Medical Students' Online Compatibility


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Medical Students' Online Compatibility

  1. 1. Web-based Survey and Regression Analysis to Determine USAIM Students’ Online Compatibility – A Pilot Study Dr S. Sanyal MBBS, MS (Surgery), ADPHA, MSc (Health Informatics) Associate Professor, Faculty of Gross Anatomy and Neurosciences University of Seychelles American Institute of Medicine (USAIM), Seychelles Original research conducted in USAIM May 2008
  2. 2. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study COPYRIGHT AND DISCLAIMER Copyright NoticeAttention is drawn to the fact that copyright of this project rests with its author and USAIM. This copy ofthe project has been supplied on condition that anyone who consults it is understood to recognise that itscopyright rests with its author and USAIM, and that no quotation from the project and no informationderived from it may be published without the prior written consent of the author or USAIM. Restrictions on UseThis project may be made available for consultation within the USAIM Library and may be photocopied orlent to other libraries solely for the purposes of education, research and consultation. DisclaimerThe opinions expressed in this work are entirely those of the author except where indicated in the text. Disclosures and conflicts of interestThe author discloses no incentives, financial or otherwise, and no conflicts of interest during conduct of thisstudy and production of this treatise. Signature 2008-05-1 ****** USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 i
  3. 3. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study ACKNOWLEDGEMENTSThe author wishes to thank all those who helped in the research project and the production of this treatise,either directly or indirectly. The first and foremost is Dr Fauzia Alkhairy, MD; President of University ofSeychelles American Institute of Medicine (USAIM), Fort Wayne, Indiana, USA. Without her permissionthe whole project would not have taken off in the first place. Next are Mr Tariq Alkhairy, ManagingDirector of USAIM, and Dr Rana Shinde, PhD; Dean of USAIM, whose tacit support during the conduct ofthe student survey within the USAIM campus was invaluable. Thank you to all personalities.Then the author would like to thank the entire student body of USAIM for being such enthusiasticparticipants in the Web-based survey. Such was the enthusiasm that many students completed the surveyfrom home, from their personal Internet connections, due to paucity of time during regular college hours.Such a response was heart-warming, to say the least.Next the author would like to acknowledge the tacit cooperation of other staff members and colleagues inthe faculty, notably Dr Sanjay Kulkarni, MD, Department of Microbiology and Immunology, USAIM; hewas a great morale-booster during the process of the survey, by being there when it was needed most. DrJustin Gnanou, MD, Department of Biochemistry, USAIM, though he is no longer with us in USAIM,deserves special thanks for making the SPSS v.10 software package available to the author.There are two researchers who the author has never met. They are Franz Faul and Edgar Erdfelder of theDepartment of Psychology, University of Bonn, Germany. They deserve thanks in absentia for taking thepains to make the G*Power power analysis software package available free of charge to researchers all overthe world.The author also gratefully acknowledges M/s eLearners™Advisor for enabling the use of an adaptation oftheir questionnaire for the purpose of this Web-based survey.Finally, how can the author overlook the silent contribution of his lovely spouse? During the trying monthsof the project, she bore with his infrequent phone calls, taciturn monosyllabic responses and pre-occupationswith the project with silent fortitude and patient forbearing, which only the deep unspoken understandingcapabilities of a woman can bring forth. *********** USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 ii
  4. 4. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study TABLE OF CONTENTSTITLE PAGECOPYRIGHT AND DISCLAIMER Page iACKNOWLEDGEMENTS Page iiABSTRACT Page ivCHAPTER 1: PRELIMINARIES AND LITERATURE REVIEW Page 1 – 7CHAPTER 2: MATERIALS AND METHODS Page 8 – 15CHAPTER 3: STATISTICAL ANALYSIS AND RESULTS Page 16 – 40CHAPTER 4: DISCUSSION Page 41 – 57REFERENCES Page 58 – 61 USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 iii
  5. 5. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study ABSTRACTImmediate objective: To identify technical glitches (problems) in the newly-devised Web-basedquestionnaire and try to devise a future-proof system through troubleshootingShort term goals: (1) Determine USAIM students’ online learning preparedness against 5 set parameters;(2) Devise a mathematically objective scoring system for each parameter; (3) Determine overall onlinepreparedness (Compatibility Score) of USAIM students; (4) Determine robustness of LS questionnairecurrently being used for the study; (5) Identify relationships between students’ personal and generalcharacteristics vis-à-vis online learning; (6) Suggest improvements to questionnaire and survey; and (7)Suggest ways of overcoming barriers to online learningLong term goals: (a) Use Compatibility Score as baseline for future studies in USAIM and elsewhere; and(b) Render online learning and examinations a regular and feasible option for USAIMDesign: It was designed as a Web-based questionnaire survey of USAIM students. It was a one-shot, cross-sectional, non-experimental pilot study.Setting: The study was conducted within the campus of USAIM.Participants / Data sources: Thirty-five students from PC-1 to PC-5 were the participants. Their feedbackfrom the questionnaire provided the data for statistical analysisMain outcome measures: The following mathematical outcomes were generated: (A) Weighted scores fortechnology access parameters; (B) Weighted scores for personal parameters; (C) Weighted scores fortechnical proficiencies; (D) Weighted scores for online LS preferences; (E) Weighted scores for students’general considerations; (F) Overall Compatibility Score of USAIM students; (G) Correlation, internalconsistency and factor analysis scores of online LS questionnaire items; (H) Correlation and regressionanalysis scores of personal factors vs. general considerations; (I) Predictive model and formula of students’online learning characteristics; and (J) Power analysis scores vis-à-vis sample size.Results: Identification of 5 problems and their tentative solutions; Weighted scores (expressed as percentageof maximum) of measured parameters were; Type of Internet access (63.7%); Primary computer (80%);Motivation (70%); Schedule (58.5%); Hours of online study (57.8%); Technical proficiencies (73.9%);Online LS preferences (64%); Online concerns (64%); Education level (54.3%); Age (73.3%); OverallCompatibility Score of USAIM students (64%); Pearson’s correlations (‘Pro-Yes’ vs. ‘Anti-No’) r = 0.3; (p= 0.48; 2-tailed; N = 8); Reliability coefficients (Intra-class, Cronbach α, Guttman, Spearman-Brown) 0.42to 0.45; PCA factor analysis – Component-1 (‘Anti-onlineness’ factor); Pearson’s correlation (‘Concerns’vs. ‘Age’) r = -0.963; (p = 0.037; 2-tailed; N = 4); Regression analysis (‘Concerns’ vs. ‘Age’) ‘Concerns’ =80.261 – 0.898(‘Age’); Regression analysis (‘Concerns’ vs. ‘Motivation’) ‘Concerns’ = 80.261 +0.638(‘Motivation’); Predictive model ‘Concerns’ = Constant + [0.638(‘Motivation’)] – [0.898(‘Age’)]; Posthoc power analysis (N = 35) – Power = 0.43 (1-tailed), 0.30 (2-tailed); Compromise power analysis (N = 35)– Power = 0.77 (1-tailed), 0.68 (2-tailed); A priori analysis – Required N = 102 (1-tailed), 128 (2-tailed)Conclusions: Glitches in the Web-based questionnaire are attributable to excessive ‘hits’ on Google siteserver from a single user-session. Average online readiness and overall online Compatibility of USAIMstudents are in the ‘Good’ category. Learning style questionnaire needs to be re-structured. Thequestionnaire as a whole needs to be rendered more robust from research perspective. Online concerns ofstudents are directly proportional to their motivation and inversely proportional to their age. Subjectrecruitment for a formal study needs to be at least 3.7 times more than this pilot study. This would render theresults of a robust statistical analysis more valid. Overall, USAIM students are poised on the threshold ofintroduction of online courses and examinations. Once they are introduced, the natural progression oflearning curve would take care of the ongoing hurdles. *********** USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 iv
