a possble nterpretaton s that 7 The 4,001 observatons were placed n decles accordng to the fracton of tme avalable. Ths was accomplshed by sortng all observatons accordng to the tme fracton, n ascendng order and dentfyng the cutoff pont for each decle. Student Performance, Page 9
10 Table 2. Statstcs for Quzzes of Four Sectons of FM at UNF. Panel A By Secton Secton Score Hour Avg. Tme Avg. Tme (Fracton N Number/Varable (Hours) a of Total) b 434 c , d , c , d Panel B By Quz Number Quz Number/Varable Score Hour Avg. Tme Avg. Tme (Fracton N (Hours) of Total) Panel C By Decle e Decle/Varable Score Hour Avg. Tme Avg. Tme (Fracton N (Hours) of Total) Notes to Table 2: a Ths s the average tme a student would stll have had to complete a quz at the tme he or she fnshes takng the quz. b Computed as the average tme (n hours) dvded by the total amount of tme a student had to complete the quz. c Day class (.e., starts before 5 p.m.) d Nght class (.e., starts after 5 p.m.) e The 4,001 observatons were placed n decles accordng to the fracton of tme avalable. Ths was accomplshed by sortng all observatons accordng to the tme fracton, n ascendng order and dentfyng the cutoff pont for each decle. students who do better tend to 1) allow themselves more tme to complete the quz and 2) budget ther tme to take the quz n the late afternoon, probably rght after ther day class (or before ther nght class). Ths s further supported by the fact that decle 9, whch has the hghest average quz score of 81.87, has an average tme fracton of 46.9%, whch translates to a tme of about 63 hours, or almost three days. Ths means that the most successful students take ther quzzes late on Wednesday or early on Thursday. Snce coverage of the necessary materal s Student Performance, Page 10
11 typcally fnshed on Wednesdays, ths result s not surprsng and s encouragng from a teachng perspectve. Table 3. Quz Statstcs by Hour of Day and Day of the Week for Four Sectons of FM at UNF. Panel A By Hour Hour Taken a /Varable Score N Panel B By Day Day of Week b /Varable Score N Monday Tuesday Wednesday Thursday Frday Saturday ,975 Sunday Notes to Table 3: a Zulu tme s used. For example, hour 13 s 1p.m. b In the Fall Semester of 2004, students had from 8 a.m. on Monday to 11 p.m. on the followng Saturday to take a quz (a total of 134 hours avalable). In the Sprng Semester of 2005, students had from 8 a.m. to 10 p.m. on the followng Saturday to take a quz (a total of 135 hours). Quzzes 3 and 4 n the Fall Semester of 2004 were extended due to cancelled classes, resultng n a total avalable tme of 303 hours and 207 hours, respectvely. Ths s the reason Sunday has some observatons. Student Performance, Page 11
12 Table 3, Panel A presents the quz statstcs by hour of completon. Lookng n the last column, 10% of the total sample (or 400 students) complete the quz between 8 and 9 p.m. Moreover, the number of students fnshng quzzes s steadly ncreasng from 10 a.m. to 10 p.m. on a gven day. These students tend to perform reasonably well, on average, wth quz scores n the 70s, although the students takng the quz between 9 and 10 p.m. and between 10 and 11 p.m. have an average only n the hgh 60s. Although only few students tend to do so, those takng the quz between 1 and 6 a.m. (nght owls) tend to perform poorly, wth quz averages between 58 and 68, whle those few students takng the quz between 6 and 8 a.m. (early rsers) tend to perform well, wth quz averages rangng from 82 to 91. The average quz scores and number of students takng a quz by day of the week are presented n Table 3, Panel B. The most observatons are recorded for Saturday, typcally the last day to take the quz; about 49% of students complete the quz on Saturday. Ironcally, these students also acheve the lowest quz average of only As would be expected, the students that perform the best take the quz on ether Wednesday or Thursday, wth quz averages of and 80.59, respectvely. These students allow themselves enough tme to complete the quz by the tme t expres on Saturday, yet beneft from the fact that all the necessary materal has been covered n class. Those students takng quzzes on Monday also do relatvely well wth an average quz score of Methodology Once the data were obtaned, the followng regresson model was estmated