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Cited by 11Higher Education Research StudiesEvasion and Academic Success FactorsMobile Learning in Education

Thx 4 the msg: Assessing the Impact of Texting on Student Engagement and Persistence

Open access
Tippetts, Megan M., Davis, Bobbi, Nalbone, Stephanie, Zick, Cathleen D.·2022·Research in Higher Education
DOI 10.1007/s11162-022-09678-8PMC PMC8853065
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Abstract

As colleges and universities strive to increase persistence and aid students in reaching graduation, they are utilizing alternative communication strategies like text messaging. Behavioral economics researchers suggest personalized, regular nudges can help college students make decisions that positively impact their college career and keep them on track for graduation. The current study presents the results of a randomized field experiment where a text messaging program was implemented in a large college at a public university. The intervention utilized a mixture of automated and personalized text messages from academic advisors and allowed for two-way communication between individual students and their major advisor. Mulitvariate analyses revealed the intervention had no impact on university persistence, but it did increase the odds of persisting in the college to the end of the semester, moving the average, overall college persistence rate from 93 to 95%. Effects were concentrated on underclass students, whose persistence rate moved from 87 to 93% at the college level. Underclass students also showed statistically significant university persistence effects, moving from 90 to 95%. Students who received texts but never engaged with the texting program were significantly less likely to request an advising appointment or to apply to be a student ambassador than were students in the control group. More research is needed to understand what motivates a student to engage with the texting software and to identify what the longer-term consequences of using text messaging to communicate with students might be.Supplementary information The online version contains supplementary material available at 10.1007/s11162-022-09678-8.

AI snapshot

Written from the paper’s full text.

TL;DR

In a randomized field experiment in a large public-university college, a semi-automated advisor texting program did not improve university persistence for the full sample but increased college persistence, with effects concentrated among students with fewer than 60 completed credits. Students who never engaged with the texts showed lower odds of some college engagement behaviors than controls.

Key findings

  • Full-sample multivariate logistic regression: treatment students had 1.48 times higher odds of persisting under the college definition (predicted 95% vs. 93% for controls); there was no statistically significant full-sample effect on university persistence.
  • For students with fewer than 60 completed credits, treatment students were 2.13 times more likely to persist at the university and 2.09 times more likely to persist within the college; the abstract reports underclass persistence moving from 90% to 95% at the university and from 87% to 93% at the college. No significant persistence differences appeared for students with 60–99 completed credits.
  • Treatment students who responded to at least one text were 1.27 times more likely to meet with an advisor than controls overall, and 1.82 times more likely if they had fewer than 60 credits.
  • Treatment students who never responded to a text had 25% lower odds of meeting with an advisor and 64% lower odds of applying to be an ambassador than controls; non-engaged students with 60–99 credits were 31% less likely to meet with an advisor and 60% less likely to apply to be an ambassador.

Methods

  • Randomized field experiment (ASCENT) in one large college at a public university during spring 2020; eligible students had at least one major in the college and fewer than 100 earned credits. Of 2,225 eligible students, 286 were text-ineligible; final analytic groups were treatment N = 1,451 and control N = 488 after COVID-related changes collapsed two treatment arms.
  • Treatment students received approximately weekly automated and personalized texts from major advisors and could opt out; controls received standard advising emails and Canvas communications. Outcomes included university persistence (not withdrawing, taking leave, or dropping all classes) and college persistence (also not changing major out of the college), plus advising appointments, scholarship applications, and ambassador applications.
  • Analyses used bivariate comparisons and multivariate logistic regression with covariates (sex, age, race/ethnicity, state residency, entered as freshman, honors, GPA, academic level); career-stage splits compared students with <60 vs. 60–99 completed credits, and engagement with the texting platform was included as a covariate in some models.

Limitations

  • The paper states limited generalizability to other college settings; only one semester of follow-up, so longer-term engagement and persistence to graduation could not be assessed; limited engagement measures because the platform provided only categorical low/medium/high engagement and no club, event, or faculty-interaction data; text-ineligible phone numbers created a self-selection issue; and the COVID-19 pandemic disrupted spring 2020 with unknown impact on persistence.
  • The paper states that students who opted out differed somewhat from those who remained (e.g., state residency and persistence outcomes; Appendix Table 5), though they remained in the treatment group under intent-to-treat.
  • The text makes evident that randomization produced marginal differences (treatment group marginally younger and less likely to be upperclass), which were controlled in multivariate models, and that COVID forced the collapse of two treatment arms and moved the planned in-person registration event to a virtual format, changing the intervention.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1007/s11162-022-09678-8

Cites

49 of 49 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

1 of 19 cited sources checked · 1 supported · 0 flagged

  • Findingown data
    § Abstract · p. 1

    Students who received texts but never engaged with the texting program were significantly less likely to apply to be a student ambassador than were students in the control group.

