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Does Internet Usage Predict College Adjustment among First-Year Students?
Does Internet Usage Predict College Adjustment among First-Year Students?
Kelvin BentleyNorthwestern State University
Kelvin BentleyNorthwestern State University
TopicsTopics
• Research Background• Hypotheses• Method• Results• Conclusions and Directions for
Future Research
• Research Background• Hypotheses• Method• Results• Conclusions and Directions for
Future Research
Research BackgroundResearch Background
• Research attempting to link Internet usage to loneliness and depression– Kraut and colleagues (1998)
• “Internet addiction” research with college students– Morahan-Martin and Schumacher (2000)– Davis and colleagues (1998)– Shrerer and colleagues(1997)
• Research attempting to link Internet usage to loneliness and depression– Kraut and colleagues (1998)
• “Internet addiction” research with college students– Morahan-Martin and Schumacher (2000)– Davis and colleagues (1998)– Shrerer and colleagues(1997)
Research BackgroundResearch Background
• Examination of coping styles and college adjustment– Aspinwall and Taylor (1992)– Leong, Bonz, & Zachar (1997)
• Examining relationships between computer self-efficacy, coping style, and computer hassles– Hudiburg and Necessary (1996)
• Examination of coping styles and college adjustment– Aspinwall and Taylor (1992)– Leong, Bonz, & Zachar (1997)
• Examining relationships between computer self-efficacy, coping style, and computer hassles– Hudiburg and Necessary (1996)
HypothesesHypotheses
• Students will have poor adjustment to college if the following are true:– They are women (mainly for personal-
emotional adjustment)– They are infrequent users of the
Internet– They have low levels of Internet self-
efficacy– They have experienced frequent
computer- and Internet-related hassles.
• Students will have poor adjustment to college if the following are true:– They are women (mainly for personal-
emotional adjustment)– They are infrequent users of the
Internet– They have low levels of Internet self-
efficacy– They have experienced frequent
computer- and Internet-related hassles.
Overview of ParticipantsOverview of Participants
• 244 Northwestern State University students enrolled in various psychology courses during the Fall 2001 semester– Average age: 21.7 years– Gender
• 65 Men• 175 Women• 4 students had data that was missing
• 244 Northwestern State University students enrolled in various psychology courses during the Fall 2001 semester– Average age: 21.7 years– Gender
• 65 Men• 175 Women• 4 students had data that was missing
Overview of ParticipantsOverview of Participants
• Classification of Participants– 70 Freshmen– 91 Sophomores– 30 Juniors– 52 Seniors
• Classification of Participants– 70 Freshmen– 91 Sophomores– 30 Juniors– 52 Seniors
Overview of ParticipantsOverview of Participants
• 133 European-Americans• 64 African-Americans• 2 Hispanic-Americans• 12 Native Americans• 22 students reported “Other”• 7 students had missing data
• 133 European-Americans• 64 African-Americans• 2 Hispanic-Americans• 12 Native Americans• 22 students reported “Other”• 7 students had missing data
Overview of MeasuresOverview of Measures
• Independent Variables– Computer usage
• Internet-based• Non-Internet based
– Internet self-efficacy– Computer- and Internet-related
hassles
• Independent Variables– Computer usage
• Internet-based• Non-Internet based
– Internet self-efficacy– Computer- and Internet-related
hassles
Overview of Study Variables
Overview of Study Variables
• Independent Variables– Coping Style
• Task-focused• Emotion-focused• Avoidant-focused
• Independent Variables– Coping Style
• Task-focused• Emotion-focused• Avoidant-focused
Overview of Study Variables
Overview of Study Variables
• Dependent Variables– College Adjustment
• Academic• Social • Personal-Emotional• Attachment to the Institution
• Dependent Variables– College Adjustment
• Academic• Social • Personal-Emotional• Attachment to the Institution
Sex by Grade ANOVA’sSex by Grade ANOVA’s
Descriptive Statistics
Dependent Variable: EMOTION
42.9167 10.6127 12
38.7609 10.6407 23
32.2308 9.0199 13
39.9375 10.6800 16
38.5078 10.6880 64
40.2857 11.5487 56
42.5788 12.0918 65
46.0000 11.6619 16
44.2500 14.1490 36
42.5007 12.3705 173
40.7500 11.3577 68
41.5810 11.7913 88
39.8276 12.5016 29
42.9231 13.2278 52
41.4225 12.0491 237
YEAR1
2
3
4
Total
1
2
3
4
Total
1
2
3
4
Total
GENDER0
1
Total
Mean Std. Deviation N
Tests of Between-Subjects Effects
Dependent Variable: EMOTION
2105.704a 7 300.815 2.142 .040
274283.328 1 274283.328 1953.271 .000
952.613 1 952.613 6.784 .010
176.496 3 58.832 .419 .740
1120.153 3 373.384 2.659 .049
32156.762 229 140.423
440912.016 237
34262.466 236
SourceCorrected Model
Intercept
GENDER
YEAR
GENDER * YEAR
Error
Total
Corrected Total
Type III Sumof Squares df Mean Square F Sig.
R Squared = .061 (Adjusted R Squared = .033)a.