to test hypotheses 1 through 3: QSCORE, t = α 0 1FRACT 2 NUMBER 3PAVG 4 PTIME 5 FAVG + ε, (1) where QSCORE, = the score on the quz after student takes the quz at tme t; t FRACT, = the amount of avalable tme remanng to take a quz when t s completed t by student at tme expressed as a fracton of the total tme avalable to take a quz; NUMBER, = the number of the quz student takes at tme rangng from 1 to 8; t PAVG, = the average for all quzzes student has taken pror to tme t; t PTIME, = the average fracton of total tme remanng student had to complete all t quzzes taken pror to tme t; FAVG, = a dummy varable equal to unty f student had a falng quz average at t tme t and zero otherwse. A postve and sgnfcant α 1 coeffcent would ndcate that students who allow themselves less tme to complete the quz perform worse and that those students who allow themselves more tme to complete the quz perform better. Such a fndng would support H1. The coeffcents α 2, α 3, and α 5 are used to test H2, that students quz scores ncrease as they take addtonal quzzes throughout the semester, partcularly f ther prevous quz average was Student Performance, Page 12
13 low or f they are have a falng quz average. The predcted sgn for these coeffcents are postve, negatve, and postve, respectvely. The coeffcent α 4 s used to test H3, that students who allowed themselves not enough tme to take prevous quzzes wll perform better on subsequent quzzes. The predcted sgn of α 4 s negatve. Regresson Results The regresson results from estmatng Equaton (1) are presented n Table 4. To avod multcollnearty between the varables, several models are presented. Snce the varables PTIME and PAVG, the average tme on prevous quzzes and the average on prevous quzzes, respectvely, are undefned for the frst quz, the total number of observatons s reduced to 3,422 quz scores. The adjusted Rsquared coeffcent s presented for each model n the last column. As can be seen from Table 4, the adjusted Rsquared ranges from 2.41% to 13.01%, dependng on the model used. The varable FRACT has the expected postve and sgnfcant coeffcent n every model. For example, n the full model (Model 1), FRACT has a coeffcent of Ths ndcates that the quz score wll ncrease by approxmately 1.1 ponts, on average, for every addtonal 10% of the total tme avalable students allow themselves to complete the quz. The magntude of FRACT ranges from n Model 1 to n Model 3, and the varable s sgnfcant at the 1% level n every model. Ths provdes strong support for Hypothess 1, that students who allow themselves more tme to take a quz perform better than those that do not. The quz numbers (NUMBER), the average on prevous quzzes taken (PAVG), and the exstence of a falng average on prevous quzzes (FAVG) are used to test Hypothess 2, that students quz scores wll ncrease wth hgher number quzzes, especally f ther prevous quz average was low and f they have a falng quz average. Recall that the expected coeffcents of the three varables are postve, negatve, and postve, respectvely. Lookng back at Table 4, the varable NUMBER has the expected postve and sgnfcant coeffcent n every model n whch t s ncluded, rangng from 1.92 n Model 3 to 2.47 n Model 1. Ths ndcates tha on average, quz scores are hgher for quzzes taken later n the semester, whch supports H2. Moreover, snce there are eght quzzes n a gven semester, ths ndcates that the dfference between Quz 8 and Quz 2 s more than a letter grade, on average. PAVG s ncluded n two models and has a postve and sgnfcant coeffcent n both cases. Ths ndcates that the hgher the average on prevous quzzes, the hgher wll be the quz score on the next quz. Thus, t appears that those students who perform well perform better as the semester progresses and that those students who perform poorly perform worse as the semester progresses. Ths result s unexpected n lght of the Chrstensen, Fogarty, and Wallace (2002) and Krohn and O Connor (2005), who argue ndrectly that the betterperformng students do worse subsequently and vce versa. A possble explanaton for ths result s that the FM courses at UNF are of a very hgh dffculty level. Consequently, students who struggle wth the early materal wll do even worse later n the semester, whle those who do well early contnue to mprove ther performance, perhaps because they choose a more favorable envronment to study n or because they begn studyng n groups. Ths s partcularly true gven the cumulatve nature of the materal n ths course; a good grasp of the early materal benefts students n later quzzes. Ths would also explan the sgnfcant postve coeffcent that s observed for FAVG, the dummy varable for a falng prevous quz average, n Table 4. Student Performance, Page 13