    “Students who received texts but never engaged with the texting program were significantly less likely to request an advising appointment or to apply to be a student ambassador than were students in the control group.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract · p. 1

    Underclass students showed statistically significant university persistence effects, moving from 90% to 95%.

    “Underclass students also showed statistically significant university persistence effects, moving from 90 to 95%.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract · p. 1

    The intervention had no impact on university persistence.

    “Mulitvariate analyses revealed the intervention had no impact on university persistence, but it did increase the odds of persisting in the college to the end of the semester, moving the average, overall college persistence rate from 93 to 95%.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract · p. 1

    Effects were concentrated on underclass students, whose college persistence rate moved from 87% to 93%.

    “Effects were concentrated on underclass students, whose persistence rate moved from 87 to 93% at the college level.”
    Quote in the paperSubstantial claim
  • Findingown data
    § Abstract · p. 1

    Students who received texts but never engaged with the texting program were significantly less likely to request an advising appointment than were students in the control group.

    “Students who received texts but never engaged with the texting program were significantly less likely to request an advising appointment or to apply to be a student ambassador than were students in the control group.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim. 15
  • May combine two claims. 18
  • The quote only partly states this claim. 1

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § Literature Review · p. 4

    Students who participated in advising via text reported that, overall, they enjoyed text messaging, noting it kept them on track toward success in their academic careers.

    “Arnold et al. (2020) asked students who participated in advising via text about their experience. Using focus groups and text message queries, they reported that, overall, students enjoyed text messaging, noting it kept them on track toward success in their academic careers.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Arnold et al. (2020)

  • May combine two claims.

    Findingown data
    § Abstract · p. 1

    The intervention increased the odds of persisting in the college to the end of the semester, moving the average overall college persistence rate from 93% to 95%.

    “Mulitvariate analyses revealed the intervention had no impact on university persistence, but it did increase the odds of persisting in the college to the end of the semester, moving the average, overall college persistence rate from 93 to 95%.”
    Quote in the paperSubstantial claim

  • The quote only partly states this claim.

    Findingown data
    § Multivariate Results · p. 12

    No statistically significant results were found when comparing the treatment to the control group in the full sample for advising appointments, scholarship applications, and ambassador applications.

    “No statistically significant results were found when comparing the treatment to the control group in the full sample”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The COVID-19 pandemic and the shift to online instruction did not differentially affect the treatment and control groups' persistence and engagement outcomes.

  • May combine two claims.

    Findingown data
    § Multivariate Results · p. 12

    Treatment group students with fewer than 60 credit hours were 2.13 times more likely to persist at the university than otherwise similar control students, equating to a 5 percentage point gain.

    “These treatment group students, those who have fewer than 60 credit hours, were 2.13 times more likely to persist at the university and 2.09 times more likely to persist within the college than otherwise similar students in the control group.”
    • Also stated in: § Multivariate Results · p. 12 · plain
      “These odds ratios equate to 5% point gain in persistence at the university and a 6% point gain for persistence in the college, respectively, for those in the freshman/sophomore treatment group.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The COVID-19 pandemic and the shift to online instruction did not differentially affect the treatment and control groups' persistence and engagement outcomes.

  • May combine two claims.

    Findingown data
    § Bivariate Results · p. 11

    Using the university's definition of persistence, 94.47% of the control group and 96.07% of the treatment group persisted, but these bivariate differences did not reach conventional levels of statistical significance.

    “Using the university's definition of persistence, 94.47% of the control group and 96.07% of the treatment group persisted, but these bivariate differences did not reach conventional levels of statistical significance.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The COVID-19 pandemic and the shift to online instruction did not differentially affect the treatment and control groups' persistence and engagement outcomes.

  • May combine two claims.

    Findingown data
    § Multivariate Results · p. 12

    In the full sample, treatment group students were 1.48 times more likely to persist using the college's definition of persistence than control group students, equating to a 95% probability of persistence for treatment vs 93% for control.

    “Students who were in the treatment group in the full sample were 1.48 times more likely to persist when using the college's definition of persistence, which equates to a 95% probability that a student in the treatment group will persist compared to a 93% probability that a student will persist in the control group.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The COVID-19 pandemic and the shift to online instruction did not differentially affect the treatment and control groups' persistence and engagement outcomes.

  • May combine two claims.

