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Signs of Trouble: Online Student Behaviors and Faculty Intervention

As convenient as distance learning is, its online nature poses challenges in identifying the obstacles students face.

Online adjunct faculty members may not have access to or knowledge of a student’s prior academic record, feedback or information about student preferences, expectations and challenges. They can only assess students’ unique needs based on their work and whatever the student shares. In the early weeks of a term, faculty members make observations about students they anticipate may struggle or could benefit from extra support. Within online programs, the specific student behaviors that influence these faculty hypotheses, as well as their accuracy, is less well known.

Faculty members must rely on student behaviors in the online classroom to inform their outreach and intervention strategy, but which student behaviors lead faculty to accurately conclude the student is likely to struggle? How might we assess the accuracy of faculty predictions to inform the institution’s support and intervention strategy?

We surveyed experienced faculty members within five online courses at Southern New Hampshire University to gain insight into these questions. We asked them to share specific student behaviors they were concerned about in the first two weeks of the term and to give us a list of students who displayed them. These data enabled us to evaluate student outcomes and assess the accuracy of faculty predictions at the conclusion of the term.

Survey Results

The survey was distributed to repeat faculty members in March 2022 and had a response rate of 22.5%. 81% percent of faculty respondents believe they can identify students who are likely to struggle in the course based on early behavior. The specific behaviors they identified include:

  • Students who miss assignments or submit late
  • Students who struggle with writing
  • Students who do not access the learning management system until the middle of week one

Faculty also identified the types of supports they offer students including:

  • Help via email
  • Referrals to academic support and tutoring
  • One-on-one sessions
  • Working with academic advising to ensure the student is well supported

What Did We Learn?

Faculty prediction accuracy was mixed. Of all students who ended the term unsuccessfully, faculty accurately predicted 16% in the first two weeks. This number implies that faculty were unable to identify many of the students who struggled early in the term. However, of the students who faculty members predicted would struggle based on early behavior, 67% of them did. 44% of students who dropped or withdrew from their course submitted a late assignment in week one. These numbers align with faculty concerns about missing and late assignments but also indicate that 56% of students who submitted their work on time went on to drop the class or withdraw. While late assignments might be a strong predictor of risk, on-time submission does not necessarily indicate that the student will successfully complete the term. This finding underscores the need to support and engage with all students, regardless of early success or challenges.

What Can We Do With This Information?

Proactive support: Faculty members often recommend academic support services or other support the university offers to students struggling in the early weeks of the term. These services typically require the student to initiate contact. Creating a new proactive process that enables academic support services to reach out directly to the student may remove a barrier and increase usage of these critical resources.   

Listen to student voices: We know that late submissions can be correlated to withdrawal, but what happened in the early weeks of the course that led to late submission? What challenges are students facing as they begin their online learning journey? Understanding the challenges directly from the student perspective can enable personalized, relevant supports and interventions.

Streamline instructor outreach: Many faculty respondents said they are proactive in offering support through email or one-on-one virtual sessions, but that the outreach process is time-consuming. Streamlining the outreach process may enable more faculty members to work with their students in a personalized way.

What Is Already Being Done?

One-on-one virtual sessions: Students struggling early in the term may want one-on-one support from a faculty member. To make this easier for students and faculty, SNHU has invested in virtual, live meeting software, minimizing the chance that faculty will use a non-university-approved virtual meeting software to connect with students. This helps ensure consistency in the student and faculty experience.

Removing UX barriers in the early experience: Studying the user experience (UX) within the online learning management system (LMS) can help identify where barriers have been introduced and where the early student experience may be streamlined. For example, in studying Brightspace, SNHU’s LMS, we noticed the link to academic support was inaccessible. By moving the access point to a prominent location, we made it easier to access and aligned it with student expectations, increasing usage. 

Listening to the student voice: SNHU has built infrastructure to enable deployment of timely surveys throughout the student journey (what we call the “voice of customer” program). SNHU is maturing the way we gather and use student voice to improve program and course offerings, as well as continuously improve services. One current pilot uses in-course surveys to gather real-time feedback and provide information to faculty that can be used to support students through targeted interventions.

Future Research Areas

This research does not include quantifying the impact faculty intervention had on students who struggled early in the term but who ended it successfully. This could be accomplished through surveying or interviewing students identified as likely to struggle about their course experience and how they overcame early obstacles. Hypotheses can be tested in future terms to enable targeted support for students and potentially increase student success.

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