  6. 6. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study CHAPTER-1: PRELIMINARIES AND LITERATURE REVIEW “The voyage of discovery is not to seek for new landscape, but to install a pair of new eyes.” ~~Anon~~1. IntroductionImplementing online technologies towards imparting learning constitute the next big wave to hit theeducational arena, after the chalk and blackboard. This is not so surprising, considering the ubiquity ofcomputers, Internet and the inexorable progression of related technologies.[1] The Sloan Consortium (Sloan-C™) defines Online Courses as those where 80% or more of the course content is delivered online. Thereare usually no face-to-face (F-2-F) interactions between faculty and students. Other types of impartingeducation, based on decreasing proportion of course content delivered online are; Hybrid / blended Course(30-79% course content delivered online, there are both online discussions and face-to-face meetings); Web-facilitated Course (1-29% course content (assignment, syllabus etc) delivered through course managementsystem (CMS) or Web pages, uses Web technologies to facilitate an essentially F-2-F course deliveryprogram); and Traditional (no course content delivered online, only orally or in writing).[2]2. Models of online educationA radically different classification identifies 5 new ‘Models’ for online learning, aimed towards improvinglearning at affordable costs. In the Supplemental Model the basic structure of traditional course (number ofclass meetings etc) is retained; only some technology-based out-of-class activities are added to encouragegreater student engagement with course content. In the Replacement Model the key characteristic is areduction in class meeting time, replacing face-to-face time with online, interactive learning activities bystudents. The Emporium Model is based on the premise that a student learns best when he wants to learnrather that when the instructor wants to teach. This model therefore eliminates all class meetings andreplaces them with a learning resource center featuring online materials and on-demand personalizedassistance. In the Fully Online Model, the single-handed, monolithic, repetitive, labor-intensive task of aprofessor of traditional course has been transferred to the online scenario. This model assumes that theinstructor must be responsible for all interactions, personally answering every inquiry, comment ordiscussion. However, newer software systems have been developed (viz. Academic Systems software) thatpresent the course content so effectively that instructors do not have to spend any time delivering content.These 4 course-redesign models treat all students as same; therefore they represent ‘one-size-fits-all’approach. In contrast, the Buffet Model offers students an assortment of interchangeable paths that matchtheir individual learning styles (LS), abilities and tastes at every stage of the course. Even the best ‘fixed-menu’ of teaching would fail for some students. In contrast, the ‘buffet’ strategy suggests a large variety ofofferings that can be customized to fit the needs of the individual learner.[3]3. Growth of online education USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 1
  7. 7. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot StudyOver the last five years there has been a progressive increase in online courses in universities worldwide andin USA in particular. This increase pertains to all aspects educational continuum; in terms of numbers ofcourses being offered, number of colleges and higher education schools offering them, and numbers ofstudents enrolling for online courses, both in absolute terms as well as in proportion to those enrolling fortraditional courses. From 1.6 million online students in 1998 in the US, the number had escalated to 3.48million by 2006. [2,4] Among all colleges offering distance learning, the proportion using the Internet hadgrown from 22% in 1995 to 60% in 1998.[4] Overall, students in USA who were taking at least one onlinecourse in 2006 represented 20% of total enrollments in higher education. This represented a jump of nearly10% over 2005.[2] It is projected this growth will continue, albeit at a slower rate, into the future.[1,2]4. Advantages of online educationMore and more universities and colleges worldwide are jumping on the online bandwagon. The reasonscited by Sloan-C™ for adopting online courses, in order of importance are to; increase student access, attractstudents from outside traditional service areas, grow continuing and / or professional education, increase rateof degree completion, enhance value of college/university brand, provide pedagogic improvements, improvestudent retention, increase the diversity of student body, optimize physical plant utilization, improvementenrollment management responsiveness, increase strategic partnerships with other institutions, reduce /contain costs, and enhance alumni and donor outreach. Therefore these are the purported advantages ofonline education.[2] Improving student retention is a contentious issue. Statistics of Foothill College, LosAltos, CA showed that students in on-line computer classes had a drop rate of 30% compared to a drop rateof 10-15% in on-ground classes.[5] On the other hand, the University of North Carolina (UNC) School ofPublic Health has cited 10 essentially different reasons why online learning excels over traditionaleducation; Student-centred learning; Writing intensity; Highly interactive discussions; Geared to lifelonglearning; Enriched course materials; On-demand interaction and support services; Immediate feedback;Flexibility; Intimate learner community; and Faculty development and rejuvenation.[6] Here again there is anapparent contradiction. Low acceptance of online instruction by faculty has been cited as one of the barriersto online education.[2]5. The online frameworkIn terms of engagement in online courses and their attitudes towards same, institutions have been classifiedinto 5 categories by Sloan-C™. These are; (A) Fully engaged: those that have online courses that they havefully incorporated into their formal strategic long term plans; (B) Engaged: Those that have online course(s)that they believe are strategic to their long term plans but have not yet incorporated them into the formallong term strategy; (C) Not yet engaged: Those that do not have any online courses yet but believe theycritical to their long term strategy, and are therefore expected to implement some form of online courses inthe future; (D) Non-strategic online: Those that have some online course(s) but do not believe that it is USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 2
