xAPI와 Caliper의 데이터 수집 요소와 상호운용성 분석

Abstract

With the release of the 2022 revised curriculum and the introduction of artificial intelligence digital textbooks, collecting and analyzing learning activity data is crucial. We studied two of the most popular data collection standards, xAPI and Caliper Analytics. First, we provided an overview of xAPI and Caliper Analytics and compared each data collection standard in terms of purpose, data collection methods, and key features. Then, we analyzed the data collection elements of xAPI and Caliper Analytics by dividing them into Profile, Actor, Action(Verbs), Object, and Context. Based on the analysis, we discussed how to secure interoperability between the two data standards. In order to secure interoperability, it is reasonable to analyze Actor, Actions(Verbs), and Objects, and first, it is reasonable to collect data for Actors with basic names and distinctions. As for the words corresponding to Actions (Verbs) and Objects, if the focus is on learning analytics, it makes sense to align the xAPI words with Caliper Analytics' vocabulary. This is because Caliper Analytics is focused on learning analytics in an educational setting, but also because adding vocabulary to xAPI is relatively straightforward compared to Caliper Analytics. Data collection standards are becoming increasingly important, and we hope that this study will increase interest in and understanding of learning activity data collection standards.