    Findingreasoning
    § Discussion and Conclusions · p. 16

    The difference-in-difference results were not statistically significant, perhaps in part because of reduced sample size.

    “Again, the results were not statistically significant, perhaps in part, because of the reduction in sample size.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Bivariate Results · p. 11

    There was evidence of statistically significant differences in engagement with the college by students in the treatment and control groups with (1) student ambassador applications and (2) meeting with an academic advisor.

    “Turning to our measures of engagement, there was evidence of statistically significant differences in engagement with the college by students in the treatment and control groups with (1) student ambassador applications and (2) meeting with an academic advisor.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The COVID-19 pandemic and the shift to online instruction did not differentially affect the treatment and control groups' persistence and engagement outcomes.

  • May combine two claims.

    Findingown data
    § Multivariate Results · p. 12

    Treatment group students with fewer than 60 credit hours were 2.09 times more likely to persist within the college than otherwise similar control students, equating to a 6 percentage point gain.

    “These treatment group students, those who have fewer than 60 credit hours, were 2.13 times more likely to persist at the university and 2.09 times more likely to persist within the college than otherwise similar students in the control group.”
    • Also stated in: § Multivariate Results · p. 12 · plain
      “These odds ratios equate to 5% point gain in persistence at the university and a 6% point gain for persistence in the college, respectively, for those in the freshman/sophomore treatment group.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The COVID-19 pandemic and the shift to online instruction did not differentially affect the treatment and control groups' persistence and engagement outcomes.

  • May combine two claims.

    Findingown data
    § Discussion and Conclusions · p. 15

    In fall 2019 the engagement rate after the first text was 9.1%, while it was 28.3% in spring 2020.

    “In fall 2019 the engagement rate after the first text was 9.1%, while it was 28.3% in spring 2020.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § Literature Review · p. 4

    Advisors were initially hesitant to add another form of communication to their already growing caseloads, but they eventually became supportive of the program after seeing its impact on students.

    “Tippetts, et al. (2021) finds advisors were initially hesitant to add another form of communication to their already growing caseloads, but they eventually became supportive of the program after seeing its impact on students.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Tippetts, et al. (2021) source

  • May combine two claims.

    Premisecitation
    § Introduction · p. 2

    Student time constraints coupled with high advisor-to-advisee ratios means students may struggle to find open appointments to address time sensitive matters.

    “Student time constraints coupled with high advisor-to-advisee ratios means students may struggle to find open appointments to address time sensitive matters (Tuttle, 2000).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Tuttle, 2000 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § Literature Review · p. 4

    The most significant impact of a text messaging campaign to reduce summer melt in newly graduated high school students was seen when they and/or their parents engaged with the counselor by responding to one or more texts throughout the summer.

    “Castleman and Page (2015, 2017) discovered the most significant impact of a text messaging campaign to reduce summer melt in newly graduated high school students was seen when they and/or their parents engaged with the counselor by responding to one or more texts throughout the summer.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Castleman and Page (2015, 2017)

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § Literature Review · p. 4

    Text messaging may aid advisors in time management by reducing the need for one-on-one appointments, as advisor-to-advisee ratios continue to rise.

    “Additionally, text messaging may aid advisors in time management by reducing the need for one-on-one appointments, as advisor-to-advisee ratios continue to rise (Tippetts, et al., 2021; Tuttle, 2000).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Tippetts, et al., 2021 source
    • cites Tuttle, 2000 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § Introduction · p. 2

    Theory suggests one key to persistence and student success is the student's ability to navigate their new environment and integrate themselves into campus and academic life.

    “Theory suggests one key to persistence and student success is the student's ability to navigate their new environment and integrate themselves into campus and academic life (Tinto 2015, 2017).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Tinto 2015, 2017

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning
    § Literature Review · p. 4

    In the case of nudging students, recommendations from academic advisors would typically be viewed positively by students because advisors are viewed as promoting what is in the best interest of students.

    “This suggests in the case of nudging students, recommendations from academic advisors would typically be viewed positively by students because advisors are viewed as promoting what is in the best interest of students.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Discussion and Conclusions · p. 16

    A difference-in-difference analysis using spring 2019 data for majors registered both terms was conducted to adjust for unmeasured, unchanging predispositions.

    “We also reached back to the spring 2019 semester to get data on the subset of students who were majors in the college and registered both terms to undertake a difference-in-difference analysis that adjusts for unmeasured, unchanging predispositions.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Bivariate Results · p. 12

    Tests for multicollinearity among the covariates in the logistic regressions revealed no causes of concern.

