This paper identifies some of the main challenges of data governance modelling in the context of learning analytics for higher education institutions, and discusses the critical factors for designing data governance models for learning analytics. It identifies three fundamental common challenges that cut across any learning analytics data governance model, viz., the ownership of the learning analytics data sets, the interpretation of the data, and the decision making based on the data. It also proposes a set of high-level requirements necessary for modelling data governance for learning analytics.

This paper explores the cognitive presence of the learners in MOOCs through using a (computational) linguistic analysis of the learners' Point-of-View as an indicator for cognitive presence. The linguistic analysis of the written language as a medium of interaction by the students in the context of MOOCs shows hallmarks of cognitive disengagement and low cognitive presence by the learners.

This paper advances a formal approach about how to encode cognitive relevance into the design of interfaces of multimodal systems, with a focus on the automatic multimedia generation systems. We make a proposal that the optimality of the encoding of cognitive relevance depends on a proper formalization of the processes of modality allocation and modality combination. We describe how this can be done by adopting and encoding the Principle of Relevance based modality combination which evolved out of our formal analysis of modality allocations and modality combinations.

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To develop expertise, novice chemistry students require deliberate practice with immediate and thoughtful feedback. Whereas opportunities for practice are often abundant, opportunities for feedback tend to be much scarcer. To address this challenge, we collaborated with students to develop a flexible and scalable online platform called “Alchemy.” Students interact with the software through a series of prompts and multiple-choice questions, receiving targeted feedback at each step. Each student can navigate a scenario differently, influenced by their prior knowledge and misconceptions. In design, scenarios are instructor-created graphs that model their expert-level thought process­(es) and teaching experience. This graph format is a distinct and advantageous feature of Alchemy that supports linear, nonlinear, and cyclical progression through a concept or problem. Alchemy-based homework has been assigned in lecture and lab courses, at the sophomore and junior levels, with enrollments ranging from many tens to many hundreds of students. Approximately 80% of students rated Alchemy as very/extremely helpful to their learning, emphasizing the value of the step-by-step process and feedback. Alchemy is discussed in the contexts of other software platforms, its advantages and limitations, lessons learned in its initial deployments, and future directions for its development and usage.

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