- Katharine Meyer
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Despite documented benefits to college completion, more than a third of students who initially enroll in college do not ultimately earn a credential. Completing college requires students to navigate both institutional administrative tasks (e.g., registering for classes) and academic tasks within courses (e.g., completing homework). In postsecondary education, several promising interventions have shown that text-based outreach and communication can be a low-cost, easy to implement, and effective strategy for supporting administrative task navigation. In this paper, we report on two randomized controlled trials testing the effect of a text-based chatbot with artificial intelligence (AI) capability on students' academic task navigation in introductory courses (political science and economics). We find the academic chatbot significantly shifted students’ final grades, increasing the likelihood students received a course grade of B or higher by 5-6 percentage points and reduced the likelihood students dropped the course.
College success requires students to engage with their institution academically and administratively. Missteps with required administrative processes can threaten student persistence and success. Through two experimental studies, we assessed the effectiveness of an artificially intelligent text-based chatbot that provided proactive outreach and support to college students to navigate administrative processes and use campus resources. In both the two-year and four-year college context, outreach was most effective when focused on discrete administrative processes such as filing financial aid forms or registering for courses which were acute, time-sensitive, and for which outreach could be targeted to those for whom it was relevant. In the context of replicating studies to better inform policy and programmatic decision making, we draw three core lessons regarding the effective use of nudge-type efforts to promote college success.
Interactive, text message-based advising programs have become an increasingly common strategy to support college access and success for underrepresented student populations. Despite the proliferation of these programs, we know relatively little about how students engage in these text-based advising opportunities and whether that relates to stronger student outcomes – factors that could help explain why we’ve seen relatively mixed evidence about their efficacy to date. In this paper, we use data from a large-scale, two-way text advising experiment focused on improving college completion to explore variation in student engagement using nuanced interaction metrics and automated text analysis techniques (i.e., natural language processing). We then explore whether student engagement patterns are associated with key outcomes including persistence, GPA, credit accumulation, and degree completion. Our results reveal substantial variation in engagement measures across students, indicating the importance of analyzing engagement as a multi-dimensional construct. We moreover find that many of these nuanced engagement measures have strong correlations with student outcomes, even after controlling for student baseline characteristics and academic performance. Especially as virtual advising interventions proliferate across higher education institutions, we show the value of applying a more codified, comprehensive lens for examining student engagement in these programs and chart a path to potentially improving the efficacy of these programs in the future.