Observing the Use of e-Textbooks in the Classroom: Towards “Offline” Learning Analytics

Eradze, Maka; Väljataga, Terje; Laanpere, Mart

doi:10.1007/978-3-319-13296-9_28

Cited by 5 publications

(10 citation statements)

References 8 publications

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“…These stages are not strictly separated and the research methodology suggests iteratively alternating between stages. Three stages were covered in the previous works: contextual inquiry, participatory design, and product design [12,[38][39][40][41]. This phase partly goes back to contextual inquiry and product design while also presenting the software prototype as a hypothesis.…”

Section: Research Methodology and Research Questionsmentioning

confidence: 99%

Contextualising Learning Analytics with Classroom Observations: A Case study

Eradze¹,

Rodríguez‐Triana²,

Milikic³

et al. 2020

IxD&A

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Educational processes take place in physical and digital places. To analyse educational processes, Learning Analytics (LA) enable data collection from the digital learning context. At the same time, to gain more insights, the LA data can be complemented with the data coming from physical spaces enabling Multimodal Learning Analytics (MMLA). To interpret this data, theoretical grounding or contextual information is needed. Learning designs (LDs) can be used for contextualisation, however, in authentic scenarios the availability of machine-readable LD is scarce. We argue that Classroom Observations (COs), traditionally used to understand educational processes taking place in physical space, can provide the missing context and complement the data from the co-located classrooms. This paper reports on a co-design case study from an authentic scenario that used CO to make sense of the digital traces. In this paper we posit that the development of MMLA approaches can benefit from co-design methodologies; through the involvement of the end-users (project managers) in the loop, we illustrate how these data sources can be systematically integrated and analysed to better understand the use of digital resources. Results indicate that CO can drive sense-making of LA data where predefined LD is not available. Furthermore, CO can support layered contextualisation depending on research design, rigour and systematic documentation/data collection efforts.Also, co-designing the MMLA solution with the end-users proved to be a useful approach.

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Section: Research Methodology and Research Questionsmentioning

confidence: 99%

Contextualising Learning Analytics with Classroom Observations: A Case study

Eradze¹,

Rodríguez‐Triana²,

Milikic³

et al. 2020

IxD&A

Self Cite

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show abstract

“…In all cases, external human observers were in charge of the data collection and coding-twice in combination with automated LA solutions (in this case, a proposal to involve LA solutions) [45,46]-with both teachers and students as the common data objects (22 papers). Although the definition of the unit of analysis is an important methodological decision in observational studies or research in general [35,[67][68][69] we only found an explicit reference to it in one paper [66]. Nevertheless, looking at the description of the research methodology, we can infer that most of the studies focused on events (directed at interaction and behavioural analysis) (14) and activities (10).…”

Section: Rq1-what Is the Nature Of The Observations?mentioning

confidence: 99%

A Conversation between Learning Design and Classroom Observations: A Systematic Literature Review

2019

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Learning Design, as a field of research, provides practitioners with guidelines towards more effective teaching and learning. In parallel, observational methods (manual or automated) have been used in the classroom to reflect on and refine teaching and learning, often in combination with other data sources (such as surveys and interviews). Despite the fact that both Learning Design and classroom observation aim to support teaching and learning practices (respectively a priori or a posteriori), they are not often aligned. To better understand the potential synergies between these two strategies, this paper reports on a systematic literature review based on 24 works that connect learning design and classroom observations. The review analyses the purposes of the studies, the stakeholders involved, the methodological aspects of the studies, and how design and observations are connected. This review reveals the need for computer-interpretable documented designs; the lack of reported systematic approaches and technological support to connect the (multimodal) observations with the corresponding learning designs; and, the predominance of human-mediated observations of the physical space, whose applicability and scalability are limited by the human resources available. The adoption of ICT tools to support the design process would contribute to extracting the context of the observations and the pedagogical framework for the analysis. Moreover, extending the traditional manual observations with Multimodal Learning Analytic techniques, would not only reduce the observation burden but also support the systematic data collection, integration, and analysis, especially in semi-structured and structured studies.

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“…Educational practice, research and development require contextualised data and pedagogically grounded analysis to understand teaching and learning processes [1][2] [9]. Indeed, a core challenge for the learning analytics community is to determine conceptual and practical frameworks that can link teachers' intentions with the data retrieved while teaching and learning [1]. Such contextualization may be driven by the learning design, since it reflects the pedagogical intentions in a particular learning context [2] [11] [12].…”

Section: Background and Related Workmentioning

confidence: 99%

“…It has been argued that Learning Analytics (LA) is lacking in understanding the pedagogical context of student activities [1][2] [3]. To address this need, articulated learning design can contribute to the interpretation of LA data, creating an actionable feedback loop [4].…”

Section: Introductionmentioning

confidence: 99%

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Semantically Annotated Lesson observation Data in Learning Analytics Datasets: a Reference Model

Eradze¹,

Rodríguez‐Triana²,

Laanpere³

2017

IxD&A

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Learning analytics (LA) and lesson observations are two approaches frequently used to study teaching and learning processes. In both cases, in order to extract meaningful data interpretations, there is a need for contextualization. Previous works propose to enrich LA datasets with observation data and to use the learning design as a framework to guide the data gathering and the later analysis. However, the majority of lesson observation tools collect data that is not compliant with LA datasets. Moreover, the connection between the learning design and the data gathered is not straightforward. This study reflects upon our research-based design towards an LA model for context-aware semantically annotated lesson observations that may be integrated in multimodal LA datasets. Six teachers (out of which 2 were also researchers) with previous experience in lesson observation were engaged in a focus group interview and participatory design session that helped us to evaluate the LA model through the conceptual design of Observata (a lesson observation tool that implements our model). The findings show the feasibility and usefulness of the proposal as well as the potential limitations in terms of adoption.

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Observing the Use of e-Textbooks in the Classroom: Towards “Offline” Learning Analytics

Cited by 5 publications

References 8 publications

Contextualising Learning Analytics with Classroom Observations: A Case study

Contextualising Learning Analytics with Classroom Observations: A Case study

A Conversation between Learning Design and Classroom Observations: A Systematic Literature Review

Semantically Annotated Lesson observation Data in Learning Analytics Datasets: a Reference Model

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