ViSeq: Visual Analytics of Learning Sequence in Massive Open Online Courses

ConceptThread: Visualizing Threaded Concepts in MOOC Videos

Massive Open Online Courses (MOOCs) platforms are becoming increasingly popular in recent years. Online learners need to watch the whole course video on MOOC platforms to learn the underlying new knowledge, which is often tedious and time-consuming due to the lack of a quick overview of the covered knowledge and their structures. In this article, we propose ConceptThread, a visual analytics approach to effectively show the concepts and the relations among them to facilitate effective online learning. Specifically, given that the majority of MOOC videos contain slides, we first leverage video processing and speech analysis techniques, including shot recognition, speech recognition and topic modeling, to extract core knowledge concepts and construct the hierarchical and temporal relations among them. Then, by using a metaphor of thread, we present a novel visualization to intuitively display the concepts based on video sequential flow, and enable learners to perform interactive visual exploration of concepts. We conducted a quantitative study, two case studies, and a user study to extensively evaluate ConceptThread. The results demonstrate the effectiveness and usability of ConceptThread in providing online learners with a quick understanding of the knowledge content of MOOC videos.

HisVA: A Visual Analytics System for Studying History

Studying history involves many difficult tasks. Examples include searching for proper data in a large event space, understanding stories of historical events by time and space, and finding relationships among events that may not be apparent. Instructors who extensively use well-organized and well-argued materials (e.g., textbooks and online resources) can lead students to a narrow perspective in understanding history and prevent spontaneous investigation of historical events, with the students asking their own questions. In this article, we proposed HisVA, a visual analytics system that allows the efficient exploration of historical events from Wikipedia using three views: event, map, and resource. HisVA provides an effective event exploration space, where users can investigate relationships among historical events by reviewing and linking them in terms of space and time. To evaluate our system, we present two usage scenarios, a user study with a qualitative analysis of user exploration strategies, and in-class deployment results.

Survey on Visual Analysis of Event Sequence Data

Event sequence data record series of discrete events in the time order of occurrence. They are commonly observed in a variety of applications ranging from electronic health records to network logs, with the characteristics of large-scale, high-dimensional and heterogeneous. This high complexity of event sequence data makes it difficult for analysts to manually explore and find patterns, resulting in ever-increasing needs for computational and perceptual aids from visual analytics techniques to extract and communicate insights from event sequence datasets. In this paper, we review the state-of-the-art visual analytics approaches, characterize them with our proposed design space, and categorize them based on analytical tasks and applications. From our review of relevant literature, we have also identified several remaining research challenges and future research opportunities.

Passing the Data Baton : A Retrospective Analysis on Data Science Work and Workers

Data science is a rapidly growing discipline and organizations increasingly depend on data science work. Yet the ambiguity around data science, what it is, and who data scientists are can make it difficult for visualization researchers to identify impactful research trajectories. We have conducted a retrospective analysis of data science work and workers as described within the data visualization, human computer interaction, and data science literature. From this analysis we synthesis a comprehensive model that describes data science work and breakdown to data scientists into nine distinct roles. We summarise and reflect on the role that visualization has throughout data science work and the varied needs of data scientists themselves for tooling support. Our findings are intended to arm visualization researchers with a more concrete framing of data science with the hope that it will help them surface innovative opportunities for impacting data science work. Data availability: https://osf.io/z2xpd/?view_only=87fa24be486a473884adb9ffbe8db4ec.

Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC

Malaysia and many other developing countries progressively adopting massively open online course (MOOC) in their national higher education approach. We have observed an increasing need for facilitating MOOC monitoring that is associated with the rising adoption of MOOCs. Our observation suggests that recent adoption cases led analyst and instructors to focus on monitoring enrolment and learning activities. Visual analytics in MOOC support education analysts in analyzing MOOC data via interactive visualization. Existing literature on MOOC visualization focuses on enabling visual analysis on MOOC data from forum and course material. We found limited studies that investigate and characterize domain problems or design requirements of visual analytics for MOOC. This paper aims to present the empirical problem characterization and abstraction for visual analytics in MOOC learner's support monitoring. Detailed characterization and abstraction of the domain problem help visualization designer to derive design requirements in generating appropriate visualization solution. We examined the literature and conducted a case study to elicit a problem abstraction based on data, users, and tasks. We interviewed five Malaysian MOOC experts from three higher education institutes using semi-structured questions. Our case study reveals the priority of enabling MOOC analysis on learner's progression and course completion. There is an association between design and analysis priority with the pedagogical type of implemented MOOC and users. The characterized domain problems and requirements offer a design foundation for visual analytics in MOOC monitoring analysis.