Recipe for success

Bakharia, Aneesha; Kitto, Kirsty; Pardo, Abelardo; Gašević, Dragan; Dawson, Shane

doi:10.1145/2883851.2883882

Cited by 45 publications

(21 citation statements)

References 6 publications

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“…It makes use of the Experience API (xAPI) to unify the description of data gathered from various media, and a Connected Learning Recipe (or xAPI Profile) to unify the syntax and semantics of data gathered from these disparate media (Bakharia, Kitto, Pardo, Gašević, & Dawson, 2016). At present, data harvesting has been implemented for Twitter, Facebook, WordPress and YouTube comments, Trello, and Github.…”

Section: Case Study: Using the Connected Learning Analytics (Cla) Toomentioning

confidence: 99%

Designing for student-facing learning analytics

Kitto

Lupton

Davis

et al. 2017

AJET

Self Cite

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Despite a narrative that sees learning analytics (LA) as a field that aims to enhance student learning, few student-facing solutions have emerged. This can make it difficult for educators to imagine how data can be used in the classroom, and in turn diminishes the promise of LA as an enabler for encouraging important skills such as sense-making, metacognition, and reflection. We propose two learning design patterns that will help educators to incorporate LA into their teaching protocols: do-analyse-change-reflect, and active learning squared. We discuss these patterns with reference to a case study utilising the Connected Learning Analytics (CLA) toolkit, in three trials run over a period of 18 months. The results demonstrate that student-facing learning analytics is not just a future possibility, but an area that is ripe for further development.

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Section: Case Study: Using the Connected Learning Analytics (Cla) Toomentioning

confidence: 99%

Designing for student-facing learning analytics

Kitto

Lupton

Davis

et al. 2017

AJET

Self Cite

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“…One of the advantages of xAPI, i.e. its openness when it comes to designing the xAPI statements, is also one of its disadvantages [12]. This holds especially true when trying to combine data collected in different platforms.…”

Section: Xapimentioning

confidence: 99%

Dutch Cooking with xAPI Recipes: The Good, the Bad, and the Consistent

Berg

Scheffel

Drachsler

et al. 2016

2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)

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Abstract-This short paper presents the experiences of several Dutch projects in their application of the xAPI standard and different design patterns including the deployment of Learning Record Stores. In this paper we share insights and argue for the formation of an international Special Interest Group on interoperability issues to contribute to the Open Analytics Framework as envisioned by SoLAR and enacted by the Apereo Learning Analytics Initiative. Therefore, we provide an overview of the advantages and disadvantages of implementing the current xAPI standard by presenting projects that applied xAPI in very different ways followed by the lessons learned.

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“…They focus on a set of indicators to understand and assess how the team collaborated. Another very interesting proposal is the Connected Learning Analytics (CLA) toolkit (Bakharia, Kitto, Pardo, Gašević, & Dawson, 2016). A distinguishing characteristic of the CLA toolkit is that it collects data from social media applications (e.g., Facebook and Twitter) to analyze student behaviour and student relationships.…”

Section: Introductionmentioning

confidence: 99%

“…According to xAPI, each learning event is defined by a quadruple: a subject, a verb, an object, and a context, while an ontology should be implemented to define the different elements of the quadruple. As an example, Bakharia et al (2016) Table 1 as an example to represent this group of LRSs). These proposals support the collection and storage of xAPI data.…”

Section: Introductionmentioning

confidence: 99%

An Infrastructure for Workplace Learning Analytics: Tracing Knowledge Creation with the Social Semantic Server

et al. 2019

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In this paper, we propose the Social Semantic Server (SSS) as a service-based infrastructure for workplace and professional learning analytics (LA). The design and development of the SSS have evolved over eight years, starting with an analysis of workplace learning inspired by knowledge creation theories and their application in different contexts. The SSS collects data from workplace learning tools, integrates it into a common data model based on a semantically enriched artifact-actor network, and offers it back for LA applications to exploit the data. Further, the SSS design's flexibility enables it to be adapted to different workplace learning situations. This paper contributes by systematically deriving requirements for the SSS according to knowledge creation theories, and by offering support across a number of different learning tools and LA applications integrated into the SSS. We also show evidence for the usefulness of the SSS extracted from 4 authentic workplace learning situations involving 57 participants. The evaluation results indicate that the SSS satisfactorily supports decision making in diverse workplace learning situations and allow us to reflect on the importance of knowledge creation theories for this analysis. Notes for Practice• We propose the Social Semantic Server (SSS) as a service-based infrastructure for workplace and professional learning analytics (LA) that focuses on knowledge creation theories.• We identify the requirements for the SSS and present its design and development.• We evaluated the SSS by integrating a set of learning tools and LA applications into the SSS and using it in 4 authentic workplace learning situations involving 57 participants.

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Recipe for success

Cited by 45 publications

References 6 publications

Designing for student-facing learning analytics

Designing for student-facing learning analytics

Dutch Cooking with xAPI Recipes: The Good, the Bad, and the Consistent

An Infrastructure for Workplace Learning Analytics: Tracing Knowledge Creation with the Social Semantic Server

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