  8. 8. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Studyimportant for their long term strategy; and (E) Not interested: Those that do not have any online courses anddo not believe that it is important for their long term strategy.[2]6. USAIM in online frameworkThe University of Seychelles American Institute of Medicine (USAIM) is a pre-clinical medical school inSeychelles that was established in 2001. Commensurate with its progressive-minded philosophy it believesin adopting the latest technologies in imparting education. In collaboration with another organization,Boolean Education from Mumbai, India, USAIM introduced its online M.Ch (Orthopedics) Certificationprogram as part of its AACME-accredited (American Academy of Continuing Medical Education) CMEactivity (Figure-1). This is a 6-month course, 5 of which are entirely online, covering one module everymonth; and the sixth month includes a 3-day F-2-F Instructional Course Lecture Series (ICLS).[7] Thus, asper the Sloan-C™ definition (and according to its self-declaration) it is a Hybrid / blended course. But sincemore than 80% of the M.Ch Orthopedics certification course content is delivered online, it is closer to thedefinition of a true Online Course.[2] Apart from all examinations of M.Ch certification program, which arefully online, USAIM is also on the verge of introducing fully online and automated examinations for itsroutine Pre-clinical semesters (of which the author is an Associate Professor) on a regular basis. Therefore,since USAIM already has an online course and it has fully incorporated online activities into its formalstrategic long term plans, it conforms to Sloan-C™ categorization of a ‘Fully Engaged’ institution.[2]Figure-1: Screenshot from the Website showing online M.Ch Certification course offered by USAIM, Seychelles and Boolean Education, India7. Barriers to online learningIn spite of all the purported benefits and advantages of online course, they are not without their barriers.Some of the identified hurdles to widespread adoption of online learning are; students need to have moreself-imposed discipline in online courses, variable / low acceptance of online instruction by faculty, lowerstudent retention rate in online courses, high costs of developing online courses, high costs to deliver onlinecourses, and lack of acceptance of online degrees by employees. These are the identified barriers from the USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 3
  9. 9. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Studyinstitutional perspective. Not all these are barriers are given identical weightings by all institutions; in factsome institutions do not consider some of them as barriers at all.[2]Of arguably greater importance are those potential barriers that could be identified from the students’perspective. Eight barrier factors were determined by a factor analytic study in 2005; (a) administrativeissues, (b) social interaction, (c) academic skills, (d) technical skills, (e) learner motivation, (f) time andsupport for studies, (g) cost and access to the Internet, and (h) technical problems. Independent variables thataffected student ratings of these barrier factors included; gender, age, ethnicity, type of learning institution,self-rating of online learning skills, effectiveness of learning online, online learning enjoyment, prejudicialtreatment in traditional classes, and the number of online courses completed.[8]8. Background of present pilot studyThe findings from the aforementioned 2005 study provided the impetus to try to determine how many ofthose factors applied to USAIM students, and in what way, on the theoretical assumption that they were allto be enrolled for online courses in the near future. A more focussed search of the Web-based literature,based on the factors identified by the 2005 study, corroborated that technical skills, learner motivation, andaccess to Internet (technologies) were of special significance from the online learning perspective.[5,9,10]Another factor that had not been addressed in the abovementioned study pertained to students’ learning style(LS) preferences; more specifically their online LS preferences. And finally, prior academic skills and agealso have an indirect role in students’ online learning endeavours.[8-10]Technology access: Having access to technology (viz. computer and Internet) is to the online learner whatpen and paper is to the traditional student. For the former, computer and Internet access are the primaryinstruments of learning. Having to use a computer with inadequate computing power or an erratic / slowInternet connection can impede the online learner significantly. Consequently the capabilities of thetechnology used by the online learner, and access to the same, play important roles in the overall success inonline learning.[10]Self-motivation: Implicit within the structure of most traditional forms of learning is a certain level ofexternal motivation. Online learning is more loosely structured and relies more heavily on internalmotivation of the learner. They must schedule time for learning on their own and then stick to that schedule,not for external impositions by others but because they have to meet their self-imposed personal goals. Tothat extent they must be sufficiently internally motivated and must be able to put in sufficient numbers ofhours of self-study without exhortation from anyone.[5,8-10]Techno-skills: Technical skills are also a key factor in the success of an online learner. This does not implyadvanced computer skills. However, a minimum level of technical ability is essential, which can make allthe difference between success and failure. The determining factor in what constitutes this ‘minimum’ levelis simply having enough technical knowledge to ensure that the technology does not become a barrier in the USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 4
  10. 10. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Studylearning process. If the online student has to submit a paper electronically he/she should spend most of theirtime towards writing the paper and not figuring out how to attach the file to an outgoing e-mail.[10,11]Learning styles: Research has revealed that everyone has different preferences in how they learn. Thesepreferences are called ‘learning styles’ (LS). There is considerable confusion about the exact definition ofLS.[12] In one review there were 7 definitions / descriptions of LS. The most ‘accurate’ definition appears tobe that of Keefe, who described LS as characteristic cognitive, affective, and psychological behaviours thatserve as relatively stable indicators of how learners perceive, interact with and respond to the learningenvironment.[13] Grasha defined LS as personal qualities that influence a student’s ability to acquireinformation, to interact with peers and the teacher, and otherwise participate in learning experiences.[14]Theis described LS as a set of biological and developmental characteristics that make identical instructionfor learners either effective or ineffective.[15] LS pertains to a preference of the student. Some students findthat they have a dominant LS, which they utilise most frequently (or prefer to do so), and use other stylesless frequently. Other students find that they use different styles in different circumstances. Everyone has amixture of LS. There is no right mixture; nor are they fixed.[16] Some empirical evidence suggests thatlearners also have different preferences when it comes to online learning. Some prefer to learn throughlectures while others find that project-based learning better suits abilities and interests.[14,17] Knowing one’s‘online LS’ can be important in ensuring that they would select a style of online learning delivery (e.g.synchronous or asynchronous) in which they would excel.[10,18]Considering all these parameters, the present study was narrowed down to focus on 5 factors. Thesepertained to students’ access to technology, personal issues, technical competencies, online LS preferencesand some general aspects of students. Further perusal of the literature revealed several resources that hadconsidered some or all of these factors in determining students’ readiness for online learning.[10,19-24]Therefore these considerations formed the basis for the present study.It was decided to incorporate the parameters identified in the preceding paragraphs into a newly-devisedWeb-based questionnaire system. The details of creation of a Web-based questionnaire system are describedin the next chapter. It was decided to pilot this new Web-based system among the students of USAIM at thetime of conducting the survey. Therefore, the present study was actually based on two background issues;the issue of online compatibility of USAIM students, and the piloting aspect of a newly-introduced Web-based questionnaire system for the study. The two were to go hand in hand during the course of the study.9. Selection criteria for questionnaire – based on literature reviewThe survey instrument (questionnaire) and the questions themselves had to conform to the requirements ofthe study that had been planned, apart from fulfilling the precepts of a good questionnaire (described inChapter-2). Therefore a set of parameters and a scoring system was applied to the various surveyinstruments that were available. The parameters were; (a) Number of question items: Between 30 and 40 was USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 5