14 Table 4. Regresson Results for Quz Scores n Four Sectons of FM at UNF (tstatstc n parentheses). a,b Model/ Intercept FRACT NUMBER PAVG PTIME FAVG Adj. R 2 Varable Model % (12.24)*** (5.06)*** (11.97)*** (7.97)*** (0.61) (3.04)*** Model % (120.02)*** (9.24)*** Model % (48.79)*** (9.50)*** (9.08)*** Model % (16.92)*** (5.79)*** (11.81)*** (17.89)*** Model % (42.63)*** (7.52)*** (9.40)*** (2.70)*** Model (53.07)*** (6.66)*** 2.41 (11.71)*** (16.15)*** 11.41% Notes to Table 4: a The model s: QSCORE, t = α 0 1FRACT 2 NUMBER 3PAVG 4 PTIME 5 FAVG + ε where QSCORE, = the score on the quz after student takes the quz at tme t; t FRACT t, = the amount of avalable tme remanng to take a quz when t s completed by student at tme expressed as a fracton of the total tme avalable to take a quz; NUMBER, = the number of the quz student takes at tme rangng from 1 to 8; t PAVG, = the average for all quzzes student has taken pror to tme t; t PTIME t, FAVG t, = = the average fracton of total tme remanng student had to complete all quzzes taken pror to tme t; a dummy varable equal to unty f student had a falng quz average at tme t and zero otherwse., (1) b Snce both PAVG and PTIME are equal to zero for quz 1 by defnton, all quz 1 observatons drop out n the regresson analyss. Ths results n a total sample of 3,422 usable quz scores. * Sgnfcant at the 10% level. ** Sgnfcant at the 5% level. *** Sgnfcant at the 1% level. PTIME, the prevous average avalable tme expressed as a percentage of the total tme avalable, s used to test whether students who do not budget ther tme effectvely early n the semester wll adjust ther study habts to take quzzes earler and earn a hgher quz average. As shown n Table 4, PTIME s postve and sgnfcant n one of the two models n whch t was ncluded. It appears that students who have a budgeted more tme for prevous quzzes contnue to perform well on the next quz, and that those students who have not budgeted enough tme for early quzzes wll perform even worse on later quzzes. Ths supports the argument by Conte, Matheu, and Landy (1998) that tme urgency may be dffcult to alter through tranng. Student Performance, Page 14
15 Table 5. Regresson Results for Quz Scores n Four Sectons of FM at UNF, by Quz Number and Decle (tstatstc n parentheses). a,b,c Panel A By Quz Number Quz/ Intercept FRACT PAVG PTIME FAVG Adj. R 2 Varable % (3.22)*** (1.63) (3.46)*** (0.34) (0.68) % (6.19)*** (0.01) (3.31)*** (1.19) (2.05)** % (10.77)*** (1.82)* (3.12)*** (1.07) (1.42) % (4.10)*** (2.20)** (2.51)** (1.61) (0.81) % (7.68)*** (3.19)*** (4.66)*** (1.19) (0.59) % (6.28)*** (2.62)*** (4.48)*** (0.41) (1.30) (4.94)*** (5.44)*** 0.51 (5.12)*** (3.12)*** (0.54) 20.03% Panel B By Decle Decle/ Intercept FRACT NUMBER PAVG PTIME FAVG Adj. R 2 Varable , % (3.50)*** (2.58)*** (1.79)* (1.90)* (2.05)** (0.51) % (4.94)*** (0.41) (1.55) (1.86)* (0.25) (1.90)* % (4.56)*** (0.13) (3.14)** (1.33) (0.51) (2.11)** % (4.17)*** (0.09) (2.35)** (1.40) (0.31) (2.34)** % (1.92)* (0.29) (5.93)*** (3.77)*** (0.03) (0.57) % (5.18)*** (2.17)** (2.29)** (3.05)*** (1.15) (1.40) % (0.16) (2.32)** (2.27)** (2.79)*** (0.43) (0.65) % (0.38) (0.98) (5.67)*** (4.61)*** (0.70) (0.84) % (1.78)* (2.69)*** (5.64)*** (2.50)** (0.61) (0.28) (3.12)*** (1.24) 4.10 (8.04)*** 0.32 (2.69)*** (0.08) (0.68) 22.90% Student Performance, Page 15
