Journal of - Southern University New Orleans

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34Journal of Urban Education: Focus on Enrichmentsimilarly causes the probability of sending nomessages to decrease significantly and theprobability of sending one or two messagesto increase significantly.Table 1: Summary Statistic DataItem M SDCharacteristicsContacted Professor 0.444 0.212Enrolled in a class with Webpage 0.231 .204Prior Internet Experience 0.446 0.321Off-Campus Internet Hook-up 0.168 0.455Professor taught part-time 0.999 0.212E-mailed Professor during semester 0.132 0.666OverallBEN 1 0.012 0.333BEN 2 0.404 0.656BEN 3 0.002 0.222Overall GPAE-mail users 3.241 2.341Non-email users 3.199 2.991Internet users 3.455 1.344Non-Internet users 3.333 1.851Unlike the results for BEN 2 and BEN 3,however, no statistically significant resultemerged in the relationship between BEN 3and the probability of sending three or moremessages. 1In addition to how students perceive e-mail,other significant determinants include courseWeb sites, prior Internet experience, off-Campus hook-ups and existence of part-timeinstructors.The estimate associated with PART revealsthat students are more likely to send e-mailwhen their professors teaches part- time or,1 An objection to these results might be the possibility that thenon-Internet users have biased the BEN estimates to reflectoutcomes that are not representative of actual Internet users.By re estimating (1) and restricting the observations to includeonly those students with prior or current Internet experience,the BEN results are strengthened further. The marginal effectsfrom this re estimation are not reported here.simply put, when it is difficult to contact theprofessor, a situation compounded by havingan instructor as a part-time instructor. Whenour data set considers only current or priorInternet users, these results are strengthenedin the sense that the magnitude of the marginaleffects increase (not reported). Manystudents have access to an off- three or moremessages is significantly improved. Becausethe average students sends only a few messagesduring the semester, this implies thatmost e-mail comes from on-campus terminalsand campus Internet hookup but the resultsin Table 3 demonstrate that only the probabilityof sending that off-campus access allowsstudents to become more frequent e-mail users.The marginal effect that off-campus accessallows students to become more frequent e-mail users. The marginal effect of GPA on theprobability of making either a few or several
Journal of Urban Education: Focus on Enrichment 35messages is not significantly different fromzero at a 5% level of significance. It appearsthat the connection between GPA and e-mailuse is very weak. Table 3 demonstrates thatwhen students have off-campus Internethook-ups the probability of sending three orTable 2 Multinomial Regression Results of the Dependent VariablesDependent Variable: P1/P0Dependent Variable: P1/P0V a r i a b l e Coefficient t-value p value Coefficient t-value p valueConstant 4.444 4.88 0.000 9.777 7.57 0.001BEN 1 3.333 4.44 0.006 4.539 3.20 0.006BEN 2 4.552 5.55 0.004 2.668 4.03 0.005BEN 3 4.445 4.45 0.000 2.222 2.43 0.130CON 3.444 2.66 0.003 1.555 1.86 0.041EX 2.661 2.34 0.004 1.85 3.33 0.033HKUP 0.333 2.00 0.221 0.555 3.31 0.005WEB 0.777 1.56 0.056 2.021 4.31 0.000PART 1.666 1.45 0.034 1.343 2.61 0.034GPA 0.031 0.55 0.444 0.445 1.56 0.067SEM 2 0.446 1.11 0.323 0.045 1.11 0.099SEM 3 0.111 0.31 0.677 0.056 1.23 0.3112142.342Psedo R 0.45Log likelihood = 199.42Table 3: Variables Marginal Effects Evaluation of the MeanEffect on P0 Effect on P1 Effect on P2Variable Coeff p value Coeff p value Coeff p valueConstant 0,101 0.000 -0.111 0.000 -0.001 0.000BEN 1 -0.065 0.000 0.044 0.001 0.044 0.023BEN 2 -0.033 0.000 0.043 0.003 0.043 0.011BEN 3 -0.065 0.004 0.O44 0.023 0.023 0.110CON -0.077 0.001 0.045 0.023 0.054 0.300EX -0.055 0.001 0.012 0.033 0.021 0.033HKUP 0.001 0.888 -0.020 0.234 0.034 0.111WEB -0.022 0.021 0.012 0.111 0.020 0.044PART -0.033 0.012 0.021 0.076 0.113 0.120GPA -0.001 0.0312 -0.003 0.711 0.001 0.133SEM 2 0.001 0.233 -0.005 0.111 0.003 0.400SEM 3 0.031 0.151 -0.007 0.544 -0.020 0.1992 = 28.99Pseudo R 2 .3423Log likelihood = -177.22Note: The p value associated with this chi square is 0.1945The Table 3 was re estimated without the insignificant variables SEM 2 andSEM 3 and the p value was 0.0445. The re estimation did not have any significant effect on the parameter estimates,more messages is significantly improved. Notonly are the marginal effects relating to P 0and P 1 are insignificant and the P 2 significant, there is also a significant pair - wise dif-
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Journal of - Southern University New Orleans

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