  11. 11. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Studyconsidered ideal (reason described in Chapter-2 and Chapter-4); therefore it scored 1 point, anything lessscored 0; (b) Ease of administration: This depended on the format and presentation of the questionnaire,whether script-based or plain .doc format; (c) Easy questions referred to the wording, sentence construction,user-friendliness and ease of understanding; it was graded from 1+ to 5+; (d) Mixed response items referredto bimodal (Yes/No), scaled (Very/Somewhat/Not) or multi-option question items. Question items shouldnot ideally be mixed too much (elaborated under ‘Discussion’); (e) Dimensions referred to all the groupsdescribed earlier; whether they were deficient or whether there were any extra groups in the questionnaire.Each dimension scored 1 point; absence scored negative point(s); (f) Scoring method and interpretation ofresults: If it was automatically performed by the parent organization, it was better than manual scoring; (g)Validity: This referred to the accuracy (how accurately it measures what it is purported to measure) orotherwise of the items in the questionnaire; ideally questionnaire items should be independently peer-validated. Based on the overall score, the questionnaire from eLearners™Advisor[10] was selected for thisstudy because it scored the maximum points (Table-1). The questionnaire was not being piloted; rather theWeb-based system that was being introduced for the first time was being piloted. Pace AASU OLE eL DVC ION DuPaNumber of Qs items 31 (1) 35 (1) 23 (0) 40 (1) 32 (1) 12 (0) 10 (0)Ease of administration Yes (1) No (1) Yes (1) Yes (1) No (0) Yes (1) Yes (1)Easy Qs items 5+ 3+ 2+ 4+ 1+ 4+ 4+Mixed response options No (1) No (1) No (1) Yes (0) No (1) No (1) No (1)No. of dimensions 4 3 4 5 0 0 0Extra dimension(s) Time Mx None (0) None (0) None (0) ? ? ? (1)Deficient dimension(s) LS, Gen (- Personal, Gen (-1) None (0) ? ? ? 2) Gen (-2)Scoring method Self (0) Parent Parent org Parent org Parent org Parent Self (0) org (1) (1) (1) (1) org (1)Automatic result No (0) Yes (1) Yes (1) Yes (1) Yes (1) Yes (1) No (0)interpretationInstrument self-validated Yes (1) Yes (1) Yes (1) Yes (1) Yes (1) Yes (1) Yes (1)Instrument peer-validated No (0) No (0) No (0) No (0) No (0) No (0) No (0)Total score 12 10 10 14 6 9 7Table-1: Score for each parameter is given in parenthesis and colored green; See text for details.Pace[24]; AASU[19]: Armstrong Atlantic State University; OLE[20]:™; eL[10]: eLearners™Advisor(acknowledged in ‘Acknowledgements’ section); DVC[21]: Diabolo Valley College; ION[22]: Illinois Online Network, Universityof Illinois; DuPa[23]: College of DuPage10. Objective and goals of studyThe immediate objective of the pilot study was to identify technical glitches (problems) in the newly-devised Web-based questionnaire survey system and try to devise a future-proof system throughtroubleshooting. During the course of this pilot, the following additional goals were fulfilled. Thesepertained to the online compatibility issue alluded to earlier. 1. Determine USAIM students’ online learning preparedness against 5 set parameters 2. Devise a mathematically objective scoring system for each parameter 3. Determine overall online preparedness (Compatibility Score) of USAIM students 4. Determine robustness of LS questionnaire currently being used for the study USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 6
  12. 12. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study 5. Identify relationships between students’ personal / general characteristics vis-à-vis online learning 6. Suggest improvements to questionnaire and survey 7. Suggest ways of overcoming barriers to online learning 8. Use Compatibility Score as baseline for future studies in USAIM and elsewhere (long term goal) 9. Render online learning and examinations a regular and feasible option for USAIM (long term goal)11. Study outcomes measuredThe following mathematical outcomes were generated:A. Weighted scores for technology access parametersB. Weighted scores for personal parametersC. Weighted scores for technical proficienciesD. Weighted scores for online LS preferencesE. Weighted scores for students’ general considerationsF. Overall Compatibility Score of USAIM studentsG. Correlation, internal consistency and factor analysis scores of online LS questionnaire itemsH. Correlation and regression analysis scores of personal factors vs. general considerationsI. Predictive model and formula of students’ online learning behaviour characteristicsJ. Power analysis scores vis-à-vis sample size12. Summary and usefulness of researchThis preliminary chapter provided the introduction, background information and current status of on onlineeducation, provided the background of USAIM, its role in online education, the basis of this study, therationale behind questionnaire selection, and the objectives, goals and expected outcome measures from thisstudy. This research would be useful from a number of perspectives. It would tell us how the innovatively-designed Web-based survey system performs. It would provide baseline data about USAIM students’ onlinelearning potential; the so-called ‘Compatibility Score’. It would identify deficiencies or lacunae in studentsthat would require to be addressed. The Web-based nature of the survey itself would inform us aboutstudents’ online potentialities. If they can successfully undertake the online survey, it would automaticallymean they possess basic online skills. Finally it would pave the way for implementation of future onlinecourses and examinations in USAIM. The next chapter would describe the methodology involved in creatingthe Web-based questionnaire and its pilot administration to students of USAIM during the course of survey. *********** USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 7
  13. 13. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study CHAPTER-2: MATERIALS AND METHODS "Dont be afraid to take a big step. You cant cross a chasm in two small jumps." ~~David Lloyd George~~1. IntroductionFollowing up from the selection of questionnaire that was described in the previous chapter, this chapterdescribes the contents and structure of the questionnaire, the method of creation of the new Web-basedsurvey system (and troubleshooting its attendant glitches), piloting the Web-based questionnaire andconducting the survey to its successful conclusion. The quotation from David Lloyd George aptly reflectsthe ethos of this chapter insofar as it relates to the Web-based questionnaire itself.2. Survey preliminariesThis study was conducted in USAIM, Seychelles from February 2008 to March 2008. A preliminary roundof discussions with the President, Managing Director and Dean of USAIM culminated in their collective andtacit approval for the study. This was followed by submission of the study proposal in the form of apreliminary abstract, which was accepted by the Dean. Then a notice was inserted in the student noticeboard, detailing the purpose, scope and depth of the study, and the approximate