16 Notes to Table 5: a The model below s estmated for each quz (Panel A) and for each tme fracton decle (Panel B): QSCORE, t = α 0 1FRACT 2 NUMBER 3PAVG 4 PTIME 5 FAVG + ε where QSCORE, = the score on the quz after student takes the quz at tme t; t FRACT t, = the amount of avalable tme remanng to take a quz when t s completed by student at tme expressed as a fracton of the total tme avalable to take a quz; NUMBER, = the number of the quz student takes at tme rangng from 1 to 8; t PAVG, = the average for all quzzes student has taken pror to tme t; t PTIME t, FAVG t, = = the average fracton of total tme remanng student had to complete all quzzes taken pror to tme t; a dummy varable equal to unty f student had a falng quz average at tme t and zero otherwse., (1) b c Snce both PAVG and PTIME are equal to zero for quz 1 by defnton, all quz 1 observatons drop out n the regresson analyss. Ths results n a total sample of 3,422 usable quz scores. The 4,001 observatons were placed n decles accordng to the fracton of tme avalable. Ths was accomplshed by sortng all observatons accordng to the tme fracton, n ascendng order and dentfyng the cutoff pont for each decle. The decles were formed based on the total of 4,001 observatons that were avalable, and not on the 3,422 observatons used n the regresson analyss. * Sgnfcant at the 10% level. ** Sgnfcant at the 5% level. *** Sgnfcant at the 1% level. Table 5 presents the regresson results by quz number (Panel A) and by ascendng avalable tme decle (Panel B). As shown n Panel A, FRACT becomes sgnfcant at about quz 4, and both the sze of the coeffcent and the sgnfcance ncrease through quz 8. Ths ndcates that the sgnfcant coeffcent reported n Table 4 s more pronounced for later quzzes n the semester; students who budget ther tme more effectvely late n the semester beneft to a greater extent than those who budget earler n the semester. Ths fndng makes sense, as tme budgetng becomes more mportant as the dffculty of the materal ncreases. As n Table 4, the coeffcent for PAVG s postve and sgnfcant for every quz n Table 5, agan ndcatng that students wth a hgher prevous quz average do better on subsequent quzzes, regardless of quz number. Interestngly, although FAVG was negatve and sgnfcant n the overall regresson model (Table 4), t s only negatve and sgnfcant for quz 3. PTIME, the prevous average fracton of tme students allow themselves to take a quz, s very nterestng n Panel A of Table 5. Although t was postve and sgnfcant n one nstance n Table 4, t s negatve and sgnfcant n Panel A of Table 5 only for quz 8; t s nsgnfcant n all other cases. Ths suggests that students who had prevously budgeted less tme to take a quz wll earn hgher quz scores on quz 8, ndcatng that those students may adjust ther study habts by the tme the last quz arrves. Ths complements the fndngs by Conte, Matheu, and Landy (1998) ncely n that tme urgency (ncludng an ncreasng concern wth the passage of tme) may not change much throughout the semester, but changes drastcally by the tme the last quz arrves. Ths makes sense, snce the last quz s the last chance for students to ncrease ther quz average. Panel B of Table 5 presents the regresson results by ascendng decle fracton. Decle 1 has the least avalable tme (students take the quzzes very late), whle Decle 10 has the most avalable tme (students take the quzzes very early). The results n Panel B are very nterestng. Student Performance, Page 16
17 Frs FRACT has a very large and hghly sgnfcant coeffcent n Decle 1 of 1, Ths ndcates that those students leavng themselves very lttle tme to complete the quz could ncrease ther score by about 12 ponts f they ncrease the tme avalable to them by 1% of the total tme they have to take the quz. Although FRACT s also postve and sgnfcant for decles 7 and 9, t s nsgnfcant for all other decles except for Decle 6, n whch the varable s negatve and sgnfcant. 8 Second, the magntude and sgnfcance of NUMBER s ncreasng farly steadly across the tme decles. Ths ndcates that students who already leave themselves a lot of tme to complete a quz (hgh decle students) beneft partcularly for quzzes later n the semester. Thrd, PAVG s nsgnfcant for lower decles but postve and sgnfcant for decles 5 through 10. Ths supports our earler conjecture that those students who already have a hgh quz average are more effectve at budgetng ther tme, allow themselves suffcent tme to complete a quz, and acheve a hgher quz score as a result. Another nterestng fndng reported n Panel B of Table 5 s that FAVG s negatve and sgnfcant only n the lower decles 2, 3, and 4. Ths means that the negatve and sgnfcant coeffcent for ths varable reported n Table 4 s due to students who already have a falng quz average and stll do not budget more tme to take the next quz, resultng n a another falng (or