Using an AI-Supported Online Discussion Forum to Deepen Learning

Using an AI-Supported Online Discussion Forum to Deepen Learning

Tamarin Butcher, Michelle Fulks Read, Ann Evans Jensen, Gwendolyn M. Morel, Alexander Nagurney, Patrick A. Smith
Copyright: © 2020 |Pages: 29
DOI: 10.4018/978-1-7998-3292-8.ch016
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Student-to-student interaction is a key element in the learning process, and one that is often missing in online classes. The purpose of this case study is to demonstrate how a technology platform that leverages artificial intelligence (AI) can be used to deepen learning in online discussions by analyzing instructor and student perceptions and examining third-party analytics in two hybrid/blended undergraduate courses. The instructors selected Packback, a third-party online discussion platform, to address some of the engagement issues they encountered in the past when using discussion tools within learning management systems (LMS). Packback increased the depth of student discussions by providing real-time feedback to students on the quality of their posts, thus allowing students to improve the quality of their posts. Packback also allowed for more nuanced evaluation and grading of students' forum posts by instructors.
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Online discussions provide a rich environment for student learning as they serve to facilitate peer-to-peer interactions and knowledge transfer. Rich discussions in face-to-face settings are common. When implemented thoughtfully, online discussion tools can serve as a way to ensure that these learning opportunities are available in fully online classes as well. While there are many benefits to using online discussion forums, such as opportunities for regular engagement with coursework (Pazzalgia, Clements, Lavigne, & Stafford, 2016), the ability to review discussions after class (Kinskey, Miller, Hauck, & Manderfield, 2018), allowing time for reflection before posting, and the ability for “instant replay” (Cox, 2011), several challenges also exist. For example, it can be difficult to encourage deep and meaningful interaction in online classes where students may lack the motivation to participate in what may feel like “busy work” (Cox, 2011). Students may also feel disconnected from their peers and therefore be less interested in what they might have to say. In addition, assessing these activities, particularly in large-enrollment classes, can be time consuming and, at times, feel almost impossible. Often, for students to feel motivated to participate in online discussions, clear expectations need to be communicated regarding how the discussion will tie into their grade; however, even more difficult than setting expectations is building in incentives for active participation in learning through online discussions (Cox, 2011). Discussion forums are often the “heart” of an online course (Cox, 2011). Consequently, it is essential that instructors put in the thought and work required to make these discussions meaningful. Arend (2009) found that “the way discussions are used and facilitated is vital for encouraging critical thinking.”

Two professors at Texas State University sought to change their approach to discussion forums in their online courses to address issues of engagement and meaningful evaluation, which they found to be lacking when using traditional learning management system (LMS) forum tools. Specifically, they individually and independently elected to use a third-party online discussion tool called Packback that uses algorithms derived from artificial intelligence (AI) to determine the quality of student posts. According to the Packback website (, 2019), the company has 247,000 students from across 208 institutions and 1,323 instructors posting over 5 million questions and responses since May 2016. The creators at Packback describe their tool as:

an AI-supported online discussion platform that improves student curiosity, communication skills and critical thinking. Packback delivers an easy-to-use and engaging discussion experience for students and instructors, with powerful support from automated moderation, sorting and scoring algorithms.

After the pilot implementation by these two professors, a look at how the tool may have improved some areas of identified concern in the literature was warranted. The purpose of this study was to determine if the use of AI-supported platforms for online discussions helped address common particularly challenging issues including student motivation, development of students’ critical thinking, and ease of instructor assessment. This study also aims to ascertain the value of Packback, particularly with regards to its efficacy in enhancing student engagement and outcomes in online discussions.



Articles regarding the impact of online discussion forums on students began appearing in the literature around the turn of the century. These articles are replete with suggestions for instructor presence, management, and student motivation ideas, and mostly measure student satisfaction, which Allen, Bourhis, Burell & Mabry (2002) understood is impacted directly by teacher-student and student-student interactions. Without a doubt, the literature identifies number of challenges in the use of online discussion forums.

Key Terms in this Chapter

Higher-order thinking: Thinking that goes beyond observation and memorization resulting in learning that requires more cognitive processing and leading to more generalized benefits.

Artificial Intelligence: The theory and development of computer systems capable of performing tasks that normally require human intelligence.

Interactivity: With discussion forums, interactivity is a communication process that leads to jointly produced meaning.

Asynchronous Learning: Learning that does not occur at the same place or the same time; for example, online discussions occurring over the course of a week.

Netiquette: A portmanteau for the words “etiquette” and ‘internet’ that describes rules for engaging online.

Packback: An AI-supported online discussion platform that seeks to enhance the depth and meaningfulness of student discussions.

Curiosity Score: In Packback, an algorithm that measure the effort, presentation and credibility of every post made to derive an overall sense of quality.

Real-Time Feedback: In Packback, feedback provided to students immediately regarding the quality of their posts, allowing them an opportunity to edit their posts as/if needed.

Spark: In Packback, the means through which students and instructors can “upvote” or “like” posts.

Sakai: A learning management system (LMS) used at Texas State University at the time this chapter was written.

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