    “Tests for multicollinearity among the covariates in our logistic regressions revealed no causes of concern.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation
    § Discussion and Conclusions · p. 16

    Opt-out approaches are preferred to opt-in approaches if one is to reach a representative sample, because students who do not see an immediate benefit may differ in their approach to college.

    “Fishbane and Fletcher (2019), argue the former approach is preferred if one is to reach a representative sample, as students who do not see an immediate benefit may be different in their approach to college than those who do.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Fishbane and Fletcher (2019)

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Bivariate Results · p. 10

    Students in the treatment group were marginally younger than students in the control group.

    “Students in the treatment group were marginally younger than students in the control group.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Discussion and Conclusions · p. 16

    The Heckman correction for self-selection was used to account for possible differences between students with and without text-capable phone numbers.

    “In one set of analyses, the Heckman correction for self-selection was used to account for possible difference between those in the study who had a text-capable phone number and those who did not.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning
    § The Intervention · p. 9

    Students who opted out were retained in the treatment group for the analyses under an intent-to-treat approach.

    “The students who opted out remain in the treatment group for the purposes of the analyses that follow because there was an intent to treat them.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data
    § Bivariate Results · p. 10

    Randomization was successful, with only two marginally significant differences between the control and treatment groups.

    “Randomization was successful with only two marginally significant differences between the control and treatment groups.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductcitation
    § Discussion and Conclusions · p. 16

    The study design required students to opt out rather than opt in to the intervention, which heightened confidence in the results by reducing self-selection.

    “Confidence in our results is heightened by the fact that the study design required students to opt out, rather than requiring them to opt in, to the intervention.”
    • Also stated in: § Discussion and Conclusions · p. 16 · plain
      “Requiring students to opt-out rather than opt-in reduced the opportunity for such self-selection.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Fishbane and Fletcher (2019)

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Hanushek et al., 2016 source

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data
    § The Intervention · p. 9

    Only 51 students opted out of the texting program over the course of the semester, with the vast majority opting out within the first week or two.

    “Only 51 students opted out over the course of the semester with the vast majority of those opting out within the first week or two.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductown data
    § Discussion and Conclusions · p. 15

    The study followed students for only one semester, so it could not assess the impact of texting on engagement over an extended period or persistence to graduation.

    “Second, the study only followed students for one semester. As such, we were unable to assess the impact of texting on (1) engagement over an extended period of time, or (2) persistence to graduation.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Study design and conductnone given
    § Discussion and Conclusions · p. 17

    The research design utilized best practices in constructing regular, proactive, and personalized messages.

    “Our research design utilized best practices in constructing regular, proactive, and personalized messages.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given
    § Discussion and Conclusions · p. 16

    The study was conducted during the spring semester of 2020, when approximately halfway through the semester students, faculty, and staff transitioned to remote learning.

    “This study was conducted during the spring semester of 2020. Appromixately half-way through the semester, students, faculty, and staff transistioned to remote learning.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation
    § Discussion and Conclusions · p. 17

    Recent research shows students who change majors multiple times in their academic careers are more likely to take longer to graduate.

    “Recent research shows students who change majors multiple times in their academic careers are more likely to take longer to graduate (Abdou, 2019; Bullock, 2017).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Abdou, 2019

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Bullock, 2017

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Interpretationreasoning
    § Discussion and Conclusions · p. 17

    The results suggest an added benefit of texting may be that it reduces a student's likelihood of switching majors, which in turn may promote more timely graduation.

    “Our results suggest an added benefit of texting may be that it reduces a student's likelihood of switching majors which in turn may promote more timely graduation.”
    Quote in the paperSubstantial claim
30 of 30

  • The paper relies on this without support.

    Little is known about the effectiveness of randomized field experiment texting interventions in the general student population.

    “While a number of randomized field experiment (RFE) texting interventions have been undertaken with targeted populations (e.g., entering freshmen who have been identified as being at high risk for non-persistence), little is known about the effectiveness of such interventions in the general student population.”

  • The paper relies on this without support.

    Little attention has been paid to the advisor's experience with text messaging interventions.

    “However, little attention has been paid to the advisor's experience.”

  • The paper relies on this without support.

    Only a few studies assess the impact of text messaging interventions on student persistence.

    “Only a few studies assess the impact of text messaging interventions on student persistence.”

  • The paper relies on this without support.

    Texting has the potential to deliver key information from advisors in a manner that is more likely to be read by students.

    “In this context, texting has been identified as a communication mode that has the potential to deliver key information from advisors in a manner that is more likely to be read by students.”

  • The paper relies on this without support.

