Benjamin E. Erlandson

Challenges for Education in a Connected World: Digital Learning, Data Rich Environments, and Computer-Based Assessment—Introduction to the Inaugural Special Issue of Technology, Knowledge and Learning

The new scope of Technology, Knowledge and Learning emphasizes the increased interest on adaptive and personalized digital learning environments. Educational researchers are faced with new research challenges in the beginning of the twenty-first century, especially focusing on digital learning, game-based learning, automated assessment, and learning analytics. In order to provide a source of reference for future submissions to Technology, Knowledge and Learning, the following sections highlight the key themes of the journal.

Learning with Data: Visualization to Support Teaching, Learning, and Assessment

Within the established paradigm of learning analytics, this special issue has a specific focus upon factors of learning associated with interactive data visualizations. Learning analytics use dynamic information about learners and learning environments, assessing, eliciting and analysing it, for real-time modelling, prediction, and optimization of learning processes, learning environments, and educational decision-making (Ifenthaler 2015). Opportunities of learning analytics are fostering interactions between students and facilitators as well as the availability of personalised and adaptive help and feedback from peer learners in near real-time (Ifenthaler and Widanapathirana 2014). The advent of big data requires new perspectives on data processing and analysis including advanced methods and tools to visualise data for supporting learning processes. The primary purpose of visualisations of big data is to communicate complex patterns nested in big data (Chen 2010). However, not only the visualisation of numeric information using dashboards are important areas of research. The visualisation of semantic content are an emerging field of research opening up new perspectives on natural language processing and in-depth analysis of text data (Ifenthaler 2014; Ifenthaler and Pirnay-Dummer 2014). This special issue of Technology, Knowledge and Learning features articles which showcase the latest advances in the field of data visualisation for learning.

Improving Learners’ Ability to Recognize Emergence with Embedded Assessment in a Virtual Watershed

Measures of participants’ water cycle knowledge and ability to recognize emergence were taken at various points throughout a 2-h experience with the Cloverdale virtual watershed socioecological simulation. Multilevel growth models were estimated for analysis of hypothesized predictive relationships between measured variables. Significant growth was found for ability to recognize emergence in participants that completed the Cloverdale virtual scenario. Preliminary water cycle knowledge was found to predict initial ability to recognize emergence. Application of results to unobtrusive assessment of learning in virtual worlds is discussed.