Qualitative coding of brief videos that teach about the h-index

<p><strong>Dataset of qualitative coding of 31 Youtube videos on the h-index.&nbsp;</strong>The study aimed to characterize educational videos about the h-index to understand available resources and provide recommendations for future educational initiatives.</p> <p><em>Data.csv</em>: contains the metadata and qualitative coding for 31&nbsp;videos.</p> <p><em>ReadMe.csv</em>: contains the codebook including a description of variables.</p> <p><strong>Abstract. </strong>The authors analyzed videos on the h-index posted to YouTube. Videos were identified by searching YouTube and were screened by two authors. To code the videos the authors created a coding sheet, which assessed content and presentation style with a focus on the videos&rsquo; educational quality based on Cognitive Load Theory. Two authors coded each video independently with discrepancies resolved by group consensus.&nbsp;Thirty-one videos met inclusion criteria. Twenty-one videos (68%) were screencasts and seven used a &ldquo;talking head&rdquo; approach. Twenty-six videos defined the h-index (83%) and provided examples of how to calculate and find it. The importance of the h-index in high-stakes decisions was raised in 14 (45%) videos. Sixteen videos (52%) described caveats about using the h-index, with potential disadvantages to early researchers the most prevalent (n=7; 23%). All videos incorporated various educational approaches with potential impact on viewer cognitive load.&nbsp;Most videos (n=21; 68%) displayed amateurish production quality.&nbsp;The videos featured content with potential to enhance viewers&rsquo; metrics literacies such that many defined the h-index and described its calculation, providing viewers with skills to recognize and interpret the metric. However, less than half described the h-index as an author quality indicator, which has been contested, and caveats about h-index use were inconsistently presented, suggesting room for improvement. While most videos integrated practices to facilitate balancing viewers&rsquo; cognitive load, few (32%) were of professional production quality. Some videos missed opportunities to adopt particular practices that could benefit learning.&nbsp;</p>