low) quz grade. PTIME s only sgnfcant n Decle 1, wth a coeffcent of Thus, for students who leave themselves very lttle tme to take the current quz, the less tme a student budgeted for prevous quzzes, the hgher the quz score on the current quz wll be, ceters parbus. Ths s an nterestng fndng. One possble nterpretaton of ths result s that students who consstently leave themselves very lttle tme to take a quz learn how to operate better wthn the tme wndow they allow themselves, even though they do not adjust the tme wndow tself. Concluson Technologcal nnovatons n academa are constan and technology n the classroom has become commonplace. Thus, an nterestng research queston s to nvestgate the relatonshp between the tme remanng to complete onlne quzzes and quz scores for sx sectons of Fnancal Management at The Unversty of North Florda. Gven the ncreased focus by the AACSB and others on student outcome assessments, t s mportant to nvestgate whether students retan and apply the knowledge learned throughout the semester and whether a webasssted testng approach s suffcently studentcentered to be used n ntroductory fnance courses n order to satsfy AACSB expectatons and requrements. The data consst of over 4,000 ndvdual quz scores for sx sectons of Fnancal Management taught between the Summer of 2004 and the Summer of The quz scores and tmes were manually collected from the Blackboard system. An ntal analyss of the data reveals that over 50% of the tme, students take onlne quzzes when they have less than 10% of the total tme allocated for the quz remanng. Moreover, students reduce the tme avalable to them for later quzzes as the semester progresses. Nevertheless, the average student allows hmself 20% of the total tme avalable to complete a quz. The average quz score s 72.84, wth a standard devaton of about 25 ponts. On average, students tend to fnsh takng a quz around 4:30 p.m., wth a hgh standard devaton of almost 5 hours. Also, dayclass students tend to take quzzes earler than ther nghttme counterparts. 8 Ths may ndcate that students n that decle may take the quz too early, before all the necessary class materal s covered. Student Performance, Page 17
18 A more ndepth look at the data reveals the followng. Frs the average quz score tends to ncrease for hgher quz numbers, ndcatng that students become more comfortable wth the materal as the semester progresses and become more accustomed to the process of takng a quz. Second, the most successful students take the quzzes after the materal has been covered n class, but shortly thereafter. Thrd, when quz scores are sorted nto decles based on the fracton of tme avalable to take a quz, those students who allow themselves less tme to complete a quz fnsh takng the quz at ngh whle those students who allow themselves more tme fnsh takng the quz n the late afternoon. Regresson analyss reveals some addtonal nterestng relatonshps. Frs there s a strong postve relatonshp between the tme remanng to take a quz and the quz score. For every addtonal 10% of the total tme avalable to take a quz, the quz score ncreases by approxmately 1.1 ponts, on average. Second, students perform better for hgher number quzzes, partcularly f they allow themselves a large amount of tme to take the quz. Thrd, students wth ether a low prevous average or a falng average contnue to perform poorly, whle those wth an already hgh average perform well on subsequent quzzes. Moreover, students who have a falng quz average and allow themselves relatvely lttle tme to complete a quz perform the worst. Fourth, the relatonshp between the prevous amount of tme students budgeted to take a quz and the current quz score s postve and margnally sgnfcant; students who managed ther tme more effcently prevously contnue to perform well. However, students who budgeted less tme for quzzes early n the semester beneft on the last quz by earnng a hgher quz score, possbly ndcatng that they have adjusted ther study habts by the tme of the last quz and/or realze that ths s ther last chance to mprove ther quz average. Ths s partcularly true for students who do not allow themselves a lot of tme to take the current quz, whch suggests that students who consstently leave themselves very lttle tme to take a quz learn how to operate better wthn