time it would take tocomplete the questionnaire. It also contained an FAQ to clear common anticipated doubts and allayapprehensions. It was stressed that there were no wrong or right answers so that students would respondhonestly, without any misgivings. The students were also informed that all results would be statisticallyaggregated and no individually identifiable data would be asked for or displayed. Informed consent of studyparticipants was implicit.3. Study design, setting, participants and data sourcesThe study was conducted within the campus of USAIM. It was designed as a Web-based questionnairesurvey of USAIM students. It was a one-shot, cross-sectional, non-experimental study, with data collected ata single point in time to reflect a cross-section of the current student population. Therefore the currentstudents from PC-1 to PC-5 were the participants. There were 35 students at the time of conducting thesurvey, all of whom were included in the study. Their feedback from the questionnaire provided the data forstatistical analysis.4. QuestionnaireIt was decided at the outset that, unlike the previous surveys conducted by the author in USAIM, which werepaper-based, this study would utilize a Web-based questionnaire.[25,26] There were several reasons for this.Firstly, the study itself was about students’ online preparedness. Therefore it made logical sense to haveWeb-based questionnaire. If the students could access and answer the questions online, it would be asignificant reflection on their online capabilities. Secondly, online questions are easy to administer, lesstime-consuming, more efficient, and are eco-friendly insofar they do not entail any usage of paper.[25] USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 8
  14. 14. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot StudyThirdly, the software in the online system allowed automatic percentage calculation, thereby reducing thetime and effort required to manually perform the same.The contents of the questionnaire were selected from several questionnaires that were available on the net,which had been used to test for students’ online preparedness.[10,19-24] The selection criteria for thequestionnaire was described in Chapter-1. Forty questions were selected and sorted into 5 matches for onlinelearning question groups; numbered sequentially from A to E. Group A had 2 questions pertaining totechnology access. Group B had 3 questions pertaining to personal facts (insofar as they impacted thestudents’ online learning capabilities). Group C had 16 technical proficiency-related questions. Group Dcontained 16 questions to determine students’ learning style (LS) preferences. Eight questions in this groupwere worded in such a way that a ‘Yes’ response indicated pro-online LS preference. The other 8 reflectedanti-online LS preference. The pro-online and anti-online LS preference questions were alternately arrangedin Group D. Finally group E contained 3 questions of a general nature. All questions had provision for onlyone answer except the question about motivation for online learning (first question in group B), whichpermitted students to upload up to 3 options. Appendix-1 gives a sample of the questionnaire. The purposebehind adapting the questionnaire from existing ones rather than creating a fresh questionnaire from scratchwas these had already been tried and tested on student populations elsewhere; i.e. they were self-validated, ifnot entirely peer-validated. This obviated the time-wastage on piloting the questionnaire itself, which anewly-generated questionnaire would have entailed.[26,27]4.1 Precepts of good questionnaire-designWhile preparing the questionnaire, every effort was made to keep within the principles of goodquestionnaire design, both paper and Web-based.[27-30] It was within 2 pages, as per the stipulations of goodquestionnaire.[27] Estimated time of completion was not more than 20 minutes. It had 40 questions,[30] witheasy wordings and user-friendly sentence constructions. All required single option selection except thirdquestion, which required up to 3 selections. Sixteen question-options were ranked (Very / Some / None) and16 had bimodal (Yes / No) options. Among the rest, the number of available options ranged from 3 to 5.There were no open-ended questions, as advocated by some.[27] Though strictly not within the rule,differently ranked questions were somewhat mixed.[27] At the outset, a short introduction mentioning thebackground and aims of the evaluation was given. Users were told what to expect so that they would bementally prepared and were informed that they would be anonymous.[30] The questions had been pilotedelsewhere; that was one of main reasons for their selection. Therefore it was not considered necessary for theauthor himself to pilot the questionnaire again, as suggested by some.[26,27] There were certain drawbacks inthe questionnaire that have been discussed in Chapter-4.5. Generating a Web-based questionnairePerlman described Web-based questionnaire creation using customizable Web-based PERL (PracticalExtraction and Report Language) CGI (Common Gateway Interface) script. It was based on established USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 9
  15. 15. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Studyquestionnaires and automated the process of data collection. It was hard to completely customize,questionnaire terminology did not closely match the required domain for this study and there were noanalysis tools.[25] Therefore, a different technique was employed in this study. The Google-based blog-site;URL: was used as the platform for creating the Web-based questionnaire surveysystem. A new blog-site was created in February 2008. First, an introduction to the survey and USAIM logo(Figure-1a); and essentially a repetition of the earlier paper-based instructions (Figure-1b), was entered inthe main ‘Blog Posts’ box (Figure-1c). In the main blog posts page, below the ‘Blog Posts’ box was anoption; ‘Add a Page Element’ (Figure-1c). Clicking on this opened a dialog box that enabled one to ‘Createa poll’ (Figure-1d). This allowed entry of a question followed by as many answer-options as desired, set thelimit of selection of options (single / multiple options), and also set the time limit for the poll (Figure-1d).Clicking on the ‘Save’ button of ‘Create a poll’ dialog box saved the question in the ‘Page Element’ sectionof the main blog page. Forty of these poll-creating ‘Page Elements’ were added in succession to constitute40 questions of the questionnaire. For each question the student had to select one of the options through theradio buttons and click ‘Vote’ in order to save his/her poll (Figure-1e). The process had to be repeated foreach of the 40 questions. Clicking on the ‘Show results’ link for any question (Figure-1e) revealed thepercentage scores for that question (Figure-1f). The blog-site was published for public viewing. The authorpersonally accessed the blog-site and checked it several times for usability; till opening, loading andrefreshing of the page elements was satisfactorily achieved, and all buttons, options and links were found tobe successfully operating. Finally, The URL: was madeavailable to the students through a general notice.[30]a b USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 10