Descriptive Statistics
Dependent Variable: ISE
32.5000 11.5168 12
33.4545 11.4340 22
31.9231 13.5429 13
30.6875 11.3591 16
32.2540 11.6494 63
28.3750 10.7307 56
28.9032 9.1950 62
25.9333 10.5659 15
29.2500 8.6367 36
28.5385 9.6960 169
29.1029 10.9000 68
30.0952 9.9633 84
28.7143 12.1925 28
29.6923 9.4652 52
29.5474 10.3701 232
YEAR1
2
3
4
Total
1
2
3
4
Total
1
2
3
4
Total
GENDER0
1
Total
Mean Std. Deviation N
Tests of Between-Subjects Effects
Dependent Variable: ISE
836.436a 7 119.491 1.115 .354
146464.377 1 146464.377 1366.714 .000
653.801 1 653.801 6.101 .014
107.678 3 35.893 .335 .800
104.971 3 34.990 .327 .806
24005.043 224 107.165
227389.000 232
24841.478 231
SourceCorrected Model
Intercept
GENDER
YEAR
GENDER * YEAR
Error
Total
Corrected Total
Type III Sumof Squares df Mean Square F Sig.
R Squared = .034 (Adjusted R Squared = .003)a.
Gender by Computer Hassle Group ANOVA’s
Gender by Computer Hassle Group ANOVA’s
Descriptive Statistics
Dependent Variable: PADJUST
106.7111 19.3772 12
91.8492 21.8858 42
95.1519 22.0763 54
87.0000 16.0208 16
81.4211 21.5628 38
83.0741 20.0959 54
95.4476 19.8554 28
86.8958 22.2219 80
89.1130 21.8689 108
GENDER0
1
Total
0
1
Total
0
1
Total
HASGRP1.00
2.00
Total
Mean Std. Deviation N
Tests of Between-Subjects Effects
Dependent Variable: PADJUST
6350.515a 3 2116.838 4.912 .003
687264.014 1 687264.014 1594.650 .000
4635.546 1 4635.546 10.756 .001
2132.228 1 2132.228 4.947 .028
439.752 1 439.752 1.020 .315
44822.022 104 430.981
908813.516 108
51172.537 107
SourceCorrected Model
Intercept
HASGRP
GENDER
HASGRP * GENDER
Error
Total
Corrected Total
Type III Sumof Squares df Mean Square F Sig.
R Squared = .124 (Adjusted R Squared = .099)a.
Gender by Internet Self-Efficacy Group ANOVA’sGender by Internet Self-Efficacy Group ANOVA’s
Descriptive Statistics
Dependent Variable: AADJUST
128.9911 20.7453 14
148.1603 26.3082 26
141.4510 25.9396 40
143.9583 28.9145 49
150.5910 29.8521 38
146.8554 29.3424 87
140.6323 27.8719 63
149.6035 28.2749 64
145.1532 28.3244 127
ISGRP1.00
2.00
Total
1.00
2.00
Total
1.00
2.00
Total
GENDER0
1
Total
Mean Std. Deviation N
Tests of Between-Subjects Effects
Dependent Variable: AADJUST
5085.712a 3 1695.237 2.172 .095
2086924.064 1 2086924.064 2673.860 .000
1932.719 1 1932.719 2.476 .118
4250.806 1 4250.806 5.446 .021
1003.512 1 1003.512 1.286 .259
96000.416 123 780.491
2776907.026 127
101086.128 126
SourceCorrected Model
Intercept
GENDER
ISGRP
GENDER * ISGRP
Error
Total
Corrected Total
Type III Sumof Squares df Mean Square F Sig.
R Squared = .050 (Adjusted R Squared = .027)a.
Regression AnalysesRegression Analyses
Model Summaryg,h
.362a .131 .117 26.5746 .131 9.507 1 63 .003
.516b .266 .242 24.6197 .135 11.402 1 62 .001
.597c .357 .325 23.2392 .091 8.585 1 61 .005
.616d .380 .339 23.0043 .023 2.252 1 60 .139
.651e .424 .375 22.3550 .044 4.536 1 59 .037
.655f .274 .429 .370 22.4498 .005 .503 1 58 .481
Model1
2
3
4
5
6
YEAR = 1(Selected)
YEAR ~= 1(Unselected)
R
R SquareAdjustedR Square
Std. Error ofthe Estimate
R SquareChange F Change df1 df2 Sig. F Change
Change Statistics
Predictors: (Constant), HGPAa.
Predictors: (Constant), HGPA, EMOTIONb.
Predictors: (Constant), HGPA, EMOTION, TASKc.
Predictors: (Constant), HGPA, EMOTION, TASK, COMPHASSd.
Predictors: (Constant), HGPA, EMOTION, TASK, COMPHASS, EMOHASSe.
Predictors: (Constant), HGPA, EMOTION, TASK, COMPHASS, EMOHASS, TASKHASSf.
Unless noted otherwise, statistics are based only on cases for which YEAR = 1.g.
Dependent Variable: AADJUSTh.
DiscussionDiscussion
• Women used more emotion-focused coping strategies than men.– But men might be more at risk for
using these strategies in their first-year of college.
– Men have higher levels of Internet self-efficacy compared to women.
• Women used more emotion-focused coping strategies than men.– But men might be more at risk for
using these strategies in their first-year of college.
– Men have higher levels of Internet self-efficacy compared to women.
DiscussionDiscussion
• The effects of emotion-focused coping on academic adjustment was influenced by the level of computer hassles experienced. This finding remained significant when only freshmen were examined.
• The effects of emotion-focused coping on academic adjustment was influenced by the level of computer hassles experienced. This finding remained significant when only freshmen were examined.
DiscussionDiscussion
• Students in the high computer- and Internet hassles group were more likely to have lower levels of personal-emotional adjustment compared to students in the low-hassles group.– The women of this group had lower
personal-emotional adjustment scores compared to men.
• Students in the high computer- and Internet hassles group were more likely to have lower levels of personal-emotional adjustment compared to students in the low-hassles group.– The women of this group had lower
personal-emotional adjustment scores compared to men.
Future Research Includes…
Future Research Includes…
• Design a research model to examine the predictors of college adjustment among online college students compared to f2f learners.
• Design a research model to examine the predictors of college adjustment among online college students compared to f2f learners.