Table 2 Video analytics comparison
Study | Data, variables, context (What?) | Objectives (Why?) | Methods (How?) | Stakeholders (Who?) | Experiment | Tool lifecycle |
|---|---|---|---|---|---|---|
Identifying Learning Strategies Associated with Active use of Video Annotation Software [35] | CLAS and MSQL trace data, midterm scores, number of annotations, covariates derived from MSLQ and SPQ questionnaires | Monitoring, Analysis, Reflection: investigate the impact of video annotation software usage on learning and academic performance | Linear regression modelling (Statistics) | Researchers, Learners | N | S |
Analytics of the Effects of Video Useand Instruction to Support Reflective Learning [36] | CLAS trace data, assignment of participants to the two different experimental conditions, annotation counts, LIWC special variables for linguistic analysis | Monitoring, Analysis, Awareness and Reflection: usage of video annotation tools within graded and non-graded instructional approach | Non-parametric statistical hypothesis tests; LIWC 2007 software, SPSS analysis (Statistics) | Researchers, Learners | N | S |
Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course [32] | VLAS trace data, video navigation, survey results, students learning performance/score collected via system questionnaires | Monitoring and Analysis: understanding interactions with video lectures; investigate relationship between video analytics, attitudes and learning performance | Aggregated time series visualization; Charts examinations; T-Tests (Graphics) | Researchers | C | R |
How Video Production Affects Student Engagement: An Empirical Study of MOOC Videos [38] | edX trace data, interviews with edX staff, page navigation, video interactions, submitting a problem for grading | Recommendations: how video production decisions affect student engagement in online educational videos | Data mining (Statistics, Graphics) | Video Producers, Teachers | R | S |
The Who, What, When, and Why of Lecture Capture [33] | "Recollect" event monitor trace data, interactions of users with player, events collected from player’s “heartbeat” mechanism, student questionnaires | Monitoring, Analysis, Auditing and Interventions: create a low-level semantic logging framework within learning environment; analyse interaction and perception data to form groups based on learning preferences | K-means clustering (Statistics, Graphics) | Researchers | C | S |
Using a Video Annotation Tool for Authentic Learning: A Case Study [34] | Two-part survey, direct observation, semi structured/interactive interview | Reflection, Evaluation, Feedback: determine if integration of video annotation tool (MAT) into a learning environment is effective | Information visualization (Charts) | Teachers Learners | C | S |
CourseMapper | Traces collected from students interaction with media, annotations time frame and count | Feedback, Reflection, Monitoring, Awareness: highlight important and “hot” parts of a mediacontent via annotations and heatmaps | Information visualization (Heatmaps, Annotation map stack) | Learners, Teachers | N, C | R |