Temporal Aspects of Learning Analytics - Grounding Analyses in Concepts of Time

Abstract

This chapter represents an effort to lay out a common framework for the concepts of time to (a) support diverse researchers working on temporal aspects of learning analytics to communicate better, (b) facilitate an understanding of how different approaches to studying time in learning articulate and (c) map out the space of temporal analysis to reduce redundancy of efforts. We distinguish two concepts of time, namely the passage of time and order in time. Passage of time considers time as a continuous flow of events and order in time focuses on the organization among events. Within the passage of time we distinguish four metrics: position, duration, frequency and rate. Within order in time we discriminate between consistency, recurrent and non-recurrent change and irregular change. Metrics extracted to index passage of time can be used in many different statistical methods, whereas analysis of order in time commonly requires the usage of advanced analysis methods. For either, decisions about the level of granularity at which time is considered and segmentation of time into "windows" have important effects on analysis results. We argue that understanding the value of temporal concepts and implications for the related analysis, is foundational for closing the loop and advancing learning analytics design with temporal insights. The primary goal of learning analytics is to understand and optimize learning, a process that occurs over time; thus a consideration of temporality is relevant to the vast majority of research in the field. The "measurement, collection , analysis and reporting of data about learners and their contexts" [15] inherently requires conceptualising time and the underlying assumptions about its relation to learning. The importance of time in analyses of learning is emphasised by Reimann [40] in his seminal work "Time is Precious" and a number of researchers since [20, 23, 31, 33]. Despite its central importance to learning, rarely is a conceptualisation of time or its underlying assumptions treated explicitly by researchers. A notable exception is the two-part special section dedicated to temporal analyses of learning data in the Journal of Learning Analytics [7, 25]. Here two dramatically different conceptualizations of temporality are sketched out. The first relates to the passage of time addressing questions about how often or for how long particular activities take place during learning. The second relates to temporal order investigating how activities during learning are organized in relation to each other. In this chapter, we elaborate on these two con-ceptualizations, relate them to common temporal metrics used in learning analytics research, and propose a framework for thinking about time that can be instrumental in learning analytics research. We additionally outline how this framework supports closing the loop in designing interventions and learning environments that translate temporal insights into pedagogical action and new learning designs.