Abstract. Enabling teachers to define or portray efficient teaching ideas for sharing, reuse or adaptation has attracted the interest of Learning Design researchers and has led to the development of a variety of learning design tools. In this paper, we introduce a multi-dimensional framework for the analysis of learning design tools and use it to review twenty-nine tools currently available to researchers and practitioners. Lastly, we categorise these tools according to the main functionality that they offer.

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Learning analytics is an emerging field focusing on tracing, collecting, and analysing data through learners' interactions with educational content. The standardisation of the data collected to supporting interoperability and reuse is one of the key open issues in this field. One of the most promising routes to data standardisation is through the xAPI: a framework for developing standard 'statements' as representations of learning activity. This paper presents work conducted within the context of the Institute of Coding. 1 Additionally, we have developed a system called ADA for automating the learning analytics data processing life cycle. To our knowledge, ADA is the only system aiming to automate the turning data into xAPI statements for standardisation, sending data to and extracting data from a learning record store or mongoDB, and providing learning analytics. The Open University Learning Analytics Dataset is used in the test case. The test case study has led to the extension of the xAPI with five new methods: 1) persona attributes, 2) register, 3) unregister, 4) submit, and 5) a number of views information.

Extensive research has been carried out for the development of learning design tools; nevertheless, their adoption by HE lecturers remains low. Sharing, guidance, and various forms of representation are the main pillars of learning design tools. However, these features do not seem to be sufficient reasons to convince lecturers to adopt these tools in daily learning design practices in HE. This is attached to the gap between learning design tools and actual learning design practice of university lecturers. Sociomateriality provides an analytical lens for unpacking complex practices for identifying the design space of digital tools for learning design without predetermined boundaries. This paper is a first step in exploring how we can follow sociomaterialty in unpacking complex learning design practices in HE to inform the development of software for learning design. It conducts a survey with one hundred ten university lecturers on their learning design practices. It analyses data through sociomaterial theory and derives a sociomaterial evaluation framework. This is used as an instrument for the analysis of seven available learning design tools. A misalignment between tools and HE lecturers' learning design practice is revealed. Points of misalignment extend the space for what it means to design digital tools that support-learning design practices in HE, and they could be used to highlight areas for improvement to inform and strengthen further the way we design support tools for learning design.