  16. 16. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Studyc de fFigure-1a,b: Shows creation of a blog post for the online survey, with USAIM logo, introduction and instructions for the survey; Figure-1c,d: Shows method ofcreating an online question (with options) through the ‘Create a poll’ dialog box. Figure-1e,f: Shows the resultant online questionnaires and responses by studentsautomatically expressed as percentage of total respondents.6. Sequence of surveyAfter the preliminary notice, the URL of the blog-site containing the survey was released to the students andthey were given 2 weeks to complete the questionnaire. Throughout the release period the author regularlyvisited the site to keep track of the numbers of students responding to the questionnaire. Moreover, theresearcher was always available to solve doubts, queries and troubleshoot glitches. After 1 week a remindernotice was issued for those who had not visited the site or attempted the survey. After all students hadcompleted the questionnaire, the author visited the site and manually extracted the percentage scores foreach option (through the ‘Show results’ link) for each question, which had been automatically calculated bythe blog-site server. The raw data were entered on an MS® Excel® worksheet and tabulated for furtheranalysis. The result scores were analyzed with a specific view towards arriving at the stated goals of thestudy. This is detailed in the next chapter. At the conclusion of the analysis, a summary of the aggregatedresults, without identifying anybody, and USAIM students’ online Compatibility Score was put on thestudent notice board for everybody’s information.7. Troubleshooting technical glitches in Web-based questionnaireThis was a study to pilot the newly-devised Web-based questionnaire, and identify the technical glitches inthe system. They required ongoing identification and correction throughout the process of the survey. In USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 11
  17. 17. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Studyfact, it was part and parcel of the survey process itself. Therefore it is apt to describe the glitches and themeasures taken to circumvent them in this chapter itself. Technical explanations are dealt in Chapter-4.Several glitches were encountered that required ongoing attendance. Firstly, the full blog-site page requiredconsiderable time to open fully, after numerous (~ 40) ‘clicking’ sounds. This was because each questionwas entered as a separate poll in a separate page element in the blog-site, as per the feature of that site.Therefore during opening of the page, each question (element) required a separate response from the siteserver. There was nothing that could be done about this, except to warn the students about this andencourage patience. Secondly, the most serious problem encountered was the en masse error message, “Thispage cannot be displayed”, corresponding to each question, even though the Internet connection was stable.This occurred when several students simultaneously tried to access the site from different machines on theUSAIM server. Investigation revealed that the Google server, which was the main site server for the blog-site, interpreted these simultaneous hits as suspected virus attacks on its server, and therefore tried to shutout the USAIM server. Therefore, perforce the students had to access the site one at a time when they werewithin the USAIM network. The third problem was when students tried to progress rapidly through thequestions; after certain time, the last few questions tended to display the same error message, possibly as aresult of the same erroneous interpretation by the Google server. A fourth situation, similar to the previous,was encountered when students clicked on the ‘Vote’ button and, without waiting for the page to refresh,progressed to the next question and clicked on its option radio-button. The same error message wasdisplayed. Therefore the students had to be told to progress through the questions at a moderate, but not toorapid, pace. They were instructed to wait for the page to refresh after each ‘voting’. Another problem wasencountered when one student immediately followed the next (usually, but always, on the same machine).The page used to open with the questions displayed in the post-voting mode of the previous student, askingif the student wanted to change his poll opinion. If the next student clicked on this, the page got refreshedbut the previous student’s response got erased. This also required that there should be a sufficient time gapbetween two students’ access to the blog-site. Because of these problems many students had to complete thequestionnaire in more than one sitting. Not all students encountered all these problems, however. Quite afew managed to complete the whole questionnaire without encountering a single glitch, especially those whoaccessed it from home on their personal laptops through their own Internet connection provided by theirpersonal ISP.8. ConclusionThree aspects of this study were covered in this chapter. Firstly, the nuts and bolts of the whole surveyprocess (questionnaire, Web-based system and the survey proper) were exhaustively described. Secondly, itdescribed the fulfilment of the immediate objective of this study, namely to assess the functioning andidentify the problems in the newly-devised Web-based system. Thirdly, the process described herein led tothe generation of data that led to the fulfilment of other goals of this study. These are discussed in Chapter-3. *********** USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 12
  18. 18. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot StudyAPPENDIX-1: Text of the online questionnaire hfT` fàâwxÇàáË bÇÄ|Çx fâÜäxç dâxáà|ÉÇÇt|ÜxAvailable at URL: (Totally 40 questions)Q1) What type of Internet access will you have at home during your online studies?No AccessDial-up/Modem AccessHigh-Speed/Wireless AccessQ2) Please select the option that best describes the primary computer you will be usingPurchased 1 - 2 years agoPurchased 3 - 4 years agoPurchased > 4 years agoI plan to buy a new PC soonIm unsure what PC I will useQ3) Which of the following would be your motivation(s) for undertaking the online course? (Select up to 3)A) It seems like the fastest and easiest way to studyB) To increase my earning potential in my future careerC) To qualify for a good position or careerD) A personal interest or goal (I like this method of learning)E) Outside influences rather than my own goals or needs (My lecturer is telling me to do it!)Q4) My schedule is...A) Predictable (I can devote regular blocks of time for online study)B) Somewhat Unpredictable (My schedule changes often, but I can usually put in some time for online study)C) Very Unpredictable (My schedule is rarely the same; however, I shall see what I can do)Q5) Each day I could dedicate the following number of hours for online study:A) 1 to <2B) 2 to <3C) 3 to <4D) 4 to <5E) 5 or moreQ6) Fast and accurate typing on a computer keyboardA) Very skilledB) Some skillsC) No skillsQ7) Open files saved on a floppy disk, hard drive or CDA) Very skilledB) Some skillsC) No skillsQ8) Save a file with a new name, file type or file locationA) Very skilledB) Some skillsC) No skillsQ9) Copy, cut and paste text/files between windows/programsA) Very skilledB) Some skillsC) No skillsQ10) Format fonts and document layout using a word processorA) Very skilledB) Some skillsC) No skillsQ11) Insert a picture/object into a word processing documentA) Very skilledB) Some skillsC) No skillsQ12) Solve basic computer problems (e.g. computer freezes)A) Very skilledB) Some skillsC) No skillsQ13) Learn new software programs or applicationsA) Very skilledB) Some skillsC) No skillsQ14) Visit a web site (if you are given the address/URL)A) Very skilledB) Some skillsC) No skills USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 13
