Quantitative Indices of Student Social Media Engagement in Tertiary Education: A Systematic Review and a Taxonomy
You can now measure college students’ social-media use with the same precision you use for any other behavior.
01Research in Context
What this study did
The team read every paper that measured college students’ social-media use with numbers.
They pulled out 63 studies from 2010 to 2023.
Then they sorted the ways researchers counted likes, minutes, and words into a simple list.
What they found
Three big buckets showed up.
Count metrics: posts, likes, shares.
Time metrics: minutes online, session length.
Text metrics: word counts, emotion words, hashtags.
No more guessing with surveys — you can now pick a ready-made ruler.
How this fits with other research
Williams-Buttari et al. (2023) cut phone use with cash contracts, but they still used self-report logs.
Tarifa-Rodriguez gives you the exact counts you need to replace those logs.
Ben-Yehudah et al. (2019) showed digital text hurts ADHD students’ grades.
The new metrics let you track if shorter sessions or fewer emotion words protect learning.
Gonzalo et al. (2024) found colleges rarely follow their own inclusion plans.
You can now measure if social-media engagement drops when real supports arrive.
Why it matters
Stop asking students how much they scroll.
Start counting posts, minutes, and words instead.
Pick one metric from the list, set a goal, and graph it like any other behavior.
You will see change faster and write sharper reports.
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02At a glance
03Original abstract
AbstractRecent studies have evaluated the use of social media as learning aids in tertiary education. Emerging research in this area has focused primarily on non-quantitative approaches to student social media engagement. However, quantitative engagement outcomes may be extracted from student posts, comments, likes, and views. The goal of the present review was to provide a research-informed taxonomy of quantitative and behavior-based metrics of student social media engagement. We selected 75 empirical studies comprising a pooled sample of 11,605 tertiary education students. Included studies used social media for educational purposes and reported student social media engagement outcomes (source databases: PsycInfo and ERIC). We used independent raters and stringent interrater agreement and data extraction processes to mitigate bias during the screening of references. Over half of the studies (52%, n = 39) utilized ad hoc interviews and surveys to estimate student social media engagement, whereas thirty-three studies (44%) used some form of quantitative analysis of engagement. Based on this literature, we present a selection of count-based, time-based, and text-analysis metrics. The proposed taxonomy of engagement metrics resulting provides the methodological basis for the analysis of social media behavior in educational settings, particularly, for human operant and behavioral education studies. Implications for future research are discussed.
Journal of Behavioral Education, 2024 · doi:10.1007/s10864-023-09516-6