Looking for options for that next learning analytics piece? Consider the 54th iteration of the Hawaii International Conference on System Sciences (HICSS) and the learning analytics minitrack.
First, the important information. HICSS will be an on-site (non-virtual) conference. The planners have committed to this mode of delivery after surveying the HICSS community (see the front page of the website).
Second, the due date for papers is July 15th. See the author instructions for all important details. Some minitracks have expedited publication opportunities.
Now, the minitrack. As you’ll read below, the minitrack is fairly broad and inclusive regarding the topics and approaches the co-chairs are interested in. They seem equally encouraging of ethics and policy, pedagogy, and technological design topics. Amy VanScoy are working on a paper based on our national survey of 500 instructors regarding their views on learning analytics and privacy. You can read more about our project here.
Here’s the text verbatim from the website:
The mini-track is interested in papers that take on analyzing teaching and learning behaviors through learning managements systems (or learning platforms) through data-driven approaches. The interest extends to papers that shed light on the type of data that is required in order to improve teaching and learning in different levels of education and how data can be used to better understand, and improve, the educational environment. The interest thereby extends to papers discussing different approaches in data analytics (for instance by opening up the box of how machine learning techniques to discover relevant factors that can be used to improve teaching and learning and discussing the outcome) as well as to papers discussing qualitative research on teaching and learning, where data is used to support these processes. The interest is therefore not merely in big data and grand projects but also extends to the use of small data, that can support teaching or learning. The papers can take the point of departure from the teacher side, or from a student perspective, or even be written from the intersection between the teachers’ and the students’ practices. In addition to that, the papers can take on challenges and benefits for management, operations, practice or research.
We welcome papers that reflect on, and relate to, learning analytics and datafication in educational settings alongside papers that reflect on changes in learning platforms, teaching practices, learning practices, student profiling, use of third-party applications (for instance for lecture capture) to support education, and everything from small apps to large systems and infrastructures in educational contexts that generate data that can be analyzed and used to impact educational outcomes. We also welcome a dialog on continuous education and learning through work and the impact of technologies on workplace learning or continuous education strategies. We encourage papers based on both qualitative and quantitative methods, and on machine learning approaches, as well as empirical, methodological and theoretical papers that inspire a dialog with the growing literature on learning analytics and datafication of educational settings. The interest extends to all educational levels where the partnership between students and teachers is important, in addition to papers reporting on continuous education and workplace learning. In addition to that, we welcome all contributions that address the challenges and benefits for management, operations and for research and encourage a wide debate on learning analytics, technology advancements and datafication in general.