  19. 19. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot StudyQ15) Send and receive e-mail messagesA) Very skilledB) Some skillsC) No skillsQ16) Send and receive attachments/files through e-mailA) Very skilledB) Some skillsC) No skillsQ17) Use search engines to find answers and resourcesA) Very skilledB) Some skillsC) No skillsQ18) Use "message boards" or "forums" or "newsgroups"A) Very skilledB) Some skillsC) No skillsQ19) Use a "chat room" or "instant messaging"A) Very skilledB) Some skillsC) No skillsQ20) Download and install software or a "plug-in"A) Very skilledB) Some skillsC) No skillsQ21) Protect your PC from threats (viruses, spyware, hackers)A) Very skilledB) Some skillsC) No skillsQ22) Socializing with my classmates is important for my educationA) YesB) NoA) YesB) NoQ23) I am comfortable building online relationships and networking online.A) YesB) NoQ24) I always need to share my knowledge, thoughts and experiences with others.A) YesB) NoQ25) I am a disciplined student and I can usually stick to my study plan.A) YesB) NoQ26) I have difficulty completing assignments on time, and sometimes need extension dates.A) YesB) NoQ27) I prefer to learn through independent projects instead of structured assignments.A) YesB) NoQ28) I prefer lecture-based learning rather than discussion-based / project-based learningA) YesB) NoQ29) I have decent computer reading speed and I can learn well that way.A) YesB) NoQ30) I do not participate much in group discussions unless specifically called upon to do so.A) YesB) NoQ31) I prefer working alone on assignments instead of in study-groups.A) YesB) NoQ32) I prefer verbal discussions rather than submitting my ideas in writing.A) YesB) NoQ33) I prefer structuring my own projects instead of being given specific directions. USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 14
  20. 20. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot StudyA) YesB) NoQ34) I prefer hearing verbal explanations instead of reading written ones.A) YesB) NoQ35) I have good writing skills and can effectively communicate my ideas in writing.A) YesB) NoQ36) I am much more comfortable communicating face-to-face rather than with email.A) YesB) NoQ37) I am good at structuring my own learning; independent study courses are right for meQ38) What is your age?A) <18 yearsB) 18 to <19 yearsC) 19 to <20 yearsD) 20 to <21 yearsE) = or > 21 yearsQ39) What is the highest level of education that you have completed till date?A) Class 10 or equivalentB) High school (10 + 2)C) Some college courses (e.g. Pre-med)D) Bachelor’s degreeQ40) Do you have any concerns about the quality of online courses?A) No concerns at all (Hey, cool man!)B) Some concerns (I’m just a wee bit worried!)C) Many concerns (Gee, I’m highly worried!!)D) Unimaginably concerned (It ain’t for me dude!) ******************* USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 15
  21. 21. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study CHAPTER-3: STATISTICAL ANALYSIS AND RESULTS “You are never granted a wish without the power to make it come true. You have to work for it, however.” ~~Anon~~1. IntroductionContinuing from the data collection described in the previous chapter, this chapter deals with univariate andbivariate statistical analysis of the data and the output generated there from. The results of the surveypertained to four broad set of student-specific parameters that were considered relevant for online learning.These were; technical access parameters (type of Internet access, primary computer that would be used foronline courses); personal parameters (motivation for online learning, scheduling ability for same, ability todevote certain numbers of hours of self-study per day); technical proficiency (which included 16 items);learning style preferences insofar as they pertained to online learning (which also included 16 items); andgeneral considerations (concerns about online learning, previous education levels, age groups).A. UNIVARIATE STATISTICS2. Weightings and score-generationAll results were collected as percentages of students responding to various item-options in each question. Inorder to render the crude percentage results more meaningful, they were fitted into a scoring system.[10,23]Moreover, since each options for the questions were not of equal importance, there also has to be logicalweighting system for the options, based on their relative importance.[10] Each item of the parameters understudy was given a weighting factor that ranged from ‘0’ to ‘5’. ‘0’ was the weighting for the response thatwas not at all useful, and ‘5’ weighting was allotted to the most important response-option in the onlinelearning context. The intermediate weightings ranged sequentially between the two extremes, depending ontheir relative order of importance from online learning point of view. However for each parameter the actualweighting range was variable; some had ranges 0-3, others had ranges 0-4, 0-2 1-3, 1-4 or 1-5, etc;depending on the number of response-options for that parameter.3. Technology access parameters3.1 Type of Internet accessThis parameter pertains to type, speed and bandwidth of Internet connection that students would have fortheir online course. The weighting for items in this parameter ranged from ‘0’ to ‘3’; ‘0’ being for ‘Noaccess’ and ‘3’ being for ‘High-speed / Wireless access’, this latter being considered ideal for onlinecourses.[11] ‘Cable modem’ and ‘Dial-up’ received weightings of ‘2’ and ‘1’ respectively, the former beingconsidered superior to latter. Slightly less than half (48%) of the students had access to high-speed orwireless Internet at home. The weighted score collectively secured by the students for this parameter was191, out of a theoretical maximum (Max) of 300. This worked out to 63.7% of Max for the parameter ‘Typeof Internet access’ (Table-1, Figure-1). USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 16
  22. 22. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study 60 Type of Internet AccessType of Internet access % W P Max 50No Access 19 0 0 48 40Dial-up modem Access 19 1 19 % Stuudents 30Cable modem access 14 2 28High-Speed/Wireless Access 48 3 144 300 20 19 19Total 100 191 300 10 14Final score 63.7% 100% 0Table-1: Shows percentage of students with various types of Internet No Access Dial-up modem Access Cable modem access High-Speed/Wireless Type of Access Accessaccess at home. The items have been weighted (W) from 0 to 3 based ontheir relative importance. Next column gives the product (P) of previous 2 columns, the collective score for this parameter and the % of maximum (Max) possiblescore. Figure-1: Shows histogram of percentages of students with various types of Internet access at home for online studies.3.2 Primary computerThis parameter refers to the main computer that students claimed they would use at home for their onlinecourses. Weightings for items in this parameter ranged from ‘0’ (those who were unsure which PC to use) to‘4’ (those possessing latest PCs). Older PCs secured lesser weightings. Two-thirds (68%) of the students hadpurchased their primary computer within the last 1 or 2 years. The collective weighted score for thisparameter was 320, out of a theoretical Max of 400, giving students a score of 80% of Max for theparameter labelled as ‘Primary computer’ (Table-2, Figure-2). 80 Duration of Primary ComputerPrimary computer % W P Max 68 70Purchased 1 - 2 years ago 68 4 272 400 60Purchased 3 - 4 years ago 11 3 33 50Purchased > 4 years ago 5 2 10 % Students 40Plan to buy new PC soon 5 1 5 30Unsure what PC to use 11 0 0 20 11 11Total 100 320 400 10 5 5Final score 80% 100% 0 Purchased 1 - 2 Purchased 3 - 4 Purchased > 4 years I plan to buy a new Im unsure w hat PC ITable-2: Shows percentage of students with various types of years ago years ago ago PC soon w ill useprimary computer at home for online studies. The items have Durationbeen weighted (W) from 0 to 4 based on their relativeimportance. Next column gives the product (P) of previous 2 columns, the collective score for this parameter and the percentage of maximum (Max) possiblescore. Figure-2: Shows histogram of percentages of students with various types of primary computer at home for online studies.4. Personal parameters4.1 MotivationThis was considered as the single most important parameter under personal factors, which has the capacityto determine whether a student would be able to pursue an online course successfully or not.[5,8-11,24] Theweightings employed for items in this parameter were thus; ‘Outside influences’ carried ‘0’ weight becausethey were not students’ internal motivations. ‘Personal interest’ carried the maximum weight of ‘2’ for theconverse reason. Other response items (‘Fast easy learning’, ‘Earning potential’, ‘Good position’) wereequivocal response-options; they may or may not be applicable to a given situation. Therefore they could allbe considered as motivations under certain, but not all, circumstances. They carried a uniform weighting-factor of ‘1’ each. Personal interest was the most frequent (50%) motivating factor for pursuing onlinestudies. One-third or more (33% - 44%) cited other reasons also, because students were permitted to tick upto three response options in this parameter. A small proportion (16%) admitted being influenced by outsidesources, viz. lecturers. The collective weighted score for this parameter was 210, out of a theoretical Max of USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 17