    The COVID-19 pandemic and the shift to online instruction did not differentially affect the treatment and control groups' persistence and engagement outcomes.

    “The RFE during spring semester 2020 coincided with the beginning of the COVID-19 pandemic. In the middle of March, the university moved all classes to an online delivery mode.”

  • The paper relies on this without support.

    Building a relationship between students and their major advisor early has clear benefits for helping students navigate their major requirements and persist to the following semester.

    “Building a relationship between students and their major advisor early has clear benefits to helping students navigate their major requirements to ensure they make it to the following semester.”
6 of 6

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Bivariate college-persistence significance is overstated

    Major

    The prose claims p < 0.05 for the overall treatment-control difference. Table 1 marks that comparison with a single asterisk, which its legend defines as p < 0.10, and reports a chi-square value of 3.25.

  • Treatment-group college persistence differs from Table 1

    Major

    The bivariate results report 93.86% for the treatment group, whereas Table 1 reports 93.25%.

  • Treatment-group university persistence differs from Table 1

    Major

    The bivariate results report 96.07% for the treatment group, whereas Table 1 reports 95.86%.

  • University graduation rate is reported as both 70% and 62%

    Minor

    The setting section gives two different six-year graduation rates for the university without distinguishing the populations or periods they cover.

  • Number of treatment students who responded to texts differs

    Minor

    The narrative reports 851 treatment students responding to at least one text, while both the treatment-group footnote and Table 6 report 902.

  • Underclass control-group college persistence is misstated

    Minor

    The discussion of Table 2 says 87% of underclass control students persisted within the college, but the table reports 84.74%. This changes the stated size of the treatment-control gap.

6 of 6

Cites

Flagged first, then by citations

1 of the 50 references couldn’t be matched to a known paper.

Research works printed but not linked: 9

  1. Abdou, N. W. (2019) Predictors of four-year graduation rates: A quantitative study on the impact of enrollment in major related course, student engagement, and student-faculty interactions on graduation rates of first-time student. Dissertation, California State Univerity, Fullteron.
  2. Bullock, C. D. (2017) Factors that influence graduation efficiency of baccalaureate recipients at Weber State University. Doctoral dissertation. University of Utah.
  3. Castleman, B. L., & Page, L. C. (2015). Summer nudging: Can personalized text messages and peer mentor outreach increase college going among low-income high school graduates? Journal of Economic Behavior & Organization, 115, 114–160. https://doi.org/10.1016/j.jebo.2014.12.008 · DOI · Paper page
  4. Castleman, B. L., & Page, L. C. (2016a). Can text messages mitigate summer melt? New England Journal of Higher Education.
  5. Corbett, C., Hill, C., & Rose, A. S. (2008). Where the girls are: The facts about gender equality in education. American Association of University Women Education Foundation.
  6. Selingo, J. J. (2018). The new generation of students: How colleges can recruit, teach, and serve Gen Z. The Chronicle of Higher Education.
  7. Snyder, T. D., Brey, C. D., & Dillow, S. A. (2019). Digest of education statistics 2018 (NCES 2020-009). National Center for Education Statistics, Institute of Education Services, U.S. Department of Education.
  8. Stiles, R. J., & Wilcox, K. (2016). Blending human intelligence and analytics for student success. Journal of Educause Learning Initiative.
  9. Tough, P. (2019). The years that matter most: How college makes or breaks us. Houghton Mifflin Harcourt.

Cited by

Sorted by citations

Related

Authors
Tippetts, M. M., Davis, B., Nalbone, S., & Zick, C. D.
Affiliations
University of Utah (US)
Corresponding author
Tippetts, Megan M.
ORCID
Venue
Research in Higher Education
Publisher
Springer Science and Business Media LLC
Published
2022-02-16
Volume
63
Issue
6
Pages
1073-1093
ISSN
  • 0361-0365 (ISSN-L)
  • 1573-188X
DOI
10.1007/s11162-022-09678-8
PMC
PMC8853065
OpenAlex
W4213426234
Semantic Scholar
aa2e3dce86072b332f0cc8dfca5e675514266dc8
Cited by
11
References
50
Citations by year
2026: 3 · 2025: 4 · 2024: 1 · 2023: 1 · 2022: 1 · 2021: 1
FWCI
3.70
Type
journal article
Language
en
Open access
Licence
Locations
  • Research in Higher Education (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Education › Higher Education Research Studies
  • Social Sciences › Demography › Evasion and Academic Success Factors
  • Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
Keywords
text messaging, student persistence, student engagement, academic advising, nudging, behavioral economics, personalized communication, student ambassadors, college completion

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