the tme wndow they allocate themselves. Ffth, a regresson analyss based on tme fracton decles reveals that students who allow themselves the least amount of tme to take a quz could ncrease ther quz scores by about 12 ponts for every addtonal percentage pont of avalable tme they budget for themselves to take the quz. The results reported here are nterestng not only for Fnancal Management courses at The Unversty of North Florda, but offer some nterestng mplcatons for Fnancal Management courses across the country, snce these tend to be very smlar n content and nature. Furthermore, many of the fndngs reported here are also applcable to any project students have to complete on ther own (or n groups) outsde of the classroom. Gven the drastcally ncreasng use of technology n the classroom, tme management by students left to ther own devces and not forced to complete a quz wthn the classroom deserves addtonal analyss, but we hope the approach taken here offers some suggestons for future research n ths area. Student Performance, Page 18
19 References Benedc M.E. and J. Hoag Seatng locaton n large lectures: are seatng preferences or locaton related to course performance? Journal of Economc Educaton 35: Burns, D.J Anxety at the tme of the fnal exam: relatonshps wth expectatons and performance. Journal of Educaton for Busness 80: Chapman, K.J., R. Davs, D. Toy, and L. Wrght Academc ntegrty n the busness school envronment: I ll get by wth a lttle help from my frends. Journal of Marketng Educaton 26: Chrstensen, T.E., T.J. Fogarty, and W.A. Wallace The assocaton between the drectonal accuracy of selfeffcacy and accountng course performance. Issues n Accountng Educaton 17: Conte, J.M., J.E. Matheu, and F.J. Landy The nomologcal and predctve valdty of tme urgency. Journal of Organzatonal Behavor 19: Dellana, S.A., W.H. Collns, and D. West Onlne educaton n a management scence course effectveness and performance factors. Journal of Educaton for Busness 76: Doyle, J.M. and W.C. Wood Prncples course assessmen accredtaton, and the deprecaton of economc knowledge. Journal of Educaton for Busness 80: Edlng, R.J Informaton technology n the classroom: experences and recommendatons. CampusWde Informaton Systems 17: 10. Jadal, F Paperless classrooms. Tech Drectons 59: Krohn, G.A. and C.M. O Connor Student effort and performance over the semester. Journal of Economc Educaton 36: Okpala, A.O., Okpala, C.O., and R. Ells Academc efforts and study habts among students n a prncples of macroeconomcs course. Journal of Educaton for Busness 75: Pope, N. and Y. Ma Gradersk: an nsurable event n the classroom. Rsk Management and Insurance Revew 7: Prluck, R Webasssted courses for busness educaton: an examnaton of two sectons of prncples of marketng. Journal of Marketng Educaton 26: 161. Rabnowtz, A.M Success strateges for students. The CPA Journal 71: Student Performance, Page 19
20 Serwatka, J.A Assessment n onlne CIS courses. The Journal of Computer Informaton Systems 44: 16. Smth, A.D. and W.T. Rupp Manageral mplcatons of computerbased onlne/facetoface busness educaton: a case study. Onlne Informaton Revew 28: 100. Speer, C., I. Vessey, and J.S. Valacch The effects of nterruptons, task complexty, and nformaton presentaton on computersupported decsonmakng performance. Decson Scences 34: Speer, C., J.S. Valacch, and I. Vessey The nfluence of task nterrupton on ndvdual decson makng: an nformaton overload perspectve. Decson Scences 30: Stoel, L. and K.H. Lee Modelng the effect of experence on student acceptance of webbased courseware. Internet Research 13: Taylor, S.A., M. Humphreys, R. Sngley, and G.L. Hunter Busness student preferences: explorng the relatve mportance of web management n course desgn. Journal of Marketng Educaton 26: Webb, J.P Technology: a tool for the learnng envronment. CampusWde Informaton Systems 18: Wes T., S. Ravenscrof and C. Shrader Cheatng and moral judgment n the college classroom: a natural experment. Journal of Busness Ethcs 54: 173. Young, M.R., B.R. Klemz, and J.W. Murphy Enhancng learnng outcomes: the effects of nstructonal technology, learnng styles, nstructonal methods, and student behavor. Journal of Marketng Educaton 25: 130. Student Performance, Page 20
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