  23. 23. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Study300, giving them a score of 70% for the parameter labelled as ‘Motivation’ to pursue online courses, as oneof the personal factors (Table-3, Figure-3).Motivation % W P Max 60 Motivation for Online StudyFast, easy learning 44 1 44 100 50Earning potential 33 1 33 100 50 40 44Good position 33 1 33 100 % StudentsPersonal interest 50 2 100 200 30 33 33Outside influences 16 0 0 0 20Total * 210 300 16 (3/5 of 500) 10Final score 70.0% 100% 0*Students were permitted to tick up to 3 choices Fast, easy learning Earning potential Good position Personal interest Outside influencesTable-3: Shows percentage of students with various Motivating Factorsmotivating factors for online studies. The items have beenweighted (W) from 0 to 2 based on their relative importance (see text). Next column gives the product (P) of previous 2 columns, the collective score for thisparameter and the percentage of maximum (Max) possible score. Max of 300 for this parameter was computed as three-fifths of 500 (3/5 x 500), because studentswere permitted to tick up to a maximum of 3 response-options. Figure-3: Shows histogram of % of students with various motivating factors for online studies.4.2 ScheduleThis parameter, also under personal factors, refers to how predictably students could devote a fixed numberof hours of self-study at home during their online course. Ability to maintain predictable hours of study wasalso considered important for successful online studies.[10,11,24] Therefore the weighting scheme for items inthis parameter, which ranged from ‘0’ to ‘2’, was straightforwardly based on this aspect of the schedule,with ‘0’ for ‘Unpredictable’ ‘1’ for ‘Somewhat unpredictable’ and ‘2’ for ‘Predictable’ study schedules.Somewhat less than half (47%) admitted that they had somewhat unpredictable schedules insofar as itpertained to devoting notional self-study time for online course. However, more than one-third (35%)indicated they had the ability to maintain predictable study hours. The collective weighted score for thisparameter was 117, out of a theoretical Max of 200, giving them a score of 58.5% of Max for the parameterlabelled as ‘Schedule’ to pursue online courses (Table-4, Figure-4). Schedule for Online StudySchedule % W P Max 50 45Predictable 35 2 70 200 47 40Somewhat unpredictable 47 1 47 35 35Unpredictable 18 0 0 30 % StudentsTotal 100 117 200 25 20Final score 58.5% 100% 15 18Table-4: Shows percentage of students with predictability of 10various schedules for online studies. The items have been 5weighted (W) from 0 to 2 based on their relative importance. 0Next column gives the product (P) of previous 2 columns, the Predictable Somew hat unpredictable Unpredictablecollective score for this parameter and the percentage of Prdictabilitymaximum (Max) possible score. Figure-4: Shows histogramof percentage of students with predictability of various schedules for online studies.4.3 Hours of online studyThis parameter pertains to the number of hours that students can devote daily as part of their online studies.A 3-credit course requires 9 to 12 hours (some say 10 to15 hours) of study per week.[10,11,24] The options inthis study pertained to numbers of hours/day; the rationale being those who could study more hours/daywere more likely to complete their scheduled weekly credits. The weighting for this parameter ranged from‘5’ (capable of 5+ hours of study/day) to ‘1’ (capable of 1-2 hours/day). Majority (42%) of students statedthey could devote 3-4 hours of online study/day. About one-third (32%) could devote 2-3 hours/day. Since USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 18
  24. 24. Web-based Survey and Analysis of USAIM Students’ Online Compatibility – Pilot Studyno student could put in 5+ hours, it was considered realistic to peg the Max possible score for this parameterat 400. The collective weighted score for this parameter was 231; considered out of a Max of 400, it gave ascore of 57.8% for the parameter labelled as ‘Hours of online study’ per day (Table-5, Figure-5). Hours of Online Study PossibleHours of online study % W P Max 451 to <2 21 1 21 40 42 352 to <3 32 2 64 30 323 to <4 42 3 126 25 % Students4 to <5 5 4 20 *400 20 215 or more 0 5 0 15Total 100 231 400 10Final score 57.8% 100% 5 5 0 0Table-5: Shows percentage of students capable of various 1 to <2 2 to <3 3 to <4 4 to <5 5 or morehours of online study per day. The items have been Hours / dayweighted (W) from 1 to 5 in ascending order ofimportance. Next column gives the product (P) of previous 2 columns, the collective score for this parameter and the percentage of maximum (Max) possiblescore. [*Since no student could put in the maximum number of hours as per the response items, it was considered realistic to consider the next highest (400) as themaximum possible score.] Figure-5: Shows histogram of percentage of students capable of various hours of online study per day.5. Technical proficiencyThis parameter considered 16 items to determine how proficient the students were in handling computers.They had to grade their capability for each item in terms of ‘Very skilled’, ‘Some skills’ and ‘No skills’.Therefore it was logical to allocate weights of ‘2’, ‘1’ and ‘0’ respectively to each of these skill levels,according to a modified Likert scale. Students proved to be most proficient in visiting Websites andEmailing messages; achieving weighted scores of 98% in each. Using search engines scored 90%. Theywere moderately weak in downloading / installing software (58%), and protecting PCs from virus (60%).Using message board and basic problem-solving was their Achilles heel; achieving only 48% and 50%weighted scores respectively. There were very few items where students professed no skills; they were thesame two items that was their Achilles heel (24% and 23% respectively). The collective weighted score forthis parameter was 2366, out of a theoretical Max of 3200, giving them a score of 73.9% for the parameterlabelled as ‘Technical proficiencies’ to pursue online courses (Table-6, Figure-6). Very W1 Score1 Some W2 Score2 No W3 Score3 Σ Score Max % skilled skills skills (%) (%) (%)Keyboard typing 32 2 64 58 1 58 10 0 0 122 200 61%Opening files 53 2 106 47 1 47 0 0 0 153 200 77%Saving files 72 2 144 28 1 28 0 0 0 172 200 86%Copying-pasting files 63 2 126 32 1 32 5 0 0 158 200 79%Formatting document 47 2 94 47 1 47 6 0 0 141 200 71%Inserting picture/object 70 2 140 20 1 20 10 0 0 160 200 80%Basic problem solving 23 2 46 54 1 54 23 0 0 100 200 50%Learning new software 42 2 84 48 1 48 10 0 0 132 200 66%Visiting website 95 2 190 5 1 5 0 0 0 195 200 98%Emailing messages 95 2 190 5 1 5 0 0 0 195 200 98%Attaching files to msgs 73 2 146 27 1 27 0 0 0 173 200 87%Using search engines 80 2 160 20 1 20 0 0 0 180 200 90%Using message board 19 2 38 57 1 57 24 0 0 95 200 48%Using chat room 59 2 118 36 1 36 5 0 0 154 200 77%Download/install software 33 2 66 50 1 50 17 0 0 116 200 58%Protecting PC from virus 35 2 70 50 1 50 15 0 0 120 200 60%Total 2366 3200 USAIM Online Survey; Dr S. Sanyal, Assoc. Prof., Faculty of Anatomy & Neurosciences, USAIM, Seychelles May 2008 19